Section 14.0 Ecological Benchmarks

1 For this analysis, CSCLs refer to constituent concentrations (e.g., mg/kg soil) in environmental media that

are presumed to cause de minimis effects on ecological receptors. Benchmarks, in mg/kg/d, provide protective

ingestion doses that are estimated to cause de minimis effects to mammalian and avian receptors.

14-1

14.0 Ecological Benchmarks

The Ecological Risk Module was created to generate risk estimates for receptor taxa of

concern. The risk quotient method was used to identify the potential for adverse effects to

terrestrial and freshwater receptors. The risk quotient compares, by ratio, the modeled media

concentrations to an estimated protective level for receptors of concern in the respective

exposure media (i.e., water, soil, sediment, prey items). When the ratio exceeds 1, there is a

potential for adverse effects to that receptor; when the ratio is less than 1, minimal risk to the

receptor is indicated. The specific methods used to calculate the protective level (i.e.,

benchmarks and chemical stressor concentration limits [CSCLs]) varied with the receptor taxa.1

Protective CSCLs were derived (in ppm) for specific communities and populations in direct

contact with contaminated media (i.e., terrestrial plants, soil biota, sediment biota, fish/aquatic

invertebrates, herpetofauna). Protective benchmark doses (mg/kg/d) were developed for

mammals and birds based on exposure through the food web by ingestion of contaminated food

items. A complete review of how modeled media exposure concentrations were generated is

provided in the documentation of the ecological exposure module. This section describes in

detail how the benchmarks and CSCLs used in the risk quotient were derived. 

14.1 Parameters

The key database developed in support of the ecological risk module was the

benchmark/CSCL database. The parameters used to calculate ecological risk in the module are

listed in Table 14-1. As the table indicates, all the parameters generated in the benchmark/CSCL

database are chemical-specific properties. 

14.2 Data Sources

In developing the chemical-specific benchmark/CSCL database, the major source of

ecotoxicity data was the primary literature. Secondary sources of data included documents and

databases developed by the U.S. Environmental Protection Agency, other government agencies

(e.g., the National Oceanographic and Atmospheric Administration [NOAA]), and other research

facilities (e.g., Oak Ridge National Laboratories [ORNL]). Given that changes were made to the

priority constituent list after initial literature searches were completed, secondary review sources

were the only references reviewed for some of the chemicals. The status of the literature 
Section 14.0 Ecological Benchmarks

14-2

Steps in Identifying Ecotoxicological Data

 

Step 1: Review Existing Synopses

# Develop understanding of behavior of

constituents and generally recognized adverse

effects.

# Summarize available data and identify primary

studies for further analysis.

# Delineate key parameters that would mitigate (or

enhance) the toxicity of constituents.

Step 2: Search Toxicological Databases

# Compile quantitative data on effects.

# Fill data gaps identified from review of

synopses.

# Identify critical endpoints for benchmark

development.

 

Step 3: Conduct Online Literature Search

# Focus on critical endpoints and fill in data gaps.

# Identify recent studies and data not available in

synopses or toxicological databases.

# Provide supporting information for benchmark

development.

Table 14-1. Parameters Included in the Benchmark/CSCL Database

Parameter Description Parameter Code

Ecological benchmark for representative receptors that receive ingested

doses

ChemEBRec

CSCL for water based on total concentrations ChemCSCLWaterTotRec

CSCL for water based on dissolved concentrations ChemCSCLWaterDissRec

CSCL for sediment ChemCSCLSedimentRec

CSCL for soil ChemCSCLSoilRec

searches for each constituent is presented in Table 14-2. Secondary review sources helped

identify the most current literature available for benchmark and CSCL development;

unfortunately, sufficient time was not available to complete more thorough literature searches for

many of the constituents. 

To provide a context for how data

searches were initiated to develop the

benchmark/CSCL database, the general steps

taken in primary literature searches are

outlined here. The key steps to the literature

review process consisted of (1) reviewing

existing synopses, (2) searching toxicological

databases, and (3) conducting comprehensive

online literature searches (see text box). A

more detailed description of each step is

provided in subsequent sections. This

framework is not meant to be all-inclusive;

rather, it provides key approaches and

examples of data sources that have been

shown to be highly productive in

characterizing ecotoxicological effects. 

14.2.1 Review Existing Synopses

In this step, major reviews of

ecotoxicological effects are investigated. 

This step ensures that no obvious sources of

effects data are missed and provides a road

map for what information might be available. 

Documents such as U.S. Fish and Wildlife 
Section 14.0 Ecological Benchmarks

14-3

Table 14-2. Status of Literature Review Process for Chemicals of Concern

Primary Literature Review Completed Secondary Source Review Completed

Methoxychlor

Pentachlorophenol (PCP)

2,3,7,8-Tetrachlorodibenzo-p-dioxin

Arsenic

Mercury

Lead

Silver

Zinc

Cadmium

Beryllium

Bis-(2-ethylhexyl) phthalate

Benzo[a]pyrene

Antimony

Thallium

Chromium

Barium

Nickel

Selenium

Vanadium

Chromium, total

Chromium III

Chromium VI

Benzene

Toluene (methyl benzene)

Ethylene dibromide

(1,2-dibromoethane)

Thiram

Methylene chloride (dichloromethane)

1,1,1-Trichloroethane

Vinyl chloride (chloroethylene)

Trichloroethylene

Chlorobenzene

Hexachloro-1,3-butadiene

2,4-Dichlorophenoxyacetic acid (2,4-D)

Phenol

Methyl ethyl ketone

Methyl methacrylate 

Dibenz[a,h]anthracene

Carbon disulfide

Acetonitrile

Pyridine

Nitrobenzene

Aniline

Tetrachloroethylene

Chloroform (trichloromethane)

Acrylonitrile (2-propenenitrile)

Service (FWS) synoptic reviews, EPA water quality criteria documents, and Agency for Toxic

Substances and Disease Registry (ATSDR) toxicological profiles provide a broad overview of

the fate and toxicological effects of constituents. These reviews provide a necessary foundation

to delineate environmental characteristics that mitigate (or enhance) toxicity. Further, these

reviews offer a first look at whether the available data suggest that the constituent is likely to be

of ecological concern. 

14.2.2 Search Toxicological Databases

Two distinct steps were made in searching toxicological databases. First, databases

related to animal health effects, commonly used in conjunction with human health risk

assessments, were searched to identify effects data for mammals and birds. Second, ecologically

related databases were searched to evaluate the toxicity data available for other receptors (e.g.,

terrestrial plants, algae, fish/aquatic invertebrates). Expanded descriptions of these steps and

databases follow:
Section 14.0 Ecological Benchmarks

14-4

# Step 1—The Hazardous Substance Database (HSDB) and the Registry of Toxic

Effects of Chemical Substances (RTECS) were reviewed for toxicological

information of constituents on animals. These databases were selected because

(1) they included a wide variety of toxicity data, (2) they were readily available,

and (3) they provided a rapid (if incomplete) picture of the chemical toxicology. 

Results from searching these databases also were useful in identifying primary

references for the development of stressor-response profiles and benchmarks for

mammals and birds. These databases are limited, however, because toxicological

data are presented only for mammals (including humans) and birds and because

narrative text is generally insufficient to interpret the study data. Nevertheless,

these data were enormously important in defining the range of effect levels and

critical endpoints (e.g., teratogenicity) necessary for the stressor-response profile. 

# Step 2—EPA’s ECOTOX database has become an essential reference for

benchmark development because (1) it is the largest database of ecological effects

data currently available, (2) it includes primary literature citations, and (3) it is

readily available. 

Three databases were available within ECOTOX covering different groups of

ecological receptors: (1) TERRETOX for terrestrial wildlife and soil biota,

(2) PHYTOTOX for effects on terrestrial plant species, and (3) the Aquatic

Information Retrieval (AQUIRE) system for effects on aquatic biota (fish,

invertebrates, and aquatic plants). The drawback to using ECOTOX is that its

databases are only updated periodically. AQUIRE is updated annually. 

TERRETOX and PHYTOTOX offer a thorough search of data up to 1991;

however, updates from 1991 to the present only partially represent the primary

literature. The ecological effects information culled from ECOTOX was used to

fill data gaps and to refine the bibliographic and keyword search for specific

receptors in the next step. If sufficient data were not identified in ECOTOX (e.g.,

toxicity is only characterized for a few species), a more broad-based strategy was

adopted for the online literature search.

14.2.3 Conduct Online Literature Search

Commercial online databases such as Dissertation Abstracts include extensive

bibliographic databases that can provide additional information not found in ECOTOX or other

similar databases. The general strategy for searching online bibliographic databases is

summarized in Steps 1and 2 as follows:

Step 1—The bibliographic database search began with Toxline®/Medline® because they

are relatively low-cost databases that specialize in toxicological citations. Research Triangle

Institute (RTI) has used these databases frequently with a high degree of success.

Step 2—Based on the results of the primary search in Toxline®/Medline®, it was

sometimes necessary to reconsider the search strategy and submit a new search or to search more

costly databases (e.g., royalty databases). Depending on the data gaps for specific ecological

receptors (e.g., no data on birds), a more appropriate database was searched. For example, if we
Section 14.0 Ecological Benchmarks

14-5

needed data on avian effects, we would select a database such as Biological Abstracts rather than

a database limited to aquatic effects (i.e., Water Resources). For data-poor constituents, more

general environmental databases such as Environline® or Pollution Abstracts were searched. 

Following primary literature searches, appropriate studies were identified for benchmark

and CSCL derivation. A summary of the key documents and databases consulted to develop

benchmarks and CSCLs is provided in Table 14-3. The actual primary references that were

specifically identified to derive benchmark doses for mammals and birds are provided in

Table 14-4. For constituents added after primary literature searches were completed, only

Steps 1 and 2 were completed (see text box). For these chemicals, the searches were limited to

the effects data outlined in the sources presented in Table 14-3. The benchmarks and CSCLs for

the newer constituents should be considered preliminary until further primary literature reviews

are conducted. 

14.3 Methodology

14.3.1 Benchmark/CSCL Database

14.3.1.1 Database Compilation. The methods used to derive each of the benchmarks

and CSCLs were different across receptor taxa. Because of these differences, the methods used

to develop benchmarks and CSCLs are reviewed separately for each receptor taxon. The

discussion of the methods used in developing the benchmark/CSCL database is organized around

the specific module parameters listed in Table 14-1. Because parameters are media-specific,

some parameters cover more than one receptor category. For instance, total water CSCLs are

generated for herpetofauna, the freshwater community, and algae/aquatic plants. In these cases,

receptor-specific methods are discussed as subsections. 

14.3.1.1.1 Ecological Benchmarks for Representative Receptors (ChemEBRec).

Ecological benchmarks (EBs), derived in units of dose (mg/kg/d), were developed for

representative taxa of mammals and birds. The EBs were appropriate for upper-trophic-level

consumers because the primary exposure route occurs through ingestion of contaminated prey

items. Because the degree of exposure to mammals and birds is dependent on the foraging

range, uptake rates, and percentage of the diet that is contaminated, in constructing the example

3MRA data set ecological exposure modeling system, these life history factors were used to

develop an estimated dose for representative mammals and birds exposed to constituents. The

risk estimate was derived by comparing exposure doses to the benchmark dose to assess whether

the benchmark dose had been exceeded. An exceedance indicates the potential for adverse

effects.

The overall approach used to establish these benchmarks is similar to the methods

applied to derive reference doses (RfDs) for humans, as described in the Integrated Risk

Information System (IRIS) (U.S. EPA, 1993c). The method adopted for the representative

national data set uses a hierarchy for the selection of ecotoxicity data and extrapolates from a test

species to the species of interest (in this case, wildlife). There are fundamental differences

between the goals of noncancer risk assessments for humans and ecological receptors. For

example, risk assessments
Section 14.0 Ecological Benchmarks

14-6

Table 14-3. Key Sources of Information Consulted in the Development of

Benchmarks and CSCLs

Source Contents

Mammals and Birds

U.S. EPA (Environmental Protection Agency). 1995b.

Great Lakes Water Quality Initiative Criteria

Documents for the Protection of Wildlife. Office of

Water.

This document provides wildlife criteria in surface

water for exposures to DDT, 2,3,7,8-(TCDD),

mercury, and polychlorinated biphenyls (PCBs).

Sample, B.E., D.M. Opresko, and G.W. Suter, II. 

1996. Toxicological Benchmarks for Wildlife: 1996

Revision.

This compendium reference reviews ecotoxicity data

derived from the primary literature of various

constituents to species of mammals and birds. 

U.S. EPA (Environmental Protection Agency). 1999a.

Ecotoxicological Database System. Office of Research

and Development, U.S. Environmental Protection

Agency.

The terrestrial animal toxicity database (TERRETOX)

contains more than 33,000 toxicity tests on terrestrial

wildlife for more than 1,200 chemicals and 253

species.

U.S. FWS (Fish and Wildlife Service). Various years. 

Contaminant Hazard Reviews. U.S. Department of the

Interior (e.g., Eisler, 1989). 

These profiles review chemical-specific toxicity to

various ecological receptors. These compendia also

expand discussions to assess issues of bioaccumulation

and biochemical effects.

Plant Community

Efroymson, R.A., M.E. Will, G.W. Suter, II, and A.C.

Wooten. 1997. Toxicological Benchmarks for

Screening Contaminants of Potential Concern for

Effects on Terrestrial Plants: 1997 Revision.

This document provides ecotoxicity effects data for

terrestrial plants exposed in soil and solution media. 

Approximately 45 constituents have proposed soil

criteria. 

U.S. EPA (Environmental Protection Agency). 1999a.

Ecotoxicological Database System. Office of Research

and Development, U.S. Environmental Protection

Agency. 

The terrestrial plant toxicity (PHYTOTOX) database

contains more than 49,000 toxicity tests on terrestrial

plants for more than 1,600 organic and inorganic

chemicals and 900 species.

Freshwater Community

U.S. EPA (Environmental Protection Agency). 1999a.

Ecotoxicological Database System. Office of Research

and Development, U.S. Environmental Protection

Agency.

The aquatic biota toxicity database (AQUIRE) contains

more than 145,000 toxicity tests for more than 5,900

organic and inorganic chemicals and 2,900 aquatic

species.

U.S. EPA (Environmental Protection Agency). 

Various years. Ambient Water Quality Criteria. 

Office of Water, Washington, DC. (Example U.S.

EPA, 1989).

These chemical-specific documents provide the

ecotoxicity data and derivation methodologies used to

develop the National Ambient Water Quality Criteria

(NAWQC).

(continued)
Table 14-3. (continued)

Section 14.0 Ecological Benchmarks

Source Contents

14-7

Freshwater Community (continued)

U.S. EPA (Environmental Protection Agency). 1995a.

Great Lakes Water Quality Initiative Criteria

Documents for the Protection of Aquatic Life in

Ambient Water. Office of Water.

U.S. EPA (Environmental Protection Agency). 1996a.

1995 Updates. Water Quality Criteria Documents for

the Protection of Aquatic Life in Ambient Water. EPA

820B96-001. Office of Water, Washington, DC.

For a limited number of constituents, the Great Lakes

Water Quality Initiative (GLWQI) has proposed

surface water criteria for aquatic biota using analogous

methods as implemented in the derivation of the

NAWQC.

Suter, II, G.W., and C. Tsao. 1996. Toxicological

Benchmarks for Screening Potential Contaminants of

Concern for Effects on Aquatic Biota: 1996 Revision.

This compendium reference provides acute and chronic

water quality criteria for freshwater species, including

algae.

Algae and Aquatic Plants

Suter II, G.W. and C. Tsao. 1996. Toxicological

Benchmarks for Screening Potential Contaminants of

Concern for Effects on Aquatic Biota: 1996 Revision.

This compendium reference provides acute and chronic

water quality criteria for freshwater species, including

algae.

U.S. EPA (Environmental Protection Agency). 1999a. 

Ecotoxicology Database System. Environmental

Research Laboratory, Office of Research and

Development.

The AQUIRE database contains more than 145,000

toxicity tests for more than 5,900 organic and inorganic

chemicals and 2,900 aquatic species.

Soil Community

Efroymson, R.A., M.E. Will, and G.W. Suter, II. 

1997. Toxicological Benchmarks for Contaminants of

Potential Concern for Effects on Soil and Litter

Invertebrates and Heterotrophic Process: 1997

Revision. Oak Ridge National Laboratory. 

This document provides effects data for soil biota (i.e.,

microbial processes and earthworms). Approximately

35 constituents have proposed soil criteria, and some

field studies are included.

CCME (Canadian Council of Ministers of the

Environment). 1997. Recommended Canadian Soil

Quality Guidelines. 

The criteria developed by the CCME are

concentrations above which effects are likely to be

observed. 

Sediment Community

U.S. EPA (Environmental Protection Agency). 1993a.

Technical Basis for Deriving Sediment Quality Criteria

for Nonionic Organic Contaminants for the Protection

of Benthic Organisms by Using Equilibrium

Partitioning.

This document supplies toxicological criteria (sediment

quality criteria [SQC]) for nonionic hydrophobic

organic chemicals using final chronic values (FCVs)

and secondary chronic values (SCVs) developed for

surface water. The criteria are estimated based on the

assumption that the partitioning of the constituent 

between sediment organic carbon and pore water is at

equilibrium.

(continued)
Table 14-3. (continued)

Section 14.0 Ecological Benchmarks

Source Contents

14-8

Sediment Community (continued)

Long, E.R., and L.G. Morgan. 1991. The Potential

for Biological Effects of Sediment-Sorbed

Contaminants Tested in the National Status and Trends

Program. National Oceanic and Atmospheric

Administration (NOAA) Technical Memorandum.

Field-measured sediment concentrations are correlated

with impacts to sediment biota in estuarine

environments. Measures of abundance, mortality, and

species composition are the primary toxicity endpoints.

Jones, D.S., G.W. Suter, II, and R.N. Hull. 1997. 

Toxicological Benchmarks for Screening Contaminants

of Potential Concern for Effects on SedimentAssociated Biota: 1997 Revision. Oak Ridge National

Laboratory.

This document proposes sediment criteria for both

organic and inorganic constituents using both field and

estimation methodologies.

Long, E.R., D.D. MacDonald, S.L. Smith, and F.D.

Calder. 1995. Incidence of adverse biological effects

with ranges of chemical concentrations in marine and

estuarine sediments. Environmental Management

19(1):81-97. 

This paper contains an updated version of the NOAA

approach (Long and Morgan, 1991) in which

additional data were added to the data set. The range

of sediment concentrations that may result in adverse

impacts to benthic-dwelling invertebrates are indicated.

MacDonald, D.D. 1994. Approach to the Assessment

of Sediment Quality in Florida Coastal Waters. Vol. 1. 

Florida Department of Environmental Protection

(FDEP), Tallahassee, FL.

This approach applies statistical derivation methods to

determine sediment criteria using NOAA data. The

resulting criteria are more conservative than NOAA

values.

Herpetofauna

Power, T., K.L. Clark, A. Harfenist, and D.B. Peakall. 

1989. A Review and Evaluation of the Amphibian

Toxicological Literature. Technical Report Series No.

61, Canadian Wildlife Service.

This reference was developed by Environment Canada

to review the ecotoxicity literature so that risks to

amphibian populations could be evaluated. 

U.S. EPA (Environmental Protection Agency). 1996b. 

Amphibian Toxicity Data for Water Quality Criteria

Chemicals. EPA/600/R-96/124. National Health and

Environmental Effects Research Laboratory, Corvallis,

OR. 

This reference was developed by EPA to evaluate the

primary literature available on amphibians in an effort

to include more amphibian data into the development

of NAWQC under the data requirement for species in

phylum Chordata. 

Devillers, J., and J.M. Exbrayat (eds). 1992. 

Ecotoxicity of Chemicals to Amphibians. Philadelphia,

PA: Gordon and Breach Science. 

This text provides test study summarizes for

amphibians reporting endpoints related to reproduction

and survival.
Section 14.0 Ecological Benchmarks

14-9

Table 14-4. Primary Literature Used in Mammalian and Avian Benchmark Derivationa

Constituent Mammalian Reference Avian Reference

Antimony Rossi et al., 1987 ID

Arsenic Byron et al., 1967 Stanley et al., 1994

Barium ID Johnson et al., 1960

Benzene Sample et al., 1996 ID

Benzo(a)pyrene MacKenzie and Angevine, 1981 ID

Bis(2-ethylhexyl) phthalate Shiota and Nishimura, 1982 ID

Cadmium Sutou et al., 1980 White and Finley, 1978

Chloroform Sample et al., 1996 ID

Chromium III (insoluble salts) Sample et al., 1996 ID

Chromium VI Zahid et al., 1990 ID

Lead Krasovskii et al., 1979 Edens and Garlich, 1983

Mercury Wobeser et al., 1976a, 1976b Heinz, 1974, 1975, 1979

Methyl ethyl ketone Sample et al., 1996 ID

Nickel Ambrose et al., 1976 Sample et al., 1996

Pentachlorophenol Welsh et al., 1987 Prescott et al., 1982

Selenium Rosenfeld and Beath, 1954 Heinz and Hoffman, 1987

TCDD, 2,3,7,8- Murray et al., 1979 Nosek et al., 1992

Thallium Sample et al., 1996 ID

Toluene Sample et al., 1996 ID

Trichloroethylene Sample et al., 1996 ID

Trichloroethane, 1,1,1- Sample et al., 1996 ID

Vanadium Domingo et al., 1986 Romoser et al., 1961

Vinyl chloride Sample et al., 1996 ID

Zinc Schlicker and Cox, 1968 Sample et al., 1996

ID=Insufficient data identified for benchmark derivation.

a

Chemicals not listed had insufficient data to develop mammalian or avian benchmarks.
Section 14.0 Ecological Benchmarks

14-10

conducted for humans seek to protect the individual, while ecological risk assessments seek to

protect populations or communities of important species (U.S. EPA, 1992a). Consequently,

benchmark studies for mammals and birds were selected using a few key guidelines. These

guidelines represent the minimum requirements for a study to be of sufficient rigor for

benchmark derivation.

# Measurement Endpoints—Studies containing measurement endpoints reported as

either a no-observed-adverse-effect level (NOAEL) or a lowest-observedadverse-effect level (LOAEL) in units of daily dose were preferred. From these

results, the geometric mean between the NOAEL and the LOAEL (i.e., maximum

acceptable toxicant concentration [MATC]) was calculated. The MATC was the

preferred benchmark for representative mammalian and avian species. 

# Toxicity Endpoints—Because population viability in mammals and birds was

selected as the assessment endpoint, the benchmarks were developed from

toxicity endpoints of reproductive or developmental success or, if unavailable,

other effects that could conceivably impair population dynamics. 

# Methods—No specific test methodologies were required in studies used for

benchmark derivation. Standard laboratory practices (e.g., control dose groups),

however, were required. Field data may not be appropriate to develop a daily

dose exposure.

# Receptor Requirements—Ecotoxicity data for wildlife species were preferred

(e.g., mallards or mink); however, because of the paucity of studies exposing

wildlife species, rats and mice were typically the surrogate species exposed in

benchmark studies. 

# Durations—Studies were selected that reflected chronic or subchronic exposure

durations extending over a large percentage of the test species’ lifetime, over

multiple generations, or over a particularly sensitive life stage of a species. 

# Exposure Routes—Studies indicating oral exposure (e.g., dietary, gavage) were

preferred to studies using other exposure routes (e.g., intraperitoneal injection). 

Mammals and birds in the field are typically more highly exposed through

ingestion of contaminated prey than through inhalation or direct contact, although

there are exceptions (e.g., burrowing animals). 

# Dosing Scheme—Dose-response curves characterized by at least three data points

were selected over studies exposing animals to one dose level. This helped

identify both a NOAEL and a LOAEL for MATC calculations.

In addition to the primary literature, several review sources of ecotoxicity data were

identified containing study data of sufficient quality to meet data requirements (Table 14-3). 

Several benchmark studies, however, were selected from Sample et al. (1996), a compendium of

study values reporting NOAELs and LOAELS for chronic and subchronic durations measuring

reproductive and developmental endpoints.
Section 14.0 Ecological Benchmarks

14-11

Mammalian and avian benchmarks represent population-inference benchmarks. By

developing benchmarks from NOAELs and LOAELs in mammals and birds, benchmarks were

estimated to provide protection from ingested doses that may inhibit the reproductive capacities

of these populations. The ability of the population to sustain itself (within normal biological

variation) was inferred from individual effects such as fecundity. This inference, however, has

yet to be validated from field or microcosm studies on exposed populations. Without validation,

it is likely that some benchmarks are overprotective and others are underprotective of wildlife

populations. Although this method does not confirm protection of populations, by protecting

individuals from adverse effects to reproductive and developmental endpoints, some level of

protection is provided to populations. 

Once the benchmark study was identified, a scaled benchmark was calculated for

representative receptors of mammals. This method used an allometric scaling equation based on

body weight to extrapolate test species doses to estimate wildlife species doses. For mammals, a

scaling factor of 3/4 was used (Equation 14-1). This is the default methodology EPA proposes

for carcinogenicity assessments and reportable quantity documents for adjusting animal data to

an equivalent human dose (U.S. EPA, 1992b). For birds, recent research suggests that the crossspecies scaling equation used for mammals is not appropriate for avian species (Mineau et al.,

1996). Using a database that characterized acute toxicity of pesticides to avian receptors of

various body weights, Mineau et al. (1996) concluded that applying mammalian scaling

equations may not sufficiently predict protective doses for avian species. Benchmarks scaled for

small-bodied avian species using the mammalian equation generated scaled doses that were not

protective enough for small birds. Mineau et al. (1996) suggested a scaling factor of 1 provided

a better dose estimate for birds. Therefore, a scaling factor of 1 was applied for avian receptors

(Equation 14-2). 

(14-1)

(14-2)

where

EBw = scaled ecological benchmark for species w (mg/kg/d)

MATCt = maximum acceptable toxicant concentration (mg/kg/d) 

bwt = body weight of the surrogate test species (kg)

bww = body weight of the representative wildlife species (kg).

Body weights for ecological receptors were identified from two primary sources: the

Wildlife Exposure Factors Handbook (U.S. EPA, 1993b) and Sample et al. (1997). Body

weights for wildlife species not covered in these sources were identified through primary
Section 14.0 Ecological Benchmarks

2

Herpetofauna includes species of amphibians and reptiles. Insufficient ecotoxicity data were identified to

derive CSCLs for reptiles. Therefore, continued discussions only review amphibians. 

14-12

Data Requirements for FCV Calculation

# The family Salmonidae in the class

Osteichthyes,

# One other family (preferably a commercially or

recreationally important warmwater species) in

the class Osteichthyes (e.g., bluegill, channel

catfish),

# A third family in the phylum Chordata (e.g., fish,

amphibian),

# A planktonic crustacean (e.g., a cladoceran,

copepod),

# A benthic crustacean (e.g., ostracod, isopod,

amphipod),

# An insect (e.g., mayfly, dragonfly, damselfly,

stonefly, midge),

# A family in a phylum other than Arthropoda or

Chordata (e.g., Rotifera, Annelida, Mollusca),

and

# A family in any order of insect or any phylum

not already presented.

literature sources. (See the exposure factors database documentation section for an expanded

discussion of receptor body weights.) Applying these decision criteria and methods resulted in

the selection of benchmark studies and derivation of benchmark doses presented in

Appendix 14A, Tables 14A-1 and 14A-2, for mammals and birds, respectively. The final scaled

benchmarks for representative species are presented in Appendix 14A, Table 14A-10.

14.3.1.1.2 Total Surface Water CSCLs (ChemCSCLWaterTotRec). The CSCLs

developed for surface water based on total concentrations of the constituent covered the

following receptor taxa: freshwater community (i.e., fish and aquatic invertebrates),

algae/aquatic plants, and herpetofauna.2 The methods used to derive CSCLs are reviewed here

for each receptor taxon. The CSCL developed for the freshwater community was derived to

reflect both total and dissolved water concentrations (see Section 14.3.1.1.3 for a discussion of

the methods used to derive dissolved CSCLs). The resulting CSCLs developed for these taxa are

presented in Appendix 14A in Table 14A-3 (total freshwater community), Table 14A-5 (algae

and aquatic plants), and Table 14A-6 (amphibians). 

Freshwater Community

The freshwater community CSCL was

developed to protect species of fish and

aquatic invertebrates. The CSCL does not

extend to protect species of mammals and

birds that may forage in freshwater

ecosystems. The methods adopted to develop

freshwater community CSCLs are consistent

with those supported across EPA offices. 

The CSCLs were derived using

methodologies founded through the

development of the National Ambient Water

Quality Criteria (NAWQC). These methods

require the compilation of appropriate acute

and chronic ecotoxicity data reporting effects

to survival, growth, and reproduction in

aquatic biota for specific members of the

freshwater community. The NAWQC

method uses a list of ecotoxicity data

requirements for eight taxonomic families

that represent typical freshwater species (see

accompanying text box). Whether a final

chronic value (FCV) or a secondary chronic

value (SCV) is calculated depends on how

well the eight taxonomic families are

represented by the data. 
Section 14.0 Ecological Benchmarks

14-13

For populations of the freshwater community (e.g., fish, aquatic invertebrates), the FCV

developed for the NAWQC or the criterion continuous concentration (CCC) developed for the

Great Lakes Water Quality Initiative (GLWQI) was the preferred CSCL to use for this analysis

(U.S. EPA, 1995a, 1996a). If neither a CCC nor an FCV was available, an SCV was calculated

using Tier II methods developed through the GLWQI (Stephan et al., 1985; Suter and Tsao,

1996). 

A brief overview of the derivation methodology is provided here; however, note that this

description is a simplification of the actual methods and does not address many of the nuances of

study selection and data interpretation. For a complete review of calculation methods, refer to

Stephan et al. (1985).

# FCV and CCC—An FCV and a CCC are calculated in one of two ways. If

acceptable chronic toxicity data are available on at least one species representing

each of the eight different data requirements, the FCV is essentially the

concentration corresponding to a cumulative probability of 0.05 for the

appropriate species. If the chronic toxicity data do not meet the eight family

requirements, the FCV is calculated by (1) calculating a final acute value (FAV)

that meets the eight species requirements, (2) estimating an acute-to-chronic ratio

(ACR) as the ratio of at least three comparable (e.g., same-species) acute and

chronic toxicity studies, (3) dividing the FAV by 2, and (4) dividing the result of

the Step 3 value by the ACR. 

# SCV—An SCV is calculated using analogous methods as those applied in

calculating the FCV. The Tier II methods, however, (1) require chronic data on at

least one of the eight species requirements, (2) use a secondary acute value (SAV)

in place of the FAV, and (3) are derived based on a statistical analysis of

NAWQC data conducted by Host et al. (1991). Host et al. (1991) developed

adjustment factors (AFs) depending on the number of taxonomic families

represented in the database. The Tier II methodology was designed to generate

SCVs that are below FCVs (for a complete data set) with a 95 percent confidence

limit. 

Algae and Aquatic Plants

For algae and aquatic plants, toxicological benchmarks were identified in the open

literature or from data compiled in Toxicological Benchmarks for Screening Potential

Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision (Suter and Tsao, 1996). 

For most contaminants, studies were not available for aquatic vascular plants, but lowest-effects

concentrations were identified for algae. The criteria for algae and aquatic plants were based on 

a lowest-observed-effect concentration (LOEC) for vascular aquatic plants or an effective

concentration (ECxx) for a species of freshwater algae, frequently a species of green algae (e.g.,

Selenastrum capricornutum). Because of the lack of data in this receptor group and the

differences between vascular aquatic plants and algae sensitivity, usually the lowest value of

those identified was used. In instances where only a median effective carcentration (EC50) was

identified to characterize effects to algae growth and survival, a safety factor of 5 was applied to

generate an estimated low effects concentration.
Section 14.0 Ecological Benchmarks

14-14

Amphibians

Amphibians appear to be highly sensitive to a number of toxicants during the

developmental stages of their life cycle (e.g., trace metals). Amphibians are essential parts of a

number of food webs (particularly wetlands) and are likely to provide a fairly sensitive indicator

for chemical stressors relevant to higher levels of biological organization. Though amphibians

are a significant ecological receptor, ecotoxicity data characterizing the chronic dose-response

relationship for chemicals of concern are limited. After a review of several compendia

presenting amphibian ecotoxicity data (e.g., Devillers and Exbrayat, 1992; Power et al., 1989;

U.S. EPA, 1996b) as well as primary literature sources, no suitable subchronic or chronic studies

were identified that reported effects to reproductive or developmental endpoints in amphibian

species. Therefore, a CSCL based on chronic endpoints and exposure durations was not derived. 

Instead, the CSCL was developed from a geometric mean of acute (i.e., LC50, lethal water

concentration resulting in 50 percent mortality) amphibian ecotoxicity data. A few general

guidelines were followed in selecting analogous acute studies for developing the CSCL: 

# Test duration was usually less than 15 d.

# Toxicity endpoints included mortality (LC50) 

# Exposure occurred during early life stages (i.e., embryo, larvae, and tadpole).

Because the criteria are based on acute data (i.e., lethality), the severity of the potential

adverse effects that this criteria indicates is significant. Incorporating the amphibian data into

the NAWQC within the data requirement categories is currently under consideration. Because

amphibian species are more likely to breed in standing waters such as wetlands, ponds, or

temporary puddles, the appropriateness of combining protection of amphibian receptors with the

freshwater community CSCL is unclear.

14.3.1.1.3 Dissolved Surface Water CSCLs (ChemCSCLWaterDissRec). Conversion

factors were available for several of the metal constituents to convert total metal concentrations

in the water column to total dissolved concentrations (U.S. EPA, 1999b). Although the total

concentrations supplied by the NAWQC and GLWQI are still deemed scientifically defensible

by EPA, the Agency recommends the use of dissolved metal concentrations when they are

available (Prothro, 1993). 

Methods are currently only available to develop dissolved CSCLs for metals in the

freshwater community. Dissolved CSCLs were derived from total water CSCLs using a

conversion factor. The conversion factors applicable to chronic criterion in freshwater are

presented in Table 14-5. The conversion factors were developed by EPA using a series of 

filtration experiments that measured the difference between filtered and unfiltered concentrations

of metals in surface waters. Dissolved CSCLs were derived by multiplying the total CSCL by

the conversion factor (Equation 14-3).

(14-3)

 

where
Section 14.0 Ecological Benchmarks

14-15

Metal CSCL total = either an FCV or an SCV in freshwater

Conversion Factor = the fraction of dissolved metal. 

The final CSCLs generated for the freshwater community based on the total dissolved

constituent concentrations are provided in Table 14A-4 of Appendix 14A.

Table 14-5. Conversion Factors for Dissolved Metala

Constituent Conversion Factor

Arsenic 1.00

Cadmium2 1.1017-[(ln hardness)(0.04184)] 

Chromium III 0.860

Chromium VI 0.960

Leadb 1.4620-[(ln hardness)(0.14571)]

Mercury 0.850

Zinc 0.986

aConversion factor for chronic CSCLs in freshwater.

b Dependent on the water hardness (assumed to be 100 mg CaCO3/L for this analysis).

14.3.1.1.4 Sediment CSCL (ChemCSCLSedimentRec). Two methods were applied in

developing the CSCL for the benthic community (e.g., worms, amphipods). The first and

preferred method used measured sediment concentrations that resulted in minimal effects to the

composition and abundance of the sediment community. The sediment criteria were derived

from the upper limit of the range of sediment contaminant concentrations dominated by noeffects data to survival, species diversity, and abundance endpoints. Measurements to derive the

CSCLs were taken at the national scale and reflected a variety of sediment types and benthic

community species. The second CSCL derivation method used the equilibrium partitioning

(EqP) relationship between sediments and surface waters to predict a protective concentration for

the benthic community. This method was used only for nonionic organic constituents. For the

benthic community, the approach used to establish CSCLs was based on a complete assessment

of several sources proposing protective sediment CSCLs (Table 14-3). A discussion of each

method (i.e., measured and estimated CSCLs) is provided. The resulting benthic CSCLs are

presented in Appendix 14A, Table 14A-7.

Measured Sediment CSCLs

The primary sources of measured sediment CSCLs are the National Oceanic and

Atmospheric Administration (NOAA) and the Florida Department of Environmental Protection

(FDEP) sediment documents. NOAA annually collects and analyzes sediment samples from

sites located in coastal marine and estuarine environments throughout the United States as part of
Section 14.0 Ecological Benchmarks

14-16

the National Status and Trends (NS&T) Program. Data collected by NOAA include measured

sediment concentrations and the corresponding measures of toxicity in resident species such as

amphipods, arthropods, and bivalves on a variety of community-based endpoints (e.g.,

abundance, mortality, species composition, and species richness). These data are used by

NOAA to estimate the 10th percentile effects concentration (ER-L) and a median effects

concentration (ER-M) for adverse effects in the sediment community. These values are not

NOAA standards; rather, they are used to rank sites based on the potential for adverse ecological

effects. In contrast, the FDEP sediment criteria were developed from the ER-L and ER-M data

to approximate a probable effects level (PEL, estimated from ER-M data) and a threshold effects

level (TEL, estimated from ER-L data). PELs and TELs correspond to the statistically derived

upper limit of contaminated sediment concentrations that demonstrate probable effects and no

effects to the benthic community, respectively. Generally, FDEP values are more conservative

than NOAA values. Even though these criteria were developed for a marine community,

researchers have demonstrated that marine TELs have good correlation with no-effects levels

found for freshwater systems (Smith et al., 1996). In order of preference, TELs were adopted as

CSCLs if available; if not, ER-L values were used. The FDEP criteria were chosen above the

NOAA criteria for the following reasons:

# The same database was used for both the NOAA criteria and the FDEP criteria

development.

# In most cases, the FDEP criteria were more conservative than the NOAA criteria

because a larger portion of the low-effects data was used in benchmark

development.

# The marine TELs developed by the FDEP were found to be analogous to TELs

observed in freshwater organisms (Smith et al., 1996). 

Estimated Sediment CSCLs

When measured effects data were not available for organic constituents using the TEL or

ER-L approach, the value was derived using the EqP approach to estimate the sediment CSCL

(U.S. EPA, 1993a). The surface water FCV or SCV was used to generate a sediment CSCL

using the partitioning relationships among surface water, pore water, and organic carbon in

sediment. This method assumes that the equilibrium partitioning between the sediment and the

water column is a function of the organic carbon. Equations 14-4 and 14-5 were used to

calculate the sediment CSCL depending on whether an FCV or an SCV was available. In

calculating sediment CSCL for nonionic chemicals, the fraction organic carbon (foc) was

assumed to be 1 percent total organic carbon and Kocs (organic carbon partitioning coefficients)

were adopted as reported in Jones et al. (1997). However, because sediment CSCLs were

derived for organic constituents based on site-specific foc, the CSCLs in Table 14A-7 were

recalculated within the 3MRA modeling system on a site-specific basis.

(14-4)
Section 14.0 Ecological Benchmarks

14-17

(14-5)

14.3.1.1.5 Soil CSCLs (ChemCSCLSoilRec). Soil CSCLs were derived for the

terrestrial plant community and the soil community. Each of the specific methods, including the

rationale and the derivation methods, is outlined in the following sections. The results of the soil

CSCL development are presented in Table 14A-8 (terrestrial plant community) and Table 14A-9

(soil community) of Appendix 14A. 

Terrestrial Plants

For the terrestrial plant community, toxicological benchmarks were identified from a

summary document prepared at the Oak Ridge National Laboratory (ORNL): Toxicological

Benchmarks for Screening Potential Contaminants of Concern for Effects on Terrestrial Plants:

1997 Revision (Efroymson, Will, Suter, and Wooten, 1997). The measurement endpoints were

generally limited to growth and yield parameters for the following reasons: 

# They are the most common class of responses reported in phytotoxicity studies

and, therefore, allow for criterion calculations for a large number of constituents.

# They are ecologically significant responses, both in terms of plant populations

and, by extension, the ability of producers to support higher trophic levels. 

As presented in Efroymson, Will, Suter, and Wooten (1997), criteria for phytotoxicity were

selected by rank ordering the LOEC values and then approximating the 10th percentile. If there

were 10 or fewer values for a chemical, the lowest LOEC was used. If there were more than 10

values, the 10th percentile LOEC was used. 

Soil Community

Two methods were used in deriving soil community CSCLs: a community-based CSCL

and an earthworm/microbial CSCL. 

Community-Based CSCL—The first, and preferred, method was based on a communitylevel approach similar to that applied in deriving the NAWQC. This method developed a CSCL

based on NOECs to reproductive and development endpoints in a number of key functional taxa

in the soil community. The CSCL was designed to protect the structure and function of the soil

community and its critical role in the overall nutrient processing that occurs in the terrestrial

food web. A detailed discussion of the decision criteria and calculations used to develop a

community-based CSCL are provided in the following section “Methodology to Develop

Community-Based CSCLs.” Review of the primary literature only supplied sufficient data to

develop a community-based soil CSCL for the constituents of lead and cadmium. 

Two key uncertainties were noted in the development of community-based CSCLs. First,

the ecotoxicity data used in the method are based on NOECs. The CSCLs developed using the

earthworm/microbial method for the soil community were based on low-effects levels. Because

these CSCLs are based on no-effects soil concentrations, some added conservatism was
Section 14.0 Ecological Benchmarks

14-18

generated in the soil community CSCLs for lead and cadmium. Second, the species taxa groups

designed to represent key compartments in the soil community did not include microbes. This

introduces some uncertainty in the soil CSCL because microflora make up approximately 80 to

90 percent of the biomass in soil and microflora are responsible for the majority of the biological

activity in soil (e.g., N mineralization). 

Earthworm and Microbial CSCLs—The second method used to derive soil CSCLs

required the identification of LOECs for earthworms and microbial endpoints. However,

because a single species alone cannot predict the potential toxicological impacts to the soil

community, the community-based method was preferred over using an earthworm or microbial

CSCL. 

Earthworms have been recognized to play important roles in promoting soil fertility,

releasing nutrients, and providing aeration and aggregation of soil, as well as being an important

food source for higher trophic level organisms. In addition, their constant contact with soil

media and permeable epidermis makes them more susceptible to contaminant exposures.

Likewise, microbial communities play a key functional role in soil fertility, decomposition

processes, and nutrient cycling, providing nutrients in available forms to plants. Microbial

CSCLs were only used when they indicated a significantly higher sensitivity to a particular

constituent than the corresponding earthworm toxicity data. This was the case only for nickel

and zinc. 

The earthworm and microbial CSCLs were developed using the ER-L approach, which

was also applied to develop terrestrial plant CSCLs. When more than 10 studies were identified

reporting LOECs, then the 10th percentile of the values was derived as the CSCL. When less

than 10 values were identified, however, the lowest LOEC was selected as the CSCL. When

sufficient LOEC data were identified, this method was used to develop soil CSCLs for all

constituents except lead and cadmium.

Methodology to Develop Community-Based CSCLs–The process of developing

community-based soil CSCLs may be divided into three basic components: (1) selection of

representative soil species, (2) collection of toxicological data on soil species, and (3) calculation

of a CSCL for the soil community. Each of these steps is detailed in the following sections. 

Selection of Representative Soil Species —Two important assumptions were made in

developing the approach to select representative soil species. First, species using resources in a

similar way (e.g., similar diet) should receive similar exposures (i.e., guild theory). Second,

taxonomically related soil invertebrates tend to have similar toxicological sensitivity to

chemicals (Neuhauser et al., 1986). Soil communities are made up of numerous groups of

species performing one or more functions for the community. Thus, the set of representative

species was designed to reflect the breadth and variety of taxonomic and structural/functional

groups. Five metrics were identified to serve as a practical guide in the selection of appropriate

soil species. Figure 14-1 illustrates the generalized soil community that is reflected in these

metrics.

Five metrics were used to select representative soil species, as follows:
Section 14.0 Ecological Benchmarks

14-19

1. Organism size–classified into three groups: microfauna (<0.15 mm; e.g.,

Protozoa, Nematoda), mesofauna (0.16 to 10 mm; e.g., Enchytraeidae, Acari), and

macrofauna (>10 mm; i.e., larger invertebrates). This convenient, albeit somewhat

arbitrary, classification was useful in considering the interactions between soil

species and their habitat.

2. Distribution in soil horizon–divided into three layers: deep mineral, shallow

organic, and soil litter. Exposures to soil contaminants are presumed to occur for

organisms at any horizon. The top two horizons, however, tend to receive higher

exposures to persistent and relatively immobile contaminants (such as some

metals).

3. Abundance–the number of individuals present in a typical habitat. Caution must

be implemented in using this criterion because abundant species are not always

the most ecologically significant. For example, nematodes and annelids both

contribute equally to the flux of CO2, yet nematodes outnumber annelids more

than 100 to 1 (Reiche, 1977).

4. Energy metabolism–the relative importance of a species to the overall community

can be based on the contribution of energy that species provides (Curry, 1994).

Increasingly, energy budgets are being viewed as useful tools in assessing

ecological significance.

5. Function in community–feeding preferences of different organisms largely define

their role in the trophic structure (see Figure 14-1), shaping the dynamics of the

soil community. The selection of species should adequately represent different

functional roles within the trophic structure. To ensure a balanced representation

of a generalized soil community, organisms were classified into four functional

categories (Brown, 1978):
Section 14.0 Ecological Benchmarks

14-20

Figure 14-1. Simplified trophic structure of a generalized soil community.

# Microphytic–organisms that feed on fungal spores, hyphae, lichens, and bacteria

(e.g., ants, fungus gnats, nematodes, and Protozoa)

# Saprophytic–organisms that feed on dead or decaying organic matter (e.g., 

earthworms, Acari, and Collembola)

# Phytophagous–organisms that feed on living plant material including plant stems,

leaves, roots, or woody parts (e.g., mollusks, symphylids, termites, and insect

larvae)

# Carnivorous–organisms that are true predators (e.g., carabids, mites, and spiders).

Collection of Toxicological Data on Soil Species—Guidelines were established to collect

data on NOECs for representative species in the soil community. The toxicological data included

studies on a variety of relevant physiological and process-based endpoints (e.g., cocoon

production, maintenance of reproductive processes). Assumed routes of exposure were direct

contact and ingestion. Toxicological representation of each of the following species groups was

the goal of data collection efforts.
Section 14.0 Ecological Benchmarks

14-21

(14-6)

Group 1–one species from the phylum Nematoda. Nematodes are the most abundant

organisms in the soil and provide the third largest amount of biomass. In addition, they represent

the only microfauna evaluated.

Group 2–one species of soil mite (Acarina) from one of the following suborders:

Cryptostigmata, Prostigmata, Mesostigmata, or Metastigmata. Soil mites are important as

decomposers, predators, and plant eaters. Mites provide the largest amount of CO2 flux among

these groups.

Group 3–one insect from the order Collembola. Springtails were selected because they

are saprophytic and the second most abundant invertebrates in the soil. Their high abundance

also results in moderately high biomass.

Groups 4 and 5–two annelids from the orders Plesiopora or Opisthopora (families

Enchytraeidea and Lumbricidae preferred). The Oligochaeta represent some of the largest soil

organisms and, as subterranean animals, are important saprophytic feeders. Members of

Opisthopora are the largest contributors to soil fauna biomass.

Groups 6 and 7–two additional species of arthropods selected from one of the following

taxonomic groups: Diptera, Coleoptara, Isopoda, Chilopoda, and Diplopoda. Arthropods play a

variety of critical roles in the soil community and rank high in terms of all five metrics.

Group 8–a species of mollusk from the order Stylommatophora. Although the majority

of mollusks are marine organisms, they represent surface decomposers in the trophic structure

that are not duplicated by the other organisms in the representative set.

Calculation of CSCL for the Soil Community—The statistical approach adopted consisted

of two steps: (1) fitting the NOEC data on representative species of soil biota to a lognormal

distribution and (2) extrapolating to a criterion based on the mean and standard deviation of the

toxicity data set. Key assumptions were that NOEC data are distributed lognormally and the 95

percent level of protection is ecologically significant. The approach to calculating CSCLs for

the soil community was based on efforts by Dutch scientists (the RIVM methodology) to

develop hazardous concentrations (HCs) at specified levels of protection (primarily 95 percent)

at both a 95th percentile and a 50th percentile level of confidence (Aldenberg & Slob, 1993;

Sloof, 1992; VanStraalen & Denneman, 1989). For the soil community CSCL, the 50th

percentile level of confidence was selected because the 95th percentile appeared to be overly

conservative for a no-effects approach. Equation 14-6 was used to calculate soil community

CSCLs.

where

HC5% = soil concentration protecting 95 percent of the soil species
Section 14.0 Ecological Benchmarks

14-22

xm = sample mean of the log NOEC data

kl = extrapolation constant for calculating the one-sided leftmost confidence limit

for a 95 percent protection level

sm = sample standard deviation of the log NOEC data.

Note that only one value for kl

 is calculated for the 50th and 95th percentile confidence

limits, respectively, for each sample size (m). Consequently, it is assumed that there is just one

extrapolation constant with the required confidence property for each species sample size and

extrapolation factors may be determined through Monte Carlo simulation by generating random

sample averages and deviations for the standard logistic distribution and adjusting for a specified

confidence level (i.e., 50th or 95th). 

14.3.1.2 Database Processing. Minimal manual processing of the benchmark/CSCL

database was conducted. Most of the CSCL and benchmark values generated were manually

entered into the data table. The parameters for the benchmark/CSCL database were onedimensional chemical properties that were dimensioned on the variable Num Receptor in the

Ecological Risk Module. 

Processing of the benchmark/CSCL database was conducted for the scaling of

mammalian and avian benchmarks and the derivation of module-generated, site-based CSCLs

(e.g., hardness dependent upon water quality criteria). Data processing was conducted on the

mammalian benchmarks, which were scaled by body weight to extrapolate from surrogate

laboratory species to representative wildlife species (see Section 14.3.1). In addition, some of

the criteria were generated on a site-specific basis using parameters of water hardness (mg

CaCO3/L) and foc in sediment. In cases where CSCLs were developed on a site-specific basis, 

CSCLs reported in the database may not reflect the value used in calculate hazard quotient (HQ)

calculations. 

14.3.1.3 Assumptions and Uncertainties. In this section, the key assumptions and

uncertainties associated with the application and development of the ecological benchmark and

CSCL database are reviewed. The discussion of assumptions and uncertainties is constructed

around three key issues: (1) the relationship between assessment endpoints and measures of

effect, (2) the quality of the ecotoxicological data, and (3) the extrapolation methods used to

derive receptor-specific benchmarks and CSCLs from the ecotoxicity data.

14.3.1.3.1 Relationship Between Assessment Endpoints and Measures of Effect. In

developing ecological benchmarks and CSCLs for the representative national data set, it is

crucial to establish the relationship between the assessment endpoints (i.e., the ecological values

to be protected) and the measures of effect (i.e., the ecotoxicity data used to support benchmarks

and CSCLs). Because the 3MRA modeling system is predictive, there is no mechanism to verify

that assessment endpoints are, in fact, protected by the measures of effect selected to support

benchmark/CSCL development. Consequently, there is uncertainty in applying the

benchmarks/CSCLs to evaluate risks to the assessment endpoints chosen for the example data

set. These uncertainties are discussed below along with key assumptions that are implicit in

developing benchmarks and CSCLs (e.g., 95 percent protection level for aquatic biota). 
Section 14.0 Ecological Benchmarks

14-23

Mammals and Birds

# Assessment Endpoint: maintain viable mammalian and avian wildlife

populations. The attribute to be protected was the reproductive and

developmental success of representative species.

# Measure of Effect: a de minimis threshold for developmental and reproductive

toxicity in mammalian and avian wildlife species. The threshold was calculated

as the geometric mean of the NOAEL and LOAEL, frequently referred to as the

maximum acceptable toxicant concentration (MATC). Implicit in this calculation

is the assumption that the toxicological sensitivity is lognormal. 

An important source of uncertainty is the benchmark calculation of the MATC. Based on

numerous discussions among the technical staff at OSW, this threshold value was determined to

be appropriate given the assessment endpoints for a national assessment. The rationale for this

determination is based on two assertions: (1) the MATC is above a no effects level and,

therefore, is associated with some finite level of risk (i.e., the regulations would not be based on

no effects), and (2) the MATC is conservative in that it does not allow for the level of effect

associated with a low effects level (often estimated at roughly 20 percent of the population). In

making the assumption that a threshold for effects on individual organisms can be used to predict

the potential risks to populations, we accept considerable uncertainty regarding the “true” effects

on wildlife populations that can only be addressed through simulations with population-level

models. These models are designed to address various elements of population dynamics, such as

predator prey interactions, carrying capacity of the habitat, immigration and emigration, and

initial population size (to name but a few attributes of population-level models). Nevertheless,

because the MATC is assumed to be below the level of effect distinguishable from natural

population variability, it is assumed that the benchmark provides a reasonably conservative level

of protection to wildlife populations.

A second important source of uncertainty is in the selection of study endpoints, in

essence, how well an MATC based on reproductive/developmental effects translates into

maintenance of wildlife populations. Although the selection of reproductive and developmental

effects is consistent with current EPA guidance on ecological risk assessment, it is not possible

to demonstrate with certainty that these are the critical endpoints of concern. For example,

neurological effects that impact behavior may occur at a threshold value below the MATC. 

Depending upon the nature and severity of the effect (e.g., inability to avoid predators), a

constituent may affect enough organisms that relatively few reach reproductive maturity. As a

result, the overall impacts on the wildlife population may be greater than those inferred from

endpoints on reproductive fitness and developmental effects. The implications for receptors with

relatively large home ranges (e.g., wolves) are difficult to interpret. For these receptors, the

study area may impact only a single reproducing pair of animals and the endpoint of interest may

be crucial in determining: (1) whether adverse effects occur and (2) what the ecological

significance of those effects might be. 
Section 14.0 Ecological Benchmarks

14-24

CSCLs for the Freshwater and Soil Communities

# Assessment Endpoint: maintain sustainable community structure and function.

The attributes to be protected were growth, survival, and reproductive success of

species that represent key functional roles in the community.

# Measure of Effect: concentration in soil or surface water, respectively, based on

ecotoxicity studies on endpoints that include lethality, fecundity, growth, and

survival. The CSCLs for the freshwater and soil communities were typically

derived at a 95 percent protection level using both no effects and low effects data,

as appropriate. When available, the Ambient Water Quality Criteria for chronic

effects were chosen as the freshwater CSCLs.

The CSCLs derived for the soil and freshwater organisms are intended to ensure

protection of critical structures and functions of the respective communities. However, the

CSCLs are not true community-level measures of effect in that they do not consider the complex

interactions among community members. Consequently, there is uncertainty inherent in

inferring risk estimates for the community from a statistical interpretation of data on individual

organisms. 

In addition, there has been some criticism of the method used to develop the communitybased soil CSCL because it does not incorporate microbial populations as a taxa category. There

is some question about the endpoint and level of effect that would result in an ecologically

significant no- or low-adverse effects to microorganisms (e.g., LOEC, EC25, or EC50 for

nitrification). There is no doubt that microbial communities are critical to the continued

functioning of soil communities, and work is ongoing to consider how to appropriately include

this receptor group in the species requirements. Their absence in the current method generates

some uncertainty that the measure of effect provides protection to this key receptor.

Ecotoxicity data on earthworms were used to derive CSCLs for the soil community if no

other suitable data were identified (i.e., if the data set were limited exclusively to earthworms). 

However, earthworms represent only one element of a healthy soil community and there is large

uncertainty in applying these data to evaluate risks to the entire community. Earthworms play an

important role in the soil community (e.g., soil fertility, nutrient release, aeration, food source for

predators) and, because ecotoxicity data are relatively abundant, are valuable as indicator

species. 

Benthic Community

# Assessment Endpoint: maintain sustainable community structure and function. 

The attributes of the benthic community to be protected included the growth,

survival, and reproductive success of benthic biota. 

# Measure of Effect: concentration in sediment based on ecotoxicity studies on

endpoints that include lethality, fecundity, growth, and survival. The CSCLs for

the sediment community were typically derived at a 95 percent protection level

using both no effects and low effects data, as appropriate. As with the freshwater
Section 14.0 Ecological Benchmarks

14-25

CSCLs, the Ambient Water Quality Criteria for chronic effects were used to

support the sediment CSCLs. In addition, field data on the toxicity of metals to

sediment communities in saltwater were also used to develop sediment CSCLs

and include a number of “true” community-level effects (e.g., abundance of

sediment biota).

The CSCLs for metals were derived from field studies conducted in marine ecosystems. 

These data were based on effects to marine biota and reflect the surface water chemistry and

equilibria characteristic of marine systems. It is implicitly assumed that: (1) the relative

sensitivity of species in saltwater sediments is similar to those in freshwater sediments, and

(2) the behavior of metals (e.g., bioavailability) in the marine environment is not significantly

different from the freshwater environment. However, comparisons made between freshwater

and marine CSCLs developed using analogous methods indicate that there is not a significant

difference between the effects seen across these systems at low exposure levels (Smith et al.,

1996). The methods used to collect field data do not fully support a definitive cause-effect

relationship because they do not account for other stressors that may impact the sediment

community (i.e., temperature, predation). The CSCLs for non-ionizing organic constituents were

developed based on EPA guidelines for sediment community criteria.

Terrestrial Plant Community

# Assessment Endpoint: maintain structure and function of terrestrial plant

community. The attributes to be protected included growth and survival of

terrestrial plants. 

# Measure of Effect: soil concentrations related to growth, yield, seedling

emergence germination endpoints. The low effects data on phytotoxicity were

rank ordered and the plant CSCL was estimated as the 10th percentile value.

The endpoints for plants were limited to low effects concentrations for growth and yield

parameters such as seed germination, seedling emergence, and vegetative vigor. It is unclear,

however, if the selected measure of effect actually represents a biologically significant effect to

populations of wild plants since terrestrial plant communities are quite robust and can shift to

more tolerant plant species, and still maintain an adequate prey base for herbivores. There is

added uncertainty because most of the ecotoxicity data identified were based on studies using

agricultural varieties of plants. Further, other effects, such as RNA synthesis or respiration, may

be more sensitive indicators of potentially significant risks to plants. Substantial uncertainty will

be associated with evaluating risks to the plant community until studies are available to

determine: (1) the most sensitive, biologically significant endpoint for plants (e.g., seed

germination, early growth), and (2) the effects level at which the effect should be considered

significant in terms of plant population growth and survival. 

Algae/Aquatic Plants

# Assessment Endpoint: maintain primary producers in freshwater systems,

including both algal and vascular aquatic plant communities. The attribute to be

protected for this taxa was the growth and biomass.
Section 14.0 Ecological Benchmarks

14-26

# Measure of Effect: surface water concentrations related to gross measures of

“health” (e.g., biomass) for the algal community and a variety of endpoints for

aquatic plants (e.g., number of fronds, root number, plant number, root length).

For algae, the EC20 was selected as an adequate threshold for adverse effects and,

because of the paucity of data, the lowest LOEC for endpoints of interest was

chosen for vascular aquatic plants.

Algae and aquatic plants not only provide a food source for aquatic biota, but also

provide needed structure and habitat for many aquatic species. Because the assessment endpoint

includes the functional contribution of primary aquatic producers to aquatic ecosystems, there is

uncertainty in applying low effects concentrations to this receptor group to protect its value to

the ecosystem as a whole. Nevertheless, the design of the 3MRA modeling system goes well

beyond screening and, therefore, use of no effects data was considered inappropriate.

Data availability on algae far exceeded the data identified for vascular aquatic plants. As

a result, the CSCL for aquatic producers generally reflects ecotoxicity studies on algae. Because

little is known about the relative sensitivity between algae and aquatic plants, representing this

receptor group with algal data introduces additional uncertainty in the risk estimates for

freshwater systems. There are significant differences in uptake, transport, and biochemical

processes between algae and aquatic plants and, therefore, uncertainty in determining how well

the measures of effect act to maintain communities of primary producers in aquatic systems.

Amphibians

# Assessment Endpoint: maintain viable amphibian populations. The attribute to be

protected was the survival and developmental success of these receptors. 

# Measure of Effect: The measure of effect selected to meet the assessment

endpoint was the acute LC50s for lethality and survival and developmental effects

resulting from early lifestage exposures.

As indicated by the assessment endpoint, this surface water CSCL was designed to

protect amphibian species. 

There is additional uncertainty that the measure of effect used for herpetofauna

adequately represents a level of protection suitable to the assessment. The CSCL represents a

relatively severe effect that includes lethality to 50 percent of the population; this level of effect

far exceeds other CSCLs developed for the representative national data set and should be

considered as nonconservative. Therefore, there is substantial uncertainty in applying this

measure of effect given the goal of maintaining viable herp populations. Acute data were used to

develop this CSCL because so few chronic data were available. There potentially could be

dramatic impacts to other more sensitive endpoints such as reproduction at these surface water

CSCLs and, moreover, herpetofauna appear to be under considerable stress from other, as yet

unidentified, factors.

The CSCLs for herpetofauna cannot be categorized as protective given nature and

magnitude of potential effects. Additional analysis of the risk results for this receptor group may
Section 14.0 Ecological Benchmarks

14-27

be warranted for exit criteria associated with herpetofauna HQs close to the target value of 1.

The uncertainty associated with the protection of this species needs special attention when the

risk results are interpreted.

14.3.1.3.2 Data Quality Issues. In addition to uncertainties associated with the

application of benchmarks/CSCLs, there are uncertainties inherent in the development of

benchmarks/CSCLs (e.g., extrapolating from dose-response data; interspecies scaling of

benchmarks). The quality and quantity of data used to develop the benchmarks and CSCLs

varies greatly across the receptor groups. Thus, there are uncertainties inherent in deriving

benchmarks and CSCLs using such a wide range of ecotoxicological data. The key data quality

issues are reviewed here.

No-Effects Concentrations Used When Low-Effects Data Were Unavailable

For some of the receptor taxa, only a no-effects concentration was identified through

literature searches. In cases where no-effects data were available but sufficient low-effects data

were not, the no-effects level was used. As a result, some benchmarks are more conservative

than others. This was the case for the soil community CSCLs calculated for lead and cadmium.

Statistically Based Soil Community CSCLs

The community-based soil CSCL was developed to assess the potential effects to

multiple trophic elements and various key taxa. This method was applied only for a limited

number of metals in the analysis; however, there are several unresolved issues in the application

of this method.

# A variety of endpoints were aggregated to derive a geometric mean for the NOEC

data for each of the eight representative soil species data requirements. The

geometric mean of multiple values representing several measurement endpoints

has statistical meaning but not well-defined biological significance. The loss of

the true stressor-response relationship in this approach makes interpreting the

ecological significance of CSCL exceedances difficult. 

# The issue of bioavailability is particularly important in assessing the impacts to

the soil community, particularly for metals that exist in multiple ionic forms in the

environment. The toxicity and mobility of a metal can be highly influenced by

the local environmental chemistry of the soil matrix. Characterizing the

bioavailability of metals in different environmental conditions is crucial in

establishing CSCLs that are useful across different soil matrices. Bioavailability

was not accounted for in this methodology.

# Although soil invertebrates may be classified according to ecological function

(e.g., trophic level, feeding habits), few studies were identified that supported the

assumption that taxonomically related soil invertebrates have toxicologically

similar responses to chemical stressors (e.g., Neuhauser et al., 1986). In addition,

many species of soil invertebrates were excluded that occur only in specialized

microenvironments such as dung piles, carrion, and rotting wood (i.e., niche
Section 14.0 Ecological Benchmarks

14-28

organisms). As a result, species were selected to represent a range of trophic

levels and functions in the community (rather than selecting the "most sensitive"

species). This community-based approach assumes that, if key components in the

soil community are protected, community structure and function will not be

adversely affected. However, this approach has not been validated in field or

mesocosm studies. The development of a more generalized soil comunity

reduced the resolution of the potential impacts to this community.

Statistical versus Biological Endpoints

There is some uncertainty associated with using the MATC as a benchmark because it is

derived from statistically relevant endpoints rather than biologically relevant endpoints. 

Because the NOAELs and LOAELs are generated using hypothesis-testing statistics, the

quantification of these effects levels depends on the size, design, and variability of an experiment

(e.g., range-finding test or definitive test). Because the MATC is a geometric mean of two

statistically derived toxicity endpoints, uncertainty is generated by establishing this value as a

“protective” benchmark. In some cases, low-effects and no-effects concentrations derived using

hypothesis testing result in chronic benchmarks for aquatic organisms (e.g., MATCs) that result

in greater than 50 percent mortality (Stephan et al., 1985). For example, the MATC has been

shown to correspond to fairly high levels of effect. Data from 176 tests on 93 chemicals with

18 species indicated that average reductions in reproductive endpoints at the MATC were

20 percent for parental survival, 42 percent for fecundity, and 35 percent for an integrative

weight/egg parameter (Suter et al., 1987). The uncertainty associated with the biological

relevance and conservatism of these doses needs to be considered in the characterization of the

risk results. 

Research and Analysis of Data Supporting Benchmarks and CSCLs

A complete and exhaustive primary literature search has been completed for almost half

of the constituents considered in this analysis. For other constituents, secondary sources have

been consulted to identify appropriate benchmarks and CSCLs. The different levels of data

review and analysis were the result of changes made to the list of constituents after primary

literature searches were completed. Rather than conducting primary literature searches for the

newly added constituents, compendia were used to identify preliminary benchmarks and CSCLs

to support the risk estimates. The limited literature review given to these chemicals, listed in

Table 14-2, magnifies the uncertainties in developing benchmarks and CSCLs. 

14.3.1.3.3 Extrapolation

Uncertainty Factors Applied

Additional uncertainty was introduced into the analysis through developing the measures

of effect by applying uncertainty factors to convert LOAELs for mammalian and avian

benchmarks to NOAELs. When only LOAELs were available, the LOAEL was divided by 10 to

estimate the NOAEL. This is not an uncommon procedure when only a low-effects

concentration is available; however, EPA has recently assessed the accuracy of uncertainty

factors and reported that, in many cases, the difference can be less than 10. Applying a factor of
Section 14.0 Ecological Benchmarks

14-29

10 may create added conservatism in the MATCs generated for mammals and birds (Abt

Associates, Inc., 1995). For algae and aquatic plants, a similar uncertainty factor of 5 was

applied to convert EC50 data to estimate a low-effects concentration. 

Allometric Scaling

For mammals, differences in interspecies uncertainty were indirectly addressed through

the use of the species-scaling equation. This method is used by EPA in carcinogenicity

assessments when extrapolating from rats to humans. Wildlife toxicologists commonly scale

dose to body weight without incorporating the exponential factor. There is continued

disagreement among experts whether the application of scaling factors is appropriate in

ecological risk because this method may not account for physiological/biochemical differences

in species sensitivity. Applying this method to species demonstrating different sensitivities

across chemical classes introduces some uncertainty in the analysis. Allometric scaling was not

applied to avian receptors because a recent study indicated that scaling benchmark doses for

birds may not be protective of small-bodied avian receptors (Mineau et al., 1996).

Laboratory-to-Field Extrapolation

The toxicological benchmarks for ecological receptors were developed assuming that

effects that are observed in laboratory test species are applicable to wildlife species under similar

field conditions. As a result, there were no laboratory-to-field extrapolation factors applied to

account for the additional stress that may be encountered under field conditions (e.g., cold or

drought). Van Straalen and Denneman (1989) and Stephan et al. (1985) examined arguments

both for and against a laboratory-to-field extrapolation factor and concluded that laboratory-tofield extrapolation factors were not necessary; i.e., criteria derived with laboratory data should

protect soil fauna in the field. However, other authors have suggested that laboratory species

tend to be more homogeneous and have narrower tolerance distributions than their field

counterparts, and that the distribution of the target population of species is likely to have a

different shape and scale relative to the laboratory species (Smith and Cairns, 1993; Suter et al.,

1983). As a result, the distribution of the endpoint will be narrower for the laboratory species. 

In addition, Smith and Cairns (1993) point out that local adaptation to conditions may make an

individual species more or less tolerant to a chemical stressor. 

14.4 Quality Assurance/Quality Control

14.4.1 Technical QA/QC

Each value in the benchmark/CSCL database has undergone some level of technical QA. 

Constituents that were included in the proposed representative national data set have undergone

extensive review and have been periodically updated to reflect new findings. Additional

constituents included after the primary literature review was completed have been technically

reviewed for appropriateness. Technical QA efforts went into reviewing the decision criteria

used in benchmark and CSCL development to ensure that the implementation of the methods

produced appropriate values.
Section 14.0 Ecological Benchmarks

14-30

14.4.2 Data Entry QA/QC

Data entry was performed primarily by hard-copy data entry. Data were checked by

different ecological staff members by reviewing data input from the original and secondary

sources. Identified errors were reviewed and corrected. The calculations used in allometric

scaling were manually checked for confirmation that equations in the spreadsheet were coded

properly.

14.4.3 Data Formatting QA/QC

Manual QA/QC checks were conducted to identify errors that may have occurred during

data formatting efforts. Approximately 10 percent of the values were checked to ensure

formatting for the modeling system did not change or shift values.

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Wobeser, G., N. O. Nielsen, and B. Schiefer. 1976. Mercury and mink II. Experimental methyl

mercury intoxication. Can J Comp Med, 40:34-45. January.

Zahid, Z.R., Z.S. Al-Hakkak, E.A. Kadhim, E.A. Elias, and I.S. Al-Jumaily. 1990. Comparative

effects of trivalent and hexavalent chromium on spermatogenesis of the mouse. Toxicol. 

Environ. Chem. 25:131-136.
Appendix 14A Ecological Benchmarks

14-37

Appendix 14A

Ecological Benchmarks

Table 14A-1. Mammalian Benchmark Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-39

Table 14A-2. Avian Benchmark Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-45

Table 14A-3. Freshwater Community CSLs Based on Total Water Concentrations . . . . 14-49

Table 14A-4. Freshwater Community CSCLs Based on Total Dissolved Water 

Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-56

Table 14A-5. Aquatic Plants and Algae CSCLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-59

Table 14A-6. Amphibian CSCLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-64

Table 14A-7. Benthic Community CSCLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-69

Table 14A-8. Terrestrial Plant CSCLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-76

Table 14A-9. Soil Community CSCLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14-81

Table 14A-10. Scaled Benchmark Doses for Ecological Receptors . . . . . . . . . . . . . . . . . . 14-87
Appendix 14A Ecological Benchmarks

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14-39

Table 14A-1. Mammalian Benchmark Studies CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Organics 75-05-8 Acetonitrile ID --- --- No studies evaluating reproductive endpoints were identified. 107-13-1 Acrylonitrile ID --- --- No studies evaluating reproductive endpoints were identified. 62-53-3 Aniline ID --- --- No studies evaluating reproductive endpoints were identified. 71-43-2 Benzene 83.4 Mouse Reproduction/ 6 to 12 d of gestation Benchmark dose was the MATC calculated from a NOAEL of 26.36 mg/kg-d and a LOAEL of 263.6 mg/kg-d. 75-15-0 Carbon disulfide ID --- --- No studies evaluating reproductive endpoints were identified. 108-90-7 Chlorobenzene ID --- --- No studies evaluating reproductive endpoints were identified. 67-66-3 Chloroform 24.8 Rat Reproduction/ 13 weeks sub- chronic Benchmark dose was the MATC calculated from a NOAEL of 15 mg/kg-d and a LOAEL of 41 mg/kg-d. 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- --- No studies evaluating reproductive endpoints were identified. 

106-93-4 Ethylene dibromide ID --- --- No studies evaluating reproductive endpoints were identified. 
14-40

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-1. (continued) 87-68-3 Hexachloro-1,3-butadiene ID --- --- No studies evaluating reproductive endpoints were identified. 

72-43-5 Methoxychlor 141 Rat Reproduction/ 6 to 15 d gestation Benchmark dose was the MATC calculated from a NOAEL of 100 mg/kg-d and a LOAEL of 200 mg/kg-d. 78-93-3 Methyl ethyl ketone 2,845 Rat Reproduction/ 2 generations Benchmark dose was the MATC calculated from a NOAEL of 1,771 mg/kg-d and a LOAEL of 4,571 mg/kg-d. 80-62-6 Methyl methacrylate ID --- --- No studies evaluating reproductive endpoints were identified. 75-09-2 Methylene chloride ID --- --- No studies evaluating reproductive endpoints were identified. 98-95-3 Nitrobenzene ID --- --- No studies evaluating reproductive endpoints were identified. 108-95-2 Phenol ID --- --- No studies evaluating reproductive endpoints were identified. 110-86-1 Pyridine ID --- --- No studies evaluating reproductive endpoints were identified. 127-18-4 Tetrachloroethylene ID --- --- No studies evaluating reproductive endpoints were identified. 137-26-8 Thiram ID --- --- No studies evaluating reproductive endpoints were identified. 
14-41

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-1. (continued) 108-88-3 Toluene 82.2 Mouse Reproduction/ 6 to 12 d of gestation Benchmark dose was the MATC calculated from a NOAEL of 26 mg/kg-d and a LOAEL of 260 mg/kg-d. 

71-55-6 1,1,1-Trichloroethane 1,000 Mouse Reproduction/ 2 generations Benchmark dose was the NOAEL of 1,000 mg/kg-d. No LOAEL was identified. 79-01-6 Trichloroethylene 2.2 Mouse Hepatic toxicity/6 weeks Benchmark dose was the MATC calculated from a NOAEL of 0.7 mg/kg-d and a LOAEL of 7 mg/kg-d. 75-01-4 Vinyl chloride 0.54 Rat Longevity/144 weeks Benchmark dose was the MATC calculated from a NOAEL of 0.17 mg/kg-d and a LOAEL of 1.7 mg/kg-d. Metals 7440-36-0 Antimony 0.45 Rat Reproduction/ 60 d Benchmark dose was the MATC calculated from a NOAEL of 0.143 mg/kg-d LOAEL of 1.431 mg/kg-d. 7440-38-2 Arsenic 6.54 Rat Growth and development/ 2 yr Benchmark dose was the MATC calculated from a NOAEL of 4.6 mg/kg-d and a LOAEL of 9.3 mg/kg-d. 7440-39-3 Barium ID --- --- No studies evaluating reproductive endpoints were identified. 
14-42

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-1. (continued) 7440-41-7 Beryllium ID --- --- No studies evaluating reproductive endpoints were identified. 

7440-43-9 Cadmium 3.16 Rat Reproduction/ 6 weeks through gestation Benchmark dose was the MATC calculated from a NOAEL of 1 mg/kg-d and a LOAEL of 10 mg/kg-d. 7440-47-3 Chromium ID --- --- No studies evaluating reproductive endpoints were identified. 16065-83-1 Chromium III (insoluble salts) 2737 Rat Reproduction/ 2 yr Benchmark dose was the NOAEL of 2,737 mg/kg-d. No LOAEL was identified. 18540-29-9 Chromium VI 10.4 Mouse Growth/1 yr Benchmark dose was the MATC calculated from a NOAEL of 3.3 mg/kg-d and a LOAEL of 33 mg/kg-d. 7439-92-1 Lead 0.016 Rat Reproduction Benchmark dose was the MATC calculated from a NOAEL of 0.005 mg/kg-d and a LOAEL of 0.05 mg/kg-d. 7440-02-0 Nickel 75.7 Rat Reproduction/ 3 yrs Benchmark dose was the MATC calculated from a NOAEL of 53.5 mg/kg-d and a LOAEL of 107 mg/kg-d. 7782-49-2 Selenium 0.26 Rat Reproduction/ 78 d Benchmark dose was the MATC calculated from a NOAEL of 0.20 mg/kg-d and a LOAEL of 0.34 mg/kg-d. 
14-43

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-1. (continued) 7440-22-4 Silver ID --- --- No studies evaluating reproductive endpoints were identified. 

7446-18-6 Thallium 0.023 Rat Reproduction./ 60 d Benchmark dose was the MATC calculated from a NOAEL of 0.0074 mg/kg-d and a LOAEL of 0.074 mg/kg-d. 7440-62-2 Vanadium 1.6 Rat Reproduction/ 60 d Benchmark dose was the MATC calculated from a NOAEL of 0.5 mg/kg-d and a LOAEL of 5 mg/kg-d. 7440-66-6 Zinc 290 Rat Reproduction/ 1 to 16 d of gestation Benchmark dose was the MATC calculated from a NOAEL of 200 mg/kg-d and a LOAEL of 410 mg/kg-d. Special 117-81-7 Bis(2-ethylhexyl) phthalate 115 Mouse Reproduction/ through gestation Benchmark dose was the MATC calculated from a NOAEL of 70 mg/kg-d and a LOAEL of 190 mg/kg-d. 50-32-8 Benzo(a)pyrene 3.2 Mouse Reproduction/ 7 to 16 d of gestation Benchmark dose was the MATC calculated from a NOAEL of 1 mg/kg-d and a LOAEL of 10 mg/kg-d. 53-70-3 Dibenz(a,h)anthracene ID --- --- No studies evaluating reproductive endpoints were identified. 
14-44

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-1. (continued) 87-86-5 Pentachlorophenol 7.2 Rat Reproduction/ 181 d Benchmark dose was the MATC calculated from a NOAEL of 4 mg/kg-d and a LOAEL of 13 mg/kg-d. 

Mercury and Dioxin 7439-97-6m Methyl mercury 0.099 Mink Reproduction/ Benchmark dose was the MATC calculated from a NOAEL of 0.055 mg/kg-d and a LOAEL of 0.18 mg/kg-d. 7439-97-6e Mercury (elemental) ID --- --- No studies evaluating reproductive endpoints were identified. 7439-97-6 Mercury (divalent) 1 Mink Reproduction/ 6 months Benchmark dose was the NOAEL of 1 mg/kg-d. No LOAEL was identified. 1746-01-6 2,3,7,8-Tetrachlorodibenzo-p- dioxin (2,3,7,8-TCDD) 0.0000032 Rat Reproduction/ 3 generations Benchmark dose was the MATC calculated from a NOAEL of 0.000001 mg/kg-d and a LOAEL of 0.00001 mg/kg-d. 

ID = Insufficient data. LOAEL = Lowest-observed-adverse-effects level. --- = Not applicable because insufficient data were identified. MATC = Maximum acceptable toxicant concentration. NOAEL = No-observed-adverse-effects level.
14-45

Table 14A-2. Avian Benchmark Studies CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Organics All Organics ID --- --- No studies evaluating reproductive endpoints were identified. 

Metals 7440-36-0 Antimony ID --- --- No studies evaluating reproductive endpoints were identified. 

7440-38-2 Arsenic 0.011 Mallard Reproduction/ 128 d Benchmark dose was the MATC calculated from a NOAEL of 0.0057 mg/kg-d and a LOAEL of 0.023 mg/kg-d. 

7440-39-3 Barium 30 Chicken Reproduction/ 3 weeks Benchmark dose was the MATC calculated from a NOAEL of 21 mg/kg-d and a LOAEL of 42 mg/kg-d. 

7440-41-7 Beryllium ID --- --- No studies evaluating reproductive endpoints were identified. 

7440-43-9 Cadmium 4.4 Mallard Reproduction/ 90 d Benchmark dose was the MATC calculated from a NOAEL of 1.4 mg/kg-d and a LOAEL of 14 mg/kg-d. 
14-46

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-2. (continued) 7440-47-3 Chromium ID --- --- No studies evaluating reproductive endpoints were identified. 

16065-83-1 Chromium III (insoluble salts) 2.2 Duck Reproduction/ 10 months Benchmark dose was the MATC calculated from a NOAEL of 1 mg/kg-d and a LOAEL of 5 mg/kg-d. 18540-29-9 Chromium VI ID --- --- No studies evaluating reproductive endpoints were identified. 

7439-92-1 Lead 0.066 Quail Reproduction/ 4 weeks Benchmark dose was the MATC calculated from a NOAEL of 0.021 mg/kg-d and a LOAEL of 0.21 mg/kg-d. 

7440-02-0 Nickel 91 Mallard Growth and behavior/ 90 d Benchmark dose was the MATC calculated from a NOAEL of 77.4 mg/kg-d and a LOAEL of 07 mg/kg-d. 

7782-49-2 Selenium 0.71 Mallard Reproduction/ 4 weeks Benchmark dose was the MATC calculated from a NOAEL of 0.05 mg/kg-d and a LOAEL of 1.0 mg/kg-d. 

7440-22-4 Silver ID --- --- No studies evaluating reproductive endpoints were identified. 

7446-18-6 Thallium ID --- --- No studies evaluating reproductive endpoints were identified. 
14-47

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-2. (continued) 7440-62-2 Vanadium 1.8 Chicken Growth at sensitive life stage/30 d Benchmark dose was the MATC calculated from a NOAEL of 1.5 mg/kg-d and a LOAEL of 2.2 mg/kg-d. 

7440-66-6 Zinc 32 Hen Reproduction/ 44 weeks Benchmark dose was the MATC calculated from a NOAEL of 11 mg/kg-d and a LOAEL of 94 mg/kg-d. 

Special 117-81-7 Bis(2-ethylhexyl) phthalate 1.1 Ringed dove Reproduction/ 90 d Benchmark dose was the NOAEL of 1.1 mg/kg-d. No LOAEL values were identified. 50-32-8 Benzo(a)pyrene ID --- --- No studies evaluating reproductive endpoints were identified. 

53-70-3 Dibenz(a,h)anthracene ID --- --- No studies evaluating reproductive endpoints were identified. 

87-86-5 Pentachlorophenol 62 Chicks Growth at sensitive life stage/8 weeks Benchmark dose was the MATC calculated from a NOAEL of 44 mg/kg-d and a LOAEL of 88 mg/kg-d. 
14-48

CAS Number Constituent Name Benchmark Dose (mg/kg-d) Test Species Endpoint/ Duration Notes 

Table 14A-2. (continued) Mercury and Dioxin 7439-97-6m Methyl mercury 0.025 Mallard Reproduction/ 3 generations Benchmark dose was the MATC calculated from a NOAEL of 0.0078 mg/kg-d and a LOAEL of 0.078 mg/kg-d. 

7439-97-6e Mercury (elemental) ID --- --- No studies evaluating reproductive endpoints were identified. 

7439-97-6 Mercury (divalent) 0.64 Japanese quail Reproduction/ 1 yr Benchmark dose was the MATC calculated from a NOAEL of 0.45 mg/kg-d and a LOAEL of 0.9 mg/kg-d. 

1746-01-6 2,3,7,8- Tetrachlorodibenzo-p- dioxin (2,3,7,8-TCDD) 0.0000443 Pheasant Reproduction/ 10 weeks Benchmark dose was the MATC calculated from a NOAEL of 0.000014 mg/kg-d and a LOAEL of 0.00014 mg/kg-d. 

ID = Insufficient data. LOAEL = Lowest-observed-adverse-effects level. MATC = Maximum acceptable toxicant concentration. NOAEL = No-observed-adverse-effects level. --- = Not applicable because insufficient data were identified.
14-49

Table 14A-3. Freshwater Community CSLs Based on Total Water Concentrations CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Organics 75-05-8 Acetonitrile ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

107-13-1 Acrylonitrile ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

62-53-3 Aniline ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

71-43-2 Benzene 0.13 SCV Value was calculated using the Tier II methodology from 29 data points representing 6 of the 8 species requirements. 

75-15-0 Carbon disulfide 0.00092 SCV Value was calculated using the Tier II methodology from one data point representing two of the eight species requirements. 

108-90-7 Chlorobenzene 0.064 SCV Value was calculated using the Tier II methodology from 12 data points representing 4 of the 8 species requirements. 

67-66-3 Chloroform 0.028 SCV Value was calculated using the Tier II methodology from 15 data points representing 3 of the 8 species requirements. 

94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 
14-50

CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Table 14A-3. (continued) 106-93-4 Ethylene dibromide ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

87-68-3 Hexachloro-1,3-butadiene ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

72-43-5 Methoxychlor 0.000019 SCV Value was adopted from OSWER calculated using the Tier II methodology. 

78-93-3 Methyl ethyl ketone ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

80-62-6 Methyl methacrylate ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

75-09-2 Methylene chloride 2.2 SCV Value was calculated using the Tier II methodology from five data points representing three of the eight species requirements. 

98-95-3 Nitrobenzene ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

108-95-2 Phenol 0.11 FCV Value was calculated as the chronic NAWQC meeting all of the data and species requirements. 

110-86-1 Pyridine ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

127-18-4 Tetrachloroethylene 0.098 SCV Value was calculated using the Tier II methodology from nine data points representing four of the eight species requirements. 
14-51

CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Table 14A-3. (continued) 137-26-8 Thiram ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

108-88-3 Toluene 0.0098 SCV Value was calculated using the Tier II methodology from seven data points representing two of the eight species requirements. 

71-55-6 1,1,1-Trichloroethane 0.011 SCV Value was calculated using the Tier II methodology from two data points representing two of the eight species requirements. 

79-01-6 Trichloroethylene 0.047 SCV Value was calculated using the Tier II methodology from five data points representing two of the eight species requirements. 

75-01-4 Vinyl chloride ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

Metals 7440-36-0 Antimony 0.03 Draft FCV Value is a draft FCV and met all data requirements for calculating NAWQC. 

7440-38-2 Arsenic 0.15 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. 

7440-39-3 Barium 0.004 SCV Value was calculated using the Tier II methodology from 12 data points representing 4 of the 8 species requirements. 
14-52

CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Table 14A-3. (continued) 7440-41-7 Beryllium 0.00066 SCV Value was calculated using the Tier II methodology from 27 data points representing 6 of the 8 species requirements. 

7440-43-9 Cadmium 0.0025 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. This criteria is dependent on water hardness and was calculated using the following equation, assuming a water hardness of 100 mg CaCO3/L: CCC = e 0.7852(ln hardness) - 2.715 

7440-47-3 Chromium ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

16065-83-1 Chromium III (insoluble salts) 0.086 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. This criteria is dependent on water hardness and was calculated using the following equation, assuming a water hardness of 100 mg CaCO3/L: CCC = e 0.819(ln hardness) + 0.6848 

18540-29-9 Chromium VI 0.011 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. 

7439-92-1 Lead 0.0032 FCV Value is an FCV and met all data requirements for calculating NAWQC. 
14-53

CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Table 14A-3. (continued) 7440-02-0 Nickel 0.052 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. This criteria is dependent on water hardness and was calculated using the following equation, assuming a water hardness of 100 mg CaCO3/L: CCC = e 0.846(ln hardness) + 0.0584 

7782-49-2 Selenium 0.005 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota, including some field studies. 

7440-22-4 Silver 0.00036 SCV Value derived from the NAWQC FAV for silver. 7446-18-6 Thallium 0.012 SCV Value was calculated using the Tier II methodology from 10 data points representing 3 of the 8 species requirements. 7440-62-2 Vanadium 0.02 SCV Value was calculated using the Tier II methodology from 25 data points representing 4 of the 8 species requirements. 

7440-66-6 Zinc 0.12 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. This criteria is dependent on water hardness and was calculated using the following equation, assuming a water hardness of 100 mg CaCO3/L: CCC = e 0.8473(ln hardness) + 0.884 
14-54

CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Table 14A-3. (continued) Special 117-81-7 Bis(2-ethylhexyl) phthalate 0.003 SCV Value was calculated using the Tier II methodology from 15 data points representing 5 of the eight species requirements. 

50-32-8 Benzo(a)pyrene 0.000014 SCV Value was calculated using the Tier II methodology from one data point representing one of the eight species requirements. 

53-70-3 Dibenz(a,h)anthracene ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

87-86-5 Pentachlorophenol 0.0055 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. This criteria is dependent on pH and was calculated using the following equation, assuming a pH of 6.8: CCC = e 1.005(pH) - 5.134 0.884 

Mercury and Dioxin 7439-97-6m Methyl mercury 0.0000028 SCV Value was calculated using the Tier II methodology from four data points representing one of the eight species requirements. 

7439-97-6e Mercury (elemental) ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 
14-55

CAS Number Constituent Name CSCL (Total) (mg/L) Method Notes 

Table 14A-3. (continued) 7439-97-6 Mercury (divalent) 0.00091 CCC NAWQC value was updated through the GLWQI incorporating newly identified toxicity data for freshwater biota. 

1746-01-6 TCDD 2,3,7,8- ID --- Insufficient ecotoxicity data were available to develop a water quality criteria. 

CSCL = Chemical stressor concentration limit. CCC = Criterion continuous concentration. FCV = Final chronic value. GLWQI = Great lakeswater quality initiative. ID = Insufficient data. NAWQC = National ambient water quality criteria. SCV = Secondary chronic value. --- = Not applicable because insufficient data identified.
14-56

Table 14A-4. Freshwater Community CSCLs Based on Total Dissolved Water Concentra

CAS Number Constituent Name1 CSCL (Total)2 (mg/L) Conversion Factor3 CSCL (Dissolved) (mg/L) Notes 

Metals 7440-36-0 Antimony 0.03 ID ID Insufficient data were available to derive a dissolved surface water concentration. U

7440-38-2 Arsenic 0.15 1.00 0.15 EPA’s Office of Water supports the use of dissolved criteria over the total criteria because dissolved criteria reflect the bioavailable fraction of the metal. U

7440-39-3 Barium 0.004 ID ID Insufficient data were available to derive a dissolved surface water concentration. S

S

7440-41-7 Beryllium 0.00066 ID ID Insufficient data were available to derive a dissolved surface water concentration. S

S

7440-43-9 Cadmium 0.0025 0.909 0.0023 Conversion factor was derived as a hardness, dependent criterion assuming 100 mg CaCO3/L using the following equation: CF =1.101672-[(ln hardness)(0.041838)] U

7440-47-3 Chromium ID ID ID Insufficient data were available to derive a dissolved surface water concentration. -

16065-83-1 Chromium III (insoluble salts) 0.086 0.860 0.074 EPA’s Office of Water supports the use of dissolved criteria over the total criteria because dissolved criteria reflect the bioavailable fraction of the metal. U
14-57

CAS Number Constituent Name1 CSCL (Total)2 (mg/L) Conversion Factor3 CSCL (Dissolved) (mg/L) Notes 

Table 14A-4. (continued) 18540-29-9 Chromium VI 0.011 0.962 0.011 EPA’s Office of Water supports the use of dissolved criteria over the total criteria because dissolved criteria reflect the bioavailable fraction of the metal. U

7439-92-1 Lead 0.0032 0.791 0.0025 Conversion factor was derived as a hardness- dependent criterion, assuming 100 mg CaCO3/L using the following equation: CF =1.46203-[(ln hardness)(0.145712)] U

7440-02-0 Nickel 0.052 0.997 0.052 EPA’s Office of Water supports the use of dissolved criteria over the total criteria because dissolved criteria reflect the bioavailable fraction of the metal. U

7782-49-2 Selenium 0.005 ID ID Insufficient data were available to derive a dissolved surface water concentration. U

7440-22-4 Silver 0.00036 ID ID Insufficient data were available to derive a dissolved surface water concentration. S

7446-18-6 Thallium 0.012 ID ID Insufficient data were available to derive a dissolved surface water concentration. S

S

7440-62-2 Vanadium 0.02 ID ID Insufficient data were available to derive a dissolved surface water concentration. S

S
14-58

CAS Number Constituent Name1 CSCL (Total)2 (mg/L) Conversion Factor3 CSCL (Dissolved) (mg/L) Notes 

Table 14A-4. (continued) 7440-66-6 Zinc 0.12 0.986 0.12 EPA’s Office of Water supports the use of dissolved criteria over the total criteria because dissolved criteria reflect the bioavailable fraction of the metal. U

1 Dissolved CSCLs are currently available to estimate concentrations of metals in surface waters; therefore, constituents categorized 

constitutents, and mercury and dioxin compounds are not included in this table. 2 Values were derived as indicated in Table 10. 3 Conversion factors were developed to estimate the fraction of the total concentration that was dissolved in the water column. The c

developed by EPA for converting freshwater chronic criteria were adopted. ID = Insufficient data. CSCL = Chemical stressor concentration limit. — = Not applicable because insufficient data were indentified.
14-59

Table 14A-5. Aquatic Plants and Algae CSCLs CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Organics 75-05-8 Acetonitrile ID --- Insufficient data were available to develop an aquatic plant CSCL. 

107-13-1 Acrylonitrile ID --- Insufficient data were available to develop an aquatic plant CSCL. 

62-53-3 Aniline ID --- Insufficient data were available to develop an aquatic plant CSCL. 

71-43-2 Benzene 530 Lowest chronic value EC50 Based on a 48-h EC50 test by exposing Chlorella vulgaris. 

75-15-0 Carbon disulfide ID --- Insufficient data were available to develop an aquatic plant CSCL. 

108-90-7 Chlorobenzene 220 Lowest chronic value EC50 Based on a 96-h EC50 test for cell number, by exposing Selenastrum capricornutum. 

67-66-3 Chloroform ID --- Insufficient data were available to develop an aquatic plant CSCL. 

94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- Insufficient data were available to develop an aquatic plant CSCL. 

106-93-4 Ethylene dibromide ID --- Insufficient data were available to develop an aquatic plant CSCL. 

87-68-3 Hexachloro-1,3-butadiene ID --- Insufficient data were available to develop an aquatic plant CSCL. 
14-60

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-5. (continued) 72-43-5 Methoxychlor ID --- Insufficient data were available to develop an aquatic plant CSCL. 

78-93-3 Methyl ethyl ketone ID --- Insufficient data were available to develop an aquatic plant CSCL. 

80-62-6 Methyl methacrylate ID --- Insufficient data were available to develop an aquatic plant CSCL. SSC 

75-09-2 Methylene chloride ID --- Insufficient data were available to develop an aquatic plant CSCL. 

98-95-3 Nitrobenzene ID --- Insufficient data were available to develop an aquatic plant CSCL. 

108-95-2 Phenol 20 Lowest chronic value EC50 Based on a value that exhibited 60 percent reduction in cell numbers and 12percent growth inhibition by exposing Selenastrum capricornutum. 

110-86-1 Pyridine ID --- Insufficient data were available to develop an aquatic plant CSCL. 

127-18-4 Tetrachloroethylene ID --- Insufficient data were available to develop an aquatic plant CSCL. 

137-26-8 Thiram ID --- Insufficient data were available to develop an aquatic plant CSCL. 

108-88-3 Toluene 250 Lowest chronic value EC50 Based on an unspecified 10-d test by exposing Chlorella vulgaris. 
14-61

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-5. (continued) 71-55-6 1,1,1-Trichloroethane 669 Lowest chronic value EC50 Based on a value that exhibited 60 percent reduction in cell numbers and 12percent growth inhibition by exposing Selenastrum capricornutum. 

79-01-6 Trichloroethylene ID --- Insufficient data were available to develop an aquatic plant CSCL. 

75-01-4 Vinyl chloride ID --- Insufficient data were available to develop an aquatic plant CSCL. 

Metals 7440-36-0 Antimony 0.61 Lowest chronic value EC50 Based on a 4-d EC50 for chlorophyll A inhibition by exposing Selenastrum capricornutum. 

7440-38-2 Arsenic 0.048 Lowest chronic value EC50 Based on a 14-d EC50 test by exposing Scendesmus obliquus. 

7440-39-3 Barium ID --- Insufficient data were available to develop an aquatic plant CSCL. 7440-41-7 Beryllium 100 Lowest chronic value EC50 Based on a 10 to 20percent reduction in autotrophic growth rates by exposing Chlorella vannieli. 

7440-43-9 Cadmium 0.002 Lowest chronic value EC50 Based on the population growth rate by exposing Asterionella formosa. 7440-47-3 Chromium ID --- Insufficient data were available to develop an aquatic plant CSCL. 
14-62

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-5. (continued) 16065-83-1 Chromium III (insoluble salts) 0.4 Lowest chronic value EC50 Based on a 4-d chronic test in which there was a 50percent inhibition of growth, by exposing Selenastrum capricornutum. 

18540-29-9 Chromium VI 0.002 Lowest chronic value EC50 Based on a value that showed incipient inhibition of growth by exposing Microcystis aeruginosa. 7439-92-1 Lead 0.5 Lowest chronic value EC50 Based on value based on 53percent, 35percent, and 52percent growth inhibition by exposing Chlorella vulgaris, Scenedesmus quadricauda, and Selenastrum capricornutum. 7440-02-0 Nickel 0.005 Lowest chronic value EC50 Based on a value that showed incipient inhibition of growth by exposing Microcystis aeruginosa. 

7782-49-2 Selenium 0.1 Lowest chronic value EC50 Based on 14-d chronic toxicity tests by exposing Scenedesmus obliquus. 

7440-22-4 Silver 0.03 Lowest chronic value EC50 Based on growth inhibition by exposing Chlorella vulgaris. 7446-18-6 Thallium 0.1 Lowest chronic value EC50 Based on a 4-d EC50 which reduced the plant’s cell numbers by exposing Selenastrum capricornutum. 

7440-62-2 Vanadium ID --- Insufficient data were available to develop an aquatic plant CSCL. 7440-66-6 Zinc 0.03 Lowest chronic value EC50 Based on 7-d tests that showed incipient inhibition of growth by exposing Selenastrum capricornutum. 
14-63

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-5. (continued) Special 117-81-7 Bis(2-ethylhexyl) phthalate ID --- Insufficient data were available to develop an aquatic plant CSCL. 

50-32-8 Benzo(a)pyrene ID --- Insufficient data were available to develop an aquatic plant CSCL. 

53-70-3 Dibenz(a,h)anthracene ID --- Insufficient data were available to develop an aquatic plant CSCL. 

87-86-5 Pentachlorophenol ID --- Insufficient data were available to develop an aquatic plant CSCL. 

Mercury and Dioxin 7439-97-6m Methyl mercury ID --- Insufficient data were available to develop an aquatic plant CSCL. 

7439-97-6e Mercury (elemental) ID --- Insufficient data were available to develop an aquatic plant CSCL. 

7439-97-6 Mercury (divalent) 0.005 Lowest chronic value EC50 Based on an 8-d test that showed incipient inhibition of growth by exposing Microcystis aeruginosa. 

1746-01-6 TCDD 2,3,7,8- ID --- Insufficient data were available to develop an aquatic plant CSCL. 

CSCL = Chemical stressor concentration limit. EC50 = Effective concentration for 50% of the organisms. ID = Insufficient data. --- = Not applicable because insufficient data were identified.
14-64

Table 14A-6. Amphibian CSCLs CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Organics 75-05-8 Acetonitrile ID --- Insufficient data were available to develop an amphibian CSCL. 

107-13-1 Acrylonitrile ID --- Insufficient data were available to develop an amphibian CSCL. 

62-53-3 Aniline 370 Geomean of acute values The geomean of LC50 values was based on 7 values ranging from 95 to 940 mg/L. 

71-43-2 Benzene 34 Geomean of acute values The geomean of LC50 values was based on 4 values ranging from 3.7 to 370 mg/L. 75-15-0 Carbon disulfide ID --- Insufficient data were available to develop an amphibian CSCL. 

108-90-7 Chlorobenzene ID --- Insufficient data were available to develop an amphibian CSCL. 

67-66-3 Chloroform 11 Geomean of acute values The geomean of LC50 values was based on 7 values ranging from 2.7 to 68 mg/L. 

94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- Insufficient data were available to develop an amphibian CSCL. 

106-93-4 Ethylene dibromide ID --- Insufficient data were available to develop an amphibian CSCL. 

87-68-3 Hexachloro-1,3-butadiene ID --- Insufficient data were available to develop an amphibian CSCL. 
14-65

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-6. (continued) 72-43-5 Methoxychlor 0.29 Geomean of acute values The geomean of LC50 values was based on 4 values ranging from 0.10 to 0.33 mg/L. 

78-93-3 Methyl ethyl ketone ID --- Insufficient data were available to develop an amphibian CSCL. 

80-62-6 Methyl methacrylate ID --- Insufficient data were available to develop an amphibian CSCL. 

75-09-2 Methylene chloride ID --- Insufficient data were available to develop an amphibian CSCL. 

98-95-3 Nitrobenzene 0.64 Geomean of acute values The geomean of LC50 values was based on one valu

108-95-2 Phenol 1.3 Geomean of acute values The geomean of LC50 values was based on 9 values ranging from 0.04 to 51 mg/L. 

110-86-1 Pyridine ID --- Insufficient data were available to develop an amphibian CSCL. 

127-18-4 Tetrachloroethylene ID --- Insufficient data were available to develop an amphibian CSCL. 

137-26-8 Thiram ID --- Insufficient data were available to develop an amphibian CSCL. 

108-88-3 Toluene 0.58 Geomean of acute values The geomean of LC50 values was based on two values, 0.39 and 0.85 mg/L. 

71-55-6 1,1,-Trichloroethane ID --- Insufficient data were available to develop an amphibian CSCL. 
14-66

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-6. (continued) 79-01-6 Trichloroethylene 89 Geomean of acute values The geomean of LC50 values was based on six value

ranging from 34 to 443 mg/L. 

75-01-4 Vinyl chloride ID --- Insufficient data were available to develop an amphibian CSCL. 

Metals 7440-36-0 Antimony 0.3 Geomean of aacute values The geomean of LC50 values was based on one valu

7440-38-2 Arsenic 4.3 Geomean of acute values The geomean of LC50 values was based on six value

ranging from 0.040 to 71 mg/L. 

7440-39-3 Barium ID --- Insufficient data were available to develop an amphibian CSCL. 

7440-41-7 Beryllium 11 Geomean of acute values The geomean of LC50 values was based on 8 values ranging from 3.2 to 32 mg/L. 

7440-43-9 Cadmium 2.2 Geomean of acute values The geomean of LC50 values was based on 28 value

ranging from 0.04 to 20 mg/L. 

7440-47-3 Chromium 12 Geomean of acute values The geomean of LC50 values was based on 10 value

ranging from 0.03 to 100 mg/L. 

16065-83-1 Chromium III (insoluble salts) ID --- Insufficient data were available to develop an amphibian CSCL. 

18540-29-9 Chromium VI ID --- Insufficient data were available to develop an amphibian CSCL. 
14-67

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-6. (continued) 7439-92-1 Lead 2.1 Geomean of acute values The geomean of LC50 values was based on 6 values ranging from 0.04 to 105 mg/L. 

7440-02-0 Nickel 2.2 Geomean of acute values The geomean of LC50 values was based on 11 value

ranging from 0.05 to 53 mg/L. 

7782-49-2 Selenium 1.8 Geomean of acute values The geomean of LC50 values was based on 13 value

ranging from 0.09 to 11 mg/L. 

7440-22-4 Silver 0.03 Geomean of acute values The geomean of LC50 values was based on 7 values having ranging from 0.004 to 26 mg/L. 7446-18-6 Thallium 0.11 Geomean of acute values The geomean of LC50 values was based on one valu

7440-62-2 Vanadium ID --- Insufficient data were available to develop an amphibian CSCL. 

7440-66-6 Zinc 10 Geomean of acute values The geomean of LC50 values was based on 25 value

ranging from 0.01 to 47 mg/L. 

Special 117-81-7 Bis(2-ethylhexyl) phthalate ID --- Insufficient data were available to develop an amphibian CSCL. 

50-32-8 Benzo(a)pyrene ID --- Insufficient data were available to develop an amphibian CSCL. 
14-68

CAS Number Constituent Name CSCL (mg/L) Methodology Notes 

Table 14A-6. (continued) 53-70-3 Dibenz(a,h)anthracene ID --- Insufficient data were available to develop an amphibian CSCL. 

87-86-5 Pentachlorophenol 0.070 Geomean of acute values The geomean of LC50 values was based on 10 value

ranging from 0.0003 to 0.35 mg/L. 

Mercury and Dioxin 7439-97-6m Methyl mercury 0.06 Geomean of acute values The geomean of LC50 values was based on 67 value

ranging from 0.001 to 108 mg/L. 

7439-97-6e Mercury (elemental) ID --- Insufficient data were available to develop an amphibian CSCL. 

7439-97-6 Mercury (divalent) 0.06 Geomean of acute values The geomean of LC50 values was based on 2 values ranging from 0.056 to 0.060 mg/L. 

1746-01-6 TCDD 2,3,7,8- ID --- Insufficient data were available to develop an amphibian CSCL. 

CSCL = Chemical stressor concentration limit. ID = Insufficient data. LC50 = Lethal concentration for 50% of the organisms. --- = Not applicable because insufficient data were identified.
14-69

Table 14A-7. Benthic Community CSCLs CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Organics 75-05-8 Acetonitrile ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

107-13-1 Acrylonitrile ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

62-53-3 Aniline ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

71-43-2 Benzene 0.16 EqP Based on the SCV of 0.13 mg/L calculated by Su

and Tsao (1996), assuming 1percent total organic carbon and log Koc equal to 2.09. 

75-15-0 Carbon disulfide 0.00085 EqP Based on the SCV of 0.00092 mg/L calculated by Suter and Tsao (1996), assuming 1 percent total organic carbon and log Koc equal to 1.97. 

108-90-7 Chlorobenzene 0.41 EqP Based on the SCV of 0.064 mg/L calculated by S

and Tsao (1996), assuming 1 percent total organic carbon and log Koc equal to 2.81. 

67-66-3 Chloroform 0.022 EqP Based on the SCV of 0.028 mg/L calculated by S

and Tsao (1996), assuming 1percent total organic carbon and log Koc equal to 1.89. 
14-70

CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Table 14A-7. (continued) 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

106-93-4 Ethylene dibromide ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 87-68-3 Hexachloro-1,3-butadiene ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied estimate a benthic community CSCL. 

72-43-5 Methoxychlor 0.019 EqP Based on the SCV of 0.000019 mg/L calculated b

Suter and Tsao (1996), assuming 1percent total organic carbon and log Koc equal to 4.99. 

78-93-3 Methyl ethyl ketone ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

80-62-6 Methyl methacrylate ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

75-09-2 Methylene chloride 0.37 EqP Based on the SCV of 2.2 mg/L calculated by Sute

and Tsao (1996), assuming 1percent total organic carbon and log Koc equal to 1.23. 

98-95-3 Nitrobenzene ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 
14-71

CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Table 14A-7. (continued) 108-95-2 Phenol 0.031 EqP Based on the FCV of 0.11 mg/L calculated by Su

and Tsao (1996), assuming 1 percent total organic carbon and log Koc equal to 1.46. 

110-86-1 Pyridine ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

127-18-4 Tetrachloroethylene ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

137-26-8 Thiram ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 

108-88-3 Toluene 0.05 EqP Based on the SCV of 0.0098 mg/L calculated by Suter and Tsao (1996), assuming 1 percent total organic carbon and log Koc equal to 2.70. 

71-55-6 1,1,1-Trichloroethane 0.03 EqP Based on the SCV of 0.011 mg/L calculated by S

and Tsao (1996), assuming 1 percent total organic carbon and log Koc equal to 2.44. 

79-01-6 Trichloroethylene 0.22 EqP Based on the SCV of 0.047 mg/L calculated by S

and Tsao (1996), assuming 1 percent total organic carbon and log Koc equal to 2.66. 

75-01-4 Vinyl chloride ID --- No water quality criteria have been developed; therefore, the EqP approach could not be applied 

estimate a benthic community CSCL. 
14-72

CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Table 14A-7. (continued) Metals 7440-36-0 Antimony 2 ER-L Estimated from a distribution of 13 effects concentrations measured in field sediments. Endpoints were associated with decreased abundance and species diversity as well as shifts 

community structure. 

7440-38-2 Arsenic 7.2 TEL Estimated from a distribution of 295 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

7440-39-3 Barium ID --- Insufficient data were available to develop a bent

community CSCL. 

7440-41-7 Beryllium ID --- Insufficient data were available to develop a bent

community CSCL. 

7440-43-9 Cadmium 0.68 TEL Estimated from a distribution of 433 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

7440-47-3 Chromium 52 TEL Estimated from a distribution of 354 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 
14-73

CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Table 14A-7. (continued) 16065-83-1 Chromium III ID --- Insufficient data were available to develop a bent

community CSCL. 

18540-29-9 Chromium VI ID --- Insufficient data were available to develop a bent

community CSCL. 

7439-92-1 Lead 30 TEL Estimated from a distribution of 402 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

7440-02-0 Nickel 16 TEL Estimated from a distribution of 355 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

7782-49-2 Selenium ID --- Insufficient data were available to develop a bent

community CSCL. 

7440-22-4 Silver 0.73 TEL Estimated from a distribution of 190 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

7446-18-6 Thallium ID --- Insufficient data were available to develop a bent

community CSCL. 

7440-62-2 Vanadium ID --- Insufficient data were available to develop a bent

community CSCL. 
14-74

CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Table 14A-7. (continued) 7440-66-6 Zinc 120 TEL Estimated from a distribution of 411 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

Special 117-81-7 Bis(2-ethylhexyl) phthalate 0.18 TEL Estimated from a distribution of 131 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

50-32-8 Benzo(a)pyrene 0.089 TEL Estimated from a distribution of 259 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

53-70-3 Dibenz(a,h)anthracene 0.0062 TEL Estimated from a distribution of 246 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure 

87-86-5 Pentachlorophenol ID --- Insufficient data were available to develop a bent

community CSCL. 

Mercury and Dioxin 7439-97-6m Methyl mercury ID --- Insufficient data were available to develop a bent

community CSCL. 
14-75

CAS Number Constituent CSCL (mg/kg sediment DW) Methodology Notes 

Table 14A-7. (continued) 7439-97-6e Mercury (elemental) ID --- Insufficient data were available to develop a bent

community CSCL. 

7439-97-6 Mercury (divalent) 0.13 TEL Estimated from a distribution of 331 sediment concentrations associated with no- and low-effect

concentrations to endpoints of lethality, abundancdiversity, and benthic community structure. 

1746-01-6 TCDD 2,3,7,8- ID --- Insufficient data were available to develop a bent

community CSCL. 

ID = Insufficient data. CSCL = Chemical stressor concentration limit. FCV = Final chronic value. SCV = Secondary chronic value. ER-L = Effects range low- The value was the 10th percentile from the ranked distribution of sediment effecEqP = Equilibrium partitioning. The value is the product of the following calculation. --- = Not applicable because insufficient data identified. Benthic Community CSCL = Surface Well Water CSCL x This is calculation foc) x Koc TEL = Threshold effects level - The value calculated from the following equation, where EDS-L is the 15t

effects data set and NEDS-M is the 50th percentile of the no-effects data set:
14-76

Table 14A-8. Terrestrial Plant CSCLs CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Organics 75-05-8 Acetonitrile ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

107-13-1 Acrylonitrile ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

62-53-3 Aniline ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

71-43-2 Benzene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

75-15-0 Carbon disulfide ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

108-90-7 Chlorobenzene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

67-66-3 Chloroform ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- Insufficient data were available to develop a terrestrial plant CSCL. 106-93-4 Ethylene dibromide ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

87-68-3 Hexachloro-1,3-butadiene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 
14-77

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-8. (continued) 72-43-5 Methoxychlor ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

78-93-3 Methyl ethyl ketone ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

80-62-6 Methyl methacrylate ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

75-09-2 Methylene chloride ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

98-95-3 Nitrobenzene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

108-95-2 Phenol 70 Lowest LOEC Derived from the lowest of two toxicity values (range: 79 to 170 mg/kg soil) based on effects to plant weight. 

110-86-1 Pyridine ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

127-18-4 Tetrachloroethylene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

137-26-8 Thiram ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

108-88-3 Toluene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

71-55-6 1,1,1-Trichloroethane ID --- Insufficient data were available to develop a terrestrial plant CSCL. 
14-78

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-8. (continued) 79-01-6 Trichloroethylene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

75-01-4 Vinyl chloride ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

Metals 7440-36-0 Antimony 5 Lowest LOEC Value was the only LOEC identified based on phytotoxic effects. 

7440-38-2 Arsenic 10 ER-L Derived as the 10th percentile of 15 toxicity values (range: 2 to 1,000 mg/kg soil) based on effects to plant weight and yield. 

7440-39-3 Barium 500 Lowest LOEC Derived from the lowest of two toxicity values (range: 500 to 2,000 mg/kg soil) based on effects to plant weight. 

7440-41-7 Beryllium 10 Lowest LOEC Derived from the lowest of three toxicity values (range: 10 to 25 mg/kg soil) based on effects to plant weight and survival. 

7440-43-9 Cadmium 4 ER-L Derived as the10th percentile of 74 toxicity values (range: 1 to 300 mg/kg soil) based on effects to plant weight, yield, and germination success. 

7440-47-3 Chromium ID --- Insufficient data were available to develop a terrestrial plant CSCL. 
14-79

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-8. (continued) 16065-83-1 Chromium III ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

18540-29-9 Chromium VI 1 Lowest LOEC Derived from the lowest of seven toxicity values (range: 1.8 to 31 mg/kg soil) based on effects to plant weight. 

7439-92-1 Lead 50 ER-L Derived as the 10th percentile of 17 toxicity values (range: 50 to 5,000 mg/kg soil) based on effects to plant weight and transpiration. 

7440-02-0 Nickel 30 ER-L Derived as the 10th percentile of 14 toxicity values (range: 25 to 290 mg/kg soil) based on effects to plant weight. 

7782-49-2 Selenium 1 ER-L Derived as the 10th of 14 toxicity values (range: 1 to 4 mg/kg soil) based on effects to plant weight. 

7440-22-4 Silver 2 Lowest LOEC Value was the only LOEC identified based on phytotoxic effects. 

7446-18-6 Thallium 1 Lowest LOEC Value was the only LOEC identified based on phytotoxic effects. 

7440-62-2 Vanadium 2 Lowest LOEC Derived from the lowest of two toxicity values (range: 2.5 to 50 mg/kg soil) based on phytotoxic effects. 

7440-66-6 Zinc 50 ER-L Derived as the 10th percentile of 14 toxicity values (range: 25 to 400 mg/kg soil) based on effects to plant weight, growth, and yield. 
14-80

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-8. (continued) Special 117-81-7 Bis(2-ethylhexyl) phthalate ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

50-32-8 Benzo(a)pyrene ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

53-70-3 Dibenz(a,h)anthracene ID --- In sufficient data were available to develop a terrestrial plant CSCL. 

87-86-5 Pentachlorophenol 3 Lowest LOEC Derived from the lowest of four toxicity values (range: 8 to 20 mg/kg soil) based on effects to plant weight. 

Mercury and Dioxin 7439-97-6m Methyl mercury ID --- Insufficient data were available to develop a terrestrial plant CSCL. 7439-97-6e Mercury (elemental) ID --- Insufficient data were available to develop a terrestrial plant CSCL. 

7439-97-6 Mercury (divalent) 0.3 Lowest LOEC Derived from the lowest of two toxicity values (range: 0.3 to 64 mg/kg soil) based on effects to seedling height and phytotoxicity. 

1746-01-6 TCDD 2,3,7,8- ID --- Insufficient data were available to develop a terrestrial plant CSCL. CSCL = Chemical stressor concentration limit. ER-L = Effects range low—The value was the 10th percentile from the ranked distribution of soil effects concentrations. ID = Insufficient data. LOEC = Lowest observed effect concentration. --- = Not applicable because insufficient data were identified.
14-81

Table 14A-9. Soil Community CSCLs CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Organics 75-05-8 Acetonitrile ID --- Insufficient data were available to develop a soil community CSCL. 

107-13-1 Acrylonitrile ID --- Insufficient data were available to develop a soil community CSCL. 62-53-3 Aniline ID --- Insufficient data were available to develop a soil community CSCL. 71-43-2 Benzene ID --- Insufficient data were available to develop a soil community CSCL. 75-15-0 Carbon disulfide ID --- Insufficient data were available to develop a soil community CSCL. 108-90-7 Chlorobenzene 40 Lowest LC50 Value is based on the lowest of four values assessing lethality to populations of earthworms. The lowest LC50 of 240 was used, applying an uncertainty factor of 5. 

67-66-3 Chloroform ID --- Insufficient data were available to develop a soil community CSCL. 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID --- Insufficient data were available to develop a soil community CSCL. 106-93-4 Ethylene dibromide ID --- Insufficient data were available to develop a soil community CSCL. 87-68-3 Hexachloro-1,3-butadiene ID --- Insufficient data were available to develop a soil community CSCL. 
14-82

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-9. (continued) 72-43-5 Methoxychlor ID --- Insufficient data were available to develop a soil community CSCL. 

78-93-3 Methyl ethyl ketone ID --- Insufficient data were available to develop a soil community CSCL. 80-62-6 Methyl methacrylate ID --- Insufficient data were available to develop a soil community CSCL. 75-09-2 Methylene chloride ID --- Insufficient data were available to develop a soil community CSCL. 98-95-3 Nitrobenzene 40 Lowest LC50 Value is based on the lowest of four values assessing lethality to populations of earthworms. The lowest LC50 of 226 was used, applying an uncertainty factor of 5. 

108-95-2 Phenol 30 Lowest LC50 Value is based on the lowest of five values assessing lethality to populations of earthworms. The lowest LC50 of 188 was used, applying an uncertainty factor of 5. 110-86-1 Pyridine ID --- Insufficient data were available to develop a soil community CSCL. 127-18-4 Tetrachloroethylene ID --- Insufficient data were available to develop a soil community CSCL. 137-26-8 Thiram ID --- Insufficient data were available to develop a soil community CSCL. 108-88-3 Toluene ID --- Insufficient data were available to develop a soil community CSCL. 71-55-6 1,1,1-Trichloroethane ID --- Insufficient data were available to develop a soil community CSCL. 
14-83

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-9. (continued) 79-01-6 Trichloroethylene ID --- Insufficient data were available to develop a soil community CSCL. 

75-01-4 Vinyl chloride ID --- Insufficient data were available to develop a soil community CSCL. Metals 7440-36-0 Antimony ID --- Insufficient data were available to develop a soil community CSCL. 7440-38-2 Arsenic 60 Lowest LOEC Value was the only LOEC identified based on reproductive endpoints in earthworms. 7440-39-3 Barium ID --- Insufficient data were available to develop a soil community CSCL. 7440-41-7 Beryllium ID --- Insufficient data were available to develop a soil community CSCL. 7440-43-9 Cadmium 1 Community- based CSCL Based on NOEC data for eight different taxonomic groups represented in the soil community. Concentrations ranged from 1 to 19 mg/kg soil based on toxicity endpoints of reproduction, growth, and development. 
14-84

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-9. (continued) 7440-47-3 Chromium 66 Geometric mean The ecotoxicity data indicate that soil concentrations indicating effects to survival are below soil concentrations indicating reproductive effects in earthworms. A geometric mean of LOEC data from both reproductive and survival endpoints was used to remain consistent with the assessment endpoints of the analysis.. 

16065-83-1 Chromium III 66 Geometric mean Hexavalent chromium is reduced to Cr3+ under normal soil pH and redox conditions (Katz and Salem, 1994); hence, a greater portion of chromium in the soil is found as Cr3+; therefore, the same benchmark used for total chromium is appropriate for Cr3+. 

18540-29-9 Chromium VI 0.4 Lowest LOEC Value was the only LOEC identified based on reproductive endpoints in earthworms. 7439-92-1 Lead 28 Community- based CSCL Based on NOEC data for six different taxonomic groups represented in the soil community. Concentrations ranged from 23 to 1,100 mg/kg soil based on toxicity endpoints of reproduction, growth, and litter breakdown. 
14-85

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-9. (continued) 7440-02-0 Nickel 90 ER-L Derived as the 10th percentile of 56 toxicity values (range: 50 to 8,100 mg/kg soil) based on effects microbial growth and productivity endpoints. Microbial endpoints appeared more sensitive than earthworms. 

7782-49-2 Selenium 70 Lowest LOEC Value was the only LOEC identified based on reproductive endpoints in earthworms. 7440-22-4 Silver ID --- Insufficient data were available to develop a soil community CSCL. 7446-18-6 Thallium ID --- Insufficient data were available to develop a soil community CSCL. 7440-62-2 Vanadium ID --- Insufficient data were available to develop a soil community CSCL. 7440-66-6 Zinc 100 ER-L Derived as the 10th percentile of 46 toxicity values (range: 50 to 9,700 mg/kg soil) based on effects microbial growth and productivity endpoints. Microbial endpoints appeared more sensitive than earthworms. Special 117-81-7 Bis(2-ethylhexyl) phthalate ID --- Insufficient data were available to develop a soil community CSCL. 50-32-8 Benzo(a)pyrene ID --- Insufficient data were available to develop a soil community CSCL. 53-70-3 Dibenz(a,h)anthracene ID --- Insufficient data were available to develop a soil community CSCL. 
14-86

CAS Number Constituent CSCL (mg/kg soil DW) Methodology Notes 

Table 14A-9. (continued) 87-86-5 Pentachlorophenol 6 ER-L Derived as the 10th percentile of 21 toxicity values (range: 16 to 2,300 mg/kg soil) based on effects earthworm mortality and reproductive success. 

Mercury and Dioxin 7439-97-6m Methyl mercury ID --- Insufficient data were available to develop a soil community CSCL. 7439-97-6e Mercury (elemental) ID --- Insufficient data were available to develop a soil community CSCL. 7439-97-6 Mercury (divalent) 0.1 Lowest LOEC Derived from the lowest of two toxicity values (range: 0.5 to 12.5 mg/kg soil) based on effects to earthworm survival and reproduction. 1746-01-6 TCDD 2,3,7,8- ID --- Insufficient data were available to develop a soil community CSCL. ID = Insufficient data. LOEC = Lowest observed effects concentration. CSCL = Chemical stressor concentration limit. ER-L = Effects range low— The value was the 10th percentile from the ranked distribution of soil effects concentrations. NOEC = No observed effects concentration. --- = Not applicable because insufficient data were identified.
14-87

Table 14A-10. Scaled Benchmark Doses for Ecological Receptors CAS Number Chemical Name Chemical Type Alligator Snapping Turtle American Kestrel American Robin American Woodcock Bald Eagle Beaver Belted Kingfisher Black Bear B

T

Jac

75-05-8 Acetonitrile O ID ID ID ID ID ID ID ID 107-13-1 Acrylonitrile O ID ID ID ID ID ID ID ID 62-53-3 Aniline O ID ID ID ID ID ID ID ID 7440-36-0 Antimony M ID ID ID ID ID 0.15 ID 0.11 7440-38-2 Arsenic M ID 0.011 0.011 0.011 0.011 2.5 0.011 1.6 7440-39-3 Barium M ID 30 30 30 30 ID 30 ID 71-43-2 Benzene O ID ID ID ID ID 17 ID 12 50-32-8 Benzo(a)pyrene S ID ID ID ID ID 0.67 ID 0.41 7440-41-7 Beryllium M ID ID ID ID ID ID ID ID 117-81-7 Bis(2-ethylhexyl) phthalate S ID 1.1 1.1 1.1 1.1 23 1.1 16 7440-43-9 Cadmium M ID 4.4 4.4 4.4 4.4 1.2 4.4 0.77 75-15-0 Carbon disulfide O ID ID ID ID ID ID ID ID 108-90-7 Chlorobenzene O ID ID ID ID ID ID ID ID 67-66-3 Chloroform O ID ID ID ID ID 9.1 ID 5.7 7440-47-3 Chromium M ID ID ID ID ID ID ID ID 16065-83-1 Chromium III (insoluble salts) M ID 2.2 2.2 2.2 2.2 1,000 2.2 570 118540-29-9 Chromium VI M ID ID ID ID ID 1.9 ID 1.2 53-70-3 Dibenz(a,h)anthracene S ID ID ID ID ID ID ID ID 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) O ID ID ID ID ID ID ID ID 106-93-4 Ethylene dibromide O ID ID ID ID ID ID ID ID 87-68-3 Hexachloro-1,3-butadiene O ID ID ID ID ID ID ID ID 7439-92-1 Lead M ID 0.066 0.066 0.066 0.066 0.0062 0.066 0.0036 0
14-88

CAS Number Chemical Name Chemical Type Alligator Snapping Turtle American Kestrel American Robin American Woodcock Bald Eagle Beaver Belted Kingfisher Black Bear B

T

Jac

Table 14A-10. (continued) 7439-97-6 Mercury (divalent) Hg ID 0.64 0.64 0.64 0.64 0.48 0.64 0.34 

7439976e Mercury (elemental) Hg ID ID ID ID ID ID ID ID 72-43-5 Methoxychlor O ID ID ID ID ID 44 ID 31 78-93-3 Methyl ethyl ketone O ID ID ID ID ID 1000 ID 650 7439976m Methyl mercury Hg ID 0.025 0.025 0.025 0.025 0.045 0.025 0.032 080-62-6 Methyl methacrylate O ID ID ID ID ID ID ID ID 75-09-2 Methylene chloride O ID ID ID ID ID ID ID ID 7440-02-0 Nickel M ID 91 91 91 91 22 91 14 98-95-3 Nitrobenzene O ID ID ID ID ID ID ID ID 87-86-5 Pentachlorophenol O ID 62 62 62 62 2.6 62 1.6 108-95-2 Phenol O ID ID ID ID ID ID ID ID 110-86-1 Pyridine O ID ID ID ID ID ID ID ID 7782-49-2 Selenium M ID 0.71 0.71 0.71 0.71 0.094 0.71 0.066 7440-22-4 Silver M ID ID ID ID ID ID ID ID 1746-01-6 2,3,7,8-Tetrachlorodibenzo-p- dioxin D ID 4.4E-05 4.4E-05 4.4E-05 4.4E-05 6.5E-07 4.4E-05 4.0E-07 1

127-18-4 Tetrachloroethylene O ID ID ID ID ID ID ID ID 7446-18-6 Thallium S ID ID ID ID ID 0.0087 ID 0.005 0137-26-8 Thiram O ID ID ID ID ID ID ID ID 108-88-3 Toluene O ID ID ID ID ID 16 ID 10 71-55-6 1,1,1-Trichloroethane O ID ID ID ID ID 210 ID 130 79-01-6 Trichloroethylene O ID ID ID ID ID 0.44 ID 0.27 7440-62-2 Vanadium M ID 1.8 1.8 1.8 1.8 0.54 1.8 0.38 75-01-4 Vinyl chloride O ID ID ID ID ID 0.2 ID 0.12 7440-66-6 Zinc M ID 32 32 32 32 88 32 62 
14-89

Table 14A-10. (continued) CAS Number Chemical Name Canada Goose Cerulean Warbler Cooper's Hawk Coyote Deer Mouse Eastern Box Turtle Eastern Cottontail Eastern Newt Flatwoods Salamander Gopher Frog 

75-05-8 Acetonitrile ID ID ID ID ID ID ID ID ID ID 107-13-1 Acrylonitrile ID ID ID ID ID ID ID ID ID ID 62-53-3 Aniline ID ID ID ID ID ID ID 370 370 370 7440-36-0 Antimony ID ID ID 0.18 0.84 ID 0.3 0.3 0.3 0.3 7440-38-2 Arsenic 0.011 0.011 0.011 2.8 14 ID 5.1 4.3 4.3 4.3 7440-39-3 Barium 30 30 30 ID ID ID ID ID ID ID 71-43-2 Benzene ID ID ID 19 91 ID 33 34 34 34 50-32-8 Benzo(a)pyrene ID ID ID 0.73 3.7 ID 1.3 ID ID ID 7440-41-7 Beryllium ID ID ID ID ID ID ID 11 11 11 117-81-7 Bis(2-ethylhexyl) phthalate 1.1 1.1 1.1 26 130 ID 46 ID ID ID 7440-43-9 Cadmium 4.4 4.4 4.4 1.4 7 ID 2.5 1.9 1.9 1.9 75-15-0 Carbon disulfide ID ID ID ID ID ID ID ID ID ID 108-90-7 Chlorobenzene ID ID ID ID ID ID ID ID ID ID 67-66-3 Chloroform ID ID ID 10 51 ID 18 15 15 15 7440-47-3 Chromium ID ID ID ID ID ID ID 8.8 8.8 8.8 16065-83-1 Chromium III (insoluble salts) 2.2 2.2 2.2 1,100 5,600 ID 2,000 ID ID ID 18540-29-9 Chromium VI ID ID ID 2.1 11 ID 3.9 ID ID ID 53-70-3 Dibenz(a,h)anthracene ID ID ID ID ID ID ID ID ID ID 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID ID ID ID ID ID ID ID ID ID 

106-93-4 Ethylene dibromide ID ID ID ID ID ID ID ID ID ID 
14-90

CAS Number Chemical Name Canada Goose Cerulean Warbler Cooper's Hawk Coyote Deer Mouse Eastern Box Turtle Eastern Cottontail Eastern Newt Flatwoods Salamander Gopher Frog 

Table 14A-10. (continued) 87-68-3 Hexachloro-1,3-butadiene ID ID ID ID ID ID ID ID ID ID 

7439-92-1 Lead 0.066 0.066 0.066 0.0069 0.035 ID 0.013 2.1 2.1 2.1 7439-97-6 Mercury (divalent) 0.64 0.64 0.64 0.55 2.6 ID 0.95 2.1 2.1 2.1 7439976e Mercury (elemental) ID ID ID ID ID ID ID ID ID ID 72-43-5 Methoxychlor ID ID ID 51 240 ID 88 0.19 0.19 0.19 78-93-3 Methyl ethyl ketone ID ID ID 1100 5800 ID 2100 ID ID ID 7439976m Methyl mercury 0.025 0.025 0.025 0.051 0.25 ID 0.089 ID ID ID 80-62-6 Methyl methacrylate ID ID ID ID ID ID ID ID ID ID 75-09-2 Methylene chloride ID ID ID ID ID ID ID ID ID ID 7440-02-0 Nickel 91 91 91 25 130 ID 45 2.2 2.2 2.2 98-95-3 Nitrobenzene ID ID ID ID ID ID ID 0.64 0.64 0.64 87-86-5 Pentachlorophenol 62 62 62 2.9 15 ID 5.2 0.013 0.013 0.013 108-95-2 Phenol ID ID ID ID ID ID ID 1.3 1.3 1.3 110-86-1 Pyridine ID ID ID ID ID ID ID ID ID ID 7782-49-2 Selenium 0.71 0.71 0.71 0.11 0.51 ID 0.19 1.6 1.6 1.6 7440-22-4 Silver ID ID ID ID ID ID ID 0.03 0.03 0.03 1746-01-6 2,3,7,8-Tetrachlorodibenzo-p- dioxin 4.4E-05 4.4E-05 4.4E-05 7.1E-07 3.6E-06 ID 1.3E-06 ID ID ID 

127-18-4 Tetrachloroethylene ID ID ID ID ID ID ID ID ID ID 7446-18-6 Thallium ID ID ID 0.0095 0.049 ID 0.018 0.11 0.11 0.11 137-26-8 Thiram ID ID ID ID ID ID ID ID ID ID 
14-91

CAS Number Chemical Name Canada Goose Cerulean Warbler Cooper's Hawk Coyote Deer Mouse Eastern Box Turtle Eastern Cottontail Eastern Newt Flatwoods Salamander Gopher Frog 

Table 14A-10. (continued) 108-88-3 Toluene ID ID ID 18 91 ID 33 0.58 0.58 0.58 

71-55-6 1,1,1-Trichloroethane ID ID ID 230 1200 ID 410 ID ID ID 79-01-6 Trichloroethylene ID ID ID 0.48 2.5 ID 0.88 89 89 89 7440-62-2 Vanadium 1.8 1.8 1.8 0.61 2.9 ID 1.1 ID ID ID 75-01-4 Vinyl chloride ID ID ID 0.22 1.1 ID 0.39 ID ID ID 7440-66-6 Zinc 32 32 32 100 480 ID 180 6.5 6.5 6.5 
14-92

Table 14A-10. (continued) CAS Number Chemical Name Green Frog Green Heron Herring Gull Kit Fox Least Weasel Lesser Scaup Little Brown Bat Loggerhead Shrike Long- Tailed Weasel Ma

D

75-05-8 Acetonitrile ID ID ID ID ID ID ID ID ID 107-13-1 Acrylonitrile ID ID ID ID ID ID ID ID ID 62-53-3 Aniline 370 ID ID ID ID ID ID ID ID 7440-36-0 Antimony 0.3 ID ID 0.27 0.73 ID 1.1 ID 0.55 7440-38-2 Arsenic 4.3 0.011 0.011 4.6 12 0.011 17 0.011 8.1 0.7440-39-3 Barium ID 30 30 ID ID 30 ID 30 ID 71-43-2 Benzene 34 ID ID 30 79 ID 120 ID 59 50-32-8 Benzo(a)pyrene ID ID ID 1.2 3.1 ID 4.6 ID 2.1 7440-41-7 Beryllium 11 ID ID ID ID ID ID ID ID 117-81-7 Bis(2-ethylhexyl) phthalate ID 1.1 1.1 41 110 1.1 160 1.1 82 17440-43-9 Cadmium 1.9 4.4 4.4 2.2 5.8 4.4 8.5 4.4 4 475-15-0 Carbon disulfide ID ID ID ID ID ID ID ID ID 108-90-7 Chlorobenzene ID ID ID ID ID ID ID ID ID 67-66-3 Chloroform 15 ID ID 16 42 ID 62 ID 29 7440-47-3 Chromium 8.8 ID ID ID ID ID ID ID ID 16065-83-1 Chromium III (insoluble salts) ID 2.2 2.2 1,800 4,600 2.2 7,500 2.2 3,000 218540-29-9 Chromium VI ID ID ID 3.5 9 ID 13 ID 6.2 53-70-3 Dibenz(a,h)anthracene ID ID ID ID ID ID ID ID ID 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID ID ID ID ID ID ID ID ID 106-93-4 Ethylene dibromide ID ID ID ID ID ID ID ID ID 
14-93

CAS Number Chemical Name Green Frog Green Heron Herring Gull Kit Fox Least Weasel Lesser Scaup Little Brown Bat Loggerhead Shrike Long- Tailed Weasel Ma

D

Table 14A-10. (continued) 87-68-3 Hexachloro-1,3-butadiene ID ID ID ID ID ID ID ID ID 

7439-92-1 Lead 2.1 0.066 0.066 0.011 0.028 0.066 0.046 0.066 0.018 0.7439-97-6 Mercury (divalent) 2.1 0.64 0.64 0.85 2.3 0.64 3.4 0.64 1.7 07439976e Mercury (elemental) ID ID ID ID ID ID ID ID ID 72-43-5 Methoxychlor 0.19 ID ID 79 210 ID 310 ID 160 78-93-3 Methyl ethyl ketone ID ID ID 1,900 4,900 ID 7,100 ID 3,300 7439976m Methyl mercury ID 0.025 0.025 0.08 0.22 0.025 0.32 0.025 0.16 0.80-62-6 Methyl methacrylate ID ID ID ID ID ID ID ID ID 75-09-2 Methylene chloride ID ID ID ID ID ID ID ID ID 7440-02-0 Nickel 2.2 91 91 41 100 91 150 91 71 98-95-3 Nitrobenzene 0.64 ID ID ID ID ID ID ID ID 87-86-5 Pentachlorophenol 0.013 62 62 4.7 12 62 18 62 8.3 108-95-2 Phenol 1.3 ID ID ID ID ID ID ID ID 110-86-1 Pyridine ID ID ID ID ID ID ID ID ID 7782-49-2 Selenium 1.6 0.71 0.71 0.17 0.45 0.71 0.66 0.71 0.33 07440-22-4 Silver 0.03 ID ID ID ID ID ID ID ID 1746-01-6 2,3,7,8-Tetrachlorodibenzo-p- dioxin ID 4.4E-05 4.4E-05 1.2E-06 3.0E-06 4.4E-05 4.4E-06 4.4E-05 2.1E-06 4.4

127-18-4 Tetrachloroethylene ID ID ID ID ID ID ID ID ID 7446-18-6 Thallium 0.11 ID ID 0.015 0.039 ID 0.064 ID 0.026 137-26-8 Thiram ID ID ID ID ID ID ID ID ID 
14-94

CAS Number Chemical Name Green Frog Green Heron Herring Gull Kit Fox Least Weasel Lesser Scaup Little Brown Bat Loggerhead Shrike Long- Tailed Weasel Ma

D

Table 14A-10. (continued) 108-88-3 Toluene 0.58 ID ID 30 76 ID 110 ID 52 

71-55-6 1,1,1-Trichloroethane ID ID ID 370 960 ID 1,400 ID 660 79-01-6 Trichloroethylene 89 ID ID 0.8 2 ID 3 ID 1.4 7440-62-2 Vanadium ID 1.8 1.8 0.96 2.6 1.8 3.8 1.8 1.9 175-01-4 Vinyl chloride ID ID ID 0.36 0.92 ID 1.4 ID 0.63 7440-66-6 Zinc 6.5 32 32 160 420 32 620 32 310 
14-95

Table 14A-10. (continued) CAS Number Chemical Name Mink Mule Deer Muskrat Northern Bobwhite Northern Water Snake Osprey Painted Turtle Pine Vole Prairie Vole Ra

75-05-8 Acetonitrile ID ID ID ID ID ID ID ID ID 107-13-1 Acrylonitrile ID ID ID ID ID ID ID ID ID 62-53-3 Aniline ID ID ID ID ID ID ID ID ID 7440-36-0 Antimony 0.35 0.12 0.34 ID ID ID ID 0.8 0.75 7440-38-2 Arsenic 5.3 1.8 5.5 0.011 ID 0.011 ID 13 12 7440-39-3 Barium ID ID ID 30 ID 30 ID ID ID 71-43-2 Benzene 38 13 36 ID ID ID ID 86 81 50-32-8 Benzo(a)pyrene 1.4 0.47 1.4 ID ID ID ID 3.5 3.1 7440-41-7 Beryllium ID ID ID ID ID ID ID ID ID 117-81-7 Bis(2-ethylhexyl) phthalate 53 17 50 1.1 ID 1.1 ID 120 110 7440-43-9 Cadmium 2.6 0.88 2.7 4.4 ID 4.4 ID 6.5 5.8 75-15-0 Carbon disulfide ID ID ID ID ID ID ID ID ID 108-90-7 Chlorobenzene ID ID ID ID ID ID ID ID ID 67-66-3 Chloroform 19 6.5 20 ID ID ID ID 48 42 7440-47-3 Chromium ID ID ID ID ID ID ID ID ID 16065-83-1 Chromium III (insoluble salts) 2,000 680 2,200 2.2 ID 2.2 ID 5,300 5,000 18540-29-9 Chromium VI 4.1 1.4 4.2 ID ID ID ID 10 9 53-70-3 Dibenz(a,h)anthracene ID ID ID ID ID ID ID ID ID 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID ID ID ID ID ID ID ID ID 

106-93-4 Ethylene dibromide ID ID ID ID ID ID ID ID ID 
14-96

CAS Number Chemical Name Mink Mule Deer Muskrat Northern Bobwhite Northern Water Snake Osprey Painted Turtle Pine Vole Prairie Vole Ra

Table 14A-10. (continued) 87-68-3 Hexachloro-1,3-butadiene ID ID ID ID ID ID ID ID ID 

7439-92-1 Lead 0.012 0.0042 0.013 0.066 ID 0.066 ID 0.033 0.031 07439-97-6 Mercury (divalent) 1.1 0.36 1 0.64 ID 0.64 ID 2.5 2.3 7439976e Mercury (elemental) ID ID ID ID ID ID ID ID ID 72-43-5 Methoxychlor 100 34 97 ID ID ID ID 230 220 78-93-3 Methyl ethyl ketone 2,200 740 2,300 ID ID ID ID 5,500 4,800 7439976m Methyl mercury 0.1 0.034 0.098 0.025 ID 0.025 ID 0.23 0.22 80-62-6 Methyl methacrylate ID ID ID ID ID ID ID ID ID 75-09-2 Methylene chloride ID ID ID ID ID ID ID ID ID 7440-02-0 Nickel 47 16 49 91 ID 91 ID 120 100 98-95-3 Nitrobenzene ID ID ID ID ID ID ID ID ID 87-86-5 Pentachlorophenol 5.5 1.9 5.7 62 ID 62 ID 14 12 108-95-2 Phenol ID ID ID ID ID ID ID ID ID 110-86-1 Pyridine ID ID ID ID ID ID ID ID ID 7782-49-2 Selenium 0.22 0.071 0.21 0.71 ID 0.71 ID 0.49 0.46 7440-22-4 Silver ID ID ID ID ID ID ID ID ID 1746-01-6 2,3,7,8-Tetrachlorodibenzo-p- dioxin 1.4E-06 4.6E-07 1.4E-06 4.4E-05 ID 4.4E-05 ID 3.4E-06 3.0E-06 8

127-18-4 Tetrachloroethylene ID ID ID ID ID ID ID ID ID 7446-18-6 Thallium 0.017 0.0059 0.019 ID ID ID ID 0.046 0.043 137-26-8 Thiram ID ID ID ID ID ID ID ID ID 
14-97

CAS Number Chemical Name Mink Mule Deer Muskrat Northern Bobwhite Northern Water Snake Osprey Painted Turtle Pine Vole Prairie Vole Ra

Table 14A-10. (continued) 108-88-3 Toluene 34 12 35 ID ID ID ID 86 76 

71-55-6 1,1,1-Trichloroethane 430 150 450 ID ID ID ID 1,100 960 79-01-6 Trichloroethylene 0.92 0.31 0.95 ID ID ID ID 2.3 2 7440-62-2 Vanadium 1.2 0.41 1.2 1.8 ID 1.8 ID 2.8 2.6 75-01-4 Vinyl chloride 0.41 0.14 0.43 ID ID ID ID 1 0.92 7440-66-6 Zinc 200 67 190 32 ID 32 ID 460 430 
14-98

Table 14A-10. (continued) CAS Number Chemical Name Red-Tailed Hawk River Otter Short-Tailed Shrew Short-Tailed Weasel Snapping Turtle Southern Hognose Snake Spotted Sandpiper Tree Swallow 

M

75-05-8 Acetonitrile ID ID ID ID ID ID ID ID 107-13-1 Acrylonitrile ID ID ID ID ID ID ID ID 62-53-3 Aniline ID ID ID ID ID ID ID ID 7440-36-0 Antimony ID 0.2 0.89 0.59 ID ID ID ID 7440-38-2 Arsenic 0.011 3.1 15 7.9 ID ID 0.011 0.011 7440-39-3 Barium 30 ID ID ID ID ID 30 30 71-43-2 Benzene ID 21 96 63 ID ID ID ID 50-32-8 Benzo(a)pyrene ID 0.81 4 2.1 ID ID ID ID 7440-41-7 Beryllium ID ID ID ID ID ID ID ID 117-81-7 Bis(2-ethylhexyl) phthalate 1.1 29 130 88 ID ID 1.1 1.1 7440-43-9 Cadmium 4.4 1.5 7.4 3.9 ID ID 4.4 4.4 75-15-0 Carbon disulfide ID ID ID ID ID ID ID ID 108-90-7 Chlorobenzene ID ID ID ID ID ID ID ID 67-66-3 Chloroform ID 11 55 28 ID ID ID ID 7440-47-3 Chromium ID ID ID ID ID ID ID ID 16065-83-1 Chromium III (insoluble salts) 2.2 1200 5800 2800 ID ID 2.2 2.2 18540-29-9 Chromium VI ID 2.4 12 6.1 ID ID ID ID 53-70-3 Dibenz(a,h)anthracene ID ID ID ID ID ID ID ID 94-75-7 2,4-Dichlorophenoxyacetic acid (2,4-D) ID ID ID ID ID ID ID ID 

106-93-4 Ethylene dibromide ID ID ID ID ID ID ID ID 
14-99

CAS Number Chemical Name Red-Tailed Hawk River Otter Short-Tailed Shrew Short-Tailed Weasel Snapping Turtle Southern Hognose Snake Spotted Sandpiper Tree Swallow 

M

Table 14A-10. (continued) 87-68-3 Hexachloro-1,3-butadiene ID ID ID ID ID ID ID ID 

7439-92-1 Lead 0.066 0.0076 0.036 0.017 ID ID 0.066 0.066 7439-97-6 Mercury (divalent) 0.64 0.61 2.8 1.8 ID ID 0.64 0.64 7439976e Mercury (elemental) ID ID ID ID ID ID ID ID 72-43-5 Methoxychlor ID 57 260 170 ID ID ID ID 78-93-3 Methyl ethyl ketone ID 1,300 6,300 3,300 ID ID ID ID 7439976m Methyl mercury 0.025 0.057 0.26 0.17 ID ID 0.025 0.025 80-62-6 Methyl methacrylate ID ID ID ID ID ID ID ID 75-09-2 Methylene chloride ID ID ID ID ID ID ID ID 7440-02-0 Nickel 91 27 130 70 ID ID 91 91 98-95-3 Nitrobenzene ID ID ID ID ID ID ID ID 87-86-5 Pentachlorophenol 62 3.2 16 8.2 ID ID 62 62 108-95-2 Phenol ID ID ID ID ID ID ID ID 110-86-1 Pyridine ID ID ID ID ID ID ID ID 7782-49-2 Selenium 0.71 0.12 0.54 0.36 ID ID 0.71 0.71 7440-22-4 Silver ID ID ID ID ID ID ID ID 1746-01-6 2,3,7,8-Tetrachlorodibenzo-p- dioxin 4.4E-05 7.9E-07 3.9E-06 2.0E-06 ID ID 4.4E-05 4.4E-05 

127-18-4 Tetrachloroethylene ID ID ID ID ID ID ID ID 7446-18-6 Thallium ID 0.011 0.05 0.024 ID ID ID ID 137-26-8 Thiram ID ID ID ID ID ID ID ID 
14-100

CAS Number Chemical Name Red-Tailed Hawk River Otter Short-Tailed Shrew Short-Tailed Weasel Snapping Turtle Southern Hognose Snake Spotted Sandpiper Tree Swallow 

M

Table 14A-10. (continued) 1 08-88-3 Toluene ID 20 98 51 ID ID ID ID 

71-55-6 1,1,1-Trichloroethane ID 250 1,200 650 ID ID ID ID 79-01-6 Trichloroethylene ID 0.54 2.6 1.4 ID ID ID ID 7440-62-2 Vanadium 1.8 0.69 3.1 2.1 ID ID 1.8 1.8 75-01-4 Vinyl chloride ID 0.24 1.2 0.62 ID ID ID ID 7440-66-6 Zinc 32 110 510 340 ID ID 32 32 

ID = Insufficient data. O = Organic constituent. M = Metal. S = Special. Hg = Mercury.