Pollution Prevention (P2)
Assessment
Framework
U.S. Environmental Protection Agency
Office of Pollution Prevention and Toxics
November 1998
Draft
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Disclaimer
This document is a preliminary draft. It has not been formally released by
the Environmental Protection Agency and should not at this stage be
construed to represent Agency policy. Mention of trade names or
commercial products does not constitute endorsement or
recommendation for use.
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Introduction
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Contents
The Pollution Prevention (P2) Chemical Screening Assessment Framework
Executive Summary 3
What Is Pollution Prevention? 4
Pollution Prevention in the Industrial and Commercial Chemicals Sector:
Risk Information Improves Decision Making 5
The Risk Assessment Process 7
How Do These Methods Help the Risk Assessor? 8
These Methods Use Chemical Structure to Provide Information in
Four Areas 9
What is Required to Use the Framework Models? 10
Inputs and Outputs of the Framework Models 11
About This Document 12
Models Presented 13
EPIWIN© and SMILES© 15
SMILES© Notations 16
Models to Estimate Physical/Chemical Properties of Chemicals 17
MPBPVP© - Melting Point, Boiling Point, Vapor Pressure 19
KOWWIN© - Octanol-Water Partition Coefficient (KO W*) 23
WSKOWIN© - Water Solubility 27
PCKOCWIN© - Organic Carbon Adsorption Coefficient (KOC) 31
HENRYWIN© - Henry's Law Constant 35
BCFWIN© - Bioconcentration Factor 39
Models to Estimate Chemical Fate in the Environment 41
AOPWIN©- Atmospheric Oxidation Potential 43
BIOWIN©- Biodegradation 47
HYDROWIN©- Hydrolysis 51
STP - Percent Removal in Wastewater Treatment 55
Models to Estimate Hazard to Humans and the Environment 59
OncoLogic®- Potential Carcinogenicity 61
ECOSAR - Ecotoxicity in Surface Water 75
"Definitions of terms in italics are provided in the Glossary.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Contents (continued)
Models to Estimate Exposure and/or Risk 79
Screening Exposure Assessment Software (SEAS) to Evaluate Stream
Concentrations and Human PDRs Resulting from Discharges to
Surface Water 81
ReachScan - Impact of Surface Water Discharges to Drinking Water 89
PDM3 - CC Exceedences by Discharges to Surface Water 95
SCIES - Consumer Inhalatipn Exposure 99
Dermal - Consumer Dermal Exposure 103
Occupational Exposure Spreadsheets to Estimate Worker Exposure
from Transfer and Open Surface Operations, Textile Dyeing, and
Degreasing Operations 107
Computer Requirements 115
Glossary of Useful Terms 117
Appendix A - Case Studies A-1
Case Study A - Potential Aquatic and Human Exposures to
Surface Water Discharges from a Manufacturing Facility: Uses
the Models ECOSAR, SEAS, PDM3 A-3
Case Study B - Potential Exposures to Surface Water Discharges
from a Manufacturing Facility: Uses the Models KOCWIN, BIOWIN,
KOWWIN, STP, and ReachScan A-15
Case Study C - Consumer Dermal Exposure: Uses the
Dermal Model A-33
Case Study D - Worker Exposure: Uses the Occupational Exposure
Spreadsheets to Estimate Worker Exposure from Transfer and Open
Surface Operations, Textile Dyeing, and Degreasing Operations A-41
Appendix B - Data Sources B-1
Physical/Chemical Property Data B-3
Chemical Human Hazard Data B-4
Chemical Environmental Hazard Data B-5
Release Data B-6
Exposure and Population Data B-7
Appendix C - Summary of Writing SMILES Notations C-1
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Pollution Prevention (P2) Chemical Screening Assessment Framework
The Pollution Prevention (P2) Chemical Screening
Assessment Framework
Developed by:
The Office of Pollution Prevention and Toxics
U.S. Environmental Protection Agency
Executive Summary
Of the approximately 80,000 chemicals used in commerce in the United States,
few have been tested, and only a fraction have sufficient information to allow a
thorough evaluation of risk. Businesses, governmental organizations, and other
stakeholders often don't have the data necessary to identify problem chemicals or
identify safer substitutes or other options that are less risky, prevent pollution, and
may save companies environmental management costs. At times, companies
must make product and process decisions without enough data regarding the risk
tradeoffs.
The Office of Pollution Prevention and Toxics (OPPT) has developed computer-
based methods that derive important risk assessment information based on
chemical structure and other factors. These methods provide information on
carcinogenicity, toxicity to aquatic organisms, worker and general population
exposures, bioconcentration and environmental fate, among other data. OPPT
routinely uses these methods to highlight chemicals of concern, to identify safer
substitutes, and to reduce or eliminate risks.
The Pollution Prevention (P2) Chemical Screening Assessment Framework ("P2
Framework" or "Framework") is a document that contains many of OPPTs most
important computer-based methods for assessing risk. The P2 Framework
provides important risk-related tools not previously available. Its purpose is to
provide information that can inform decision making and help promote the design,
development, and application of safer chemicals and processes. The document
describes each assessment methodology and the importance of the data
generated, and provides case studies showing how methods can be used
collectively to answer complicated risk assessment questions and identify
pollution prevention opportunities. The P2 Framework, as currently constructed,
does not address all biological endpoints. It is a screening-level methodology that
is of most value when chemical-specific data are lacking.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
What Is Pollution Prevention?
Pollution prevention embodies the common sense understanding that it is
easier to prevent problems than to fix them. Congress, by enacting the
Pollution Prevention Act of 1990, created a bold national objective for
environmental protection by outlining a hierarchy in dealing with pollution:
•/ Pollution should be prevented or reduced at the source whenever feasible;
•/ Pollution that cannot be prevented should be recycled in an
environmentally safe manner whenever feasible;
•/ Pollution that cannot be prevented or recycled should be treated in
an environmentally safe manner whenever feasible; and.
•/ Disposal or other releases into the environment should be employed only
as a last resort and should be conducted in an environmentally safe
manner.
Pollution prevention means "source reduction," as defined under the Pollution
Prevention Act. The Pollution Prevention Act defines "source reduction" to
mean any practice which:
S Reduces the amount of any hazardous substance, pollutant, or
contaminant entering any waste stream or otherwise released into the
environment prior to recycling, treatment, or disposal; and
S Reduces the hazards to public health and the environment associated with
the release of such substances, pollutants, or contaminants.
Source reduction can be achieved through equipment or technology
modifications, processes or procedure modification, reformulation or redesign
of products, substitution of materials, etc.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Pollution Prevention in the
Industrial and Commercial Chemicals Sector:
Risk Information Improves Decision Making
Approximately 80,000 different chemicals are available in commerce in the
United States. An additional 2,000 new chemicals per year are evaluated by
EPA. Relatively few have been tested, and only a fraction have sufficient
information to allow a thorough evaluation of risk. Businesses, governmental
organization and other stakeholders may not have the data necessary to
identify problem chemicals or identify substitutes or options that are less risky,
prevent pollution, and may be less costly in terms of environmental
management. At times, some companies must make product and process
decisions without data regarding the risk tradeoffs.
To identify and take advantage of pollution prevention opportunities,
stakeholders need access to risk-related information. Companies often decide
which chemicals or processes to use primarily on the basis of cost and product
performance, among other criteria. If companies had access to risk-related
information about chemicals, they could improve decision making and take
advantage of pollution prevention opportunities.
A generalized example might help illustrate how risk-related information can
drive pollution prevention outcomes. Company A plans to formulate a
concentrated, heavy duty industrial cleaner, and needs to incorporate a
solvent within the product to meet the customers performance criteria. Twelve
solvents are identified that will meet the criteria, all of which have the same
cost and product performance characteristics. The company knows the
chemical is likely to be discharged to water, and is concerned about toxicity to
aquatic life. The company decides to test each of the 12 solvents for three
parameters: 1) persistence in the environment, 2) bioconcentration, and 3) fish
acute toxicity; results are summarized as follows:
Seven of the 12 solvents showed: Five of the 12 solvents showed:
/ very low bioconcentration potential S high bioconcentration potential
/ rapid degradation S persistence in the environment for
/ low aquatic toxicity several months
/moderate to high fish acute toxicity
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Pollution Prevention in the
Industrial and Commercial Chemicals Sector:
Risk Information Improves Decision Making (continued)
Testing indicates that 5 of the 12 solvents raise significant pollution and
toxicity concerns. As a result, the company chose one of the seven solvents
with low bioconcentration potential, a high degradation rate, and low aquatic
toxicity. In this example, price and product performance characteristics of
potential solvents were equivalent, and it was risk-related information that led
to a clear pollution prevention outcome.
The Pollution Prevention (P2) Chemical Screening
Assessment Framework
EPA's Office of Pollution Prevention and Toxics (OPPT) has developed
computer-based methods that derive important risk assessment information,
such as the information discussed in the above example. OPPT routinely
uses these methods to highlight chemicals of concern, evaluate the relative
safety of substitute chemicals, and identify opportunities for reducing or
eliminating risk. The P2 Framework is a compilation of some of OPPPs most
important methods for assessing risk when chemical specific data are lacking.
It describes each assessment methodology and the importance of the data
generated for decision making. The Framework includes case studies
showing how methods can be used collectively to answer complicated risk
assessment questions and identify P2 opportunities.
The P2 Framework provides important risk assessment information not
previously available. The purpose of the P2 Framework is to help identify
pollution prevention opportunities by providing information that can inform
decision making and help promote the design, development and application of
safer chemicals and processes.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
The Risk Assessment Process
The National Academy of Sciences has described risk characterization as
consisting of four related components:
/ Hazard Identification: The effects of a chemical on health of
humans or other organisms (for example, increased cancer
cases or birth defects);
/ Dose-Response Assessment: The relationship between the
amount of exposure to a substance and the extent of injury
or disease;
•/ Exposure Assessment: The magnitude, frequency and
duration of exposure to a chemical (for example, exposures
from proposed or actual manufacture, use, or disposal of a
chemical); and
•/ Risk Characterization: The probability of harm to an
exposed individual or population.
The components of the risk assessment process are illustrated in the
following figure:
The Risk Assessment Paradigm
Hazard
Identification
Dose-Response
Assessment
Exposure
Assessment
Risk
Characterization
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Pollution Prevention (P2) Chemical Screening Assessment Framework
How Do These Methods Help
the Risk Assessor?
P2 Framework Methods Help Assess Risk of a Chemical
Most methods presented in OPPPs P2 Assessment Framework deal with two
steps of the risk assessment process: hazard identification and exposure
assessment. Ideally, information on the potential hazards posed by a chemical
as well as exposure information will be available, but often this is not the case.
Methods included in the P2 Framework are intended to provide information to
help in assessing risk posed by a chemical or group of chemicals.
What to Do When There Are No Data
The methods are intended to be used when data are unavailable or to
supplement available data. These methods are generally computer models
that assess a particular aspect of a chemical's possible impact on humans or
the environment. For example, one model estimates toxicity to fish, aquatic
invertebrates, and algae. This is important information if the chemical is or will
be discharged to streams during manufacture, processing, use, or disposal.
The OncoLogic® model estimates the likelihood that a chemical would cause
cancer in humans. Other models estimate potential exposures to a chemical in
consumer products. Models are also presented for estimating properties such
as vapor pressure and water solubility, which are important for projecting the
nature, magnitude, and duration of exposure.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
These Methods Provide Information in Four Areas
The P2 Assessment Framework provides information in the following areas,
based on chemical structure:
Physical/Chemical Properties
/ Melting point
S Boiling point
/Vapor pressure
•S Water solubility
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Pollution Prevention (P2) Chemical Screening Assessment Framework
What is Required to Use the Framework Models?
Essential Information
All of the tools require minimal, but important information. For example, physical and chemical
properties such as molecular weight are important. Other models require the user to input the
amount of chemical likely to be discharged to a stream or river. The table on the following page
summarizes the required input information as well as the output data for each model.
Knowledge or Expertise Required
Knowledge needed will vary depending on the application. For example, the models KOWWIN® and
PCKOCW1N® only require chemical structure or CAS number; however, ECOSAR and OncoLogic®
require that the user have a good understanding of organic chemistry. User's Guides and technical
assistance are available to help when you are uncertain how to proceed.
Model Availability
Models to Estimate Physical/Chemical Properties of Chemicals:
MPBPVP®, KOWWIN©, WSKOW®, PCKOCWIN®, HENRYW1N®, and BCFW1N© can be obtained
by contacting Syracuse Research Corporation (SRC), Contact: Philip Howard, Ph.D. Environmental
Sciences Center, Syracuse Research Corporation, 6225 Running Ridge Rd., North Syracuse, NY
13212. Phone: 315-452-8417, Fax: 315-452-8440, Email: howardp@syrres.com, website:
http://esc.syrres.com
Models to Estimate Chemical Fate in the Environment:
AOPWIN®, BIOWIN®, and HYDROWIN® can be obtained by contacting SRC. STP can be obtained by
contacting Mary Katherine Powers, EPA/OPPT, Phone: 202-260-3898, Email: powers.mary@epa.gov
Models to Estimate Hazard to Humans and the Environment:
OncoLogic® can be purchased by contacting: Marilyn S. Amott, Ph.D., LogiChem, Inc., PO Box 357,
Boyertown, PA 19512, Phone: 610-367-1636, Fax: 610-367-1893, Email: marnott@logichem.com
ECOSAR can be obtained by downloading from the Internet at: http://www.epa.gov/opptintr/newchms
or by contacting Mary Katherine Powers, EPA, OPPT
Models to Estimate Exposure and/or Risk:
SEAS, ReachScan, PDM3, Dermal, SCIES and Occupational Exposure Spreadsheets can be
obtained by contacting Mary Katherine Powers, EPA/OPPT
Computer Requirements
These models are designed to run on an IBM
compatible personal computer. The specific
computer requirements (memory and disk
size) necessary to run each of these models
are provided on page 116 of this manual
The
computer
"Wizard"
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Inputs and Outputs of the Framework Models
Models to Estimate Physical/Chemical Properties
Model Output
MPBPVP Melting point
Boiling point
Vapor pressure
KOWWIN Octanol-water partition coefficient
WSKOW Water solubility
PCKOCWIN Soil sorption coefficient
HENRYWIN Henry's Law constant
BCF Estimated bioconcentration factor
Input
Chemical structure in SMILES
Chemical structure in SMILES
Chemical structure in SMILES
Chemical structure in SMILES
Chemical structure in SMILES
LogKOW
Models to Estimate Chemical Fate in the Environment
Model Output
AOPWIN Atmospheric oxidation
BIOWIN Biodegradation
HYDROWIN Hydrolysis
STP Percent removal
Input
Chemical structure in SMILES
Chemical structure in SMILES
Chemical structure in SMILES
Chemical properties
Models to Estimate Hazards to Humans and the Environmental
Model Output
OncoLogic Cancer hazard ranking
ECOSAR Ecotoxicity values
(Acute and Chronic LDSOs)
Input
Chemical structure
Chemical structure in SMILES
Models to Estimate Exposure and / or Risk
Model Output
Dermal Consumer dermal potential dose rate (PDR)
SCIES Consumer inhalation PDRs
ReachScan Chemical concentration downstream at
drinking water intake point
PDM3 Days per year concern concentration is
exceeded
SEAS Stream concentration, drinking water and fish
ingestion PDRs
Occupational Worker exposure to vapors
Spreadsheets
Input
Weight fraction
Molecular weight, vapor
pressure, weight fraction
Facility location (NPDES),
release data
Release quantity, concern
concentration
Stream flow data, release
quantity, BCF
Molecular weight, vapor
pressure, operation hrs/day,
worker exposure hrs/day
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Pollution Prevention (P2) Chemical Screening Assessment Framework
About This Document
Contents of This Document
This manual explains the models used by OPPT to screen potential exposures
and risks posed by chemicals. Each model answers important questions about a
chemical's potential impact on humans or the environment. The models are
described in this document by briefly detailing the important information they
provide. Flow diagrams presenting step-by-step use of some of the more
complex models are also included. In addition, a series of structured examples
(case studies) are provided to show how the models can answer specific
environmental questions and how the models can be used in combination to
answer complicated exposure/risk-related questions.
We believe this information will be useful to you. The manual provides some
information on how to use the models. However, we recognize that you may still
have questions after you read this material. Technical assistance is available
from OPPT to answer those questions.
Users of This Document
You are reading this manual because you are interested in opportunities to
prevent pollution. These opportunities may also decrease costs to your company
or organization. As you read, please keep in mind that this version of the P2
Framework is the first step in an evolving process. All comments and
suggestions for improvement are welcome. Please direct comments to:
Mary Katherine Powers, EPA/OPPT
Phone: 202-260-3898
Email: powers.mary@epa.gov
How This Document Is Organized
This document presents brief overviews of 18 models. Each overview provides
enough information to successfully run each model. More detailed information on
each model is provided in the User's Guide or supplemental documentation for
that model.
Case studies follow the overviews and are provided to illustrate how the models
can be used in combination to answer complicated risk-related questions.
A glossary of relevant terms is also included. Terms in the text of the document
that appear in italics are defined in the glossary.
12
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Models Presented
The 18 models included in this manual are listed below,
and are presented in the illustration on the following page.
The illustration can be used as an informal "road map" to
help decide which models you will need to use.
PHYSICAL/CHEMICAL
PROPERTY MODELS
MPBPVP©
KOWWIN©
WSKOWWIN©
PCKOCWIN©
HENRYWIN©
BCFWIN©
FATE MODELS
AOPWIN©
BIOWIN©
HYDROWIN©
STP
HAZARD MODELS
OncoLogic®
ECOSAR
EXPOSURE and/or RISK
MODELS
SEAS
ReachScan
PDM3
Dermal
SCIES
Occupational
Spreadsheets
13
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Models to Assess Potential Risk of Chemicals
Physical/Chemical
Properties
MPBPVPWIN
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Pollution Prevention (P2) Chemical Screening Assessment Framework
EPIWIN© and SMILES©
What Is EPIWIN©?
Estimations Programs Interface for Windows® (EPIWIN®) provides a quick and
easy way to run all eight Windows-based estimation programs, listed below, from
a single entry for a single chemical. The chemical structure or CAS number is
entered only once, and EPIWIN® executes all of the programs in sequence and
captures their output. Any of the estimation programs may be run separately.
The EPIWIN® Programs also can input chemical structure formats generated by
other computer programs. These importable formats include:
Alchemy III MOL files HyperChem HIM files PCModel files
Beilstein ROSDAL files MDL ISIS SKC files Softshell SCF files
BioCAD Catalyst TPL files MDL MOL files Tripos Sybyl Line Notation
ChemDraw files Molecular Presentation Tripos SYBYL MOL2 files
ChemDraw Connection Tables Graphics MPG files
The
computer
"Wizard"
PIWIN© Can
equentially Run:
AOPWIN©
HENRYWIN©
PCKOCWIN©
BIOWIN©
HYDROWIN©
MPBPVP©
WSKOW©
KOWWIN©
What Is SMILES©?
SMILES© is "Simplified Molecular Input Line
Entry System," which translates a chemical's
structure into a string of symbols that is easily
understood by computer software. You can
learn to write SMILES© notations, or you can
purchase a data base containing SMILES©
notations of many chemicals. For all EPIWIN©
estimation programs, enter only the SMILES©
notation for the chemical, and the program
provides the estimation you need.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES® Notations
(Examples are Provided in Appendix C)
Writing SMILES® Notations
The SMILES® notation system was designed by chemists for
computer use (Weininger, 1988. J. Chem. Inf. Comput. Sci. 28: 31-
6). SMILES® notations depict the molecular structure of a chemical
as a 2-dimensiona! picture. Learning to write a SMILES® notation is
not difficult but it can be tricky. The same 3-dimensional structure
can be correctly written in many different SMILES® notations.
The rules for writing SMILES® notations are included in the EPIWIN® User's Guide
available from Syracuse Research Corporation (SRC); however, you can purchase the
SMILECAS data base from SRC that contains SMILES® notations of many chemicals.
Some Rules for Writing SMILES® Notations
Atoms are represented by atomic symbols. Aliphatic atoms are entered in upper case, and
aromatic atoms (carbon, oxygen, sulfur, selenium, and nitrogen) are entered in lower case.
Examples:
Ethane (CH3-CH3) CC
Benzene (C6 H6) c1 cccccl
Ethylbenzene (C6 H5 C2 H5) CCdccccd
Bromoethane (CH3-CH2-Br) CCBr
1,3-Dichloropropane (CL-CH2-CH2- CH2-CL) CLCCCCL
Four types of Bonds are represented in SMILES®. These include:
• Single Bonds - represented by a hyphen"-". However, the program drops the hyphen, so it
is not necessary to type it Ethane (CH3-CH3) is CC and not C-C.
• Double Bonds - represented by an equal "=" and must be indicated. Ethylene (CH2=CH2) is
C=C.
Triple Bonds — represented by a number symbol "#", for example acetylene (CH^CH-j) is
C#C.
• Aromatic Bonds - represented by a":", and are indicated by lower case.
Normally single bonds and aromatic bonds do not need to be written in the SMILES notation.
Branches are designated in enclosed parentheses, for example 2-Propanol is CC(O)C. Branches
can not begin a SMILES® notation and must follow the atom and not the bond symbol.
Cyclic Structures are the most complicated to write. Numbers (1-9) are used to indicate where
the ring starts and stops, and never follow a branch.
A summary of directions for writing SMILES® notations are included iri1 Appendix C of this
document Complete directions for writing SMILES® notations are included in the EPIWIN®
User's Guide, available from Syracuse Research Corporation, 6225 Running Ridge Road, North
Syracuse, New York 13212-2509, 315-452-8000.
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P/Chem Properties Models
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Models to Estimate
Physical/Chemical Properties of Chemicals
Following are brief fact sheets providing information on the
models OPPT uses to estimate physical and chemical properties
of chemicals. Information provided on each model includes:
•S What physical/chemical property does the model
estimate?
•/ What is significant about the physical/chemical property
to exposure assessment?
/ Why is knowing physical/chemical properties important?
•/ Why would I want to use the model?
/ What do I need to run the model?
/ What are the inputs and outputs for the model?
PHYSICAL/CHEMICAL
PROPERTY MODELS
MPBPVP©
KOWWIN©
WSKOWWIN©
PCKOCWIN©
HENRYWIN©
BCFWIN©
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
18
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Pollution Prevention (P2) Chemical Screening Assessment Framework
MPBPVP© to Estimate
Melting Point, Boiling Point, and Vapor Pressure
Why is Melting Point (MP) Important?
MP is the temperature at which a chemical
changes from solid to liquid, and gives clues to
other chemical properties:
/MP indicates state (solid-liquid-gas) of the
chemical in the ambient environment.
/ High MP indicates low water solubility.
/ Low MP indicates increased absorption is
possible through the skin, Gl tract, or lungs.
/The range of measured MPs indicates its
purity: narrow = more pure, wide = less pure.
/MP <100°C = increased volatility and higher
potential inhalation exposures.
What Does the MPBPVP®
Model Do?
MPBPVP© estimates a
chemical's melting
point, boiling point,
and vapor pressure at
25°C.
Why Use the MPBPVP© Model?
ambient environment, anc
temperature it will change
Why is Boiling Point (BP)
Important?
BP is temperature at which the VP of a
chemical in a liquid state equals
atmospheric pressure, and, like MP,
gives clues to other chemical properties:
/High BP indicates low VP, seen, for
example in structurally large
substances like polymers.
Why is Vapor Pressure (VP)
Important?
VP is pressure at which a liquid and its
vapor are in equilibrium at a given
temperature, and, like MP and BP, gives
clues to other chemical properties:
/Chemicals with high VPs often have
higher potential inhalation exposures
than chemicals with low VPs.
/ Chemicals with VP >1 f>3 ton tend to
volatilize easily and can have higher
potential inhalation exposures.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
MPBPVP© to Estimate
Melting Point, Boiling Point, and Vapor Pressure
What You Need to Use
MPBPVP©
/ CAS number or chemical
structure (may be in
SMILECAS
data base)
Inputs
/ CAS number or
chemical structure in
SMILES® notation
Examples of Melting Points at 25° C
CAS Number n Chemical Degrees C
60571 U Dieldrin 135
108952 I Phenol -2
75092 I Dichloromethane -90
67641 I Acetone -94
50000 I Formaldehyde -111
Examples of Boiling Points at 25° C
CAS Number n Chemical Degrees C
60571 H Dieldrin 340
108952 I Phenol 170
75092 I Dichloromethane 80
67641 II Acetone 45
50000 I Formaldehyde 10
Examples of Vapor Pressures at 25° C
CAS Number
50000
67561
75092
108952
60571
Chemical mm Hg@25C
Formaldehyde 1330
Methanol 396
Dichloromethane 86
Phenol 1
Dieldrin 1.77E-5
Outputs
Molecular weight and formula"
Estimations of melting point,
boiling point, and vapor pressui1
at25°C
Chemical structure can be
printed or saved as either MDL
ISIS SKC file or MDL MOL
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the MPBPVP© Model
INPUTS:
CAS Number = 108883 (Methyl-benzene)
RESULTS:
SMILES
CHEM
MOL FOR
MOL WT
C(CCCC1) (C1)C
benzene, methly-
C7H8
92.14
SUMMARY-
Boiling Point: 125.72 deg C (Adapted Stein and Brown method)
Melting Point: -78.09 deg C (Adapted Joback method)
Mean Melt Pt: -59.17 deg C (Adapted Joback; Gold, Ogle methods)
Selected MP: -59.17 deg C (Mean value)
Melting point is
calculated by two
different methods,
mean value is
determined, and the
mean is selected as
the melting point. 1
\uie
>
Vapor Pressure Estimations (23 deg C):
(Using BP: 125 deg C (estimated))
(MP not used for liquids)
VP: 13 mm Hg (Antoine method)
VP: 11.3 mm Hg (Modified Grain method)
VP: 15.4 mm Hg (Mackay method)
Selected VP: 12.1 mm Hg (Mean of Antoine and Grain methods)
Vapor pressure
also is calculated
by two different
methods, and a
mean value is
selected as the
vapor pressure. >
TYPE | NUM | BOIL DESCRIPTION
| COEFF | VALUE
Group | 1 |
Group j 5 j
Group j 1 j
I I
RESULT- uncorr |
RESULT- coir |
I
TYPE | NUM |
Group | 1 |
Group j 5 |
Group j 1 j
I I
RESULT |
I
RESULT |
I
-CHS |
CH (aromatic) j
-C (aromatic) j
Equation Constant j
BOILING POINT in deg Kelvin |
BOILING POINT in deg Kelvin |
BOILING POINT in deg C |
MELT DESCRIPTION |
-CHS |
CH (aromatic) j
-C (aromatic) |
Equation Constant j
MELTING POINT in deg Kelvin |
MELTING POINT in deg C |
MELTING POINT in deg Kelvin |
MELTING POINT in deg C |
21.98 |
28.53 |
30.76 |
I
COEFF |
-5.10 |
8.13 |
37.02 |
I
21.98
142.65
30.76
198.18
393.57
398.88
125.72
VALUE
-5.10
40.65
37.02
122.50
195.07
-78.09
173.50
-99.66
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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Pollution Prevention (P2) Chemical Screening Assessment Framework
KOWWIN© to Estimate
Octanol-Water Partition Coefficient (KOW)
What Is KOW?
KOW indicates whether a
chemical predominantly will be
found in water (is hydrophilic) or
in fatty tissue of animals or other
organic materials (is lipophilic) in
an aquatic environment.
What Does the KOWWIN© Model Do?
KOWWIN©
estimates a
chemical's octanol-
water partition
coefficient (KOW).
Important Note
KOW is often reported as a
log due to the extremely
wide range of measured
KOW values.
Why Use the KOWWIN© Model?
Why Is KOW Important?
Lipophilic chemicals can
bioaccumulate in fatty tissue
offish and bioconcentrate in
animals (including humans)
that consume the fish.
I need to know
where the chemical will
go inthe stream - Partitioning
Bioconcentratio
Relationship Between Log KOW and BCF
Log KOW
As log KOW increases the solubility
in lipids increases. This means an
increase in the potential to
bioconcentrate in aquatic organisms.
This relationship begins to change
around log KOW of 6.
For chemicals with log KOW
exceeding 6 the potential to
bioconcentrate begins to drop
approaching 0 at log KOW of 12.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
KOWWIN© to Estimate
Octanol-Water Partition Coefficient (KOW)
Examples of KOW Values
What You Need to Use
KOWWIN©
./ CAS number or chemical
structure (may be ir[
SMILECAS
data base)
CAS Number
60571
1912249
75092
50000
67641
Chemical
Dieldrin
Atrazine
Dichloromethane
Formaldehyde
Acetone
log KOW
5.2
2.6
1.3
0.4
-0.2
Important Note
A log KOW of 0 indicates
an equal affinity for lipids
and for water.
Inputs
/ CAS number or chemical
structure in SMILES©
notation
Outputs
/ Log KOW
Molecular weight and formula
•/ Chemical structure can be
printed or saved as either
MDL ISIS SKC file or MDL
MOL file
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the KOWWIN® Model
INPUTS:
RESULTS:
CAS Number = 60571 (dieldrin)
Log Kow (estimated) : 5.45
Experimental Database Structure Match:
Name
CAS Num
Exp Log P
ExpRef
Dieldrin
000060-57-1
5.40
DeBruijn, J. etal; 1989
Experimental Database Structure Match:
Name
CAS Num
Exp Log P
ExpRef
SMILES
CHEM
MOL FOR
MOLWT
TYPE NU
Frag
Frag
Frag
Frag
Frag
Frag
Frag
Frag
Factor
Const
Endrin
000072-20-8
5.20
DeBruijn, J. et al; 1989
CLC4=C(CL)C5(CL)C3C1CC(C2OC12)C3C4(CL)C5(CL)CL
Dieldrin
C12 H8 CL6 O1
380.91
M LOGKOW FRAGMENT DESCRIPTION CC
)EFF VALUE
1 -CH2- [aliphatic carbon] 0.4911 0.4911
6 -CH [aliphatic carbon] 0.3614 2.1684
1 C [aliphatic carbon-No H, not tert] 0.9723 0.9723
2 =CH- or =C<[olefinc carbon] 0.3836 0.7672
1 -O- [oxygen, aliphatic attach] -1.2566 -1.2566
4 -CL [chlorine, aliphatic attach] 0.3102 1.2408
2 -CH2- [chlorine, olefinic attach] 0.4923 0.9846
2 -tert Carbon [3 or more carbon attach] 0.2676 0.5352
2 -CH2- [aliphatic carbon] 0.3421 0.6842
Equation Constant
0.2290
LogKow= 5.4478
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
26
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Pollution Prevention (P2) Chemical Screening Assessment Framework
WSKOW© to Estimate
Water Solubility
What Does the WSKOW© Model Do?
What Is Water
Solubility?
Water solubility is the degree to
which a compound will dissolve
in water. It is reported as the
amount of the chemical (in
milligrams) that will dissolve in
1 liter of water (mg/L).
WSKOW© uses the
log KOW to
estimate the
compound's water
solubility at 25°C.
Why Use the WSKOW© Model?
I need to know if the
compound will dissolve in
surface water - Solubility.
Why Is Knowing Solubility (S) Important?
Chemicals with low S will have low
concentration in aqueous media.
Chemicals with high S:
^Are more likely to be transported along
with the water during storm events or
through the water table; and
/ Have low log KOW values, and are more
likely to be absorbed through Gl tract, or
lungs. The exception is the case of
dispersable molecules like surfactants,
and detergents. These can have high
predicted log KOW. They can be
absorbed into the lung.
Solubility Classification
(mg/Lor ppm)
Very soluble
Soluble
Moderately sol.
Slightly Soluble
Insoluble
> 10,000
> 1,000-10,000
> 100-1,000
>0.1 - 100
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Pollution Prevention (P2) Chemical Screening Assessment Framework
WSKOW® to Estimate
Water Solubility
Examples of Water Solubility Values
What You Need to Use
WSKOW®
/ CAS number or chemical
structure (may be in
SMILECAS
data base)
CAS Number
67561
67641
50000
1912249
60571
Chemical Water Sol. (mg/L)
Methanol 1 .OOE+06
Acetone 2.20E+05
Formaldehyde 5.74E+04
Atrazine 2.14E+02
Dieldrin 1.46E-01
Important Note
WSKOW© is not
appropriate for
surfactants, which
are dispersible.
Inputs
/ CAS number or chemical
structure in SMILES®
notation
Outputs
/ Molecular weight and formula
/ Water solubility at 25°C
(milligrams per liter)
•/ Chemical structure can be printe
or saved as either MDL ISIS S
file or MDL MOL file
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the WSKOW® Model
INPUTS:
CAS Number = 1912249 (atrazine)
RESULTS:
Water sol: 214.1 mg/L
SMILES
CHEM
MOL FOR
MOLWT
n(c(nc(n1 )NC(C)C)NCC)c1 CL
Atrazine
C8 H14 CL1 N5
215.69
LogKow (estimated) : 2.82
Log Kow (experimental) : 2.61
CAS Num
Name
Refer
001912-24-9
Atrazine
Hanschetal; 1995
Low Kow used by Water solubility estimates: 2.61
Equation Used to Make Water Sol estimate:
Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
(used when Melting Point NOT available)
Correction(s): Value
No Applicable Correction Factors
Log Water Solubility (inMoles/L) : -3.003
Water Solubility at 25 deg C (mg/L) : 214.1
29
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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Pollution Prevention (P2) Chemical Screening Assessment Framework
PCKOCWIN@ to Estimate
Organic Carbon Adsorption Coefficient (KOC)
What Is KOC?
KOC is the ratio of amount of
chemical adsorbed per unit mass of
organic carbon (the "OC") in soils,
sediments, or sludge to the
concentration of the chemical in the
solution at equilibrium.
KOC indicates whether a chemical is
likely to be be found in water or the
organic carbon portion of soils or
sediments.
What Does the PCKOCWIN®
Model Do?
PCKOCWIN0
estimates a
chemical's soil
sorption coefficient
(KOC).
Why Use the PCKOCWIN® Model?
I need to know
where the chemical will
go in the stream - Partitioning.
Important Note
Like KOW, KOC is also
often reported as a log due
to the extremely wide range
of measured KOC values.
Why Is KOC Important?
KOC value provides an indication of
whether or not a chemical will migrate
with ground water.
High KOC indicates the chemical is
likely to sorb to soils, sediments, or
sludge and is less likely to migrate to
ground water or to surface waters.
Low KOC indicates chemical is not
likely to sorb to soils, sediments, or
sludge, thus is more is likely to
migrate to water.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
PCKOCWIN® to Estimate
Organic Carbon Adsorption Coefficient
Examples of KOC Values
What You Need to Use
PCKOCWIN®
•/ CAS number or chemical
structure (may be ir
SMILECAS
data base)
CAS Number
60571
1912249
75092
106898
67641
Chemical Log Koc
Dieldrin 4.025
Atrazine 2.362
Dichloromethane 1.376
Epichlorohydrin 0.652
Acetone 0.297
Sorption Values (log KOC)
Very strong
Strong
Moderate
Low
Negligible
>4.5
3.5-4.5
2.5-3.5
1.5-2.5
Log KOC and Removal Rates
When Log KOC >4.5 chemical will
be removed by sorption to sludge
in wastewater treatment plants.
Inputs
/ CAS number or chemical
structure in SMILES2
notation
/ Estimated KOC
/ Molecular weight and formula
Chemical structure can be
printed or saved as either MD
ISIS SKC file or MDL MOL fHe
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the PCKOCWIN Model
INPUTS:
CAS Number = 106898 (epichlorohydrin)
RESULTS:
SMILES
CHEM
MOL FOR
MOLWT
Koc (estimated) : 4.49
O(C1CCL)C1
Oxirane, (chloromethyl)-
C3 H5 CL1 O1
92.53
First Order Molecular Connectivity Index
Non-Corrected Log Koc
Fragment Correction(s):
1 Ether, aliphatic (-C-O-C-)
Corrected Log Koc :
Estimated Koc : 4.491
2.432
1.9166
-1.2643
0.6523
33
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
34
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Pollution Prevention (P2) Chemical Screening Assessment Framework
HENRYWIN® to Estimate
Henry's Law Constant
What Is Henry's Law
Constant?
Henry's Law constant (HLC)
is the ratio of a chemical's
vapor pressure to its water
solubility. HLC gives a
relative measure of the
volatility of a compound from
water by measuring the
extent to which a compound
will partition between water
and the air.
What Does the HENRYWIN® Model Do?
HENRYWIN0 estimates the
Henry's Law Constant
(HLC) of an organic
compound by two different
methods. It also can
estimate the HLC of an
unknown compound based
on the HLC of a known
compound.
©
Why Use the HENRYWirr Model?
need to know if the
compound will volatilize from
water or remain in the water.
Why Is Knowing Henry's
Law Constant Important?
Knowing the HLC helps the risk
assessor predict the fate of the
chemical once it is released to
surface water.
•/ High HLC indicates chemical is
likely to volatilize from solution
and partition in air.
/ Low HLC indicates chemical is
not likely to volatilize and will
remain in surface water.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
HENRYWIN® to Estimate
Henry's Law Constant
What You Need to Use
HENRYWIN®
/ CAS number or chemical
structure (may be in
SMILECAS
data base)
CAS Number
75092
50000
67641
67561
60571
Examples of HLC Values
Chemical HLC (atm-m3/mole)
Dichloromethane 3.0 x 10'3
Formaldehyde 6.1 x 10'5
Acetone 4.0 x10'5
Methanol 4.4 x10'6
Dieldrin 5.4 x 10'7
Volatility Potential:
Very volatile
Volatile
Moderately volatile
Slightly volatile
Nonvolatile
10~1 -10~3
10'3-1(r5
10'5-10'7
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the HENRYWIN Model
INPUTS:
RESULTS:
SMILES
CHEM
MOL FOR
MOLWT
CLASS |
HYDROGEN |
HYDROGEN |
FRAGMENT |
FACTOR |
RESULT |
CAS Number = 67561 (methanol)
Bond Est : 4.27E-006 atm-m3/mole
Group Est : 3.62E-006 atm-m3/mole
OC
Methanol
C1 H4 O1
32.04
BOND CONTRIBUTION DESCRIPTION
3 Hydrogen to Carbon (aliphatic) bonds
1 Hydrogen to Oxygen bonds
1 C-O
* Non-cyclic alkyl or olefinic alcohol
^jTwo methods are used to |
estimate HLC. The group
contribution method is best
used for pesticides. I
|COMMENT| VALUE
| | -0.3590
| | 3.2318
| | 1.0855
| | -0.2000
BOND ESTIMATION METHOD for LWAPC VALUE | TOTAL | 3.758
HENRY'S LAW CONTSTANT at 25 deg C = 4.27E-006 atm-m3/mole
= 1.48E-004unitless
| GROUP CONTRIBUTION DESCRIPTION
I
I
1 CHS (X)
1 O-H (C)
(COMMENT) VALUE
| | -0.62
| | 4.45
RESULT | GROUP ESTIMATION METHOD for LOG GAMMA VALUE | TOTAL | 3.83
HENRY'S LAW CONTSTANT at 25 deg C = 3.62E-006 atm-m3/mole
= 1 .48E-004 unitless
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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Pollution Prevention (P2) Chemical Screening Assessment Framework
BCF to Estimate Bioconcentration Factor
What Is BCF?
A bioconcentration factor (BCF) is the
ratio (in L/kg) of a chemical's
concentration in the tissue of an
aquatic organism to its concentration
in the ambient water.
Why Is BCF Important?
BCF indicates potential for a
chemical to bioaccumulate in
lipids (fatty tissue) of aquatic
organisms, and to
bioconcentrate as it moves up
the food web.
Why Use a BCF Model?
What You Need to Use
the BCFWIN8
/ CAS number or chemical
structure (may be in
SMILECAS database); or
/LogKOtVofthe
chemical
I need to
know if the chemical will
bioaccumulate in aquatic life and
move up the food chain.
Relationship Between Log KOW and BCF
Log KOW
As log KOW increases the solubility
in lipids increases. This means an
increase in the potential to
bioconcentrate in aquatic organisms
This relationship begins to change
around log KOW of 6.
For chemicals with log KOW
exceeding 6 the potential to
bioconcentrate begins to drop
approaching 0 at log KOW of 12.
Bioconcentration Potential
High
Moderate
Low
>1,000
250-1,000
<250
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Pollution Prevention (P2) Chemical Screening Assessment Framework
BCF to Estimate Bioconcentration Factor
Examples of BCF Values
CAS Number P Chemical
Log BCF
8001352 I Toxaphene 4.5
12789036 I Chlordane 4.8
60571 I Dieldrin 3.7
108703 A 1,3,5-Trichlorobenzene 2.7
Inputs
/ CAS number or chemical
structure in SMILES
•/ Log KOWoi the chemical
•/ Estimated Log BCF
Estimated Log KOW
Molecular weight and
INPUTS:
CAS Number = 8001352 (toxaphene)
RESULTS:
SMILES
CHEM
MOL FOR
MOLWT
Log BCF (v2.00) estimate): 4.53
CLC(C)(CL)C1C2)C(C2(CL)CL)(C1(C(CL)CL)CCL)CCL
Toxaphene
C10H10CL8
413.82
Log Kow (estimated)
Log Kow (experimental)
Log KOW used by BCF estimates
Equation Used to Make BCF estimate:
Log BCF = 0.77 Log Kow - 0.70 + Correction
Correction(s): Value
No Applicable Correction Factors
Estimated Log BCF = 4.532 (BCF = 3.405e+004)
6.79
not available from database
6.79
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Fate Models
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Models to Estimate
Chemical Fate in the Environment
Following are brief fact sheets providing information on the
models OPPT uses to estimate the fate of a chemical once it is
released to the environment. Information provided on each
model includes:
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
42
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Pollution Prevention (P2) Chemical Screening Assessment Framework
AOPWIN® to Estimate
Atmospheric Oxidation Potential
What Is AOP?
The Atmospheric Oxidation
Program (AOP) estimates rate
constants and half-lives of
atmospheric reactions of organic
compounds released to the air
with hydroxyl radicals (-OH) and
with ozone in the atmosphere.
What Does the AOPWINT Model Do?
AOPWIN® estimates the
rate at which certain
organic compounds will
be destroyed by reactions
with compounds in the
atmosphere.
Why Use the AOPWIhT Model?
I need to know how long it will take^
for an organic compound to be
destroyed by reactions in the air -
Atmospheric Oxidation^
Potential.
Why Is Atmospheric
Oxidation Important?
The rate at which an organic
compound will be oxidized
(destroyed) indicates the length
of time the compound may
reside in the atmosphere. This
also is known as the chemical's
atmospheric residence time.
v0s.
^—--
Important Note
If a chemical has a high AOP
rate there still is a potential for
inhalation exposure if the travel
time from source to receptor is
greater than the time for
complete oxidation of the
compound.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
AOPWIN@ to Estimate
Atmospheric Oxidation Potential
What You Need to Use
AOPWIN®
/ CAS number or chemical
structure (may be in
SMILECAS
data base)
CAS Number
75092
67641
67561
60571
1912249
Examples of AOP Values
Chemical AOP 1/2 Life (days)
Dichloromethane 79.3
Acetone 52.4
Methanol 17.4
Dieldrin 1.2
Atrazine 0.4
AOP Half-life Value Classifications
Rapid < 2 hrs
Moderate 2 hrs - < 1 day
Slow > 1 day-<10 days
Negligible > 10 days
Inputs
/ CAS number or chemical
structure in SMILES®
notation
Outputs
•/ Molecular weight and formula
Chemical structure can be printed or
saved as either MDL ISIS SKC file or
MDL MOL file
Hydroxyl radical (-OH) rate constant
and half-life
Ozone reaction constant and half-h
pr olefins and acetylenes onh
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the AOPWIN Model
INPUTS:
CAS Number = 1912249 (atrazine)
RESULTS:
SMILES
CHEM
MOL FOR
MOLWT
Hydrogen Abstraction
Reaction with N, S, and -OH
Addition to Triple Bonds
Addition to Olefinic Bonds
**Addition to Aromatic Rings
Addition to Fused Rings
OVERALL OH
HALF-LIFE
HALF-LIVE
n(c(nc(n1 )NC(C)C)NCC)c1 CL
Atrazine
C8 H14 CL1 N5
215.69
SUMMARY: HYDROXYL RADICALS-
24.2300 E-
0.0000 E-
0.0000 E-
0.0000 E-
0.1176E-
0.0000 E-
12 cmS/molecule-sec
12 cmS/molecule-sec
12 cm3/molecule-sec
12 cmS/molecule-sec
12 cmS/molecule-sec
12 cmS/molecule-sec
27.3476 E-12 cm3/molecule-sec
0.391 Days (12-hr day; 1.5E6 OH/cm3)
4.693 Hrs
* * Designates Estimation(s) Using ASSUMED Value(s)
SUMMARY : OZONE REACTION
*** NO OZONE REACTION ESTIMATION
(ONLY Qlefins and Acetylenes are Estimated)
Experimental Database : NO Structure Matches
ozone are estimated
only for olefins and
acetylenes.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
BIOWIN to Estimate
Biodegradation
What You Need to Use
BIOWIN®
•/ CAS number or chemical
structure (may be in
SM1LECAS
data base)
Examples of Biodegradation Rates
CAS Number
60571
1912249
75092
67641
67561
Chemical Ultimate Biodeg. (weeks)
Dieldrin recalcitrant
Atrazine months
Dichloromethane weeks-months
Acetone weeks
Methanol days-weeks
Biodegradation Rates
Rapid
Moderate
Slow
Very slow
Inputs
/ CAS number or chemical
structure in SMILES® notation
> 60% in < 7 days
> 30% in < 28 days
< 30% in < 28 days
< 30% in > 28 days
Outputs
Molecular weight and formula
•/ Predicted primary and ultimate
biodegradation in hours, days,
weeks, or months; also predicted,
via separate but by linked model,
the probability of fast
biodegradation using two different^
methods
Chemical structure can be prinf
saved as either MDL
le opMDL MOL file
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the BIOWIN Model
INPUTS:
CAS Number = 67561 (methanol)
RESULTS:
SMILES OC
CHEM Methanol
MOL FOR C1 H4 O1
MOLWT 32.04
Linear Model Prediction : Biodegrades Fast
Non-Linear Model Prediction : Biodearades Fast
Ultimate Biodegradation Timeframe : Days-Weeks '""
Primary Biodegradation Timeframe : Days-Weeks
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Aliphatic alcohol [-OH]
MolWt | * | Molecular Weight Parameter
Const j * j Equation Constant
RESULT | LINEAR BIODEGRADATION PROBABILITY
This chemical j
completely in
4^days to weeks^
COEFF | VALUE
0.1587 | 0.1587
| -0.0153
| 0.7475
| 0.8910
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Aliphatic alcohol [-OH]
MolWt j * j Molecular Weight Parameter
RESULT | NON-LINEAR BIODEGRADATION PROBABILITY
COEFF | VALUE
1.1178 | 1.1178
| -0.4550
| 0.9752
A Probability Greater Than or equal to 0.5 indicates -> Biodegrades Fast
A Probability Less Than 0.5 indicates -» Does NOT Biodegrade Fast
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Aliphatic alcohol [-OH]
MolWt j * j Molecular Weight Parameter
Const j * | Equation Constant
RESULT | SURVEY MODEL -ULTIMATE BIODEGRADATION
COEFF | VALUE
0.1600 | 0.1600
| -0.0708
| 3.1992
| 3.2883
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 I Aliphatic alcohol [-OH]
MolWt | * | Molecular Weight Parameter
Const | * j Equation Constant
RESULT | SURVEY MODEL -PRIMARY BIODEGRADATION
Result Classification : 5.00 -* hours 4.00 -» days 3.00
(Primary and Ultimate) 2.00 -* months 1 .00 -* longer
COEFF | VALUE
0.1294 | 0.1294
| -0.0462
| 3.8477
| 3.9310
-» weeks
49
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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Pollution Prevention (P2) Chemical Screening Assessment Framework
HYDROWIN© to Estimate
Hydrolysis
What Is Aquatic
Hydrolysis?
Once a chemical enters a
surface water body, it
may react with water in a
manner in which the
water molecule, or the
hydroxide ion, displaces
an atom or group of
atoms in the chemical.
What Does the HYDROWIN© Model Do?
HYDROWIN® estimates acid- and
base-catalyzed rate constants for
certain chemical classes (esters,
carbamates, epoxides,
halomethanes, and certain alkyl
halides). The rate constants are
used to calculate hydrolysis half-
lives at selected pHs.
Why Use the HYDROWIN® Model?
I need to know
if the chemical will react with
water in the stream - Hydrolysis.
Why Is Hydrolysis
Important?
The rate at which a compound
reacts with (and is broken down
by) water helps a risk assessor
estimate the concentration of the
compound after it is released to
surface water. Understanding
hydrolysis is important in
determining the fate of the
chemical in water.
51
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Pollution Prevention (P2) Chemical Screening Assessment Framework
HYDROWIN© to Estimate
Hydrolysis
What You Need to Use
HYDROWIN©
•/ CAS number or chemical
structure (may be
SMILECAS
data base)
Examples of Hydrolysis Rates
CAS Number Chemical
60571 I Dieldrin
Hydrolysis
1/2 Life (yrs)
12.82
106898 I Epichlorohydrin 0.02
Inputs
/ CAS number or chemical
structure in SMILES©
notation
Outputs
V Molecular weight and fonfiul
/
•/ Estimated hydrolysis at 25°C
y Half-life at pHs 8 and 7
•/ Chemical structure can be
printed or saved as either
MDL ISIS SKC file or MD
OLfile
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the HYDROWIN© Model
INPUTS:
CAS Number = 60571 (dieldrin)
RESULTS:
SMILES
CHEM
MOL FOR
MOLWT
CLC4=C(CL)C5(CL)C3C1CC(C2OC12)C3C4(CL)C5(CL)CL
Dieldrin
C12 H8 CL6 O1
380.91
NOTE: Fragments) on this compound are NOT available from the fragment library.
Substitute(s) have been used !!! Substitute R1, R2, R3, or R4 fragments are marked with
double astericks "**".
EPOXIDE: R1 O
K2>c—>cR4
** R1:-CH(Et)(i-Pr) ** R3: -CH(Et) (i-Pr)
R2: -H R4: -H
Ka hydrolysis at (epoxy O) atom # 12: 1.713E-002 L/mol-sec
Total Ka (acid-catalyzed) at 25 deg C : 1.713E-002 L/mol-sec
Ka Half-Life at pH 7: 12.823 years
The rate constant estimated for the EPOXIDE DOES NOT include
the neutral hydrolysis rate constant!!!
For some epoxides, the neutral rate constant is the dominant hydrolysis
rate at environmental pHs!
If the neutral rate constant is important, they HYDRO estimated rate will
under-estimate the actual rate!
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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Pollution Prevention (P2) Chemical Screening Assessment Framework
STP to Estimate
Percent Removal in Wastewater Treatment
What Are "STPs" and
"POTWs"?
STP is "Sewage Treatment
Plant," and POTW is "Publicly
Owned Treatment Works."
Both are names for utilities that
treat waste water and usually
discharge the treated water to
nearby surface water bodies.
What Does the STP Model Do?
STP predicts the
percent of a compound
that will be removed
from the waste water
in wastewater
treatment.
Why Use the STP Model?
I need to know
how much of the chemical will
be removed from the waste
water during treatment in the
POTW.
Why Is Knowing the
Percent Destroyed in a
POTW Important?
Knowing how much of the
chemical will be removed from
waste water during wastewater
treatment enables the risk
assessor to predict how much
of the chemical may be
discharged by the POTW to
surface water and potentially
affect aquatic life.
55
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Pollution Prevention (P2) Chemical Screening Assessment Framework
STP to Estimate
Percent Removal in Wastewater Treatment
Examples of Removal Rates
CAS Number Chemical Removal
in STP (%)
Dieldrin 83.11
Dichioromethane 55.11
Formaldehyde 67.3
Acetone 73.06
Phenol 97.47
What You Need to Use the STP Model
/ Molecular weight (grams per mole)
•/ Water solubility (mg/L)
•/Vapor pressure (millimeters of mercury)
y Log KOW
•/ Biodegradation half life in 2 g/L activated
sludge
•/ Information on the Sewage
Treatment Plant (defaults
can be used instead):
• Plant operating conditions
• Plant design
•/ Percent removal in
wastewater treatment
Overall chemical mas
balance
The STP Model is discussed in the following articles:
Clark, B.; J.G. Henry; and D. Mackay. 1995. Environmental Science and
Technology 29(6): 1488-1494.
Clark, B.; D. Mackay; L Tasfi; G.L.H. Henry; and S. Salenieks. 1989. A Model
of Organic Chemical Fate in a Biological Wastewater Treatment Plant. Prepared
for the Ontario Ministry of the Environment, A. Ho and H. Monteith - scientific
authorities.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the STP Model
INPUTS:
Temperature [deg C] 25 Primary clarifier tank
Molecular weight (g/mol) 78 Aeration vessel
Water solubility (mg/l) 1800 Final settling tank
30.00
5.00
5.00
Vapor pressure (mm Hg) 95.25784 Plant operating conditions Default
Log Kow 1.99 Plant design
RESULTS:
PREDICTED FATE OF AN ORGANIC CHEMICAL
IN A WASTEWATER TREATMENT FACILITY
PROPERTIES OF Chemical B
Molecular weight (g/mol) 78
Aqueous solubility (mg/l) 1800
Vapor pressure (Pa) 12700
(atm) .1253393
(mm Hg) 95.25784
Henry's Law constant (Atm-m3/mol) 5.431 35E-03
Air-water partition coefficient .2221261
Octanol-water partition coefficient (Kow) 97.72372
Log Kow 1.99
Biomass to water partition coefficient 20.34475
Temperature [deg C] 25
Biodeg. rate consts (hM), half lives in biomass (h) and in 2000
-Primary tank 0.59 1.17
-Aeration tank 3.54 0.20
-Settling tank 3.54 0.20
OVERALL CHEMICAL MASS BALANCE
g/h mol/h
Influent 0.10E+02 0.1E+00
Primary sludge 0.45E-01 0.6E-03
Waste sludge 0.32E-01 0.4E-03
Primary volatilization 0.12E+00 0.2E-02
Settling volatilization 0.67E-01 0.9E-03
Aeration off gas 0.41 E+01 0.5E-01
Primary biodegradation 0.57E+00 0.7E-02
Settling biodegradatjon 0.21 E+00 0.3E-02
Aeration biodegradation 0.30E+01 0.4E-01
Final water effluent 0.19E+01 0.2E-01
Total removal 0.81 E+01 0.1 E+00
Total biodegradation 0.37E+01 0.5E-01
Default
mg/L MLSS (h)
30.00
5.00
5.00
'
percent
100.00
0.45
0.32
1.18
0.67
41.05
5.65
2.10
29.75
18.83
81.17
37.50
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Pollution Prevention (P2) Chemical Screening Assessment Framework
STP Model Flow Diagram
Specify
Chemical to be
Analyzed
/ Enter
Chemical
Paramters
/
/ Specify
7 Plant Operating
Conditions
Specify
Plant Design
* The program includes parameters
of 16 commonly encountered
chemicals, including:
benzene
toluene
1,1,2trichloroethene
1,1,1 trichloroethane
1,4dichlorobenzene
napththalene
pyrene
phenol
2-4D
gamma BHC
butyl-benzyl phthalate
di-butyl phthalate
di-octyl phthalate
2-ethylhexyl phthalate
pentachlorophenol
anthracene
Print and Save
RESULTS
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Hazard Models
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Models to Estimate
Hazard to Humans and the Environment
Following are brief fact sheets providing information on the models
OPPT uses to estimate hazard to humans and the environment from
exposure to chemicals released to the environment. Information
provided on each model includes:
•/ What hazard does the model estimate?
/ What is significant about the hazard to exposure
assessment?
•/ Why is knowing the hazard important?
•/ Why would I want to use the model?
•/ What do I need to run the model?
/ What are the inputs and outputs for the model?
HAZARD MODELS
OncoLogic®
ECOSAR
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® to Estimate
Potential Carcinogenicity
What Does the Model Do?
OncoLogic®
estimates the
potential
carcinogenicity
of a chemical.
How Does the Model Work?
OncoLogic® estimates the potential for a
chemical to cause cancer in humans using
the known carcinogenicity of chemicals with
similar chemical structures, information on
mechanisms of action, short-term predictive
tests, epidemiological studies, and expert
judgment.
Why is Carcinogenicity of
a Chemical Important?
An understanding of the
potential for the chemical to
cause cancer helps the risk
assessor estimate the impact of
the release on the surrounding
human population.
Why Use the OncoLogic® Model?
I need to know
the potential for the chemical to
cause cancer in humans -
Carcinogenicity.
I also need to know
should do further testing of
the chemical -
Bioassavs
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® to Estimate
Potential Carcinogenicity
Inputs
/ Class of chemical (fiber,
polymer, metal, or organic
compound)
/ Chemical structure
/ Functional groups present
/ Additional properties listed in
Flow Diagrams for each
module.
What You Need to Use OncoLogic®
/ Good understanding of organic chemistry
/ Chemical class of the compound
/ Certain physical and chemical
properties of the compound
Important Note
OncoLogic® has modules to
estimate carcinogenicity of 4
types of compounds:
-/ Fibers y Metals
/ Polymers / Organics
/ Summary of predicted
concern level (high to lo
Line of reasoning for
estimation
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Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® Model
Flow Diagram
Inputs: Chemical Information
Requested by Module
(See Following Flow Diagrams,
for Specific Module Inputs)
\7
Justification Report
is Displayed
*NOTE: Flow
diagrams for each
of the 4 modules
follow this basic
diagram.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® Model Flow Diagram - Fibers
Evaluate in
another ONCO
Module
Enter
Chemical's Unique
File Name* /
Enter
Chemical's Unique
Substance ID*
Inputs Needed for Fibers
Evaluation:
Water solubility (yes/no)
Diameter (microns)
Length (microns)
Enter
Water Solubility
(Y/N/Unk)
Enter Diameter (microns)
Length (microns)
High Density Charge? (Y/N/Unk)
Additional Properties* (if known)
Additional Moieties# (if known)
Enter
Manufacturing
/ Process
Additional Inputs Needed for
Refining the Evaluation Are:
Presence of electrical charge
Properties*
Flexibility
Durability
In vivo biodegradability
Surface characteristics
Splitting properties
Mo/effes*
High molecular weight polymer
Low molecular weight organic
moiety
Metals or metalloids
Manufacturing process
Use scenario
Select
Standard Evaluation
or Worst Case
Scenario
I
Justification Report
is Displayed
*NOTE: The chemical's file name
and substance ID are unique names
that the user enters. The chemical's
file name is limited to 8 characters.
The program will take up to 240
characters for^he chemical's
substance ID.
64
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from OncoLogic® Fibers
Justification Report
INPUTS:
Chemical file name = Fiber) High density charge = Unk
Substance Id = Fiber!
Additional properties: Water soluble = No
Durability •/ Diameter = 0.1 - 0.5 microns
Moieties = none Median(s) = 0
Manufacturing process = Crystallization Length = 1-3 microns
Scenario evaluation = Standard Aspect ratio = 0
Justification Report is saved in ONCO dir. as ASCII file as "Chemical file name.JST
RESULTS:
SUMMARY:
Code Number Fiber)
Substance Id: Fiber)
The final level of this fiber-type substance is HIGH.
JUSTIFICATION:
STANDARD EVALUATION
The unifying concept of fiber carcinogenisis is the Stanton Hypothesis. This hypothesis
states that the dimensions of a fiber are the major criteria for establishing the concern for
its carcinogenic potential.
The STANDARD evaluation is the accepted method for determining the carcinogenic
potential of a fiber. It is based on the median diameter and length. The distribution of
dimensions is assumed to be uniform. When a range is entered, the program calculates
the median as the average of the high and low values.
Since the diameter of the fiber is equal to or greater than 0.25 microns and less than 1.5
microns, and its aspect ratio is greater than 5 and not more than 32, the initial level of
concern for carcinogenic potential of this fiber is MODERATE.
Naturally occurring fibers and synthetic fibers that are manufactured through a
crystallization process are assumed to have strong electron donor/basic sites on their
surface, since these conditions provide time for orderly build-up of surface structure. This
increases the level of concern to HIGH-MODERATE.
The fiber exhibits the following property or properties: durability. These characteristics
make minor modifications to the concern level and many are inter-related. Thus,
regardless of the number of these characteristics the fiber exhibits, the final level of
concern is increased by only one step to HIGH.
The final concern for this fiber-type substance is HIGH.
65
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Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® Model Flow Diagram - Polymers
Enter Chemical's Unique File
Name* and Substance ID *
Answer Question on Covalently
Linked Repeating Subunits
Answer Question on
Residual Monomers
Answer Questions on
Low Molecular Weight Species.
Answer Question on
Metals/Metalloids
Answer Question on
Cross-linking
Answer Question on
Reactive Functional Groups
(RFGs)
Answer Question on
Water Solubility*
/ Answer Questions on
Polyfunctionality (RFC equivalent
weight, interjunction distance)
Answer Question on
Hyperplasitc Effects
Answer Question on
Ingestion
Inputs Needed for Polymers Evaluation:
Molecular weight
Water solubility and behavior in water
Polyfunctional behavior
Hyperplastic effects
Possible Ingestion
Information on chemical structure/properties,
including presence of
Covalently-linked units
Residual monomer
Residual functional groups
Low molecular weight species
Metals or metalloids
Cross-linkages
Reactive functional groups
Internal releasable subunits
Terminal/pendant releasable subunits
* If water solubility is in ppm, convert to
percent by dividing the number by 10,000. If
water solubility is unknown, enter 0.
Answer Question on
Releasable Subunits
Justification Report is Displayed
66
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from OncoLogic® Polymers
Justification Report
INPUTS:
Chemical file name
Substance Id
Molecular weight
Covalently linked units
Residual monomers >2%
Low MW species (<500) present
Polymer reactive functional groups (RFGs)
RFGs present
Oxygen RFG
Additional RFGs present
Metals/Metalloids present
Crosslinkages present
Polymer RFGs present
Identify Polymer RFG
Oxygen RFG
Additional RFGs present
Water solubility as percent weight
Polyfunctional
Functional groups equivalent, wt.
Interjunction distance
Hyperplastic effects
Absorption into soft tissue
Ingestion possible
Internal release subunits
Terminal pendant subunits
Polymer!
Polymer substance A
1,100
Yes
No
Yes
Yes
Oxygen
Epoxide (unsubsituted)
No
No
No
Yes
Oxygen
Epoxide (unsubsituted)
No
0.2
Yes
550
Yes
No
Unknown
Yes
No
No
Justification Report is saved in ONCO directory as ASCII file as "Chemical file nameJST
RESULTS:
SUMMARY:
CODE NUMBER: polymer!
SUBSTANCE ID: polymer substance A
The final level of carcinogenicity concern for this polymer is LOW MODERATE.
Based on the reactive functional group Epoxide (unsubstttuted), the level of concern for the low
molecular weight species LOW MODERATE.
CAUTIONARY NOTES:
1. Plasticizers and other additives, if present, should be evaluated separately in the Organics
Subsystem.
2. Counterions of polymers with ionic backbones should be evaluated separately.
Continued on next page
67
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from OncoLogic® Polymers
Justification Report
Continued from previous page
JUSTIFICATION:
Because the substance consists of covalently linked repeating units and has a molecular weight
greater than or equal to 1000, the substance is classified as a high molecular weight polymer.
Since the polymer contains less than 2% residual monomer(s), the carcinogenicity concern for any
residual monomers is LOW.
The polymer contains low molecular weight species (>2% below 500), with a reactive-functional-
group-bearing sidechain. The level of carcinogenicity concern for the low molecular weight species
is based on the reactive functional group: Epoxide (unsubstituted).
The level of carcinogenicity concern for the low molecular weight species is LOW MODERATE.
The polymer is not cross-linked.
Since the percent water solubility is greater than or equal to 0.1 %, the polymer is considered to be
soluble in water.
The reactive functional group (RFG) which was used during the evaluation of the polymer is: Epoxide
(unsubstituted).
This water soluble polymer is polyfunctional. Based on the expert-assigned inherent carcinogenic
potential of the RFG(s) that you have entered and the entered information on the functional group
equivalent weight of 550 daltons, which is low enough to cause concern, and the interjunction
distance of less than ten atoms, which is within the favorable distance for potential cross-linking, the
RFG which is retained for the'evaluation of the polymer is Epoxide (unsubstituted).
Since this polymer has been demonstrated not to cause (or is not known to have caused)
inflammatory and/or hyperplastic changes, carcinogenicity concerns arising from these
pathophysiological changes can be eliminated.
The RFG which is contained in this polymer is known to be stable in solution or as an emulsion in
water. The current level of carcinogenicity concern based on the RFG is retained.
The water soluble polymer has a molecular weight less than or equal to 5,000. The polymer contains
reactive-functional-group-bearing sidechains but has not (or is not known to have) demonstrated an
ability to be absorbed and to accumulate in soft tissue. Therefore, the level of carcinogenicity
concern for this polymer is LOW MODERATE.
The final concern for this polymer is LOW MODERATE.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® Model Flow Diagram - Metals
Enter: Chemical's Unique File
Name* and Substance D'
i Chemical Radioactive, or Does
it Contain Radioactive
Metals/Metalloids? /'
No
A.
Answer Question on
Water Solubility*
Answer Question on
Crystalline Lattice
Anwer Questions on
Metals/Metalloids Present
Select: Metals Present
Is Metallized Dye Present
Enter Metal Classification
Enter Oxidation State
Enter Expected Routes of
Exposure
/' Answ er Question Organic Moiety
Justification Report is Displayed
Analysis ends
here. Program
does not evaluate
radioactive
compounds.
Inputs Needed for Metals Evaluation:
Chemical structure
Radioactivity
Presence of metallized dye or pigment
Metal classification
Oxidation state
Water solubility
Crystalline lattice present?
Routes of exposure expected
Organic moiety under physiological
conditions
* If water solubility is in ppm, convert to
percent by dividing the number by 10,000.
If water solubility is unknown, enter 0.
69
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from OncoLogic® Metals
Justification Report
INPUTS:
Chemical file name = Crystal Oxidation state = Hexavalent
Substance Id = Crystal Water solubility = Sparingly soluble
Radioactivity = No Crystalline lattice = Yes
Metals present = CrandZr Route of exposure = Inhalation
Metallized dye or pigment = No Organic moiety = No
Metal classification = Inorganic or other comp.
Justification Report is saved in ONCO directory as ASCII file as 'Chemical file name.JST
RESULTS:
Code Number crystal
Substance Id: crystal
SUMMARY:
The final level of concern for this Cr-containing inorganic or organic compound, when the
anticipated exposure is via the inhalation route, is HIGH.
JUSTIFICATION:
Since this substance contains more than one metal, Cr, Zr, the system has considered all
metals present. The level of concern and the line of reasoning are based on the metal which
provides the highest level of carcinogenicity concern. When more than one metal gives the
same highest level of concern, the line of reasoning is given for only one of the metals.
In general, virtually all Cr-containing compounds are of some carcinogenicity concern unless
they can be dearly shown to be not bioavailable. Exposure to these compounds by inhalation
or injection is of greater concern than exposure by the oral or dermal route.
The carcinogenic potential of inorganic chromium compounds is affected by their oxidation
state, crystallinity, and solubility, which affect the extent of compound uptake by cells.
Hexavalent compounds are more easily taken up by cells than trivalent; and crystalline
compounds are more easily taken up than amorphous compounds. Sparingly soluble and
insoluble compounds are more likely than soluble compounds to be retained at the site of
exposure, and thus have more of an opportunity to be taken up by the cells. Organic chromium
compounds containing a Cr-C covalent bond are treated as inorganic compounds because the
Cr-C covalent bond is expected to be easily hydrolyzed in aqueous solution.
Since the substance is a(an) inorganic or organic compound, and the oxidation state of
chromium is hexavalent, and exposure to this sparingly soluble, crystalline substance is,
expected to be by the inhalation route, the level of carcinogenicity concern is HIGH.
The final level of concern for this Cr-containing inorganic or organic compound, when the
anticipated exposure is via the inhalation route, is HIGH.
70
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Pollution Prevention (P2) Chemical Screening Assessment Framework
OncoLogic® Model Flow Diagram - Organics
New or Previous
Evaluation?
Enter Chemical's Unique
File Name*
v
Select Organic Class
Enter Chemical's Unique
Substance ID * /
Select Aromatic
Amine-related Compound/
Answer Question on /
Amine-generating Groups/
Select Aryl Rings
Is Chemical (CAS No.,
name, structure) in
Database?
Build Structure by Adding /
Groups Present Rings, /
Heteroatoms, Intercyclic /
Linkages, Subunits /
V
Justification Report is
Displayed
Inputs Needed for Organics Evaluation:
Organic chemical class
CAS number/Chemical name (if listed)
Molecular structure, including presence of:
Rings
Functional groups
Linkages
Substituents
71
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from OncoLogic® Organics
Justification Report
INPUTS:
Chemical file name = Aminel
Organic class = Aromatic amine
Substance Id = Aromatic amine#1
Aromatic-related compound class = None
Amine-generating group = Yes
Aryl rings selected:
6-member rings = 1
Heteroatoms = No
Answers are correct
Structure building:
Select:
- Build
-Add
- Substituents
-Alkoxy(-OCH3)
- Amine-generating group (NO3)
- Other (Br)
RESULTS:
OCK
Justification Report is saved in ONCO directory as ASCII file as "Chemical file name.JST"
SUMMARY
Code Number Aminel
Substance Id: Aromatic Amine#1
The level of carcinogenicity concern for this compound is HIGH-MODERATE.
JUSTIFICATION:
In general, the level of carcinogenicity concern of an aromatic amine is determined
by considering the number or rings, the presence or absence of heteroatoms in the
rings; the number and position of amino groups; the nature, number and position of
other nitrogen-containing 'amine-generating groups;" and the type, number and
position of additional substituents.
Continued on next page
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from OncoLogic® Organics
Justification Report (continued)
OCH,
Continued from preceding page
Aromatic amine compounds are expected to be metabolized to N-hydroxylated/N-
acetylated derivatives which are subject to further bioactivation, producing
electrophilic reactive intermediates that are capable of interaction with cellular
nucleophiles (such as DNA) to initiate carcinogenesis.
Nitro groups of aryl compounds can be reduced by nitro reductase to amino groups
yielding aromatic amine compounds. The evaluation of this compound proceeds as
if the nitro group were a free amine group.
An aromatic compound containing one benzene ring, one amino group, and one
methyl or methoxy group ortho- to the amino group, has a carcinogenicity concern of
HIGH-MODERATE.
The additional chloro and/or bromo group(s) generally raise(s) the level of concern,
but they also impose an upper limit of HIGH-MODERATE on the concern level of the
compound. Therefore, the level of concern remains HIGH-MODERATE.
The final level of carcinogenicity concern for this compound is HIGH-MODERATE.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
ECOSAR (V. 0,99) to Estimate Aquatic Toxicity
What Does the ECOSAR Model Do?
How Does the Mode) Work?
ECOSAR (Ecological Structure
Activity Relationships) estimates the
aquatic toxicity of a chemical based
on the known aquatic toxicity of
chemicals having sJmilar chemical
structures.
ECOSAR estimates
the aquatic toxicity
of a chemical to
fish, invertebrates,
and algae.
Why Use the ECOSAR Model?
need to know
the toxicity of the chemical to
the plant and animal life in the
stream - Aquatic Toxicity,
ECOSAR is available for downloading
form the Internet on the EPA, OPPT's
New Chemicals Program web site:
httpt//www.epa.gov/opptintr/newchms
Why is Aquatic
Toxicity of a
Chemical Important?
An understanding of the
chemical's aquatic toxicity helps
the risk assessor estimate if the
release of the chemical will
adversely affect plants and
animals in the stream.
74
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Pollution Prevention (P2) Chemical Screening Assessment Framework
ECOSAR (V. 0.99) to Estimate Aquatic Toxicity
Important Note
i
The current version of
ECOSAR can not be used
to estimate toxicity of
certain chemical classes, for
example: charged dyes,
polymers, inorganics, or
organometallics.
*ClogP vs. log KOW
Most SARs in ECOSAR were
developed using KOW values
predicted using ClogP which is a
program developed by BioByte
Corp. For this reason ClogP
instead of the log KOW predicted
by EPIWIN should be entered, if
available.
BioByte Corp. can be reached at:
Ph: 909-624-5992
Internet: http://www.biobyte.com
What You Need to Use ECOSAR
for Windows (Version 0.99)
/ Knowledge of environmental
toxicology and organic chemistry
/ CAS number and/or SMILES5
notation of the chemical
/ Certain physical/chemical
properties of the chemical:
• Log KOW (ClogP*)
• Melting point
Inputs
/SMILES© notation
/Chemical name (optional)
/CAS number (optional)
/Chemical properties (if available)
• Log KOW estimated by ClogP*
• Melting point
• Measured water solubility (optional)
• Measured Log KOW (optional)
/ Predicted aquatic toxici
the chemical (in parts
million)
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
ECOSAR (V. 0.99) to Estimate Aquatic Toxicity
Data Entry and Results Screens
Be
Fnu-rSUILES:
cfcE=el][c1)C
Enter KAME
WSNmBta:
Chaniairoi
Chemical A
dWrt«5DlfinB*_}:
Either SMILES® or
CAS number must be
entered to run the
program.
VeS0B ftS«lBes
-------
Drill i
rOlll
ition Prevention (P2) Chemical Screening Assessment Frames
work
Results Page from the ECOSAR Model
SMILES c(cccc1)(d)C
CHEM Chemical A
CAS Num
ChemlDI
ChemlD2
ChemlDS
MOL FOR C7 H8
MOLWT 92.14
Log Kow 2.54 (User entered)'
Melt Pt 25.0 deg C
Wat Sol 573.1 mg/L (measured)
ECOSAR Class(es) Found
Neutral Organics
ECOSAR Class Organism
Konemann Equation Fish (guppy)
Neutral Organics Daphnid
Neutral Organics Daphnid
Neutral Organics Daphnid
Neutral Organics Daphnid
Neutral Organics Fish (saltwater)
Neutral Organics Fish
Neutral Organics Fish
Neutral Organics Green Algae
Neutral Organics Green Algae
Neutral Organics Mysid Shrimp
Neutral Organics Earthworm
Inputs:
SMILES c(cccd)(d)C
Log Kow 2.540 (ClogP)
Meas. WS 573.1
Melting Pt 25.0
Meas. Log Kow 2.730
Predicted
Duration End Pt mg/L (ppm)
14-day LC50 41.891
48-hr LC50 23.608
16-day LC50 4.063
16-day EC50 1.533
14-day LC50 41.891
96-hr LC50 6.313
96-hr LC50 21.225 .
ChV 2.983 ^
96-hr EC50 1 5.225 [Jt
ChV 2.080 V£
96-hr LC50 4.163 fis
14-day LC50 386 488 v —
ie chronic ]
ilue(ChV)for
h is 3.0 ppm.^J
Interpreting the Results from ECOSAR
Standard toxicity profile used by EPA for freshwater species (mg/L or ppm):
Acute effects Duration Endpoint
96-h LC50
48-h LC50
96-h EC50
Duration Endpoint
30-d ChV
16-d EC50 or ChV
ChV
fish
daphnid
green algae
Chronic effects
fish
daphnid
green algae
Establishing ecotoxictty concern levels: Review ACUTE values (lowest value will be most
toxic), and use the following criteria:
High = Any of the 3 values are < 1 mg/L
Moderate = Lowest of the 3 is > 1 and < 100 mg/L
Low = All 3 are > 100, or there are No Effects at Saturation (occurs when
water solubility of the chemical is higher than an effect concentration).
Determining concern concentration (CC): CC is the lowest ChV divided by an uncertainty
factor (assessment or safety factor) of 10. In order to be conservative and because the
uncertainty (or assessment) factor is one significant digit the CC will be rounded up to be one
significant digit e.g., a CC of 175 will be rounded up to 200.
77
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
78
-------
Exposure/Risk Models
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Models to Estimate
Exposure and/or Risk
Following are brief fact sheets providing information on the
models OPPT uses to estimate the risk to receptors from
exposure to chemicals released to the environment. Information
provided on each model includes:
y What exposure/risk property does the model estimate"?
y What is significant about the exposure/risk property to
exposure assessment?
y Why is knowing the exposure/risk property important?
y Why would I want to use the model7
y What do I need to run the model?
•/ What are the inputs and outputs for the model?
EXPOSURE/RISK MODELS
SEAS
ReachScan
PDM3
Dermal
SGIES
Occupational
Spreadsheets
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Screening Exposure Assessment Software (SEAS)
To Evaluate Stream Concentrations and Human PDRs
Resulting from Discharges to Surface Water
What Does the SEAS Model Do?
SEAS gives screening level estimates of
chemical concentrations in a stream, and
human potential dose rates (PDRs) from
drinking water or ingesting fish from the
water body where the chemical was
released. SEAS estimates concentrations
based on site-specific data or generic /
Standard Industrial Classification (SIC)
code-based data.
Why Use the SEAS Model?
I need to know
if the amount of a chemical
released to a surface water may
pose a health threat to humans
or the aquatic ecosystem.
Why Is Knowing the
Stream Concentration of
a Chemical Important?
Knowing the concentration of
a chemical after it is released
to surface water helps the risk
assessor estimate the dose for
someone drinking water from
that water body, or ingesting
fish from the water.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Screening Exposure Assessment Software (SEAS) to Evaluate
Stream Concentrations and Human PDRs
Resulting from Discharges to Surface Water
Inputs
y Determine if analysis of release
activity will be site-specific, generic
SIC, or for still water
y Facility and water body data are
needed for site-specific analysis
y The SIC designation that matches
your facility activity is needed for
generic SIC analysis (see SIC
codes listed on the following page)
Chemical specific data
. BCF (can be estimated by
ECOSAR)
. Percent removed during waste
water treatment (can be
estimated by the STP model)
Release activity data
y
What You Need to Use
the SEAS Model
y Chemical-specific data
y Release activity data
y Stream flow data
EITHER
y Site-specific data
• Reach number
• Receiving stream Name
OR
/ SIC code
y
Direct or Indirect discharge
Release days/year
Amount of release (mg/kg)
/ Chemical concentration in the
stream at the mean, low, and pi
flow rates
/ Estimated potential dose rates
(mg/yr) for drinking water and fish
ingestion
/ Acute and chronic dilution factors
for still waters
-------
Poliution Prevention (P2) Chemical Screening Assessment Framework
SIC Codes for 41 Industries
INDUSTRY
1 Adhesives and Sealants Manufacture
2 Auto and Other Laundries
3 Can (metal) Manufacture
4 Dyes and Pigments Manufacture
5 Electronic Components Manufacture
6 Electroplating
7 Foundries
8 Ink Formulation
9 Inorganic Chemicals Manufacture
10 Large Household Appliances and Parts
Manufacture
11 Leather Tanning and Finishing
12 Lubricant Manufacture
13 Manufacture of Photographic Equipment
and Supplies
14 Metal Finishing
15 Motor Vehicle Manufacture
16 Organic Chemicals Manufacture
17 Ore Mining and Dressing
18 Paint Formulation
19 Paper and Paperboard Mills
20 Paper Mills except Building Paper Mills
21 Paper Board Mills
22 Building Paper and Board Mills
23 Pesticides Manufacture
24 Petroleum Refining
25 Photographic Processing
26 Plastic Products Manufacture
27 Plastic Resins and Synthetic Fabrics
28 POTWs (Industrial)
29 POTWs (All Facilities)
30 Primary Metal Forming Manufacture
31 Printing
32 Pulp Mills
33 Rubber Products Manufacture
34 Soaps, Detergents, etc. Manufacture
35 Steam Electric Power Plants
36 Textile Dyeing and Finishing (Carpets)
37 Textile Dyeing and Finishing (Knit Goods)
38 Textile Dyeing and Finishing (Wool Goods)
39 Textile Dyeing and Finishing (Woven Goods)
40 Textile Dyeing and Finishing (Knit, Wool,
and Woven Goods)
41 Yam and Thread Mills
Standard Industrial Classification
(SIC) Code(s)
2891
7211,7213-7219,7542
3411
2865
3674, 3679
3471
332, 336
2983
281
3631-3633, 3639. 3431, 3469
3111
2911,2992
7221,7333,7395,7819
3411-62, 3465-71, 3482-3599, 3613-23, 3629,
3634-6, 3643-51, 3661-71, 3673, 3676-8, 3693^,
3699, 3711-3841, 3851, 3873-999
3711,3713
2865, 2869
101-109
2851
2621,2631,2661
2621
2631
2661
2819, 2869, 2879
2911
7221,7333,7395,7819
3079
2821,2823,2824
4952
4952
3315-17, 3351-57, 3463, 3497
271-277
2611
3011,3021,3031,3041
2841-44
4911
2271-72, 2279
225, 2292
2231
2261-62, 2269
2231,2250,2269,2292
2281-84
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the SEAS Model
Site-Specific Human and Aquatic Exposures to Surface Water Releases
INPUTS:
Release ID
#1
Release activity
Manufacturing
Facility name
ABODE
Facility location
Cmalltnum KIV
ornaiROwn, IN i
Name of receiving water
Little Genesee Cr.
Reach number
05010001025
Facility on reach?
Yes
Discharge type
Direct
NPDES
NY1111111
Data source
Other (SIDS)
Percent removal (from STP
Model)
50%
Flow data (from ReachScan):
-Harmonic mean flow
202.80 MLD
-7Q1 Glow flow
30.50 MLD
-Plant effluent flow
1.4 MLD
BCR (from ECOSAR Model)
93.3
Water ingested per day"
2L/day
Fish ingested per day"
16.9 g/day
Release (kg/site/day)
200kg
Release days per year
300
Remark
COC*"=100ppb
CCOC from ECOSAR1
^owvs iiuiii twwortrvy
Note: COC is not a required
input
* BCF is necessary to calculate
fi^h inn^oHrtri PFiR hi ft nnt
Il9ll III^CoLHJlI i L/rx, UUl MUt
drinking water PDR.
"Default values from U.S. EPA.
Exposure Factors Handbook
(revision due out Feb. 1 998).
*~COC is needed if considering
risks to aquatic life.
RESULTS:
INITIAL REVIEW EXPOSURE REPORT Page 1 of
CASE NUMBER(S):
Site-Specific Human and Aquatic Exposures to Surface Water Releases
RELEASE IDfr. 1
RELEASE ACTMTY:(X) MFC ( )PRO ( )IND USE ( )COMM USE ( )CONS USE
Facility Name: ABCDE Company
Facility Location: Smalltown, NY
Receiving Stream Name: Little Genesee Cr.
Reach Number 05010001025
Facility on Reach? [X] Yes [ ] No
Discharge Type: [X] Direct [ ] Indirect
NPDES Permit #: NY1 1 1 1 1 1 1 (for indirects, use POTW permit #)
Data Source: ] Task 73
] IFD
] Submitter
] Contractor
] Region/State
fX] Other SIDS
Removal in Wastewater Treatment : 50.000%
Plant Effluent Row (MLD) : 1 .4
Release (kg/site/day) : 200.00 100.000
(before treatment) (after treatment)
Release days/yr : 300
ESTIMATED PDRs (mg/yr)
FLOW TYPE STREAM FLOW (MLD) STREAM CONC (ug/L) DRINKING H20 FISH INGEST*
MEAN 202.80 493.10 295.86 233.25
LOW 30.50 3278.69
PLANT 1.40 7.14E+04
•Where: Stream cone. = [(release after treatment) X (1 000)] / (stream flow)
Drinking H20 PDR = (mean stream cone.) X (water ingested) X
[(release days/yr) X (0.001)]
Fish Ingestion PDR = (mean stream cone.) X (Bio Concentration Factor) X
(fish ingested/day) X (release days/yr) X (1.0E-06)
REMARKS: COC = 100ppb
1 CFS = 2.4465 MLD 1 MGD = 3.7854 MLD
Rjl
O4
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the SEAS Model
SIC-Code Based Human and Aquatic Exposures to Surface Water Releases
INPUTS:
Release ID
#1
Release activity
Manufacturing
Q/f* rw/A Hocrfintinn /coo
Of O LrL/UC? UC7OU IfJUUI 1 ^OCC
list on page 83)
Industrial POTWs
Percent removal (from STP
Model)
90-99%
BCF* (from ECOSAR model)
1111
Release (kg/site/day)
22-28 kg/day
Release days per year
78-112
Water ingested per day**
2L/day
Fish ingested per day**
16.9g/day
Remark
COC*** = 100ppb
(COG from ECOSAR)
Note: COC is not a
necessary input
* BCF is necessary to
calculate fish ingestion PDR,
but not drinking water PDR.
"Default values obtained
from U.S. EPA Exposure
Factors Handbook (revision
due out early 1998).
***COC is needed if
considering risks to aquatic
life.
RESULTS:
INITIAL REVIEW EXPOSURE REPORT Page 1 of
CASE NUMBER(S):
SIC-Code Based Human and Aquatic Exposures to Surface Water Releases
RELEASE IDft 1
RELEASE ACTIVITY: (X) MFG ( )PRO ( )IND USE ( )COMM USE ( )CONS USE
RELEASE ACTIVITY CODE(S) : 4952
SIC CODE DESCRIPTION : POTWs (Indus., includes POTWs which receive ind. disch.)
Removal in Wastewater Treatment : 90.000 - 99.000%
Bio Concentration Factor 1 1 1 1 .00
Plant Effluent Flow* (MLD) : 1 .000
Release (kg/site/day) : 22.000-28.000 2.8
(before treatment) (after treatment)
Release days/yr: 78-112
Water ingested (liters/day): 2.000
Fish consumed (grams/day): 16.9
PLANT | % | STREAM FLOW (MLD) | STREAM CONC (ug/L) | HUMAN PDRs (MG/YR)
TYPE | TILE | MEAN LOW [MEAN LOW | WATER FISH*
All 50 824.23 78.74 3.40 35.56 0.76 7.14
All 10 112.79 7.57 24.82 369.88 5.56 52.20
•Where: Stream cone. = [(release after treatment) X (1000)] / (stream flow)
Drinking H20 PDR = (mean stream cone.) X (water ingested) X
[(release days/yr) X (0.001)]
Fish Ingestion PDR =(mean stream cone.) X (Bio Concentration Factor) X
(fish ingested/day) X (release days/yr) X (1.0E-06)
REMARKS: COC = 100ppb
1 CFS = 2.4465 MLD 1 MGD = 3.7854 MLD
NOTES
*Plant effluent flow is not an input The reported value is the flow rate the program uses from the standard
scenario for this particular industry (industrial POTWs).
85
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the SEAS Model
Aquatic Exposures From Releases to Lakes, Bays, Estuaries, Oceans
INPUTS:
Release ID
#1
Release activity
Manufacturing
Facility name
Test Company
Facility location
Anywhere, NJ
Name of receiving water
Atlantic Ocean
Reach number
02020202020
Facility on reach?
Yes
Discharge type
Direct
NPDES
NJ1111111
. Data source
Task 73
Percent removal (from STP
Model)
90-99%
Flow data (from ReachScan
Model):
-Plant effluent flow
200 MLD
Release (kg/site/day)
15-22 kg
Release days per year
100-113
BCF* (from ECOSAR Model)
1122
Dilution factors (from
ReachScan Model):
-Acute =10
-Chronic = 14
Fish ingested per day**
16.9g/day
* BCF is necessary to
calculate fish ingestion PDR.
"Default values obtained
from U.S. EPA Exposure
Factors Handbook (revision
due out Feb. 1998).
RESULTS:
INITIAL REVIEW EXPOSURE REPORT Page 1 of
CASE NUMBER(S):
Aquatic Exposures from Releases to Lakes, Bays, Estuaries, and Oceans
RELEASE IDfc 1
RELEASE ACTIVITY: (X)MFG ( )PRO ( )IND USE ( )COMM USE ( )CONS USE
Facility Name: Test Company
Facility Location: Anywhere, NJ
Receiving Water Name: Atlantic Ocean
Reach Number 02020202020
Facility on Reach? [X] Yes [ ] No
Discharge Type: [X] Direct [ ] Indirect
NPDES Permit #: NJ1 1 1 1 1 1 1 (for indirects, use POTW permit #)
Data Source: [X] Task 73
[ 1IFD
[ ] Submitter
[ ] Contractor
[ ] Region/State
[ ] Other
Removal in Wastewater Treatment: 90.000% - 99.000%
Plant Effluent Flow (MLD): 200.000
Release (kg/site/day): 15.000-22.000 2.200
(before treatment) (after treatment)
Bio Concentration Factor 1 122.000
Fish ingested (grams/day): 16.900
Release days/y r. 1 00 - 1 1 3
| MIXING ZONE | SURFACE WATER | FISH INGEST |
| DILUTION FACTOR | WATER (ug/L)* | PDR* I
| ACUTE | 10.00 | 1.10 | 2.36 |
| CHRONIC | 14.00 | 0.79 | 1.68 |
•Where, SURFACE WATER CONG. = [pollutant loading after treatment/
Plant effluent flow (MLD)] * 1000/Critical dilution factor)
FISH INGESTION PDR = (mean stream cone) X (Bio Concentration Factor) X
(fish ingested/day) X (release days/yr) X (1 .0 E-6)
REMARKS:
1MGD = 3.7854 MLD
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
SEAS Model Flow Diagram
Enter: Site Data
and Release Data
Select: SIC
Code Analysis
Select: Site-
Specific Analysis
: Still Waters (Lakes, Bays
Estuaries, Oceans) Analysis
Select
Appropriate
SIC Code*
Input:
Facility Name
Facility Location
Receiving Stream Name
Reach Number
Facility on Reach? Yes/No
Direct/Indirect Discharge
NPDES Nuirtber
Data Source
*S/C codes for the
41 industrial
activities are
provided in the
description of the
SEAS model, on
page 83 of this
document.
i
Enter:
Percent Removal in Wastew ater Treatment
Amount Released Before Treatment (mg/kg/day)
Release Days per Year /
BCF
Water Consumption Rate (L/day) /
Fish Consumption Rate (g/day) /
I
Enter:
Stream Flow Data (MLD)
Site-Specific Inputs:
Harmonic Mean
Low Flow
Plant Row
/ Still Waters Inputs:
Dilution Factors:
Chronic and Acute
Ingestion Rates: /
87
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
ReachScan to Evaluate Impact of Surface Water
Discharges to Drinking Water
What Is ReachScan?
It's a model
that estimates a chemical's
concentration downstream from
the point of discharge, and reports
drinking water utilities that have
intakes downstream from
the discharge point.
What Does the ReachScan Model Do?
ReachScan reports the names
of downstream water utilities,
their distance from the
discharging facility, the number
of people those water utilities
serve, as well as stream
concentrations of the chemical
discharged at given distances
downstream.
Why Use ReachScan?
ReachScan estimates stream concentration of a facility's
discharged chemical at a downstream drinking water
utility's intake by one of two methods:
(1) simple dilution, or
(2) accounting for fate processes (degradation).
It can also search for facilities that are up or downstream
from a specified facility, water utility, or reach (specific
river/stream segment).
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
ReachScan to Evaluate Impact of Surface Water
Discharges to Drinking Water
Why Do I Need ReachScan?
need to know what the
stream concentration will be of a
chemical discharged from my
facility at the point where a
downstream drinking water utility^
will use the water.
Inputs
y Facility information for the point at which the discharge enters the surface
water, including: National Pollutant Discharge Elimination System (NPDES)
number, name, SIC code, or reach number
/ Distance up or downstream to be considered
>/ Amount of chemical released to stream after treatment (mg/kg/day)
y Chemical properties (molecular weight, solubility, vapor pressure, sorption
coefficient (Koc), and half-life)
/ If using PDM3: plant effluent flow, release days, and concentration of
concern
Outputs
/Endangered species in the county
PDM3 results (if assessed)
/Downstream drinking water utility or facility
• Chemical concentration at that point
Population served by water utility
Distance downstream (km)
flow at that point
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the ReachScan Model
INPUTS:
Hydrologic Region = 02
Search by NPDES Number
NPDES Number = PA0027031
Search Query
Distance of search (KM) = 100
Downstream
Utility (drinking water utility)
Endangered Species = Yes
Concentration Parameters
Loading - amount released after
treatment (kg/day) = 300
Consider Environmental Effects
Flow type* = Mean
Environmental Effects Data
Chemical name (optional)
Test chemical
Molecular weight (g/mol)
150**
Water solubility (ppm)
100**
Vapor pressure (mm-Hg)
1.0-'**
Sorption coefficient
1000**
Half-life due to degradation (hrs)
336
Suspended solids cone, ppm)
15.0**
Environmental Effects / PDM
Analysis :
Downstream cone, at every
10 KM
Dischargers effluent flow =
5.0 MLD
Number of release days =
365 days/yr
Cone, of concern —
10.0ppb(orug/L)
* Mean flow is selected for drinking
water concerns; Low flow for
aquatic life concerns.
"•Program defaults were used to
run the model, however data may
be entered in place of defaults.
RESULTS:
ReachScan Report Page 1 of
REGION Region 02
CALC PARAMETERS 3.000E+02 kg | Env. Effects : Y | Mean
SEARCH PARAMETERS Downstream | Utility | 100.00km
SIC Facility Name NPDES Reach #
4952 WEST CHESTER BOROUGH-GOOSE CRE PA0027031 02040205007
MEAN
REACH H FLOW VEL KM DN POP V
UTILITY NAME NUMBER C (MLD) (M/S) STREAM SERVED C
WILMINGTON WATER CO02040205006 Y 1252.37 0.47 30.6 140000 V
02040205005 2127.21 0.47 37.6 0
02040204060 2139.9 0.47 39.0 0
02040204050 47681.18 1.12 59.4 0
02040204052 N/A N/A LEVO 0
02040204051 N/A N/A LEVO 0
02040204046 48284.90 1.12 66.2 0
02040204048 N/A N/A LEVO 0
02040204047 N/A N/A LEVO 0
02040204042 48338.91 1.127 2.8 0
02040204044 N/A N/A LEVO 0
02040204043 N/A N/A LEVO 0
02040204039 48510.39 1.13 74.1 0
02040204040 N/A N/A LEVO 0
02040204036 48590.89 1.13 83.9 0
02040204037 N/A N/A LEVO 0
02040204033 48852.24 1.13 87.9 0
02040204034 N/A N/A LEVO 0
02040204029 48912.95 1.13 95.3 0
02040204031 N/A N/A LEVO 0
02040204030 N/A N/A LEVO 0
1
km Up
Reach
3.86
CONC
(M9/L)
2.31 E+02
1.35E+02
1.34E+02
6.10E+00
N/A
N/A
6.00E+00
N/A
N/A
5.97+00
N/A
N/A
5.95E+00
N/A
5.91 E+00
N/A
5.87E+00
N/A
5.84E+00
N/A
N/A
TOT SEARCH DIST. FINAL REACH TOT TIME OF TRAVEL FINAL CONCENTRATION
100.00 KM 02040204025 38.88 HOURS 5.75E+00 uG/L
5/15/97 ReachScan: Environmental Parameters used in search:
Chemical Name: Test Chemical
Molecular Weight (g / mol) 1 .50E+02
Water Solubility (ppm) 1 .OOE+02
Vapor Pressure (mm / hg) 1 .OOE-07
Sorption Coefficient 1.00E+03
Chemical Half-Life due to Degradation (hours) 3.36E+02
Suspended Solids Concentration (ppm) 1 .50E+01
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Print Outs from the ReachScan Model
ReachScan (RDM) Report
REGION Region 02
CALC PARAMETERS
1.000E+03kg
SEARCH PARAMETERS Downstream
PDM PARAMETERS
SIC Facility Name
1.00ug
4952 WEST CHESTER BOROUGH-GOOSE
MNFLO
REACH # (MLD)
02040205006 897.68
02040205006 897.68
02040205006 897.68
02040204050 47681.10
02040204050 47681.10
02040204046 48284.72
02040204042 48338.83
02040204036 48590.81
02040204029 48912.87
02040204025 49541.05
LWFLO
(MLD)
366.90
366.90
366.90
6999.61
6999.61
7033.32
7036.17
7048.94
7067.56
7104.90
| Env. Effects :
| Utility
| 365.00 days
CRE
LOADING
kg
3.80850E-01
3.80850E-01
3.80850E-01
1.32574E-02
1.32574E-02
3.68709E-03
1.05845E-03
1.30875E-04
1.53253E-05
2.82970E-06
Page
Y|
I
I
NPDES
1of1
Mean
100.00 km
5.000E-KJO MLD
Reach
km Up
Reach
PA0027031 02040205007 3.86
% YEAR DAYS/YR
11.00
11.00
11.00
0.00
0.00
0.00
* **
* **
* **
* **
40.15
40.15
40.15
0.00
0.00
0.00
* **
* **
*.**
* **
KMDN
STREAM
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
100.00
Endangered Species Report
County
Inventory Name
Scientific Name
Common Name
Group Name
Family
Status
Proposed Date
Critical Habit
County
Inventory Name
Scientific Name
Common Name
Group Name
Family
Status
Proposed Date
Critical Habit
: Chester
State
State FIPS
County FIPS
PA
42
029
SQUIRREL, DELMARVA PENINSULA FOX
Stiurus niger cinereus
Delmarva Peninsula Fox Squirrel
Mammal
Stiuridae
EXN
Chester
BAT, INDIANA
Myotis sodalis
Indiana bat
Mammal
VesperSfionidae
ECN
75-12-16
17.95(a)
Order
Action
ESPP
Order
Action
ESPP
: Rodentia
: 1
: N
State
State FIPS
County FIPS
: Chiroptera
: C
: N
PA
42
029
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
ReachScan Model Flow Diagram
Select:
Region*
View
Endangered
Species
Select
Method for Search:
LNPDESNo.
2. Facility Name
3. SIC Code
4. Water Utility Name
5. Reach No.
Print
Endangered
Species Report
Adjust Search Query
/ to Search by:
Distance Up or Downstream
Facility or Water Utility
Enter
Loading (Rel. after Treatment)
(kg/day)
Environmental Fate **
Flow (mean/low)'
When you select
"Consider
Env. Effects"
you'll go into the
PDM model.
Consider
Env. Effects
Run PDM
Analysis
U.S.G.S. Hydrologic Region of the U.S. A map of the Regions is included in Case Study B, Appendix A.
If "No" is chosen, the model will calculate concentrations using default values, and predicted concentrations
may be higher than the actual value.
For drinking water concerns, select mean flow; for aquatic life concerns, select low flow.
93
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
94
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Probabilistic Dilution Model (PDM3) to Evaluate COC
Exceedences by Discharges to Surface Water
What Is PDM3?
It's a screening-level
model that estimates chemical
concentration in a stream and can be
used with either detailed site-specific
data, or more general Standard
Industrial Classification (SIC) code-y
based information.
What Does the PDM3 Model Do?
PDM3 estimates how
many days per year a
chemical discharged in a
plant's effluent will
exceed a concentration
of concern in the
receiving water.
What Is a Concern Concentration (CC)?
A CC is a concentration
level, usually reported in parts per
billion (ppb) or parts per million
(ppm), which is based on
ecotoxicity data. Harm to the
aquatic environment is more
likely to occur if the CC is
exceeded.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Probabilistic Dilution Model (PDM3) to Evaluate CC
Exceedences by Discharges to Surface Water
Why Use PDM3?
I need to know if the amount
of chemical discharged to a
stream will result in stream
concentrations that may
adversely affect aquatic
organisms.
Inputs
Site-specific
/ Reach number
/ Effluent (plant) flow (MLD)
/ Release days per year
/ Loading - amount released
after treatment (kg/day)
/ CC
What You Need to Use RDM3
y PDM3 User's Manual
/ Inputs required for type of
analysis to be conducted (see
below), or
/ ECOSAR program - optional
(can be used to derive concern
concentration CC)
SIC Code-based
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the PDM3 Model
Site Specific Analysis
INPUTS:
Option
Site specific
Reach#
02040205007
Effluent (plant) flow (MLD)
1.4
Release days per yr = 300
Loading (amount released
after treatment) (kg/day)
100
COC (from ECOSAR)
100 ppb
RESULTS:
PDM3 Option(1)-Site specific analysis -
Estimated flows from Gage file
Reach Number
02040205007
Stream Flow (MLD)
Mean : 349.564
Low : 45.145
Effluent Flow: 1.4
# Release Days: 300
Load(kg/site/d): 100
COC Percent of Days/yr
(ug/I) yr exceeded exceeded
100.00000 69.09
252.19
The PDM3 model
provides stream flow
data based on the
Reach number
entered.
Stream
concentrations
will exceed the
CC for 253 days
per year.
Enter stream concentration of concern (ug/l) or other commands to alter
input values or display functions.
F1:HELP
F2:Print/Save Results
F10:Retum to Main Menu
SIC Code Based Analysis
INPUTS:
Option
SIC code based
Analysis choice
High end case*
SIC code
POTWs Industrial
Release days per yr
365
Loading (amount released
after treatment) (kg/day)
75
COC (from ECOSAR)
10000 ppb
•High-end case exposure
is defined on the following
page of this manual.
RESULTS:
PDM3 Option(2)-SIC Code Higf
for Facility in POTWs (Industrie
# Release Days: 365
Load(kg/site/d): 75
i-end Analysis -
) (4952)
COC Percent of Days/yr
(ug/I) yr exceeded exceeded
10000.00 60.63 221.31
X-
^Stream
concentn
will excee
days per
I Enter stream concentration of concern (ug/l) or other commands to after II
input values or display functions. [I
F1 :HELP F2:Print/Save Results F1 0:Retum to Main Menu
N
rtions
;d the
!2
year.^
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
PDM3 Model Flow Diagram
Select Industry
for Analysis
Enter.
Release Days
per Year
Enter
Loading (Release After
Treatment) (kg/day) /
Enter
Concentration of
Concern(ppb)
Run Model
Print and Save
RESULTS
*What is "High-end" Case
Exposure?
EPA's Guidelines for Exposure
Assessment (1992) defines "high-
end" exposure as a plausible
estimate of an individual exposure
or dose for those persons at the
upper end of an exposure or dose
distribution, above the 90th
percentile, but no higher than the
individual in the population who has
the highest exposure.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
SCIES to Estimate
Consumer Inhalation Exposure
What Is SCIES?
SCIES is
the Screening
Consumer inhalation
Exposure Software
What Does the SCIES Model Do?
^B^VHM^^B
SCIES estimates indoor air
concentrations of eleven
chemical products in the
room of use and in another
room of the house.
Why Use the SCIES Model?
I need to know how much of
the chemical may be inhaled
by a person using the product,
or by a person within the same
building where the product is
being used (called potential
dose rate or POP).
Eleven Chemical Products
/All-purpose liquid cleaner
•/ Machine wash laundry detergent (liquid)
/ Liquid fabric softener (semivoiatile)
/ Liquid fabric softener (volatile)
/Vinyl upholstery cleaner
/ Floor wax / polish
/ Fabric protector
•/ Aerosol paints / clear coatings
/ Latex paint
y Oil-based paint
•/ Solid air freshener
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
SCIES to Estimate
Consumer Inhalation Exposure
What You Need to
Use SCIES
Chemical Information
•/Weight fraction
/ Molecular weight
y Vapor pressure
Use Scenario Information
-/ Room of use
/ Start time of use
Optional for Using SCIES
/ MPBPVP® program - optional
(can be used to estimate
vapor pressure)
/ SMILECAS data base -
optional (can be used to
translate chemical structure
into the required notation for
the MPBPVP program)
Potential dose rate for
person using product (user)
•/ Potential dose rate for
person not using product
(non-user)
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
SCIES Model Flow Diagram
Select:
Product Category
Adjust Defaults
(if necessary)
Select
Input Chemical
Properties
Enter MW, VP,
Wt Fraction
Select:
Return to Defaults
Menu
Select:
Room for Use of
Product
Adjust Starting
Time
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the SCIES Model
INPUTS:
Scenario
All-purpose
liquid
cleaner
Chemical properties
Molecular
weight (g/mole)
17
Vapor pressure
(torr)
10
Weight fraction of
chemical in product
0.25
Room of use
Bathroom
Start time of use
0700 (7 am)
RESULTS:
Ail-Purpose Liquid Cleaner with Ammonia
Product
category
entered
Annual Frequency of Use
Mass of Product
Duration of Use
Zone 1 Volume
Whole House Volume
House Air Exchange Rate
User Inhalation Rate
Non-User Inhalation Rate
Molecular Weight
Vapor Pressure
Weight Fraction
Starting Time
OUTPUT SUMMARY
Evaporation Time
Release Time
Duration Following Each Use
Interval Between Uses
156 Events/Year
94.000 grams
0.144 hours
20.000 cubic meters
292.000 cubic meters
0.200 air exchanges/hr
1.300 cubic meter/hr (during use)
1.100 cubic meter/hr (& user after use)
17.000 g/mole
10.000 torr
0.250
7:00 AM
1.076 hours
1.076 hours (Evaporation Time)
56.010 hours
56.154 hours
User Potential Dose Rate From Inhalation
Non-User Potential Dose Rate From Inhalation
1.83414E+05mg/yr
7.97573E+04 mg/yr
Concentration in Zone of Release
During period of use
During period after use
Concentration in Zone 2
During period of use
During period after use
Average (mg/m3) Peak (mg/m3)
152.108
19.378
0.331
6.259
Concentration to which User and Non-User are exposed
Person Using Product (user) 18.963
Person Not Using Product (non-user) 8.277
479.830
997.398
1.499
51.757
997.398
348.425
HOURLY ACTIVITY PATTERN
User
Non-Use
Hour
1111113333333674227444
111111134542467422744411
03 06A 09 12 15 18 21 24
/Meanings of
^ the room
codes are
listed below.
START HOUR
Room of Use: Bathroom
These codes represent rooms in the building where the product may be used:
1: bedroom 4: living room 7: out
2: kitchen 5: utility room
3: bathroom 6: car
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Dermal - Consumer Dermal Exposure
What Does the Dermal Model Do?
Dermal estimates the
predicted Lifetime Average
Daily Dose (LADD) Rate.
Average Daily Dose (ADD),
and Acute Potential Dose
Rate (APDR), for an individual
from Dermal contact with
chemicals in consumer
products.
Why Use Dermal?
I need to know
if the amount of a chemical in~a
consumer product could pose a
health threat to consumers from
contact with the person's skir
Why Is Knowing the Potential
for Dermal Contact Important?
Knowing the likely dermal dose that
may occur from using a consumer
product helps the risk assessor
evaluate the safety of a product prior to
its manufacture and use.
Important Note
The Windows version of the
Dermal model has been
developed and will replace the
DOS version. This section
presents the Windows version.
which will be available in fall
1998.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Dermal - Consumer Dermal Exposure
What You Need to Use Dermal
/ Information on the consumer product
in which the chemical will be used
/ Weight fraction of the target
chemical in the consumer
product
Inputs
•S Appropriate consumer scenario of the 6
available selections, including create your own
scenario
/ Population potentially affected
/ Weight fraction of chemical in consumer
product
create your own Dermal exposure scenario,
you'll need the following data
. Frequency of use (total body or hands only)
. Surface area (totaJ body and hands)
. Molecular weight (optional
. Amount retained or adsorbed to skin
Important Note
—-—m
The HELP screen explains the
default values used by the model
and provides background on the
concepts used.
•/ Predicted Lifetime Average
Daily Dose (LADD) Rate
/ Average Daily Dose (ADD)
Acute Potential Dose Rat
m
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from the
Dermal Model (Windows Version)
INPUTS:
Scenario
Product
directly applied
to skin
(dermal)
Product
Bar soap
Weight fractions
Median
0.005
High end
0.0075
RESULTS:
Consumer Dermal Exposure Estimates
PMN: Unknown
Scenario: Bar Soap
Years of Use (years)
SA/BW-Body(cm2/kg)
SA/BW- Hands (cm2/kg)
Frequency of Use (events/yr)
Frequency of Use Hands (events/yr)
| Exposure Units
j
Cancer
LADD (mg/kg-day)
LADD (meq/kg-day)
Results
0.002695
Not Available
Product: Unknown
Population: Adult
75 (does not apply to APDR)
284
15.6
324.5
730
Descriptor AT (days)
"what if 2.738e+04
"what if Not Available
Chronic Non-Cancer
ADD (mg/kg-day)
ADD (meq/kg-day)
Acute
i APDR (mg/kg-day)
r APDR (nieq/kg-dayy
0.002695
Not Available
0.004492
Not Available
"what if 2.7386+04 ;
"what if Not Available
i
"whatif 1
"what if Not Available
LADD - Lifetime Average Daily Dose, reported in mg/kg-day or in milliequivalents/kg-day.
ADD - Average Daily Dose, units as LADD
APDR - Acute Potential Dose Rate, units as LADD
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Dermal Model Flow Diagram
Product
Applied to
Surface:
General
Purpose
Cleaner,
Latex Paint
Product
Added
to Water
Laundry
Detergent
Product
Directly
Contacting
Skin:
Bar Soap,
Used Motor
Oil
User
Defined
Scenario
Enter Scenario Data
and Adjust Defaults
(if necessary)
Enter Dermal Inputs
and Adjust Defaults
(if necessary)
/Enter Weight Fraction
in Product (Median
and High End)
Submit Data
for Calculation
RESULTS are
Displayed
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Spreadsheet to Estimate Worker Exposures
What Do These Models Do?
These spreadsheets estimate potential
worker exposure to:
/ vapors inhaled during the filling of
containers such as drums with liquids
or during activities near open pools of
liquids;
/ dust inhaled and/or hand contact with
components of dye mixtures used in
textile dyeing operations; and
y solvent vapors inhaled during
degreasing operations.
When Can the Models Be Used?
The transfer/open surface model can be used
to estimate exposure for a variety of worker
activities in variety of industrial settings.
including:
•/ Filling tanks or drums with liquids
/Working near an open pool of liquid; and
/ Sampling liquids.
The other models can be used in specific
industrial settings, including:
/Textile dyeing; and
/ Degreasing operations
How Do the Models Work?
The spreadsheets, developed to run in Lotus'!23 software, work by combining:
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Spreadsheet to Estimate Worker Inhalation Exposure to
Vapors from Sampling, Transfer (Filling) Operations and
Open Surfaces (Pools) of Liquids
What You Need to Use These Worker
Exposure Spreadsheets
y Chemical specific information
y Information on operation in which
chemical will be used
/ Experience using Lotus spreadsheets
(Windows versions)
Required Inputs Cell No.
y Molecular weight C6
y Pure vapor pressure (torr) or
partial pressure C7
y Operations hours/day C8
y Worker exposure hours/day C9
Optional Inputs
(default values available) Cell No.
y Container volumes C11-C14
y Fill rates C18-C21
y Mixing factors C25-C26
y Inhalation rate C32
y Wind speed C15
y Saturation factors C22-C24
y Ventilation rates C27-C31
y Temperature C36
Outputs
Inhalation potential dose rate (PDR)
(mg/day, "typical" and "worst case")
V Vapor generation rates (g/sec and
and "worst
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from
Spreadsheet to Estimate Worker Inhalation Exposure to
Vapors from Sampling, Transfer (Filling) Operations and
Open Surfaces (Pools) of Liquids
INPUTS Cell No.
Molecular weight 250 C6
Vapor pressure 0.1 torr C7
Hrs/day operations 6 C8
Hrs/day worker exposure 6 C9
Exposure and generation rates from
transfer operations can be found at cells
E44-E54, and from sampling and open
surface at cells D60-D77.
RESULTS:
WORKER EXPOSURES AND VAPOR GENERATION RATES FROM TRANSFER OPERATIONS
Inhalation Exposure Vapor Generation
l[mg/day] Cm[mg/mA3] Cv[ppm] G[g/sec]
Drumming (55 gal)
Worst Case 7.32E+02 9.76E+01 9.54E+00 2.35E-03
Typical Case 8.13E+00 1.08E+00 1.06E-01 7.85E-04
Cans/Bottles (5 gal)
Worst Case 6.62E+01 8.83E+00 8.63E-01 2.13E-04
Typical Case 7.36E-01 9.81E-02 9.59E-03 7.10E-05
Tank Truck (5,000 gal)
Worst Case 1.67E+01 2.23E+00 2.18E-01 1.42E-02
Typical Case 1.86E+00 2.48E-01 2.42E-02 1.42E-02
Tank Car (20,000 gal)
Worst Case 3.34E+01 4.46E+00 4.36E-01 2.84E-02
Typical Case 3.72E+00 4.95E-01 4.84E-02 2.84E-02
WORKER EXPOSURES AND VAPOR GENERATION RATES DUE TO SAMPLING AND OPEN SURFACE
Sampling
Worst Case
Typical Case
Open surface
Worst Case
Typical Case
Inhalation
l[mg/day]
4.47E+01
7.48E-01
1.24E+03
6.73E+02
2.38E+02
8.41 E+01
2.96E+01
1.62E+01
5.72E+00
4.12E+01
2.24E-K)1
7.93E+00
2.80E+00
9.87E-01
5.39E-01
1.91E-01
Exposure
Cm[mg/mA3]
5.96E+00
9.97E-02
1.65E+02
8.98E+01
3.17E+01
1.12E+01
3.95E+00
2.16E+00
7.63E-01
5.50E+00
2.99E+00
1.06E+00
3.74E-01
1.32E-01
7.19E-02
2.54E-02
Cv[ppm]
5.83E-01
9.75E-03
1.61 E+01
8.78E+00
3.10E+00
1.10E+00
3.86E-01
2.11E-01
7.46E-02
5.38E-01
2.93E-01
1.03E-01
3.66E-02
1.29E-02
7.03E-03
2.49E-03
AREA
A[cmA2]
7.85E+01
3.85E+01
6.58E+03
2.92E+03
7.31 E+02
1.83E+02
4.54E+01
2.03E+01
5.07E+00
6.58E+03
2.92E+03
7.31 E+02
1.83E+02
4.54E+01
2.03E+01
5.07E+00
DIAMETER
z[cm]
1.00E+01
7.00E+00
9.15E+01
6.10E+01
3.05E+01
1.53E+01
7.60E+00
5.08E+00
2.54E+00
9.15E+01
6.10E+01
3.05E+01
1.53E+01
7.60E+00
5.08E+00
2.54E+00
Q[ft3/min]
5.00E+02
3.50E+03
5.00E+02
5.00E+02
5.00E+02
5.00E+02
5.00E+02
5.00E+02
5.00E+02
3.00E+03
3.00E+03
3.00E+03
3.00E+03
3.00E+03
3.00E+03
3.00E+03
k
1.00E-01
5.00E-01
1.00E-01
1.00E-01
1.00E-01
1.00E-01
1.00E-01
1.00E-01
1.00E-01
5.00E-01
5.00E-01
5.00E-01
5.00E-01
5.00E-01
5.00E-01
5.00E-01
G[kg/day]
5.09E-02
1.70E-02
4.60E-03
1.53E-03
3.07E-01
3.07E-01
6.13E-01
6.13E-01
Vapor Generation
G(g/sec)
1.44E-04
8.42E-05
3.98E-03
2.17E-03
7.66E-04
2.71 E-04
9.52E-05
5.21 E-05
1.84E-05
3.98E-03
2.17E-03
7.66E-04
2.71 E-04
9.52E-05
5.21 E-05
1.84E-05
G(kg/day)
3.11E-03
1.82E-03
8.59E-02
4.68E-02
1.65E-02
5.85E-03
2.06E-03
1.12E-03
3.97E-04
8.59E-02
4.68E-02
1.65E-02
5.85E-03
2.06E-03
1.12E-03
3.97E-04
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Spreadsheet to Estimate Worker Exposures from
Textile Dyeing
When Can the Model Be Used?
This model can be used to estimate exposure from batch or continuous operations where less
than 54 kg of powered or liquid textile dye is weighed per day. If the dye is in liquid form and
vapor pressure exceeds 0.001 torr, the Transfer/Open Surface Model should be used.
Batch and Continuous Operations
INPUTS
y Pounds fiber/lot
y Percent formulated dye weight/fabric weight
y Percent dye strength
y Number of machines/site
y Number of shifts of operation/day
y Number of kilograms purchased/site
y Annual production/import vol. of chemical in dye
•/ Percent degree of dye exhaustion
y Number of dye weighings/lot (worst case)
y Number of dye weighings/lot (typical case)
y Liquor ratio (Batch Operations only)
y Percent wet pick-up (Continuous Operations only)
y Number of machines/machine operator
/ Number of dye weighers/shift
Important Note
Default values (found in cells R4
through R33) are available for all
input variables except annual
production or import volumes.
Each default value should be
reviewed. If actual scenario-
specific values are available for
any of these variables, they
should be entered instead of
using the default values.
Default values are presented on
the following page.
Inhalation potential dose rates
(PDRs) (mg/day, "typical" and
"worst case")
Number of facilities and worke
exposed, and number of days of
worker exposure
Dermal potential dose rates
DRs) (mg/day)
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Spreadsheet to Estimate Worker Exposures from
Textile Dyeing
Input Variables and the Default Values
INPUT VARIABLES
Cell No.
R4
R5
R6
R7
R8
R9
R10
R11
R12
R13
R14
R15
R16
R21
R22
R23
R24
R25
R26
R27
R28
R29
R30
R31
R32
R33
DEFAULTS
1000
2.5
58
4
3
1000
0
0
3
1.5
20
2
1
3600
2.5
50
1
3
1000
0
0
4
2
80
2
1
BATCH OPERATIONS
pounds fiber per lot (1000 Ibs)
% formulated dye on weight of fabric (owf) (0.1-5)
% dye strength (liq. 10-40; pdwr = 20^60)
number of machines per site (1-20 mach. with 4 typical)
number of shifts of operation/day (2 or 3)
number of kilograms purchased per site (1000 kilos)
PVorlV(inkgs)
% degree of exhaustion (60-99)
number of dye weighings per lot (worst case) (3)
number of dye weighings per lot (average case) (1 .5)
liquor ratio (12-25; typically 20)
number of machines per machine operator (2)
number of dye weighers/shift (1)
CONTINUOUS OPERATIONS
pounds fiber per lot (3600 Ibs)
% formulated dye owf (0.1-5)
% dye strength (liq. 10-40; pdwr = 20-60)
number of machines per site (1-5 mach. with 1 typical)
number of shifts of operation/day (2 or 3)
number of kilograms purchased per site (1000 kilos)
PV or IV (in kgs)
% degree of fixation (75-99)
number of dye weighings per lot (worst case) (4)
number of dye weighings per lot (average case) (2)
% wet pick-up (80-200; typically 80)
number of machine operators per machine (2)
number of dye weighers/shift (1)
111
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from Spreadsheet to
Estimate Worker Exposures from Textile Dyeing
The results presented here are based on default values (see
previous page). There were no scenario-specific inputs for this
model run.
OUTPUT
SUMMARY OF RESULTS
Cell No.
18
19
no
111
112
113
114
115
116
117
118
119
Cell No.
122
123
124
125
126
127
128
129
130
131
132
133
DEFAULTS
75
9
25
2.9175
9.8473
377-1131
150
30-89
21.09
9
25
4745.45455
DEFAULTS
6
12
2
1.9514
6.5864
325 - 975
12
46 - 209
15.13
12
2
363
BATCH OPERATIONS
total number of dye weighers
number of days exposure
number of sites
mg/day average case inhalation exposure
mg/day worst case inhalation exposure
mg/day Dermal exposure
total number of machine operators
mg/day Dermal exposure
kilograms per site-day released
number of days of release
number of sites
kilograms total releases to water
CONTINUOUS OPERATIONS
total number of dye weighers
number of days exposure
number of sites
mg/day average case inhalation exposure
mg/day worst case inhalation exposure
mg/day Dermal exposure
total number of machine operators
mg/day Dermal exposure
kilograms per site-day released
number of days of release
number of sites
kilograms total releases to water
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Spreadsheet to Estimate Worker Exposures
from Degreasing Operations
When Can the Model Be Used?
This model can be used to estimate inhalation
exposure from volatile liquid solvents used in two
types of vapor degreasing unit operations
1. Open top vapor degreasing (OTVD)
2. Conveyorized or in-line degreasing
Required Inputs Cell No.
/ Production/import
volume (kg/yr) C3
/ Molecular weight C4
Important Note
-is-
The primary default values used by the model should be
reviewed and if actual scenario- specific values are available,
these should be entered instead of using the default values.
The primary default values which should be checked include:
Small and medium batch cleaners: idling 6 hr/day, working 2
hr/day, down 16 hr/day for 260 days/yr, down 24 hr/day for 105
days/yr.
Large and very large batch cleaners: idling 2 hr/day, working 6
hr/day, down 16 hr/day for 260 days/yr; down 24 hr/day for 105
days/yr.
Convevorized In-line cleaners: idling 0 hr/day, working 8 hr/day,
down 16 hr/day for 260 days/yr; down 24 hr/day for 105 days/yr.
Estimated numbers of sites and
workers
Days per year of exposure
•/ Annual emissions in kg/yr
/ Inhalation potential dose rate
mg/d, "routine" and "boundin
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Sample Output from Spreadsheet to Estimate Worker
Exposures from Degreasing Operations
"Routine" and "bounding" Potential Dose Rate results can be found at cells
G101-G114 and H101-H114, respectively.
INPUTS: Cell No.
RESULTS:
PV=10,000,000 (kg/yr) C3
MW = 200 C4
SUMMARY OF AIR EMISSIONS FOR VAPOR DEGREASING SCENARIO
Scenario
Uncontrolled
Batch OTVD
Conveyorized
Controlled
Batch OTVD
Conveyorized
TOTAL
Small
Medium
Large
Very Large
Small
Medium
Large
Very Large
Estimated
# of Sites
94
26
12
7
5
25
39
39
32
126
410
Estimated
Release
Days/yr
260
260
260
260
260
260
260
260
260
260
Annual
Emissions
(kg/year)
7900
14500
40200
78100
49800
7100
13600
34000
66200
19900
9064000
SUMMARY OF INHALATION EXPOSURES FOR VAPOR DEGREASING SCENARIO
Scenario
Uncontrolled
Batch OTVD
Conveyorized
Controlled
Batch OTVD
Conveyorized
TOTAL
Small
Medium
Large
Very Large
Small
Medium
Large
Very Large •
Estimated
#ofWkrs
280-850
77-230
34-104
21-64
13-41
75-175
117-275
117-274
96-225
378 - 883
1200- 3100
Potential
Dose Rate
Routine
(mg/d)
1,000
2,000
5,000
11,000
11,000
600
1,000
3.000
6,000
4,320
Bounding
(mg/d)
31,000
66,000
163,000
316,000
324,000
18,400
39,800
98,000
190,000
130,000
Duration
(days/yr)
260
260
260
260
260
260
260
260
260
260
260
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Computer Requirements
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Computer Requirements
All EPIWIN Programs Require:
y IBM-compatible PC with MS Windows 3.1 or higher,
a mouse, and at least 4 MB of RAM
y 6.3 MB of hard disk space for SMILECAS
Each EPIWIN Program Requires the Following Amount
of Hard Disk Space:
0.8MB
2.6MB
2.0MB
0.8MB
0.8MB
0.8MB
0.8MB
0.8MB
MPBPVP
KOWWIN
WSKOW
PCKOCWIN
HENRYWIN
AOPW1N
BIOWIN
HYDROWIN
BCFWIN
0.8 MB
Computer Requirements for Other Models Presented Include:
STP
/ PC with MS-DOS 3.0 or higher, VGA color
monitor, and printer
y 512K of memory
y 110K megabytes of hard disk space
ReachScan
y PC with MS-DOS 3.0 or higher, color
monitor, and printer
y640K of memory
y 18 megabytes of hard disk space
OncoLogic
y 386 PC with MS-DOS 5.0 or later, a
mouse, and color monitor
y 570K of conventional RAM
y 60 megabytes of hard disk space
y A disk cache will significantly improve
performance
ECOSAR
y PC with a 640-KB memory and at least
512-KB of free memory
y Expanded memory will improve
performance
y A disk cache will significantly improve
performance
y At least 51 file handlers specified in your
CONFIG.SISfile
SEAS
y PC with Windows 3.1 or higher, SVGA
color monitor with 800 x 600 resolution,
and printer
y 4 megabytes of memory
y 8 megabytes of hard disk space
PDM3
/PC with MS-DOS 3.0 or higher, color
monitor, and printer
y 640K of memory
y 5 megabytes of hard disk space
Dermal (DOS Version)
y PC with MS-DOS 3.0 or higher
y 80K of available system memory
Dermal Windows Version has the same
requirements described for SEAS and the
Occupational Spreadsheets
SCIES
y PC with MS-DOS 3.0 or higher and color
monitor
y 512K of memory
/150K of disk space
Occupational Spreadsheets
y PC with Windows 3.1 or higher, SVGA
color monitor with 800 x 600 resolution,
and printer, Lotus123, Vers. 4.0 or higher
y 4 megabytes of memory
y 8 megabytes of hard disk space
116
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
117 f-
-------
Glossary
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Glossary of Useful Terms
7Q10 flow: Lowest 7-consecutive day average stream flow over a 10 year period
(used to assess chronic risks to aquatic live).
ADD (Average daily dose): The estimate of dose averaged over the number of years of
use/exposure to the chemical; used in assessments of risk of non-cancer chronic health
effects.
APDR (Acute potential dose rate): The estimated dose on a given day; used in
assessments of the risk of acute toxic effects.
BCF: Bioconcentration factor (BCF) is the ratio (in L/kg) of a chemical's
concentration in the tissue of an aquatic organism to its concentration in the
ambient water. BCF indicates the potential for the chemical to concentrate in lipids
(fats) of organisms.
Bioaccumulation: Accumulation of lipid soluble substances in body fat (lipids) of
aquatic organisms at concentrations higher than that of the surrounding water.
Bioconcentration: Increased body concentrations of lipid soluble substances seen as
organisms higher in the food web consume organisms that have already accumulated lipid
soluble substances from the surrounding aquatic media.
Chemical class: The general chemical group to which a chemical belongs
(e.g.. acid, base, hydrocarbon, etc.).
CC/COC: Concern concentration (or concentration of concern), reported in parts per billion
(ppb) or parts per million (ppm), providing the concentration of a chemical in a stream CC is
determined by dividing the lowest chronic toxicity value by 10. Harm to the aquatic
environment is more likely to occur if the CC is exceeded.
Direct discharge: Under NPDES permitting, the discharge of chemicals or compounds
directly to a surface water body.
Effluent: The stream flowing out of a facility or water body. The concentrations in it's flow
are used to estimate potential health effects of the discharge.
Half-life: Time required for one-half of a chemical or compound to degrade.
Harmonic mean: The number of daily flow measurements divided by the sum of the
reciprocals of the flows. A value that is more conservative than the arithmetic mean flow
value. Used to assess chronic risks to humans.
High end: A plausible estimate of an individual exposure or dose for those persons at the
upper end of an exposure or dose distribution, above the 90th percentile, but no higher than
the individual in the population who has the highest exposure.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Glossary of Useful Terms (continued)
Hydrophilic: Having an affinity for, or capable of dissolving in, water.
Influent: Stream flowing into a facility or water body.
Indirect discharge: Under NPOES permitting, unlike a direct discharger, an indirect
discharger pumps effluent to another facility that has a permit to discharge to the stream.
KOC: Organic carbon partition coefficient - the ratio of amount of a chemical adsorbed per
unit weight of organic carbon to the chemical concentration in solution at equilibrium Is an
indication of how the chemical will partition itself between the solid and solution phases of a
water-saturated or unsaturated soil.
KOW: Octanol-water partition coefficient - the ratio of a chemical's concentration in the
octanol phase to if s concentration in the aqueous phase of a two-phase octanol/water system.
LAOD (Lifetime average daily dose): The estimated dose to an individual averaged over a
lifetime of 70 years; used in assessments of carcinogenic risk.
Lipophilic: Having an affinity for, or capable of dissolving in, fat and fatty materials.
Loading: The amount of chemical that is discharged to a stream after treatment, reported in
kg/day.
Moiety(ies): Compounds formed when a larger compound is subdivided.
NPDES: National Pollutant Discharge Elimination System requires that dischargers of
chemicals to surface waters obtain a permit from EPA An NPDES permit number is a nine-
character number with the two letter State abbreviation beginning the number (e.g.,
NC0001234).
P2: Pollution prevention, i.e., concept stating that it is easier to prevent pollution than to clean
up pollution after it has occurred.
PDR(s): Potential dose rate(s) provide an estimate of possible exposure rate to receptor from
expected use, usually derived by modeling using default exposure factors.
Reach: A reach is a stream or river segment identified by EPA and assigned an 11-digit
identification number. The first two numbers indicate the hydrologic region of the United
States in which the reach is located.
SARs: Structure Activity Relationships is the concept that allows the prediction of the aquatic
toxicity of chemicals based on the similarity of their molecular structure to chemicals for which
the aquatic toxicity has been measured previously.
SIC: Standard Industrial Classification system is a four digit number that identifies the specific
industrial activity. For a complete listing of SIC codes, see Standard Industrial Classification
Manual. 1987. Supt. of Documents, U.S. Government Printing Office, Washington, DC.
119
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
120
-------
Append. A Case Studies
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
APPENDIX A
Case Studies
Case Study A - Potential Aquatic and Human
Exposures to Surface Water Discharges
from a Manufacturing Facility
Uses the Models ECOSAR, SEAS, PDM3
Case Study B - Potential Exposures to Surface Water
Discharges from a Manufacturing Facility
Uses the Models PCKOCWIN, BIOWIN,
KOWWIN, STP, and ReachScan
Case Study C - Consumer Dermal Exposure
Uses the DERMAL Model
Case Study D - Worker Inhalation Exposure
Uses the Occupational Exposure Spreadsheets
to Estimate Worker Exposure
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Case Study A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
Uses the Models ECOSAR, SEAS, PDM3
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
INTRODUCTION
The purpose of this case study is to determine the aquatic toxicity of Chemical A and to
assess potential aquatic impacts and human exposures that may occur as a result of effluent
discharges from the manufacturing facility (Company ABCDE) in Smalltown, New York. The
following models will be used to accomplish this task: ECOSAR, SEAS, and PDM3.
• ECOSAR will be used first to estimate a concern concentration for the chemical.
• SEAS will then be used to estimate the surface water concentration of the chemical.
PDM3 will be used to assess the likelihood of potential impacts.
Chemical A is a compound in the neutral organic chemical class. No significant ecological
toxicity testing has been done on Chemical A.
STEP 1. TOXICITY DETERMINATION
Because no aquatic toxicity testing has been conducted on Chemical A, ECOSAR will be
used to predict its aquatic toxicity based on structural similarities to other neutral organic
chemicals. The following physical/chemical properties will be assumed for Chemical A that
are inputs to run the ECOSAR model:
measured water solubility = 573.1 mg/L;
melting point = 25° C;
• log KOW = 2.540 (ClogP); and
measured log KQW = 2.730.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility (continued)
Running ECOSAR for Windows - After opening ECOSAR for Windows the Data Entry Screen,
is displayed. Data entered for this case study are shown in Figure A1. Figure A2 presents the
results of running the model-
Figure A1
Data Entry Screen
Ecosar Classes vO.93
EE3E3
Previous [ 6etU^|:aE^j^TQgjniBiu|^a6riate |
Enter SMILES:
Enter NAME:
CAS Number.
Chemical ID i:
Chemical ID Z:
cjcoxi|[ci)c
chemical A
Either SMILES or
CAS number must
be entered to run
the program.
C1 r
tngKw.f
573.1
2.540
Measured Lag Row: J2.730
7^
Required inputs are:
Log Kow (ClogP)
Melting point
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDYA
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
Figure A2
Results of Running ECOSAR
SMILES
CHEM
CAS Mum
ChemlDI
ChemlD2
ChemlDS
MOL FOR
MOLWT
Log Kow
Melt Pt
Wat Sol
ECOSAR Class(es)
Neutral Organics
ECOSAR Class
Konemann Equation
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
Neutral Organics
c(cccc1)(c1)C
Chemical A
C7H8
92.14
2.54 (User entered)
25degC
573.1 mg/L (measured)
Found
Organism
Fish (guppy)
Daphnid
Daphnid
Daphnid
Daphnid
Fish (saltwater)
Fish
Fish
Green Algae
Green Algae
Mysid Shrimp
Earthworm
Inputs:
Log Kow (ClogP) 2.540
Meas. WS 573.1
Melting Pt 25.0
Meas. Log Kow 2.730
Duration End Pt
14-day LC50
48-hr LC50
16-day LC50
16-day EC50
14-day LC50
96-hr LC50
96-hr LC50
ChV
96-hr EC50
ChV
96-hr LC50
14-day LC50
Predicted
mg/L (ppm)
41.89
23.61
4.06
1.53
41.89
6.31
21.23
2.98 v^
15.23 /-• u . ^
208 The chronic
4'16 value for fish is
386^49 L3-° ppm'
Note: The standard toxicity profile used by EPA for freshwater
species is:
Acute Effects:
Chronic Effects:
Fish
Daphnid
Green algal
Fish
Daphnid
96-hr LC50
48-hr LC50
96-hr EC50
Chronic Value (ChV)
ChV
Green algal ChV
A-7
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility (continued)
The next step is translating the predicted endpoints into a freshwater (FW) concern
concentration (CC). The following equation is used to calculate the FW CC. The lowest
chronic value, the predicted endpoint for Daphnid (1.53 ppm), was used. An uncertainty factor
(assessment or safety factor) of 10 was used to account for the uncertainty of laboratory to field
variation, and as a margin of safety.
(Predicted Endpoint x 1,000 conversion from ppm to ppb) / safety factor
(1.53 ppm x 1,000) /10 =153 ppb, rounded up to 200 ppb.*
*Note: The CC is rounded up to one significant digit to be conservative, and because the
safety factor is one significant digit
STEP 2. ESTIMATION OF SURFACE WATER CONCENTRATIONS
Now that a FW CC for Chemical A (200 ppb) has been established, the site-specific
release can be evaluated. Assume the following:
• Company ABCDE will discharge 200 kg/day of Chemical A for 300 days per year; and
• There will be 50 percent removal of Chemical A in wastewater treatment.
After talking to Company representatives, the assessor has determined that
• Company ABCDE discharges to the Little Genesee Creek;
• The Reach number is 05010001025;
• This particular reach has a mean flow of 202.8 million liters per day (MLD) and a low
flow of 30.5 MLD; and
• The plant effluent flow (discharge rate) from the Company ABCDE factory is 1.4 MLD.
#*
Using this information the assessor can use the SEAS model to calculate: trie concentration of
Chemical A in the Little Genesee Creek; the drinking water potential dose rate (PDR); and the
potential dose rate from ingestion offish.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility (continued)
Running SEAS - The following is a step-by-step description of how to run the SEAS model.
Figure A3 presents a flow chart on how to run the model and Figure A4 presents the results.
Once you have entered the SEAS model:
1. Select: Site-specific Aquatic and Human Exposure to Surface Water Releases;
2. Enter the facility-specific flow data, release data, and physical/chemical properties for
Chemical A; and,
3. Select: Run the model.
SEAS Results - The results of the SEAS model run indicates that the concentration of
Chemical A will be 3,279 ppb in the Little Genesee Creek during a period of low stream flow.
The estimate of the drinking water PDR was 617.28 mg/yr which equals 1.69 mg/kg/day. The
estimate of the fish ingestion Potential Dose Rate (APDR) was 486.66 mg/yr which equals 1.33
mg/kg/day.
STEP 3. ESTIMATING THE NUMBER OF DAYS PER YEAR THE CC IS EXCEEDED
The PDM model can be run to determine the number of days the stream concentration will
exceed the concern concentration (200 ppb).
Running PDM - The following is a step-by-step description of how to run the PDM model.
Figure A5 presents a flow chart on how to run the model and Figure A6 presents the model
results.
Once you have entered into the PDM model:
1. Select: Site-specific analysis;
2. Enter the Reach number 05010001025;
3. Enter the facility specific data and release information:
Effluent flow =1.4 MLD
Number of release days = 300 days/yr
Loading (release after treatment) = 100 kg/day (200 kg/day x 50% removal); and
4. Select: Run the model.
PDM Results - The results of the PDM model run indicate that the concentration of Chemical A
exceeded the CC for 240 days out of 300 release days during the operation of the Company
ABCDE plant in Smalltown, New York.
A-9
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Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
Figure A3
Running SEAS
Select Site-specific Aquatic and
Human Exposure to
Surface Water Releases
I
Enter Information on Facility
and Physical/Chemical
Properties of Chemical
Run the Model
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
Figure A4 - Results of Running SEAS
RESULTS:
INITIAL REVIEW EXPOSURE REPORT Page 1 of
CASE NUMBER(S):
Site-Specific Human and Aquatic Exposures to Surface Water Releases
RELEASE ID#: 1
RELEASE ACTMTY:(X) MFG ( )PRO ()INDUSE ( )COMM USE ( )CONS USE
Facility Name: ABODE Company
Facility Location: Smalltown, NY
Receiving Stream Name: Little Genesee Cr.
Reach Number 05010001025
Facility on Reach? [X] Yes [ ] No
Discharge Type: [X] Direct [ ] Indirect
NPDES Permit #: NY1111111 (for indirects, use POTW permit #)
Data Source: [ ] Task 73
[] IFD
[ ] Submitter
[ ] Contractor
[ ] Region/State
fX] Other SIDS
Removal in Wastewater Treatment: 50.000%
Plant Effluent Row (MLD): 1.4
Release (kg/site/day): 200.00 100.000
(before treatment) (after treatment)
Release days/yr: 300
ESTIMATED PDRs (mg/yr)
FLOW TYPE STREAM FLOW (MLD) STREAM CONG (pg/L) DRINKING H20 FISH INGEST*
MEAN 202.80 493.10 295.86 233.25
LOW 30.50 3278.69
PLANT 1.40 7.14E+04
•Where: Stream cone. = [(release after treatment) X (1000)] / (stream flow)
Drinking H20 PDR = (mean stream cone.) X (water ingested) X
[(release days/yr) X (0.001)]
Fish Ingestion PDR = (mean stream cone.) X (Bio Concentration Factor) X
(fish ingested/day) X (release days/yr) X (1 .OE-06)
REMARKS: COC = 200ppb ==^=============================
1 CFS = 2.4465 MLD 1 MGD = 3.7854 MLD
A-11 f
- '
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
Figure A5
Running PDM3
Select: Site-specific Analysis
or
SIC Code-based Analysis
Select Worst Case Analysis
or
Average Case Analysis
1
Enter Site-specific Information
Run the Model
A-12
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY A
Potential Aquatic and Human Exposures to Surface
Water Discharges from a Manufacturing Facility
Figure A6
Results of Running PDM3
PDM EXPOSURE REPORT
CASE (S):
Page _ of _
Site-Specific Probabilistic Dilution Model (PDM) Results
Hypothetical Reach
RELEASE ID#:
RELEASE ACTIVITY: (X) MFG
( ) COMM USE
( )PRO ( ) IND USE
( ) CONS USE
Facility Name: ABCDE Company
Facility Location: Smalltown, NY
Receiving Water Name: Little Genesee Cr.
Reach Number 05010001025
Facility on Reach? [X] Yes [ ] No
Discharge Type: [X] Direct [ ] Indirect
NPDES Permit #: NY1111111 (for indirects, use POTW permit #)
Removal in Wastewater Treatment: 50.000%
Mean Stream Flow (MLD): 202.8
Low Stream Flow (MLD): 30.5
Effluent Flow (MLD): 1.4
RELEASE AMOUNT CONCERN PERCENT DAYS
DAYS/YR RELEASED CONC. OF YEAR PER YEAR
{kg/site/day) (ug/L) EXCEEDED* EXCEEDED
300
100.00
200.00000
65.62
239.52
"PERCENT OF YEAR EXCEEDED" is obtained by dividing the "DAYS PER YEAR
EXCEEDED' by 365 days/yr.
REMARKS: COC = 200ppb
A-13
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
A-14
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Case Study B
Potential Exposures to Surface Water Discharges
from a Manufacturing Facility
Uses the Models PCKOCWIN, BIOWIN, KOWWIN,
STP, and ReachScan
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
A-16
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility
INTRODUCTION
The purpose of this case study is to assess potential drinking water exposures to humans
and presence of endangered species that may be exposed to discharges from a manufacturing
facility. The Hamlette Pharmaceutical Manufacturing Company (HPM) is located in
Pennsylvania. HPM wishes to use Chemical B in their manufacturing process. HPM
discharges to the local POTW, which is upstream from the intake for a downstream
community's water treatment plant. Chemical B, which could be toxic to humans at certain
concentrations, is a component of the discharge stream going to the POTW. HPM risk
assessors must estimate the potential exposure of humans to drinking water contaminated with
Chemical B as a result of effluent discharge from their manufacturing facility. The risk
assessor also wants to evaluate the potential presence of endangered species. The following
models will be used to accomplish these tasks: KOCWIN, BIOWIN, KOVWvlN, STP, and
ReachScan.
KOCWIN will be used estimate the KOC (sorption coefficient) of Chemical B;
BIOWIN will be used estimate the aquatic biodegradation rate of Chemical B;
KOWWIN will be used estimate the KOW (octanol/water partition coefficient) of
Chemical B;
STP will be used estimate the percentage of Chemical B that will be removed from the
wastewater during treatment in the POTW; and
ReachScan will then be used to calculate the stream concentration of Chemical B at
the intake pipe of the local water treatment plant
The risk assessor knows the following information about the HPM plant:
• Discharge rate = 2000 kg/day;
Number of release days/year = 150; and
• Discharges are pumped to the West Chester Borough-Goose Creek POTW.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
The risk assessor telephones the POTW manager and receives the following information:
• NPDES number of the POTW = PA0027031; and
Hydrologic region = 02.
STEP 1. PHYSICAL/CHEMICAL PROPERTY DETERMINATION
Chemical B is an aromatic hydrocarbon with the following known physical/chemical properties:
Mmolecular weight = 78;
• Water solubility = 1800 mg/l;
• Vapor pressure = 95.3 mm-Hg; and
• SMILES notation = c1 cccccl.
The SMILES (Simplified Molecular Input Line Entry System) notation for many chemicals can
be obtained from SMILECAS database. If the SMILES notation for the chemical is not in the
database, instructions are included in Appendix B of this document on how to determine the
notation.
KOW and biodegradation rates are needed to run the STP model. KOC is needed to run
ReachScan. However, KOC is necessary only if the risk assessor is considering
environmental effects and the PDM analysis is run.
Running KOC WIN - The only input required is the SMILES notation which translates the
chemical structure into a format understood by computer models. Enter the SMILES notation
and the model then calculates a KOC value for Chemical B.
KOCWIN Results - KOC = 165.5 (see Figure B1).
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Running BIOW1N The SMILES notation is the only input required. Enter the SMILES
notation and the model then calculates the primary biodegradation time frame for Chemical B.
BIOWIN Results - Primary biodegradation (see Figure B2) time frame = days to weeks and the
ultimate degradation time frame = weeks to months. Therefore, for running the STP model, a
biodegradation rate of 30 hours (slowly degradable) will be assumed. For Running the
ReachScan model, a biodegradation rate of 336 hours (14'days x 24 hrs) will be assumed.
Running KOWWIN Enter the SMILES notation and the model calculates an estimated KOW
for Chemical B.
KOWWIN Results - Estimated KOW= 1.99 (see Figure B3).
STEP 2. ESTIMATION OF REMOVAL DURING WASTEWATER TREATMENT
Running STP - HPM's risk assessor knows the projected discharge of Chemical B to the
POTW is 2000.0 kg/day for 150 days of the year. She uses that discharge information along
with physical/chemical parameters of Chemical B to run the STP model in order to determine
the percent removal of the chemical at the POTW. Following is a step-by-step description of
how to run the STP model. See for printouts of model screens showing results.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Once you have entered the STP model:
1. Select: New Chemical;
2. Enter Chemical Data:
Chemical Name = Chemical B
Temperature (degrees C) = 25
Molecular weight (g/mol) = 78
Water solubility (mg/l) = 1800
• Vapor pressure (mm-Hg) = 95.3
• Log KOW (from KOWWIN) = 1.99
Primary biodegradation (from BIOWIN) = 30 hrs (slowly degradable) corresponds to
"days-weeks"
Biodegradation in aeration vessel estimated to be = 3 hours (moderately degradable)
Biodegradation in final settling tank estimated to be = 3 hours (moderately degradable);
3. Select Sewage Treatment Plant Operating Conditions = (3) default conditions; and
4. Select Sewage Treatment Plant Design = (3) default conditions.
STP Results (See Figure A6)
There will be 85 percent removal of Chemical B in wastewater treatment. Therefore, the daily
release rate during the 150 days per year of release is 300 kg/day (15% x 2,000 kg/day
released).
STEP 3. ESTIMATION OF SURFACE WATER CONCENTRATION
ReachScan is then used to calculate stream concentration after treatment in the POTW. The
HPM risk assessor knows the hydrologic region number and NPDES number of the receiving
POTW. She will use this information to retrieve flow data for the POTW to^yhich HPM
discharges.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
After entering ReachScan she goes through the following steps. Printouts of the ReachScan
files are included as Figures B7 to B16.
1. Select a Region: Region 02
2. Search by NPDES number of the POTW: PA0027031
3. Search Query:
(F7) Check for reported presence of endangered species in the county
Search: distance of 100 km; downstream; for the presence of a utility
4. Enter Concentration Parameters
• Loading (amount released after treatment in kg/day) = 300.0
Consider Environmental Fate = Yes (Note: If environmental fate is not considered,
the model will calculate the concentration using default values, and the predicted
concentration may be higher than the actual value that would be observed.)
Select flow type = mean (for drinking water concerns select mean, for aquatic life
concerns select low)
5. Enter Environmental Effects data
• Chemical name = Chemical B
• Molecular weight = 78
• Solubility = 1800 mg/L
• Vapor pressure = 95.3 mm-Hg
• Sorption coefficient (KOC) = 165.6
• Half-life = 336 hrs
Suspended solids = use default value already entered
Note: If considering environmental effects, you should run PDM analysis at this step.
ReachScan Results - (See Figure B16)
• Utility name: Wilmington Water Company
- Mean stream flow = 1,252 MLD
- Km downstream from HPM = 30.6 km
- Population served = 140,000
- Concentration of Chemical B in the influent = 0.26 pg/L
Endangered species present
Aquatic = none; and
- Terrestrial = Delmarva Peninsula fox squirrel, Indiana bat.
A-21
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Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
STEP 4. ESTIMATION OF DRINKING WATER CONCENTRATION
The risk assessor will then estimate the potential exposure from ingesting drinking water
contaminated with Chemical B at a concentration of 0.26 ug/L. She assumes an ingestion rate
of 2 liters per day. Therefore, the potential exposure is (2 L/day) x (0.26 ug/L) = 0.52 ug/day.
Figure B1
Results of Running PCKOCWIN Model
Koc (estimated) : 165
SMILES
CHEM
MOL FOR
MOLWT
dcccccl
Chemical B
C6H6
78.11
First Order Molecular Connectivity Index : 3.00
Non-Corrected Log Koc : 2.2187
Fragment Correction(s): —< NONE
Corrected Log Koc : 2.2187
Estimated Koc : 165
A-22
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Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B2 - Results of Running BIOWIN Model
SMILES dcccccl
CHEM Chemical B
MOL FOR C6 H6
MOLWT 78.11
Linear Model Prediction
Non-Linear Model Prediction
Ultimate Biodegradation Timeframe
Primary Biodegradation Timeframe
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Unsubstituted aromatic (3 or less rings)
MolWt | * j Molecular Weight Parameter
Const | * | Equation Constant
RESULT | LINEAR BIODEGRADATION PROBABILITY
Biodegrades Fast
Biodegrades Fast
Weeks-Months
Days-Weeks
| COEFF |
| 0.3192 |
I J
I . I
I I
VALUE
0.3192
-0.0372
0.7475
0.8910
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Unsubstituted aromatic (3 or less rings)
MolWt | * j Molecular Weight Parameter
RESULT | NON-LINEAR BIODEGRADATION PROBABILITY
| COEFF |
| 7.1908 |
I I
I I
VALUE
7.1908
-1.1092
0.9999
A Probability Greater Than or equal to 0.5 indicates -» Biodegrades Fast
A Probability Less Than 0.5 indicates -» Does NOT Biodegrade Fast
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Unsubstituted aromatic (3 or less rings)
MolWt | * | Molecular Weight Parameter
Const | * | Equation Constant
RESULT | SURVEY MODEL -ULTIMATE BIODEGRADATION
| COEFF |
| 0.1600 |
I I
I I
I I
VALUE
0.1600
-0.0708
3.1992
3.2883
TYPE | NUM | BIODEG FRAGMENT DESCRIPTION
Frag | 1 | Unsubstituted aromatic (3 or less rings)
MolWt | * | Molecular Weight Parameter
Const | * | Equation Constant
RESULT | SURVEY MODEL -PRIMARY BIODEGRADATION
Result Classification : 5.00 -» hours 4.00 -> days
(Primary and Ultimate) 2.00 -» months 1 .00 -» longer
| COEFF |
| -0.5859 |
I I
I I
I I
3.00 -» weeks
VALUE
-0.5859
-0.1726
3.1992
2.4406
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B3
Results of Running KOWWIN Model
Log Kow (estimated) : 1.99
Experimental Database Structure Match:
Name : Benzene
CAS Num 000071-43-2
Exp Log P 2.13
Exp Ref Hansch & leo, 1985
SMILES
CHEM
MOL FOR
MOLWT
TYPE | NUM
Frag | 6
Const j
dcecccl
Chemical B
C6H6
78.11
| LOGKOW FRAGMENT DESCRIPTION
| Aliphatic carbon
j Equation Constant
| COEFF | VALUE
| 0.2940 | 1.7640
j | 0.2290
LogKow= 1.9930
A-24
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B4
New Chemical Data Input Screen in STP
Predicted Fate of an Organic Chemical in a
Wastewater Treatment Facility
Part 1: Chemical Properties
(1) A new chemical
(2) Use the chemical information from the last run
A chemical from the following list:
(3) Benzene
(5) 1,1,2 trichloroethene
(7) 1,4 dichlorobenzene
(9) pyrene
(11)2-40
(13) butyl-benzyl phthalate
(15) di-octyl phthalate
(17) pentachlorophenol
(4) Toluene
(6) 1,1,1 trichloroethane
(8) napththalene
(10) phenol
(12) gamma BHC
(14) di-butyl phthalate
(16) 2 ethyl hexyl phthalate
(18) anthracene
Your selection —> 1
(0) Exit the program
Figure B5
New Chemical Data Input Screen in STP
New Chemical Data Input Previously entered values are in [ ]
CHEMICAL NAME :[ ] ? Chemical B
TEMPERATURE (degrees C) : [ 0 ] ? 25
MOLECULAR WEIGHT (g/mol) : [ 0 ] 7 78
WATER SOLUBILITY (mg/l) : [ 0 ] ? 1800
VAPOR PRESSURE (mm-Hg) : [ 0 ] 7 95.25784
LOGKOW :[0] 71.99
Biodegradation Data Input Previously entered values are in [ ]
Half lives may be selected as indicative of biodegradability
1 hour = rapidly degradable
3 hours = moderately degradable
10 hours = slowly, but significantly degradable
30 hours = slowly degradable
Enter the biodegradation half life at MLSS of 2000 mg/l (H) at
conditions in
PRIMARY CLARIFIER : [0] ? 30
AERATION VESSEL : [ 0 ] ? 5
FINAL SETTLING TANK : [0] .75
A-25
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B6
Results of Running STP
PREDICTED FATE OF AN ORGANIC CHEMICAL
IN A WASTEWATER TREATMENT FACILITY
PROPERTIES OF Chemical B
Molecular weight (g/mol)
Aqueous solubility (mg/l)
Vapour pressure (Pa)
(atm)
(mm Hg)
Henry's Law constant (Atm-m3/mol)
Air-water partition coefficient
Octanol-water partition coefficient (Kow)
Log Kow
Biomass to water partition coefficient
Temperature [deg C]
Biodeg. rate consts (hA-1), half lives in biomass
-Primary tank 0.59
-Aeration tank 3.54
-Settling tank 3.54
OVERALL CHEMICAL MASS BALANCE
g/h
Influent 0.10E+02
Primary sludge 0.45E-01
Waste sludge 0.32E-01
Primary volatilization 0. 1 2E+00
Settling volatilization 0.67E-01
Aeration off gas 0.41 E+01
Primary biodegradation 0.57E+00
Settling biodegradation 0.21 E+00
Aeration biodegradation 0.30E+01
Final water effluent 0. 1 9E+01
Total removal 0.81 E+01
Total biodegradation 0.37E+01
78
1800
12700
.1253393
95.25784
5.431 35E-03
.2221261
97.72372
1.99
20.34475
25
(h) and in 2000
1.17
0.20
0.20
mol/h
0.1 E+00
0.6E-03
0.4E-03
0.2E-02
0.9E-03
0.5E-01
0.7E-02
0.3E-02
0.4E-01
0.2E-01
0.1 E+00
0.5E-01
mg/L MLSS (h)
30.00
5.00
5.00
percent
100.00
0.45
0.32
1.18
0.67
41.05
5.65
2.10
29.75
18.83
81.17
37.50
-------
UNITED STATES DEPARTMENT OF THE INTERIOR
QEOLOOICAI. SURVEY
ACCOUNTING UNITS OF THE
NATIONAL WATER DATA NETWORK
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B7
Initial Screen in ReachScan
1
ReachScan
i
Methodology and Program Development by
Sidney W.Abel, III
US EPA -
Office of Pollution
Prevention and Toxics
Washington, DC 20460
Phone (202) 260-3920
Gerald LaVeck
US EPA -
Office Water
Washington, DC 20460
Phone (202) 260-7771
Keith Drewes
Versar, Inc.
Exposure Assessment
Springfield, VA 221 51
Phone (703) 750-3000
Phone (800) 2-VERSAR
Press any key to continue . . .
^^^^
! Updated : March 9, 1995
Versar, Inc. i
i
Figure B8
ReachScan Opening Screen
ReachScan Opening Menu
Select a Region
Change Data File Location
Change Output File Location
Exit ReachScan
J Current Data Location: J:\env_ops\common\expmodel\rscanpdm\
F1:Help
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B9
Select a Hydrologic Region Screen in ReachScan
Region 01
Region 02
Region 03
Region 04
Region 05
Region 06
Region 07
Region 08
Region 09
Region
Region
Region
Region
Region
Region
Region
Region 17
Region 18
10
11
12
13
14
15
16
Figure B10
ReachScan Main Menu Screen
ReachScan Main Menu
Begin Search by NPDES Number
Begin Search by Facility Name
Begin Search by SIC Code
Begin Search by Water Utility Name
Begin Search by Reach Number
Select Another Region
Change Data File Location
Exit ReachScan
j Active Region: Region 02
I Current Data Location: J:\env_ops\common\expmodel\rscanpdm\
F1: Help
A-28
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B11
NPDES Selection Screen in ReachScan
NPDES Selection
SIC FACILITY NAME NPDES REACH KM UP
4952 WEST CHESTER BOROUGH-GOOSE-CRE PA0027031 02040205007 3.86
-j F1:Help | ' F9: Back j Total Items-> 1 j 1 to edit parameter. Use arrow keys to move about.
F1:Help F7: Endangered Species F9: Back F10:Next
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B13
Endangered Species Report Screen in ReachScan
Endangered Species Report
County :
Inventory Name
Scientific Name
Common Name
Group Name
Family
Status
Proposed Date
Critical Habitat
County
Inventory Name
Scientific Name
Common Name
Group Name
Family
Status
Proposed Date
Critical Habitat
CHESTER
State :
PA State FIPS
County FIPS
: 42
: 029
SQUIRREL, DELMARVA PENINSULA FOX
Sciurus niger dnereus
Delmarva Peninsula fox squirrel
MAMMAL
Scuiridae
EXN
CHESTER
BAT, INDIANA
Myotis sodalis
Indiana bat
MAMMAL
Vespertilionidae
ECN
75-12-6
17.92 (a)
Order :
Action :
State :
Order :
Action :
ESPP :
Rodentia
1
"PA State FIPS :
County FIPS
Chiroptera
C
N
42
: 029
Figure B14
Concentration Parameters Screen in ReachScan
Concentration Parameters
Region
Calc Parameters
Search Parameters
SIC Facility Name
Region 02
3.00E+02
Down
I Yes |
| Utility |
NPDES
Mean
100.00
Reach
km Up
4952 WEST CHESTER BOROUGH-GOOSE-CRE PA0027031 02040205007
3.86
I Loading in kg/day
1 Consider Environmental Fate
! Select Flow Type
3.00E+02 |
Yes '
Mean J
Press to edit parameter. Use arrow keys to move about.
F1:Help F7: Endangered Species F9:Back F10:Next : Exit
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY B
Potential Exposures to Surface Water
Discharges from a Manufacturing Facility (continued)
Figure B15
Environmental Effects Screen in ReachScan
Environmental Effects
Region Region 02
Calc Parameters 3.00E+02 |
Search Parameters Down |
SIC Facility Name
4952
Yes |
Utility |
NPDES
Mean
100.00
Reach
WEST CHESTER BOROUGH-GOOSE-CRE PA0027031 02040205007
Chemical Name (optional)
Molecular Weight (g/mol)
Water Solubility (ppm)
Vapor Pressure (mm-Hg)
Sorption Coefficient
Chemial half-live due to Degradation (hrs)
Suspended Solids Concentration (ppm)
Press to edit parameter.
F1: Help F7: Endangered Species
Chemical B
7.80E+01
1.80E+03
9.53E+01
1.66E+02
3.36E+02
1.50E+01
km Up
3.86
Use arrow keys to move about.
F9: Back F10: Next Help Print Fite
MEAN
H FLOW VEL KM DN POP V CONC
C (MLD) (M/S) STREAM SERVED C (u/l)
Y 1252.37 0.47 30.6 140000 V 2.61 E-01
2127.21 0.47 37.6 0 3.18E-02
2139.9 0.47 39.0 0 2.34E-02
47681.18 1.12 59.4 0 8.34E-05
N/A N/A LEVO 0 N/A
N/A N/A LEVO 0 N/A
48284.90 1.12 66.2 0 2.29E-05
N/A N/A LEVO 0 N/A
N/A N/A LEVO 0 N/A
48338.91 1.12 72.8 0 6.57E-06
N/A N/A LEVO 0 N/A
N/A N/A LEVO 0 N/A
Back Next : Main Menu
-| A-31
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Case Study C
Consumer Dermal Exposure
Uses the DERMAL Model
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
A-34
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY C
Consumer Exposure from Dermal Contact
INTRODUCTION
The purpose of this case study is to assess consumer exposure that may result from
dermal contact with a proposed new additive to a consumer product. The Brown
Manufacturing Corporation (BMC) is considering using Chemical C as a colorant in a new bar
soap product. The BMC risk assessor must estimate potential consumer exposure to
Chemical C before BMC product developers can make the decision to proceed with the new
formulation. The assessor will use the DERMAL model to predict a Potential Lifetime Average
Daily Dose (LADD) Rate, a Potential Average Daily Dose (ADD) Rate, and an Acute Potential
Dose Rate (APDR) for a consumer from dermal contact with Chemical C in the soap product
through hand and body washes.
The BMC assessor knows the following information about the proposed product and Chemical
C:
• Weight fraction of Chemical C in the final soap product will be 0.0025 - 0.0075
(percent by weight) (median = 0.005); and
• The chronic oral RfD for an adult (70 kg average body weight) for Chemical C
is 0.02 mg/kg-day.
ESTIMATION OF APDR AND LADD USING THE DERMAL MODEL
Enter DERMAL (Figure C1). Proceed with the following steps:
1. Select Begin New Consumer (Figure C2);
2. Enter Product Name (optional) (Figure C2);
3. Select Scenario (Figure C3): Bar Soap;
4. At the Scenario Input Screen (Figure C3), select Dermal Input at the top right of the screen
(Figure C4). At the Dermal Input screen you may review the default values used by the
model. Default values are included for both hand washes and total body washes. Default
values include skin surface area exposed and frequency of washes. If actual factors are
expected to differ from the defaults presented, the actual factors should be used. For
LADDs and APDRs, using default values would result in higher estimates.
5. At the Dermal Input Screen (Figure C4) select PChem Properties at the top right
of the screen (Figure C5);
6. Enter weight fraction values (Figure C5):
. Median = 0.005
• High end (90th%) = 0.0075;
7. Select Submit Data for Calculation. The DERMAL model automatically displays
the input data (Figure C6) and model results (Figure C7).
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY C
Consumer Exposure from Dermal Contact
DERMAL Model Results
After running the DERMAL model, the BMC assessor obtained the following predicted
exposure results (see Figure C7):
LADD = 2.655e-03 mg/kg-day
ADD = 2.691 e-03 mg/kg-day
APDR = 4.492e-03 mg/kg-day
In-house studies have demonstrated that the dermal absorption fraction of Chemical C is
10 to 20 percent of the applied dose. Using the more conservative value of 20 percent
absorption, the assessor will adjust the predicted ADPR 4.492e-03 mg/kg-day to obtain a
predicted absorbed adult dose of 8.984e-04 mg/kg-day. This is below the reported adult
chronic oral RfD for Chemical C of 2.00e-02 mg/kg-day. The assessor will report to product
developers that the amount of Chemical C in the soap formulation will not exceed the chronic
oral RfD for Chemical C.
A-36
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY C
Consumer Exposure from Dermal Contact
Figure C1
The DERMAL Model
Figure C2
Introduction Screen in the DERMAL Model
"Fto u the CoMtener faB-it partioa oftfarraodcl R
iopQrtfacT«qmf9e iafocswioa 'UK» 6e boxes beltrv
o^| pa dit foikHTtnsinput (
3}efMar-e
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY C
Consumer Exposure from Dermal Contact
Figure C3
Scenario Input Screen
Puduct Crwc^* CcwlKting Sfcii (D»»afl
Figure C4
Demnal Input Screen
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY C
Consumer Exposure from Dermal Contact
Figure C5
Physical/Chemical (P/Chem) Properties Input Screen
a 'IrJjoUVw Inpu' |D
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY C
Consumer Exposure from Dermal Contact
Figure C6
Dermal Model Inputs
PMN:
Unknown
Consumer Dermal Exposure Inputs
Product: Unknown
Scenario:
BarSoap
Population: Adult
Molecular Weight (g/mote)
Milltequivalent Weight (mge/mote)
0 WF - Med 0.005
WF-90% 0.0075
Inhalation Inputs
' There are no inhalation inputs for this scenario
; Activity Patterns
There are no activity pattern data for this scenario
Dermal Inputs
Frequency of Use - Body (events/yr) 324
Frequency of Use - Hands (events/yr) 730
Amount Retained/Adsorbed to Skin (gfcm2-event)
SA/BW-Body(cm2/kg)
SA/BW - Hands (cm2/kg)
1.9e-06
284
15.6
Averaging Time, Chronic (days) 2.738e+04
Averaging Time, non-Chronic (days) 2.701 e+04
Averaging Time, Acute (days) 1
Figure C7
Dermal Model Results
PMN:
Consumer Dermal Exposure Extirpates
Unknown Product: Unknown
Scenario: Bar Soap
Years of Use (years)
SA/BW- Body (cm2/kg)
SA/BW - Hands (cm2/kg)
Frequency of Use (eventstyr)
Frequency of Use Hands (events^ r)
Exposure Units
Population: Adult
74 (does not apply to APDR)
284
15.6
324
730
Results Descriptor AT (days) '•
Cancer t - :
LADD (mg/kg-day)
LADD(meq/kg-day)
Chronic Non-Cancer
ADD (mg/kg-day)
ADD (meq/kg-day)
Acute
APDR (mg/kg-day)
APDR (meq/kg-day)
0.002655 "what if \ 2.738e-i-04
Not Available "what if [ Not Available :
] j
0.002691 "whatiT • 2.738e+04 !
Not Available 'what if j Notifiable \
'• I :
0.004492 "what if > 1
Not Available "what if : Not Available
LADD - Lifetime Average Daily Dose, reported in mg/kg-day or in miDiequivalents/kg-day.
ADD - Average Dafly Dose, units as LADD
APDR- Acute Potential Dose Rate, units as LADD
A-40
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Case Study D
Worker Inhalation Exposure
Uses the Occupational Exposure Spreadsheet
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY D
Worker Inhalation Exposure
INTRODUCTION
The purpose of this case study is to assess worker exposure from the
inhalation of vapors generated during the transfer/repackaging of a chemical in an
industrial setting. The Deal Chemical Company plans to import Chemical D and
repackage the chemical for shipment to manufacturers. Deal's risk assessor needs
to estimate the potential worker exposures to Chemical D by vapors generated
during various transfer/repackaging processes that could be used. The assessor
will estimate worker exposure using the Lotus Spreadsheet for Worker Inhalation
Exposure. The assessor knows the following information about the chemical and
the processes:
Molecular weight = 250;
Vapor pressure = 0.1 torr;
Hours per day of operations = 6; and
Hours per day of worker exposure = 6.
ESTIMATION OF WORKER INHALATION EXPOSURE
Enter the Lotus Spreadsheet for Inhalation Exposure (Figure D1). Enter the
required site-specific inputs:
1. Enter the following values in the designated spreadsheet cells:
Molecular weight = 250 cell C6;
Vapor pressure = 0.1 torr cell C7;
Hours of operation = 6/day cell C8; and
Hours of worker exposure = 6/day cell C9.
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY D
Worker Inhalation Exposure
2. After entering the specific inputs in Step 1, the spreadsheet automatically
calculates predicted worker exposure and vapor generation rates from transfer
operations. The results are automatically displayed after data are entered in the
proper cells. The spreadsheet is designed to automatically calculate worker
exposure from both transfer operations and from sampling and open surface
operations. Therefore, the assessor must select the exposure and vapor
generation rates appropriate for the specific scenario (i.e., for transfer operations
or for sampling and open surface operations).
RESULTS
The results of the calculation for worker exposures from transfer
operations are displayed in Figure D2. Worker exposure and vapor generation
results are shown (typical and worst case) for drumming, cans/bottles, tank truck
and tank car operations. The inhalation exposures are shown in mg/day, and
air concentrations in mg/m3 and ppm. Vapor generation rates are shown in
g/sec and kg/day.
A-44
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY D
Worker Inhalation Exposure
Figure D1
Spreadsheet to Estimate Worker Inhalation Exposure to Vapors from Transfer (Filling)
Operations and Open Surfaces (Pools) of Liquid
CEB SPREADSHEET FOR WORKER INHALATION EXPOSURE AND VAPOR GENERATION FROM TRANSFER AND
OPEN SURFACE OPERATIONS (1/22/97)
(Uses Cv (eqn 4-14) and vapor generation rate (eqns 4-21 and 4-24) from CEB Eng. Manual)
(Default values are listed in Tables 4-10,4-11, and 4-12 in CEB Eng. Manual)
REQUIRED, CASE-SPECIFIC INPUTS:
Molecular weight
Pure vapor pressure (torr):
Mrs/Day (operations)
Hrs/Day (worker exposure):
OTHER REQUIRED INPUTS:
Volumes (cm3):
Wind Speed (ft/min):
Fill Rates (#/hr)
Saturation Factors:
Mixing Factors:
Ventillation Rates (ft3/min):
Inhalation Rate (m3/hr):
Universal Gas Constant
Total Pressure (atm):
Temperature (K)
Air Molar Volume (l/gmole)
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00.
2.10E+05
1.90E+04
1.90E+07
7.60E+07
4.40E+02
2.00E+01
3.00E+01
2.00E+00
1 .OOE+00
5.00E-01
1 .OOE+00
1 .OOE+00
5.00E-01
1 .OOE-01
3.00E+03
5.00E+02
1 .32E+05
2.38E+05
1 .25E+00
8.21 E+01
1. OOE+00
2.98E+02
2.45E+01
N
These are the four required inputs
[should be less than or equal to 8)
Drumming (55 gallons = 2.1E+05 cm3)
Cans/bottles (5 gallons = 1.9E+04 cm3)
Tank truck (5,000 gallons = 1.9 E+07 cm3)
Tank car (20,000 gallons = 7.6E+07 cm3)
(average outdoor wind speed = 9 mph (792 ft/min), per CEB Eng. Man.
(pg 4-17); average indoor wind speed = 100 ft/min (1.136 mph), per
CEB Eng. Man (App. K); 440 ft/min (5 mph) is the CEB default value,
per Nhan)
Typical cans/drums (20/hr)
Worst case cans/drums (30/hr)
Typical and worst case tank truck (2/hr)
Typical and worst case tank car (1/hr)
Typical cans/drums (0.5, dimensionless)
Worst case cans/drums (1.0, dimensionless)
Typical and worst case tank truck/tank car (1.0, dimensionless)
Typical for all (0.5, dimensionless)
Worst case for all (0.1, dimensionless)
Typical case cans/drums (3,000 ft3/min)
Worst case cans/drums (500 ft3/min)
Worst case for tank cars/trucks (ft3/min; dependent on wind speed
(26.400*wind speed in mph); NO ENTRY REQUIRED, CALC BASED
ON ABOVE WIND SPEED)
Typical case for tank cars/trucks (ft3/min; constant based on 9mph,
per CEB Eng. Man)
Standard inhalation rate (1.25 m3/hr)
R (82.05 atm cm3/gmole K)
(1 atm)
(298 K)
(24.45 l/gmole)
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
CASE STUDY D
Worker Inhalation Exposure
Figure D2
Results from Spreadsheet to Estimate Worker Inhalation Exposure to
Vapors from Transfer (Filling) Operations and Open Surfaces (Pools) of Liquid
Exposure and generation rates from transfer operations can
be found at cells E44-E54, and
from sampling and open
surface at cells D60-D77.
RESULTS:
WORKER EXPOSURES AND VAPOR
GENERATION RATES
INPUTS Cell No.
Molecular weight
250
Vapor pressure
0.1 torr
C6
C7
Mrs/day operations
6
C8
Mrs/day worker exposure
6
C9
FROM TRANSFER OPERATIONS
Inhalation Exposure
l[mg/day]
Drumming (55 gal)
Worst Case 7.32E+02
Typical Case 8.13E+00
Cans/Bottles (5 gal)
Worst Case 6.62E+01
Typical Case 7.36E-01
Tank Truck (5,000 gaO
Worst Case 1.67E+01
Typical Case 1.86E+00
Tank Car (20,000 gal)
Worst Case 3.34E+01
Typical Case 3.72E+00
Cm[mg/mA3]
9.76E+01
1.08E+00
8.83E+00
9.81 E-02
2.23E+00
2.48E-01
4.46E+00
4.95E-01
Cv[ppm]
9.54E+00
1.06E-01
8.63E-01
9.59E-03
2.18E-01
2.42E-02
4.36E-01
4.84E-02
WORKER EXPOSURES AND VAPOR GENERATION RATES
Inhalation Exposure
Sampling l[mg/day] Cm[mg/mA3]
Worst Case 4.47E+01 5.96E+00
Typical Case 7.48E-01 9.97E-02
Open surface
Worst Case 1.24E+03 1.65E+02
6.73E+02 8.98E+01
2.38E+02 3.17E+01
8.41 E+01 1.12E+01
2.96E+01 3.95E+00
1.62E+01 2.16E+00
5.72E+00 7.63E-01
Typical Case 4.12E+01 5.50E+00
2.24E+01 2.99E+00
7.93E+00 1.06E+00
2.80E+00 3.74E-01
9.87E-01 1.32E-01
5.39E-01 7.19E-02
1.91E-01 2.54E-02
Cv[ppm]
5.83E-01
9.75E-03
1.61 E+01
8.78E+00
3.10E+00
1.10E+00
3.86E-01
2.11E-01
7.46E-02
5.38E-01
2.93E-01
1.03E-01
3.66E-02
1.29E-02
7.03E-03
2.49E-03
AREA
A[cmA2]
7.85E+01
3.85E+01
6.58E+03
2.92E+03
7.31 E+02
1.83E+02
4.54E+01
2.03E+01
5.07E+00
6.58E+03
2.92E+03
7.31 E+02
1.83E+02
4.54E+01
2.03E+01
5.07E+00
I A-4
I
Vapor Generation
G[g/sec]
2.35E-03
7.85E-04
2.13E-04
7.10E-05
1.42E-02
1.42E-02
2.84E-02
2.84E-02
G[kg/day]
5.09E-02
1.70E-02
4.60E-03
1.53E-03
3.07E-01
3.07E-01
6.13E-01
6.13E-01
DUE TO SAMPLING AND OPEN SURFACE
DIAMETER
z[cm]
1.00E+01
7.00E+00
9.15E+01
6.10E+01
3.05E+01
1.53E+01
7.60E+00
5.08E+00
2.54E+00
9.15E+01
6.10E+01
3.05E+01
1.53E+01
7.60E+00
5.08E+00
2.54E+00
6
Q[ft3/min]
5.00E+02
3.50E+03
5.00E+02
5.00E+02
5.00E+02
5.00E+02
5.00E+02
5.00E+02
5.00E+02
3.00E+03
3.00E+03
3.00E+03
3.00E+03
3.00E+03
3.00E+03
3.00E+03
Vapor Generation
k G(g/sec)
1.00E-01 1.44E-04
5.00E-01 8.42E-05
1.00E-01 3.98E-03
1.00E-01 2.17E-03
1.00E-01 7.66E-04
1.00E-01 2.71 E-04
1.00E-01 9.52E-05
1.00E-01 5.21 E-05
1.00E-01 1.84E-05
5.GJOE-01 3.98E-03
5.00E-01 2.17E-03
5.00E-01 7.66E-04
5.00E-01 2.71 E-04
5.00E-01 9.52E-05
5.00E-01 5.21 E-05
5.00E-01 1.84E-05
G(kg/day)
3.11E-03
1.82E-03
8.59E-02
4.68E-02
1.65E-02
5.85E-03
2.06E-03
1.12E-03
3.97E-04
8.59E-02
4.68E-02
1.65E-02
5.85E-03
2.06E-03
1.12E-03
3.97E-04
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Append. B Data Sources
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Pollution Prevention (P2) Chemical Screening Assessment Framework
APPENDIX B
Data Sources
Physical/Chemical Property Data
Chemical Human Hazard Data
Chemical Environmental Hazard Data
Release Data
Exposure and Population Data
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Data Sources: Physical/Chemical Property Data
Physical/chemical property and fate data sources:
Handbook of Chemical Property Estimation Methods: Environmental Behavior of Organic
Compounds, 1990. Warren J. Lyman, William F. Reehl, and David H. Rosenblatt American
Chemical Society; ISBN: 0841217610. Contains methods for estimating density, vapor
pressure, water solubility, and other chemical properties relevant to environmental fate.
Kirk-Othmer Concise Encyclopedia of Chemical Technology, 3rd Edition, 1989. Martin
Grayson (Contributor), Herman F. Mark, and Donald F. Othmer. John Wiley & Sons; ISBM:
0471517003. (A revised 27 volume set edition is due out Dec. 1998). This is a comprehensive
source of chemical information.
Hawley's Condensed Chemical Dictionary, 13th Edition, 1997. Gessner Goodrich Hawley
(Editor), and Richard J., Sr. Lewis (Editor). John Wiley & Sons; ISBN: 0471292052. (A CD-
ROM version is also available). A compendium of technical data and descriptive information
covering many thousand chemicals, including their industrial uses, and trademark names.
CRC Handbook of Chemistry and Physics: A Ready-Reference Book of Chemical and
Physical Data, 78th Edition, 1997. David R. Lide (Editor). CRC Press; ISBN: 0849304784.
Handbook contains CAS Registry numbers, and chemical and physical properties.
The Merck Index: An Encyclopedia of Chemicals, Drugs and Biologicals, 12th Edition. 1996.
Chapman & Hall; ISBN: 0911910123. Handbook contains chemical and physical properties,
and CAS Registry numbers.
Handbook of Environmental Data on Organic Chemicals, 3rd Edition, 1997. Karel Verschueren
(Editor). John Wiley & Sons; ISBN: 0471286591. An extensive text compiling information on
organic products. The data given include physical properties; e.g., formula, physical
appearance, molecular weight, melting point boiling point vapor pressure, and solubility.
Computerized searches involve accessing the EPA CHEMFATE database and DIALOG data
files as well as STN International and the Hazardous Substances Data Bank (HSDB).
CHEMFATE contains evaluated physical property values, rate constants, and monitoring
concentrations for approximately 1,700 commercially significant compounds. CHEMFATE is
readily searched by CAS registry number. DATALOG contains more than 186,000 records for
12,000 chemicals entered under 18 different indexing terms, including physical-chemical
properties.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Physical/chemical property and fate data sources:
Chemical Abstracts Service (CAS), a division of the American Chemical Society, provides fee-
based online access to databases of chemical information. A useful method of searching is
through CAS's Science and Technology Network (STN) that searches numerous databases of
chemical information. CAS's Internet address is: http://www.cas.org.
HSDB (Hazardous Substances Data Bank). This is an on-line data base containing
information on a chemical's properties, human and environmental toxicity, environmental fate,
regulations, and treatments.
Howard, P.H.; Boethling, R.S.; Jarvis, W.F.; and Meylan, W. 1991. Handbook of
Environmental Degradation Rates. New York: Lewis Publishers, Inc. ISBN: 0873713583.
Howard, P.H.; Sage, G.W.; LaMacchia, A.; Colb, A. 1982. The Development of an
Environmental Fate Data Base. J. Chem. Inform. Comput Sci., 22, 38-44.
Howard P.H.; Hueber, A.E.; Mulesky, B.C.; Crisman, J.S.; Meylan, W.; Crosbie, E.; Gray, DA;
Sage, G.W.; Howard, K.P.; LaMacchia, A.; Boethling, R.; Troast, R. 1986. BIOLOG, BIODEG
and FATE/EXPOS: New files on microbial degradation and toxicity as well as enviromental
fate/exposure of chemicals. Environ. Toxic. Chem. 5:977-988.
PHYSPROP. Howard, P.H.; Meylan, W.M. 1997. Handbook of Physical Properties of Organic
Chemicals. CRC/Lewis Publishers, Boca Raton, FL. There is also a database version.
»
SRC Handbooks (a separate series):
Handbook of Environmental Fate and Exposure Data for Organic Chemicals. 1989. P.M.
Howard (ed.) Voll. Large Production and Priority Pollutants. Lewis Publishers, Chelsea, Ml.
Handbook of Environmental Fate and Exposure Data for Organic Chemicals. 1990. P.H.
Howard (ed.) Vol II. Solvents. Lewis Publishers, Chelsea, Ml.
Handbook of Environmental Fate and Exposure Data for Organic Chemicals. 1991. P.H.
Howard (ed.) Vol III. Pesticides. Lewis Publishers, Chelsea, Ml.
Handbook of Environmental Fate and Exposure Data for Organic Chemicals. 1992. P.H.
Howard (ed.) Vol IV. Solvents II. Lewis Publishers, Chelsea, Ml.
Handbook of Environmental Fate and Exposure Data for Organic Chemicals. 1997. P.H.
Howard (ed.) Vol V. Solvents III. CRC/Lewis Publishers, Boca Raton, FL.
B-4
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Data Sources: Chemical Human Hazard Data
Chemical human hazard data sources:
U.S. EPA. IRIS (Integrated Risk Information System). Reviews studies used in the derivation
of RfD, RfC, unit risk, and slope factor values. A web prototype is available on the Internet at
the following address: http://www.epa.gov/ngispgm3/iris.
U.S. EPA. Health Effects Assessment Summary Tables (HEAST), 1994. Contains RfD, RfC,
unit risk, and slope factor values for selected chemicals. Available through the National
Information Service (NTIS), Doc. No. PB94-921199.
U.S. EPA. Health Assessment Documents (HAD). Reviews health effects of specific
chemicals.
U.S. Department of Health and Human Services, Agency for Toxic Substances and Disease
Registry (ATSDR). Undated. Toxicological Profiles. Contains toxicological profiles of
hazardous chemicals most often found at facilities on CERCLA's National Priority List
TSCATS. Provides public assess to information submitted to U.S. EPA under the various
sections of TSCA (Toxic Substances Control Act). TSCATS is available from several on-line
sources (CIS, NLM) or on the Internet at the following address:
http://www.rtk.net/www/data/tsc_all.html.
Chemical Categories. Developed under the New Chemicals Program within EPA's Office of
Prevention, Pesticides, and Toxic Substances (OPPT), this document includes summaries of
chemical categories developed to facilitate the review process of new chemicals
(Premanufacture Notices) under TSCA Section 5. It is not intended to be a comprehensive list
of all chemical substances. Chemical Categories is available on the Internet at the following
address: http://www.epa.gov/opptintr/chemcat
Patty's Industrial Hygiene and Toxicology, Vols. 1-4. John Wiley & Sons. (CD-ROM version
is available). Contains toxicology and properties of selected industrial chemicals and classes
of chemicals.
National Institute of Occupational Safety and Health (NIOSH). Presents Health Hazard
Evaluations and Industry-wide Studies. Contains literature reviews of occupational exposure
data, health effects data, and animal studies. Rationale are presented for the derivation of
NIOSH exposure levels.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Data Sources: Chemical Environmental Hazard Data
Chemical environmental hazard data sources:
U.S. EPA. Ambient Water Quality Criteria Documents. Contains aquatic toxicity values
chemicals for which ambient water quality criteria have been developed, and is useful for
organic and inorganic compounds.
U.S. EPA. AQUIRE (Aquatic Information Retrieve! Toxicity Data Base). This is a
comprehensive data base of measured aquatic toxicity values derived from open literature.
Some data are not peer-reviewed. Data should be confirmed with original literature citation.
HSDB (Hazardous Substances Data Bank). This is an on-line data base containing
information on a chemical's properties, human and environmental toxicity, environmental fate,
regulations, and treatments.
Handbook of Environmental Data on Organic Chemicals, 3rd Edition, 1997. Karel
Verschueren (Editor). John Wiley & Sons; ISBN: 0471286591. An extensive text compiling
information of organic products. The data given include physical properties: e.g., formula,
physical appearance, molecular weight melting point boiling point, vapor pressure, and
solubility.
Acute Toxicities of Organic Chemicals to Fathead Minnows (Pimephales Promelas), Vols. 1-5.
Brooke, L.T., D.J. Call, D.L Geigerand C.E. Northcott, Eds. 1984-1990. This is a
comprehensive source of measured fish toxicity values for a single species (fathead
minnows), including fish LC50 data.
Subchronic Toxicities of Industrial and Agricultural Chemicals to Fathead Minnows
(Pimephales Promelas), Volume 1. S Call, D.J. and D.L. Geiger, Eds. 1992. ource of
measured fish toxicity values for a single species (fathead minnows), including fish EC50 data.
Syracuse Research Corporation. Summary of TSCA Section 4 Activity, 1993. Summarizes
TSCA Section 4 activity by CAS number.
U.S. Atomic Energy Commission. 1973. Toxicity of Power Plant Chemi^ls to Aquatic Life.
Presents aquatic toxicity values for organic and inorganic chemicals used by power plant.
B-6
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Data Sources: Release Data
Environmental release data sources:
TRI data base (EPA Mainframe). Contains environmental release data by chemical and
associated media of discharge. Data can be collected for all chemicals listed under section
313 of SARA Title III.
NATICH (Nation Air Toxics Information Clearing House) data base. This is an air pollution
data based on air permits issued by state and local agencies is available.
PCS (The Permit Compliance System) is an information management system maintained by
the U.S. EPA's Office of Wastewater Enforcement and Compliance (OWEC), to track the
permit, compliance, and enforcement status of facilities regulated by the National Pollutant
Discharge Elimination System (NPDES). PCS tracks information about wastewater treatment,
industrial, and Federal facilities discharging into navigable waters.
AIRS (Aerometric Information Retrieval System) is the national repository for information
about airborne pollution in the United States. There are seven "criteria pollutants" for which
data must be reported to EPA and stored in AIRS: PM 10 (particulate matter less than 10
microns in size), carbon monoxide, sulfur dioxide, nitrogen dioxide, lead, reactive volatile
organic compounds (VOC), and ozone.
CEB Engineering Manual Vol. I. Provides information and models for estimating worker
exposures and environmental releases.
Kirk-Othmer Concise Encyclopedia of Chemical Technology, 3rd Edition, 1989. Martin
Grayson (Contributor), Herman F. Mark, and Donald F. Othmer. John Wiley & Sons; ISBN:
0471517003. This is a comprehensive source of chemical synthesis processes.
Office of Water Effluent Limitations Guidelines and Standards (for selected industries).
U.S. EPA. ISDB (Industry Studies Database). Contains survey data collected by the Office of
Solid Waste (OSW) covering both RCRA and non-RCRA wastes generated by 470 facilities in
11 industries. The data include company identify and location, SIC code, product name,
production volume, waste stream properties and category, constituents and their
concentrations in the waste stream, management practice and location, and quantity of waste
stream.
Published chemical monitoring data reports.
Company Product Literature.
B-7
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Data Sources: Exposure and Population Data
Exposure parameter data sources:
U.S. EPA. Exposure Factors Handbook. Presents a summary of available data on human
behaviors and characteristics which affect exposure to environmental contaminants and
presents recommended values to use for these factors. It provides factor data on ingestion
rates of foods, water, breastmilk, and soil; factors for inhalation and dermal exposure; data for
bodyweight, lifetime, activity factors; data for use of consumer products; and data for
exposures that occur in residences.
U.S. EPA. Methods for Assessing Exposure to Chemical Substances. Volumes 1-13.
Population data sources:
U.S. EPA. Methods for Enumerating and Characterizing Populations Exposed to Chemical
Substances. Volume 4. Presents methods and data sources for identifying and characterizing
populations of interest
U.S. Bureau of the Census. Census of Population Reports. Available from the U.S. Bureau of
the Census on CD-ROM and on the Internet Populations are characterized geographically by
social and economic characteristics, and also by housing characteristics.
B-8
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
-------
Append. C SMILES
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
APPENDIX C
Summary of
Writing
SMILES Notations
-------
Pollution Prevention (P2) Chemical Screening Assessment Framework
The Purpose of SMILES
The purpose of SMILES is to go from this...
OH
CH
CH
CH,
CH
CH
.CH
CH
CH
OH CH
to this.
OlC2C(O)C=CC3C2(C4)c5clc(O)ccc5CC3N(C)C4
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Atoms
Atomic symbols and their corresponding SMILES
notations:
C methane (CH4)
N ammonia (NH3)
O water (H2O)
P phosphine (PH3)
S hydrogen sulfide (H2S)
Cl hydrogen chloride (HC1)
Elements must be described in brackets:
[Au] elemental gold
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Bonds
Single, double, triple, and aromatic bonds are
represented by the following symbols:
single - triple #
double = aromatic :
Examples are:
CC
C=C
COC
CCO
CO
0=C=0
O=CO
C#N
ethane (CH3CH3)
ethylene (CH2=CH2)
dimethyl ether (CH3OCH3)
ethanol (CH3CH2OH)
formaldehyde (CH2O)
carbon dioxide (CO2)
formic acid (HCOOH)
hydrogen cyanide (HCN)
molecular hydrogen (H2)
Normally single bonds and aromatic bonds^do not
need to be written in the SMILES notation.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Bonds in Linear Structures
For linear structures, SMILES notation corresponds to
conventional diagrammatic notation except that
hydrogen can be omitted. For example, there are
three correct ways to represent:
6-hydroxy-1,4-hexadiene
structure: CH2=CH-CH-,-CH=CH-CHo-OH
\
valid SMILES:
C=CCC=CCO
C=C-C-C=C-C-O
OCC=CCC=C
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Branches
Branches are specified by enclosures in parentheses,
for example:
CH
CH
CCN(CC)CC
triethylamine
H3C—CH—C—OH
CC(C)C(=O)O
isobutyric acid
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Branches
Branches also can be nested or stacked, for example:
CH
CH2 CH-CH3
I I
H3C=CH-CH— CH— CH2— CH2-CH3
i
C=CC(CCC)C(C(C)C)CCC
3-propyl-4-isopropyl-1 -heptene
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Cyclic Structures
Cyclic structures are represented by breaking one
single or aromatic bond in each ring. The bonds are
numbered in any order, designating ring-
opening/closure bonds by a digit immediately
following the atomic symbol at each ring closure.
This leaves a connected noncyclic graph, which is
written as a noncyclic structure by using the three
rules described for atoms, bonds, and branches. A
typical example is:
cyclohexane
H2C
H2C.
ChL C
CH, C
C1CCCC1
.C,
CH,
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Cyclic Structures
Usually there are many different but equally valid
descriptions of the same structure, for example,
the following SMILES notations for
H2C
1 -methyl-3-bromo-cyclohexene
.CH
'CH,
Br
w ^ / w
Br
(a)
CCl=CC(Br)CCCl
(b)
CCl=CC(CCCl)Br
Many other SMILES notations may be written for
the same structure from different ring closures.
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Representing Cyclic Structures
A single atom may have more than one ring closure.
An example of this is cubane, in which two atoms
have more than two ring closures.
The generation of the SMILES notation for cubane:
C12C3C4C1C5C4C3C25
HC
\
HC-
OH
HC — CH
HC GH
'12
'25
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Evolution of SMILES for Morphine
Morphine: Break and number 5 ring closures:
OH^ /CHL^ O^
CH CH CHg
CH .CH ^M.
/ ^CC ^StU— ^CH2 /
6 ^CH-f^ 4
\ /C /CH2 *
CH CH
/CH ^CH2
OH CH2 O
^C^ ^C CH3
/C^ /-C^ ^\
/ 'r-(^^ /7^f^^ ^*
~^ ^-V-V-^ — " —
^^^i i-^* |" A »
on
< /-C^ x/C
C ^C^
'C^c^C
Generate SMILES for the resulting non-cyclic structure by
starting at the * and following along the string to the arrow.:
^C^ ^C C
C2 .C3 ,N
/^ jr O ^^
C*' px^
U2\^ U3
, 1 C4
/C5 ./C
C1 C5
0/C\o/C
h
^C4
X
X
"N
VA
OlC2C(O)C=CC3C2(C4)c5clc(0)ccc5CC3N(C)C4
r 'id
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Disconnected Structures
Disconnected compounds are written as individual
structures separated by a period. The order in which
ions or ligands are listed is arbitrary. There is no
implied paring of one charge with another, and it is
not necessary to have a net charge of zero. If
desired, the SMILES of one ion may be imbedded in
another, as shown in the example of:
sodium phenoxide
[Na+].[O-]clcccccl
or
clcc([O-].[Na+])cccl
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Aromaticity
Aromatic structures may be distinguished by writing
the atoms in the aromatic ring in lower case letters,
for example:
benzoic acid
,OH O
C ^C'
i=C>clccccclC(=O)O
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Compounds Containing
Aromatic Nitrogen
To avoid confusion aromatic nitrogens require special
attention. There are two types of atomatic nitrogens
that are distinguished within the SMILES system.
Both types may be specified with the aromatic symbol
"n." Examples are pyridine and pyrrole:
HC'
'HC
,HC
nlcccccl
pyridine
CH'
CH, ^—'.CH
CH
O=nlcccccl
CH'
,CH
CH
[O-][N+]clcccccl
and
Cnlcccccl
methyl pyrrole
pyridine-N-oxide
NH
CH /"-^ CH
\o/
CH—CM
[nH]lcccccl
1 H-pyrrole
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Pollution Prevention (P2) Chemical Screening Assessment Framework
SMILES
(Simplified Molecular Input Line Entry System)
Examples of Aromatic and Nonaromatic Compounds
CH=CH
OH-( ( ) )-OH 0=C C=0
CH=CH
O=clccc(O)ccl 0=C1C=CC(=O)C=C1
Hydrpquinone Quinone
In-ring oxygen and sulfur atoms donate a single pair, for
example, thiophene:
«c
HC C'H
IP x—X PM
\\O//
• .* .^h. .^ *. •
slccccl
Thiophene
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Pollution Prevention (P2) Chemical Screening Assessment Framework
Notes
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