&EPA
United States
Environmental Protection
Agency
Great Lakes
National Program Office
77 West Jackson Boulevard
Chicago, Illinois 60604
EPA 905-R95-001
January 1995
Assessment and
Remediation of
Contaminated Sediments
(ARCS) Program
BASELINE RISK ASSESSMENT FOR
AQUATIC LIFE FOR THE BUFFALO RIVER,
NEW YORK AREA OF CONCERN
United States Areas of Concern
ARCS Priority Areas of Concern
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BASELINE RISK ASSESSMENT FOR AQUATIC LIFE
FOR THE BUFFALO RIVER, NEW YORK,
AREA OF CONCERN
by
Dora R. Passino-Reader, Patrick L. Hudson,
and James P. Hickey
National Biological Survey
Great Lakes Science Center
1451 Green Road
Ann Arbor, Michigan 48105
Project Officer
i
Marc L. Tuchman
_/
j
^ GREAT LAKES NATIONAL PROGRAM OFFICE
U.S. ENVIRONMENTAL PROTECTION AGENCY
CHICAGO, ILLINOIS
U.S. Environmental Protection Agency
Region 5, Library (PL-12J)
77 West Jackson Boulevard, 12th Floor
Chicago, IL 60604-3590
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DISCLAIMER
The information in this document has been funded by the U.S. Environmental
Protection Agency. It has been subjected to the Agency's peer and
administrative review, and it has been approved for publication as an EPA
document. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use by the U.S. Environmental Protection
Agency.
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ABSTRACT
The Great Lakes National Program Office of the U.S. Environmental Protection
Agency initiated the Assessment and Remediation of Contaminated Sediments
(ARCS) program to address concerns of environmental degradation at 43 Areas of
Concern in the Great Lakes. In our first report (Passino-Reader et al. 1992),
we developed a generic approach for baseline hazard evaluation of aquatic life
in the Great Lakes Areas of Concern. In this report, we demonstrate the
application of the generic approach to the Buffalo River (New York) Area of
Concern. Using available historical data on residues in sediments, water, and
biota, we evaluated exposure for 41 contaminants from the Buffalo River for
eight taxa of fish and invertebrates representing the major trophic levels in
the Buffalo River. By comparing exposure concentrations with reference
toxicities, we calculated risk to the eight receptor organisms for typical and
worst cases of exposure to the 41 contaminants. For mixtures of the
contaminants present at the Buffalo River, primarily metals and polyaromatic
hydrocarbons, we compared sediment concentrations with effects range-low (EL-
R) values as reference values for toxicity of mixtures to estimate risk to
aquatic biota.
11
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TABLE OF CONTENTS
Disclaimer i
Abstract ii
List of Figures v
List of Tables vi
Acknowledgments viii
1.0 Executive Summary 1
2.O Introduction 7
2.1 Background 7
2.2 Objectives 7
2.3 Organization of Report 8
3.0 Risk Assessment Framework 9
3.1 Overview of the Procedures and Data Requirements 9
3.2 Site Characterization 9
3.3 Review and Evaluation of Environmental Quality Data 9
3.4 Hazard Identification 11
3.5 Exposure Assessment 11
3.6 Toxicity Assessment 11
3.7 Risk Characterization 12
3.8 Uncertainty Analysis 12
4.0 Characterization of the Exposure Setting:
Buffalo River Area of Concern 13
4.1 General Description of AOC 13
4.2 Abiotic Factors of Aquatic Habitat 13
4.3 Biotic Factors of Aquatic Habitat 16
4.4 Sources and Types of Pollution 26
5.O Data Compilation and Evaluation 29
5.1 Introduction 29
5.2 Sources and Data Summary 29
5.2.1 Sediment Data 29
5.2.2 Water Quality Data 32
5.2.3 Benthic Invertebrate Data 33
5.2.4 Fish Data 35
5.3 QA/QC Results 35
5.
5.
5.
5,
5.
Data Defining Typical Conditions 36
.1 Sediment 36
.2 Water Column 37
.3 Benthos 40
,4 Fish 40
5.5 Data Defining Worst Case Conditions 40
5.5.1 Sediment 40
5.5.2 Water 40
5.5.3 Benthos 45
iii
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5.5.4 Fish 45
6.0 Hazard Identification 48
6.1 Toxicity Profiles for Chemicals 48
6.2 Receptor Responses to Hazards 48
6.2.1 Description of Major Receptors 49
7.0 Exposure Assessment 51
7.1 Identification of Probable Exposure Pathways 51
7.1.1 Description of Each Pathway 51
7.1.2 Evaluation of Exposure Pathways and Concentrations 54
7.2 Determination of Exposure Point Concentrations 56
7.3 Estimation of Chemical Uptakes/Exposure 56
7.3.1 Bioaccumulation/Bioconcentration Factors for Chemicals in
AOC 56
7.3.2 Presentation of Uptake/Exposure Extent 56
8.0 Toxicity Assessment (Dose-Response and Exposure-Response) 67
8.1 Aquatic Toxicity Estimates for Chemical Pollutants Present in
Buffalo River Sediments (1985-1989) 67
8.1.1 Toxicity Estimates for Buffalo River Contaminants 67
8.2 Summation of All Chemicals to Which Receptors are Exposed . . 71
8.3 Identification of Chemicals with No, or Inadequate, Toxicity
Data 71
8.4 Identification of Toxicological Endpoints to be Assessed 71
8.4.1 Data for AOC from Toxicity/Chemistry Workgroup of ARCS ... 71
8.5 Summation of All Chemicals to be Addressed in the Evaluation 73
9.0 Risk Characterization 75
9.1 Individual Chemicals 75
9.2 Multiple Chemicals 93
9.3 Presentation of Risks/Hazards in Summary Format 94
10.0 Characterization of Qualitative Uncertainties 99
10.1 Uncertainty in Data Compilation and Evaluation Step (Hazard
Evaluation Procedure) 99
10.2 Uncertainty in Exposure Assessment (Use of Existing Data) . 102
10.3 Uncertainty in Risk Assessment (Cause and Effect
Relationships) 103
10.4. Summary of Uncertainty 104
References 106
APPENDIX A. Methods for Estimating Missing Water Quality Data Ill
IV
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LIST OF FIGURES
Figure 3.1 Baseline risk assessment 10
Figure 4.1 The Buffalo River Watershed and Area of Concern 14
Figure 4.2 Location of Sediment Sampling Sites in the Area of Concern (from
NTSDEC, 1989) 15
Figure 5.1 Location of Sampling Sites for Fish, Worms, Algae, Clams,
Mussels Biomonitoring and Artificial Substrates in the Buffalo
River AOC 34
V
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LIST OF TABLES
Table 1.1 Summary of contaminant risk associated with all exposure
pathways for aquatic receptor organisms in the Buffalo River
AOC 4
Table 4.1 Submersed aquatic macrophytes in Buffalo Harbor, 1978 (Games
1981) 18
Table 4.2 Crustacean zooplankton collected in the Buffalo River and
Harbor during 1977 and 1979 (after Hard 1980) 19
Table 4.3 Month and area of maximum abundance of common zooplankton
species in the Buffalo River (after Ward 1980) 20
Table 4.4 Densities (No. m"2) of major benthic invertebrate groups found
in the sediments of the channelized portion of the Buffalo
River, 1969-1990 21
Table 4.5 Taxa list of benthic invertebrates in the Buffalo River and
Harbor area (from Bergantz 1977, Simpson 1980, Makarewicz et al.
1982, Robert Bode, NTDEC, personal communication) 23
Table 4.6 Total number and capture frequency of fish collected monthly by
electroshocking (60-m section) and experimental gillnetting
(53 m long) from April, 1981 to January, 1982 in the Buffalo
River and Outer Harbor of Buffalo River (after Makarewicz et al.
1982) 24
Table 4.7 Species composition and relative abundance of fish in the Times
Beach Confined Disposal Facility in 1988 (after Smith et al.
1989) 25
Table 5.1 Metal and Organic Contaminant Exposure Summary. 30
Table 5.2 Non Food Residue 38
Table 5.3 Estimated partition coefficients and computed water ....
concentrations 39
Table 5.4 Benthos Metal and Organochlorine Contaminant Residue Data for
Typical Exposure Conditions 41
Table 5.5 Benthos Polynuclear Aromatic Hydrocarbon (PAH) Residue Data for
Typical and Reasonable Worst-Case Exposure Conditions .... 42
Table 5.6 Fish Contaminant Residue Data, (pg/g wet wt) for Typical
Exposure Conditions. Detection limits in parentheses .... 43
Table 5.7 Fish Polynuclear Aromatic Hydrocarbon (PAH) Residue Data for
Typical and Reasonable Worst-Case Exposure Conditions
(ug/kg) 44
Table 5.8 Benthos Contaminant Metal and Organochlorine Residue Data for
Reasonable Worst Case Exposure Conditions . 46
Table 5.9 Fish Contaminant Metal and Organochlorine Residue Data (ug/g
wet wt) for Reasonable Worst-Case Exposure Conditions. ... 47
Table 6.1 Major fish species and their presumed food habits in the Buffalo
River, New York 50
Table 7.1 Primary contaminant exposure pathways 52
Table 7.2 Food sources used in calculating contaminant residues in food
for each receptor organism 53
Table 7.3 Vehicles by which receptor organisms are exposed at the Buffalo
River AOC. This matrix table was used in calculating risk. . 55
Table 7.4 Bioconcentration (BCF) values used in exposure point
concentration determinations 57
Table 7.5 Food Organism Residue. 58
VI
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Table 7 . 6
Table 7.7
Table 7.8
Table 7.9
Table 7 . 10
Table 7.11
Table 7 . 12
Table 7.13
Table 8 . 1
Table 8 . 2
Table 8 . 3
Table 8.4
Table 9.1
Table 9.2
Table 9.3
Table 9.4
Table 9.5
Table 9.6
Table 9.7
Table 9.8
Table 9.9
Table 9.10
Table 9.11
Table 9.12
Table 9.13
Table 9.14
Table 9.15
Table 9.16
Table 9.17
Table 9.18
Table 9.19
Food Residue, Organism, Subsurface Benthos ...
Food Residue, Organism, Surf*ce Benthos ,
Food Residue, Organism Aufwuchs .
Food Residue, Organism Zooplankton
Food Residue, Organism, Carp
Reference Toxicity, Vehicle, Sediment .... .
Reference Toxicity Vehicle, Water
Reference Toxicity, Vehicle, Food .........
Effects range-low (ER-L) and effects range-median (ER-M)for
mixtures of chemicals in sediments (Long and Morgan 1990) .
Risk From Food, Organism, Subsurface Benthos . , . . .
Risk From Food, Organism, Aufwuchs ..IT,---....
Risk From Food, Organism, Brown Bullhead ....
Risk fffaft Food, Organism, Carp .....,.,,......
Risk From Food, Organism, Gizzard Shad
Risk From Food, Organism, Pumpkinseed
Contaminant Risk, Organism, Subsurface Benthos
Contaminant Risk, Organism, Surface Benthos
Contaminant Risk, Organism, Aufwuchs
contaminant Risk, Organism, ftooplankton ...........
Contaminant Risk, Organism, Brown Bullhead
Contaminant Risk, Organism, Carp
Contaminant Risk, Organism, Gizzard Shad
Contaminant Risk, Organism, Pumpkinseed
Contaminant Risk, HQ Total, Case, Typical
Contaminant Risk, HQ Total, Case, Worst
Risk from exposure to typical chemical sediment mixtures
59
60
61
62
63
64
65
66
69
70
72
74
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
96
97
98
VI1
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ACKNOWLEDGMENTS
We thank the following Work Group chairpersons and subgroup coordinators for
their encouragement and leadership: Marc Tuchman, Carol Braverman, and Cynthia
Fuller. Dr. Christopher Ingersoll provided us with copies of preliminary data
from the Toxicity/Chemistry Work Group. We thank Scott Nelson, Calvin Lee,
Valliaramai Palaniappan, and Kenneth Reader for computer programs to calculate
exposure and risk. Lynn Ogilvie assembled tables. We also thank Marilyn
Murphy for word processing and Lynn Ogilvie, Jay Williams, Richard Quintal,
Erin Himrod, and Brandon Driscoll for proofreading the report. We thank Dr.
John E. Gannon for his encouragement and support throughout the preparation of
this report. We also thank the following individuals who reviewed this report:
Douglas Beltman, Dr. Denny R. Buckler, Dr. Judy Crane, Linda Hoist, Dr.
Christopher Ingersoll, Dr. Peter Landrum, Charles R. Lee, and Marc L. Tuchman.
Contribution no. 866 of the Great Lakes Science Center, National Biological
Survey, Ann Arbor, Michigan.
Vlll
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CHAPTER 1
EXECUTIVE SUMMARY
The 1987 amendments to the Clean Water Act, in Section 118 (c) (3), authorized
the U.S. Environmental Protection Agency's (USEPA) Great Lakes National
Program Office (GLNPO) to initiate the Assessment and Remediation of
Contaminated Sediments (ARCS) Program. The Buffalo River in New York State is
one of five Areas of Concern in the Great Lakes that is being used to
demonstrate assessment and clean-up techniques. In this report, we have
developed and applied assessment techniques appropriate to determine a
baseline hazard evaluation for aquatic life exposed primarily to contaminated
sediments at the Buffalo River Area of Concern.
The baseline aquatic life hazard assessment is a first step in a comprehensive
risk assessment. This assessment follows, where possible, the approach
derived for human health risk assessment at the Buffalo River Area of Concern
(Crane 1993). The assessment follows the Remedial Action Plan (RAP) for the
site and provides a means of quantifying reference levels of risk posed by
chemicals determined to be of potential concern. The reference level results
reflect a conservative estimate of the potential exposures and risks
experienced by Buffalo River aquatic species. A conservative estimate of risk
is determined because: 1) it is impossible to characterize with a known level
of accuracy, individual specific exposures and risk and 2) in the estimation
of risk it is desired to error on the side of increased risk in order to be
protective of aquatic health in decisions concerning remediation. The
baseline or reference level risk estimates are used in conjunction with other
information to determine the need to remediate the site. If remediation
strategies are developed, the baseline risk levels are then used as a
reference level risk by which to judge the relative effectiveness of
remediation alternatives. The process of developing remediation strategies
and determining residual risks is performed in a comprehensive risk assessment
following the baseline.
Typically, the determination of which chemicals to include in an exposure and
risk assessment involves a two step procedure. First, a monitoring study is
conducted and samples are analyzed for all chemicals included on a standard
list of hazardous chemicals such as the EPA priority pollutant list. Those
contaminants that are "frequently" detected above recommended limits (e.g.,
sediment quality criteria) are included in the assessment of aquatic life
exposure and risk. In the case of contaminated sediments there are no
sediment quality criteria for the majority of the chemicals, but only water
quality criteria (WQC). Aquatic toxicologists are developing the following
approaches to sediment" quality criteria: Apparent Effects Threshold (AET),
Effects Range-Low (ER-L), Sediment Quality Triad (SQT), Screening Level
Concentration (SLC), and Equilibrium Partitioning (EP). Therefore, for single
chemicals the approach taken in this assessment is to include estimates of
exposure for all chemicals of potential hazard and detected in the sediment
sampling programs conducted in the Buffalo River. Risk estimates are then
characterized for those chemicals or groups of chemicals for which toxicity
end points (i.e., SQC, EP, WQC, NOEAL, QSAR) are available. Also, for
mixtures we utilized available values for ER-L, AET, SQT, and SLC.
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The following contaminants were considered in this risk assessment on the
basis of their presence in either sediment samples, as monitored in 1985 and
1989, or aquatic biota as measured between 1977 and 1989:
METALS: Cadmium, Chromium, Copper, Iron, Lead, Manganese, Mercury,
Nickel, Silver, Zinc
PAHs: Acenaphthene, Acenaphthylene, Anthracene,
Benzo(a)anthracene, Benzo(a)pyrene, Benzo(b)flouoranthene,
Benzo(ghi)perylene, Benzo(k)fluoranthene, Chrysene,
Dibenzo(a,h)anthracene, Fluoranthene, Fluorene,
Indeno(1,2,3-cd)pyrene, Napthalene, Phenanthrene, Pyrene
PESTICIDES: alph-BHC, beta-BHC, Lindane (gamma-BHC), Aldrin, Chlordane,
Dieldrin, Endrin, Heptachlor, Heptachlor epoxide,
Hexachlorobenzene, Mirex, p,p'DDD, p,p'DDE, p,p'DDT
PCBs: Total PCBs
The typical concentrations for sediment based exposures were estimated using
the average of all samples taken in the most recent sediment sampling study
(i.e., 1989). Reasonable worst-case concentrations were estimated from
sediment data collected in 1985. Typical and reasonable worst-case
concentrations for water quality were derived using two different techniques.
For organic contaminants, sediment data representing typical and reasonable
worst-case conditions were used along with a chemical specific partitioning
coefficients and an assumption of equilibrium to compute a water quality
value. Metal concentrations in the water are derived from a review of STORET
data representative of samples taken from the Buffalo River between 1983 and
1987.
In characterizing exposure and risk, both typical and 'reasonable worst-case'
conditions were investigated for five pathways for eight organisms in the food
web: (1) gill absorption from water, (2) ingested food, (3) ingested
sediment, (4) dermal contact with sediment, and (5) dermal absorption from
water. The distinction between typical and reasonable worst case was based
solely on the environmental concentration data used to compute exposure and
risk.
In the generic document for aquatic risk assessment (Passino-Reader et al.,
1992), the methods for human health assessment (Crane 1993; USEPA 1989a,
1989b, 1992a, 1992b) were adapted to develop new methods for aquatic baseline
risk assessment. Using this approach, a model and equations to calculate
uptake of each of the 41 contaminants by five uptake routes for each of the
eight receptor organisms were developed for the Buffalo River AOC. The eight
receptor organisms were pumpkinseed fish, gizzard shad, carp, brown bullhead,
zooplankton, aufwuchs, surface benthos, and subsurface benthos. However,
large gaps existed for parameters in the model, e.g., partitioning of
contaminants over dermal surfaces for aquatic organisms and assimilation
efficiencies during ingestion of food and sediment for the eight receptor
organisms and 41 chemicals. Hence, in this case study of aquatic risk
assessment for the Buffalo River, we have turned to the more commonly used
methods in aquatic risk assessment, i.e., comparisons of concentrations in the
media with reference toxicities.
First, we constructed a matrix of the media by which each of the eight
receptor organisms were exposed, including which types of food they ate. Then
we determined the concentrations of the 41 contaminants in each of the media,
including residues in the specific foods eaten by each receptor organism. The
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contaminant residues were generally higher in fish than in invertebrates.
Next, we estimated reference toxicities for each medium and receptor organism.
For water, water quality criteria have been established by USEPA for some of
the contaminants. For contaminants lacking water quality criteria, we
estimated reference toxicities for water using NOAEL, chronic toxicity data,
acute toxicity data, or quantitative structure-activity relationships (QSAR),
specifically the linear solvation energy relationship model (LSER) (Hickey and
Passino-Reader 1991) . For sediments, interim sediment quality criteria were
used when available. For other chemicals, we used equilibrium partitioning
thresholds (EP). For the majority of chemicals we used the water reference
toxicities and calculated the corresponding sediment concentrations, using the
approach of Burmaster et al. (1991).
No reference toxicities are established for contaminant exposure of aquatic
organisms by food. Comparable food reference toxicities for humans include
USFDA guidelines. Hence, we proposed a new term, "food quality criteria",
which would be analogous to water quality criteria or sediment quality
criteria. Exposure to contaminated food is a necessary component of aquatic
risk assessment. Therefore, we developed the following method to estimate
food quality criteria for use in the baseline aquatic risk assessment. We
developed a basic equation:
FQC = WQC * BCF
where FQC = food quality criteria, WQC = water quality criteria for the
predator, and BCF = bioconcentration factor for the prey.
Risk for noncarcinogenic chemicals was quantified by a hazard quotient (USEPA
1989a), i.e.:
Hazard quotient = Exposure level
Reference dose
For pumpkinseed and brown bullhead that were eating both fish and
invertebrates, the calculated risk from eating fish was generally higher than
the risk of eating invertebrates. The relative importance of different
exposure routes may be assessed by examining the risks calculated for each
pathway (Tables 9.1 to 9.16). The relative risks varied depending upon the
receptor organism and the type of chemical (See Chapter 9). Risk was not
summed across all chemicals because of the unknown contributions of chemicals
below threshold levels of toxic effects.
Table 1.1 presents for each of the eight receptor organisms only those
chemicals that have a risk (total hazard quotient) greater than one. These
results show that for the typical case cadmium, chromium, copper, iron, lead.
mercury, pyrene. and heptachlor epoxide present a significant risk to most of
the eight receptor organisms. For the worst case, the above compounds plus
zinc, indeno(1.2.3-cd)pyrene. endrin. and total PCBs represent a significant
risk to aquatic receptors.
In considering the conclusions, one must understand the twofold intent of the
baseline assessment. The objective is to develop a reference value for risk
at the Area of Concern. This risk value is used in two ways. First, it is
used as an 'indicator1 of the potential for adverse affects. It is
intentionally conservative to ensure that risks are not underestimated. The
second use of the baseline risk estimate is to use the risk estimates as a
reference point in the analysis of residual risks of remediation alternatives.
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Table 1.1.
Summary of contaminant risk associated with all exposure pathways for aquatic receptor organisms in the Buffalo River
AOC. Only chemicals with risk greater than one are shown. Typical and worst cases are shown seperately.
CASE Typical
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Zinc
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a) f luoranthene
Benzo(ghi )perylene
Chrysene
Indeno(1,2,3-cd)pyrene
Pyrene
Lindane ( gamma -BHC)
Chlordane
Dieldrin
Heptachlor epoxide
Mi rex
PCBs (total)
ORGANISM
Subsurface
Benthos
2.1
56.0
180.0
2900.0
12.0
51.0
18.0
19.0
20.0
3.2
18.0
10.0
5.2
3.6
15.0
13.0
2.1
Surface
Benthos
3.9
58.0
180.0
2900.0
17.0
51.0
32.0
19.0
21.0
3.3
18.0
10.0
5.4
3.8
16.0
16.0
4.0
Aufwuchs
3.9
58.0
180.0
2900.0
17.0
51.0
32.0
19.0
21.0
3.3
18.0
10.0
5.4
3.8
16.0
16.0
4.0
Zooplankton
1.8
3.6
1.1
3.8
5.1
25.0
1.1
2.6
3.9
Brown Bullhead
1.8
3.6
1.3
3.8
5.0
26.0
2.4
1.6
110.0
4.0
4.3
1.2
610.0
Carp
1.8
3.6
1.1
3.8
5.0
25.0
2.4
2.5
3.9
1.5
Gizzard Shad
1.8
3.6
1.1
3.8
5.1
25.0
2.6
3.9
Pumpkinseed
2.7
3.2
1.2
3.8
7.6
21.0
3.8
3.5
3.8
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Table 1.1. (Continued)
CASE Worst
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a) f I uorant hene
Benzo(ghi )perylene
Benzo( k) f I uoranthene
Chrysene
lndeno(1,2,3-cd)pyrene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane ( gamma -BHC)
Chlordane
Endrin
Heptachlor epoxide
PCBs (total)
ORGANISM
Subsurface
Benthos
11.0
470.0
660.0
5600.0
540.0
75.0
93.0
30.0
710.0
98.0
25.0
74.0
18.0
63.0
13.0
7.9
190.0
2.1
51.0
1.7
1.1
23.0
3.7
460.0
Surface
Benthos
15.0
470.0
660.0
5600.0
550.0
76.0
110.0
30.0
710.0
99.0
26.0
76.0
18.0
66.0
14.0
8.2
200.0
2.2
61.0
1.8
1.2
24.0
7.2
480.0
Aufuuchs
15.0
470.0
660.0
5600.0
550.0
76.0
110.0
30.0
710.0
99.0
26.0
76.0
18.0
66.0
14.0
8.2
200.0
2.2
61.0
1.8
1.2
24.0
7.2
480.0
Zooplankton
3.8
17.0
2.2
7.5
11.0
79.0
2.0
1.2
1.5
1.3
4.5
14.0
10.0
1.6
7.6
17.0
Brown Bullhead
3.8
17.0
6.5
7.5
11.0
97.0
2.0
3.2
9.2
6.7
4.1
1.5
7.0
1300.0
Carp
3.8
17.0
2.3
7.5
11.0
79.0
2.0
3.2
9.2
6.7
4.1
1.5
7.0
50.0
Gizzard Shad
3.8
17.0
2.2
7.5
11.0
79.0
2.0
3.3
10.0
1.6
7.6
17.0
Pumpkinseed
5.5
3.2
1.8
7.5
14.0
33.0
3.4
15.0
1.7
1.0
1.9
5.8
45.0
tn
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In this sense, it is used to estimate the relative reduction of risk that
would occur given the implementation of various alternative remediation
strategies.
With this in mind, an appropriate interpretation of the conclusions is that
there is a need to further refine the baseline estimates. The following is a
list of specific recommendations for further work to be performed in order to
refine the estimates of risk reported here:
1. The occurrence of 'hot spots' in the Buffalo River is an open question.
The 1985 sediment sampling shows heightened levels of contamination in a
small portion of the river. The 1989 sediment sampling data is not
sufficient to conclude that the high concentrations measured in 1985 have
decreased. Further, neither the 1985 nor the 1989 sediment data sets is
sufficient for determining the number of locations of other hot spots. It
is recommended that a sampling strategy be developed and implemented to
address the need related to locating and sampling currently existing hot
spots.
2. This baseline assessment assumes that all risks experienced as a result of
exposure within the Buffalo River are due solely to contaminated sediments.
This implies that there are no additional sources of contamination.
However, there are additional sources of contamination, such as combined
sewer overflows and abandoned hazardous waste sites. The extent to which
these sources contribute to exposures and risks is unknown. Before any
remediation strategies are selected, it will be important to accurately
inventory existing sources and to estimate their individual and collective
impact on future water and sediment conditions in the Buffalo River.
3. After the above recommendations have been addressed, the baseline estimate
of exposures and risks should be updated. Incorporation of current data on
residues, toxicity, and benthic community structure at the Buffalo River is
critical for completion of the comprehensive aquatic hazard evaluation.
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CHAPTER 2
INTRODUCTION
2.1. Background
The Great Lakes Water Quality Board of the International Joint Commission has
identified 42 Areas of Concern in the Great Lakes Basin where the objectives
of the 1978 Great Lakes Water Quality Agreement and other jurisdictional
standards, criteria or guidelines are exceeded. Erie, Pennsylvania, was
recently added to become the 43rd Area of Concern. For these Areas of Concern
remedial measures are necessary to restore beneficial uses.
The 1987 amendments to the Clean Water Act, in Section 118(c)(3), authorized
the U.S. Environmental Protection Agency's (USEPA) Great Lakes National
Program Office (GLNPO) to coordinate and conduct a 5-year study and
demonstration project relating to the control and removal of toxic pollutants
in the Great Lakes, with emphasis on removal of toxic pollutants from bottom
sediments (USEPA/GLNPO 1989). Five areas were specified as requiring primary
consideration: Saginaw Bay, Michigan; Buffalo River, New York; Grand Calumet
River, Indiana; Ashtabula River, Ohio; and Sheboygan Harbor, Wisconsin. In
response, GLNPO initiated the Assessment and Remediation of Contaminated
Sediments (ARCS) Program. Information from ARCS Program activities will be
used to guide the development of RAPs for the 43 Areas of Concern.
2.2 Objectives
The primary objective of the RAM Work Group applicable to this report is as
follows—"Hazard Evaluation: To evaluate exposures to, and impacts resulting
from, contact with contaminated sediments and media contaminated by sediment
contaminants incurred by all receptors of concern under the "no action1
alternative and other remedial alternatives. This evaluation will draw upon
the development and integration of predictive tools to describe future hazards
and risks".
The objectives of the baseline aquatic hazard evaluation of the Buffalo River
Area of Concern are as follows:
1. To provide a generic assessment approach to be used in the ARCS Program to
describe actual and potential hazards of contaminated sediments to aquatic
life (receptors) of concern in the Great Lakes.
2. To apply this generic approach to the following site in the ARCS Program:
Buffalo River, NY.
3. To identify aquatic receptors being impacted by sediment-related
contaminants and those requiring protection.
4. To develop preliminary remediation goals for sediment contaminants based on
health of aquatic receptors.
5. To identify information gaps that would be required to fully describe the
risks to aquatic receptors.
-------
2 . 3 Organization of Report
This report is organized into sections, essentially based on the steps for
human health risk assessment (USEPA 1987a, 1989a). Chapter 3 describes in
generic terms, the framework developed here for conducting risk assessments
for aquatic life exposed to contaminated sediments. Chapter 4 characterizes
the exposure setting of the Buffalo River in terms of the natural setting,
land use, abiotic and biotic factors in the aquatic habitat, and sources and
types of pollutants. Chapter 5 presents data compilation and evaluation,
primarily for contaminant residue data but also biological and toxicological
data. Chapter 6 presents the framework for hazard identification, including
the receptor species (invertebrates and fish). Chapter 7 presents the
exposure assessment in terms of the receptor species at the Buffalo River,
exposure pathways, and chemical uptake. Chapter 8 combines dose-response data
and exposure-response data to provide a toxicity assessment. Chapter 9
contains the risk characterization for chemicals of concern at the Buffalo
River. Chapter 10 analyzes the uncertainty associated with the risk
characterization.
-------
CHAPTER 3
RISK ASSESSMENT FRAMEWORK
The purpose of this section is to outline a general framework for conducting
baseline hazard evaluations for aquatic life at Great Lakes Areas of Concern.
The Buffalo River AOC will be used as an example to illustrate the application
of this method. The components of the baseline risk assessment are shown in
Figure 3.1.
3.1 Overview of the Procedures and Data Requirements
Figure 3.1 illustrates the sequence of steps necessary to perform a baseline
risk assessment for aquatic life at sites where sediments are assumed to be
the primary source of contamination.
The overall aim of the baseline risk assessment is to establish the following:
1) what contaminants are present at potentially significant levels in the Area
of Concern, 2) the manner, magnitude, and frequency of exposure of aquatic
receptors (fish and invertebrates), and 3) a "characterization" of the
potential adverse health effects resulting from exposure of aquatic receptors.
The characterization of baseline risk is site-specific and quantitative to the
extent possible using available data. Where there is an absence of data about
the specific Area of Concern, the assessment includes appropriate assumptions
and utilizes published data from other studies.
3.2 Site Characterization
The site characterization step is intended to focus the risk assessment on
those contaminants and aquatic receptors of primary concern, i.e., those
contaminants that show the greatest potential for resulting in substantial
adverse effects. The site characterization should include information on the
location of the site, a history of industrial development, likely contaminants
of concern, and a description of the environmental setting of the site (USEPA
1989a). Inputs to this step include previous assessments, monitoring study
results, historical and present land use patterns, aquatic species present,
lists of hazardous chemicals (e.g., the Priority Pollutant List), and abiotic
and biotic factors of the aquatic habitat. No detailed quantitative analyses
are included in this step. The input material is reviewed and used to define
the nature and limits of contaminant hazard to aquatic life.
3.3 Review and Evaluation of Environmental Quality Data
The objective of this step is to assemble the most complete and current data
set possible representing contamination levels in all relevant media, i.e.,
sediment, water, and biota. Ideally, the data would be sufficient to fully
describe the level of contamination for each chemical on spatial and temporal
scales and ideally all potential exposures to aquatic receptors. Thus the
task within a baseline assessment becomes one of organizing those site
specific data that do exist in order to draw as complete a picture as possible
of the degree and distribution of contamination at the site.
All data used in the assessment should undergo a quality assurance/quality
control (QA/QC) review. This involves collecting information related to the
sampling and analytical techniques used in generating the data. For use in
the ARCS Program, this step is conducted using a quantitative system (Chapter
-------
SITE CHARACTERIZATION
T
Hazard Identification
Review/Evaluation
of Existing
Chemical Data
1
Toxic Assessment
Determination of
Probable Exposure
Pathways
i
Determination of
Exposure Point
Concentrations
Determination of
Contaminant
I n take/Exposure
Risk/Hazard
Characterization
Characterization of
Uncertainty
Evaluation of Baseline Risks
Figure 3.1. Baseline risk assessment.
10
-------
5 of this report; Schumacher and Conkling 1990) that scores data sets with
respect to accuracy, precision, spike recovery, blanks, and other procedures.
3.4 Hazard Identification
Hazard identification continues the process begun in the site characterization
step to define the contaminants of concern for the aquatic hazard evaluation.
"The qualitative assessment or hazard identification part of risk assessment
contains a review of the relevant biological and chemical information bearing
on whether or not an agent may pose a carcinogenic hazard" (USEPA 1987). For
the purpose of the ARCS hazard evaluation, noncarcinogenic responses were
considered in detail as well. Since chemicals seldom occur in a pure state
and are often transformed in the body, the review should include available
information on degradation products of contaminants and metabolites.
3.5 Exposure Assessment
Exposure assessment includes an identification of exposed and potentially
exposed receptors (fish, benthos, plankton) at the AOC; descriptions of
probable exposure pathways for each type of receptor; determination of
exposure point concentrations for each chemical; and estimation of intake for
each chemical and receptor.
Information required for the exposure assessment includes the site
characterization, exposure concentrations, and protocols for computing
exposure of each receptor species. A description of each pathway and a
mathematical expression that permits computation of exposure for each pathway
and receptor is necessary. Below are listed the exposure pathways that should
be considered in an aquatic assessment of risk due to contaminated sediments:
Ingestion of water
Ingestion of food
Ingestion of sediment
Dermal contact with water
Dermal contact with sediments
Gill contact with water
Gill contact with sediments
Only those pathways that are "active" at a particular AOC and receptors need
to be included in the risk assessment. In all cases site specific data is
preferred over regional or national averages.
3 . 6 Toxicity Assessment
Exposure-response and dose-response (concentration response) data from
laboratory studies will be combined with field data on exposure-response, when
available, to estimate exposures to which receptors of interest are subjected.
Emphasis will be placed on adverse effects of chemicals on relevant species
resulting from sediment exposure.
Site specific data from the Toxicity/Chemistry Work Group of ARCS were used
when available. Acute and chronic toxicity data on single chemicals were used
for initial screening of the list of chemicals from the contaminated sediments
and water at the Buffalo River AOC. Bioassay data using whole sediments were
used from the Toxicity/Chemistry Work Group to enable more accurate evaluation
of risk. To complement these data from laboratory bioassays, data on benthic
community structure from the AOC are a necessary component from the field.
While laboratory studies can show relationships between receptors and
11
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individual or combined stressors under controlled conditions, field studies
show the integrated response of receptor populations and communities to all
stressors under natural conditions.
3.7 Risk Characterization
Risk characterization is composed of two parts. One is a presentation of the
numerical estimates of risk; the other is a framework to help judge the
significance of the risk. Risk characterization includes the exposure
assessment and dose-response (concentration-response) assessment. It is
critical that the numerical estimates not be allowed to stand alone, separated
from the various assumptions and uncertainties upon which they are based.
Pending data availability, the evaluation will incorporate the use of Apparent
Effects Threshold (AET), the Sediment Quality Triad (SQT), and Screening Level
Concentration (SLC) as "risk characterization" techniques. Risk should be
characterized for both individual chemical and multiple chemical exposure.
Risk will be estimated across pathways and across media.
3.8 Uncertainty Analysis
EPA guidelines specify that each risk assessment include a discussion of
uncertainty. Statistics implies thinking in terms of uncertainties.
Statistics are used to reason from the sample to the population. Samples used
in this risk assessment may have been impacted for example by poor sampling
design (nonrandom), inadequate field gear (hole in net), poor laboratory
technique (contamination), errors in data entry, and always by chance. These
problems of precision and accuracy will modify our inferences on the subject
of interest, i.e., sediment concentration or body burden of a particular
metal. Statistics supplies scientist with procedures to correct these
problems and to state how often we are right on the average. However, many
times available data are of unknown quality and may not be representative of
the spatial, temporal, or environmental media of interest to the risk
assessor. In the uncertainty analysis we will attempt to point out problems
of accuracy and where possible estimate the precision of various parameter
estimates.
12
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CHAPTER 4
CHARACTERIZATION OF THE EXPOSURE SETTING:
BUFFALO RIVER AREA OF CONCERN
4 .1 General Description of AOC
The Buffalo River is located in the vicinity of the city of Buffalo in
northwestern New York State (Figure 4.1). With its three main tributaries—
Cayuga, Buffalo, and Cazenovia Creeks—it has a drainage basin of about 1,150
km2 (446 mi2) (see NYDEC 1989). The Buffalo River proper is only 12.5 km (7.8
mi) long, originating at the confluence of Buffalo and Cayuga Creeks and
flowing westward into Lake Erie. A navigable channel is maintained in the
lower 8.8 km (5.5 mi) to allow the passage of large lake vessels to the
industrial facilities located along the lower river.
The AOC (Figure 4.2) includes the entire 12.5 km of the Buffalo River (128
ha), as well as the Buffalo Ship Canal (13.4 ha), Outer Harbor (365 ha), Times
Beach Confined Disposal Facility (18 ha), and the Erie Basin Marina (11 ha).
The AOC is characterized by heavy industrial development which began during
the 1800's when the Erie Canal was completed. Both industrial and residential
growth increased through the 1950's, but with changes in transportation
patterns and migration of industries from the Northeast, some of the
industrial and commercial activities ceased along the river. The Buffalo
River still remains a site of considerable industrial activity, and to aid
transportation, the navigable channel is maintained by dredging. However, the
quality of the dredged sediments exceed criteria for open water disposal for
arsenic, barium, copper, iron, lead, manganese, zinc and cyanide. The dredged
sediments are presently placed in the Times Beach Confined Disposal Facility
which is expected to be filled by the mid-1990's.
The sources of past and present pollution to the AOC (NYSDEC 1989) are as
follows: (1) wastewater facility discharges, mainly from industrial chemical
production, specialty chemical production (dye related products), coke
production, oil refining, steel production, and grain milling firms; (2)
inactive hazardous waste sites, of which 32 exist in the Buffalo River
watershed; (3) sewer system overflows with 23 overflows in the Buffalo River
and 16 in the lower Cazenovia Creek; (4) bottom sediments, which are a sink
for contaminants from water and air and potentially a source of contaminants
to water and air; (5) other point and non-point sources.
4.2 Abiotic Factors of Aquatic Habitat
The Buffalo River averages about 100 m (64-275 m) in width with the navigable
portion trough shaped (6.8 m deep) and running two-thirds of the cross
sectional area. The rest of the cross sectional area contains shallow zones
on one or both sides averaging around 3 m in depth near the diked shore and
sloping to 5.4 m near the navigational channel. Makarewicz et al. (1982)
reported the substrate in shallow areas as sandy and the channel substrate as
a gray-black gyttja or dark grey clay. Bergantz (1977) found a mean
percentage sand/silt/clay of 15/51/34 and total organic carbon to average
3.25% (1.33-4.85%). The gradient of the river is very small, less than 17 cm
km"1. During average (17 m's'1) and low flows (1.4 m-s'1) , the river is
13
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Buffalo River
Area of Concern
FIGURE 4.1. The Buffalo River watershed and Area of Concern. The
locations of U.S. Geological Survey gauging stations (•) and the-Buffalo
Airport (X) are shown. From Irvine et al. (1992).
14
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tn
1981 « U.S. Environmental Prolecllon. Agency slles
1989 • U.S. Army Corps of Engineers^ Jompl«J al each sll«)
1985 A NYS D«parlm«nl .of Envlronm«nlol Con»«rvollon »ll«s
Y//\ Crl« Counly sampling aroo
Outer
Harbor
FIGURE .4.2. Location of sediment sampling sites 1n the Area of Concern (from NYSDEC, 1989). Sample
locations for the Aqua Tech (1989) report are similar to those of the USEPA. From Irvine et al. (1992).
-------
influenced by lake level variation associated with the passage of storms
across Lake Erie and seasonal thermal differences between lake water and river
water. The lake may rise 3.7 m above low water datum and a 24-hr increase of
Lake Erie elevation up to 1 m can cause flow reversals and influence the
entire 12.5 km of the Buffalo River. For high flows (in excess of 849 roV1),
the waterway has a riverine character. Surface velocities of 1 ms"1 have been
documented, but during average summertime conditions, velocities are less than
0.02 ms'1 and average resident times may exceed 5 days. Upstream velocities of
0.13 ms'1 have been measured (Sargent 1975). The Buffalo River Improvement
Corporation was formed in the late 1960's to supply water from the Buffalo
Harbor to five major industries along the Buffalo River for process and
cooling purposes. The water is pumped from Lake Erie and ultimately augments
flow in the Buffalo River. Designed to supply 5.3 m^s'1 it currently discharges
about 1 n^s'1 (about 5% of average flow) .
The wider portion of the Buffalo River serves as the most efficient trap area
and collects sediments under high flow conditions while much of the remainder
of the river system is scoured and sediments deposited in the outer harbor.
At discharges above 566 m^s"1, even sand particles are transported. Based on
average annual peak daily flow of 340 mV1 in the Buffalo River for a 45 year
period (1940-1985), the average annual suspended sediment yield for the
drainage basin has been estimated as 95,600 metric tons.
The Buffalo River does not freeze over in the winter and may reach 32°C around
mid to late July. The river does stratify vertically with differences between
surface and bottom layers of 13.5°C. Longitudinal temperature difference up
to 12°C can also result with the intrusion of cold Lake Erie water up into the
river. Dissolved oxygen values in the summer are usually depressed (50-70%
saturation) and levels as low as 1.0 mgL'1 have been measured as recently as
1988 (Adrian and Merckel 1988). Conductivity ranges from 240 to 440 umhoscnT1,
alkalinity from 63 to 105 mg CaCO,/L and total solids from 195-412 mgL'1. In
1987, total phosphorus averaged 105 ugL'1. Secchi disk readings range from 0.5
to 3 m and transparency at the downstream station at times was twice that of
the upstream station (Ward 1980; Carnes 1981; Ecology and Environment 1982).
Temperatures in the embayments and small boat harbors may reach around 24°C in
late July and these areas may freeze over in February. Longitudinal
differences in temperature of 9.3°C may occur in surface temperatures between
shallow and deep areas of the embayments during the summer. Percent oxygen
saturation usually exceeds 80% except for a low value (52%) under ice cover in
February. Conductivity in the embayments ranges from 283 to 462 umhos cm'2 and
alkalinity from 60 to 93 mg CaCO3 IT1. Percent light transmission to the bottom
usually exceeds the compensation point (<1%) up to 3m (Carnes 1981) . The
Buffalo Ship Canal is a long (250-275 m) , narrow slip dredged to 5-6 m deep.
About 50% of the area is shallow and located at the southern end. The dredged
site is characterized by a very steep drop-off from shallow shore areas
containing many old pier posts. Bottom sediments are gray-black gyttja
(Makarewicz et al. 1982).
4.3 Biotic Factors of Aquatic Habitat
Biological sampling of the Buffalo River AOC began in the 1960s, and
investigations of all the trophic levels have been carried out at least once
over the last 30 years. Benthic invertebrate sampling has had the best
temporal and spatial resolution. The following is a brief summary of
biological collections to date.
16
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No quantitative phytoplankton data has been collected from the Buffalo River
AOC except for a cursury look at Times Beach CDF plankton by Stafford et al.
(1987). Ward (1980) did measure chlorophyll a as an estimate of algal
biomass. Chlorophyll a ranged from 0.373 to 20.3 ugL'1. The highest values
were recorded in late July at the upstream station adjacent to the entrance of
Cazenovic Creek. The overall highest volumes were at either upstream or
downstream stations.
Thirteen species of submersed aquatic macrophytes have been reported by Carnes
(1981) and Makarewicz et al. (1982) from the Buffalo River-Harbor area (Table
4.1). Vallisneria americana. Heteranthera dubia and Elodea canadensis were
the most abundant, especially in Cargill Bay and the nearby small boat harbor
(Carnes 1981). Carnes (1981) found Vallisneria to have a strong positive
association with a sand substrate while Elodea and Heteranthera were
associated with silt and clay. Makarewicz et al. (1982) noted high densities
of Myriophyllum. Vallisneria. and various species of Potamoaeton at the COE
Disposal Site 1. They also observed high densities in the small boat harbor
and in the vicinity of the north breakwall. Sparse macrophytes were also
noted at several shallow areas in the harbor, the river mouth, entrance to the
ship canal and at a wide area of the river 4.5 miles upstream. Also, large
cubical blocks used for shoreline protection in the harbor develop luxurious
growths of the macroalgae Cladophora by August (Makarewicz et al. 1982). The
wetland area of the Times Beach CDF is dominated by Carex stipata. Phraomites
australis. Scirpus atrovirens and Typha latifolia (Marquenie et al. 1987).
The aquatic area contains dense populations of submersed aquatic macrophytes.
A cursury examination of the plankton and benthos was made by Stafford et al.
(1987) and typical planktonic forms (Asterionella. Bosmina. and cyclopoids)
and benthic groups (Oligochaeta, amphipods, mayflies, Diptera) were found.
Ward (1980) made monthly surveys of crustacean zooplankton in the Buffalo
River between Michigan Street Bridge and the ConRail tracks in 1979 and
collected 35 different taxa (Table 4.2). She found densities to be greatest
at either the upstream or downstream stations, i.e., densities in August were
eight times higher at the two extreme stations than in the middle four
stations. Typically 70 to 100% of the specimens collected were immature
copepods (nauplii and copepodites). The highest density recorded was 400
copepods L"L at the upstream station in July of which 76% were nauplii.
Densities ran around 100 IT1 in June, July, and August; 18 L"1 in May; and 2-3
L"1 in September and October. Mature zooplankton species were most abundant
between June and August with higher densities usually occurring at the
furthest downstream station (Table 4.3). Of the common taxa, Bosmina is most
numerous, and during its peak abundance in June was evenly distributed
throughout the river. Biomass was estimated based on Ward's (1980) numerical
data and average weight of various groups. Biomass ranged from 1.4 to 525.4
mg/L dry weight with estimates peaking in June.
Benthic populations have been sampled in the Buffalo River since 1963 (Blum
1963). Blum found no benthic invertebrates in the dredged section of the
river, but by the late 1970's - early 1980's, densities of invertebrates
averaged around 40,000 m~2 (Table 4.4) in the downstream 6 miles of the river
(Bergantz 1977, Ecology and Environment, Inc. 1982). The most recent
investigation of the river (Canfield et al. 1992) in 1989 found the fauna of
the river bottom composed of 12 major groups of invertebrates with at least 37
distinct taxa. Oligochaetes have been the most abundant and diverse group and
usually make up over 90% of the fauna. Oligochaete densities up to 130,000 m'2
have been recorded but densities have recently dropped to levels less than
10,000 m^ (Table 4.4), which is typical of less eutrophic situations. Eight
species of oligochaetes have been collected with 4 species of Limnodrilus
dominating (L. hoffmeisteri. L. claparediamus. L. cervic. L. udekiamus) in
17
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Table 4.1. Submersed aquatic macrophytes in Buffalo Harbor, 1978 (Carnes
1981).
Pondweed Family
Potamoqeton pectinatus
Potamoqeton pusillus
Potamoqeton foliosus
Potamoqeton richardsonii
Potamoqeton crispus
Zannichellia palustris
Naid Family
Na.ias flexilis
Frog's-Bit Family
El odea canadensis
Vallisneria americana
Pickerelweed Family
Heteranthera dubia
Hornwort Family
Ceratophvllum demersum
Water-Milfoil Family
Myriophvllum spicatum
Muck-grass
Chara sp.
18
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Table 4.2. Crustacean zooplankton collected in the Buffalo River and
Harbor during 1977 and 1979 (after Ward 1980).
Study
Cladocera
Alona spp. (affinis, guttata,
quadrangula, rectangula)
Bosmina with mucro
Ceriodaphnia lacustris
Chydorus sphaericus
Daphm'a ambigua
0. galeata menodtae
D. longiremis
D. parvula
D. pulex
D. retrocurva
Diaphanosoma leuchtenbergianum
Eubosmina coregoni
Holopedium gibberum
Ilyocryptus sordidus
Leptodora kindtii
Macrothrix laticorm's
Moina rectirostris
Scapholeberis kingi
Copepoda
Calanoida
Diaptomus ashlandi
D. minutus
D. oregonensis
D. sicilis
D. siciloides
Eurytemora affinis
Cyclopoida
Cyclops bicuspidatus thomasi
C. vernal is
Eucy clops agilis
Me socy clops edax
Paracyclops fimbriatus poppei
Tropocyclops prasinus
mexicanus
Harpacticoida
Attheyella illinoisensis
Canthocamptus robertcokeri
River
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Harbor
X
X
X
X
-
X
X
-
.
X
X
X
X
_
X
_
_
-
X
X
X
X
X
X
X
X
X
X
X
X
-
X
19
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Table 4.3. Month and area of maximum abundance of common zooplankton
species in the Buffalo River (after Ward 1980).
Taxa
Bosmina spp.
Daohnia oulex
Cvcloos bicuspidatus
Diaohanosoma sp.
Daohnia retrocurva
MesocvcloDS edax
Daphnia qaleata
Diaotomus oreqonensis
Peak Average
Abundance
(No./L)
20
7
4
4
3
3
2
1
Month of Peak
Abundance
June
August
June
July-August
July
August
July
July-August
Location of
Peak
Abundance
even
downstream
downstream
downstream
downstream
downstream
downstream
downstream
20
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Table 4.4. Densities (No. m~2) of major benthic invertebrate groups found in the sediments
of the channelized portion of the Buffalo River, 1969-1990.
Group
Oligochaetes
Chironomids
Fingernail clams
Snails
Leeches
Fl atworms
Mayflies
Caddisflies
Amphipods
1969'
2530
80
3
14
.
-
.
.
-
19702
1890
18
_
10
_
3
_
-
-
19723
2100
2
6
18
1
.
-
-
-
19774
39000
38
312
40
10
-
2
-
-
19825
38840
240
94
460
60
15
-
-
-
1989'
8730
430
70
59
8
-
8
3
9
1 Sweeney 1970. 2 Sweeney 1971. ' Sweeney and Merckel 1972.
5 Ecology and Environment 1982. 6 Canfield et al. 1992.
4 Bergantz 1977.
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1976-77 (Bergantz 1977) but L. hoffmeisteri. Ouistadrilus multisetosus. and L.
cervic dominating in 1989 (Canfield et al. 1992). The fingernail clams,
Pisidium and Sphaerium. and the chironomid genera, Chironomus and Procladius.
are the only other taxa routinely collected in bottom grabs (Bergantz 1977;
Simpson 1980) through the 1970's.
Overall the benthic collections in 1989 (Canfield et al. 1992) indicated a
marked improvement in the benthic community of the Buffalo River. The
reduction in abundance of oligochaetes, the increased abundance and diversity
of chironomids (11 taxa), the presence of several mayflies, caddisflies, and
amphipods on soft sediments, and the collection of single specimens of a
crayfish and dragonfly all suggest a more balanced and diverse community. The
differences were most obvious at the extreme upper and lower stations on the
river which are influenced by upstream and Lake Erie effects (source of
invertebrates, deposition of clean sediments, etc.). However, the high
density of oligochaetes and the absence of the above groups at station 6-8
suggest a continued degraded condition in the middle section of the river.
The majority of the species listed from the river in Table 4.5 were collected
by New York State's Biological Stream Monitoring Project using artificial
substrate samplers (Hester-Dendy) installed 0.9 m below the surface water.
The river at the dual railroad bridge has been sampled in 1976, 1982, 1987,
and 1988 (R. Bode, NYDEC, personal communication). Although up to 31 species
have been found at a particular date the presence of large numbers of tolerant
species indicates a severely to moderately impacted area. The chironomid
Dicrotendipes simpsoni and the oligochaetes Nais variabilis. Dero nivea. Dero
digitata dominated the 1987-88 multiplate samples.
Makarewicz et al. (1982) sampled benthos in the harbor at a shallow weed
choked embayment and along the outer wall of the south breakwall. The
embayment samples were dominated by snails and clams, accounting for 94.5% of
11,000 to 21,000 invertebrates collected. Species of Amnicola. Valvata and
Pisidium made up the bulk of the specimens. The mixed cobble and sand
substrate in the breakwater was difficult to sample and yielded only around 50
organisms per square meter. Besides snails and clams, several species of
chironomids were relatively abundant.
There have been 43 species of fish collected from the Buffalo River AOC (Table
4.6, 4.7) in recent history, all of which occur in Lake Erie proper or its
tributaries. This compares with a 100 species found in Lake Erie plus an
additional 30 that occur only in tributaries to Lake Erie (Bailey & Smith
1981). Twenty-seven species were collected in the Buffalo River proper in
1981 with pumpkinseed, carp, goldfish, gizzard shad, brown bullhead, yellow
perch and white sucker abundant year around residents (Makarewicz et al.
1982). Emerald and spottail shiners are common in May when they utilize the
river for spawning. More recent collections by Adrain & Merckel (1988) had a
similar fish fauna (29 species) but with some shift in dominance rank. In
1988 the dominant species was gizzard shad, followed by pumpkinseed, golden
shiner, goldfish, emerald shiner, carp and brown bullhead. Smallmouth and
largemouth bass were the dominant piscivores. Pumpkinseed, yellow perch,
white suckers, carp, and goldfish are also common in the ship canal
(Makarewicz et al. 1982). Several larval yellow perch were collected in the
river by Makarewicz et al. (1982) in 1981 suggesting possible use as a
spawning or nursery area and pumpkinseeds were observed nesting in shallow
areas in the river. Adrain and Merckel (1988) collected 292 fish larvae of
which 71% were gizzard shad. Eight other taxa made up the rest of the catch.
Thirty-six species of fish were collected in the harbor in 1981 with permanent
population dominated by yellow perch, carp, rock bass, pumpkinseed, white
sucker and smallmouth bass (Makarewicz et al. 1982). Emerald and spottail
22
-------
Table 4.5. Taxa list of benthic invertebrates in the Buffalo River and Harbor area
(from Bergantz 1977, Simpson 1980, Makarewicz et al. 1982, Canfield et al.
1992, Robert Bode, NYDEC, personal communication).
Harbor Harbor
Harbor Embay- Harbor Embay
River Proper merits River Proper -menu
TurbeUana
Duoesia Carina
Nemaloda
Prtematolaimus so.
Annelida
Naididae
Autodrllus oioueU
AutoPhorus so.
Chaetoqaster diaphanus
Dero dioilala
Dero furcala
Dero nivea
Dero obtusa
Nais barbala
Nan bretscherl
Naia communis
Nai3 oardalis
Nals simplex
Nais varlabilis
Rialstes parasna
Stvtarla lacusms
Tubfflddae
Umnodrilus cervix
Umnodnlus hoflmeislen
Umnodnlus udekiamus
Umnodrilus claoaredianus
Petoscolex mulusetosus
Potamoihrix veidovskvi
Quislradrtlua muttisetosus
TubHex lubrtex
Hirudinea
Hetobdella slaanalis
Crustacea
Asellus so.
Gammarus tascialua
Gammarus oseudolimnaeus
Insecta
Trichoptera
Aqravtea so.
Ceradea so.
Cvrnellus fraternus
Leucotnchia ap.
Nectoosvche so.
Neurediosis so.
Orlhotnchia so.
Ephemeroptera
Caenis so.
Slenaeron inlerounctatum
Coleoptera
Stenelmis so.
Chironomdae
Ablabesmvia maltochi
Ablabesmvia monilis
Chironomua decorus or.
Cladopelma so.
Coekttanvpus
Conchaoelooia so.
Cncotoous btanctus
CrtcotoDus Intersectus or.
Cricotopus svtvesms or.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Cricotopus iremulua qr.
Crvolochironomus lulvus or.
Dicrotendipes lucrter
Dicrolendipes modestus
Dicroptendipea simosoni
EukieKerlella discotonpes gr.
Glvptolendipes tobrterus
Hamischia curalamellala
Microchironomus
Nanodadius dislinctus
Nanodadius spiniptenus
Parachlnoromus abortivus
Parachlronomus Ireguens
Parakieffenella so.
Paramenna so.
Paralanvlarsus SOD.
Penlaneura so.
Phaenopseclra (lavipes
Polypedilum convrelum
Prodadius sublenei
Pseudochironomus so.
Rheotanvtareus exrouus or.
Tanvpus
Tanvlareus olabrescens gr.
Tanvlarsus guertus gr.
Thienemannimvia gr. spp.
Tribetos SOP.
Simulidae
Simulium vmatum
Gastropoda
Amnicola binnevana
Amnicola Integra
Amnicola limosa
Bithvnia lentaculala
Femssia nvulans
Goniobasis livescena
Gvraulus parvus
Helisoma anceos
Helisoma tnvolis
Laevapex fuscus
Lvmnaea emargmala
Menetus dilalalus
Phvsa heterostropha
Pleurocera acula
Pomatiopsis cingnnatiensis
Valvata tewia
Valvata oiscinalis
Varvala sincera
Valvaia tncannala
Vlviparus georqianus
Petocypoda
Anodonta imbecillis
Anooonia orandis
Eliptto comolanala
Musculium
Pisidium
Sohaenum corneum
Schaerium parlumeum
Sohaenum rhomboldeum
Sphaenum simile
Sphaenum transversum
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
23
-------
Table 4.6. Total number and capture frequency of fish collected monthly by
electroshocking (60-m section) and experimental gillnetting (53 m long)
from April, 1981 to January, 1982 in the Buffalo River and Outer Harbor of
Buffalo River (after Makarewicz et al. 1982).
Cannon name
Alewlfe
Black crappie
Bluegill
Bluntnose minnow
Bridle shiner
Brown bullhead
Brown trout
Carp
Carp x goldfish hybrid
Chinook salmon
Coho salmon
Cannon shiner
Emerald shiner
Freshwater drum
6tzzard shad
Golden shiner
Goldfish
Greater redhorse
Lake trout
Largemouth bass
Logperch
Muskel lunge
Northern hognose sucker
Northern pike
Pumpkin seed
Out 11 back carpsucker
Rainbow trout
Rock bass
Shorthead redhorse
Slimy sculpin
Smallmouth bass
Smelt
Spottatl shiner
Stonecat
Trout-perch
Walleye
Warmouth
White bass
White perch
White sucker
Yellow perch
Scientific name
Alosa oseudoharenqus
Pomoxls nlaromaculatus
leoomis macrochlrus
Pimeohales notatus
Notropls blfrenatus
Ictalurus nebulosus
Salmo trutta
Cvprlnus caroio
Oncorhvnchus tshawvtscha
Oncorhynchus kisutch
Notroois cornutus
Notropls atheHnoldes
Aolodlnotus qrunniens
Oorosoma ceoedtanum
Notemiaonus crvsoleucas
Carassius auratus
Moxostome valenciennesi
Salvelinus namavcush
Hicropterus salmoides
Perctna niqromaculatus
Esox masaulnonqy
Hypentelium ni an cons
Esox lucius
lepomis aibbosus
Carol odes cyprlnus
Salmo qalrdneri
Afflbl oolites cuoerstrls
Moxostoma macrol ep1 dotum
Cottus coonatus
Mtcrooterus dolomfeui
Osmerus mordax
Hotroois hudsonius
Noturus flavus
Percoosts omlscomavcus
Stlzostedion vltreum
Chaenobrvttus qulosus
Horone chrvsops
Morone americana
Catostomus conmersoni
Perca flavescens
Electroshocking
Total
number
-
2
2
2
1
15
.
46
3
_
_
4
47
9
51
27
36
_
1
11
2
_
.
1
172
_
3
34
3
2
23
_
83
.
1
1
3
1
1
22
76
Capture
frequency
.
1
1
3
1
7
_
34
3
_
_
6
19
12
24
19
26
_
1
15
1
_
.
1
46
_
4
18
4
1
16
_
13
_
1
1
4
1
1
15
29
Gillnetting
Total
number
3
8
-
.
.
92
1
276
12
1
1
.
_
20
64
20
13
1
.
4
.
33
2
17
15
2
7
108
25
-
28
2
.
20
-
22
-
2
8
300
479
Capture
frequency
2
4
.
.
.
25
1
53
4
1
1
_
.
9
16
10
9
1
-
3
.
14
1
4
9
1
5
32
13
-
13
1
.
9
-
11
-
1
4
55
62
24
-------
Table 4.7. Species composition and relative abundance of fish in the Times
Beach Confined Disposal Facility in 1988 (after Smith et al.
1989).
Species
Pumpkinseed
Rock Bass
Golden shiner
Goldfish X Carp hybrid
Carp
Goldfish
Brown bullhead
Bluntnose minnow
Yellow perch
Emerald shiner
Bluegill
Largemouth bass
White sucker
Northern pike
Spottail shiner
Freshwater drum
White crappie
Iowa darter
Total Captured
No. Captured
806
315
239
167
122
79
45
30
22
9
8
8
6
3
1
1
1
1
1863
%
43.3
16.9
12.8
9.0
6.5
4.2
2.4
1.6
1.2
0.5
0.4
0.4
0.3
0.2
+
+
+
+
+ = less than 0.1%
25
-------
shiners are common in the spring, and gizzard shad in the late summer and
fall. The shallow embayments in the harbor are dominated by pumpkinseed,
yellow perch, northern pike, muskellunge, and carp. Larval yellow perch,
emerald shiners, and smelt along with yearling rock bass were collected in the
harbor. Rock bass and smallmouth bass were observed nesting in the breakwalls
of the harbor.
Smith et al. (1989) collected 18 species of fish inside the Times Beach
Confined Disposal Facility (CDF) in 1989 (Table 4.7). Mark and recapture
estimates on seven species (brown bullhead, goldfish, gold carp, golden
shiner, pumpkinseed, rock bass, and largemouth bass) indicated a population
size of approximately 40,000 fish (5000/ha). Growth of fish inside the CDF
was similar to adjacent or nearby waters. Eighty-nine percent of the brown
bullhead had at least one external abnormality (lip, papilloma, skin
discoloration, stubbed barbels, blindness, body lesions, and parasites).
4.4 Sources and Types of Pollution
Through the 1970s and early 1980s five major industrial facilities discharged
to the Buffalo River (NYSDEC 1989). The facilities were: Allied Chemical
Corporation-Industrial Chemicals Division; Allied Chemical Corporation-
Specialty Chemicals Division; Donner-Hanna Coke; Mobil Oil Corporation, and
Republic Steel Corporation. Three of these (Donner-Hanna Coke, Mobil Oil and
Republic Steel) have terminated production and substantial changes have taken
place at the remaining two facilities (NYSDEC 1989). In the late 1970s the
Industrial Chemical Division of Allied Chemical Corporation produced sulfuric
acid, sulfur trioxide, oleum, nitric acid, oxalic acid, ammonium thiosulfate,
potassium nitrite and heavy metal nitrates. Process and cooling water was
supplied by the Buffalo River Improvement Corporation (BRIC) at the rate of
about 15 mgd. Some of the facilities were sold to PVS Chemical Corporation in
October 1981, and Allied Chemical discontinued all chemical production in
November 1982. At present PVS Chemical produces sulfuric acid, sulfur
trioxide, and oleum and discharges 10 mgd of non-contact cooling water.
The Specialty Chemical Division of Allied Chemical made as many as 1800 dye
related products in 1970. Process and cooling water was supplied by BRIC at
the rate of about 22 mgd. In 1971 a pretreatment facility for process
wastewater was completed and these flows were diverted from the Buffalo River
to the Buffalo Sewer Authority system. In 1977, the dye plant was sold to
Buffalo Color Corporation. The company currently produces only eight chemical
products. Current discharges average about 11 mgd of non-contact cooling
water.
Donner-Hanna Coke produced metallurgical coke through May of 1982 when the
operation was closed. The firm discharged BRIC - supplied process water and
cooling water to the Buffalo River at about 16 mgd. Phenol recovery equipment
was used to treat the discharge through December 1975, after which
sedimentation facilities were added.
The Mobil Oil facility was a 43,000 barrel per day refinery until May 1981
when it ceased operation. BRIC supplied 21 mgd of water, of which 1.6 mgd was
used in the refinery process and the remainder was used as once-through non-
contact cooling water. The process water discharge, which was originally
treated in an oil-water separator, was redirected from the Buffalo River to
the Buffalo Sewer Authority system in November 1979. The facility currently
serves only as a storage terminal.
26
-------
Republic Steel Corporation discharge consisted of BRIG supplied non-contact
cooling water at about 35 mgd and process water at 13 mgd. In the 1980's, the
firm finished a wastewater treatment facility to eliminate process water
discharges into the river but ceased operation in mid 1981.
In addition to these facilities, there are eleven other smaller firms that
discharge into the Buffalo River whose combined flow of either sanitary,
process water, stormwater runoff or non-contact cooling water is less then 10
mgd. Prior to 1981 many of the industrial discharges were handled by the
Buffalo Sewage Authority which discharged directly into the Buffalo River.
With the completion of the Kelly Island sewer project, the Sewage Authority
discharges now into the Niagara River. In addition, the Waste Water Treatment
Plants (WWTP) serving the towns in the watershed were tied into the Buffalo
River Authority in 1977. The only WWTP discharging into the Buffalo River is
the Village of East Aurora, whose plant originally provided secondary
treatment and has recently been upgraded to advanced treatment.
From 1985 to 1987, wastewater from 8 of the 20 municipal and industrial
dischargers into the Buffalo River were found to contain more than 0.1 Ib.
day"1 of priority pollutants (NYSDEC 1989). The highest concentrations were
found in the discharge of Buffalo Color and PVS Chemical with particularly
high levels of chloroform, zinc, methylene chlorine, chromium, and phenols
O1.4 Ibs. day'1) .
There are 23 sewer system overflows into the Buffalo River and 16 in lower
Cazenovia Creek. Since the early 1980's, the Buffalo Sewer Authority has been
undertaking a sewer remediation program to upgrade the structural features of
the system, a sewer cleaning program and an overflow structure backflow
prevention program to improve system carrying capacity (NYDEC 1989). Some
representative compounds and concentrations (ug/L) that could overflow based
on influent concentration entering the treatment facility are: phenol (93),
aniline (160), 4,4'DDT (0.10), acetone (140), 1,4-dichlorobenzene (23),
toluene (110), copper (132), lead (67), and cyanide (16).
There are 32 currently listed inactive hazardous waste disposal sites in the
Buffalo River Watershed (NYSDEC 1989). They range in size from 1 to 100 acres
with contents ranging from calcium carbonate to PCB contaminated oils, cyanide
salts and tetraethyl lead. At some sites (4), contaminant migration to
surface water has been confirmed.
The discharge of chemicals into the Buffalo River over the last 60 years has
resulted in a buildup of contaminants in the bottom sediments. Even if
sources of toxic discharge are curtailed and new sediment buries the
contaminated sediments, a rare hydrological event could redistribute the
contaminant sediments to the mud-water interface again. The Buffalo River
contains excessive levels of at least 26 organic compounds and 11 heavy
metals. Lateral and vertical distributions of the contaminated sediments is
unknown.
The major types of pollutants in the Buffalo River are as follows:
polychlorinated biphenyls (PCBs), chlordanes, polynuclear aromatic
hydrocarbons (PAHs), DDT and metabolites, metals, and cyanides. There are no
permitted discharges of PCBs but because of their low solubility in water they
are unlikely to be detected. PCBs have been found in almost every sediment
sample taken with median values as high as 0.87 ug/g and they have been
detected at several inactive waste sites. PCBs have been detected in the
tissue of carp, white sucker, pumpkinseed, brown bullhead, spottail shiners,
yellow perch, and rock bass. High levels of PCBs in carp have led to a fish
consumption advisory for this species.
27
-------
Chlordane, a pesticide banned in New York State since 1985, has not been
analyzed in the water column of the Buffalo River. It has been found in 16 of
16 sediment samples in 1981 but has not been detected at any hazardous waste
sites. Chlordane has been detected in the tissue of brown bullhead and carp
and unacceptable levels in carp have led to a State fish consumption advisory
for this species.
DDT (and metabolities), a banned pesticide in New York State since 1971, has
not been found in water samples from the Buffalo River, or at any inactive
waste sites. It was detected in only one out of seven samples of influent
entering the Buffalo Sewer Authority WWTP. Bottom sediments (18 out of 28
samples in 1981) appear to be the only source. DDT has been detected in carp,
white sucker, and brown bullhead.
PAHs are common in Buffalo River sediments, at five inactive hazardous waste
sites, and at the Times Beach CDF. This group of chemicals have also been
measured in water samples from the Buffalo River and in the influent to the
Buffalo Sewer Authority WWTP. PAHs have also been detected in the tissue of
the following fish species: yellow perch, pumpkinseed, rock bass, and carp.
Levels of arsenic, barium, copper, iron, lead, manganese, zinc, and cyanides
in the Buffalo River sediments exceed the criteria for open lake disposal.
Sources of these contaminants in the Buffalo River include inactive hazardous
waste disposal sites (21), industrial wastewater facility discharges (4), and
sewer system overflows (39). Metals and cyanides have been found in the
tissue of the following species: yellow perch, pumpkinseed, rock bass, and
carp.
28
-------
CHAPTER 5
DATA COMPILATION AND EVALUATION
5.1 Introduction
This section identifies the existing contaminant data available for each
location and media (water, sediment, biota) where there exists the potential
for aquatic life contact. The task is to evaluate the data's timeliness and
quality and to organize it in a logical and consistent manner. Quality here
refers to a review and evaluation of the QA/QC procedures used in the
collection and analysis of the original sampling data. This evaluation
provides necessary input for the eventual interpretation of risk results,
particularly concerning the uncertainty and thus level of confidence the
assessor has in the characterization of risk. This assessment will include an
estimate of both typical and reasonable worse case risks. The estimate of
typical risk represents that risk determined using a combination of average
contaminant concentration data and aquatic exposure scenarios that reflect
actual site-specific conditions or assumptions that reflect typical or
expected conditions. Reasonable worse case estimates of risk are determined
by combining a statistical measure (e.g., 90th percentile or one standard
deviation) of a contaminant concentration value with assumptions that reflect
professional judgement regarding realistic upper bound contact rates, e.g.,
exposures.
The source and content of the data sets represents information taken from
reports produced by the principle investigators cited and values from the
STORET water quality data base maintained by USEPA. In the organizational
effort it was concluded that insufficient data were available on
concentrations of organic contaminants in water. Organic pollutants in the
water column were predicted from sediment quality, and these predictions were
based on well-established equilibrium partitioning relationships as discussed
in Appendix A.
The environmental data were discussed by media or vehicle of exposure. The
source, content, and quality of each data set used in the assessment is
summarized. The QA/QC evaluation followed in this study is summarized with
the data section. Following this summary is a description of how the data
sets are utilized within this assessment to provide environmental
contamination data for both a typical and reasonable worst-case exposure/risk.
5.2 Sources and Data Summary
Available data (compiled in Lee et al. 1991 and discussed individually) were
surveyed in order to establish exposure concentrations for the Buffalo River
AOC for each location and media (e.g., sediment, benthos, fish, water column)
to assess aquatic environmental health. A summary of contaminants detected in
organisms in the Buffalo River is presented in Table 5.1 The sources of data
available and used for each of these media are discussed below.
5.2.1 Sediment Data
Data for sediment concentrations were available from a number of sources.
Surveys were conducted during 1981 by the US Environmental Protection Agency/
Great Lakes National Program Office (USEPA/GLPNO) (Rockwell et al. 1983) and
29
-------
Table 5.1. Metal and Organic Contaminant Exposure Summary
Contami nant
PCBs
p,p'-DDD
o,p'-DDE
p,p'-DOE
o,p'-DDT
p,p'-DDT
DDT total
aldrin/dieldrin
heptachlor & epoxide
a-BHC
fl-BHC
T-BHC
lindane group
a-chlordane
Y-chlordane
total chlordane
hexachl orobenzene
phenanthrene
anthracene
fluoranthene
pyrene
3 , 6-di methyl phenanthrene
triphenylene
benzo(b)fluorene
benzo(a)anthracene
chrysene
benro(e) pyrene
benzo ( j ) f 1 uoranthene
perylene
benzo(b)fl uoranthene
benzo(k)fl uoranthene
benzo(a)pyrene
dibenzo(a.j) anthracene
dibenzo(a,i Jpyrene
algae
/I
X
clams
\1
X
X
X
X
X
X
X
X
X
X
X
X
X
mussel s
\2
X
X
X
X
X
worms
\3
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
fish
\3,4
X
X
X
X
X
X
X
X
X
X
X
X
X
X
30
-------
Table 5.1 (Continued)
Contaminant
benzo(g,h,i Iperylene
i ndeno( 1 , 2 , 3-c , d) pyrene
3-methyl chol anthrene
anthanthrene
Al umi num
Arsenic
Cadmi urn
Chromi urn
Cobalt
Copper
Lead
Manganese
Mercury
Nickel
Selenium
Zinc
algae
/I
X
X
X
X
X
X
X
X
X
X
X
X
clams
\1
mussels
\2
worms
\3
X
X
X
X
X
X
X
fish
\3.4
X
X
X
X
X
\1 Ontario Ministry of the Environment 1984
\2 E. = Elliptic: Marquenie et al. 1986
\3 Marquenie et al. 1987
\4 NYSDEC RAP 1989
31
-------
the US Army Corps of Engineers - Buffalo District (USACOE) (Pethybridge 1981),
during 1983 and 1985 by the New York State Department of Environmental
Conservation (NYSDEC) (NYSDEC 1985 as cited in NYSDEC 1989) and during 1989 by
Aqua Tech Environmental Consultants Inc (Aqua-Tech 1989).
Data used for the risk assessment were from the studies conducted in 1985 by
NYSDEC (NYSDEC 1985 as cited in NYSDEC 1989) and during 1989 by Aqua Tech
Environmental Consultants Inc (Aqua-Tech 1989).
Figure 4.2. shows sampling locations for the different studies. (Lee et al.
1991).
5.2.1.1 1985 NYSDEC Data Summary
[Erie County, 1985 (Table A6 in NYSDEC 1989)] Sediment sampling was
performed in 1985 by the Buffalo River Sediment Study, as a joint project
of Erie County, the NYSDEC, and the USEPA. The sediment analyses are
summarized in the "Draft Report Buffalo River Sediment Study" (NYSDEC 1985,
as cited in NYSDEC 1989). The 1985 sediment data used in this report are
summarized further in Table 5.2.
The goal of the 1985 study was to develop and field test procedures to
estimate the character of river sediments. A total of 162 samples and 58
sediment cores (using a 1.2-m Vibracore tube) were collected along a 0.46
km foot section pilot study area of the Buffalo River between Mile Point
4.43 and 4.73 (Figure 4.2). An average of three cores per week were
collected between June and October, 1985. In addition, sixteen Dredge grab
samples were collected in the Buffalo River upstream from the confluence
with Cazanovia Creek. These served as control samples since they were
collected upstream from industrial waste discharges. The sediments were
analyzed for metals, PAHs, pesticides and PCBs. The samples collected in
1985 were judged to be from the most contaminated areas of the river, and
therefore indicative of a higher range of contaminants than a random
sampling in the river.
5.2.1.2 1989 Buffalo River Sediment Study
[Aqua-Tech 1989] Sediment sampling was performed in the Buffalo Harbor
area by Aqua Tech Environmental Consultants Inc., under contract to U.S.
Army Corps of Engineers - Buffalo District. The results of this sampling
is reported in "Sediment Analyses - Buffalo River and Harbor, Buffalo, NY"
(Aqua-Tech 1989). The 1989 sediment data used in this report are
summarized in Tables 5.2 and 5.3 as the typical case.
Twenty-two sediment samples were obtained at a depth of 10-20 cm by using a
Petite Ponar grab sampler. Sampling occurred at sites in the Buffalo River
and Harbor and in the Black Rock Canal. Three samples were taken within
15.2 m of each site location. Each site was analyzed for metals, PAHs,
PCBs and pesticides. These sampling sites were distributed along the river
and indicate a more average state of the surficial sediments within the
river.
5.2.2 Water Quality Data
The only source of water quality data used in this assessment came from a
NYSDEC monitoring study of the Buffalo River between 1982 to 1986.
5.2.2.1 NYSDEC Surveys (as cited in NYSDEC 1989)
Water samples were collected between April 1982 and March 1986 from the
Ohio Street Bridge sampling station at 1.1 miles from the harbor on the
Buffalo River (Figure 4.2). The data were stored in the STORET water
32
-------
quality database and were, in part, included in the "Draft Buffalo River
Remedial Action Plan" (NYSDEC 1989). A listing of the STORET summary
statistics describing the water quality results was presented in the
Remedial Action Plan and represents the primary sources of surface water
quality for metals used in the aquatic health risk assessment.
Analytical detection limits were relatively high, resulting in non-
detectable concentrations for a number of water quality constituents.
Therefore, it was determined to estimate data for organic contaminants with
reported non-detectable concentrations using partitioning relationships as
described in Section 5.4.2.
5.2.3 Benthic Invertebrate Data
Benthos concentration data were available from surveys (see Figure 5.1)
conducted during 1983 by the USACOE/WES (worms, Marquenie et al. 1987;
mussels, Marquenie et al. 1986 and 1990) and the Ontario Ministry of the
Environment (clams and algae, OME 1984).
5.2.3.1 1983 Marquenie Study - Worms (Marquenie et al. 1987)
[USACOE, Buffalo District, TB, 1989 (Tables 9, 14, 19)] The survey was
conducted to determine, in part, an inventory of contaminants in
invertebrates inhabiting the Times Beach CDF. Native worms were collected
at the Times Beach CDF and the reference area situated along the east side
of the Niagara River (Figure 5.1). Samples of native worms were collected
in 1983 by and were identified according to species. Tissues were analyzed
for heavy metals, PCBs and hexachlorobenzene (Tables 5.4 and 5.8) as well
as PAHs (Table 5.5). These were terrestrial worms, but their contaminant
data was used to augment the scant data available to demonstrate this
model.
5.2.3.2 1983 Marquenie Study - Mussels
[USACOE, Info/AOC (Lee et al. 1991) (Table 6, 54)] Mussels, Elliotio
dilatata. were collected (Marquenie et al. 1986 and 1990) from a pristine
lake and exposed in the Buffalo River, Lake Erie and a confined disposal
site, Times Beach, Buffalo, New York (Figure 5.1). The mussels were purged
for 1 week in a remote spot of a pristine lake, then 15 randomly selected
individuals were glued to 50 cm long strings of fine nylon. The batches
were taken to the various sites and sunk to the bottom and allowed to
burrow in the sediment with a suitable anchor. After a period of 36 days
the mussels were recollected. The tissues were analyzed for 11 specific
PCB congeners, o,p'-DDE and p,p'-DDE and hexachlorobenzene (HCB) (Tables
5.4 and 5.8).
5.2.3.3 1984 Niagara River Toxics Committee - Clams and Algae
[USACOE Info/AOC (Lee et al. 1991) (Tables 6, 50, 51, 52, 55, 56)] Data
for clams and algae were taken from a 1984 Report of the Niagara River
Toxics Committee, Subproject 28, prepared for the Ontario Ministry of the
Environment (OME 1984). The concentrations and detection limits for a
series of organochlorine contaminants found in clams (Elliptic companatus)
exposed to Lake Erie and Niagara River waters in 1981 are shown in Tables
5.4. and 5.8. Five clams each were exposed in situ to the sediment for 21
days at 15 separate sites. The residues were presented for total PCBs,
three benzene hydrochlorides, hexachlorobenzene, two chlordanes, dieldrin,
four DDT congeners, endosulfan sulfate, heptachlor epoxide, mirex, and
octachlorostyrene. A measure of percent fat (lipid) for the clams was
provided for 11 of the 15 sites. No further details were provided or
33
-------
ALGA • ONTARIO MINISTRY ENVIRONMENT 1980. 81. 82 (R-21)
CLAM - ONTARIO MINISTRY ENVIRONMENT 1980 (R-21)
MUSSEL BIOMONITORINO • US ARMY CORPS OF ENGINEERS 1986 (R-11)
FISH SURVEY SITES - US ARMY CORPS OF ENGINEERS 1982 (R-10)
ARTIFICIAL SUBSTRATE SAMPLES - U.S. EPA 1985 (R-7)
Erie
Basin
Marina
FIGURE 5.1. Location of sampling sites for fish, alga, clams, mussels biomonitoring and artificial
substrates in the Buffalo River AOC. Worms collected at same sites as fish. From Lee et al. (1991) and
Marquerie et al. (1987).
-------
available. Also presented in Tables 5.4 and 5.8 (from the same 1984
report) are the concentrations (dry weight) of total PCBs, and 12 metals
(arsenic, cadmium, lead, copper, mercury and zinc) found in a
filamentous algae Cladophora glomerata at two sites in the Buffalo River.
The data represent several different sampling periods over 2 years. No
further details were available.
5.2.4 Fish Data
A comparative bioaccumulation assessment survey was performed in 1983 by the
USACOE/WES for the USACOE, Buffalo District (Marquenie et al. 1987). NYSDEC
had sampled spottail shiners in 1985 and 1987 and ongoing fish monitoring
program (NYSDEC 1989) and sampled carp and brown bullheads in 1987 (Laniak et
al. 1992, but no data were available).
The data sets used were Marquenie et. al 1987 and NYSDEC 1989.
5.2.4.1 1983 Marquenie study - fish (Marquenie, et al. 1987)
[USACOE, Buffalo District, 1989 (Tables 11, 12, 16, 20-21)] The survey was
conducted to determine, in part, an inventory of contaminants in fish
inhabiting the waters in the Times Beach CDF. Fish species were collected
in August 1983 from the open water of the Times Beach confined disposal
site and from a reference area in the Buffalo River predominantly by
seining and to a lesser extent by hook and line (Figure 5.1). Each species
was pooled into one sample. Fillets of the lateral musculature were
prepared. Liver tissues were prepared to evaluate the presence of
contaminants on a physiological basis and to compare Times Beach with the
reference site for contaminants that do not bioaccumulate in muscle tissue
(e.g., cadmium). Individuals of the same species were pooled, packed in
polyethylene bags, and stored at -20° C. Prior to dissection of livers and
muscle tissue, all specimens were measured (total length) and weighed.
Livers and muscle tissues were pooled by species and stored at -20° C in
acid-washed containers. Tissues were analyzed for heavy metals, PCBs,
hexachlorobenzene (Tables 5.6 and 5.9) as well as PAHs (Table 5.7).
5.2.4.2 Other Studies
(1) NYSDEC 1977-1984 Carp and others (Table 4.4, RAP; USACOE Info/AOC,
Lee et al. 1991, Tables 6, 49)
(2) NYSDEC Spottail shiners (RAP, Table 4.9)
A fish monitoring program was administered by the New York State Department
of Environmental Conservation through the Statewide Toxic Substances
Monitoring Program, and published in the Toxic Substances in Fish and
Wildlife technical report of 1987 (US Dept of Interior 1987; NYSDEC 1989).
There are no reports for the dates of 1977-1984, for which the tissue
samples are reported in Tables 5.6, 5.7, and 5.9. In 1985 and 1987, the
NYSDEC collected young-of-year spottail shiners from the Buffalo River
(NYSDEC 1989), and the tissue sample analyses are reported in Table 5.6,
5.7, and 5.9. No purpose of study, analytical methods, or QA/QC methods
were reported with the data, although detection limits and action-level
criteria were reported.
5.3 QA/QC Results
All of the data used in this risk assessment underwent a QA/QC review by
Lockheed Engineering and Sciences Company (Lockheed-ESC) under a contract with
the EPA Environmental Monitoring Systems Laboratory in Las Vegas, NV. A
complete evaluation of the data could not be made because of difficulty with
35
-------
obtaining the QA/QC data for most data sets. However, it appears that the
data were generated following either established or contract laboratory
protocols. These protocols generally comparable to if not more extensive in
their incorporation of QA/QC samples than specified in the ARCS QA/QC program.
Therefore, it was the opinion of Brian Schumacher, the ARCS QA/QC reviewer
(formerly of Lockheed-ESC), that most data sets are acceptable for use in this
risk assessment (Brian Schumacher (EPA Environmental Monitoring Systems
Laboratory-Las Vegas), personal communication, 1991). With this caveat, the
data were used in the present risk assessment principally to demonstrate the
aquatic risk assessment model, in as much as no more current or acceptable
data were made available.
5.4 Data Defining Typical Conditions
The key considerations when considering the organization of available
environmental quality data into a form suitable for estimating aquatic
exposure and risk are 1) the contaminants of concern and 2) spatial and
temporal changes in contaminant concentration. The selection of chemicals for
consideration might reasonably be determined by comparing the measured levels
with recommended aquatic health-based levels. Those contaminants that are
found to exceed the threshold levels are included in the exposure and risk
assessment. However, there are no widely accepted aquatic-health-based
standards for any contaminated environmental media. In the present
assessment, all toxic compounds detected will be included in the exposure
assessment. These baseline assessments are intended to help develop
guidelines to aid in the selection of chemicals for future exposure and risk
assessments. The data organization should also reflect any variation in
aquatic contaminant concentrations with location ("hot spots") or time.
Aquatic organisms are in constant contact with their environmental media
(water, and/or sediment) and so the data were organized to reflect variability
of measured data only.
For the Buffalo River sediment data sets available, it was determined that
spatial variability within the data sets was not significant (no particular
"hot spots' of high contamination were noted within each data set). Most
recent information available indicates differences between stations evaluated
for toxicity in the Buffalo River (Nelson et al. 1992). There was a
significant difference in contaminant concentrations noted between the 1985
(NYSDEC 1985, as cited in NYSDEC 1989) and 1989 (Aqua-Tech 1989) sediment
surveys. The 1985 sediment data generally contain higher contaminant residues
than does the 1989 data set. Since the surveys were done at different sites
in the Buffalo River, this difference is assumed to be location-specific
(i.e., location of a contamination "hot spot") and not the result of the
system cleansing itself over the intervening four years. Spatial variability
will be considered here by using the 1989 sediment to represent typical
exposure conditions, and the 1985 sediment data will represent a reasonable
worst case situation. The data do not suggest that contaminant concentrations
vary with time, and will not be a factor in the exposure assessment. Sections
5.4 and 5.5 describe the manner in which specific data were configured to
develop the appropriate typical and worst case data sets, respectively. Also
included are the actual data used for these conditions. These data will be
reviewed later in view of other critical criteria. These data were used to
demonstrate the model since more applicable data were not available at the
time this report was prepared.
36
-------
5.4.1 Sediment
(Aqua Tech 1989). The decision to use the means of all samples to compute
exposure was based primarily on one considera'tion. There is generally
relatively little variation in contaminant concentration that is location-
specific (no "hot spots"), and so there is no justification by which to
differentiate on the basis of location. In fact, the sampling was not
performed in sufficient detail to detect hot spots. The mean of each set of
measurements was computed and taken to be representative of the typical
conditions in the superficial sediments of the Buffalo River. The means of
the sample data were provided in Tables 5.2 and 5.3.
The organic compounds that were not detected in either the 1985 or 1989
exposure sediment data were not necessarily eliminated from consideration for
the exposure assessment, exposure pathways, and toxicological (aquatic health
risk) analysis. Organic contaminants that were present at detectable
concentrations in the 1985 data, but were not observed at the detection limits
of the 1989 sediment data, were considered not present for the typical case.
The metals data for 1989 constitute a complete set that can be used with the
inclusion of all metals for concentrations above the detection limit. The
typical conditions were represented by the arithmetic mean of the 1989 data
(Table 5.2).
5.4.2 Water Column
"Total" metals data from the STORET data base and the Remedial Action Plan
(NYSDEC 1989) are used directly as representative of the combined suspended
particles and aqueous concentrations of metals. Because of the availability
of means and standard deviations, the typical case has been represented as the
mean metal concentration.
Water column concentrations reported in the STORET data base indicate that
organics, if present, are at levels below detection limits. It is
unreasonable to assume these organics are not present in the water column
since they are detected in the sediments. A standard assumption in many risk
assessments is to assume a concentration equal to half the detection limit,
but is only valid if the compound is detected at some of the sites. However,
in this assessment, an estimate of water column concentrations was determined
based on chemical equilibrium. The assumption that water column
concentrations are in equilibrium with sediment concentrations provides a
conservative estimate and avoids the arbitrary nature of other methods of
approximation. The details of the equilibrium-based approximation were
described in Appendix A.
The mean contaminant concentrations in 1989 sediments are listed in Table 5.2,
and the resulting water column concentrations used for analysis of typical
aquatic health risks are also listed in Table 5.2 (Crane 1993).
Tables 5.2 and 5.3 list the typical water column concentrations derived using
the above methodologies also detailed in the generic document. Those
chemicals listed as non-detected in the water column were not detected in the
sediments.
37
-------
Table 5.2. Concentrations of contaminants in sediment and water
(nonfood residue) for typical and worst cases.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
BenzoC a ) ant h racene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi)perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamna-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachtor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p,p'DDD
p.p'DOE
p.p'DDT
PCBs (total)
VEHICLE
Sediment
CASE
Typical
CONC
8.00E-01
1.20E+01
4.40E+01
2.88E+04
6.30E+00
5.00E+02
3.30E-01
3.00E+01
2.49E+02
1.80E-01
6.10E-01
9.50E-01
1.65E+00
4.50E-01
6.90E-01
1.57E+00
3.30E-01
4.50E-01
3.10E-01
7.70E-01
9.30E-01
4.00E-02
Worst
CONC
4.30E+00
9.97E+01
1.57E+02
5.55E+04
2.94E+02
7.33E+02
1.71E+00
4.82E+01
8.50E-01
1.20E+03
1.00E+00
1.00E+00
1.50E+00
4.80E+00
4.00E+00
2.90E+00
5.50E+00
2.20E+00
1.50E+00
6.20E+00
3.70E+00
1.00E+00
5.70E+00
9.00E-01
3.10E+00
3.60E+00
4.60E-02
2.90E-02
1.00E-02
7.20E-02
5.00E-03
1.90E-02
1.30E-02
3.80E+00
Water
CASE
Typical
CONC
2.00E-03
2.00E-02
9.00E-03
1 .90E+00
1.60E-02
1.89E-01
1.70E-04
5.00E-03
2.00E-05
2.90E-02
3.15E-04
8.58E-05
5.75E-05
9.98E-05
1.49E-05
9.52E-05
9.94E-04
1.03E-03
1.51E-05
7.77E-03
1.32E-03
6.15E-04
3.90E-03
Worst
CONC
4.00E-03
2.00E-02
1.30E-02
3.76E+00
2.90E-02
4.22E-01
2.60E-04
8.00E-03
2.00E-05
4.40E-02
4.90E-03
9.77E-03
2.63E-03
6.75E-04
2.42E-04
1.75E-04
1.82E-04
1.33E-04
2.07E-04
1.60E-04
2.34E-03
3.11E-03
1.91E-04
2.26E-02
5.31E-03
2.38E-03
2.84E-04
1.79E-04
2.42E-06
7.02E-03
2.45E-07
4.35E-07
6.44E-07
2.37E-04
Blank = not detected in sediment. Data from Laniak et al.
1992.
Metal concentrations in water from STORET data base.
Typical water concentrations are mean values.
Worst case water concentrations represent mean plus one standard deviation.
Concentrations = mg/kg for sediment and mg/L for water.
38
-------
Table 5.3. Estimated partition coefficients and computed water concentrations1.
Chemical
Acenaphthene
Acenaphthylene
Anthracene
Ben 20 (a) anthracene
Benzo (a) pyrene
Benzo (b) f luoranthene
Benzo (ghi) perylene
Benzo (k) f luoranthene
Chrysene
Dibenzo (a , h) anthracene
Fluor anthene
Fluorene
Indeno (1,2, 3-cd) pyrene
Napthalene
Phenanthrene
Pyrene
alpha-BBC
beta-BHC
Lindane
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Beptachlor epoxida
Bexachlorobenzene
Mi rex
P, D ' -DDD
1 r ******
PD ' —DDE
, fff wu
p , p ' -DDT
MT t r *r*r •
PCBs
Log Row2
4
3.7
4.5
5.6
6.1
6.1
6.5
6.1
5.6
6.8
4.9
4.2
6.5
3.3
4.5
4.9
3.9
3.9
3.9
5.3
3.3
3.5
5.3
4.4
2.7
5.2
7.4
6.2
7
6.2
6.0
Row
l.OOE+04
5.01E+03
2.B2E+04
3.98E+05
1.15E+06
1.15E+06
3.24E+06
1.15E+06
4.07E+05
6.31E+06
7.94E+04
1.58E+04
3.16E+06
1.95E+03
2.88E+04
7.59E+04
7.94E+03
7.94E+03
7.94E+03
2.00E+03
2.00E+03
3.16E+03
2.18E+05
2.51E+04
5.01E+02
1.58E+05
2.51E+07
1.S8E+06
l.OOE+07
1.55E+06
1.10E+06
Calc. Roc
6.30E+03
3.16E+03
1.78E+04
2.51E+05
7.23E+05
7.23E+05
2.04E+06
7.23E+05
2.57E-fOS
3.98E+06
5.00E+04
9.98E+03
1.99E+06
1.23E+03
1.82E+04
4.78E+04
5 . OOE-t-03
5.00E+03
5.00E+03
1.26E+05
1.26E+03
1 . 99E+03
1.37E+05
1.58E+04
3.16E+02
9.98E+04
1.58E+07
9.98E+05
6.30E+06
9.76E+05
6.91E+05
Rp (1/Rg)
7.90E+00
4.00E+00
2.24E-f01
3.15E+02
9.11E+02
9.11E+02
2.57E+03
9.11E+02
3.23E+02
5.01E+03
6.31E+01
1.26E+01
2.51E+03
1.50E+00
2.29E+01
6.02E+01
6.30E+00
6.30E+00
6.30E+00
1.58E+02
1 . 60E+00
2.50E+00
1.73E+02
1.99E+01
4.00E-01
1.26E+02
1.99E+04
1.26E+03
7.94E+03
1.23E+03
8.70E+02
Mean 1989
Cone, in
Sediments
(rag/Kg)
N/D
N/D
0.18
0.61
0.95
1.65
0.45
H/D
0.59
N/D
1.57
0.33
0.45
0.31
0.77
0.93
N/D
N/D
N/D
N/D
N/D
N/D
N/D
N/D
0.04
N/D
N/D
N/D
N/D
N/D
N/D
"Typical"
Calc . Cone .
in Water
(mg/L)
3.15E-04
8.58E-05
5.75E-05
9.98E-05
1.49E-05
9.52E-05
9.94E-04
1.03E-03
1.51E-05
7.77E-03
1.32E-03
6.15E-04
3.90E-03
90 %tile
1985 Cone.
in
Sediments
(mg/Rg)
l.OOE+00
l.OOE+00
1.50E+00
4.80E+00
4 . OOE+00
2.90E+00
5.50E+00
2.20E+00
1.50E+00
6.20E+00
3.70E+00
l.OOE+00
5.70E+00
9.00E-01
3.10E+00
3.60E+00
4.60E-02
2.90E-02
N/D
N/D
N/D
N/D
l.OOE-02
N/D
7.20E-02
N/D
N/D
5.00E-03
1.90E-02
1.30E-02
3.8
Reasonable
Worst Case
Calc. Cone.
in Water
-------
5.4.3 Benthos
Only limited data existed regarding contamination levels in Buffalo River
benthos. The Ontario Ministry of the Environment studied the contamination to
clams and algae collected in 1980-81. A summary of the data is reported in
Lee et al. 1991. Marquenie et al. (1986, 1987, 1990) sampled the biota of the
Times Beach confined disposal facility and the Buffalo River within the Area
of Concern in 1983. For use in assessment, average contaminant levels for the
various benthic organisms in the Buffalo River were used to quantify exposure
and risk under typical exposure conditions. These values are given in Tables
5.4 and 5.5. Worms were used even though they were terrestrial to have an
example in the model of a key food chain organism.
5.4.4 Fish
Only limited data existed regarding contamination levels in Buffalo River
fish. The NYSDEC gathered and organized fish data collected between 1977 and
1984, and collected spottail shiners in 1985 and 1987. A summary of the data
is reported in the Buffalo River RAP (NYSDEC 1989). Marquenie et al.1987
studied the population of the Times Beach CDF in 1983. For use in this
assessment, average contaminant levels for the various fish were used to
estimate exposure and risk in a CDF, not in the Buffalo River. These values
are summarized in Tables 5.6 and 5.7.
5.5 Data Defining Reasonable Worst Case Conditions
Data for reasonable worst-case conditions were computed for each of four
uptake media: sediment, water column, benthos, and fish. Contact by the
organisms along the food chain with these media results in exposure and risk
in the Buffalo River Area Of Concern. The data that were used to represent
reasonable worst-case conditions for analysis are described below.
5.5.1 Sediment
Reasonable worst-case conditions were estimated using the sediment data from
1985 (NYSDEC 1985, as cited in NYSDEC 1989). In Tables 5.2 and 5.3, the 90th
percentile values of the available sample data distribution are shown for the
1985 data. The 90" percentile of the sample data distribution for each set of
1985 measurements is considered to be representative of the Buffalo River,
based on assumptions described earlier (Section 5.1). These data did not have
an acceptable QA/QC, so the uncertainty associated with these data and any
interpretation (or calculation) are high.
5.5.2 Water
Similarly to the typical case for organics in surface water, the worst-case
for organic pollutants in the water column (Table 5.2) is based on
equilibrium partitioning (see 5.4.2 and Appendix A).
The organic contaminant sediment concentrations associated with the worst case
scenario (Table 5.3) were used to determine the water column concentrations.
The resulting reasonable worst case water column concentrations are listed in
Tables 5.2 and 5.3.
40
-------
Table 5.4. Benthos Metal and Organochlorine Contaminant Residue Data for
Typical Exposure Conditions
Contain nant
PCBs. total
p,p'-DDD
o.p'-DDE
p.p'-DDE
o.p'-DDT
p.p'-DDT
DDT total
aldrin/dieldrin
heptachlor & epoxide
alpha-BHC
beta-BHC
gamna-BHC
lindane group
al pha-chl ordane
gamma -chl ordane
total chl ordane
hexachl orobenzene
Aluminum
Arsenic
Cadmium
Chromi urn
Cobalt
Copper
Lead
Manganese
Mercury
Nickel
Selenium
Zinc
X fat/lipid
Algae1
(C. qlomerata)
ug/g dry wt
0.093
1740.
9.2
0.6
7.4
2.5
11.0
24.0
510.
0.06
6.4
nd
83.
Clams'
(E. complanatus)
ng/g wet wt
trace
nd
2
nd
nd
2
nd
nd
3
nd
3
6
2
2
4
nd
1.0
Mussels2
(E. dilatata)
ug/kg wet wt
25.16
0.57
1.50
0.59
Worms3
(L. rubellus)
ug/kg dry wt
each <40
13.
10.3
20.0
25.2
0.51
1 C. - Cladophora. E. - Elllptio: Ontario Ministry of the
2 E. - Elliptio: Marquenie et al. 1986. PCBs total of 11
.contaminant residues averaged over 11 sites
3 L. - Lumbricus: Marquenie et al. 1987. PCBs total of 9
average of two measurements; wet weight approximately 5x
41
Environment 1984
congeners; all
congeners and is
dry weight
-------
Table 5.5. Benthos Polynuclear Aromatic
Typical and Reasonable Worst
Hydrocarbon (PAH) Residue Data for
-Case Exposure Conditions
Contaminant
phenanthrene
anthracene
fluoranthene
pyrene
3,6-dimethyl -phenanthrene
triphenylene
benzo(b)pyrene
benzo(a)anthracene
chrysene
benzo(e)pyrene
benzo ( j ) f 1 uoranthene
perylene
benzo (b) fluoranthene
benzo ( k) f 1 uoranthene
benzo(a)pyrene
di benzo ( a, j) -anthracene
di benzo ( a, i) pyrene
benzo (g , h , i ) peryl ene
i ndeno(l, 2, 3-c,d) -pyrene
3-methyl chol anthrene
anthanthrene
Typical Values
worms'
(L. rubellus) ug/kg
dry wt
0.14
0.0069
0.069
(0.002)
(0.0055)
(0.02)
(0.01)
0.017
0.030
(0.0035)
(0.15)
0.0038
0.029
0.013
0.014
(0.015)
(0.015)
0.012
(0.015)
(0.004)
(0.003)
Worst Case
worms'
(L. rubellus) uq/kg
dry wt
0.28
0.095
0.43
0.27
0.014
0.75
0.084
0.375
0.36
0.28
(0.15)
0.16
0.36
0.21
0.45
0.123
0.14
0.70
0.39
(0.004)
0.113
L. = Lumbricus; Marquenie et al. 1987
Values in parentheses are approximate detection limits
wet wt. approx. 5x dry weight
42
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Table 5.6. Fish Contaminant Residue Data (ug/g wet wt) for Typical Exposure Conditions.
limits in parentheses .
Detection
Contaminant
PCBs , total
p,p'-DDD
p , p ' -DDE
p,p'-DDT
DDT total
aldrin/dieldrin
endrin
heptachlor £ epoxide
lindane group
mi rex
total chlordane
hexachlorobenzene
Arsenic
Cadmium
Copper
Mercury
% fat/lipid
Carp1
5.10
0.62
0.03
(0.01)
0.01
0.02
0.01
0.19
0.04
0.13
12.77
White
Sucker1
0.71
0.34
0.01
(0.01)
(0.01)
(0.01)
(0.01)
0.29
1.22
Pumpkinseed1
0.40
<0.048 \2
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
(0.01)
0.0012 \2
0.0965 \2
<0.005 \2
0.360 \2
0.16
0.132 \2
1.28
Brown
Bullhead1
0.87
0.30
0.01
(0.01)
(0.01)
(0.01)
(0.01)
0.10
(0.01)
4.73
Yellow
Perch2
0.063
0.00087
0.0319
<0.004
0.380
0.0847
Spottail
Shiner3
0.144
0.008
0.011
(0.005)
0.019
(0.002)
(0.001)
(0.005)
(0.005)
(0.005)
1 NYSDEC 1989 RAP; averaged values used where
2 Marquenie et al.; Buffalo River/muscle valu<
PCB values are the totals of 9 congeners.
3 NYSDEC 1989 RAP; 1987 values
appropriate.
-------
Table 5.7. Fish Polynuclear Aromatic Hydrocarbon (PAH) Residue Data for Typical and Reasonable Worst-Case
Exposure Conditions (ug/kg)1
Contaminant
phenanthrene
anthracene
fluoranthene
pyrene
3, 6-dimethyl -phenanthrene
triphenylene
benzo (b) f luorene
benzo ( a ) anthracene
chrysene
benzo (e) pyrene
benzo (j ) fluoranthene
perylene
benzo (b) fluoranthene
benzo (k) fluoranthene
benzo (a) pyrene
dibenzo (a, j ) -anthracene
dibenzo (a, i) pyrene
benzo (g, h, i) perylene
indeno (1,2, 3-c, d) -pyrene
3-methylcholanthrene
anthanthrene
Typical Conditions
Yellow
Perch
0.007
0.0005
0.013
(0.02)
(0.003)
(0.01)
(0.008)
(0.007)
(0.01)
(0.03)
(0.1)
(0.0015)
(0.003)
0.0006
(0.0025)
(0.01)
(0.01)
0.028
(0.01)
(0.0035)
(0.003)
Pumpkinseed
0.006
0.0040
0.0002
(0.02)
(0.003)
(0.01)
(0.008)
(0.007)
(0.01)
(0.03)
(0.1)
(0.0015)
(0.003)
0.0006
(0.0025)
(0.01)
(0.01)
0.027
(0.01)
(0.0035)
(0.003)
Worst-Case Conditions
Yellow
Perch
0.014
0.005
0.005
(0.02)
0.001
0.011
(0.008)
(0.007)
(0.01)
(0.03)
(0.1)
(0.0015)
(0.003)
0.0008
(0.0025)
(0.01)
(0.01)
0.030
(0.01)
(0.0035)
(0.003)
Pumpkinseed
0.02
0.008
0.012
(0.02)
(0.003)
0.030
(0.008)
(0.007)
(0.01)
(0.03)
(0.1)
(0.0015)
(0.003)
0.0005
(0.0025)
(0.01)
(0.01)
0.024
(0.01)
(0.0035)
(0.003)
Rock
Bass
0.024
0.004
0.006
(0.02)
(0.003)
(0.01)
(0.008)
(0.007)
(0.01)
(0.03)
(0.1)
(0.0015)
(0.003)
0.0011
(0.0025)
(0.01)
(0.01)
(0.01)
(0.0035)
(0.003)
Carp
0.078
0.019
0.019
(0.02)
(0.003)
(0.01)
(0.008)
(0.007)
(0.01)
(0.03)
(0.1)
0.002
0.007
(0.0025)
(0.01)
(0.01)
(0.01)
(0.0035)
(0.003)
1 Marquenie et al. 1987; muscle values; Values in parentheses are approximate detection limits
-------
The worst-case for metals has been represented as the mean metal concentration
reported in STORET plus one standard derivation. This is assumed to
approximate a reasonable upper bound. (See Section 5.1)
5.5.3 Benthos
Because of the limited data available to represent benthos contamination, an
attempt to describe the reasonable worst-case concentration levels was made.
The resulting reasonable worst-case benthos contaminant concentrations are
listed in Tables 5.5 (PAH) and 5.8 (all others).
5.5.4 Fish
Because of the limited data available to represent fish contamination, an
attempt to describe the reasonable worst-case concentration levels was made.
The worst case was taken to be the highest concentration data set. The
resulting reasonable worst-case fish contaminant concentrations are listed in
Tables 5.7 (PAH) and 5.9 (all others).
45
-------
Table 5.8. Benthos Contaminant Residue Data for Reasonable Worst Case
Exposure Conditions
Contaminant
PCBs, total
D.D'-DDO
o.p'-DDE
p,p'-OOE
o.p'-OOT
D.P'-OOT
DDT total
aldrin/dieldrin
heptachlor & epoxide
alpha-BHC
beta-BHC
ganma-BHC
lindane group
al pha-chl ordane
ganroa-chl ordane
total chl ordane
hexachl orobenzene
Aluminum
Arseni c
Cadmium
Chraniun
Cobalt
Copper
Lead
Manganese
Mercury
Nickel
Selenium
Zinc
X fat/lipid
Algae'
(C. glomerata)
uq/q dry wt
220
2973.
11.3
0.5
13.7
5.6
21.7
60.0
1620.
0.13
12.7
0.9
99.
Clams'
(E. complanatusl
ng/g wet wt
1264
7
n/d
5
trace
12
n/d
3
5
3
n/d
8
13
13
26
2
1.0
Mussels2
(E. dilatatal
ug/kg wet wt
126.8
4.1
6.9
11.0
2.27
worms1
(I. rubellusl
ug/kg dry wt
2746.5
315.0
41.85
98.7
59.0
1.64
1 C. - Cladophora. E. - Elliptic: Ontario Ministry of the Environment 1984
2 E. - Elliptic: Marquenie et al. 1986
3 L. - Lumbricus: Marquenie et al. 1987. PCBs total of 9 congeners and is
average of two measurements; wet weight approximately 5x dry weight.
46
-------
Table 5.9. Fish Contaminant Residue Data (ug/g wet wt) for Reasonable Worst-Case
Exposure Conditions.
Contaminant
PCBs, total
p,p'-DDD
p,p'-DDE
p,p'-DDT
DDT total
aldrin/dieldrin
endrin
heptachlor & epoxide
lindane group
mi rex
total chlordane
hexachlorobenzene
Arsenic
Cadmium
Copper
Mercury
Carp'
1.100
0.038
0.161
<0.0055
0.550
0.154
Rock Bass'
0.430
0.007
0.108
<0.0070
0.220
0.563
Pumpkinseed'
0.280
0.0085
0.107
<0.0035
0.610
0.1325
Yellow
Perch1
0.175
0.0075
0.042
<0.0025
0.480
0.229
Spottail
Shiner2
0.80
0.034
0.041
(0.005)
0.078
0.005
(0.001)
(0.005)
(0.002)
Marquenie et al; Times Beach/muscle values,
PCB values are the totals of 9 congeners.
NYSDEC 1989 RAP; 1985 values
-------
CHAPTER 6
HAZARD IDENTIFICATION
Hazard identification is a qualitative assessment of chemical and biological
information bearing on whether or not a chemical poses a hazard to
individuals, populations, and communities within an ecosystem. The first step
in the identification is to develop toxicity profiles of major contaminant
groups in the Buffalo River. The following contaminant groups were considered
based on their presence in either sediment or fish tissue: PCBs, chlorinated
hydrocarbon insecticides, metals, and PAHs. The toxicity profiles will
summarize physical and chemical properties of the group, metabolic and
pharmacokinetic properties, and relevant structure activity correlations that
support or argue against predicting its hazardous effect. The next step in
the hazard identification is to discuss the type of response to a contaminant
an aquatic receptor might exhibit, how we measure the response, and the type
of endpoints we use.
6.1 Toxicity Profiles for Chemicals
Physical and chemical characteristics of contaminants that would make them
suspect as a toxic substance include (1) persistence in the environment, (2)
environmental mobility, (3) failure to form inert compounds, (4) toxicity, and
(5) ability to sequester in lipids. Properties that can be used to predict
these characteristics include: aqueous solubilities, partition coefficients,
disassociation constants, formation of chemical complexes, degradation,
hydrolysis or photolysis, volatilization, Henry's Law Constants, leaching and
dissipation characteristics, and chemical structures.
The uptake of a chemical and its distribution within the animal's body,
including accumulation, remobilization, and excretion, are strongly dependent
on the above factors. Since chemical alterations may occur by metabolism, not
only the effect of the parent compound, but also that of the metabolites,
which often have different physical-chemical properties, must be considered.
The basic mechanism by which a toxic agent exerts its injurious effect is
fundamental for an understanding of biological responses of flora and fauna.
A toxicity profile provides information on both the contaminant behavior in
the environment and in the receptor. For further discussion of the above, see
Butler (1978) and Passino-Reader et al. (1992). The toxicity profiles are
provided in the generic document (Passino-Reader et al. 1992).
6.2 Receptor Responses to Hazards
Because of the complexity of natural systems, it is difficult to assess the
hazards to all receptors and document all responses. Typically particular
types of receptors and responses are selected to be "indicators" of potential
harm to all components of the aquatic ecosystem under study. For example,
benthic diversity at the community level has frequently been used to assess
environmental quality. This approach avoids many of the sources of error
associated with extrapolation from the laboratory into the field; however, it
is not always possible to identify the cause of the observed degradation of
the biological community. Selection of receptors usually is driven by
practicality, as the receptors and responses selected tend to be those for
which the most toxicity data were available, which is usually those species
that can be tested reliably in the laboratory. See generic document (Passino-
48
-------
Reader et al. 1992) for discussion of receptor responses and utility of
field/laboratory studies for hazard evaluation.
6.2.1 Description of Major Receptors
Receptors can be categorized into various levels ranging from individual cells
to ecosystems. We propose to focus at the community level (fish, zooplankton,
aufwuchs, benthos, aquatic plants). At this level one can still involve
processes at the cellular level and yet hypothesize impacts at the ecosystem
level. Since a major exposure route in aquatic systems is through the food
chain, the aquatic receptors in the Buffalo River and Harbor can be divided
into 5 categories based on functional feeding groups of the major fish species
(Table 6.1). The fish groups include a planktivore (gizzard shad), 4
omnivores (pumpkinseed, carp, white sucker, brown bullhead) and 1 piscivore
(smallmouth bass). The aufwuchs group can be split into animal and plant
species and the benthos into a surface and subsurface species. Aufwuchs are
associated with hard substrate whereas surface benthos are associated with
soft substrate. Cyclopoids and cladocerans make up the zooplankton group and
submersed macrophytes the aquatic plant group.
49
-------
Table 6.1. Major fish species and their presumed food habits in the Buffalo River, New York.
Fish Species
Gizzard Shad
Pumpkinseed
Carp
White Sucker
Brown Bullhead
Muskel lunge
Plankton
X
X
Daphnia
Cyclops
Bosmina
Diaphanosoma
F
Aufwuchs
X
X
Cladophora
Dictotendipes
Asellas
Nias
Phvsa
ood Habits Categor
Surface Benthos
X
X
X
X
Pisidium
Gammarus
Procladius
y
Subsurface
Benthos
X
X
Limnodrilus
Chi ronomus
Fish
X
X
X
Shad
Pumpkinseed
Shiners
tn
o
-------
CHAPTER 7
EXPOSURE ASSESSMENT
Exposure can be defined as the contact of an organism with a chemical or
physical agent. In an aquatic environment, an array of organisms will be
present representing different levels in the food web and inhabiting different
media in the environment, and so each may have a different set of exposure
routes for any contaminant. The aquatic exposure assessment step results in a
cumulative estimate of exposure to a series of identified contaminants over
the lifetime of an organism.
Inputs to the exposure assessment include the characterization of the exposure
setting, data compilation and evaluation of contaminant residues, and
identification of receptor organisms at the site.
7.1 Identification of Probable Exposure Pathways
A major step in the exposure assessment is the identification of potentially
significant pathways for each type of organism present in the aquatic
environment at the site. The contaminant load at the site is presumed to
result principally from an equilibrium with the sediment, and an examination
of the data in Chapter 5 would tend to support this. The total exposure each
organism receives will be a sum of the exposure by all media, i.e., sediment,
water, and food.
7.1.1 Description of Each Pathway
A listing of probable exposure pathways for representative organisms present
at the Buffalo River AOC aquatic environment is given in Table 7.1. Only the
pathways assumed to be 'active' are included.
7.1.1.1 Gill absorption from water
The most vulnerable point of fish and some aquatic invertebrates to
poisoning is the gills, where respiration takes place. The gills provide a
direct pathway from the aquatic environment to the organism's bloodstream,
bypassing the skin and digestive tracts, each with their own physical
barriers and chemical detoxification mechanisms. The contaminant
equilibrium between sediment and water column will tend to dictate aqueous
contaminant concentration at the gills, and this may be augmented on
occasion by direct discharge to the water and by equilibrium between air
and water. Most of the contaminants of concern in the water column will
then partition out at the gills into the more lipophilic environment of the
bloodstream and be transported to sites of action. Although the gills are
a primary surface for partitioning in fish, the entire body surface is
important in invertebrates.
7.1.1.2 Ingested food
The data tables in sections 5.4 and 5.5 contain the available contaminant
residue data for important resident organisms, and Tables 6.1 and 7.2 list
the dietary habits of the major fish species for the Buffalo River AOC.
The phenomenon of biomagnification along the food chain results in a
greater concentration of contaminants at each level. A knowledge of the
biomass of an organism's consumption rate, assimilation efficiency, and the
duration of a particular diet over an organism's lifetime minus depuration
51
-------
Table 7.1. Primary contaminant exposure pathways.
Gizzard Shad
1. Gill absorption from H20
2. Ingested food
3. Ingested sediment
Brown Bullhead and Carp
1. Gill absorption from H20
2. Dermal absorption from sediment
3. Ingested food
4. Ingested sediments
5. Dermal absorption from H20
Pumpkinseed
1. Gill absorption from H20
2. Ingested food
Zooolankton
1. Gill absorption from H20
2. Ingested sediment
3. Ingested food
Aufwuchs
1. Ingested sediments
2. Dermal absorption from sediment
3. Ingested food
4. Dermal absorption from H20
5. Gill absorption from H20
Surface Benthos
1. Gill absorption from H20
2. Dermal absorption from H20
3. Dermal absorption from sediment
4. Ingested sediment
5. Ingested food
Subsurface Benthos
1. Dermal absorption from sediment
2. Ingested sediment
3. Ingested food
52
-------
Table 7.2 Food sources used in calculating contaminant residues in
food for each receptor organism.
Receptor Food category* or method of calculation
Pumpkinseed Worms (W), Plankton (P), Gizzard shad (G)
Gizzard shad Plankton (P)
Brown bullhead Worms (W), Fish (F)
Carp Worms (W)
Zooplankton Plankton (P)
Aufwuchs Cs * 10
Surface benthos Cs * 10
Subsurface benthos Cs * 10
* Food categories are defined in Table 7.5. Cs = contaminant concentration in
sediment (Table 5.2).
53
-------
rate can determine the resultant body burden for a contaminant of concern for
a particular species.
7.1.1.3 Ingested sediment
While all organisms in an aquatic environment may ingest suspended
sediment, the amount is generally considered insignificant. Benthic
inhabitants (bottom feeders) especially subsurface benthos would be
expected to ingest more sediment than pelagic (water column) organisms.
7.1.1.4 Dermal contact with sediment
The benthic organisms have prolonged contact with the sediments, and so
this becomes an important potential pathway for contaminant uptake.
Consideration of duration and area of contact with the sediment,
contaminant sediment-water partition coefficients and a measure of
contaminant partitioning through the skin can be used to calculate
exposure-point concentrations and body burden for this route.
7.1.1.5 Dermal absorption from water
For invertebrates, absorption directly from the water becomes a significant
pathway. Use of the contaminant concentrations in the water column due to
equilibrium with sediment, air and/or direct discharge into the water
column, together with a measure of partitioning into the organism and
appropriate bioconcentration factors can be used to calculate exposure
point concentrations that may serve as the body burden for the organism.
7.1.2 Evaluation of Exposure Pathways and Concentrations
As described in the Generic Document (Passino-Reader et al. 1992), we
initially derived equations and calculated uptake of each chemical by each
receptor organism. The equations derived were adapted from those for uptake
of contaminants by humans (Crane 1993; USEPA 1989a). However, attempting this
approach underscored the large data gaps that made it difficult to
successfully apply human exposure models to aquatic biota at the Buffalo
River. Estimating uptake of each chemical by each receptor from ingestion of
food was the most difficult because of sparse data on residues of the 41
chemicals in all trophic levels. Also little information was available to
quantitate the ingestion and depuration rates of specific foods by each
receptor and assimilation efficiencies for each chemical and receptor.
Subsequently, information in Tables 6.1 (food habits of fish) and 7.1
(exposure pathways) was used to construct a matrix (Table 7.3) showing the
vehicles, both media and food, by which the different receptor organisms at
the Buffalo River were exposed. Table 7.3 was also used in calculations of
risk.
The next step was to determine the concentration of each contaminant in each
vehicle to which each receptor was exposed. As compiled in Chapter 5,
concentrations in water and sediment for typical and worst cases were shown in
Table 5.2. The concentrations of each contaminant in the four types of food
are shown in Table 7.5, which was compiled in part from Tables 5.4 to 5.9.
In Table 7.5, phytoplankton (P) residues (CJ equalled water concentrations
(CJ times 100 for metals or times 1,000 for organic chemicals, where 100 for
metals and 1,000 for organics represent estimated bioconcentration factors.
Gizzard shad (G) residues are intended to represent chemical concentrations in
forage fish. Measured organochlorine concentrations for spottail shiners
(Tables 5.6 and 5.9) were included in the food category G for total PCBs,
p,p'DDD, and p,p'DDE. In an earlier approach (Passino-Reader et al. 1992) in
54
-------
Table 7.3. Vehicles by which receptor organisms are exposed at the
Buffalo River AOC. This matrix table was used in calculating
risk.
Receptor
Pumpkinseed
Gizzard shad
Brown bullhead
Carp
Zooplankton
Aufwuchs
Surface benthos
Subsurface benthos
Vehicle
Water
X
X
X
X
X
X
X
0
Sediment
0
X
X
X
X
X
X
X
Food
Invertebrate
X
X
X
X
X
X
X
X
Fish
X
0
X
0
0
0
0
0
55
-------
which total contaminant exposure concentrations were calculated for gizzard
shad, these calculated concentrations were included in food category G for all
chemicals except those for which spottail shiner data existed. However, in
the present approach, which does not include calculating total exposure
concentrations, we estimated residue concentrations for food category G by
multiplying the water concentration (CJ for each chemical (Table 5.2) times
the BCF values for fish (BCFt) for each chemical (Table 7.4).
Since food of the subsurface benthos, surface benthos, and aufwuchs is
primarily in contact with sediments, their food was considered to have
chemical residue concentrations equal to a factor times the concentrations
of the chemicals in the sediment (Table 5.2). The factor was chosen to be
10 for all 41 chemicals. For example, the concentration of cadmium in food
(Ce) of subsurface benthos, surface benthos, and aufwuchs equals C, * 10 =
0.80 * 10 = 8.0 mg/kg for the typical case.
To present explicitly the concentrations in food used for each receptor
organism, based on food habits (Table 6.1) and concentrations in the types
of food (Table 7.5), we constructed Tables 7.6 to 7.13.
7.2 Determination of Exposure Point Concentrations
The concentration data used in the analysis of exposure, and their origins,
were discussed in the generic document and preceding sections. To estimate
the exposure for each of the pathways in Table 7.1, data are required for
sediment, water, benthos, and fish concentrations. Data for exposure due to
organism concentrations by consumption along the food chain are taken from
direct measurements of organism body burdens when available.
7. 3 Estimation of Chemical Uptakes/Exposure
7.3.1 Bioaccumulation/Bioconcentration Factors for Chemicals in AOC
Measured bioconcentration factors (BCF) for invertebrates and fish are
assembled in Tables VII.D.1-1 and VII.D.1-2 in Passino-Reader et al. (1992),
for organic and inorganic contaminants, respectively. For contaminants for
which no BCF values are listed in these two tables, we calculated values for
BCF, using the regression equations given in Lyman et al. (1990). The values
of BCF used for calculating the contaminant concentrations in organisms are
presented in Table 7.4 of this report, which includes all available measured
values plus calculated values where necessary.
7.3.2 Presentation of Uptake/Exposure Extent
The calculated values for uptake/exposure for representative receptor species
and all chemicals selected in the hazard identification across all "active"
exposure pathways are presented in tabular form here.
The contaminant residue values in the four types of food are given in Table
7.5. Values for C, and Cw are found in Chapter 5.
The contaminant concentrations in the food of each of the eight receptor
organisms are presented in Tables 7.6 to 7.13.
56
-------
Table 7.4. Bioconcentration (BCF) values used in exposure point concentration
determinations.
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo (a) anthracene
Benzo (a) pyrene
Benzo (b) f luoranthene
Benzo (ghi) perylene
Benzo (k) f luoranthene
Chrysene
Dibenzo (ah) anthracene
Fluoranthene
Fluorene
Indeno (1 , 2 , 3-bc) pyrene
Naphthalene
Phenanthrene
Pyrene
tt-BHC
3-BHC
Tf-BHC (Lindane)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Rexachlorobenzene
Mi rex
p , p ' ODD
p , p ' DDE
p , p ' DDT
PCB (Total)
Invertebrates
3,500
200
200
100
1,700
100
40,000
100
100
1,130
135*
77*
900
2,757*
3,000
7,078*
15,049*
7,078*
2,757*
26,497*
10,000
197*
15,049*
131
325
2,700
100
100
100
4,500
7,300
2,800
1,920
2,500
1,700
1,030
18,000
9,100
36,000
2,560
5,862*
Fish
60,000
5
300
100
50
100
64,000
100
100
432
646*
382*
1,549*
10,617*
25,468*
25,468*
51,286*
25,468*
10,617*
86,696*
3,119*
916*
51,286*
200
1,549*
3,119*
700
700
700
6,281
990
13,000
13,000
21,300
66*
3,740
40,800
2,710
12,000
12,000
1,500
Comments
Not available. Default value.
Not available. Default value.
As methyl mercury
Not available. Default value.
* Calculated by following
BCF = 0.76 Log K^ - 0.23.
equations from Lyman et al. (1990): For fish, Log
For invertebrates, Log BCF = 0.819 Log K,,, - 1.146.
57
-------
Table 7.5. Concentrations of contaminants in food organisms used in exposure assessment, in mg/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo< a ) anthracene
Benzo(a)pyrene
Benzo(a)f luoranthene
BenzoCghi )perytene
Benzo(k)f luoranthene
Chrysene
Oibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gaima-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexachlorobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'DOT
(PCBs (total)
FOOD
F
CASE
Typical
CONC
2.00E-02
1 .80E+00
1.45E+00
2.00E-01
1.40E+00
3.00E-02
6.50E-01
3.50E-01
3.00E-02
3.00E-02
3.00E-02
1.00E-01
9.50E-01
1.00E-01
5.00E-02
5.00E-02
2.00E-01
5.00E-02
4.00E-02
4.40E-02
1.00E-02
2.55E+01
Worst
CONC
3.05E+01
2.82E+01
9.50E-01
3.50E-01
1.50E+00
5.50E-02
9.50E-01
3.90E+00
1.90E+00
3.40E-02
4.10E-02
7.80E-02
5.50E+01
G
CASE
Typical
CONC
1.20E+02
1.00E-01
2.70E+00
1 .90E+02
8.00E-01
1.89E+01
1.09E+01
5.00E-01
2.00E-03
1.25E+01
4.88E-01
9.11E-01
1.46E+00
2.54E+00
7.63E-01
1.01E+00
3.10E+00
9.40E-01
7.72E-01
1.55E+00
2.04E+00
1 .92E+00
2.57E-01
8.00E-03
1.10E-02
Worst
CONC
2.40E+02
1.00E-01
3.90E+00
3.76E+02
1.45E+00
4.22E+01
1.66E+01
8.00E-01
2.00E-03
1 .90E+01
3.17E+00
3.73E+00
4.07E+00
7.17E+00
6.16E+00
4.47E+00
9.33E+00
3.39E+00
2.20E+00
1 .38E+01
7.31E+00
2.85E+00
9.78E+00
4.51E+00
8.23E+00
7.43E+00
1.99E-01
1.25E-01
3.15E-02
4.63E-01
3.40E-02
4.10E-02
7.72E-03
1.44E-01 8.00E-01
P
CASE
Typical
CONC
2.00E-01
2.00E+00
9.00E-01
1 .90E+02
1 .60E+00
1 .89E*01
1.70E-02
5.00E-01
2.00E-03
2.90E+00
3.15E-01
8.58E-02
5.74E-02
9.98E-02
1.49E-02
9.52E-02
9.94E-01
1.03E+00
1.51E-02
7.77E+00
1.32E+00
6.15E-01
3.90E+00
Worst
CONC
4.00E-01
2.00E+00
1.30E+00
3.76E+02
2.90E+00
4.22E+01
2.60E-02
8.00E-01
2.00E-03
4.40E+00
4.90E+00
9.77E+00
2.62E+00
6.75E-01
2.42E-01
1.75E-01
1.82E-01
1.33E-01
2.07E-01
1.60E-01
2.34E+00
3.11E+00
1.91E-01
2.26E+01
5.31E+00
2.38E+00
2.84E-01
1.79E-01
2.42E-03
7.02E+00
2.45E-04
4.35E-04
6.44E-04
2.37E-01
U
CASE
Typical
CONC
2.00E-02
2.52E-02
5.10E-04
6.90E-06
1.70E-05
1.40E-05
2.90E-04
1.20E-04
1.30E-04
3.00E-04
1.50E-04
6.90E-05
1.50E-05
1.40E-04
2.00E-06
1.50E-02
1.50E-02
2.00E-02
1.30E-02
1.00E-02
1.00E-02
1.26E-01
Worst
CONC
9.87E-02
5.90E-02
1.64E-03
9.50E-05
3.17E-04
4.50E-04
3.60E-04
7.00E-04
2.10E-04
3.60E-04
1.23E-04
4.30E-04
3.90E-04
2.80E-04
2.70E-04
2.50E-02
1.50E-02
4.00E-02
1.30E-01
7.50E-03
7.50E-03
3.15E-01
3.50E-02
3.45E-02
6.00E-02
2.75E+00
P = phytoplankton, where Ce = Cw * 100 for metals and Ce = Cw * 1,000 for organic chemicals.
W = clams, norms, and mussels (Tables 5.4, 5.5, and 5.8). The highest (most conservative) values were
used. Also the dry weights were used (5 * wet weight).
G = gizzard shad where Ce = Cw * BCFf for each chemical except total PCBs, p.p'DDD, and p.p'DDE where
spottail shiner residues were available (Tables 5.6 and 5.9).
F = fish (Tables 5.6, 5.7, and 5.9 except spottail shiners). Where nuscle tissue values were used, a
factor of 10 was used to approximate whole fish values.
Blank = not detected or no data
58
-------
Table 7.6. Concentrations of contaminants in food consumed by
Subsurface Benthos, mg/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi)perylene
BenzoOOf luoranthene
Chrysene
D i benzo( a , h ) ant h racene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
8.00E+00
1 .20E+02
4.40E+02
2.88E+05
6.30E+01
5.00E+03
3.30E+00
3.00E+02
2.49E+03
1.80E+00
6.10E+00
9.50E+00
1.65E+01
4.50E+00
6.90E+00
1.57E+01
3.30E+00
4.50E+00
3.10E+00
7.70E+00
9.30E+00
4.00E-01
Worst
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
4.30E+01
9.97E+02
1.57E+03
5.55E+05
2.94E+03
7.33E+03
1.71E+01
4.82E+02
8.50E+00
1.20E+04
1.00E+01
1.00E+01
1.50E+01
4.80E+01
4.00E+01
2.90E+01
5.50E+01
2.20E+01
1.50E+01
6.20E+01
3.70E+01
1.00E+01
5.70E+01
9.00E*00
3.10E+01
3.60E+01
4.60E-01
2.90E-01
1.00E-01
7.20E-01
5.00E-02
1.90E-01
1.30E-01
3.80E+01
59
-------
Table 7.7. Concentrations of contaminants in food consumed by
Surface Benthos, mg/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a > f I uoranthene
Benzo(ghi )perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane ( gamma- BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'DOT
PCBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
8.00E+00
1.20E+02
4.40E+02
2.83E+05
6.30E+01
5.00E+03
3.30E+00
3.00E+02
2.49E+03
1 .80E+00
6.10E+00
9.50E+00
1 .65E+01
4.50E+00
6.90E+00
1.57E+01
3.30E+00
4.50E+00
3.10E+00
7.70E+00
9.30E+00
4.00E-01
Worst
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
A.30E+01
9.97E+02
1.57E+03
5.55E+05
2.94E+03
7.33E+03
1.71E+01
4.82E+02
8.50E+00
1.20E+04
1.00E+01
1.00E+01
1.50E+01
4.80E+01
4.00E+01
2.90E+01
5.50E+01
2.20E+01
1.50E+01
6.20E+01
3.70E+01
1.00E+01
5.70E-I-01
9.00E+00
3.10E+01
3.60E+01
4.60E-01
2.90E-01
1.00E-01
7.20E-01
5.00E-02
1.90E-01
1.30E-01
3.80E+01
60
-------
Table 7.8. Concentrations of contaminants in food consumed by
Aufuuchs, mg/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
8enzo( a )anth racene
Benzo(a)pyrene
BenzoC a ) f I uoranthene
Benzo(ghi)perylene
Benzo( k ) f luoranthene
Chrysene
Oibenzo(a,h)anthracene
F luoranthene
Fluorene
I ndenod , 2 , 3 - cd ) py rene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Hi rex
p.p'DDD
p.p'DDE
p.p'DDT
>CBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
8.00E+00
1 .20E+02
4.40E+02
2.88E+05
6.30E+01
5.00E+03
3.30E+00
3.00E+02
2.49E+03
1 .80E+00
6.10E+00
9.50E+00
1 .65E+01
4.50E+00
6.90E+00
1.57E+01
3.30E+00
4.50E+00
3.10E+00
7.70E+00
9.30E+00
4.00E-01
Worst
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
4.30E+01
9.97E+02
1.S7E+03
5.55E+05
2.94E+03
7.33E+03
1.71E+01
4.82E+02
8.50E+00
1.20E+04
1.00E+01
1.00E+01
1.50E+01
4.80E+01
4.00E+01
2.90E+01
5.50E+01
2.20E+01
1.50E+01
6.20E+01
3.70E+01
1.00E+01
5.70E+01
9.00E+00
3.10E+01
3.60E+01
4.60E-01
2.90E-01
1.00E-01
7.20E-01
5.00E-02
1.90E-01
1.30E-01
3.80E+01
61
-------
Table 7.9. Concentrations of contaminants in food consorted by
Zooplankton, nig/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
3enzo( a )anthracene
Benzo(a)pyrene
Benzo( a ) f I uoranthene
BenzoCghi )perylene
BenzoC k ) f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
I ndeno( 1 , 2 , 3 - cd ) py rene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane ( gamma -BHC)
Aldrin
Chlordane
Oieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'ODE
p.p'ODT
PCBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
Dig/kg
2.00E-03
2.00E-02
9.00E-03
1.90E+00
1.60E-02
1.89E-01
1.70E-04
5.00E-03
2.00E-05
2.90E-02
8.05E-02
1.94E-02
1.06E-02
1.84E-02
1.83E-03
1.80E-02
2.49E-01
2.62E-01
1.87E-03
3.00E-01
3.00E-01
1.55E-01
1.00E-01
Worst
Organism
Type
Inverte-
brate
Food Type
Inverte-
brate
Cone.
mg/kg
4.00E-03
2.00E-02
1.30E-02
3.76E+00
2.90E-02
4.22E-01
2.60E-04
8.00E-03
2.00E-05
4.40E-02
1.26E+00
2.51E+00
6.71E-01
1.53E-01
4.46E-02
3.23E-02
2.24E-02
2.45E-02
4.67E-02
1.35E-02
5.87E-01
7.95E-01
2.37E-02
5.81E+00
1.35E+00
5.98E-01
7.30E-02
4.60E-02
5.80E-04
1.81E+00
4.06E-05
2.74E-05
1.08E-04
4.43E-02
62
-------
Table 7.10. Concentrations of contaminants in food consumed by
Brown Bullhead, mg/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
BenzoC a ) anth racene
Benzo(a)pyrene
Benzo(a}f luoranthene
Benzo(ghi )perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DOE
p.p'DDT
PCBs (total)
CASE
Typical
Organism Type
Fish
Food Type
Fish
Cone.
mg/kg
2.00E-02
1.80E+00
1.45E+00
2.00E-01
1.40E+00
3.00E-02
6.50E-01
3.50E-01
3.00E-02
3.00E-02
3.00E-02
1.00E-01
9.50E-01
1.00E-01
5.00E-02
5.00E-02
2.00E-01
5.00E-02
4.00E-02
4.40E-02
1.00E-02
2.55E+01
Inverte-
brate
Cone.
mg/kg
2.00E-02
2.52E-02
5.10E-04
6.90E-06
1.70E-05
1.40E-05
2.90E-04
1.20E-04
1.30E-04
3.00E-04
1.50E-04
6.90E-OS
1.50E-05
1.40E-04
2.00E-06
1.50E-02
1.50E-02
2.00E-02
1.30E-02
1.00E-02
1.00E-02
1.26E-01
Worst
Organism Type
Fish
Food Type
Fish
Cone.
mg/kg
3.05E+01
2.82E+01
9.50E-01
3.50E-01
1.50E+00
5.50E-02
9.50E-01
3.90E+00
1.90E+00
3.40E-02
4.10E-02
7.80E-02
5.50E+01
Inverte-
brate
Cone.
mg/kg
9.87E-02
5.90E-02
1.64E-03
9.50E-05
3.17E-04
4.50E-04
3.60E-04
7.00E-04
2.10E-04
3.60E-04
1.23E-04
4.30E-04
3.90E-04
2.80E-04
2.70E-04
2.50E-02
1.50E-02
4.00E-02
1.30E-01
7.50E-03
7.50E-03
3.15E-01
3.50E-02
3.45E-02
6.00E-02
2.75E+00
63
-------
Table 7.11. Concentrations of contaminants in food consumed by
Carp, mg/kg wet weight.
•
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Si Iver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
Benzo(a)f luoranthene
BenzoCghi )perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indenod ,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (ganroa-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p,p'ODD
p.p'DDE
p.p'ODT
PCBs (total)
CASE
Typical
Organism
Type
Fish
Food Type
Inverte-
brate
Cone.
mg/kg
2.00E-02
2.52E-02
5.10E-04
6.90E-06
1.70E-05
1.40E-05
2.90E-04
1.20E-04
1.30E-04
3.00E-04
1.50E-04
6.90E-05
1.50E-05
1.40E-04
2.00E-06
1.50E-02
1.50E-02
2.00E-02
1.30E-02
1.00E-02
1.00E-02
Worst
Organism
Type
Fish
Food Type
Inverte-
brate
Cone.
mg/kg
9.87E-02
5.90E-02
1.64E-03
9.50E-05
3.17E-04
A.50E-04
3.60E-04
7.00E-04
2.10E-04
3.60E-04
1.23E-04
4.30E-04
3.90E-04
2.80E-04
2.70E-04
2.50E-02
1.50E-02
4.00E-02
1.30E-01
7.50E-03
7.50E-03
3.15E-01
3.50E-02
3.45E-02
6.00E-02
1.26E-01| 2.75E+00
64
-------
Table 7.12. Concentrations of contaminants in food consulted by
Gizzard Shad, mg/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
Benzo( a ) f I uoranthene
Benzo(ghi )perylene
Benzo( k ) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
Indenod ,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
bet a- BMC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dietdrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
Organism
Type
Fish
Food Type
Inverte-
brate
Cone.
mg/kg
2.00E-03
2.00E-02
9.00E-03
1 .90E+00
1.60E-02
1.89E-01
1.70E-04
5.00E-03
2.00E-05
Worst
Organism
Type
Fish
Food Type
Inverte-
brate
Cone.
mg/kg
4.00E-03
2.00E-02
1.30E-02
3.76E+00
2.90E-02
4.22E-01
2.60E-04
8.00E-03
2.00E-05
2.90E-02J 4.40E-02
8.05E-02
1.94E-02
1.06E-02
1.84E-02
1.83E-03
1.80E-02
2.49E-01
2.62E-01
1.87E-03
3.00E-01
3.00E-01
1.55E-01
1.00E-01
1.26E+00
2.51E+00
6.71E-01
1.53E-01
4.46E-02
3.23E-02
2.24E-02
2.45E-02
4.67E-02
1.35E-02
5.87E-01
7.95E-01
2.37E-02
5.81E+00
1 .35E+00
5.98E-01
7.30E-02
4.60E-02
5.80E-04
1.81E+00
4.06E-05
2.74E-05
1.08E-04
4.43E-02
65
-------
Table 7.13. Concentrations of contaminants in food consulted by
Pumpkinseed, ing/kg wet weight.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
Benzo(a)f luoranthene
BenzoCghi )perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
F luorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane ( gamma- BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
Organism Type
Fish
Food Type
Fish
Cone.
mg/kg
1 .20E+02
1.00E-01
2.70E+00
1 .90E+02
8.00E-01
1 .89E+01
1.09E+01
5.00E-01
2.00E-03
1.25E+01
4.88E-01
9.11E-01
1.46E+00
2.54E+00
7.63E-01
1.01E+00
3.10E+00
9.40E-01
7.72E-01
1.55E+00
2. DAEWOO
1.92E+00
2.57E-01
8.00E-03
1.10E-02
1.44E-01
Inverte-
brate
Cone.
mg/kg
1.10E-01
2.00E+00
4.63E-01
1.90E+02
1 .60E+00
1.89E+01
8.76E-03
5.00E-01
2.00E-03
2.90E+00
1.58E-01
4.29E-02
2.87E-02
5.00E-02
7.50E-03
6.50E-05
4.78E-02
7.50E-05
4.97E-01
1.03E+00
7.54E-03
7.77E+00
6.60E-01
3.08E-01
7.50E-03
7.50E-03
1.00E-02
3.90E+00
6.50E-03
5.00E-03
5.00E-03
6.29E-02
Worst
Organism Type
Fish
Food Type
Fish
Cone.
mg/kg
2.40E+02
1.00E-01
3.90E+00
3.76E+02
1.45E+00
4.22E+01
1.66E+01
8.00E-01
2.00E-03
1.90E+01
3.17E+00
3.73E+00
4.07E+00
7.17E+00
6.16E+00
4.47E+00
9.33E+00
3.39E+00
2.20E+00
1 .38E+01
7.31E+00
2.85E+00
9.78E+00
4.51E+00
8.23E+00
7.43E+00
1.99E-01
1.25E-01
3.1SE-02
4.63E-01
3.40E-02
4.10E-02
7.72E-03
8.00E-01
Inverte-
brate
Cone.
mg/kg
2.49E-01
2.00E+00
6.80E-01
3.76E+02
2.90E+00
4.22E+01
1.38E-02
8.00E-01
2.00E-03
4.40E+00
4.90E+00
9.77E+00
1.31E+00
3.38E-01
1.21E-01
8.79E-02
9.13E-02
6.66E-02
1.04E-01
7.99E-02
1.17E+00
3.11E+00
9.55E-02
2.26E+01
2.66E+00
1.19E+00
1.54E-01
9.70E-02
2.00E-02
6.50E-02
2.42E-03
3.75E-03
3.51E+00
1.58E-01
1.76E-02
1.75E-02
3.03E-02
1.49E+00
66
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CHAPTER 8
TOXICITY ASSESSMENT (DOSE-RESPONSE AND EXPOSURE-
RESPONSE)
For aquatic organisms exposed to contaminants in media, exposure-response is
described.
8.1 Aquatic Toxicity Estimates for Chemical Pollutants Present in
Buffalo River Sediments (1985-1989)
8.1.1 Toxicity Estimates for Buffalo River Contaminants
The primary goal for this Buffalo River effort is to provide a baseline risk
assessment for the area caused by the presence of contaminated sediments found
in the river basin. As has been emphasized in previous sections of the
report, a secondary consideration is to improve the capability for a risk
forecast; this can be done using either a minimum number of new biota, water,
sediment, etc. samples or, when data are available, using the previously
collected information. The current Buffalo River assessment uses sampling and
analytical data collected during 1985 and 1989. These data are not as
complete as one would hope, but they do allow for a best available attempt at
the baseline assessment and hopefully for the introduction of some modest
improvements in the risk assessment process. Another basic area of
consideration relates to the validation of risk procedures that assume
"additivity" of risk following exposure to combinations of pollutant compounds
(i.e., if specific toxicity data are not available for the actual mixture).
The validity of this approach should be determined (through experimental
studies) because there are several responses, other than an addition of
separate effects, that can potentially occur. In some specific cases, the
additive approach could be an underestimate of potential hazard. However, the
additive approach can be very expensive in terms of clean-up costs if the
actual effect is not as severe as the additive forecast suggests. See the
generic document for further description and relevant tables for treatment of
the data.
8.1.1.1 Reference Toxicities for Aquatic Organisms—single chemicals
(See Passino-Reader et al. 1992 for tables). To calculate risk to aquatic
biota, standard reference toxicities to aquatic species are needed similar
to the reference doses (RfD) values available for humans. To complete a
set of "reference toxicity" values for compounds in sediments for the
Buffalo River, we established the following priorities. We used interim
sediment quality criteria (SQC) (USEPA 1988b) when available. When SQC
were not available, we used sediment equilibrium partitioning (EP)
thresholds (Long and Morgan 1990). When SQC and EP values were
unavailable, we used water quality criteria values (USEPA 1986; Table
VII.1.1-6 in Passino-Reader et al. 1992) and calculated the corresponding
sediment concentration, using the approach of Burmaster et al.(1991) and
assuming total organic carbon of the sediment equal to 3.25%. Lastly, we
filled in the remaining "sediment reference toxicity" values with, first,
NOAELs or, second, QSARs (Hickey and Passino-Reader 1991), using the
approach of Burmaster et al. (1991) to calculate sediment concentrations.
We have estimated NOAELs from the one data set that we have that includes
most of the chemicals, viz., acute toxicity (Table VI.A.I in Passino-Reader
et al. 1992). To put the acute toxicity data into units comparable to the
67
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exposure data, we converted the toxicity units of ug/L to mg/kg by
multiplying by 1E-03, approximating the density of water by 1.00 g/mL.
This approach also assumes that the toxicity to the organisms by chemicals
in water can be used as an estimate of their total exposure to the same
chemical by all routes. Next we used an application factor (AF) to
calculate NOAEL from acute toxicity. Realizing that application factors
can vary from greater than 1E-01 to less than 1E-02, we used a value of 1E-
01 for the calculation. Thus, NOAEL values in Table VIII.1.1-5 (Passino-
Reader et al. 1992) were calculated from acute toxicity values in Table
VI.A.I (Passino-Reader et al. 1992) with the following equation:
NOAEL (mg/kg) = LC50 Ug/L) x (10'3 mg/ug) x (L/kg) x AF (lO'1)
In selecting acute toxicity data from Table VI.A.I (Passino-Reader et al.
1992), we used Daohnia spp. to represent plankton. The order for selecting
invertebrates to represent benthos and aufwuchs was as follows: Asellus.
Gammarus. and Neanthes. For fish that are primarily in the water column,
the order of priority was: rainbow trout, bluegill, yellow perch, large
mouth bass, fathead minnow, and others. For fish that are primarily or
somewhat in contact with the bottom, the order of priority was: bullhead,
carp, and goldfish. "Reference toxicities" used in our risk assessment are
listed in Table 8.1. The method used to obtain a value for sediment
"reference toxicity" for each chemical is listed in the column labeled
"source" in Table 8.1.
A similar approach was used to obtain water "reference toxicities". We
used USEPA water quality criteria when available (U.S. Environmental
Protection Agency 1986). Otherwise, we calculated a water "reference
toxicity" by the same methods described above for sediment (except that we
did not calculate sediment concentrations). The method used to obtain a
value for each chemical is listed in the column labeled "source" in Table
8.2.
For evaluating the toxicity due to eating contaminants in food, we propose
a new term, "food quality criteria", which would be analogous to the
standard terms, water quality criteria and sediment quality criteria. To
obtain experimentally derived values for food quality criteria, organisms
would need to be dosed by feeding them clean food that has been spiked with
a single chemical. By feeding groups of animals a series of concentrations
or treatments, dose-relationship curves and LC50 values could be obtained.
Such data do exist for a very limited number of contaminants and aquatic
species. The data are too sparse to consider establishing food quality
criteria based on experimental data in a manner similar to which water or
sediment quality criteria have been established. No standard protocols
exist for deriving food quality criteria.
Exposure to contaminated food is a necessary component of aquatic risk
assessment. Therefore, we developed the following method to estimate food
quality criteria for use in the baseline aquatic risk assessment. We
developed a basic equation:
FQC = WQC * BCF
where FQC = food quality criteria, WQC = water quality criteria for the
predator, and BCF = bioconcentration factor for the prey. Three cases
exist for the Buffalo River receptor organisms, i.e., invertebrates preying
upon invertebrates (FQCU), fish preying upon invertebrates (FQCn), and fish
68
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Table 8.1. Reference toxicities for receptors exposed to contaminants by sediment.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a) anthracene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo(k)f luoranthene
Chrysene
Oibenzo(a,h)anthracene
F luoranthene
Fluorene
Indenod ,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'OOD
p.p'DDE
p.p'DDT
PCBs (total)
SOURCE
EP
woe
EP
woe
EP
NOAEL
EP
WQC
WQC
EP
EP
QSAR
EP
SQC
SQC
OSAR
QSAR
QSAR
EP
NOAEL
SQC
NOAEL
QSAR
EP
SQC
SOC
QSAR
QSAR
EP
EP
SOC
WQC
EP
woe
NOAEL
EP
woe
EP
EP
SQC
EP
ORGANISM TYPE
Fish
Cone.
mg/kg
3.10E+01
6.60E+00
1.36E+02
1.50E+04
1 .32E+02
2.50E+03
3.00E-02
9.60E+02
5.00E+00
7.60E+02
6.60E+01
3.39E+01
4.40E+01
A.28E+01
3.45E+01
3.77E+01
2.19E+01
3.77E+01
4.60E+02
1.29E+04
6.12E+01
3.24E+01
5.56E+00
4.20E+01
5.66E+00
4.26E+01
3.25E+00
3.41E+00
1.40E-02
2.10E-02
1.00E-02
1.23E-04
2.32E-02
1.95E-03
2.05E-02
2.80E-01
5.14E-01
1 .30E+01
2.80E+01
2.69E-01
2.80E+02
Inverte-
brate
Cone.
mg/kg
3.10E+01
6.60E+00
1 .36E+02
1.50E*04
1 .32E+02
2.50E+03
3.00E-02
9.60E+02
5.00E+00
7.60E+02
6.60E+01
2.15E+01
4.40E+01
4.28E+01
3.45E+01
5.65E+00
3.91E+00
5.65E+00
4.60E+02
1.29E+04
6.12E+01
3.24E+01
1.29E*00
4.20E+01
5.66E+00
4.26E+01
4.55E-01
4.39E-01
1 .40E-02
2.10E-02
1.00E-02
1.23E-04
2.32E-02
1.95E-03
2.05E-02
2.80E-01
5.14E-01
1.30E+01
2.80E+01
2.69E-01
2.80E+02
EP = equilibrium partitioning
NOAEL = no observed adverse -effect level
QSAR = quantitative structure-activity relationship
SQC = sediment quality criteria
WQC = water quality criteria
69
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Table 8.2. Reference toxicities for receptors exposed to contaminants by water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo( k ) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'DDT
PCBs (total)
SOURCE
UQC
woe
UQC
UQC
UQC
NOAEL
UQC
UQC
UQC
UOC
UQC
QSAR
QSAR
QSAR
QSAR
QSAR
QSAR
QSAR
QSAR
NOAEL
FUAC
NOAEL
QSAR
UQC
NOAEL
NOAEL
QSAR
QSAR
UQC
FUAC
UQC
UQC
UQC
UQC
NOAEL
NOAEL
UQC
NOAEL
NOAEL
NOAEL
UOC
ORGANISM TYPE
Fish
Cone.
mg/L
1.10E-03
1.10E-02
1.20E-02
1 .OOE+00
3.20E-03
9.80E-01
1.20E-05
1.60E-01
1.20E-04
1.10E-01
5.20E-01
3.30E-01
7.30E-02
3.80E-03
9.90E-04
1.60E-03
3.30E-04
1 .60E-03
3.80E-03
1.00E-01
4.00E-01
1.00E-01
8.60E-05
6.20E-01
4.50E+02
2.60E-04
2.00E-02
2.10E-02
6.00E-05
3.00E-04
4.3QE-06
1 .90E-06
2.30E-06
3.80E-06
2.00E-03
1.20E-03
1.00E-06
7.00E-03
3.20E-03
4.80E-04
1.40E-05
Inverte-
brate
Cone.
mg/L
1.10E-03
1.10E-02
1.20E-02
1. OOE+00
3.20E-03
9.80E-01
1.20E-05
1.60E-01
1.20E-04
1.10E-01
5.20E-01
2.10E-01
5.50E-02
6.90E-04
1.80E-04
2.40E-04
5.90E-05
2.40E-04
6.90E-04
1.00E-01
4.00E-01
1.00E-01
2.00E-OS
6.20E-01
6.00E-02
2.60E-04
2.80E-03
2.70E-03
6.00E-OS
3.00E-04
4.30E-06
1 .90E-06
2.30E-06
3.80E-06
2.00E-03
1.20E-03
1.00E-06
1.60E-03
3.20E-03
1.00E-04
1.40E-05
FUAC = fresh water acute criteria
NOAEL = no observed adverse effect level
QSAR = quantitative structure-activity relationship
UQC = water quality criteria
70
-------
preying upon fish (FQCff), where the first subscript refers to the predator
and the second subscript refers to the prey. For the eight receptor
organisms, these cases are shown in Table 7.3 (vehicles of exposure). The
equations for the three cases are as follows:
FQCU = WQC * BCF,
FQCfl = WQC, * BCF,
FQCff = WQCf * BCF,
Values for BCF were obtained from Table 7.4, using the respective values
for invertebrates or fish. The values for WQC were obtained from Table
8.2, using the respective values for invertebrates or fish. Using the
three equations above, the resulting values for FQC are shown in Table 8.3.
8.1.1.2 Reference Toxicities for Aquatic Organisms—Mixtures
To represent reference toxicity values for chemicals present in
environmental mixtures, we obtained values of effects range-low (ER-L) and
effects range-median (ER-M) for sediments (Long and Morgan 1990) and
present these in Table 8.4. These values were obtained from using
environmental samples, and are the concentrations measured in the sediments
at which an effect was seen on aquatic organisms. Presumably, the
additive, synergistic, or antagonist interactions of the contaminants are
accounted for. However, since not all contaminants are measured, the
observed toxicity could be due to a contaminant that was not measured.
8.2 Summation of All Chemicals to which Receptors are Exposed
A summary of the contaminants that have been detected in which kinds of
organisms in the Buffalo River AOC was presented in Table 5.1. Table 5.2
shows all contaminants measured in sediments.
8.3 Identification of Chemicals with No, or Inadequate, Toxicity Data
(See Passino-Reader et al. 1992 for tables.) Sediment quality criteria,
equilibrium partitioning, and water quality criteria were used preferentially.
Examination of Table VIII.1.1-5 of estimated NOAELs (Passino-Reader et al.
1992), based on acute toxicity data, shows the chemicals for which acute data
were lacking to estimate a NOAEL for either a specific part of the foodweb,
i.e., zooplankton, or for any representative aquatic receptor. For aquatic
life risk assessment, NOAELs would be comparable to RfDs used in human health
risk assessment. Acute data were assembled in Table VI.A.I (Passino-Reader et
al. 1992). The lack of general availability of NOAELs for chemicals and
aquatic receptors of interest for risk assessment is due to the great cost of
obtaining these values. Some data are available in the literature on chronic
or subchronic toxicity for chemicals and receptors of interest and could be
used in estimating NOAELs. In Tables 8.1 and 8.2, the compounds with "source"
indicated as QSAR lacked measured toxicity values.
8.4 Identification of lexicological Endpoints to be Assessed
8.4.1 Data for AOC from Toxicity/Chemistry Workgroup of ARCS
Nelson et al. (1992) reported results of toxicity tests with sediment samples
collected from the Buffalo River AOC in 1989. Survival and growth were
observed for the 'following test species and durations of tests: Hyalella
(Amphipoda) with 14- and 28-day flow-through exposures; chironomus
71
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Table 8.3. Reference toxicities for receptors exposed to contaminants by food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a ) f I uoranthene
BenzoCghi )perylene
Benzo(k)f luoranthene
Chrysene
Dibehzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Oieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DOO
p.p'ODE
p.p'DDT
PCBs (total)
ORGANISM TYPE
Fish
FOOD TYPE
Fish
Cone.
mg/kg
6.60E+01
5.50E-02
3.60E+00
1.00E+02
1.60E-01
9.80E+01
7.68E-01
1 .60E+01
1.20E-02
4.75E+01
3.36E+02
1.26E+02
1.13E+02
4.03E+01
2.52E+01
4.07E+01
1 .69E+01
4.07E+01
4.03E+01
8.67E+03
1.25E+03
9.16E+01
4.41E+00
1.24E+02
6.97E+05
8.11E-01
1.40E+01
1.47E+01
Inverte-
brate
Cone.
mg/kg
3.856+00
2.20E+00
2.40E+00
1.00E+02
5.44E+00
9.80E+01
4.80E-01
1.60E+01
1.20E-02
1.24E+02
7.02E+01
2.54E+01
6.57E+01
1.05E+01
2.97E+00
1.13E+01
4.97E+00
1.13E+01
1.05E+01
2.65E+03
4.00E+03
1.97E+01
1.29E+00
8.12E+01
1.46E+05
7.02E-01
2.00E+00
2.10E+00
4.20E-02J 6.00E-03
1 .88E+00
4.26E-03
2.47E-02
2.99E-02
8.09E-02
1.32E-01
4.49E+00
4.08E-02
1 .90E+01
3.8AE+01
5.76E+00
2.10E-02
1.35E+00
3.14E-02
5.32E-03
4.42E-03
9.50E-03
3.40E1-00
1.24E+00
1.80E-02
6.37E+01
1.15E+02
1.23E+00
8.21E-02
Inverte-
brate
FOOD TYPE
Inverte-
brate
Cone.
mg/kg
3.85E+00
2.20E+00
2.40E+00
1.00E+02
5.44E+00
9.80E+01
4.80E-01
1.60E+01
1.20E-02
1.24E+02
7.02E+01
1.62E+01
4.95E+01
1.90E+00
5.40E-01
1.70E+00
8.88E-01
1.70E+00
1.90E+00
2.65E+03
4.00E+03
1.97E+01
3.01E-01
8.12E+01
1.95E+01
7.02E-01
2.80E-01
2.70E-01
6.00E-03
1 .35E+00
3.14E-02
5.32E-03
4.42E-03
9.50E-03
3.40E+00
1.24E+00
1.80E-02
1 .46E+01
1.15E+02
2.56E-01
8.21E-02
72
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riparius (Diptera) with 14-day exposure; and Chironomus tentans with 10-day
static exposure. Antennal segment number and sexual maturation were also
observed for H. azteca. Earlier studies have demonstrated the carcinogenicity
of sediments from the Buffalo River to brown bullhead (Bauman et al. 1982;
Black 1983; Black et al. 1985). Table 8.4 shows effects range values from
Long and Morgan (1990). The Effects Range-Low (ER-L) is defined as the lower
10 percentile of concentrations of chemicals associated with adverse
biological effects. The Effects Range-Median (ER-M) is defined as the median
concentration of a chemical at which biological effects are measured in site-
specific estuarine or marine sediment samples used in bioassays with aquatic
organisms (Long and Morgan 1990). By comparing sediment concentrations at the
Buffalo River AOC with ER-L and ER-M values, we can identify those
contaminants that may pose a risk to aquatic biota at the Buffalo River.
8.5 Summation of All Chemicals to b* Addressed in the Evaluation
All compounds shown in Table 8.1 will be used for the evaluation.
73
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Table 8.4. Effects range-low (ER-L) and effects range-median (ER-M) for
mixtures of chemicals in sediments (Long and Morgan 1990).
Chemical
Cadmium
Chromium (hex)
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo (a) anthracene
Benzo (a) pyrene
Benzo (b) f luoranthene
Benzo (ghi ) perylene
Benzo (k) f luoranthene
Chrysene
Dibenzo (a , h) anthracene
Fluroanthene
Fluorene
Indeno (1,2, 3-cd) pyrene
Naphthalene
Phenanthrene
Pyrene
tt-BHC
B-BHC
Lindane (gamma-EEC)
Aldrin
Dieldrin
Chlordane
Endrin
Heptachlor
Heptachlor epoxide
Hexachlorobenzene
Mi rex
p , p ' ODD
p , p ' DDE
DDT (total)
PCBs (total)
Acute Marine (mg/L)
5.00 E + 00
7.00 E + 01
3.50 Z + 01
1.50 E - 01
3.00 E + 01
1.00 E -I- 00
1.20 E + 02
1.50 E - 01
8.50 E - 02
2.30 E - 01
4.00 £ - 01
4.00 E - 01
6.00 E - 02
6.00 E - 01
3.50 E - 02
3.40 E - 01
2.25 E - 01
3.50 E - 01
2.00 E - 05
5.00 E - 04
2.00 E - 05
2.00 E - 03
2.00 E - 03
3.00 E - 03
Chronic Marine (mg/L)
9.00 E + 00
3.90 E + 02
1.10 E -I- 02
1.30 E + 00
5.00 E + 01
2.20 E + 00
2.70 E + 02
6.50 E - 01
9.60 E - 01
1.60 E + 00
2.50 E -I- 00
2.60 E -I- 00
2.60 E - 01
3.60 E + 00
6.40 E - 01
2.10 E + 00
1.38 E + 00
2.20 E + 00
8.00 E - 03
6.00 E - 03
4.50 E - 02
2.00 E - 02
1.50 E - 02
3.50 E - 01
74
-------
CHAPTER 9
RISK CHARACTERIZATION
The focus of this section is to characterize the risk of adverse aquatic life
health effects due to exposure to contaminants found in the Buffalo River AOC.
The characterization reflects how contaminant levels, species distribution,
and contaminant toxicity combine to result in a risk to aquatic life health.
Within a baseline risk assessment, many data and knowledge gaps exist that
make a numerically accurate determination of risk impossible. Where either
data or knowledge with which to perform a step in the assessment are lacking,
it is necessary to develop assumptions. The purpose of the assumption is to
fill the data gap and allow the assessment process to continue. An important
characteristic of an assumption is that it should be developed with the
overall objective of the work in mind. In the case of a baseline risk
assessment, the objective is to characterize a range related to exposure and
risk that bound the potential risk between likely and worst case. It is
desired that this range reflect an overall conservative approach, that is, the
assessor attempts to estimate the risk in such a manner that it is not
underestimated. Therefore, when the need for an assumption surfaces within
this baseline assessment, a consistent effort was made to fill the data gap in
a 'reasonably conservative1 manner. The important assumptions made within
this baseline assessment are summarized in Chapter 10.
9.1 Individual Chemicals
Risk for noncarcinogenic chemicals was quantified by a hazard quotient (USEPA
1989a), i.e.:
Hazard quotient = Exposure level
Reference dose
For the baseline aquatic risk assessment, we calculated risk as a hazard
quotient (HQ) by dividing the concentration (C)in each medium by the reference
toxicity (QC) for that medium. The three basic equations were as follows:
s SCC
WQC
- FQC
75
-------
where the subscripts s, w, and e refer to sediment, water, and food,
respectively (the letter f had already been used for fish). The values for c
were obtained from Tables 5.2 and 7.6 to 7.13. The values for QC were
obtained from Tables 8.1 to 8.3.
The calculated risk from food is shown for each of the eight receptor
organisms in Tables 9.1 to 9.8. The calculated risk for all media for each
receptor organism and chemical is shown in Tables 9.9 to 9.16. Risk was
summed across all media as in USEPA (1989a); however, risk was not sunmed
across all chemicals because of the unknown contributions of chemicals below
threshold levels of toxic effects (Dr. Rolf Hartung, personal
jnication).
The values for risk from food for each receptor organism (Tables 9.1 to 9.8)
can be examined to determine the relative importance of different foods. Two
of the fish, brown bullhead and pumpkinseed, eat both fish and invertebrates
(Table 7.3). Specifically, the brown bullhead eats worms (W) and fish (F)
food categories from Table 7.2. For the brown bullhead, the calculated risk
from eating fish was consistently higher than the risk' of eating invertebrates
for organic contaminants, but not necessarily for metals (Table 9.5).
However, sufficient data were available to evaluate only three metals.
Contaminant residues (Table 7.10) in fish were generally higher than in
invertebrates for the food of brown bullhead. The food quality criteria
(FQCff) for fish eating fish are generally higher than that for fish eating
invertebrates (FQCfl). The higher FQCfI somewhat dampened the effects of eating
fish with higher residues.
Similarly, for pumpkinseed fish that are eating worms (W), plankton (P), and
gizzard shad (G) food categories, the contaminant residues in the fish were
generally, but not always, higher than in invertebrates. Consequently, the
risk from eating fish was generally higher than the risk from eating
invertebrates. These results are consistent with the concept of
bioaccumulation of contaminants up the food chain and higher risk from eating
food higher in the food chain.
For receptors eating more than one kind of invertebrate, the contribution of
different invertebrates may be compared. Gizzard shad and zooplankton are
eating the plankton (P) food category, whereas carp are eating the worms (W)
category. Table 7.5 shows that residues in the worms (W) category are
generally lower than the plankton (P) category. One would assume worms (W) to
be higher than plankton (P) because the benthic organisms are in contact with
contaminated sediments. The worms category includes available measured
residues for clams, worms, and mussels assembled from Tables 5.4, 5.5, and
5.8. The residues in the plankton category, which are assumed to be
bioconcentrated from the water, were estimated by multiplying the water
concentrations by either 100 for metals or by 1,000 for organics. Either the
available measured values in clams, worms, and mussels are lower than expected
relative to the sediment residues or the factors of 100 and 1,000 may be
overly conservative or possibly the methods for calculating water
concentrations from sediment concentrations overestimate the water
concentrations. The above discussion underscores the importance of having
synoptic, recently collected data on sediment, water, and biota to perform
risk assessment at a site.
By examining the total risk (HQ total) to each receptor from exposure by all
routes (Tables 9.9 to 9.16), the relative importance of different routes may
76
-------
Table 9.1. Risk to Subsurface Benthos from eating contaminated food,
where HQe = total risk from food.
-
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Si Iver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a ) f I uoranthene
BenzoCghi Jperylene
Benzo(lc)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
I ndeno< 1 , 2 , 3 - cd ) pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gaiuna-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p.p'DOD
p.p'DDE
p.p'ODT
PCBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food
Type
Inverte-
brate
HQ
2.1E+00
5.5E+01
1 .8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1 .9E+01
2.0E+01
3.6E-02
3.2E+00
1.8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1.3E+01
1.2E-01
HQe
HQ
2.1E+00
5.5E+01
1.8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1.9E+01
2.0E+01
3.6E-02
3.2E+00
1.8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1.3E+01
1.2E-01
Worst
Organism
Type
Inverte-
brate
Food
Type
Inverte-
brate
HQ
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-Q1
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1 .3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1.9E+02
1.1E-01
1.6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
HQe
HO
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1 .3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1.9E+02
1.1E-01
1.6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
77
-------
Table 9.2. Risk to Surface Benthos from eating contaminated food,
where HOe = total risk from food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a )anth racene
Benzo(a)pyrcne
BenzoC a ) f I uoranthene
Benzo(ghi )perylene
BenzoC k ) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane ( gamma -BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DOD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food
Type
Inverte-
brate
HQ
2.1E+00
5.5E+01
1.8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1.9E+01
2.0E+01
3.6E-02
3.2E+00
1 .8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1.3E+01
1.2E-01
HQe
HQ
2.1E+00
5.SE+01
1 .8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1.9E+01
2.0E+01
3.6E-02
3.2E+00
1.8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1.3E+01
1.2E-01
Worst
Organism
Type
Inverte-
brate
Food
Type
Inverte-
brate
HQ
1.1E+01
4.SE+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1.3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1.9E+02
1.1E-01
1.6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
HOe
HQ
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1.3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
.9E+02
.1E-01
.6E+00
.1E+01
.6E+00
.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
78
-------
Table 9.3.
Risk to Aufuuchs from eating contaminated food,
where HQe * total risk from food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a )anthracene
Benzo(a)pyrene
BenzoC a ) f I uoranthene
Benzo(ghi )perylene
BenzoC k ) f I uoranthene
Chrysene
D < benzo( a , h ) anthracene
F I uoranthene
Fluorene
I ndeno< 1 , 2 , 3 - cd ) py rene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Ltndane ( gamma- BHC)
Aldrin
Chlordane
Oieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Hi rex
p.p'ODD
p.p'DDE
p.p'ODT
PCBs (total)
CASE
Typical
Organism
Type
Inverte-
brate
Food
Type
Inverte-
brate
HQ
2.1E+00
5.5E+01
1 -8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1.9E+01
2.0E+01
3.6E-02
3.2E+00
1.8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1.3E+01
1.2E-01
HQe
HO
2.1E+00
5.5E+01
1 .8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1.9E+01
2.0E+01
3.6E-02
3.2E+00
1.8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1.3E+01
1.2E-01
.
Worst
Organism
Type
Inverte-
brate
Food
Type
Inverte-
brate
HO
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1.3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1.9E+02
1.1E-01
1.6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
A.6E+02
HQe
HQ
1.1E+01
A.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1.3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1 .9E+02
1.1E-01
1.6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
79
-------
Table 9.4. Risk to Zooplankton from eating contaminated food,
where HQe = total risk from food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Si Iver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a ) f I uorant hene
BenzoCghi )perylene
BenzoC k ) f luoranthene
Chrysene
Oibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindanc
-------
Table 9.5.
Risk to Brown Bullhead from eating contaminated food,
where HQe = total risk from food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
BenzoC a )anth racene
Benzo(a)pyrene
Benzo(a)f I uoranthene
Benzo(ghi )perylene
Benzo(k)f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
Fluoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
atpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DDE
p.p'OOT
PCBs (total)
CASE
Typical
Organism Type
Fish
Food Type
Fish
HO
3.0E-04
5.0E-01
1.9E+00
1.8E-03
8.3E-02
7.4E-04
5.2E-04
5.0E-07
2.1E-03
2.0E-03
7.1E-01
5.3E-02
2.2E+02
4.0E+00
6.2E-01
3.8E-01
4.5E-02
1.2E+00
2.1E-03
1.1E-03
1.7E-03
1.2E+03
Inverte-
brate
HQ
5.2E-03
1.1E-02
1.1E-03
1.1E-07
1.6E-06
4.7E-06
2.6E-05
2.4E-05
1.1E-05
2.9E-05
5.7E-08
1.7E-08
1.2E-05
9.6E-10
2.8E-06
7.5E-03
2.5E+00
6.4E-01
1.1E-02
8.7E-05
8.1E-03
1.5E+00
HQe
HQ
2.8E-03
2.6E-01
9.5E-01
9.0E-04
1.6E-06
4.7E-06
2.6E-05
4.2E-02
3.8E-04
2.9E-05
5.7E-08
2.6E-04
1.2E-05
2.5E-07
2.8E-06
4.8E-03
2.0E-03
1.6E+00
5.3E-02
1.1E+02
4.0E+00
6.2E-01
3.8E-01
2.8E-02
1.2E+00
2.1E-03
5.9E-04
4.9E-03
6.0E+02
Worst
Organism Type
Fish
Food Type
Fish
HO
8.5E+00
3.7E+01
8.4E-03
8.6E-03
8.9E-02
1.3E-03
7.6E-04
5.6E-06
4.2E-01
1.8E-03
1.1E-03
1.4E-02
2.6E+03
Inverte-
brate
HQ
2.6E-02
2.5E-02
3.4E-03
1.4E-06
3.0E-05
1.5E-04
3.2E-05
1.4E-04
1.9E-05
3.4E-05
4.6E-08
1.1E-07
3.0E-04
1.9E-09
3.8E-04
1.3E-02
7.1E-03
6.7E+00
4.1E+00
7.9E-01
2.2E-03
2.5E-01
5.5E-04
3.0E-04
4.9E-02
3.3E+01
HQe
HQ
2.6E-02
4.3E+00
1.9E+01
4.2E-03
3.0E-05
1.5E-04
4.3E-03
4.5E-02
6.6E-04
3.4E-05
4.6E-08
3.8E-04
3.0E-04
2.8E-06
3.8E-04
1.3E-02
7.1E-03
6.7E+00
4.1E+00
7.9E-01
2.2E-03
3.4E-01
1.2E-03
7.0E-04
3.2E-02
1.3E+03|
81
-------
Table 9.6. Risk to Carp from eating contaminated food,
where HOe = total risk from food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
Benzo( a ) f I uoranthene
Benzo(ghi )perylene
Benzo( k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
p.p'DDD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
Organism
Type
Fish
Food
Type
Inverte-
brate
HQ
5.2E-03
1.1E-02
1.1E-03
1.1E-07
1.6E-06
4.7E-06
2.6E-OS
2.4E-05
1.1E-05
2.9E-05
5.7E-08
1.7E-08
1.2E-05
9.6E-10
2.8E-06
7.5E-03
2.5E+00
6.4E-01
1.1E-02
8.7E-05
8.1E-03
1.5E+00
HOe
HQ
5.2E-03
1.1E-02
1.1E-03
1.1E-07
1.6E-06
4.7E-06
2.6E-OS
2.4E-05
1.1E-05
2.9E-05
5.7E-08
1.7E-08
1.2E-05
9.6E-10
2.8E-06
7.5E-03
2.5E+00
6.4E-01
1.1E-02
8.7E-05
8.1E-03
1.5E+00
Worst
Organism)
Type
Fish
Food
Type
Inverte-
brate
HQ
2.6E-02
2.5E-02
3.4E-03
1.4E-06
3.0E-05
1.5E-04
3.2E-05
1 .4E-04
1.9E-05
3.4E-05
4.6E-08
1.1E-07
3.0E-04
1.9E-09
3.8E-04
1.3E-02
7.1E-03
6.7E+00
4.1E+00
7.9E-01
2.2E-03
2.5E-01
5.5E-04
3.0E-04
4.9E-02
3.3E+01
HOe
HQ
2.6E-02
2.5E-02
3.4E-03
1.4E-06
3.0E-05
1.5E-04
3.2E-05
1.4E-04
1.9E-05
3.4E-05
4.6E-08
1.1E-07
3.0E-04
1.9E-09
3.8E-04
1.3E-02
7.1E-03
6.7E+00
4.1E+00
7.9E-01
2.2E-03
2.5E-01
5.5E-04
3.0E-04
4.9E-02
3.3E+01
' 82
-------
Table 9.7. Risk to Gizzard Shad from eating contaminated food,
where HOe - total risk from food.
CHEMICAL
Cadmiun
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo( k) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gainma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p.p'DOD
p.p'ODE
p.p'DDT
PCBS (total)
CASE
Typical
Organism
Type
Fish
Food
Type
Inverte-
brate
HQ
5.2E-04
9.1E-03
3.8E-03
1.9E-02
2.9E-03
1.9E-03
3.5E-04
3.1E-04
1.7E-03
2.3E-04
1.2E-03
1.9E-03
3.6E-03
1 .6E-03
3.7E-04
1.7E-03
6.2E-05
1.3E-02
1.4E-03
3.7E-03
2.1E-06
2.2E-01
2.9E-02
HQe
HQ
5.2E-04
9.1E-03
3.8E-03
1.9E-02
2.9E-03
1.9E-03
3.5E-04
3.1E-04
1.7E-03
2.3E-04
1.2E-03
1.9E-03
3.6E-03
1 .6E-03
3.7E-04
1.7E-03
6.2E-05
1.3E-02
1.4E-03
3.7E-03
2.1E-06
2.2E-01
2.9E-02
Worst
Organism
Type
Fish
Food
Type
Inverte-
brate
HO
1.0E-03
9.1E-03
5.4E-03
3.8E-02
5.3E-03
4.3E-03
5.4E-04
5.0E-04
1.7E-03
3.5E-04
1.8E-02
9.9E-02
1.0E-02
1.5E-02
1.5E-02
2.9E-03
4.5E-03
2.2E-03
4.5E-03
5.1E-06
1.5E-04
4.0E-02
1.8E-02
7.2E-02
9.2E-06
8.5E-01
3.7E-02
2.2E-02
1.3E-01
5.3E-01
6.4E-07
2.4E-07
8.8E-05
5.4E-01
HOe
HQ
1.0E-03
9.1E-03
5.4E-03
3.8E-02
5.3E-03
4.3E-03
5.4E-04
5.0E-04
1.7E-03
3.5E-04
1.8E-02
9.9E-02
1.0E-02
1.5E-02
1.5E-02
2.9E-03
4.5E-03
2.2E-03
4.5E-03
5.1E-06
1.5E-04
4.0E-02
1.8E-02
7.2E-02
9.2E-06
8.5E-01
3.7E-02
2.2E-02
1.3E-01
5.3E-01
6.4E-07
2.4E-07
8.8E-05
5.4E-01
83
-------
Table 9.8.
Risk to Pumpkinseed from eating contaminated food,
where HQe = total risk from food.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a )anthracene
Benzo(a)pyrene
BenzoC a ) f I uoranthene
BenzoCghi )perylene
BenzoC k > f I uoranthene
Chrysene
OibenzoCa,h)anthracene
F I uoranthene
Fluorene
IndenoC1,2.3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach 1 orobenzene
Mi rex
p.p'DOD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
Organism Type
Fish
Food Type
-Fish
HQ
1.8E+00
1.8E+00
7.5E-01
1 .9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
4.3E-03
2.3E-02
5.8E-02
6.2E-02
4.5E-02
2.5E-02
2.5E-03
1.0E-02
1.8E-01
1.3E-02
2.9E-06
2.4E+00
2.0E+00
4.2E-04
2.9E-04
6.9E+00
Inverte-
brate
HQ
2.9E-02
9.1E-01
1.9E-01
1 .9E+00
2.9E-01
1.9E-01
1.8E-02
3.1E-02
1.7E-01
2.3E-02
2.4E-03
4.1E-03
9.7E-03
4.4E-03
1.5E-03
5.7E-06
4.6E-03
2.8E-08
1.2E-04
5.2E-02
5.8E-03
9.6E-02
4.5E-06
4.4E-01
3.8E-03
1.3E+00
3.2E-01
1.1E+00
5.3E-03
4.3E-05
4.1E-03
7.7E-01
HQe
HQ
9.1E-01
1.4E+00
4.7E-01
1 -9E+00
2.6E+00
1.9E-01
7.0E+00
3.1E-02
1.7E-01
1.4E-01
3.4E-03
1.4E-02
3.4E-02
3.3E-02
2.3E-02
5.7E-06
1.5E-02
2.8E-08
1.3E-03
3.1E-02
9.3E-02
5.5E-02
3.7E-06
1.4E+00
3.8E-03
1.3E+00
3.2E-01
1.6E+00
5.3E-03
4.2E-04
1.7E-04
4.1E-03
3.8E+00
Worst
Organism Type
Fish
Food Type
Fish
HQ
3.6E+00
1.8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
3.0E-02
3.6E-02
1.8E-01
2.4E-01
1.1E-01
5.5E-01
8.3E-02
5.4E-02
1.6E-03
5.9E-03
3.1E-02
2.2E+00
3.6E-02
1.2E-05
9.2E+00
1.4E-02
8.5E-03
1.1E+00
3.5E+00
1.SE-03
1.1E-03
1.3E-03
Inverte-
brate
HQ
6.5E-02
9.1E-01
2.8E-01
3.8E+00
5.3E-01
4.3E-01
2.9E-02
5.0E-02
1.7E-01
3.5E-02
7.0E-02
3.8E-01
2.0E-02
3.2E-02
4.1E-02
7.8E-03
1.8E-02
5.9E-03
9.9E-03
3.0E-05
2.9E-04
1.6E-01
7.4E-02
2.8E-01
1 .8E-OS
1.7E+00
7.7E-02
4.6E-02
3.3E+00
2.1E+00
5.5E-01
3.9E-01
1.0E+00
1.3E-01
2.8E-04
1.5E-04
2.5E-02
HQe
HQ
1.8E+00
1.4E+00
6.9E-01
3.8E+00
4.8E+00
4.3E-01
1.1E+01
5.0E-02
1.7E-01
2.2E-01
4.0E-02
2.1E-01
2.8E-02
1.1E-01
1.4E-01
5.9E-02
2.8E-01
4.4E-02
3.2E-02
8.2E-04
3.1E-03
9.6E-02
1.1E+00
1.6E-01
1.5E-05
5.5E+00
4.6E-02
2.7E-02
3.3E+00
2.1E+00
8.3E-01
3.9E-01
2.3E+00
1.3E-01
1.0E-03
6.3E-04
1.3E-02
3.8E+01 1.8E+01| 2.8E+01
84
-------
Table 9.9. Risk to Subsurface Benthos from exposure to each medium and total risk,
where HQe = food, HOs = sediment, and HQu = water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anthracene
Benzo(a)pyrene
BenzoC a ) f I uoranthene
BenzoCghi )perylene
BenzoC k ) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
Indenod ,2, 3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamna-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p.p'DOD
p.p'ODE
p.p'DOT
PCBs (total)
CASE
Typical
VEHICLE
HQe
RISK
2.1E+00
5.5E+01
1 .8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1 .9E+01
2.0E+01
3.6E-02
3.2E+00
1.8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1 .3E+01
1.2E-01
HOs
RISK
2.6E-02
1.8E+00
3.2E-01
1.9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.8E-02
2.9E-01
1.1E-01
1.5E-03
2.6E-02
1.0E-02
3.5E-01
7.4E-03
1.4E-01
2.2E-02
1.9E+00
HO Total
RISK
2.1 £+00
5.7E+01
1 .8E+02
2.9E+03
1.2E+01
5.1E+01
1.8E+01
1.9E+01
2.0E+01
4.0E-02
3.2E+00
1.8E+01
1.0E+01
5.2E+00
3.6E+00
3.0E-02
1.8E-01
1.5E+01
4.5E-02
5.3E-01
1 .3E+01
2.0E+00
Worst
VEHICLE
HQe
RISK
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E*01
1.7E+01
6.2E+01
1.3E+01
7.9E*00
2.3E-02
9.3E-03
5.1E-01
1.9E+02
1.1E-01
1.6E+00
5.1Ef01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
HQs
RISK
1.4E-01
1.5E+01
1.2E+00
3.7E+00
2.2E+00
2.9E-01
5.7E+01
5.0E-02
1.7E-01
1.6E+00
1.5E-02
4.6E-02
3.4E-02
1.1E-01
1.2E-01
5.1E-01
1 .4E+00
3.9E-01
3.3E-03
4.8E-04
6.0E-02
3.1E-02
4.4E+00
2.1E-02
5.5E-01
8.5E-02
1.0E-01
6.6E-02
4.3E-01
3.5E+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HO Total
RISK
1.1E+01
4.7E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
9.3E+01
3.0E+01
7.1E+02
9.9E+01
1.6E-01
6.7E-01
3.3E-01
2.5E+01
7.4E+01
1.8E+01
6.3E+01
1 .3E+01
7.9E+00
2.3E-02
6.9E-02
5.4E-01
1.9E+02
1.3E-01
2.2E+00
5.1E+01
1.7E+00
1.2E+00
2.3E+01
3.7E+00
3.8E-03
2.3E-03
5.6E-01
4.6E+02
'85
-------
Table 9.10. Risk to Surface Benthos from exposure to each medium and total risk,
where HQe * food, HOs * sediment, and HQu = water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo( k ) f I uoranthene
Chrysene
Oibenzo(a,h)anthracene
F luoranthene
Fluorene
Indenod ,2, 3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p.p'DOD
p.p'DOE
p.p'DDT
PCBs (total)
CASE
Typical
VEHICLE
HQe
RISK
2.1E+00
5.5E+01
1 -8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1 .9E+01
2.0E+01
3.6E-02
3.2E+00
1 .8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1 .5E+01
3.8E-02
3.9E-01
1 .3E+01
1.2E-01
HQs
RISK
2.6E-02
1.8E+00
3.2E-01
1.9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.8E-02
2.9E-01
1.1E-01
1.5E-03
2.6E-02
1.0E-02
3.5E-01
7.4E-03
1.4E-01
2.2E-02
1.9E+00
HQu
RISK
1 .8E+00
1 -8E+00
7.5E-01
1 .9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
5.7E-03
1.2E-01
3.2E-01
4.2E-01
2.5E-01
1.4E-01
2.5E-03
1.0E-02
7.5E-01
1.3E-02
2.2E-02
2.4E+00
2.0E+00
HO Total
RISK
3.9E+00
5.9E+01
1 .8E+02
2.9E+03
1.7E+01
5.1E+01
3.2E+01
1.9E+01
1.7E-01
2.1E+01
4.6E-02
3.3E+00
1.8E+01
1.0E+01
5.5E+00
3.7E+00
3.2E-02
1.9E-01
1 .6E+01
5.8E-02
5.5E-01
1.5E+01
4.0E+00
Worst
VEHICLE
HQe
RISK
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1.3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1 .9E+02
1.1E-01
1 -6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E+02
HOs
RISK
1.4E-01
1.5E+01
1.2E+00
3.7E+00
2.2E+00
2.9E-01
5.7E+01
5.0E-02
1.7E-01
1.6E+00
1.5E-02
4.6E-02
3.4E-02
1.1E-01
1.2E-01
5.1E-01
1 .4E+00
3.9E-01
3.3E-03
4.8E-04
6.0E-02
3.1E-02
4.4E+00
2.1E-02
5.5E-01
8.5E-02
1.0E-01
6.6E-02
4.3E-01
3.5E+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HQw
RISK
3.6E+00
1.8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
4.7E-02
4.8E-02
9.8E-01
1 .3E+00
7.3E-01
3.1E+00
5.5E-01
3.0E-01
1.6E-03
5.9E-03
3.1E-02
9.5E+00
3.6E-02
8.9E-02
9.2E+00
1.0E-01
6.6E-02
1.1E+00
3.5E+00
1.5E-04
1.4E-04
6.4E-03
1.7E+01
HQ Total
RISK
1.5E+01
4.7E+02
6.5E+02
5.6E+03
5.5E+02
7.6E+01
1.2E+02
3.0E+01
7.1E+02
9.9E+01
1.6E-01
7.1E-01
3.8E-01
2.6E+01
7.5E+01
1.8E+01
6.7E+01
1.4E+01
8.2E+00
2.5E-02
7.5E-02
5.7E-01
2.0E+02
1.7E-01
2.2E+00
6.0E+01
1 .8E+00
1.2E+00
2.5E+01
7.2E+00
3.9E-03
2.4E-03
5.6E-01
4.8E+02
36
-------
Table 9.11. Risk to Aufuuchs from exposure to each medium and total risk,
where HQe « food, HQs = sediment, and HOu = water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
8enzo( a ) f I uoranthene
Benzo(ghi )perylene
Benzo( k ) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
tndenod ,2, 3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Oieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexachlorobenzene
Mi rex
p.p'DOD
p.p'DDE
p.p'DDT
PCBs (total)
CASE
Typical
VEHICLE
HQe
RISK
2.1E+00
5.5E+01
1 .8E+02
2.9E+03
1.2E+01
5.1E+01
6.9E+00
1 .9E+01
2.0E+01
3.6E-02
3.2E+00
1 .8E+01
9.7E+00
5.1E+00
3.6E+00
3.9E-03
1.7E-01
1.5E+01
3.8E-02
3.9E-01
1 .3E+01
1.2E-01
HQs
RISK
2.6E-02
1.BE+00
3.2E-01
1.9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.8E-02
2.9E-01
1.1E-01
1.5E-03
2.6E-02
1.0E-02
3.5E-01
7.4E-03
1.4E-01
2.2E-02
1.9E+00
HQw
RISK
1.8E+00
1 .8E+00
7.5E-01
1.9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
5.7E-03
1.2E-01
3.2E-01
4.2E-01
2.5E-01
1.4E-01
2.5E-03
1.0E-02
7.5E-01
1.3E-02
2.2E-02
2.4E+00
2.0E+00
HQ Total
RISK
3.9E+00
5.9E+01
1 .8E+02
2.9E+03
1.7E+01
5.1E+01
3.2E+01
1.9E+01
1.7E-01
2.1E+01
4.6E-02
3.3E+00
1 .8E+01
1.0E+01
5.5E+00
3.7E+00
3.2E-02
1.9E-01
1.6E+01
5.8E-02
5.5E-01
1.5E-KJ1
4.0E+00
Worst
VEHICLE
HQe
RISK
1.1E+01
4.5E+02
6.5E+02
5.6E+03
5.4E+02
7.5E+01
3.6E+01
3.0E+01
7.1E+02
9.7E+01
1.4E-01
6.2E-01
3.0E-01
2.5E+01
7.4E+01
1.7E+01
6.2E+01
1.3E+01
7.9E+00
2.3E-02
9.3E-03
5.1E-01
1 .9E+02
1.1E-01
1.6E+00
5.1E+01
1.6E+00
1.1E+00
2.3E+01
2.1E-01
3.4E-03
1.6E-03
5.1E-01
4.6E-*-02
HQs
RISK
1.4E-01
1.5E+01
1.2E+00
3.7E+00
2.2E+00
2.9E-01
5.7E+01
5.0E-02
1.7E-01
1 .6E+00
1.5E-02
4.6E-02
3.4E-02
1.1E-01
1.2E-01
5.1E-01
1.4E+00
3.9E-01
3.3E-03
4.8E-04
6.0E-02
3.1E-02
4.4E+00
2.1E-02
5.5E-01
8.5E-02
1.0E-01
6.6E-02
4.3E-01
3.5E+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HQw
RISK
3.6E+00
1.8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
4.7E-02
4.8E-02
9.8E-01
1 .3E+00
7.3E-01
3.1E+00
5.5E-01
3.0E-01
1.6E-03
5.9E-03
3.1E-02
9.5E+00
3.6E-02
8.9E-02
9.2E+00
1.0E-01
6.6E-02
1.1E+00
3.5E+00
1.5E-04
1.4E-04
6.4E-03
1.7E+01
HQ Total
RISK
1.5E+01
4.7E-t-02
6.5E+02
5.6E+03
5.5E+02
7.6E+01
1 .2E+02
3.0E+01
7.1E+02
9.9E+01
1.6E-01
7.1E-01
3.8E-01
2.6E+01
7.5E+01
1.8E+01
6.7E+01
1.4E+01
8.2E+00
2.5E-02
7.5E-02
5.7E-01
2.0E+02
1.7E-01
2.2E+00
6.0E+01
1.8E+00
1.2E+00
2.5E+01
7.2E+00
3.9E-03
2.4E-03
5.6E-01
4.8E+02]
37
-------
Table 9.12. Risk to Zooplankton from exposure to each mediun and total risk,
where HQe * food, HQs = sediment, and HOw = water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo(k)f luoranthene
Chrysene
0 i benzo( a , h ) anth racene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p.p'DDD
p.p'DOE
p.p'DDT
PCBs (total)
CASE
Typical
VEHICLE
HQe
RISK
5.2E-04
9.1E-03
3.8E-03
1.9E-02
2.9E-03
1.9E-03
3.5E-04
3.1E-04
1.7E-03
2.3E-04
1.6E-03
1.0E-02
2.0E-02
1.1E-02
2.1E-03
9.5E-03
6.2E-05
1.3E-02
6.2E-03
3.7E-03
1.5E-02
2.2E-01
2.9E-02
HQs
RISK
2.6E-02
1.8E+00
3.2E-01
1.9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.SE-02
2.9E-01
1.1E-01
1.5E-03
2.6E-02
1.0E-02
3.5E-01
7.4E-03
1.4E-01
2.2E-02
1 .9E+00
HQu
RISK
1.8E+00
1.8E+00
7.5E-01
1 .9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
5.7E-03
1.2E-01
3.2E-01
4.2E-01
2.5E-01
1.4E-01
2.5E-03
1.0E-02
7.5E-01
1.3E-02
2.2E-02
2.4E+00
2.0E+00
HO Total
RISK
1.8E+00
3.6E+00
1.1E+00
3.8E+00
5.1E+00
3.9E-01
2.5E+01
6.2E-02
1.7E-01
5.9E-01
1.1E-02
1.4E-01
3.7E-01
7.2E-01
3.6E-01
1.5E-01
2.9E-02
3.3E-02
1.1E+00
2.4E-02
1.8E-01
2.6E+00
3.9E+00
Worst
VEHICLE
HQe
RISK
1.0E-03
9.1E-03
5.4E-03
3.8E-02
5.3E-03
4.3E-03
5.4E-04
5.0E-04
1.7E-03
3.5E-04
1.8E-02
1.6E-01
1.4E-02
8.0E-02
8.3E-02
1.9E-02
2.5E-02
1.4E-02
2.5E-02
5.1E-06
1.5E-04
4.0E-02
7.9E-02
7.2E-02
6.9E-02
8.5E-01
2.6E-01
1.7E-01
1.3E-01
5.3E-01
2.8E-06
2.4E-07
4.2E-04
5.4E-01
HQs
RISK
1.4E-01
1.5E+01
1.2E+00
3.7E*00
2.2E+00
2.9E-01
5.7E+01
5.0E-02
1.7E-01
1 .6E+00
1.5E-02
4.6E-02
3.4E-02
1.1E-01
1.2E-01
5.1E-01
1.4E+00
3.9E-01
3.3E-03
4.8E-04
6.0E-02
3.1E-02
4.4E+00
2.1E-02
5.5E-01
8.5E-02
1.0E-01
6.6E-02
4.3E-01
3.5E+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HQu
RISK
3.6E+00
1 .8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
4.7E-02
4.8E-02
9.8E-01
1 .3E+00
7.3E-01
3.1E+00
5.5E-01
3.0E-01
1.6E-03
5.9E-03
3.1E-02
9.5E+00
3.6E-02
8.9E-02
9.2E+00
1.0E-01
6.6E-02
1.1E+00
3.5E+00
1.5E-04
1.4E-04
6.4E-03
1.7E+01
HQ Total
RISK
3.7E+00
1.7E+01
2.3E+00
7.5E+00
1.1E+01
7.2E-01
7.9E+01
1.0E-01
3.4E-01
2.0E+00
4.2E-02
2.5E-01
9.6E-02
1.2E+00
1.5E+00
1 .3E+00
4.5E+00
9.5E-01
3.3E-01
2.1E-03
6.6E-02
1.0E-01
1.4E+01
1.3E-01
7.1E-01
1.0E+01
4.6E-01
3.0E-01
1.7E+00
7.5E+00
5.3E-04
8.2E-04
5.5E-02
1.8E+01
88
-------
Table 9.13. Risk to Brown Bullhead from exposure to each medium and total risk,
where HQe * food, HQs » sediment, and HOw « water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a}pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo( k) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indenod ,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (ganma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexachlorobenzene
Mi rex
p.p'DDD
p.p'DDE
p,p'DDT
PCBs (total)
CASE
Typical
VEHICLE
HQe
RISK
2.7E-03
2.6E-01
9.4E-01
8.8E-04
1.6E-06
4.7E-06
2.6E-05
4.1E-02
3.7E-04
2.9E-05
5.7E-08
2.6E-04
1.2E-05
2.5E-07
2.8E-06
4.8E-03
2.0E-03
1.6E+00
5.3E-02
1.1E+02
4.0E+00
6.2E-01
3.8E-01
2.8E-02
1.2E+00
2.1E-03
6.2E-04
4.9E-03
6.1E+OZ
HQs
RISK
2.6E-02
1 .8E+00
3.2E-01
1 .9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.8E-02
4.4E-02
2.1E-02
1.5E-03
2.6E-02
1.0E-02
8.1E-02
7.4E-03
1.4E-01
2.2E-02
1.9E+00
HQw
RISK
1.8E+00
1 .8E+00
7.5E-01
1 .9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
4.3E-03
2.3E-02
5.8E-02
6.2E-02
4.SE-02
2.5E-02
2.5E-03
1.0E-02
1.8E-01
1.3E-02
2.9E-06
2.4E+00
2.0E+00
HO Total
RISK
1 .8E+00
3.6E+00
1 .3E+00
3.8E+00
5.0E+00
3.9E-01
2.6E+01
6.2E-02
1.7E-01
5.9E-01
9.3E-03
3.7E-02
8.6E-02
1.1E-01
1.1E-01
3.7E-04
2.7E-02
5.7E-08
2.9E-02
2.0E-02
2.6E-01
2.0E-02
1.4E-01
2.4E+00
4.8E-03
2.0E-03
1 .6E+00
5.3E-02
1.1E+02
4.0E+00
6.2E-01
4.3E+00
2.8E-02
1.2E+00
2.1E-03
6.2E-04
4.9E-03
6.1E+02
Worst
VEHICLE
HQe
RISK
2.6E-02
4.2E+00
1 .8E+01
4.2E-03
3.0E-05
1.5E-04
4.3E-03
4.4E-02
6.8E-04
3.4E-05
4.6E-08
3.8E-04
3.0E-04
2.8E-06
3.8E-04
1.3E-02
7.1E-03
6.7E+00
4.1E+00
7.9E-01
2.2E-03
3.4E-01
1.2E-03
6.8E-04
3.1E-02
1.3E+03
HQs
RISK
1.4E-01
1.5E+01
1.2E+00
3.7E+00
2.2E+00
2.9E-01
5.7E+01
S.OE-02
1.7E-01
1.6E+00
1.5E-02
3.0E-02
3.4E-02
1.1E-01
1.2E-01
7.7E-02
2.5E-01
5.8E-02
3.3E-03
4.8E-04
6.0E-02
3.1E-02
1.0E+00
2.1E-02
5.5E-01
8.5E-02
1.4E-02
8.5E-03
4.3E-01
3.5E+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HQw
RISK
3.6E+00
1.8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
3.0E-02
3.6E-02
1.8E-01
2.4E-01
1.1E-01
5.5E-01
8.3E-02
S.4E-02
1 .6E-03
5.9E-03
3.1E-02
2.2E+00
3.6E-02
1.2E-05
9.2E+00
1.4E-02
8.5E-03
1.1E+00
3.5E+00
3.5E-05
1.4E-04
1.3E-03
1.7E+01
HQ Total
RISK
3.8E+00
1.7E+01
6.5E+00
7.5E+00
1.1E+01
7.2E-01
9.7E+01
1.0E-01
3.4E-01
2.0E+00
2.4E-02
6.0E-02
7.4E-02
2.9E-01
3.6E-01
1.9E-01
8.4E-01
1.4E-01
5.7E-02
2.1E-03
6.6E-02
6.2E-02
3.2E+00
5.7E-02
5.5E-01
9.3E+00
4.1E-02
2.4E-02
6.7E+00
4.1E+00
1.5E+00
7.9E-01
7.0E+00
3.4E-01
1.6E-03
1.5E-03
8.0E-02
1.3E+03
89
-------
Table 9.14. Risk to Carp from exposure to each medium and total risk,
where HOe = food, HOs = sediment, and HQw * water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo( a ) f I uoranthene
Benzo(ghi )perylene
Benzo(k)f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
tndeno( 1 ,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (ganroa-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach lorobenzene
Mi rex
p,p'DDD
p.p'DDE
p.p'OOT
PCBS (total)
CASE
Typical
VEHICLE
HQe
RISK
S.2E-03
1.1E-02
1.1E-03
1.1E-07
1.6E-06
4.7E-06
2.6E-05
2.4E-OS
1.1E-05
2.9E-05
5.7E-08
1.7E-08
1 .2E-05
9.6E-10
2.8E-06
7.5E-03
2.5E+00
6.4E-01
1.1E-02
8.7E-05
8.1E-03
1.5E+00
HQs
RISK
2.6E-02
1 .8E+00
3.2E-01
1.9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.8E-02
4.4E-02
2.1E-02
1.5E-03
2.6E-02
1.0E-02
8.1E-02
7.4E-03
1.4E-01
2.2E-02
1.9E+00
HQw
RISK
1.8E+00
1 .8E+00
7.5E-01
1.9E+00
5.0E+00
1.9E-01
1 .4E+01
3.1E-02
1.7E-01
2.6E-01
4.3E-03
2.3E-02
5.8E-02
6.2E-02
4.5E-02
2.5E-02
2.5E-03
1.0E-02
1.8E-01
1.3E-02
2.9E-06
2.4E+00
2.0E+00
HO Total
RISK
1 .8E+00
3.6E+00
1.1E+00
3.8E+00
5.0E+00
3.9E-01
2.5E+01
6.2E-02
1.7E-01
5.9E-01
8.4E-03
3.7E-02
8.6E-02
1.1E-01
6.6E-02
1.1E-05
2.7E-02
5.7E-08
2.9E-02
2.0E-02
2.6E-01
2.0E-02
1.4E-01
2.4E+00
7.5E-03
2.5E+00
6.4E-01
3.9E+00
1.1E-02
8.7E-05
8.1E-03
1.5E+00
Worst
VEHICLE
HQe
RISK
2.6E-02
2.5E-02
3.4E-03
1.4E-06
3.0E-05
1.5E-04
3.2E-05
1.4E-04
1.9E-05
3.4E-05
4.6E-08
1.1E-07
3.0E-04
1.9E-09
3.8E-04
1.3E-02
7.1E-03
6.7E+00
4.1E+00
7.9E-01
2.2E-03
2.5E-01
5.5E-04
3.0E-04
4.9E-02
3.3E+01
HOs
RISK
1.4E-01
1 .5E+01
1.2E+00
3.7E+00
2.2E+00
2.9E-01
5.7E+01
5.0E-02
1.7E-01
1 .6E+00
1.5E-02
3.0E-02
3.4E-02
1.1E-01
1.2E-01
7.7E-02
2.5E-01
5.8E-02
3.3E-03
4.8E-04
6.0E-02
3.1E-02
1 .OE»00
2.1E-02
5.5E-01
8.5E-02
1.4E-02
8.5E-03
4.3E-01
3.SE+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HQw
RISK
3.6E+00
1 .8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
3.0E-02
3.6E-02
1.8E-01
2.4E-01
1.1E-01
5.5E-01
8.3E-02
5.4E-02
1 .6E-03
5.9E-03
3.1E-02
2.2E+00
3.6E-02
1.2E-05
9.2E+00
1.4E-02
8.5E-03
1.1E+00
3.5E+00
3.5E-05
1.4E-04
1.3E-03
1.7E+01
HO Total
RISK
3.8E+00
1 .7E+01
2.3E+00
7.5E+00
1.1E+01
7.2E-01
7.9E+01
1.0E-01
3.4E-01
2.0E+00
2.4E-02
6.0E-02
7.0E-02
2.9E-01
3.6E-01
1.9E-01
8.0E-01
1.4E-01
5.7E-02
2.1E-03
6.6E-02
6.2E-02
3.2E+00
5.7E-02
5.5E-01
9.3E+00
4.1E-02
2.4E-02
6.7E+00
4.1E+00
1.5E+00
7.9E-01
7.0E+00
2.5E-01
9.7E-04
1.1E-03
9.8E-02
5.0E+01
90
-------
Table 9.15. Risk to Gizzard Shad from exposure to each medium and total risk,
where HOe * food, HQs * sediment, and HQu = water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo( a ) anth racene
Benzo(a)pyrene
8enzo(a)f luoranthene
BenzoCghi )perylene
BenzoC k) f I uoranthene
Chrysene
Dibenzo(a,h)anthracene
F I uoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endr i n
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'ODE
p.p'DDT
PCBs (total)
CASE
Typical
VEHICLE
HOe
RISK
5.2E-04
9.1E-03
3.8E-03
1.9E-02
2.9E-03
1.9E-03
3.5E-04
3.1E-04
1.7E-03
2.3E-04
1.2E-03
1.9E-03
3.6E-03
1.6E-03
3.7E-04
1.7E-03
6.2E-05
1.3E-02
1.4E-03
3.7E-03
2.1E-06
2.2E-01
2.9E-02
HOs
RISK
2.6E-02
1.8E+00
3.2E-01
1 .9E+00
4.8E-02
2.0E-01
1.1E+01
3.1E-02
3.3E-01
4.1E-03
1.4E-02
2.8E-02
4.4E-02
2.1E-02
1.5E-03
2.6E-02
1.0E-02
8.1E-02
7.4E-03
1.4E-01
2.2E-02
1.9E+00
HOw
RISK
1.8E+00
1.8E+00
7.5E-01
1.9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
4.3E-03
2.3E-02
5.8E-02
6.2E-02
4.5E-02
2.5E-02
2.5E-03
1.0E-02
1.8E-01
1.3E-02
2.9E-06
2.4E+00
2.0E+00
HO Total
RISK
1.8E+00
3.6E+00
1.1E+00
3.8E+00
5.1E+00
3.9E-01
2.5E+01
6.2E-02
1.7E-01
5.9E-01
9.6E-03
3.9E-02
9.0E-02
1.1E-01
6.6E-02
2.8E-02
2.9E-02
3.3E-02
2.6E-01
2.4E-02
1.4E-01
2.6E+00
3.9E+00
Worst
VEHICLE
HOe
RISK
1.0E-03
9.1E-03
5.4E-03
3.8E-02
5.3E-03
4.3E-03
5.4E-04
5.0E-04
1.7E-03
3.5E-04
1.8E-02
9.9E-02
1.0E-02
1.5E-02
1.5E-02
2.9E-03
4.5E-03
2.2E-03
4.5E-03
5.1E-06
1.5E-04
4.0E-02
1.8E-02
7.2E-02
9.2E-06
8.5E-01
3.7E-02
2.2E-02
1.3E-01
5.3E-01
6.4E-07
2.4E-07
8.8E-05
5.4E-01
HQs
RISK
1.4E-01
1.5E+01
1.2E+00
3.7E+00
2.2E+00
2.9E-01
5.7E+01
5.0E-02
1.7E-01
1 .6E+00
1.5E-02
3.0E-02
3.4E-02
1.1E-01
1.2E-01
7.7E-02
2.5E-01
5.8E-02
3.3E-03
4.8E-04
6.0E-02
3.1E-02
1.0E+00
2.1E-02
5.5E-01
8.5E-02
1.4E-02
8.5E-03
4.3E-01
3.5E+00
3.8E-04
6.8E-04
4.8E-02
1.4E-02
HOw
RISK
3.6E+00
1 .8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
3.0E-02
3.6E-02
1.8E-01
2.4E-01
1.1E-01
5.5E-01
8.3E-02
5.4E-02
1.6E-03
5.9E-03
3.1E-02
2.2E+00
3.6E-02
1.2E-05
9.2E+00
1.4E-02
8.5E-03
1.1E+00
3.5E+00
3.5E-05
1.4E-04
1.3E-03
1.7E+01
HO Total
RISK
3.7E+00
1.7E+01
2.3E+00
7.5E+00
1.1E+01
7.2E-01
7.9E+01
1.0E-01
3.4E-01
2.0E+00
4.2E-02
1.6E-01
8.0E-02
3.1E-01
3.8E-01
1.9E-01
8.0E-01
1.4E-01
6.2E-02
2.1E-03
6.6E-02
1.0E-01
3.2E+00
1.3E-01
5.5E-01
1.0E+01
6.5E-02
3.9E-02
1.7E+00
7.5E+00
4.2E-04
8.2E-04
4.9E-02
1.8E+01
-------
Table 9.16. Risk to Pumpkinseed from exposure to each medium and total risk,
where HQe « food, HQs » sediment, and HQw » water.
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
Benzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi)perylene
Benzo( k) f I uoranthene
Chrysene
Oibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno<1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p,p'ODO
p.p'DDE
p,p'DDT
PCBs (total)
CASE
Typical
VEHICLE
HQe
RISK
9.2E-01
1.4E+00
4.7E-01
1.9E+00
2.6E+00
1.9E-01
7.1E+00
3.1E-02
1.7E-01
1.4E-01
3.4E-03
1.3E-02
3.4E-02
3.3E-02
2.3E-02
2.9E-06
1.5E-02
1.4E-08
1.3E-03
3.1E-02
9.0E-02
5.4E-02
3.7E-06
1.4E+00
1.9E-03
6.3E-01
1.6E-01
1.5E+00
2.6E-03
2.1E-04
1 .6E-04
2.0E-03
3.8E+00
HQw
RISK
1.8E+00
1.8E+00
7.5E-01
1 .9E+00
5.0E+00
1.9E-01
1.4E+01
3.1E-02
1.7E-01
2.6E-01
4.3E-03
2.3E-02
5.8E-02
6.2E-02
4.5E-02
2.5E-02
2.5E-03
1.0E-02
1.8E-01
1.3E-02
2.9E-06
2.4E+00
2.0E+00
HQ Total
RISK
2.7E+00
3.2E+00
1.2E+00
3.8E+00
7.6E+00
3.8E-01
2.1E+01
6.2E-02
3.4E-01
4.0E-01
7.7E-03
3.6E-02
9.2E-02
9.5E-02
6.8E-02
2.9E-06
4.0E-02
1.4E-08
3.8E-03
4.1E-02
2.7E-01
6.7E-02
6.6E-06
3.8E+00
1.9E-03
6.3E-01
1.6E-01
3.5E+00
2.6E-03
2.1E-04
1.6E-04
2.0E-03
3.8E+00
Worst
VEHICLE
HQe
RISK
1.9E+00
1.4E+00
6.8E-01
3.8E+00
4.8E+00
4.3E-01
1.1E+01
5.0E-02
1.7E-01
2.2E-01
4.0E-02
2.1E-01
2.8E-02
1.0E-01
1.4E-01
5.9E-02
2.8E-01
4.5E-02
3.2E-02
8.1E-04
3.1E-03
9.4E-02
1.1E+00
1.6E-01
1.SE-05
5.4E+00
4.6E-02
2.7E-02
1.7E+00
1.0E+00
8.0E-01
2.0E-01
2.3E+00
6.4E-02
1.0E-03
6.1E-04
1.3E-02
2.8E+01
HQw
RISK
3.6E+00
1.8E+00
1.1E+00
3.8E+00
9.1E+00
4.3E-01
2.2E+01
5.0E-02
1.7E-01
4.0E-01
9.4E-03
3.0E-02
3.6E-02
1.8E-01
2.4E-01
1.1E-01
5.5E-01
8.3E-02
5.4E-02
1.6E-03
5.9E-03
3.1E-02
2.2E+00
3.6E-02
1.2E-05
9.2E+00
1.4E-02
8.5E-03
1.1E+00
3.5E+00
3.5E-05
1.4E-04
1.3E-03
1.7E+01
HQ Total
RISK
5.5E+00
3.2E+00
1.8E+00
7.6E+00
1.4E+01
8.6E-01
3.3E+01
1.0E-01
3.4E-01
6.2E-01
4.9E-02
2.4E-01
6.4E-02
2.8E-01
3.8E-01
1.7E-01
8.3E-01
1.3E-01
8.6E-02
2.4E-03
9.0E-03
1.3E-01
3.3E+00
2.0E-01
2.7E-05
1.5E+01
6.0E-02
3.6E-02
1.7E+00
1.0E+00
1.9E+00
2.0E-01
5.8E+00
6.4E-02
1.0E-03
7.5E-04
1.4E-02
4.5E+01
-------
be determined. For subsurface benthos, exposure by food was more important
than exposure by sediment. For metal exposure of surface benthos, food
generally posed the greatest risk, but for organics, risk from either sediment
or water was sometimes greater than that for food. By this model for risk
assessment, results for aufwuchs were the same as for surface benthos. Our
earlier model based on calculating uptake rates for each pathway, showed some
differences between these two receptor organisms. For zooplankton, risk from
water was generally greater, although in some cases, e.g., anthracene, risk by
water, sediment, and food were essentially the same.
For brown bullhead exposure by water and sediments to polyaromatic
hydrocarbons generally resulted in a higher risk than exposure by food.
Exposure data were only available by the food route for pesticides, especially
for the typical case. For carp, exposure by sediment and water posed a great
risk for organics than exposure by food, which was the worms (W) food
category. Exposure by water and sediment resulted in similar risks, but food
residues were available for only three metals.
Gizzard shad have higher risk from exposure by water and sediments than by
food for metals and some polyaromatic hydrocarbons. For phenanthrene,
exposure by sediments resulted in the highest risk. For the worst case where
pesticide and PCB data were available, food posed the greatest risk for beta-
BHC, but not for other pesticides. Pumpkinseed, a pelagic fish, were not
considered to be exposed significantly by direct contact with sediment. Water
posed the same or greater risk compared with food for metals. Food and water
exposure to polyaromatic hydrocarbons resulted in similar risks. For the worst
case, food resulted in a greater risk for pesticides beta-BHC, p,p'DDD,
p,p'DDE, and p,p'DDT.
9.2 Multiple Chemicals
Apparent effects threshold (AET) and effects range-low (ER-L) are reference
toxicities obtained for environmental sediment samples containing mixtures of
contaminants tested by standard protocols for several organisms (Science
Advisory Board 1989; Long and Morgan 1990). In Table 9.19 risk is calculated
by a hazard quotient by dividing the typical sediment concentrations at the
Buffalo River by the ER-L values. Although many of the 41 chemicals included
in this report are missing ER-L values, chemicals with a hazard quotient
greater than one could be tentatively considered to pose a significant risk to
aquatic biota at the Buffalo River.
Nelson et al. (1992) reported on aquatic bioassays performed on whole sediment
samples collected in October 1989 at the following stations in the Buffalo
River AOC: BR-01-01, BR-01-03, BR-01-07, BR-01-08, and BR-01-09, which
represents most of the reach of the river within the AOC. In their summary of
their results, they stated that "Buffalo River sediments significantly reduced
amphipod survival in the 28-d exposure at 80% of the stations. Survival of C.
rioarius was significantly reduced in the 14-d exposure in two stations (40%),
but survival was not significantly reduced for C. tentans for any stations in
the 10-d exposure. Amphipod 14-d growth identified 100% of the Buffalo River
sediments as toxic, and significant differences from control for antennal
segment number or sexual maturation was predicted by amphipod reductions in
body length at 80% of the stations. Growth of C. rioarius identified 20% of
the Buffalo River sediments as toxic, and growth of C. tentans identified 40%
of the stations as toxic" (Nelson et al. 1992). The presentation of the data
did not indicate if particular contaminants in the sediments could be
correlated with the toxic effects. Determination of contaminant
concentrations correlated with reduced survival could guide setting
93
-------
remediation goals.
Canfield et al. (1992) reported on studies of benthic community structure of
one station (BR-01) sampled in 1989 and ten stations sampled in 1990. They
also sampled the Saginaw River AOC and Indiana Harbor AOC and compared the
results from the three AOCs. They stated that "comparisons between
concentrations of simultaneously extracted metals (SEM), total PAH, and total
PCB with measures of benthic invertebrate abundance demonstrates a consistent
pattern of decreasing invertebrate abundance with increasing contamination."
They stated that the "Buffalo River had the largest number of genera and
species (n=33) present, followed by Saginaw River (n=20) and Indiana Harbor
(n=14)." The Indiana'Harbor is-a degraded habitat. For comparison, Hudson et
al. (1986) identified 101 taxa (genera and species) in the upper Detroit
River, 98 in the upper St. Clair River, 95 in the lower St. Clair River, and
80 in the lower Detroit River. However, the Buffalo River AOC does not have
the diversity of habitat that the above large river systems have, and the
Buffalo River suffers from noncontaminant problems, such as low dissolved
oxygen and physical loss of habitat.
Johnson (1992) published results of genotoxic tests on sediment samples
collected from ten stations in the Buffalo River AOC in October 1989. He
tested freshwater sediment extracts with a new activated Mutatox Genotoxicity
Assay. Samples from all ten sites were genotoxic. He did not attempt to
identify which contaminants were causing the observed genotoxicity.
9.3 Presentation of Risks/Hazards in Sumnary Format
Tables 9.17 and 9.18 present for each of the eight receptors only those
chemicals that have a total hazard quotient greater than one and hence are
considered to represent a significant risk to aquatic receptors. These
results show that for the typical case cadmium, chromium, copper, iron, lead.
mercury, pvrene. and heptachlor epoxide present a significant risk to most of
the eight receptor organisms. For the worst case, the above compounds plus
zinc, indeno(1.2.3-cd)pyrene. endrin. and total PCBs represent a significant
risk to aquatic receptors.
In considering the conclusions, one must understand the twofold intent of the
baseline assessment. The objective is to develop a reference value for risk
at the Area of Concern. This risk value is used in two ways. First, it is
used as an 'indicator' of the potential for adverse affects. It is
intentionally conservative to ensure that risks are not underestimated. The
second use of the baseline risk estimate is to use the risk estimates as a
reference point in the analysis of residual risks of remediation alternatives.
In this sense, it is used to estimate the relative reduction of risk that
would occur given the implementation of various alternative remediation
strategies.
With this in mind, an appropriate interpretation of the conclusions is that
there is a need to further refine the baseline estimates. The following is a
list of specific recommendations for further work to be performed in order to
refine the estimates of risk reported here:
1) The occurrence of 'hot spots' in the Buffalo River is an open question.
The 1985 sediment sampling shows heightened levels of contamination in a
small portion of the river. The 1989 sediment sampling data is not
sufficient to conclude that the high concentrations measured in 1985 have
decreased. Further, neither the 1985 nor the 1989 sediment data sets is
sufficient for determining the number or locations of other hot spots. It
94
-------
is recommended that a sampling strategy be developed and implemented to
address the need relat.ed to locating and sampling currently existing hot
spots.
2) This baseline assessment assumes that all risks experienced as a result of
exposure within the Buffalo River is due solely to contaminated sediments.
This implies that there are no additional sources of contamination.
However, there are additional sources of contamination, such as combined
sewer overflows and abandoned hazardous waste sites. The extent to which
these sources contribute to exposures and risks is, at this time, unknown.
Before any remediation strategies are selected it will be important to
accurately inventory existing sources and to estimate their individual and
collective impact on future water and sediment conditions in the Buffalo
River.
3) After the above recommendations have been addressed, the baseline estimate
of exposures and risks should be updated and a comprehensive risk
assessment conducted.
95
-------
Table 9.17. Summary of total contaminant risk (HQ Total) associated with all exposure routes. Only HO Total > 1 included.
CASE Typical
VO
Ol
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)anthracene
8enzo(a)pyrene
Benzo(a)f luoranthene
Benzo(ghi )perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
Fluorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane (gamma-BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'DOE
p.p'DDT
PCBs (total)
ORGANISM
Subsur-
face
Benthos
2.1E+00
5.6E+01
1.8E+02
2.9E+03
1.2E+01
5.1E+01
1.8E+01
1.9E+01
2.0E+01
3.2E+00
1.8E+01
1.0E+01
5.2E+00
3.6E+00
1.5E+01
1.3E+01
2.1E+00
Surface
Benthos
3.9E+00
5.8E+01
1.8E+02
2.9E+03
1.7E+01
5.1E+01
3.2E+01
1 .9E+01
2.1E+01
3.3E+00
1.8E+01
1.0E+01
5.4E+00
3.8E+00
1.6E+01
1 .6E+01
4.0E+00
Aufwuchs
3.9E+00
5.8E+01
1 .8E+02
2.9E+03
1.7E+01
5.1E+01
3.2E+01
1 .9E+01
2.1E+01
3.3E+00
1.8E+01
1.0E+01
5.4E+00
3.8E+00
1.6E+01
1.6E+01
4.0E+00
Zoo-
plankton
1.8E+00
3.6E+00
1.1E+00
3.8E+00
5.1E+00
2.5E+01
1.1E+00
2.6E+00
3.9E+00
Brown
Bullhead
1 .8E+00
3.6E+00
1.3E+00
3.8E+00
5.0E+00
2.6E+01
2.4E+00
1.6E+00
1.1E+02
4.0E+00
4.3E+00
1.2E+00
6.1E+02
Carp
1.8E+00
3.6E+00
1.1E+00
3.8E+00
5.0E+00
2.5E+01
2.4E+00
2.5E+00
3.9E+00
1.5E+00
Gizzard
Shad
1.8E+00
3.6E+00
1.1E+00
3.8E+00
5.1E+00
2.5E+01
2.6E+00
3.9E+00
Pumpkin-
seed
2.7E+00
3.2E+00
1.2E+00
3.8E+00
7.6E+00
2.1E+01
3.8E+00
3.5E+00
3.8E+00
-------
Table 9.18. Summary of total contaminant risk (HO Total) associated with all exposure routes. Only HO. Total > 1 included.
CASE Worst
CHEMICAL
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthene
Acenaphthylene
Anthracene
6enzo(a)anthracene
Benzo(a)pyrene
Benzo( a ) f luoranthene
Benzo(ghi }perylene
Benzo(k)f luoranthene
Chrysene
Dibenzo(a,h)anthracene
F luoranthene
f luorene
Indeno(1,2,3-cd)pyrene
Naphthalene
Phenanthrene
Pyrene
alpha-BHC
beta-BHC
Lindane ( gamma -BHC)
Aldrin
Chlordane
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Hexach I orobenzene
Mi rex
p.p'DDD
p.p'ODE
p.p'DDT
PCBs (total)
ORGANISM
Subsur-
face
Benthos
1.1E+01
4.7E+02
6.6E+02
5.6E+03
5.4E+02
7.5E+01
9.3E+01
3.0E+01
7.1E+02
9.8E+01
2.5E+01
7.4E+01
1.8E+01
6.3E+01
1.3E+01
7.9E+00
1.9E+02
2.1E+00
5.1E+01
1.7E+00
1.1E+00
2.3E+01
3.7E+00
4.6E+02
Surface
Benthos
1.5E+01
4.7E+02
6.6E+02
5.6E+03
5.5E+02
7.6E+01
1.1E+02
3.0E+01
7.1E+02
9.9E+01
2.6E+01
7.6E+01
1.8E+01
6.6E+01
1.4E+01
8.2E+00
2.0E+02
2.2E+00
6.1E+01
1.8E+00
1.2E+00
2.4E+01
7.2E+00
4.8E+02
Aufwuchs
1.5E+01
4.7E+02
6.6E+02
5.6E+03
5.5E+02
7.6E+01
1.1E+02
3.0E+01
7.1E+02
9.9E*01
2.6E+01
7.6E+01
1.8E+01
6.6E+01
1.4E+01
8.2E+00
2.0E+02
2.2E+00
6.1E+01
1.8E+00
1.2E+00
2.4E+01
7.2E+00
4.8E+02
Zoo-
plankton
3.8E+00
1.7E+01
2.2E+00
7.5E+00
1.1E+01
7.9E+01
2.0E+00
1.2E+00
1.5E+00
1.3E+00
4.5E+00
1.4E+01
1.0E+01
1 .6E+00
7.6E+00
1.7E+01
Broun
Bullhead
3.8E+00
1.7E+01
6.5E+00
7.5E+00
1.1E+01
9.7E+01
2.0E+00
3.2E+00
9.2E+00
6.7E+00
4.1E+00
1.5E+00
7.0E+00
1.3E+03
Carp
3.8E+00
1.7E+01
2.3E+00
7.5E+00
1.1E+01
7.9E+01
2.0E+00
3.2E+00
9.2E+00
6.7E+00
4.1E+00
1.5E+00
7.0E+00
5.0E+01
Gizzard
Shad
3.8E+00
1.7E+01
2.2E+00
7.5E+00
1.1E+01
7.9E+01
2.0E+00
3.3E+00
1.0E+01
1 .6E+00
7.6E+00
1 .7E+01
Pumpkin-
seed
5.5E+00
3.2E+00
1.8E+00
7.5E+00
1.4E+01
3.3E+01
.
3.4E+00
1.5E+01
1.7E+00
1.0E+00
1 .9E+00
5.8E+00
4.5E+01
-------
Table 9.19 Risk from exposure to typical chemical sediment mixtures (sediment
concentrations/ER-L) at the Buffalo River.
Chemical
Cadmium
Chromium (hex)
Copper
Iron
Lead
Manganese
Mercury
Nickel
Silver
Zinc
Acenaphthone
Acenaphthyl ene
Anthracene
Benzo (a) anthracene
Benzo (a) pyrene
Benzo (b) f luoranthene
Benzo (ghi) perylene
Benzo (k) f luoranthene
Chrysene
Dibenzo (a , h) anthracene
Fluoranthene
Fluorene
I ndeno ( 1 , 2 , 3 -cd) pyrene
Naphthalene
Fhenanthrene
Pyrene
alpha-BHC
beta-BBC
Lindane (gamma-BBC)
Aldrin
Dieldrin
Chlordane
Endrin
Heptaehlor
Heptachlor epoxide
Hexachlorobenzene
Mirex
p , p ' DDD
p.p'DDE
DDT (total)
PCBs (total)
1989 Sed. cone.
-------
CHAPTER 10
CHARACTERIZATION OF UNCERTAINTY
Baseline risk assessments utilize available data only. Many times available
data are unknown quality and may not be representative of the spatial,
temporal or environmental media of interest to the risk assessor. In these
and other cases it is necessary to generate assumptions about the relationship
between available data and more appropriate but unavailable data. This
combination of unknown quality and necessary assumptions result, in a complex
manner, in overall uncertainty associated with the level of risk reported
within the risk assessment.
The primary role of this uncertainty analysis is to describe, qualitatively,
the nature and basis for all assumptions used at each stage of the assessment
of Buffalo River exposures and risks, and then to address the effect these
assumptions will have on the reported exposure and risk levels.
10.1 Uncertainty in Data Compilation and Evaluation Step (Hazard
Evaluation Procedure)
Environmental quality data forms the basis for conducting an exposure and risk
assessment by defining the level of contamination associated with a particular
area of concern. Of primary interest in organizing environmental quality data
is the specification of contaminant levels in all niches of the aquatic
ecosystem. The organisms would be expected to be in contact with the
contamination to varying degrees (depending on their ecological niche) over
their lifespan. While the data are quite limited in time span and location
(the data sets could be considered as "snapshots" of the contamination at
specific places and times), the available data must be configured to account
for this long-term exposure. For the environmental quality data used in this
study:
Assumption fl: The surficial sediment quality data for 1989 and 1985
represent typical and worst-case conditions, respectively, that are
representative of current contaminant levels in Buffalo River sediments.
Uncertainty about the quality of sampling and analysis protocols employed
for the sediment studies is large. The amount of descriptive information
available about the protocols for the 1985 data set is minimal, thus the
accuracy and precision of the data cannot be quantified. On a qualitative
basis the 1985 data are also given low scores by those individuals
responsible for the studies, because the analytical methodology was being
developed during the study. The 1989 data set, based on the quantitative
scoring system referenced in Section 5.3 is acceptable. One positive point
is that the 1985 and 1989 data sets show contaminant levels that are
similar in the overall range of concentrations reported, and by inference,
are of similar quality.
The impact of these data upon estimates of risk is direct and linear. If a
concentration is increased by a factor of two the estimate of risk would
increase by the same factor. The question that cannot be addressed is how
big a difference might exist between actual conditions in the Buffalo River
and those characterized by the data.
99
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Assumption #2: Spatial variation within the 1985 and 1989 sediment quality
data sets is not significant, and therefore statistical measures can be
applied to condense the data into single value estimates of typical and
reasonable worst case sediment contamination levels per contaminant.
For each of the data sets, contaminant levels varied relatively little
among the samples. For those portions of the river sampled, the
contamination was essentially uniform. While samples within each study
reflect little variation from site to site, two factors remain that cause
uncertainty.
First, monitoring survey samples were collected either at mid-channel only
(1989) or within a limited area (1985). Likely exposures occur uniformly
throughout the aquatic environment. How truly these samplings represent
the overall sediment contamination is unknown.
Second, within the context of an aquatic health risk assessment are
locations within the area of concern that exhibit high contaminant
concentrations. This generally occurs where sedimentation is enhanced,
such as near bends in the river or where water slows considerably. These
"hot spots" are important as exposure points due to organism contact with
the relatively high contamination. While it appears that the site of the
1985 sampling represents a hot spot, there are insufficient data available
to determine the existence of other sites of elevated contamination.
The difference between actual (sediment) conditions in the Buffalo River
and those characterized by the 1989 and 1985 data cannot be estimated.
Monitoring survey samples were collected either at mid-channel only (1989)
or within a limited area (1985). Exposures occur uniformly throughout the
aquatic environment. The 1985 and 1989 data sets (as well as the earlier
reported data not used in this assessment) show contaminant levels that are
similar in the overall range of concentrations reported, and by inference,
are of similar quality. All of the sediment studies together represent a
wide area of the Buffalo River. How truly these samplings represent the
overall sediment contamination is unknown.
Assumption #3: Equilibrium partitioning, constrained by solubility limits,
is an appropriate technique by which to estimate dissolved levels of
hydrophobia organic compounds in the water column.
The need for this assumption arises due to the fact that water column
concentrations for virtually all hydrophobic organics sampled were reported
to be less than the applicable detection limit. It is unreasonable to
assume that the contaminants are not present in the water column, when they
are present in the sediments, and therefore an appropriate approximation is
required. An option considered but not pursued was to assume that the
organic concentrations were equal to their respective detection limits.
While this is certainly a conservative assumption, the detection limits,
themselves considered high, may be unnecessarily conservative. The use of
equilibrium partitioning is also conservative but represents a practical
upper limit as to what the concentrations may be.
The magnitude of uncertainty related to the use of equilibrium partitioning
for water column contaminant concentrations cannot be quantified without
significant sampling and/or modelling effort. These additional efforts
would be required only if the exposure and risk estimates resulting from
100
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the use of the equilibrium assumption were at levels causing concern. This
assumption assures an overestimation of the risk.
Assumption #4: Historical water column metals data residing in STORET arc
representative of current conditions.
The only available source of metals concentration data in the water column
of the Buffalo River are contained in the STORET data base maintained by
EPA. The STORET data does not include descriptions of the sampling and
analytical protocols and thus the quality of the data is unknown. The
method errors may have been significant. The water column data taken from
STORET were statistically manipulated to produce values reflecting a mean
(i.e., typical) and upper bound (i.e., reasonable worst case), and are not
meant to suggest known accuracy. Finally, the STORET data is specific to
one location in the Buffalo River and with respect to locations -where
exposure occurs, is of unknown quality.
Assumption #5: The very limited data available describing contaminant
levels in benthos (algae, clams, mussels, and worms) and fish are
representative of current conditions.
Of all the data available describing the contamination of the Buffalo
River, none are more important than those describing chemical
concentrations throughout the food chain. The consumption of contaminated
food through the food chain is a dominant aquatic health risk. This result
is based on a limited number of samples and by itself would not be
sufficient to draw definitive conclusions. Also, this assessment is based
on a very limited sampling of a few species along the food chain including
a worm that is not strictly aquatic and some representative fishes. The
amount of descriptive information available about the protocols for most of
the data sets (except for possibly mussels, worms and fish) is minimal,
thus the accuracy and precision of the data cannot be quantified. The
contaminants monitored in each data set are quite select, and there is very
little continuity between data sets. Some data sets only analyze for
specific members of a class (i.e., PCBs) and comparisons with other sets
are difficult. The data sets for different organisms are for quite
different time periods and often at somewhat different locations. It is
feasible to compute the missing contaminant residue data for the various
organisms as well as for missing members of the food chain using sediment
data, but the bioconcentration factors can vary widely from species to
species and from study to study for the same species, often differing by a
factor of 100-1000. These BCFs are not available for every species, and
the use of a representative species would introduce another unknown measure
of uncertainty. Finally, in an effort to provide some estimate of
reasonable worst-case contaminant levels, where two or more sets of data
were available for analysis, the set with the highest levels (where obvious
by visual inspection) was used.
The effect of these combinations of assumptions is to overestimate the risk
due to consumption along the food chain. The few representative organisms
for which some select residue data are available must be used to represent
the aquatic food chain in the ecosystem. How well this series of data sets
represents the actual population contaminant load is unknown, and it would
require a significant sampling and modelling effort to quantify the answer.
It is felt that additional information concerning current levels in a much
wider benthos and fish sample for a wider range of contaminants (with
higher degree of continuity of monitored contaminants between sampled
101
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organisms) should be gathered before action is taken in response to the
risks reported in this assessment.
10.2 Uncertainty in Exposure Assessment (Use of Existing Data)
The objective of this aquatic exposure assessment is to determine the long
term average daily intake of individual contaminants due to contact with
water, sediments and the food chain. There are two key sets of data required
to estimate exposure: 1) characterization of the exposed organisms, and 2)
specification of the frequency and duration of contact with contamination.
Together these data constitute an exposure scenario. Due to insufficient
information there is a need to formulate the exposure scenarios using
assumptions about some key variables.
Assumption #6: Environmental quality data, developed in the data
compilation and evaluation step, are representative of contaminant levels
that the aquatic organisms contact in the Buffalo River.
Exposure is the contact (direct or indirect) between an organism (receptor)
and a contaminated medium. All aquatic organisms are in contact with the
Buffalo River water and sediment (some more than others). The sediment
data specify contaminant levels at specific, small points at two (several)
periods of time, and the STORET water column data represent an unspecified
site (sites).
The uncertainty related to this assumption cannot be quantified. It is a
function of two factors: 1) the quality of sediment and water quality data,
and 2) how well the data represent the AOC in an exposure analysis. Both
issues were addressed in Section 10.1. As to the uncertainty of contaminant
levels throughout the AOC, the uncertainty focuses on the relationship
between concentrations measured at two particular sites in the Buffalo
River and the remainder of the aquatic AOC. There is no empirical way to
extrapolate from contaminant residues found at two sampling locales to a
description of any increase or decrease in contamination at any point in
the general aquatic ecosystem.
To respond to this uncertainty, it is reasonable that if estimated
exposures using the typical and reasonable worst case conditions are of
marginal or greater concern, then an effort to further detail the sediment
contaminant levels should be pursued.
Assumption #7 The available benthos and fish samples and their contaminant
body burdens represent the current population size, variation, condition
and activity of the aquatic organisms throughout the Buffalo River AOC.
The benthic and fish populations are much more varied than the sample
population would indicate. The various sampling was done over
approximately 10 years with little continuity of sampling locale and
organism. Few indications of organism condition, age or gender were given.
Species activity is very much dependent on age and gender (to a lesser
degree), and will dictate the degree to which an organism is exposed to a
contaminated medium. Differing species and ages can occupy different
niches of the aquatic ecosystem and so perhaps different sites of the AOC,
which can in turn influence contaminant profiles and concentrations.
Contamination will affect different species, genders and ages often in
widely different ways. Contaminant bioaccumulation and body burdens will
vary similarly.
102
-------
One uncertainty associated with this assumption occurs in all assessments,
owing to the fact that specific individual organisms exposed to site-
specific contamination are not explicitly addressed within a baseline
exposure and risk assessment.
Another uncertainty in this assumption is that organism contaminant
concentrations can vary significantly with life stage and species. The
effects of this assumption may not be important because results may not
change enough to alter any conclusions if all species and life stages could
be defined.
These two uncertainties are potentially conflicting in the relative
importance placed on species differentiation and life stage. The conflict
may not be resolved without a great deal of field work and modelling. The
uncertainty that cannot be quantified is the degree to which each affect
the overestimation of risk.
Assumption f8: The extrapolations of current aquatic organism activity to
represent long-term (lifetime) conditions are applicable to the Buffalo
River.
The estimate of health risk as presented in this assessment represents
effects of chronic exposure. Available toxicity measures of the various
contaminants are primarily for acute (short-term) effects and only for a
few of the present species. Very few data are available for chronic
effects for all the contaminants and species. A conservative approach is
to assume that the current exposures will continue sufficiently long to
cause a relevant health effect within the lifetime of the organism. This
assumption does not account for 1) the changes in organism activity over
its lifetime or 2) the possibility that environmental contamination will be
reduced with time. It is not possible to determine the extent to which
this assumption causes risks to be overestimated in the Buffalo River AOC.
It is only possible to say that this component of the exposure computation
will contribute to an overestimation of risk.
10.3 Uncertainty in Risk Assessment (Cause and Effect Relationships)
The objective of the risk assessment is to characterize the risks of human
health effects resulting from exposures estimated previously. Important data
for this step include toxicity information for individual contaminants in the
form of acute and chronic toxicity endpoints, and reference doses. The data
are far from complete for all contaminants and species, and extrapolations
must be made. There are various sources of aquatic health effects but there
remain gaps in the data necessary to quantify all chemical specific risks. In
cases where risk values are not available, a qualitative discussion of the
possible health effects is presented. The following major assumptions were
made for the risk characterization assessment.
Assumption 99: While a specific chemical contaminant may be found in the
Buffalo River in many forms, some toxic and some not, it is assumed that
all of the chemical is of the most toxic form.
Many chemicals may appear in the environment in various forms due to
chemical speciation processes (e.g., metals) or are measured only as a
total quantity (e.g., PAHs, PCBs). However, a toxicological profile and
related measures of risk are specific to a particular chemical form. In
the case of a risk assessment where the measured form of the contaminant
and the form related to the toxicity measurement are not identical, an
103
-------
assumption must be made. In this assessment, when a measured value for a
contaminant includes many congeners or species, the toxicity of the most
potent form is assumed to apply to the entire measured amount.
The impact of this assumption is to overestimate the actual risk. The
degree to which risk is overestimated is unknown and may be significant.
Assumption #10: Current levels of exposure will remain constant over a time
period commensurate with the period of exposure related to toxicity
This assumption is paired wi-th the exposure assumption concerning the long
term constancy of aquatic organism activity that results in exposure. The
level of contamination is assumed to remain constant over the long term.
Contamination conditions will not remain identical over a period of
decades. There are two sets of information that would be required if
conditions of environmental contamination change in the future: 1) a source
inventory that reflects present and future conditions, and 2) a detailed
characterization of the Buffalo River AOC sufficient to allow use of
predictive models. With these two sets of data, one could configure a
modeling study and estimate the likely levels of future contamination.
Because a baseline assessment does not include such data, assumptions
concerning future conditions must be made. The nature of this assumption
is conservative to assure an overestimation of risk.
Assumption ill: Health risks are additive.
In the absence of knowledge about the effects of simultaneous exposure to
multiple contaminants, it is assumed that the risk associated with the
combined exposure to multiple contaminants is simply the sum of the risks
related to the individual chemicals. While it is known that both
synergistic and antagonistic effects occur there are no guidelines for
their application in a baseline assessment. The assumption of additivity
of contaminant health effects is of unknown impact. Carcinogenicity is not
viewed as a significant aquatic health effect for most contaminants and
species in this assessment. Because of the unknown contributions of
chemicals below threshold levels, we did not sum the risk across all
chemicals.
10.4 Summary of Uncertainty
Uncertainty in the context of baseline assessment of aquatic health risk is
large and ubiquitous. To quantify each of the major components of risk, it is
necessary to formulate and use assumptions. Each assumption fills an
information gap between existing information and information needed to
quantify risk. The price paid for applying assumptions is uncertainty.
The two general ways to express uncertainty are qualitative and quantitative.
A quantitative assessment of uncertainty is preferable because it uses
specific knowledge of uncertainty sources and yields a statistically-based
estimate of the (here) risk of adverse aquatic health effects. A quantitative
uncertainty analysis requires its own unique set of data, which reflect the
statistical distribution of values representative of each parameter used as
input to the risk assessment. This type of data is not available in this
assessment.
104
-------
A qualitative uncertainty presentation is more descriptive and conceptual in
nature. The expertise of the assessor is needed to discuss the combination of
study objectives, approach, results, and the study limitations.
The conclusion concerning uncertainties in this assessment is that the
estimates of aquatic exposure and resulting aquatic health risk within the
Buffalo River AOC should be used for comparative purposes and not as estimates
of actual exposure and risks.
Two valid conclusions can be drawn from this assessment. First, The risk to
aquatic health is dominated by two factors, absorption at the gill and
ingestion of food, and that exposure to contaminants by other pathways results
in relatively low health risks. Second, risks characterized in this
assessment can be used to compare with residual risks estimated to remain
after various alternative clean-up actions are completed. By comparing the
residual risks one can make a determination of the relative benefit from
specific remediation protocols.
105
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APPENDIX A
Methods for Estimating Missing Water Quality Data
(Laniak et al. 1992; Karickhoff 1981)
The approach used for estimating the concentration of hydrophobic organic
compounds in surface water is to represent the total concentration of an
organic pollutant in surface water as the combination of pollutant adsorbed to
suspended particles and in aqueous solution. The total organic contaminant
concentration in the water column can be taken as the sum of the particulate
and dissolved fractions. This total may be described by
Ct = (Ca/Kt) + C,*TSS
where Ct is the total contaminant concentration (dissolved + particulate}, C3
is the sorbed concentration (mg contaminant/kg solids), and TSS is the solids
concentration (kg-solids/L) . K^, is a distribution coefficient (dimensionless,
but multiplied by [1 L/l kg-solids] conversion constant) . A distribution
constant, rather than an equilibrium constant, is used since complete
equilibrium may not be achieved in the field. The dissolved concentration
(assuming partitioning in the environment) may be estimated from C,/K^ and the
particulate concentration may be estimated from C,*TSS. Therefore, if data are
available for the sorbed concentration in the sediments, the partition
coefficient, and the concentration of suspended solids in the water column,
the dissolved and particulate fractions, as well as the total concentrations,
may be estimated. The estimates of total concentrations derived using the
above formulation are considered to be conservative since it is assumed that
there is a reasonable equilibrium established between the sediments and the
water column and that the materials in the water column are not reduced due to
outflows (e.g., volatilization), or chemical (e.g., photolysis) or biological
degradation.
For organic compounds where water quality data were not determined or
measurements were either below a specified detection limit or not pursued
rigorously, it was necessary to provide estimates of the water concentrations
using the method described above. The calculation requires estimation of the
distribution coefficient
The value of the distribution coefficient (KJ is typically estimated in three
steps. First, an octanol-water partition coefficient (Kou, a commonly
available chemical parameter; e.g., see Lyman et al. 1990) is obtained for the
chemical (s) of interest. The Kou values are then assumed to be linearly related
to an organic carbon partition coefficient (Koc) by the fraction of organic
carbon available on the sediments (f-c), as illustrated below (Crane, 1993)
K* = foe * 0.63 *„
Table 5.3 provides a summary of the values used to calculate probable water
concentrations followed by the estimated' water concentrations. For this
assessment, C5 was assumed to be equal to the sediment concentration. For TSS
an average value of (= 1.8 x 10"5 mg/kg) reported in STORET was used. For K3VI
values were obtained from the literature (Mabey et al. 1982). The sediment
contaminant concentrations and fraction organic carbon were taken from the
1985 or 1989 surveys. The 1989 data indicated a fraction organic carbon, foc,
on the order of 0.1 percent, but this value is below those typically observed
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in Great Lakes sediments (1-5 percent) and is questionable. An average value
of 3.25%, as reported in the 1985 sediment data, was used instead.
As an example, the water concentration of anthracene for the typical case was
calculated as follows (Table 5.3):
Ct = (C3/Kd) + C3 * TSS
Kd = fcc * 0.63 K^
Kd = 0.0325 * 0.63 * 2.82 x 104 = 577 L/kg
Ct = (0.180 mg/kg)/(577 L/kg) + 0.180 mg/kg) (1.8 x 10"5 kg/L)
Ct = 3.15 x 10~4 mg/L = C«
The assumption that there is no substantial contaminant concentration gradient
between the sediment bed and the suspended particles in the surface water
makes possible the estimation of surface water aqueous and absorbed
concentrations. As to whether this assumption is valid, it can be noted that
rapid circulation leading to the circulation of relatively clean waters over
the contaminated sediments and slow diffusion processes in the bed can lead to
substantial contaminant gradients and flux values.
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