Appendix 9 – Draft Protocol for SiteSpecific Multipathway Risk Assessment
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft 1-2 July 2013

Protocol for Developing a TRIM.FaTE Model Scenario to Support a 

Site-Specific Risk Assessment in the RTR Program 

WORKING DRAFT

February 2014

Prepared For:

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Research Triangle Park, NC 27711

Contract No. EP-W-12-010

Prepared By:

ICF International

2635 Meridian Parkway

Suite 200

Durham, NC 27713
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Working Draft i February 2014

CONTENTS

1. Introduction.........................................................................................................................1

1.1 Regulatory Context and Approach to Risk Assessment for PB-HAPs ........................1

1.2 Purpose of this Protocol.............................................................................................2

1.3 Scope and Limitations ...............................................................................................2

1.4 Caveats .....................................................................................................................2

1.5 Protocol Road Map....................................................................................................3

2. A Brief Introduction to TRIM.FaTE Input Requirements.......................................................3

2.1 TRIM.FaTE Input Files and Contents.........................................................................3

2.2 Recommended Sequence of Activities for TRIM.FaTE Set Up...................................4

3. Meteorological Data Development ......................................................................................5

3.1 The Role of Meteorological Data in TRIM.FaTE.........................................................5

3.2 Summary of Meteorological Parameterization in TRIM.FaTE.....................................5

3.3 Required Meteorological Parameters and Data Time Steps.......................................6

3.4 Selecting Appropriate Surface and Upper-air Data ....................................................7

3.5 Replacing Missing Data .............................................................................................8

3.6 Aggregate and Duplicate .........................................................................................10

3.7 Plume Rise ..............................................................................................................10

4. Air and Surface Parcel Design ..........................................................................................11

4.1 The Role of Spatial Layouts in TRIM.FaTE..............................................................11

4.2 Theoretical Considerations Influencing Parcel Design .............................................11

4.2.1 Cross-Wind Dispersion..............................................................................11

4.2.2 Numerical Diffusion ...................................................................................11

4.2.3 Shape of the Deposition Profile with Distance from Source .......................12

4.3 Empirical Evidence Relating to TRIM.FaTE Parcel Design ......................................12

4.4 Recommended Best Practices for Air and Surface Parcel Design ...........................12

5. Surface Hydrology and Erosion Property Definitions .........................................................15

5.1 Surface Parcel Chemical Transfer Dynamics in TRIM.FaTE....................................15

5.2 Estimating Runoff and Erosion Fractions without Sophisticated GIS 

Software..................................................................................................................16

5.3 Estimating Runoff and Erosion Fractions with Sophisticated GIS 

Software..................................................................................................................17

6. Compartment Properties Recommended for Site-Specific Parameterization.....................18

6.1 The Role of Properties in TRIM.FaTE......................................................................18
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6.2 Approach to Prioritizing Properties for Site-Specific Parameterization .....................18

6.3 Elimination of Properties from Site-Specific Parameterization..................................19

6.3.1 Process-based Elimination of Parameters .................................................19

6.3.2 Data Availability-based Elimination of Parameters.....................................20

6.3.3 Combination of Data- and Sensitivity-based Elimination of 

Parameters ...............................................................................................20

6.3.4 Elimination of Physical and Chemical Characteristics ................................21

6.4 Properties Recommended for Site-Specific Parameterization..................................21

7. Properties Recommended for Land Use-Based Values ....................................................22

8. Properties Recommended for National Values..................................................................23

9. The FaTEmaster Scenario Builder....................................................................................24

10. Potential Future Improvements .........................................................................................24

References ...............................................................................................................................25

Appendix A. Documentation of Empirical Analyses Used to Prioritize TRIM.FaTE 

Properties .......................................................................................................................A-1

Appendix B. TRIM.FaTE National Property Values .................................................................B-1

Appendix C. The FaTEmaster Scenario Builder Tool ..............................................................C-1
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TABLES

Table 3-1. Meteorological Parameters Required for Meteorology Input File for 

TRIM.FaTE...........................................................................................................6

Table 3-2. Potential Sources of Hourly Surface Meteorological Data (not allinclusive)...............................................................................................................9

Table 6-1. TRIM.FaTE Properties Recommended for Site-Specific 

Parameterization.................................................................................................22

Table 7-1. TRIM.FaTE Properties Recommended for Land use-Specific 

Parameterization.................................................................................................23
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DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft 1 February 2014

1. Introduction

This document presents a protocol for developing TRIM.FaTE scenarios in support of site-specific risk 

assessments conducted within the RTR program using the TRIM.FaTE environmental fate and transport 

model.

This section describes the regulatory context, intended purpose of the protocol, the scope and limitations 

of the protocol, and some caveats to its use. It also presents a road-map to the content and structure of 

this document.

1.1 Regulatory Context and Approach to Risk Assessment for PB-HAPs

Section 112 of the Clean Air Act (CAA) directs the U.S. Environmental Protection Agency (EPA) to assess 

the risk remaining (i.e., residual risk) from emissions of persistent and bioaccumulative hazardous air 

pollutants (PB-HAPs) following the implementation of maximum achievable control technology (MACT) 

standards for emission sources. Such risk assessments for various emission source categories are a 

major component of EPA’s Risk and Technology Review (RTR) program.

To evaluate ingestion exposures and human health risks for RTR on a source category basis, an iterative 

approach is currently employed. The approach enables EPA to confidently screen out PB-HAP emissions 

unlikely to pose health risks above levels of concern (i.e., a cancer risk exceeding 1-in-one million or a 

non-cancer hazard quotient exceeding 1

1

) and to focus additional resources on sources of greater 

concern within the category.

Two models are used to estimate ingestion exposure and ingestion risk in the RTR program:

 The Fate, Transport, and Ecological Exposure module of EPA’s Total Risk Integrated Methodology 

(TRIM.FaTE) is used to model the fate and transport of pollutants released to the environment; and

 The Multimedia Ingestion Risk Calculator (MIRC) is used to estimate transfer and uptake into the food 

chain and exposure to receptors consuming contaminated food products and soil. A subset of media 

concentration estimates from TRIM.FaTE serve as inputs to MIRC, which also depends on other 

exposure and biotransfer-related input parameters.

The RTR approach is divided into three steps of increasing refinement:

1. Tier 1 of the approach identifies facility-level emissions of PB-HAPs within a source category and 

compares them to risk-based emission thresholds.

2. Tier 2 uses the actual location of the facility emitting PB-HAPs to refine a subset of the assumptions 

associated with the modeled Tier 1 environmental scenario while maintaining the Tier 1 ingestion 

exposure scenario assumptions; and

3. The final step, for facilities that cannot be ruled out based on the Tier 1 and Tier 2 screening process, 

is to conduct a more refined assessment, up to and sometimes including site-specific multipathway 

risk assessment. A site-specific risk assessment is intended to incorporate location- or facility-specific 

characteristics regarding the environment to which PB-HAPs are emitted, relevant exposure 

pathways, ingestion rates or other exposure factors, and other parameters. Site-specific risk 

assessments undertaken in the past as part of the RTR process have involved extensive literature 

searches for model parameters and required more time and resources to complete than the Tier 1 

and Tier 2 screening analyses.

 

1

EPA considers “cancer risks exceeding 1-in-one million” to refer to risks of at least 1.5-in-one million, and “noncancer hazard quotients exceeding 1” to refer to hazard quotients of at least 1.5.
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

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1.2 Purpose of this Protocol

The site-specific protocol presented in this document is intended to serve as a guiding framework to set 

up and parameterize scenarios in TRIM.FaTE that support accurate and cost-effective site-specific risk 

assessments as part of the RTR framework.

The purpose of the protocol is to develop a standard set of guidelines and recommendations for 

conducting site-specific assessments, providing a streamlined and replicable framework for configuring 

and parameterizing the TRIM.FaTE model. The protocol aims to balance modeling accuracy with costeffectiveness in implementation, and to facilitate consistency and transparency across diverse 

assessments. This protocol is also intended to function as part of the technical documentation for future 

site-specific residual risk assessments by providing a clear and transparent description of the approach to 

parameterization and some of the relevant sources. Deviations from this protocol would need to be 

documented on a case-by-case basis. This document also provides guidance on ICF’s FaTEmaster 

Scenario Builder tool and discusses how that tool can be used to support site-specific risk assessments 

using the TRIM.FaTE model.

1.3 Scope and Limitations

The site-specific protocol presented in this document focuses on the fundamental aspects of setting up a 

scenario in TRIM.FaTE from an RTR perspective. While the TRIM.FaTE User’s Guide (U.S. EPA 2005) 

provides guidance on the mechanistic aspects of designing a simulation, the protocol focuses on 

identifying best practices that optimize model set-up efficiency while maintaining a high level of model 

precision in the RTR context.

These best practices have been developed with a focus on the impact of alternative model configuration 

and parameterization approaches on ingestion risk in the RTR process. Thus, if two alternative model 

configuration approaches are estimated to have similar impacts on risk estimates in the RTR process, the 

protocol will recommend the less effort-intensive approach where appropriate. For instance, the protocol 

identifies only a limited set of TRIM.FaTE model properties as requiring site-specific parameterization, 

while proposing land use-specific or nationally representative or health protective values for others based 

on the finding that relatively few model parameters substantially influence risk in the RTR context.

However, the protocol is not driven exclusively by considerations of cost-effectiveness. In some 

instances, the protocol aims to provide superior methods of model configuration based on model 

accuracy and scientific considerations that were previously not clearly articulated in available TRIM.FaTE 

guidance, and that have a focus on the RTR program.

This protocol is not intended to serve as a substitute for the TRIM.FaTE User’s Guide (U.S. EPA 2005) or 

the TRIM.FaTE Technical Support Document (U.S. EPA 2002). It is not step-by-step guide to running the 

model. It is recommended that the protocol be read in conjunction with the User’s Guide and the 

Technical Support Documentation to provide a holistic perspective on how the model should be used in 

site-specific RTR applications.

1.4 Caveats

The findings and recommendations presented in this document are subject to several caveats:

 Some of the conclusions presented in this protocol are based on a combination of available empirical 

evidence, theoretical considerations, and expert judgment. A “brute-force” empirical approach to test 

an extensive range of scenarios and parameters was not feasible.

 For some model parameters, ICF relied on sensitivity analyses performed on previous configurations 

of the model. It is possible that the results of previous sensitivity analyses differ slightly from the 

current Tier 1 model configuration.

 ICF did not test the sensitivity of model parameters in alternative model configurations; and 
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Working Draft 3 February 2014

 ICF did not research and identify land use-specific parameter values for soil properties values as part 

of this protocol, although it recommends their use.

Despite these limitations, the current recommendations are expected to meet the objectives of providing a 

cost-effective and accurate approach to site-specific risk assessment in the RTR program. However, 

users are encouraged to extend site-specific model design and parameterization beyond the levels 

proposed here as circumstances permit.

1.5 Protocol Road Map 

This protocol contains the following types of information:

 best practices for TRIM.FaTE model configuration for use in site-specific RTR applications;

 documentation of the rationale for best practice recommendations;

 nationally representative or health protective model parameter values for site-specific applications of 

TRIM.FaTE; and

 a guide to the FaTEmaster Scenario Builder tool to create input files for TRIM.FaTE.

These distinct elements are woven together in the following structure:

 Section 2 sets the context with a summary of TRIM.FaTE input files and their content;

 Section 3 discusses the model’s meteorological data requirements, potential data sources, 

approaches to address missing data, data processing requirements, and the issue of plume rise;

 Section 4 presents recommendations and rationale for best practices for designing air and surface 

parcels in TRIM.FaTE;

 Section 5 presents recommendations and rationale for best practices for defining surface hydrology 

and erosion parameters required by TRIM.FaTE;

 Section 6 identifies parameters recommended for site-specific parameterization;

 Section 7 identifies parameters recommended for land-use specific parameterization;

 Section 8 identifies parameters recommended for national default parameterization;

 Section 9 presents a guide to using ICF’s FaTEmaster Scenario Builder tool in site-specific RTR 

applications; and

 Section 10 discusses potential future improvements and enhancements to the protocol.

2. A Brief Introduction to TRIM.FaTE Input Requirements

TRIM.FaTE is a spatially and temporally explicit multimedia environmental fate and transport model that 

estimates the concentrations of emitted chemicals in biotic and abiotic environmental media. The model 

uses a compartmental box model approach to track the movement of chemicals in environmental media. 

The model is based on representing environmental media as compartments, moving chemical mass 

between interacting compartments consistent with a set of governing mathematical algorithms that 

describe environmental physical and chemical processes, and assuming instantaneous mixing within 

each compartment.

2.1 TRIM.FaTE Input Files and Contents 

TRIM.FaTE requires a variety of inputs from users to define the modeled environment and to quantify the 

various environmental mass transfer processes. These inputs are provided to the model in the form of the 

following files:
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 A “volume elements” file defines the spatial layout of the modeled domain in terms of threedimensional abiotic compartments. Each volume element provides a frame of reference for one or 

more biotic compartments within it.

 A “compartments” file places biotic and abiotic compartments (modeling unit containing chemical 

mass) within the volume elements.

 A library file contains all the model algorithms, properties, and emission source information. Examples

of the kinds of properties that are defined in the library file include:

– scenario characteristics (e.g., start/stop time, modeling time parameters, output options);

– source characteristics (e.g., chemicals emitted, location, emission rate);

– chemical-specific properties, including physical-chemical (e.g., molecular weight, Kow) and abiotic 

chemical-specific (e.g., degradation half-life);

– non-chemical-specific characteristics of biota (e.g., body weight, food intake rate);

– site-specific ecological setting data and characteristics of biota (e.g., type of species present, 

population and density information, food web relationships); and

– abiotic environmental setting data such as abiotic media characteristics (e.g., air/water content of 

soil, pH of surface water, suspended sediment density), runoff/erosion fractions for adjacent 

surface soil compartments, and water flow between connected surface water compartments.

 A properties file typically contains: (i) simulation- and site-specific property values that are used to 

overwrite default library values, and (ii) the location of time-varying input files for parameters such as 

meteorological and vegetation parameters.

These input files must be developed using syntax that is consistent with TRIM.FaTE requirements. ICF’s 

FaTEmaster Scenario Builder tool, discussed further in Section 9, provides a spreadsheet-based 

interface that facilitates the automated generation of syntactically accurate TRIM.FaTE input files from 

user-specified inputs. Further detail on the required syntax of the input files, and the process of setting up 

and running the model using these input files, is available in the TRIM.FaTE User’s Guide (U.S. EPA, 

2005).

Much of the challenge in a site-specific TRIM.FaTE application lies in designing a spatial layout that is 

consistent with the nature of the governing algorithms and that reflects the environmental dynamics of the 

modeled domain, researching and estimating numerous environmental properties that serve as inputs 

into the model, finding and preparing appropriate meteorological and climate-related data, and setting up 

the input files. The following sections will discuss the optimal methods of performing these tasks from the 

perspective of a site-specific RTR application.

2.2 Recommended Sequence of Activities for TRIM.FaTE Set Up

The following sections of this document focus on various aspects of TRIM.FaTE set up as discrete 

elements in the model configuration process. There are, however, interconnections between the research 

required to guide various components of the set up process. Although there are no firm rules governing 

the order in which the model’s input files must be developed, this protocol recommends a sequence of 

activities as a means to enhance efficiency and accuracy in the model configuration process:

1. Perform qualitative spatial analyses of topography, hydrography (boundaries of watersheds, flow

lines), and land cover around the site. This will aid in identifying meteorology data, identifying

modeled lakes and farms or potential farmland, and shaping the model domain;

2. Identify meteorological data based on RTR considerations (e.g., what meteorology did the RTR 

inhalation risk assessment use for the site?), data availability, data quality, and the 

representativeness of the data and instrument siting with respect to the modeled facility. Further,
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create the meteorological file and use the meteorological data and emission source parameters to 

estimate plume rise where necessary;

3. Identify lakes to model based on lake size and a preliminary assessment of risk potential and data 

availability;

4. Identify farms or potential farmland to model based on a preliminary assessment of risk potential and 

data availability;

5. Create spatial layout;

6. Estimate and define surface hydrology and erosion dynamics within the layout;

7. Gather data on site-specific properties per the protocol;

8. Enter input property data into FaTEmaster Scenario Builder tool;

9. Generate TRIM.FaTE input files; and

10. Run TRIM.FaTE.

3. Meteorological Data Development

3.1 The Role of Meteorological Data in TRIM.FaTE

The algorithms that simulate the advection of chemicals between the air compartments and the 

simultaneous deposition of chemicals to the underlying surface compartments depend on numerous 

meteorological parameters such as wind speed, wind direction, mixing height, and rainfall rate, amongst 

others. Sensitivity analyses have indicated that meteorological parameters are among the most risk 

influential parameters in the TRIM.FaTE model (U.S. EPA 2009). Previous evaluations have also 

suggested that the effects of these parameters are important in TRIM.FaTE, favoring the use of timevarying meteorological data at the temporal resolution at which the measurements are reported, rather 

than data averaged over longer time periods.

For these reasons, it is recommended that all meteorological parameters be site-specific. This accounts 

for the potential interactive effects between meteorological parameters. The meteorology data should also 

be hourly, where possible—averaging to coarser time steps can obscure real trends in the data.

This section discusses best practices in incorporating site-specific meteorological parameters in 

TRIM.FaTE applications.

3.2 Summary of Meteorological Parameterization in TRIM.FaTE

The following steps, discussed in greater detail in subsequent sections, serve as a general guide to 

generating TRIM.FaTE meteorology input data in RTR site-specific applications:

1. Determine the meteorology time step to be used (e.g., hourly, n hours per day, daily, etc.). Surface

meteorology data available from federal agencies is typically hourly. Longer time steps reduce model 

run time but can obscure real and significant trends in the data. Hourly values are recommended;

2. If it is appropriate to use the same meteorology data used in RTR inhalation risk assessments, obtain 

those data. Otherwise, identify the source(s) of meteorology data that meet the following criteria:
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The data contain all the meteorology fields required by TRIM.FaTE. Note that upper-air 

radiosonde data do not contain mixing height values. Mixing height values must be calculated, 

typically using a combination of surface and upper-air data (see Bullet 3 below);.

a. The data have no more than 10 percent missing data for any of the meteorology fields required 

by TRIM.FaTE; and

b. The data are as representative as possible of the area being modeled.

3. If necessary, use a meteorological preprocessor or other method of estimating mixing heights at the 

desired time step (upper-air data is typically measured twice daily with a radiosonde and does not 

include mixing heights);

4. Replace all missing data with values that are as reasonable as possible;

5. If desired (although not recommended), aggregate the meteorology data to larger time steps. Then, 

replicate the data as needed to create a meteorology input file that covers the entire period of 

modeling; and

6. The combination of emission source characteristics (e.g., exit gas temperatures and velocities) and 

meteorological characteristics (e.g., stability, ambient temperature) might lead to significant emission 

plume rise during some time steps. In these cases, the user may use the emission source 

characteristics and meteorology data to estimate plume rise values.

3.3 Required Meteorological Parameters and Data Time Steps

TRIM.FaTE meteorology data must include the fields in Table 3-1. Mixing heights are not part of observed 

surface meteorology data. Mixing heights can be manually estimated using a vertical profile plot of upperair data from radiosondes, though the typical method of calculating mixing heights relies on using surface 

and upper-air observed data in a meteorological processor such as AERMOD’s meteorological processor 

(AERMET) or the U.S. EPA mixing height program. These meteorological processors, sources of surface 

and upper-air data, and sources of pre-calculated mixing heights are discussed in Section 3.4.

Surface meteorology data are typically available in hourly time steps, with some wind data available at 

smaller time steps. Upper-air data from radiosondes are typically available twice per day. These data time 

steps (hourly for surface data, twice-daily for upper-air data) are typically required by meteorological 

processors to estimate hourly mixing height values. The TRIM.FaTE meteorology data file does not 

require hourly time steps, although hourly data are typically used in site-specific assessments. Larger 

time steps will shorten model run time. The aggregation of data into larger time steps (although not 

recommended) should take place after mixing height values are determined.

Table 3-1. Meteorological Parameters Required for Meteorology Input File for TRIM.FaTE

Parameter Format Units Further Description and Notes

Date M/D/YYYY NA NA

Hour Numeric NA NA

Time Zone e.g., “EST” NA NA

Horizontal Wind 

Speed

Numeric m/s NA
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Parameter Format Units Further Description and Notes

Wind Direction Numeric degrees degrees clockwise 

from north; blowing 

from

e.g., from north is 360 degrees; from 

east is 90 degrees; from south is 180 

degrees; and so on. 0 degrees is 

reserved for calm winds (e.g., wind 

speed = 0 m/s)

Air Temperature Numeric K NA

Mixing Height Numeric m Not an observed parameter. Must be 

calculated, typically using a 

meteorology processor with surface 

and upper-air data inputs.

Rain Rate Numeric m/day NA

Cumulative Rain Numeric m Total precipitation in a precipitation 

event. A multi-hour event will have 

equal cumulative rainfall values for 

each hour.

Is Day Boolean (i.e., 1 or 

0)

NA Daytime (value of 1; after sunrise) or 

nighttime (value of 0; after sunset). 

Calculated using U.S. EPA’s SRSS.exe program, available with 

TRIM.FaTE.

3.4 Selecting Appropriate Surface and Upper-air Data

RTR inhalation risk assessments match a facility with the Automated Surface Observing Station that is 

closest to the facility and that has relatively complete data for one recent year (that year is currently 

2011). That surface station is coupled with its closest, regularly reporting upper-air station. Unless 

meteorology data were measured at the facility itself, it is usually appropriate to use those same 

meteorology stations for RTR ingestion risk assessments, subject to EPA discretion and the availability of 

good quality data for multiple recent years. 

Surface and upper-air radiosonde data can be obtained from the National Climatic Data Center (NCDC), 

regional climate centers, and third party vendors. Some sources of hourly surface meteorological data 

across the United States are shown in Table 3-2. These data sources are shown with generally the more

current and more spatially dense data (i.e., the large and freely available Integrated Surface Hourly data) 

listed first. Some state agencies also maintain their own station networks and might be good sources of 

meteorology data.

Twice-daily upper-air radiosonde data from stations operated by federal agencies can be obtained for free 

from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory 

(ESRL) in Forecast Systems Laboratory (FSL) format for over 100 U.S. stations and for 1994 through 

present, where available (ESRL 2011). ESRL also has archived FSL-formatted upper-air data going back 

to 1946, available for purchase on disc. Mixing heights are not part of observational data. Hourly mixing 

heights can be manually estimated or they can be calculated using a combination of surface and upperair data. Typically, these hourly mixing height calculations are performed in a meteorology data 

preprocessor such as AERMET (U.S. EPA 2012a). AERMET accepts some of the surface meteorology 

data formats presented in Table 3-2 and FSL-formatted upper-air data. Pre-calculated, twice-daily mixing 

height data also are available from U.S. EPA for over 70 U.S. stations for 1984 through 1991 (U.S. EPA 

2010a) and can be used in the computer version of the meteorological processor for the Regulatory Air 

Model (PCRAMMET; U.S. EPA 2012c).
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The user should select appropriate data based on proximity of the station to the modeling site and on the 

station site’s representativeness of the modeling site (e.g., elevation, land use, and wind flow). Evaluating 

the representativeness of the site and data is subjective. The surface and upper-air stations closest to the 

modeling site often will be the best choices. Because the upper-air station network is much sparser than 

the surface network, proximity might be a less restrictive criterion in choosing upper-air stations compared 

to choosing surface stations. Instead, it might be more important to choose an upper-air site that 

experiences boundary layer characteristics that are similar to those of the modeling site. For example, if 

the modeling site is well inland, it might not be appropriate to use an upper-air station on the coast.

The availability and quality of the data must also be considered. It is typically recommended that no more 

than 10 percent of the data be missing, and the data values should be within expected bounds. The user 

should also note that some meteorological data are archived in UTC, or Zulu time, which is functionally 

the same as Greenwich Mean Time and equivalent to Eastern Standard Time plus five hours. The data 

should be converted to local standard time for use in TRIM.FaTE, and standard time must be used 

throughout the year (most archived meteorology data are in standard time).

One year of data might be sufficient, as long as the data on average are representative of recent 

climatological averages at the site. NCDC 30-year climate normals are recommended for comparison 

(NCDC 2011). When data from a single year are found to be significantly different from typical conditions, 

the user can use several consecutive years that, together on average, are closer to typical conditions.

3.5 Replacing Missing Data

TRIM.FaTE requires that there be no missing data in its meteorology fields. U.S. EPA’s recommended 

guidance for replacing missing meteorology data (U.S. EPA 1992) has a series of objective data 

replacement steps as a first pass, but those steps might not fill in all missing data. The guidance suggests 

some subjective procedures for filling in remaining missing data; however, these are manual steps and do 

not cover all possible cases of missing data (e.g., if more than a few contiguous hours of data are 

missing). A meteorologist or experienced air quality modeler should perform these subjective data fill 

procedures. The user should expect that the quality of substituted values will be worse for longer 

contiguous periods of missing data versus only a few contiguous hours of missing data. However, as long

as the amount of data originally missing is no more than 10 percent, and as long as the substituted values 

are not out of normal bounds, then substituted data will have only a small impact on modeling results—

especially for TRIM.FaTE assessments where the desired outputs are final accumulated media 

concentrations after several decades of modeling.

ICF developed a tool (AERMET2TRIM), based in Microsoft Access, that fills in missing data in all 

meteorology fields needed by TRIM.FaTE. The procedures are based on those provided in U.S. EPA 

(1992). AERMET2TRIM requires first that AERMET be run on the surface and upper-air data in order to 

estimate hourly mixing heights. AERMET2TRIM then reformats the data into the format required by 

TRIM.FaTE.
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Table 3-2. Potential Sources of Hourly Surface Meteorological Data (not all-inclusive)

Name Notes on Measured 

Data Years Available Spatial Coverage Source Other Notes

Integrated Surface 

Hourly (ISH) Data

NA Over 100 years to 

today, where 

available

Thousands of 

stations 

worldwide

NCDC (2008) Available in two formats -- abbreviated 

and full. AERMET requires the full format. 

The availability and structure of the 

formats have changed through the years 

and through the different available data 

storage media.

Free via online download.

Quality Controlled 

Local Climatological 

Data (QCLCD)

NA 2005 to today Approx. 1,600 

U.S. stations

NCDC (2013) Free via online download.

U.S. EPA AERMODformatted data for the 

Human Exposure 

Model (HEM-3)

Not strictly observational 

data – processed 

observational data 

through AERMOD's 

preprocessors to produce 

AERMOD-ready format.

2011 only Over 800 U.S. 

stations

U.S. EPA 

(2013)

Free from EPA.

Solar and 

Meteorological 

Surface Observation 

Network (SAMSON)

NA 1961 through 1990, 

where available

Approx. 237 

U.S. stations

NCDC (2012) File formats changed after approx. 2007.

Available for purchase on disc.

U.S. EPA Support 

Center for Regulatory 

Atmospheric 

Modeling (SCRAM)

No precipitation data 

(request DSI-3240 format 

precipitation data from 

NCDC)

1984 through 1992, 

where available

Approx. 250 

U.S. stations

U.S. EPA 

(2010b)

DSI-1440 format.

Free via online download.
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3.6 Aggregate and Duplicate

If desired (though not recommended), the user should aggregate the data to conform to the modeling 

time step being used. Values of wind speed, air temperature, mixing height, and rain rates should be 

averaged. For wind direction, the hourly values of wind speed and wind direction should be used to 

calculate the vector components of the wind (i.e., u and v values), those vector components should be 

averaged, and the averaged vectors should be used to calculate the average wind direction. Calculate 

new cumulative rain values after averaging the rain rates. Use professional judgment to determine 

appropriate values for the “Is Day” parameter.

Previous site-specific assessments conducted using TRIM.FaTE typically have used 50-year modeling 

periods. The meteorology data in TRIM.FaTE format should be duplicated as necessary to produce a 50-

year data period (or other appropriate time period that matches the facility lifetime/emissions period 

selected during the initial assessment planning stage). For example, if the meteorology data represent 

years 2008 through 2011, the user should copy-and-paste that four-year period to create 50 years of data 

(e.g., 2000 through 2049). The user should make sure that the year values are changed appropriately, 

and that leap years contain data for February 29. If the user’s original meteorology data do not contain a 

leap day, simply duplicate data from February 28 and label as February 29.

3.7 Plume Rise

Emission plumes in nature usually have a vertical component to their dispersion pattern (i.e., plume rise). 

Multiple forces can affect vertical dispersion, including the temperature of the plume compared to the 

ambient air temperature, the wind speed at the release point, the ambient vertical temperature gradient, 

atmospheric stability, the diameter of the release point, and the temperature and velocity of the emissions 

as they exit the release point.

TRIM.FaTE does not calculate plume rise. Instead, emitted chemicals are advected horizontally through 

fully mixed air compartments whose dimensions are defined by the user. This advection occurs in one of 

two air volume compartments—the mixing layer compartment (where people, plants, animals, soil, and 

water are exposed to the chemicals) or the upper-air compartment above the mixing layer (where the 

chemicals are removed from ground-level exposure; i.e., a sink). Because an emission source’s release 

height is static, the mixing height for a given modeling time step determines which air layer the chemicals 

are emitted into in that time step.

AERMET2TRIM has a function that estimates hourly plume rise given the physical parameters of an 

emission source (i.e., latitude-longitude coordinates, release point height and diameter, and exit gas 

temperature and velocity), the horizontal distance from the source at which to estimate the plume rise

(i.e., the radius of the modeled source parcel), and the meteorology data being used for the TRIM.FaTE 

analysis. Because AERMET output data do not contain cloud ceiling heights, the AERMET2TRIM plume 

rise calculations require a supplementary file containing those data (such ceiling data are available in ISH 

and SAMSON data, for example). These plume rise estimations are based on methods summarized by 

Seinfeld and Pandis (1998). The output from this function is a text file with hourly values for effective 

release height, which is the actual release height plus the hourly plume rise value. If desired, the user can 

then aggregate the data to the time step being modeled.

Including hourly effective release heights will increase model runtime. In previous TRIM.FaTE site-specific 

assessments, a 5% rule has been used to judge whether or not to use hourly heights; that is, if the 

effective release height was above the mixing height less than 5% of the time, hourly heights were not 

used (i.e., the static, physical stack height was used). The user also has the option to estimate an 

average effective release height for the entire modeling period, and simply use that average height as the 

release height for all modeling times.
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4. Air and Surface Parcel Design

4.1 The Role of Spatial Layouts in TRIM.FaTE

One of the primary inputs required by the TRIM.FaTE model is the specification of a spatial layout using 

Cartesian coordinates to define the vertices of surface and air parcels and volume elements. This 

information is input into the model via the “volume elements” input file. To construct the volume elements 

input file, users are required to divide the modeled domain into two-dimensional air parcels and surface 

parcels. Air and surface parcels need not line up in all cases. Each parcel is also associated with a 

height, which may vary in time. The parcel coordinates and height are combined to define threedimensional abiotic volume elements that contain biotic and abiotic compartments used to model the 

movement of chemical mass in TRIM.FaTE.

In a site-specific assessment, the spatial layout should capture the features of interest (e.g., farms or 

lakes) at the surface level and also specify how the overlying air domain is to be divided to produce 

accurate and informative estimates. Although the TRIM.FaTE User’s Guide (U.S. EPA 2005) provides 

useful mechanistic guidelines and rules of thumb on the design of air and surface parcels, those 

recommendations are not specific to the RTR context and are not based on an ingestion risk perspective. 

The following guidelines, as noted in the introduction to this document, are intended to support sitespecific risk assessments in the RTR program and should be considered in addition to the instructions 

and recommendations provided in the User’s Guide and Technical Support Document (U.S. EPA 2002).

4.2 Theoretical Considerations Influencing Parcel Design 

Discussed below are the theoretical considerations related to the TRIM.FaTE model that were used to 

inform the air and surface parcel design recommendations presented later in this section.

4.2.1 Cross-Wind Dispersion

TRIM.FaTE models the movement of chemical mass based on first-order differential equations. 

Consequently, the model does not account for dispersive processes in air that carry mass in a cross-wind 

direction. Air parcel design must be conscious of, and attempt to compensate for, this limitation of the 

TRIM.FaTE model. For instance, using a square grid for air parcels may result in “pipeline flow” with the 

bulk of the emitted chemical concentrated in a compartment directly downwind. The concentration 

estimates based on such a design would not align well with empirical evidence or with theoretical 

Gaussian plume models that are based on the second-order advection dispersion equation.

Although a compartmental model with instantaneous mixing (such as TRIM.FaTE) could never produce 

identical spatial results to a Gaussian plume model, air parcel design in TRIM.FaTE must attempt to 

ensure that an appropriate amount of lateral dispersion is permitted to occur. The Pasquill-Gifford 

estimates of cross-wind dispersion are commonly applied as parameters in air dispersion models for 

alternative atmospheric conditions (U.S. EPA 1995). These cross-wind dispersion estimates are in the 

form of graphs which plot cross-wind dispersion as a function of downwind distance. The Turner 

equations are mathematical representations of these plots. A plot of the Turner equations, which 

numerically approximate the Pasquill-Gifford estimates of cross-wind dispersion, suggests that 99% of the 

emitted mass in neutral atmospheric conditions is likely to be contained within a cone subtending an 

angle of 20 degrees from the source, assuming a constant wind direction through the centerline. This 

provides a guideline about the ideal breadth of air parcels, especially those downwind of features of 

interest.

4.2.2 Numerical Diffusion

All compartmental models potentially experience the issue of “numerical diffusion,” which refers, in the 

context of an air dispersion model, to the propagation of mass further downwind at a given point in time 

than is physically possible given the wind speed. Maintaining a fixed relationship between the size of the 
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time step used in the simulation, the length of compartments, and the wind speed helps prevent issues of 

numerical diffusion. Users interested in strict time accuracy are advised to ensure that compartment 

lengths are shorter than the wind speed multiplied by the model time-step. For RTR purposes, however, 

average annual values in the 50th year are of primary interest, and strict restraints on parcel length for a 

given time-step are considered less important but still good practice to implement.

4.2.3 Shape of the Deposition Profile with Distance from Source

The TRIM.FaTE model produces a deposition profile that has the largest values in the source 

compartment and decreases with increasing distance in a pattern similar to an exponential curve. 

Theoretical and empirical evidence suggests, however, that the maximum deposition rate would not be 

experienced at the point of emission, but further downwind. At a wind speed of 5 m/s, the point of 

maximum deposition for fine particulates and gases was estimated to be between 1 and 5 km (Overcamp 

1976). Users of the TRIM.FaTE model should therefore be conscious of potential overestimation of 

deposition in surface parcels adjacent to the source and a potential for bias in the deposition profile.

4.3 Empirical Evidence Relating to TRIM.FaTE Parcel Design

A limited number of TRIM.FaTE scenarios were modeled to provide empirical data about the impact on 

risks (in the RTR context) from air and surface parcel layout design. Most of these scenarios were based 

on simple variations of the Tier 1 screening scenario layout. The main findings are summarized here:

 Extending an air parcel beyond the outer boundary of the underlying surface parcel (i.e., having an air 

parcel “overhang” the surface parcel beneath it) reduces deposition over the surface parcel compared 

to air parcels that are co-terminus with surface parcels (i.e., having the air parcel directly overlay the 

surface parcel);

 The number of air parcels that precede the air parcel overlying the surface feature of interest (i.e., the 

number of air parcels between the source parcel and an air parcel of interest) does not materially 

impact deposition over that surface parcel;

 Soil concentrations in the surface compartment adjacent to the source are considerably higher than if 

the same surface compartment is set back by a short distance of approximately 400m (i.e., a 400-m 

buffer parcel between the source and the parcel of interest). This is consistent with TRIM.FaTE’s 

exponential deposition gradient; and

 Increasing the length and/or breadth of a surface compartment might substantially reduce surface soil 

concentrations

More detailed results from these scenarios are documented in Appendix A.

4.4 Recommended Best Practices for Air and Surface Parcel Design

The following recommendations for air and surface parcel design are intended to maintain a high degree 

of modeling accuracy while reducing design effort and potentially optimizing computer run time. While 

these guidelines are intended to facilitate optimal parcel design, every scenario is unique and might

require site-specific adjustments beyond the suggested approach provide here. Any adjustments or 

improvements to the proposed approach should aim to be consistent with the governing principles and 

empirical evidence discussed earlier in Section 4.

Step 1: Identify Features of Interest

Several steps are recommended for identifying features of interest:

 Use geospatial data (e.g., aerial imagery, data on watersheds and water bodies, and remotelysensed land cover and crop growth) to identify features of potential interest from the RTR 

perspective, such as farms and lakes;
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– Geospatial data can include Google Earth (Google 2013), the National Hydrography Dataset 

(USGS 2013), the National Land Cover Database (MRLC 2013), and the Cropland Data Layer 

(USDA 2013).

 Consider only lakes that are at least as large as 25 acres (approx. 10 hectares)

2

and that research 

suggests are fishable; and

 Use the following guidance to finalize the selection of lakes and farms for modeling:

– Limit farms to those within roughly 5 km of the source;

– Do not select multiple farms in the same direction from the source;

– Do not select farms adjacent to the source parcel. Choose a buffer distance of at least 400 m;

– Prefer farms and lakes closer to the emission source versus those farther away;

– Prefer lakes for which preliminary research suggests good availability of modeling data (e.g., 

flush rates, depth, pH, total phosphorus levels, suspended sediment concentration);

– Prefer lakes and farms that are frequently downwind from the emission source, if they exist, 

based on the meteorology data selected for modeling; and

– Prefer the lake(s) selected in the Tier 2 screening analysis.

Step 2: Breadth of Air Parcels (Air Parcel Radials)

Several steps are recommended for defining the breath of air parcels:

1. Emissions center point: Identify the center point of what will later become the emission source parcel. 

It should roughly be the centroid of all the actual emission sources of concern at the facility;

2. Draw 20-degree radials: Manually or using geospatial software, overlay radials that intersect at the 

source center point, are 20 degrees apart. These radials roughly create triangles and represent 

preliminary breadth boundaries of air parcels;

3. Adjust the radial grid: Rotate the radial grid so that the maximum number of surface features of 

interest (e.g., farms and lakes) falls within single triangles;

4. Smaller features of interest: For features that fall within a single triangle, use the boundaries of the 

triangle to define the breadth dimension of the air parcel overlying the surface feature;

5. Larger features of interest: For features that fall within multiple triangles, merge and adjust the 

multiple triangles into a single triangle that fully contains the feature. For instance, if a lake subtends 

an angle of 50 degrees with respect to the source, three 20 degree triangles should be merged and 

adjusted to form a 50 degree triangle to define the breadth of the overlying air parcel. This process 

will distort the shape of the surrounding triangles (i.e., they will be greater than the suggested 20 

degrees), but that is acceptable; and

6. Areas not overlying features of interest: For air parcels not overlying any features of interest, less 

resolution is required. Merge three 20 degree triangles to create a 60 degree triangle to define the 

breadth dimension of the overlying air parcel.

 

2

Based on available data, for RTR multipathway emission screening analyses, EPA defines potentially fishable lakes 

as those larger than 100 acres, without exceeding 100,000 acres. Even a 100-acre lake is unlikely to be large enough 

to sustain harvesting the number of piscivorous fish required for the current screening ingestion rate (i.e., 373 g ww 

fillet/day). This is discussed in Section B.3.1 of Attachment B in Appendix 4 to the Risk Report. However, EPA 

includes smaller lakes (as small as 25 acres) in site-specific RTR multipathway analyses to be health protective and 

to ensure that small lakes that might be more highly contaminated than estimated by the screening analyses are not 

eliminated.
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Step 3: Define the Outer Boundaries of the Domain

Draw the outer boundaries of the domain approximately 5 km beyond the farthest feature of interest (in 

relation to the emission source), using the remaining parcel radials as the design template. This 5-km 

buffer is flexible depending on the characteristics of the nearby watersheds and how they might impact 

the runoff and erosion of chemical into the features of interest. Truncate the outer boundary of the domain 

in areas without features of interest, provided that these areas contribute much less significantly than 

other areas toward chemical runoff or erosion towards the features of interest.

Step 4: Complete Air and Surface Parcels for Features of Interest

Within the triangle overlying the feature (defined in Step 2), encase the feature within a trapezoid ( ) by 

drawing straight lines at an angle to the sides of the triangle to define the inside boundary (the side 

closest to the source) and outside boundary of the feature. The trapezoid should be perpendicular to an 

imaginary radial originating at the emission source center point; put another way, these new lines should 

be parallel to each other and perpendicular to an imaginary radial bisecting the triangle, thus creating a 

trapezoid.

Where possible, the surface parcel representing the feature of interest should coincide with the air parcel 

trapezoid described above. This might require slightly distorting the dimensions of the surface feature of 

interest, but that is a permissible approach when the shape of the feature of interest is not very different 

from the overlying air parcel trapezoid.

For irregular surface features (i.e., those whose shapes are very different from the overlying air parcel

trapezoid), create additional surface parcels as required to fill the space between the actual boundaries of 

the feature of interest and the boundaries of the overlying air parcel trapezoid. The additional surface 

parcels adjacent to the features of interest should be constructed subject to the consistency of land cover, 

terrain patterns, and/or hydrography. A single adjacent parcel should never surround another parcel 

entirely. Instead, two adjacent parcels should bound the irregularly shaped feature on either side.

Step 5: Draw Air and Surface Parcels for the Emission Source

The air and surface parcels for the emission source should line up. The source parcel should be centered 

on the center point identified in Step 2 above and should accurately reflect where chemicals of concern 

are actually being emitted at the facility (i.e., it should fully contain all of the actual emission sources of 

concern). It should be a polygon where each side connects the sides of each air parcel triangle, and each 

side is perpendicular to an imaginary radial bisecting the triangle. For example, if the air parcel triangles 

each subtend exactly 60 degrees, and if the real emission sources span a 500-m distance, then the 

source parcel would be a perfect hexagon that is centered on the emission source center point and has a 

diameter of 500 m.

Step 6: Complete Air and Surface Parcels Upwind of the Features of Interest

Within the two radials that bound a feature of interest, create a single air parcel between the feature and

the source parcel (i.e., upwind of the feature of interest). Like the air parcel above the feature itself, this 

upwind air parcel will be a trapezoid bounded by two lines that define the inside and outside boundaries 

(parallel to the inside and outside lines of the feature, relative to the emission source) and by the radials.

There should be a corresponding surface parcel that lines up with the upwind air parcel. If the upwind 

region contains several different regimes of land cover, terrain, and/or hydrography that are large relative 

to the region, then divide the surface parcel into separate parcels for each of those different, major 

regimes. For example, for an upwind surface parcel oriented north-south, if the northern half contains 

urban land cover and the southern half is a deciduous forest, then it might be reasonable to divide the 

parcel into a northern parcel (with no vegetation) and a southern parcel (with deciduous forest). On the 

other hand, if the region is a scattered mix of forested and pasture/hay land cover, it would not be 

reasonable or efficient to create many very small parcels for each small area of forest or pasture/hay.

Step 7: Air and Surface Parcels Downwind of the Features of Interest
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Create an air parcel downwind of the feature of interest (i.e., on the side of the feature opposite the 

emission source) with a length dimension no larger than 5 km. The relative small size of this downwind 

parcel increases the accuracy of chemical transfer via runoff and erosion.

There should be a corresponding surface parcel that lines up with the downwind air parcel. If the 

downwind region contains several different regimes of land cover, terrain, and/or hydrography that are 

large relative to the region, then divide the surface parcel into separate parcels for each of those different, 

major regimes. 

Step 8: Complete Air and Surface Parcels Crosswind of the Features of Interest

Several considerations are recommended for defining air parcels crosswind of features of interest (i.e., 

parcels to the “left” and “right” of the feature, relative to the emission source):

 The outside boundary of an air parcel immediately crosswind of a feature of interest should not 

extend beyond the outside boundary of the feature itself (i.e., the outside boundaries of the feature 

parcel and the crosswind parcel, relative to the emission source, should connect). This is to increase 

the accuracy of chemical transfer via runoff and erosion;

 The breadth dimensions of a crosswind air parcel should be defined by the radial grid. That is, the 

“left” and “right” sides of the crosswind parcels (relative to the emission source) should be defined by 

the radial grid developed in Step 2 above;

 The inside boundary is the source parcel, unless there is already a parcel drawn between the source 

and the crosswind parcel (i.e., a parcel related to a different feature of interest); and 

 There should be a corresponding surface parcel that lines up with the crosswind air parcel. If the 

crosswind region contains several different regimes of land cover, terrain, and/or hydrography that 

are large relative to the region, divide the surface parcel into separate parcels for each of those 

different, major regimes.

Step 9: All Other Air and Surface Parcels 

All other air and surface parcels should be fitted within the boundaries defined by: (i) the air parcel radials

(Step 2); (ii) the boundaries of the features of interest and their upwind, downwind, and crosswind 

neighbors (Steps 6-8); and (iii) the outer boundaries of the domain (Step 3). These other air and surface 

parcels are subject to continuity of land cover, terrain, and/or hydrography, as discussed in the above 

steps.

5. Surface Hydrology and Erosion Property Definitions

5.1 Surface Parcel Chemical Transfer Dynamics in TRIM.FaTE 

The TRIM.FaTE model incorporates the ability to account for chemical transfers between adjacent 

surface parcels via runoff and erosion. The algorithms that model surface runoff and erosion in 

TRIM.FaTE simulate the advective chemical transfer dynamics between surface parcels without requiring 

spatial elevation information or land-cover details as inputs. Instead, the algorithms depend on inputs 

explicitly specifying the destination of erosion and runoff from a specific parcel. In other words, for each 

surface parcel, users must specify the proportion of the erosion and runoff originating in that parcel that 

reaches specific adjacent parcels. These inputs are known as link properties in TRIM.FaTE and are 

typically specified in the TRIM.FaTE “properties” file discussed in Section 2. Users must also separately 

specify the average runoff and erosion rate for each surface parcel. These inputs are combined internally 

with estimates of the chemical concentration in surface soil and soil water to estimate mass transfers that 

occur in conjunction with erosion and runoff processes.

The inter-parcel runoff and erosion parameter inputs in TRIM.FaTE are inherently site-specific because 

there is no logical default value for the percentage of runoff and erosion from one parcel that reaches an 

adjacent parcel. Simulations indicate that ingestion risk in the RTR process is sensitive to the choice of 
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these values (refer to Appendix A). This section discusses options for parameterizing these inputs in sitespecific TRIM.FaTE applications for RTR.

For users not having access to (or expertise in using) geographical information systems (GIS) software 

with features to quantitatively analyze surface hydrology and erosion, the recommended method of 

estimating parcel-to-parcel runoff/erosion fractions is summarized in Section 5.2. If sophisticated GIS 

software with features to analyze surface hydrology and erosion based on elevation is to be used, the 

recommended method is summarized in Section 5.3.

5.2 Estimating Runoff and Erosion Fractions without Sophisticated GIS Software

Without a license for sophisticated GIS software, the user can still obtain free GIS viewing tools that allow 

the user to display multiple layers of geospatial data and that have limited interaction with the data, 

including querying the data and measuring distances. With such viewing software, the method for 

estimating runoff/erosion fractions provided in Module 11 of the TRIM.FaTE User’s Guide (U.S. EPA 

2005) is appropriate. This method is summarized briefly here, with some additional tips not provided in 

the User’s Guide.

Step 1: Assemble Hydrological and Elevation Data

The user should obtain geospatial data indicating boundaries of hydrological units relevant to the 

modeling domain. These hydrological data are available from the U.S. Geological Survey (USGS) 

National Hydrography Dataset (NHD; USGS 2013). These hydrography data should already have been 

obtained and used to inform the design of the modeling parcels. The NHD offers several levels of 

hydrological units, typically from regions (the most spatially coarse) to subwatersheds (typically the 

highest spatial resolution). Considering that the typical site-specific TRIM.FaTE modeling domain has a 

radius less than 50 km and is divided into several surface parcels, subbasins or watersheds will usually 

offer the most appropriate resolution for use in configuring parcels and estimating runoff/erosion fractions. 

The NHD also offers directional flow lines of streams, rivers, and other hydrographic features.

The user should also obtain elevation data for the modeling domain. High resolution data are available 

from the USGS National Elevation Dataset (NED; USGS 2006). These elevation data should already 

have been obtained and used to help construct the modeling parcels. The data with the highest spatial 

resolution are not necessary; 30-m resolution usually is appropriate.

Step 2: Relate Surface Modeling Parcels to Each Other and to Hydrological Units

The user should display the modeling surface parcels along with the appropriate hydrologic unit 

boundaries from the NHD. For each parcel (“sending parcel”), do the following:

 For each hydrologic unit that occupies at least part of the sending parcel, estimate (or calculate, if 

able) the ratio [surface area of the part of the hydrologic unit that is inside the sending parcel] to 

[surface area of the sending parcel];

 Identify each neighboring parcel (“receiving parcel”), including sinks where appropriate for the sides 

of the sending parcel that lie along the outer boundary of the modeling;

 For each hydrologic unit that occupies at least part of the sending parcel, estimate or calculate the 

length of each interface between the hydrologic unit and each receiving parcel (not discussed in the 

TRIM.FaTE User’s Guide); and

 Estimate or calculate the fraction of the sending parcel’s perimeter that interfaces with each receiving 

parcel (not discussed in the TRIM.FaTE User’s Guide).

Step 3: Estimate Fraction of Runoff and Erosion

For each hydrologic unit that occupies at least part of a sending parcel, one should use NED elevation 

data and NHD flow lines to estimate the fraction of runoff that will flow from the hydrologic unit into each 
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receiving parcel and, where appropriate, into sinks outside the modeling domain. A fraction might be 0 if 

the elevation and flow lines suggest that all water in the hydrologic unit flows away from a receiving 

parcel.

The User’s Guide (U.S. EPA 2005) Section A.5 discusses runoff/erosion fractions. Although not 

discussed there, the NHD flow lines can help estimate the relative distribution of runoff from a sending 

parcel to its receiving parcels, or from a hydrologic unit in the sending parcel to a receiving parcel. One 

can examine the flow lines along each sending-receiving boundary to get a sense how much of the 

boundary has flows from the sending area to the receiving area. This information can be combined with 

information on how much of the sending area’s perimeter interfaces with the receiving area in question, 

aiding the user in developing runoff/erosion fractions. 

As discussed in the User’s Guide Sections A.5 and A.6—separately for each hydrologic unit in a sending 

parcel, multiply [the fraction of sending parcel’s area covered by the hydrologic unit] by [the runoff/erosion 

fraction from the hydrologic unit to the receiving parcel] for each of the sending parcel’s receiving parcels. 

Then, for each of these receiving parcels, sum this product across the hydrologic units. This sum provides 

the final fraction of runoff/erosion from each sending parcel to each receiving parcel. For each sending 

parcel, the fractions will sum to 1 when sinks are included as appropriate. 

Another option is to estimate the runoff and erosion fractions based on visual inspection. This approach 

does not explicitly relate the area of each hydrologic unit to each sending parcel. Therefore, it does not 

explicitly assume that water cannot cross the boundaries of hydrologic units. Like the methods described 

above, this option uses flow lines and the interfacial length between adjacent parcels. In this option, for 

each sending parcel, the user visually examines the NHD flow lines to see where (if at all) flow lines cross 

each interfacial boundary and into the receiving parcels. For each sending-receiving pair of parcels, the 

user should estimate (or measure, if possible) the length of the part of the interfacial boundary that has 

flow lines crossing into the receiving parcel. Then, divide that length by the total perimeter length of the 

sending parcel. This ratio provides the fraction of runoff/erosion from the sending parcel into the receiving 

parcel. Some professional judgment is required to subjectively adjust these fractions based on the relative 

magnitude of runoff across the various interfacial boundaries. These relative magnitudes can consider the 

overall terrain and flow patterns throughout the sending parcel (i.e., a flow into the receiving parcel with a 

relatively small fetch will likely carry less chemical into the receiving parcel than a flow with a relatively 

long fetch). 

5.3 Estimating Runoff and Erosion Fractions with Sophisticated GIS Software 

The method discussed in this section requires the use of ESRI® ArcGISTM software. The software license 

must enable the “Spatial Analyst” extension. ICF is currently developing an ArcGISTM model, coupled with 

a Microsoft® ExcelTM post-processing tool, that largely automates the below procedures.

In ArcGIS, select the “Flow Direction” tool of the “Spatial Analyst” extension. Given a raster elevation 

dataset (such as the NED), this tool will determine the flow direction of each raster cell to the steepest 

downhill neighboring raster cell. The output of this tool will be a raster, where the value of each raster cell 

will indicate the flow direction.

Then, select the “Flow Accumulation” tool of the “Spatial Analyst” extension. The input to the “Flow 

Accumulation” tool is the output of the “Flow Direction” tool described above. Separately for each input 

raster cell, the “Flow Accumulation” tool will follow the flow direction into the appropriate neighboring cell, 

and continue following the flow direction of that cell into a third cell, and so on, “connecting the dots” of 

the flow vectors until an endpoint is reached. This creates flow lines across the raster. Then, the tool 

calculates the number of these flow lines that cross each raster cell. This is the “flow accumulation” 

number produced by this tool. The flow accumulation is unitless, as it does not represent an actual

amount of water or chemical flowing from one place to another; the accumulation values should be 

viewed relative to each other.
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For each sending parcel, the user would use the combination of flow direction and flow accumulation data 

from the above tools to calculate the total flow (unitless) from the sending parcel to each receiving parcel. 

The runoff/erosion fraction from the sending parcel into receiving parcel “A” would be the accumulated 

flow from the sending parcel to receiving parcel “A” divided by the total accumulated flow from the 

sending parcel to all its receiving parcels. 

6. Compartment Properties Recommended for Site-Specific 

Parameterization 

6.1 The Role of Properties in TRIM.FaTE

The TRIM.FaTE model is dependent on hundreds of user-specified properties that describe the biotic and 

abiotic environments being modeled. Properties in TRIM.FaTE can be broadly divided into the following 

types:

 non-chemical specific properties that define biotic compartments (e.g., biomass of game fish in a 

lake, the length of a leaf on a deciduous plant),

 non-chemical specific properties that define abiotic compartments (e.g., porosity of surface soil, the 

total suspended solids concentration in a lake),

 chemical-specific properties (including system-wide chemical properties such as the Henry’s Law 

constant, the octanol-water partition coefficient, and compartment-specific chemical properties such 

as reaction and degradation rate constants in various environmental media), and

 simulation-specific properties (e.g., model run-time, model time step).

All user-defined (e.g., non-formula) properties in a TRIM.FaTE scenario can be assigned simulation- or 

site-specific values. In theory, the more properties that are assigned site-specific values, the more 

accurately the simulation will represent chemical fate and transport at that location. Following this logic, 

the user should try to find site-specific values for as many properties as possible. However, although each 

model property is potentially important in defining a particular environmental fate and transport process, it 

is apparent based on theoretical considerations and empirical evidence (i.e., analysis of model results 

and model evaluations) that there is a subset of model properties that more significantly influences the 

environmental concentrations that drive the risks of importance in the exposure scenarios evaluated in 

RTR assessments. The fact that some parameters are more influential on results is true for complex 

models in general. This is the focus of sensitivity analyses.

In previous site-specific risk assessments using TRIM.FaTE, which were conducted for RTR and in other 

regulatory applications, a substantial portion of the level of effort required to perform the assessments 

was directed towards site-specific property parameterization. One of the specific objectives of this 

protocol is to take advantage of the results of sensitivity analyses and model evaluations conducted of 

TRIM.FaTE. Based on these results, we have identified those compartment properties that are a high 

priority for site-specific parameterization, those that can be adequately represented by regional or landuse-specific default values, and those for which nationally representative or health-protective values are 

adequate. This classification scheme is intended to reduce the level of effort required to adequately 

parameterize site-specific assessments while maintaining a high level of accuracy in risk estimates for 

RTR.

6.2 Approach to Prioritizing Properties for Site-Specific Parameterization 

ICF relied on a combination of theoretical reasoning and empirical evidence to prioritize TRIM.FaTE 

properties for the purposes of this protocol. In this way, ICF was able to limit the need for “brute-force” 

empirical evaluations (e.g., comprehensive sensitivity analyses that systematically vary all or most of the 

user-defined inputs, such as those conducted prior to the 2009 SAB review (U.S. EPA 2009)) and 
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additional resource-intensive literature searches. ICF’s justification for determining that properties were 

not high priority was based on three lines of evidence:

1. ICF followed a “process”-based approach to rule out a large subset of TRIM.FaTE properties from 

the need for site-specific parameterization. This approach was founded on the idea that the 

TRIM.FaTE model produces greater than necessary resolution (in terms of the number of 

concentrations that are calculated for different environmental media types) when viewed from the 

RTR perspective. The individual human ingestion exposure scenarios evaluated for RTR rely most 

directly on results from TRIM.FaTE for surface soil compartments at the location of a farm and fish 

compartments in a lake of interest. All fate and transport processes—and the properties that 

exclusively define those processes—that do not strongly influence these concentrations can 

reasonably be ruled out from requiring site-specific parameterization. The implications of this 

approach will be discussed in greater detail below.

2. ICF also used practical considerations regarding data availability to rule out certain properties from 

site-specific parameterization. Over the course of numerous site-specific assessments and the 

parameterization of the screening scenarios, ICF has conducted literature searches on numerous 

TRIM.FaTE properties. ICF used the insight gained from these exercises to identify certain sets of 

parameters as being too data-scarce to parameterize on a site-specific basis at this time without 

expending a substantial amount of time and money (for possibly uncertain results).

3. Physical constants and physicochemical properties of the modeled PB-HAPs were also ruled out 

from site-specific parameterization based on their largely unchanging nature in the environment for 

the chemicals considered for RTR.

ICF evaluated the parameters not eliminated by the above considerations to determine which properties 

should be the focus of data collection efforts during site-specific TRIM.FaTE modeling for RTR. ICF 

conducted a limited number of evaluations and used the results of previous sensitivity analyses to decide 

which of these shortlisted parameters should be prioritized for site-specific parameterization, for land-usebased parameterization, or for regional parameterization.

Other scenario properties such as emission period and the model’s numerical integration time-step are 

typically not varied between site-specific assessments. These properties are not discussed further in this 

protocol, but are documented in Appendix B.

6.3 Elimination of Properties from Site-Specific Parameterization

6.3.1 Process-based Elimination of Parameters

The operative principle in the process-based elimination of parameters is that fate and transport 

processes that do not substantially influence concentrations of interest from an RTR perspective are less 

important to parameterize. ICF used theoretical considerations based on the evaluation of the underlying 

TRIM.FaTE algorithms, combined with empirical evidence from TRIM.FaTE simulations, to identify the 

less important fate and transport processes and eliminate the need to parameterize those processes on a 

site-specific basis. The specific processes identified as being of less importance in the RTR context and 

the underlying justification for ruling them out from site-specific consideration are listed below:

 Chemical transport via water percolation through the sub-surface soil layers (not including surface 

soil) does not affect farm soil or lake water concentrations. Theoretical considerations suggest that 

chemical, once transported into the lower soil layers, will not substantially make its way back to the 

surface compartments of interest;

 Chemical transport via sub-surface soil diffusive processes, although having the potential to transfer 

mass upwards, are not sizeable in comparison to advective transfer processes. An evaluation of 

relative mass flux in the Tier 1 screening scenario supports this assertion for all the chemicals 

evaluated; and
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 Chemical transport to the lake via horizontal groundwater flow and recharge is negligibly small 

compared to other advective chemical inputs into the lake. The relative mass flux for this process 

compared to other advective transfer processes carrying chemical into the lake in the Tier 1 

screening scenario supports this assertion for all chemicals evaluated.

Because the RTR user has no intrinsic interest in the concentrations prevailing in the lower soil layers, all 

of the above processes have been ruled out from consideration for site-specific parameterization. As a 

consequence, it is possible to rule out all sub-surface soil compartment properties from requiring sitespecific parameterization.

6.3.2 Data Availability-based Elimination of Parameters

Chemical-Specific Aquatic Biota Properties: The aquatic biota compartments in TRIM.FaTE—currently 

including benthic invertebrates and five types of fish—are characterized by several potentially site-specific 

properties that control algorithms influencing the uptake, degradation, and elimination of chemicals in the 

aquatic organisms. These chemical-specific properties include the absorption rates of chemical into each 

type of fish from surface water, elimination rates from fish digestive systems, degradation rates within the 

fish, and other parameters. In the course of parameterizing TRIM.FaTE for the screening scenario and 

conducting extensive evaluations of parameter sensitivity, it has become apparent that only a limited 

number of studies are available for several of these properties for most combinations of chemicals and 

organisms.

Although these properties may potentially differ in alternative climates and conditions, it appears unlikely 

that additional literature searches and evaluations would yield better, more appropriate site-specific 

values than the current defaults. Until such time as more studies on these properties are available, 

practical considerations suggest that these chemical-specific aquatic biota properties be ruled out from 

site-specific parameterization.

Chemical-Specific Abiotic Compartment Properties: TRIM.FaTE algorithms model chemical reaction 

and degradation processes in several abiotic compartments (e.g., surface soil). These algorithms depend 

on chemical-specific parameters such as degradation rates (or half-lives), transformation rates, and other 

properties. Literature searches conducted during previous site-specific assessments in the RTR process 

and other regulatory applications using TRIM.FaTE have suggested that data are limited for these 

properties.

These chemical properties (with the exception of oxidation, reduction, and methylation and demethylation 

rates influencing mercury) therefore are currently ruled out from site-specific consideration. The mercury 

transformation properties have been shown to be highly risk-influential as well as variable across different 

ecosystem types and conditions, and these properties are reserved for site- or land-use-specific 

parameterization in the future, subject to greater data availability and the results of additional evaluations.

6.3.3 Combination of Data- and Sensitivity-based Elimination of Parameters

Terrestrial Vegetation: The terrestrial vegetation compartments in TRIM.FaTE—currently including 

grass, coniferous forest, deciduous forest, wetland grass, and wetland forest—are not directly part of the 

RTR risk assessment calculations (i.e., chemical concentrations in these compartments are not used as 

inputs to the MIRC ingestion exposure model). However, these compartments act as sinks for chemicals 

and also transfer chemicals from air to soil via litterfall. In this way, the choice of terrestrial vegetation 

influences surface soil concentrations and, ultimately, risk.

The terrestrial vegetation compartments depend on properties such as the lipid content of leaves, wet 

density of leaves, area indices of leaves, etc. Although it is possible that these properties differ on a sitespecific basis—for instance, the characteristics of coniferous trees in Oregon are different from those of 

coniferous trees in North Carolina—these differences are not expected to have a substantial influence on 

risk. ICF’s simulations indicate that the impact on risk of alternative vegetation scenarios is limited after 
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accounting for differences in erosion regimes specific to land-use type (see Appendix A). It is expected 

that site-specific differences within a single vegetation type would be even lower.

Literature searches during previous site-specific assessments in the RTR process have indicated that 

highly intensive literature search would be required to parameterize the full range of terrestrial vegetation 

parameters required by the TRIM.FaTE algorithms. Based on the limited risk impact of terrestrial 

vegetation properties, and limited data availability at the site-specific level, these properties are currently 

ruled out from site-specific parameterization.

6.3.4 Elimination of Physical and Chemical Characteristics

Algorithms in the TRIM.FaTE model frequently depend on physical and chemical parameters, such as the 

Henry’s Law constant and the octanol-water partition coefficient, to partition chemicals between phases 

within a compartment. These properties are, by their nature, relatively unchanging across most standard 

environmental conditions for the non-ionic organic compounds currently evaluated (i.e., dioxins and 

PAHs)3. These properties are thus ruled out from requiring site-specific parameterization for the time 

being.

6.4 Properties Recommended for Site-Specific Parameterization

Following the elimination process described above, ICF identified a set of parameters for further 

evaluation based theoretical considerations as well as higher sensitivity potential displayed in previous

sensitivity analyses (e.g., U.S. EPA 2009). To estimate the risk influence of these parameters, ICF 

performed a limited set of additional sensitivity analyses. The evaluated parameters are listed below, 

grouped by compartment type:

 Air: dust load, fraction of organic matter.

 Surface Soil: unit soil loss, inter-compartment drainage and erosion fractions, soil particle density, soil 

air fraction, soil organic content, soil pH, soil water content.

 Surface Water and Sediment: suspended solids concentration, bed sediment density, suspended 

solids density, bed sediment porosity.

 Aquatic Biota: biomass of various aquatic biota compartments.

 Terrestrial Vegetation: “Allow exchange” and “litterfall” file inputs.

Unlike previous analyses, these sensitivity analyses were not based on fixed perturbations from the 

default values but instead used reasonable high and/or low bounds approximately corresponding to the 

range found in the environment. The impacts on risk were computed with respect to the Tier 1 screening 

scenario results at equivalent emission rates.

ICF extended the scope of the current analyses by also using the results of TRIM.FaTE sensitivity 

analyses conducted in previous regulatory applications and pertaining to air, surface soil, and surface 

water and sediment. Although these analyses were performed on a different version of the Tier 1 

screening scenario set up, the results are considered informative.

The specific details of the analyses conducted as part of this protocol development are reported in 

Appendix A, while other supporting evidence has been drawn from previous reports (e.g., U.S. EPA 

2009). Based on the results of these analyses, Table 6-1 contains TRIM.FaTE properties recommended 

for site-specific parameterization in the RTR process. These properties have been further classified as 

high, medium, and low priority to facilitate an appropriate allocation of available resources in the 

parameterization process.

 

3

For mercury, some analogous properties, such as the partition coefficient for mercury in the aqueous phase, do vary 

according to pH; these relationships are incorporated into the model as formula properties.
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Table 6-1. TRIM.FaTE Properties Recommended for Site-Specific Parameterization

Compartment Property Priority Remark

Surface Water Depth High Having depth as well as flush rate helps serve as 

a check on surface hydrology assumptions. Flush Rate High

Suspended Solids 

Concentration

High Attempt to find a column-averaged value.

pH Moderate Important for metals.

Algae Density Moderate May be estimated from total phosphorus 

concentrations in the absence of measured 

values.

Organic Carbon 

Fraction

Moderate Important for TCDD (U.S. EPA 2009). Data 

availability may be limited.

Water 

Temperature

Moderate Sensitive but unlikely to manifest wide range.

Aquatic Biota Biomass Moderate May be estimated from total phosphorus 

concentrations in absence of measured values.

Surface Soil pH Moderate Important for metals.

Terrestrial Biota “Allow Exchange” 

and “Litterfall” data 

files

Low These files govern how long leaves remain open 

for stomatal exchange during different times of 

the year and also when the leaves fall off the 

trees onto the surface soil. Although the impact 

of these properties has not been empirically 

tested, theoretical considerations suggest they 

will have a low impact when estimating average 

annual risks.

In addition to these values, meteorology parameters, surface hydrology and erosion-related parameters, 

and the spatial layout are fundamentally site-specific elements of a TRIM.FaTE simulation, as noted in 

the previous sections.

7. Properties Recommended for Land Use-Based Values 

In addition to the properties identified in Section 6 as desirable for site-specific parameterization, we 

identified properties that also influence risk substantially but for which the impacts on risk are expected to 

be largely captured by land use-specific parameters. In other words, for these properties, accounting for 

variations that correspond to land use is expected to adequately account for any variation in these 

parameters (to the extent that they influence risk). Additional variation in parameter values resulting from 

site-specific variations within a particular land use category is not expected to be significant. For example, 

differences in surface soil erosion (as expressed by the unit soil loss rate property in TRIM.FaTE) are 

expected to be larger between the average deciduous forest and the average parcel of tilled soil than 

between different types of deciduous forest or between different types of tilled soil. The use of land usespecific values for such properties is expected, therefore, to adequately capture their impact on risk 

estimates in the RTR process.

The rationale for identifying properties as land use-based in this protocol is a combination of risk 

sensitivity analysis (Appendix A and U.S. EPA 2009), professional judgment about the range exhibited in 
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the environment, and expected data availability at the site-specific level. For land use-specific properties, 

users performing a site-specific assessment should identify the land use type of each surface parcel in 

the FaTEmaster Scenario Builder tool. The tool would then automatically assign the appropriate land usespecific property values. It should be noted, however, that the tool is not currently parameterized with 

land-use specific property values.

Table 7-1 lists the TRIM.FaTE parameters that are recommended for land use-specific parameterization. 

These parameters are all related to the surface soil parcel and assume distinct values for each of the land 

use types modeled in TRIM.FaTE. These land use types currently include deciduous forest, coniferous 

forest, grass, agricultural soil, untilled soil, forested wetlands, and grassy wetlands. Other land use types 

may also be defined using the FaTEmaster Scenario Builder tool. Land use type is not an explicit input in 

TRIM.FaTE but is implicitly reflected in the TRIM.FaTE property values corresponding to each surface 

parcel.

Table 7-1. TRIM.FaTE Properties Recommended for Land use-Specific Parameterization

Property Remark

Organic carbon fraction Fraction of dry soil solids that is organic in origin.

Water content The sum of the water and air content fractions of a soil determines its 

porosity. Air content

Particle density Refers to the dry density of the average soil particle.

Rainfall/erosivity index Universal Soil Loss Equation (USLE) properties used in FaTEmaster 

Scenario Builder Tool to compute each surface soil compartment’s 

average erosion rate.

Soil erodibility index

Topographical (LS) factor

Cover/management factor

Supporting practices factor

Fraction of precipitation that 

evapotranspires

Water balance-related property used in FaTEmaster Scenario Builder 

Tool to compute each surface soil compartment’s average runoff rate.

Fraction of precipitation subject 

to overland runoff

8. Properties Recommended for National Values 

Nationally-representative or health-protective values are recommended for all TRIM.FaTE properties that 

are not identified for site-specific or land use-based parameterization in Sections 6 and 7 above. These 

properties are expected either to (1) not substantially influence risk in the RTR process, (2) not have 

adequate data to support site-specific parameterization, or (3) be relatively constant in the environment, 

as discussed in greater detail in the approach described in Section 6. These properties have been 

previously characterized in the RTR Tier 1 and Tier 2 screening threshold derivation analyses by either 
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nationally-representative values or health-protective values. The same values are recommended for 

these properties in site-specific analyses and are listed with references in Appendix B.

9. The FaTEmaster Scenario Builder 

All user inputs can be provided to TRIM.FaTE via text-based or delimited data input files. The files must

be defined in syntax specific to TRIM.FaTE; a full description of syntax requirements is provided in the 

TRIM.FaTE User’s Guide (U.S. EPA 2005)

ICF’s FaTEmaster Scenario Builder tool provides a Microsoft® ExcelTM-based environment that facilitates 

translation of user inputs into appropriately formatted TRIM.FaTE input files that can be used to set up 

and run site-specific scenarios. The FaTEmaster Scenario Builder tool does not, however, create the 

TRIM.FaTE Master Library file, which contains library properties and can be used to set property values 

that are not expected to vary between scenarios. The recommendations for the use of site-specific 

properties made earlier in this document are not envisaged to require changes to the TRIM.FaTE Master 

Library file. The FaTEmaster Scenario Builder tool is further documented in Appendix C. 

10. Potential Future Improvements 

This protocol represents a first attempt at documenting the current state of knowledge related to 

conducting site-specific environmental modeling in support of RTR multipathway risk assessments. The 

protocol could be enhanced in the future by documenting best practices and developing 

recommendations regarding the following issues (among others):

 Identification of land use-specific parameters for the identified soil properties based on literature 

review;

 Application of enhanced technical approaches, such as the use of a sensitivity score approach, to 

identify the most influential model properties;

 Potential development of regional parameters for a subset of model properties based on the results of 

further sensitivity analysis and data availability assessments;

 Greater use of graphics and figures to illustrate model set-up concepts;

 Enhanced technical editing to help the protocol be more self-explanatory and independent of other 

TRIM.FaTE support documents in its scope;

 Researching the potential for geographically variable biotransfer factors and other parameters in 

MIRC; and

 Further research and development of GIS-based approaches to surface hydrology and erosion 

property parameterization.
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References

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February 7, 2013. 

NCDC (National Climatic Data Center). 2008. Integrated Surface Database. Available at: 

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2008.

NCDC. 2011. NCDC 1981-2010 Climate Normal. Available at: 

http://www.ncdc.noaa.gov/oa/climate/normals/usnormals.html. Web page last updated 

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n=CDV.

NCDC. 2013. Quality Controlled Local Climatological Data (QCLCD). Available at: 

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Atkinson and Russell F. Lee). July 7, 1992. Available online at 

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http://www.epa.gov/ttn/fera/trim_fate.html#current_user

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U.S. EPA. 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For 

Review by the EPA’s Science Advisory Board. Attachment C-3 in Appendix C. (EPA452/R-09-006)

U.S. EPA. 2010a. SCRAM (Support Center for Regulatory Atmospheric Modeling) Mixing Height 

Data. Available at: http://www.epa.gov/ttn/scram/mixingheightdata.htm. Web page last 

updated May 13, 2010.

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2010.

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updated December 18, 2012.

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updated December 18, 2012.

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updated July 19, 2013.
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Appendix A. Documentation of Empirical Analyses Used to Prioritize 

TRIM.FaTE Properties

A.1. Introduction

ICF performed a series of empirical analyses to prioritize TRIM.FaTE model properties for site-specific 

parameterization. These analyses were based on changing the value of one or more model properties 

relative to the Tier 1 screening scenario and measuring the relative impact on risk. Unlike in a traditional 

sensitivity analysis, this analysis changed property values to approximate high and low-end values within 

the environmental range of the property of interest, instead of using a fixed perturbation. The measured 

impacts on risk, the expected range in the environment, and data availability were considered in 

prioritizing model properties for site-specific parameterization, as discussed in Sections 6 and 7.

Table A-1 summarizes the various empirical analyses that were conducted, the risk impact of the scenario 

modifications, and conclusions from the analyses.
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Table A-1. Results and Conclusions from Empirical Analyses Used to Prioritize TRIM.FaTE Properties

Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

Tier 1 SS Tier 1 Screening 

Scenario.

1.00 1.00 1.00 1.00

Designed to produce 

most conservative risk 

estimate.

All relative risks for 

modified scenarios are 

measured relative to the 

Tier 1 screening scenario.

WF1

Reduce watershed 

flows (erosion and 

runoff) to half 

screening scenario 

levels. Redirect 

remainder to sink. 

Maintain same flow 

directions as 

screening scenario.

0.56 0.69 0.21 0.38

Reducing the quantity of 

runoff and erosion 

reaching receiving 

compartments reduces 

chemical inputs into those 

compartments, including 

the lake, and reduces 

risk.

Surface hydrology and 

erosion flows (where and 

how much of the erosion 

and runoff from a 

compartment reaches) are 

potentially highly sensitive 

properties in the model 

(influencing risk by up to a 

factor of 10) and are 

recommended for sitespecific parameterization. WF2

Reduce watershed 

flows (erosion and 

runoff) to 1/10 

screening scenario 

levels. Redirect 

remainder to sink. 

Maintain same flow 

directions as 

screening scenario.

0.34 0.68 0.11 0.25

ER0 Switch off erosion. 0.39 1.02 1.10 0.43

Turning off erosion 

reduces chemical inputs 

into the lake and reduces 

chemical removal off the 

farm.

Although erosion is a 

relatively important 

process, its maximum 

impact on risk is less than 

a factor of 3, even when 
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Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

ER1 Double erosion rates. 1.09 0.99 0.86 0.86

Increasing erosion 

produces competing 

effects: while it increases 

chemical inputs into the 

lake, it also increases the 

burial rate of sediment 

and increases chemical 

removal from the farm.

accounting for variable 

runoff rates. A land-use 

specific parameterization 

approach is recommended 

for the average erosion 

rates of surface soil 

compartments.

ER-RUN1

Double erosion and 

runoff rates (same 

flush rate; higher lake 

depth).

0.94 0.96 0.74 0.89

Increasing the runoff rate 

increases the input of 

soluble chemicals into the 

lake and decreases the 

removal of those 

chemicals from the farm.

ER-RUN2

Double erosion and 

runoff rates (higher 

flush rate; same lake 

depth).

1.09 0.99 0.74 0.85

Increased runoff rates 

can be accommodated by 

means of increased lake 

depths or increased flush 

rates.

RUN1

Switch off runoff; 

maintain flush rate and 

depth.

0.99 1.00 0.70 0.96

Nullifying chemical 

transfer through runoff 

reduces chemical input 

into the lake and reduces 

chemical removal from 

the farm.

Runoff rates have a limited 

impact on risk. A land-use 

specific parameterization 

approach is recommended 

for average runoff rates 

from surface soil 

RUN2 compartments. Implement cumulative 

runoff regime.

1.02 1.00 1.14 1.10

Assumes runoff from one 

compartment does not 

evaporate but contributes 

to runoff from the 

receiving compartment.
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Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

FR1

Double lake depth, 

half flush rate, same 

rainfall, and same 

runoff fraction.

0.71 0.96 1.00 1.15

Doubling depth reduces 

concentrations but 

halving the flush rate 

reduces chemical output 

from the lake.

Lake depth and flush rate 

have a modest impact on 

risk. However, knowledge 

of both these parameters 

can help guide the surface 

hydrology and erosion 

direction flows in the 

watershed which can more 

substantially influence risk. 

Site-specific 

parameterization is 

recommended for lake 

depth and flush rate.

FR2

Half lake depth, 

double flush rate, 

same rainfall, and 

same runoff fraction.

1.28 1.07 1.00 0.92

Halving depth increases 

concentrations but 

doubling the flush rate 

increases chemical output 

from the lake.

FR3

Double depth, same 

flush rate, same 

rainfall, same runoff 

fraction (violate water 

balance in screening 

scenario).

0.69 0.96 0.58 1.02

Doubling depth reduces 

lake concentrations for 

most chemicals.

FR4

Double flush rate, 

same depth, same 

rainfall, and same 

runoff fraction (violate 

water balance in 

screening scenario).

0.95 1.00 0.58 0.89

Doubling flush rate 

reduces lake 

concentrations.

PERC1 Implement balanced 

percolation regime.

0.99 1.00 0.62 0.99

Assumes runoff from one 

compartment does not 

evaporate but percolates 

in the receiving 

compartment.

Percolation rate (the 

fraction of rainfall that is 

subject to percolation into 

the sub-surface) has a 

modest impact on risk. 

Land use-based 

parameterization is 

recommended for this 

property.
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft A-5 February 2014

Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

R1

Reduce rainfall down 

to 1/3rd SS value; 

same lake depth; 

runoff rates and flush 

rate down to 1/3rd.

0.64 0.59 0.92 0.58

Reducing rainfall reduces 

chemical washout from 

air.

This run, when combined 

with earlier runs focusing 

on the impacts of flush 

rate, suggests that the 

chemical washout impact 

of rainfall has more 

influence on risk than the 

impact of rainfall levels on 

hydrological properties like 

flush rate. This reinforces 

the argument for sitespecific meteorological 

parameters.

V_C

Set all surface 

compartments except 

farm to coniferous 

forests.

0.79 0.75 0.40 0.87

The choice of vegetation 

in surface soil 

compartments impacts 

risk by absorbing 

chemicals from air and 

soil and then redepositing 

them onto the surface soil 

via litterfall.

Land use-type has a 

limited impact on risk. 

Based on these results, 

terrestrial vegetation 

parameters are 

recommended for land-use 

specific parameterization. 

In interpreting these 

results, it is important to 

note that these runs have 

not been normalized for 

erosion rates. Therefore, 

the impacts on risk 

presented here are from a 

combination of impacts 

from differential erosion 

rates and vegetation types.

V_D

Set all surface 

compartments except 

farm to deciduous 

forests.

0.34 0.92 0.49 0.39

V_G

Set all surface 

compartments except

farm to grassland.

0.88 0.82 0.45 0.92

V_U

Set all surface 

compartments except 

farm to untilled soil.

0.42 0.73 0.37 0.81

V_WW

Set all surface 

compartments except 

farm to forested 

wetlands.

0.36 0.92 0.49 0.47
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft A-6 February 2014

Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

V_WG

Set all surface 

compartments except 

farm to grassy 

wetlands.

0.86 0.83 0.46 0.94

BM1

Increase aquatic 

biomass uniformly by 

a factor of 10.

0.84 0.39 0.90 0.99

Increasing aquatic 

biomass reduces 

chemical concentration in 

biomass as the same 

amount of chemical is 

distributed in a higher 

amount of biomass.

Risk is sensitive to the 

aquatic biomass levels. 

These properties are 

therefore recommended 

for site-specific 

parameterization. In 

interpreting the results of 

these runs, it may be noted 

that all biomass levels 

were uniformly raised. In 

real applications, the 

biomass levels of the 

upper trophic levels may 

constitute a lower 

percentage of the total 

biomass as total biomass 

increases, suggesting 

slightly lower risk 

sensitivity than apparent 

here.

BM2

Increase aquatic 

biomass uniformly by

a factor of 100.

0.35 0.32 0.29 0.79

Air_DL1 Increase air dust load 

by a factor of 10.

2.34 2.31 0.50 0.98 Increasing the dust load 

in air increases 

Although these runs 

indicate that air dust load 
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft A-7 February 2014

Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

Air_DL2 Increase air dust load 

by a factor of 100.

4.14 2.71 0.50 0.90

particulate deposition to 

the surface.

moderately influences risk, 

literature search indicated 

that the range manifested 

by this property is relatively 

small and the default value 

used is already in the high 

end of the observed range 

in the U.S. Therefore, this 

property is not 

recommended for sitespecific parameterization.

Air_FOM1

Halve the fraction of 

organic matter in air 

solids.

0.87 0.66 0.50 1.00

The organic content of air 

solids can differentially 

influence chemical 

adherence to the solid 

phase.

Although these runs 

indicate that the fraction of 

organic matter in air solids 

moderately influences risk, 

literature search indicated 

that site-specific data may 

be difficult to obtain. This 

property is not 

recommended for sitespecific parameterization.

Air_FOM2

Double the fraction of 

organic matter in air 

solids.

1.23 1.43 0.50 1.00

Soil_Air Double the soil air 

content.

1.21 1.29 0.50 1.14

Increasing the soil air 

fraction reduces soil 

solids, which distributes 

the same amount of 

chemical over a lower 

solids content, thereby 

increasing soil 

concentrations.

Although these runs 

indicate that air dust load 

moderately influences risk, 

literature search indicated 

that the range manifested 

by this property is relatively 

small and the default value 

used is already in the high 

end of the observed range 

in the U.S. Therefore, this 

property is not 

recommended for siteSoil_FOC

Increase the soil 

organic fraction 

content by a factor of 

10.

1.04 1.01 0.60 1.00

Increasing soil organic 

content increases 

chemical adherence to 

soil for some chemicals.
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft A-8 February 2014

Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

Soil_pH1 Set soil pH at 4. 1.00 1.00 0.39 1.00 Soil pH can influence 

chemical adherence to 

soil solids for some 

chemicals.

specific parameterization.

Soil_pH2 Set soil pH at 10. 1.00 1.00 0.66 1.00

Soil_Rho Set soil solids density 

at 1000 kg/m3.

1.41 1.43 0.50 1.16

Decreasing soil particle 

density increases soil 

concentrations when 

normalized by soil weight.

Soil_Water Double the soil water 

content.

1.00 1.00 0.50 1.00

Increasing soil water 

content increases 

chemical removal by 

percolation for some 

chemicals.

SusSed_TS

S1

Increase lake 

suspended solids 

concentration by a 

factor of 2.

0.73 0.98 1.01 0.74 Increasing suspended 

solids in water causes 

more chemical to be 

deposited to sediment.

Suspended solids 

concentration in lakes has 

a moderate influence on 

risk. Due to the wide range 

potentially exhibited by this 

property, it has been 

recommended for sitespecific parameterization.

SusSed_TS

S2

Increase lake 

suspended solids 

concentration by a 

factor of 10.

0.33 0.98 0.46 0.38

Sed_Bur

Halve sediment burial 

rate; same erosion 

rate (violate solids 

balance in screening 

scenario).

1.11 1.00 1.12 1.31

Decreasing the burial rate 

reduces the removal of 

chemicals from the 

sediment layer.

Sediment properties have 

a moderate impact on risk, 

given the limited range of 

values assumed by them 

in the environment. 

Additionally, data 

limitations would limit the 

potential for site-specific 

parameterization. These 

properties are therefore 

not recommended for sitespecific parameterization.
DRAFT Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk Assessment in the RTR Program

Working Draft A-9 February 2014

Scenario 

Name

Scenario Description 

(with respect to Tier 

1 Screening 

Scenario)

Normalized Risk Relative to 

Tier 1 Screening Scenario

Risk Impact of Scenario 

Modification Conclusions

TetraCDD, 

2,3,7,8-

Benzo(A)

pyrene

Cadmium Methyl 

Mercury

Sed_Rho

Decrease bed 

sediment particle 

density to 1000 kg/m3.

1.36 1.00 0.63 2.74

The lower the sediment 

particle density, the lower 

the volumetric 

resuspension rate from 

sediment and the higher 

the volumetric burial rate.

Sed_Por

Halve sediment bed 

porosity.

0.85 1.00 0.42 0.78

The lower the sediment 

porosity, the lower the 

volumetric resuspension 

rate from sediment and 

the lower the volumetric 

burial rate.
[This page intentionally left blank.]
Working Draft B-1 February 2014

Appendix B. TRIM.FaTE National Property Values

B.1. Introduction

This protocol recommends the use of nationally representative or health protective values (referred to as 

national values) for TRIM.FaTE model properties that have not been identified for site-specific or land 

use-based parameterization.

These national values are readily accessible in the FaTEmaster Scenario Builder tool, with references. 

This tool is included with the protocol and is documented in Appendix C. The national values are also 

documented in Appendix 4 of the Risk Report (see its Attachment A, Addendum 1).
[This page intentionally left blank.]
Working Draft C-1 February 2014

Appendix C. The FaTEmaster Scenario Builder Tool

C.1. Introduction

A TRIM.FaTE scenario requires a variety of inputs from users to define the modeled environment and to 

parameterize the algorithms for physical, chemical, and biological processes that transfer and transform 

chemical mass between and within environmental media. These inputs are provided to the TRIM.FaTE 

model in the form of the following files:

 A “volume elements” file, which defines the spatial layout of the modeled domain in terms of threedimensional abiotic compartments. Each volume element provides a frame of reference for one or 

more biotic compartments within it.

 A “compartments” file, which places biotic and abiotic compartments (modeling units containing 

chemical mass) within the volume elements.

 A Master Library file, which contains all the model algorithms, properties, and emission source 

information. 

 A properties file, which typically contains (i) simulation- and scenario-specific properties that overwrite 

default values specified in the Master Library and (ii) the location of time-varying input files for 

parameters such as meteorological and vegetation parameters. 

These input files must be constructed in syntax consistent with TRIM.FaTE requirements, as described in 

Module 3 of the TRIM.FaTE User’s Guide. 

ICF’s FaTEmaster Scenario Builder tool provides an MS-Excel spreadsheet-based interface that 

facilitates the automated generation of syntactically accurate TRIM.FaTE input files derived from userspecified inputs. The tool does not output the TRIM.FaTE Master Library file.

This appendix describes how the FaTEmaster Scenario Builder tool can be used to construct input files 

for the TRIM.FaTE model for use in site-specific risk assessments in the RTR process. While this 

document discusses the principal steps required to operate the tool, it does not provide line-by-line 

guidance for each of the hundreds of inputs contained within it. The tool already incorporates comments 

and guidance for each input cell and is largely self-explanatory. This overview of the tool is intended to 

facilitate an enhanced understanding of the scope of the tool and its operational structure. This document 

is not intended to serve as a guide to running the TRIM.FaTE model itself.

C.1.1. Output Files from the FaTEmaster Scenario Builder Tool

The FaTEmaster Scenario Builder Tool produces five text output files, which serve in turn as input files to 

the TRIM.FaTE model. The filenames, contents, and purpose of the output files generated by the tool are 

described in Table C-1.

C.1.2. Summary Worksheets in the FaTEmaster Scenario Builder Tool

The FaTEmaster Scenario Builder Tool consists of 15 worksheets. The names, contents, and purpose of 

these worksheets are described in Table C-2, which has been color-coded in an identical manner to the 

worksheet “tabs” in the tool.
Working Draft C-2 February 2014

Table C-1. Output Files Generated by the FaTEmaster Scenario Builder Tool

File Name Contents Purpose

Sources.txt

Coordinates specifying the 

location of the emission sources 

and the chemical emission rates.

This file facilitates the creation of 

a unique scenario-specific 

TRIM.FaTE Sources Library. This 

file must be manually imported 

through the TRIM.FaTE graphical 

interface and saved as a library. 

This Sources Library must then 

be loaded to the site-specific 

TRIM.FaTE scenario together 

with the TRIM.FaTE Master 

Library. 

Volume Elements.txt

Coordinates specifying the spatial 

dimensions of the volume 

elements and specification of the

primary abiotic compartment 

within each volume element.

This file serves as a TRIM.FaTE 

input file to define the spatial 

layout of the modeled domain in 

terms of three-dimensional abiotic 

compartments, each of which can

contain other biotic and abiotic 

compartments.

Compartments.txt

The names of biotic and nonprimary abiotic compartments 

located within each primary 

abiotic compartment defined by 

the Volume Elements file.

This file serves as a TRIM.FaTE 

input file to situate user-specified 

biotic and abiotic compartments 

within each volume element. 

These compartments are the 

discrete units that contain 

chemical mass in TRIM.FaTE.

Properties.txt

Values defining site-specific 

properties relating to the scenario, 

biotic and abiotic compartments, 

and user-specified link properties.

This files serve as a TRIM.FaTE 

input file to define the values of 

various properties that define the 

scenario. It overwrites default 

values for these properties 

specified in the TRIM.FaTE 

Master Library file.

Other Properties.txt

Values defining properties that 

are not included amongst the 

standard sections of the tool for 

user-specification. This is a 

discretionary or optional file that 

may be useful when overwriting 

library properties that are not 

redefined by the standard 

elements of the tool.

This file serves as a TRIM.FaTE 

input file to define the values of 

any of the various properties that 

define the scenario. It overwrites 

default values for these properties 

specified in the TRIM.FaTE 

Master Library file.
Working Draft C-3 February 2014

Table C-2. Summary of Worksheets Generated by the FaTEmaster Scenario Builder Tool

Worksheet Name Contents Purpose

Tracking

 Command button

 Documentation of version changes.

Contains “Export All” button that 

generates TRIM.FaTE input files 

based on values specified in other 

worksheets. Also serves as a 

documentation sheet for tool 

software developers only.

Parameters

 User-specified property values for 

several TRIM.FaTE model properties.

Provides a user-friendly interface 

for the definition of site-specific 

model properties. Adds the 

properties defined here to the 

Properties file.

Layout

 Coordinates of the vertices of the 

parcels that define the spatial layout. 

 Coordinates of the location of the 

emission sources. 

 Emission rates of each chemical 

species from each source.

Serves as a basis for the creation 

of the Volume Elements and the 

Sources output files.

Land

 User-specified parameter values for the 

USLE equation for different land use 

types.

Computes average erosion rates 

based on the USLE equation for 

surface soil compartments and 

adds those estimates to the 

Properties file. Also contains 

elements used to construct the 

Compartments file.

Soil

 User-specified property values for all 

soil layers differentiated by land use 

types.

Computes average runoff and 

percolation rates, and adds these 

estimates and other soil-related 

properties to the Properties file. 

Also contains elements used to 

construct the Compartments file.

Plants

 User-specified vegetation types and 

vegetation components for each land 

use category.

Places the appropriate vegetation 

composite compartments within 

soil compartments based on userspecified land use. This is used to 

construct the Compartments file.

Watersheds

 User-specified inter-compartment 

erosion and runoff directions and 

percentages. 

Defines inter-compartmental link 

properties for runoff and erosion 

and adds them to the Properties 

file.

Lakes

 User-specified lake and sediment 

properties.

 Equations to compute lake flush 

rates/depth and sediment resuspension 

velocity based on watershed flows.

Adds lake and sediment related 

properties, and computed lake 

and sediment hydrodynamic 

parameters, to the Properties file. 

Fish

 User-specified aquatic food web and 

biomass levels.

Adds aquatic food web and 

biomass properties to the 

Properties file. These elements 

are also used to construct the 

Compartments file.
Working Draft C-4 February 2014

Worksheet Name Contents Purpose

Soil Data

 User-specified soil properties 

differentiated by land use type.

Serves as an input sheet for soil 

properties that is called by the 

“Soil” worksheet. May potentially 

be parameterized on a regional 

basis.

Sources No user inputs are required on these worksheets. They are constructed from the 

inputs specified in the previous tabs and contain the content of the output files 

that will later be generated by the tool as text files. 

Volume

Cmpts

Props

OtherProps

User may enter supplementary properties into this worksheet consistent with 

TRIM.FaTE syntax. This worksheet can be used to overwrite properties that are

defined in the Master Library file or to define properties that are not previously 

defined either in the library file or other input files. 

C.1.3. Additional Salient Features of Worksheets in the FaTEmaster Scenario 

Builder Tool

This section provides a limited description of the features of the various worksheets within the 

FaTEmaster Scenario Builder, with a focus on the most salient operational aspects from the user 

perspective. 

A general rule when working with the tool, also mentioned clearly at the top of each worksheet, is that 

only cells color-coded green may be modified by users. Blue and white color-coded cells are not to be 

modified by users.

(i) The Tracking Worksheet

 Users should click the “Export All” command button after they have made all the necessary input 

modifications to the other worksheets. This will be the final step in operating the tool. 

 The remainder of the worksheet is intended for software developers only to document version 

changes in the tool.

(ii) The Parameters Worksheet

 Specify a “set up” file directory in cell D9.

– Model output will be directed to this directory into a sub-folder named “Output”. 

– This directory will also be the destination to which the tool will write its five output files.

– This directory should contain the time-varying meteorological values file, leaf “allow exchange” 

file, and litterfall data file later referenced in the worksheet.

 In cell D48, enter the average annual precipitation based on the average from the time-varying sitespecific meteorological file. This averaging must be performed manually offline.

 In cell D49, update the formula reference with the name of the applicable meteorological values file if 

they have changed.

 In cells D80, D92 and D103 update the formula with the names of the leaf allow exchange data files if 

they have changed.

 In cells D84, D96 and D107 update the formula with the names of the litterfall data files if they have 

changed.

 Note: Cells commented as “Reported Value” will be reported in the tables for documentation 

purposes but will not be used in TRIM.FaTE input files.
Working Draft C-5 February 2014

 Note: All other input cells may be updated as required. Cell comments have been provided for 

guidance.

(iii) The Layout Worksheet

 Based on the spatial layout for air and surface parcels developed in GIS or through manual mapping, 

enter the Cartesian coordinates of each vertex point in columns C and D. The center of the emissions 

source (or facility) parcel should be defined as the origin of the system. 

 Specify offset coordinates in cells E9 and F9 to situate the layout spatially, consistent with the 

specified map projection system in cell D4. (This is similar to a latitude and longitude specification. It 

does not affect TRIM.FaTE results, however.)

 Specify the name of each parcel in the spatial layout and the vertex points that define the parcel in a 

clockwise or anticlockwise direction around the perimeter of the parcel in columns H and K. 

 Specify the parcel category from the available options in column I.

 Specify the land use corresponding to each parcel in column J.

 Specify the source name, source parcel location, and source elevation in column U.

 Specify the chemical emission rates in column U.

(iv) The Land Worksheet

 In columns E through L, enter the USLE parameters that are used to compute average erosion rates 

for each land use type.

 Enter the vegetation type within each land use type.

(v) The Soil Worksheet

 This worksheet requires no user inputs. It draws inputs from other worksheets and calculates average 

runoff and percolation rates based on those values.

(vi) The Plants Worksheet

 Specify the vegetation components corresponding to each land use type.

 Note: If new types of vegetation components are being defined, their corresponding properties and 

algorithms should be defined in the Master Library or separately within property files. 

(vii) The Watersheds Worksheet

 For each parcel, specify which of its adjoining parcels receive the runoff and erosion originating from 

that parcel and in what amounts (specified in percentages).

 Click on the “Refresh” button after updating the worksheet.

(viii) The Lakes Worksheet

 Specify lake and sediment properties in column K.

 Specify one of either lake depth or flush rate in cells K18 and K19.

 Note: The worksheet will compute the unspecified property (either lake depth or flush rate) using a 

water balance. The water balance assumes that runoff entering the lake is the sum of runoff entering 

the lake from adjacent soil compartments and cumulative runoff from the larger watershed.

 Note: The worksheet also computes sediment resuspension velocity and sediment burial rate using 

principles discussed in the TRIM.FaTE Technical Support Document (Section 4.2.2).
Working Draft C-6 February 2014

(ix) The Fish Worksheet

 Define the aquatic food web by specifying the diet fraction for each aquatic organism.

 Specify the total biomass of each organism type and the single body weight of each organism.

(x) The Soil Data Worksheet

 For each land-use type, specify properties for all soil layers. 

 (Note: The tool has the capacity to accommodate region-specific definitions of soil parameters too but 

this functionality has not currently been parameterized.)

C.1.4. Generating Output Files from the FaTEmaster Scenario Builder Tool

After entering site-specific inputs into the various worksheets within the tool as required, the following 

steps should be used to complete the generation of output files:

 Navigate to the “Layout” tab, and click “Refresh”.

 Navigate to the “Watersheds” tab, and click “Refresh”.

 Navigate to the “Tracking” tab, and click “Export All”.

The five output files generated by the tool can then be used as input files to set up the site-specific 

TRIM.FaTE scenario. (It is reiterated that the tool does not generate the TRIM.FaTE Master Library file, 

the contents of which are largely invariable between applications.