LIBRARY ; Michigan State 1 University PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. DATE DUE DATE DUE DATE DUE MSU Is An Affirmative Action/Equal Opportunity Institution omens-M \__ -M W PARTITIONING, TOXICITY AND MUTAGENICITY OF IN-PLACE CONTAMINANTS OF SEDIMENTS FROM THE GRAND CALUMET RIVER AND INDIANA HARBOR, INDIANA BY Robert Alan Hoke A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Fisheries and Wildlife Institute of Environmental Toxicology 1992 Copyright by: Robert A. Hoke 1992 ABSTRACT PARTITIONING, TOXICITY AND MUTAGENICITY OF IN-PLACE CONTAMINANTS OF SEDIMENTS FROM THE GRAND CALUMET RIVER, INDIANA BY Robert A. Hoke The presence of a wide variety of in—place chemical contaminants in sediments from the Grand Calumet River-Indiana Harbor Canal, Indiana Area of Concern, their chemical partitioning between environmental compartments, and their potential toxicological effects were the primary focus of this study. The partitioning behavior of non-polar organic chemicals (NPOCs) present in both sediment and sediment pore waters was investigated to determine the importance of NPOC binding to dissolved organic carbon (DOC) in sediment pore water. Better concordance was observed between estimated and actual field partition coefficients with a three-phase partitioning model. These results highlight the potential importance of the DOC-binding phenomenon in determinations of the bioavailability and effects of NPOCs present in sediment pore waters. The Microtox® assay, 48 h Daphnia maqng and Ceriodaphnia dubia tests and a 10-d Chironomug tentm test were used in a toxic units approach to assess the toxicity of sediments and sediment pore waters and to conduct a preliminary identification of the potential toxicants. Based on the results of these analyses, ammonia, polycyclic aromatic hydrocarbons, metals, petroleum hydrocarbons and bicarbonate ion were the major contaminants of concern to benthic invertebrates within the study area. Separate experiments to determine the mechanism of bicarbonate ion toxicity to D. magna suggested that toxicity was due to the inhibition of the active uptake of Cl" from water. Therefore, pore water alkalinity should be considered when interpreting the results of aqueous phase toxicity tests with cladocerans and, perhaps, other species of invertebrates and fish. Evaluation of the comparative mutagenicity of solvent extracts of sediments from the study area was conducted with the Ames and MutatoxQ assays. Extracts were mutagenic with metabolic activation in both assays, however, few samples contained direct acting mutagens. The lack of mutagenicity in Mutatox® assays of pore waters indicates that short-term human exposure to mutagens in pore waters and sediments is likely to be non-problematicu Greater concern is required for the potential ecological and human health effects due to food chain transfer of mutagenic compounds in sediments from the study area. This dissertation is dedicated to the memory of my father and to my son, Ian, whose insatiable curiosity about the world around him is a constant source of wonder. ACKNOWLEDGEMENTS I would like to thank the members of my dissertation committee for sharing their knowledge and insight, as well as for being patient with my meanderings. Thanks are also due to my fellow graduate students in the Aquatic Toxicology Program at Michigan State University. Don Tillitt was responsible for helping me maintain sight of the goal while still "having a life" and.Will Gala was responsible for providing unusual insight at the most incongruous times, as exhibited by his role in the development of "weekend science". I am jparticularly grateful for having had the opportunity to study and work with Dr. John Giesy. Both in and out of the laboratory, John provides a multi-faceted learning environment which encourages students to explore new ideas and develop their full potential. I wish to thank him for providing me with the opportunity to expand my horizons, both personally and professionally. I have benefited both from his professional knowledge and advice and from his friendship. My son, Ian, has been a constant source of inspiration and curiosity about the world at large, as well as an occasional unpaid lab assistant. Finally, I would like to thank Kathee for her patience with me and the vagaries of graduate school. Her constant love, support and understanding made things easier along the way. ii TABLE OF CONTENTS LIST OF TABLES O O O O O O O O O O O O O O O O O O O O O C O O 0 LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . GENERAL INTRODUCTION 0 O O O O 0 O O O O O O O O O O O O O O O 0 Literature Cited . . . . . . . . . . . . . . . . . . . . . CHAPTER 1 A Field Evaluation of Equilibrium Partitioning in Sediments from the Grand Calumet River and Indiana Harbor, Indiana . Introduction . . . . . . . . . . . . . . . . . . . . Material and Methods . . . . . . . . . . . . . . . . Chemical Analysis . . . . . . . . . . . . . . Equilibrium Partitioning Calculations . . . . . Results . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . Literature Cited . . . . . . . . . . . . . . . . . . CHAPTER 2 Toxicity of Sediments and Sediment Pore Waters from the Grand Calumet River and Indiana Harbor, Indiana . . . . . Introduction . . . . . . . . . . . . . . . . . . . . Materials and Methods . . . . . . . . . . . . . . . Sample Collection . . . . . . . . . . . . . . Pore Water Extraction . . . . . . . . . Chemical Analysis . . . . . . . . . . . . . . Organics . . . . . . . . . . . . . . . . Metals . . . . . . . . . . . . . . . . . Miscellaneous Parameters . . . . . . . . Toxicity Tests . . . . . . . . . . . . . . . . Photobacterium phosphorgum . . . . . . . Daphnia magna and Ceriodaphnia dubia . . Chironomus tentans . . . . . . . . . . . Statistical Analysis . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . Chemical Analysis . . . . . . . . . . . . . . Organics . . . . . . . . . . . . . . . . Metals . . . . . . . . . . . . . . . . . Miscellaneous Parameters . . . . . . . . iii vi ix 11 12 16 16 19 21 45 50 51 55 S6 61 63 63 63 63 65 65 66 66 66 68 69 69 69 69 83 93 TABLE OF CONTENTS - continued Toxicity Tests . . . . . . . . . . . . . . . . . . 93 Photobacterium phosphoreum . . . . . . . . . 93 Daphnia magng and Ceriodaphnia dubia . . . 99 Chironomus tentans . . . . . . . . . . . . 103 Discussion . . . . . . . . . . . . . . . . . . . . . . 104 Acknowledgements . . . . . . . . . . . . . . . . . . . 113 Literature Cited . . . . . . . . . . . . . . . . . . . 114 CHAPTER 3 Bicarbonate as a Potential Confounding Factor in Cladoceran Toxicity Assessments of Pore Waters from Contaminated Sediments . . . . . . . . . . . . . . . . . . . . . . . . . 127 Introduction . . . . . . . . . . . . . . . . . . . . . 128 Materials and Methods . . . . . . . . . . . . . . . . 133 Toxicity of Na+ and HCO3' . . . . . . . . . . . 133 Calculation of Free C02 and MCO3' . . . . . . . 134 X-ray Dispersive Microanalysis . . . . . . . . . 135 Data Analysis . . . . . . . . . . . . . . . . . 138 Results . . . . . . . . . . . . . . . . . . . . . . . 138 Toxicity of Na+ and HCO3' . . . . . . . . . . . 138 Calculation of Free C02 and HCO3' . . . . . . . 139 X-ray Dispersive Microanalysis . . . . . . . . . 139 Discussion . . . . . . . . . . . . . . . . . . . . . . 143 Acknowledgements . . . . . . . . . . . . . . . . . . . 150 Literature Cited . . . . . . . . . . . . . . . . . . . 151 CHAPTER 4 Mutagenicity and 2,3,7,8-Tetrachlorodibenzo-p-dioxin Equivalents in Organic Solvent Extracts of Sediments from the Grand Calumet River, Indiana . . . . . . . . . . . . . . 158 Introduction . . . . . . . . . . . . . . . . . . . . . 159 Materials and Methods . . . . . . . . . . . . . . . . 163 Sample Collection . . . . . . . . . . . . . . . 163 Pore Water Extraction . . . . . . . . . . . . . 165 Mutatox Assay . . . . . . . . . . . . . . . . . 165 Ames Assay . . . . . . . . . . . . . . . . . . . 167 H4IIE Assay . . . . . . . . . . . . . . . . . . 168 Chemical Analysis . . . . . . . . . . . . . . . 169 Statistical Analysis . . . . . . . . . . . . . . 170 Results . . . . . . . . . . . . . . . . . . . . . . . 170 iv TABLE OF CONTENTS - continued Mutatox® . . . . . . . . . . . . . . . . . . . . 17o Ames Assay . . . . . . . . . . . . . . . . . . . 171 H4IIE Assay . . . . . . . . . . . . . . . . . . 174 Discussion . . . . . . . . . . . . . . . . . . . . . . 174 Acknowledgements . . . . . . . . . . . . . . . . . . . 182 Literature Cited . . . . . . . . . . . . . . . . . . . 183 SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Table Table Table Table Table Table 1. 2. LIST OF TABLES Non-polar organic compounds waters. water partition AQUIRE database were used to calculate estimated organic carbon partition coefficients (Koc) with analyzed for and present in Grand Calumet River sediments and pore Measured (M) or estimated (E) octanol- from the coefficients the following equation: 0.983 10910 Kow (27) Measured concentrations uQ/L- non-polar in sediment (BS), mg/kg, and pore waters ( PW, Cp), "dissolved" Calculated loglo Koc = 0.00028 4- organic chemical (NPOC) Grand Calumet River bulk (K pore water NPOC concentrations (PW, Cd) are reported as ug/L and ow) sediment TOC and pore water DOC are reported as % respectively dry wt. and mg/L Loglo apparent field partition coefficients, (Csoc/Cp); actual field partition coefficie theoretical KP! (Cece/Cd) sediments and pore waters I and EB; partition coefficients Kt (foc x Kow) for non-polar organic chemicals (NPOCs) measured in Grand Calumet River Organic compounds analyzed for but not detected in sediments or sediment pore waters from the The limit of detection is given for the matrix in which the compound was Grand Calumet River, not detected . IN. 0 0 Concentrations of organic chemicals in bulk or whole sediments from the Grand Calumet River, IN. Results are reported as mg/kg dry wt., except for (% dry wt.) and organic carbon, oil and grease 2,3,7,8-dibenzo—p-dioxin (pg/kg) Concentrations of waters of sediments River, IN. organic chemicals from the Grand Calumet in pore Results are reported as pg/L, except for total inorganic and organic carbon, which are reported as mg/L vi 23 25 31 70 73 79 LIST OF TABLES - continued Table 7. Concentrations of metals and acid volatile sulphide (AVS) in sediments from the Grand Calumet River, IN. Results are reported as gm/kg dry wt., except AVS, which is reported as pM S/gm dry wt . . . . . . . . . . . . . . . . . . . . . . . . . 84 Table 8. Total concentrations of metals (mg/L) in pore waters of sediments from the Grand Calumet River, IN 0 O O O O O O O O O O C O O O O O O O O O O O O O O O 87 Table 9. Concentrations of miscellaneous chemical compounds in pore waters of sediments from the Grand calumet River, IN 0 O O O O O O O I O O O O O O O 91 Table 10. Results of toxicity tests conducted with bulk sediments or pore waters of sediments from the Grand Calumet River, IN. All data are expressed as either % pore water, or % response (e.g. Q; tentans inhibition of dry wt gain relative to control) . . . . . . . . . . . . . . . . . . . . . . . . 94 Table 11. Calculated and neasured pore water toxic units (TU) for selected parameters based on pore water chemical concentrations and 15-min ECSO values from Microtox'ID tests of pore waters and pure chemicals. Microtoxo tests were osmotically adjusted with NaCl . . . . . . . . . . . . . . . . . . . 98 Table 12. Calculated and measured pore water toxic units (TU) for selected parameters based on pore water chemical concentrations and 48 h L050 values from D. magna and C. dubia acute toxicity tests of pore waters and pure chemicals . . . . . . . . . . . . 100 Table 13. Results of routine chemical analyses of sediment pore waters from the Grand Calumet River-Indiana Harbor Canal IJC AOC tested in 48-h acute assays with Q; magna and g; dubia. Maximum measured pH, conductivity, hardness and alkalinity are reported from the 100% pore water exposure treatment for each location, as well as calculated free 002 and HCO3' concentrations in vii Table Table Table Table Table Table 14. 15. 16. 17. 18. 19. pore water based on measured pH, temperature (25°C) from the cladoceran assays Toxicity to Q; magna and g; dubia of Na+ as NaCl or NaHCO3 and of HCO3- as NaHCO3 Results of X—ray microanalysis experiments with Values reported are mean each 2; = 0.05) Variance analysis data Results of Ames and Mutatoxo assays of organic solvent extracts of sediments from the Grand Calumet River and Indiana Harbor, without were Pearson product moment correlation coefficients from analyses of Ames assays with S9 activation and organic chemical analyses of sediment from Correlations tested ma na. ratios for component of with activation in both assays variance and experimental Significant treatment effects the Grand Calumet River, reported were statistically significant at p s 0.05 TCDD-EQ from the H4IIE assay in comparison to TCDD-EQ based on measured concentrations of total PCBs (as Aroclor 1248) and TCDD in bulk sediments from the Grand Calumet River and Indiana Harbor, IN C 0 viii analyses of O IN. of LIST OF TABLES - continued IN. S9 results X-ray microanalysis alkalinity, (SD) treatment. (indicated with asterisk) for elemental P/B ratios were based on a significant ANOVA for the individual element (a followed by Bonferroni indicated a significant difference from either the control or lowest experimental treatment and P/B t-test which from Extracts metabolic 130 136 140 142 172 175 176 Figure 1. Figure 2. Figure 3. Figure 4. Figure 5. LIST OF FIGURES Sampling locations in the Grand Calumet River and Indiana Harbor, Indiana . . . . . . . . . . . Loglo Kt, (f0C x Row), versus loglo apparent field . (CSochC/C ), for all non- polar organic compoun s analyzed for and present in Grand Calumet River sediments and pore waters. The relationship between Kt and KP. data is plotted (dashed line) and shown in the equation while the solid line represents a theoretical relationship with r = 1.0 . . . . . . . . . . . . . . . . . Loglo Kt (foc x K ow)' versus loglo apparent field Kp. (Csoc/Cplh for all non- polar organic compounds Wit loglox ow values <3. 0 analyzed for and present in Grand Calumet River sediments and pore waters. The relationship between Kt and data is plotted (dashed line) and shown in t e equation while the solid line represents a theoretical relationship with r = 1.0 . . . . Loglo Kt (foc x Kow), versus loglo apparent field . (Csoc/C) for all non-polar organic compounds wit tfi.loglox Kow values >3. 0 analyzed for and present in Grand Calumet River sediments and pore waters. The relationship between Kt and data is plotted (dashed line) and shown in t e equation while the solid line represents a theoretical relationship with r = 1.0 . . . . Loglo Kt, (foc x Kow), versus loglo apparent field KP. (Cece/Op)! open squares) and actual (Cece/Cd)' closed squares) for all non-polar organic compounds ‘with loglo Kow *values >3.0 analyzed for and present in Grand Calumet River sediments and pore waters. The equation in the upper left corner presents the relationship between Kt and K for these compounds while the equation in the Tower right corner presents the relationship between Kt and Kp. . . . . . . . ix 0 17 39 4O 42 Figure Figure Figure Figure Figure 7. 10. LIST OF FIGURES - continued Log10 KtI (fo (Cage/Cd)! Comparative triangles), C apparent field K . , P (closed Circles), Socha (CSOC and squares) and Oliver (29, (foc x Kow), for all non-polar organic compoun s analyzed for and present in Grand Calumet River sediments and pore waters versus X Kow). /Cp) data from this study Kadeg and Pavlou open Carpenter open diamonds) 10910 I versus (23, open Sampling locations in the Grand Calumet River and Indiana Harbor, Comparative osmotic . e Microtox Indiana effects of adjustment on assays of study site pore waters NaCl lS-m ECSO versus values sucrose for Sampling locations in the Grand Calumet River and Indiana Harbor, Indiana 0 43 44 62 96 164 GENERAL INTRODUCTION Many rivers, harbors and connecting channels of the Great Lakes have sediments which contain a wide array of chemical compounds, including organic xenobiotics (Pranckevicius 1986, Fallon and Horvath 1985) and metals (Pranckevicius 1986, Fallon and Horvath 1985, Hamdy and Post 1985). Due to municipal, industrial and non-point source waste discharges and the tendency of many chemicals to become associated with sediments (Knight 1984, Cairns et al. 1984), contaminated sediments are particularly problematic near densely populated, industrialized urban areas, such as the area surrounding the Grand Calumet River-Indiana Harbor (GCR-IH) International Joint Commission (IJC) Area of Concern (AOC) in northwest Indiana. Rodgers et a1. (1985) have summarized the recent environmental status, relative to anthropogenically-introduced chemical contamination, in these area of the Great Lakes. The drainage basin of the Grand Calumet River comprises 43,000 acres within the Calumet Lake plain in northwest Indiana which have been greatly affected by development activities. The Calumet Lake plain occupies an area of low relief which historically was formed by the bottom of Lake Chicago and three subsequent lakes prior to the formation of Lake Michigan (IDEM 1988). High linear coastal sand dunes and many low beach ridges characterized the Grand Calumet River basin prior to the beginning of industrial development in the late 1800's. The wetland areas between the beach ridges has subsequently been filled with sand from the ridges and 2 dunes and slag from the area's many steel mills (Reshkin et a1. 1975, Hartke et a1. 1975). The hydrology of the Grand Calumet River basin is complex as a result of modifications which were initially begun by Indians living in the area (i.e. a channel to connect the Grand Calumet River with the river Draining Lake Calumet). Additional alterations in the hydrology of the basin were made by various local and federal agencies to facilitate industrial development and protect the water intake of Chicago (and southern Lake Michigan) from contaminants in the many municipal and industrial effluent discharges to the river. Surface water in the system may flow east toward the Marquette Park lagoons, west to the Mississippi River or north to Lake Michigan depending on the local weather conditions and municipal/industrial effluent discharge rates and volumes. Flow in the east branch of the Grand Calumet River may be comprised of up to 93 % municipal and industrial effluent whilezmunicipal.waste treatment effluent may account for 100 % of the flow in the west branch (U.S. EPA 1985, Crawford and Wangsness 1987). The direction of flow in the west branch also has been observed to change from 34 cfs to the east to 42 cfs to the west over a 24 hour period (IDEM 1988). The severely contaminated condition of the GCR-IH ADC is based on water quality problems with conventional pollutants, metals, and organic chemicals, contaminated sediments, impacted aesthetics and biota, and fish consumption advisories (IDEM 1988). The ADC covers the entire length of the east branch and the first two miles of the west branch of the Grand Calumet River, the Indiana Harbor Canal, Indiana Harbor and the Lake Michigan nearshore zone of the harbor. The presence of a wide variety of in-place chemical contaminants in 3 sediments from the ADC and their potential effects on benthic macroinvertebrate populations were the primary focus of this study. A wasteload allocation study of the Grand Calumet River conducted by HydroQual, Inc (1984) identified the presence of numerous priority pollutants in sediments from 10 sampling locations within the GCR-IH system. Concentrations of 13 metals (As, Cd, Cr, Cu, Pb, Hg, Ni, Ag, Se, Zn, Sb, Be, T1) and cyanide were analyzed with increased concentrations of at least one metal (generally more than one) or cyanide observed in each of the 10 samples. Concentrations of 21 pesticides were generally below 0.05 pg/g and were always below 5.0 pg/g. Various PCB Aroclors (1016, 1221, 1232, 1242, 1260) also were present at concentrations below 1.0 pg/g although Aroclors 1248 and 1254 were present at concentrations as high as 17.0 and 6.9 pg/g, respectively. Forty-seven base neutral priority pollutants also were analyzed and concentrations of 24 of these generally observed to be below 0.025 yg/g. Nine of the remaining base neutral compounds exhibited concentrations > 100 pg/g in sediment from at least one location" These nine compounds were polynuclear aromatic hydrocarbons (PAHs) with maximum observed concentrations in sediments collected from locations adjacent to steel mill effluent discharges. High concentrations of other base neutral compounds also were observed near a municipal wastewater treatment plant effluent discharge. Comparison of the results of the sediment chemical analyses conducted by HydroQual, Inc (1984) with results from earlier studies demonstrated little change in concentrations of chemicals in sediments from the Grand Calumet River (HydroQual, Inc. 1984). Previous assessments of the effects of chemicals in the water column and sediments of the GCR-IH AOC on indigenous fauna have relied heavily on 4 surveys of benthic macroinvertebrate and fish community structure (U.S. EPA 1985, Polls and Dennison 1984, U.S. ACOE 1985, 1986). Effects on plankton (Cook 1966, Gannon and Beeton 1969) and other wildlife, including birds and mammals (U.S. ACOE 1985, 1986), also have been conducted on a limited basis. Elevated contaminant levels in sediment and water have been implicated in the lack of aquatic and terrestrial organisms in the GCR-IH system (IDEM 1988). Sediments from Indiana Harbor and Canal have been demonstrated to be toxic to benthic macroinvertebrates during laboratory sediment toxicity tests (Gannon and Beeton 1969, U.S. ACOE 1987). Concern also has been raised over the potential for bioaccumulation of metals and organic chemicals by terrestrial species if harbor sediments were dredged and moved to an upland disposal site (U.S. ACOE 1987). To date, however, no such comprehensive sediment toxicity evaluations have been conducted on sediments collected from the east and west branches of the Grand Calumet River. Any meaningful assessment of sediment contamination and toxicity in the GCR-IH system must include an evaluation of the contaminant-associated toxicity of sediments to aquatic life including benthic macroinvertebrates. The data needed (and which is currently lacking) for such an assessment includes synoptic measures of chemical concentrations in sediments and interstitial (pore) waters, physical characteristics of the sediments (particle size, total organic carbon, etc) and measures of sediment and interstitial water toxicity to relevant benthic test species (U.S. EPA 1985). Currently, great interest also exists among regulators, legislators and the scientific community in the development of sediment quality criteria (Shea 1989). Numerous approaches have been proposed for the development of criteria (Anonymous 1985), including' the: use of the equilibrium partitioning theory (Pavlou 1987). Empirical observations from various studies (Adams et al. 1985, Ziegenfuss et al. 1986, Adams 1987, Connell et al. 1988, Lake at al. 1990 Swartz et al. 1990) support the hypothesis that neutral organic chemical bioavailability, toxicity and bioaccumulation are more closely related to pore water chemical concentrations of contaminants than to total (bulk) sediment concentrations. These observations engendered and continue to fuel the interest in the equilibrium partitioning theory as a mechanism for predicting potential exposure to, or bioaccumulation of, contaminants by benthic biota. The information presented above led to the selection of the GCR-IH AOC as a study area for the evaluation of the usefulness of several alternative invertebrate and microbial assays for the comparative assessment of sediment and/or sediment pore water toxicity and mutagenicity. The specific objective of chapter one was to conduct a field evaluation of the equilibrium partitioning theory and the ramifications of non-polar organic compound binding to dissolved organic carbon relative to the development of sediment quality criteria using the equilibrium partitioning theory. Chapter two presents comparative toxicity data from four toxicity tests commonly used to assess sediments or sediment pore waters. It also tests the hypothesis that the toxicity of sediment pore waters can be predicted based on toxic units calculated from laboratory-derived, chemical-specific dose response relationships. Chapter three examines the toxicity of bicarbonate ion to the cladocerans Daphnia magna and Cerioda hnia dubia, evaluates the potential for bicarbonate toxicity in sediment pore waters and presents a potential 6 mechanism for the observed effects produced by the bicarbonate ion. The final chapter presents a comparative evaluation of several different assays for determining effects, other than acute toxicity, which may be linked to exposure to contaminated sediments. Literature Cited Adams, W.J., R.A. Kimerle and. R.G. Mosher. 1985. .Aquatic safety assessment of chemicals sorbed to sediments. In, my; Toxicolo and Hazard Assessment, ASTM STP 854, R.D. Cardwell, R. Purdy and R.C. Bahner, Eds. American Society for Testing and Materials, Philadelphia, PA. pp. 429-453. Cairns, M.A., A.V. Nebeker, J. H. Gakstatter and W. Griffis. 1984. Toxicity of copper-spiked sediments to freshwater invertebrates. Environ. Toxicol. Chem. 3:435-446. Connell, D.W., M. Bowman and D.W. Hawker. 1988. Bioconcentration of chlorinated hydrocarbons from sediment by oligochaetes. Ecotoxicol. Environ. Safety 16(3):293-302. Cook, G. 1966. Report on the Calumet area surveillance program for June- November-l969, Illinois-Indiana. In, Conference in the gatte; of Pollution of the Interstate Waters of the Grend Calumet Riveg, Little Calumet Riveg. Wolf Lakel Lake Miehigen eng Thei; Tributaries. Federal Water Pollution Control Administration, Chicago, IL. pp. 22—105. Crawford, G.C. and D.J. Wangsness. 1987. Streamflow and Water Quality of the Grand Calumet RiverJ Leke County, Indiana and Cook County. Illinoie. October 1984. Water—Resources Investigations Report 86-4208, U.S. Geological Survey, Indianapolis, IN. 137 p. Fallon, M.E. and F.J. Horvath. 1985. Preliminary assessment of contaminants in soft sediments of the Detroit River. J. Great Lakes Res. 11:373-387. Gannon, J.E. and A.M. Beeton. 1969. Stud'es on the f c s a ls from Selected Great Lakes Harbors on Plan 0 n Benthos. Center for Great Lakes Studies, University of Wisconsin-Milwaukee. 82 p. Hamdy, Y. and L. Post. 1985. Distribution of mercury, trace organics and other heavy metals in Detroit River sediments. J. Great Lakes Res. 11:353-365. Hartke, E.J., J.R. Hill and M. Reshkin. 1975. Environmengel Geelogy of Lake and Porter Counties. Indiana - en Aid to Planning. Indiana Department of Natural Resources, Geological Survey Special Report II. Bloomington, IN. 57 p. HydroQual, Inc. 1984. Grand Calumet River Wasteload Allece§iog §§ggy. Mahwah, NJ. 188 p. Indiana Department of Environmental Management. 1988. Northwest Indiana Environmental Action Plen. Draft Area of Concern Remedial Action Plan. IDEM, Indianapolis, IN. 183 p. Knight, A.W. 1984. The Evaluation of Contaminated Sediment o §elected Benthic Freshwate; Invertebrates. Final.Report, U.S. Environmental Protection Agency Cooperative Agreement No. CR- 808424. U.S. EPA, Environmental Research Laboratory, Corvallis, OR. Lake, J.L., N.I. Rubinstein, H. Lee II, C.A. Lake, J. Heltshe and S. Pavignano. 1990. Equilibrium partitioning and bioaccumulation of sediment-associated contaminants by 9 infaunal organisms. Environ. Toxicol. Chem. 9:1095-1106. Pavlou, S.P. 1987. The use of the equilibrium partitioning approach in determining safe levels of contaminants in marine sediments. In, Fate and Effects of Sediment-Bound Chemicals in Ageatic §ysteme, K.L. Dickson, A.W. Maki and W.A. Brungs, Eds. Pergamon Press, Elmsford, NY. pp. 388-412. Polls, I and S. Dennison. 1984. Biolo ical and Chemical Wate a1 t Seggev in Indiana Harbor Canal and Southwestern Lake Michigan for the U.S. Army Corps of Engineers. Chicago District. Metropolitan Sanitary District of Greater Chicago, Chicago, IL. 88 p. Pranckevicius, P.E. 1986. 1982 Detroit Michigan Area Survey. EPA Report No. 905-4-86-002, U.S. Environmental Protection .Agency, Chicago, IL. Rodgers, P.W., M.S. Kieser and G.W. Peterson. 1985. Su e Exieting Status of theegpper Great Lakes Connecting cgaggele QEEQ- Limno-Tech, Inc., Ann Arbor, MI. Shea, D. 1988. Developing national sediment quality criteria. Environ. Sci. Tech. 22:1256-1261. Swartz, R.C., D.W. Schults, T.H. DeWitt, G.R. Ditsworth and J.O. Lamberson. 1990. Toxicity of fluoranthene in sediment to marine amphipods: a test of the equilibrium partitioning approach to sediment quality criteria. Environ. Sci. Tech. 9:1071-1080. U.S. Army Corps of Engineers. 1985. Great Lekes Connecting Channele end fleebors. Draft Final Feeeibilitv Report end Environmental ‘— Impact Statement. U.S. ACOE, Detroit, MI. 228 p. 10 Army Corps of Engineers. 1986. Indiana Harbor Confined Dieegeel Eecilitv end. Maintenance Dredging. Lake County. Indiana. Qraft Environmental Impact Statement. U.S. ACOE, Chicago, IL. 78 p. Army Corps of Engineers. 1987. Disposel Alternative for PCB- Qontaminated Sediments from Indiana Harbor, Indiana. U.S. ACOE, Waterways Experiment Station, Vicksburg, MS. 211 p. Environmental Protection Agency. 1985a. Master Plan for Impgevieg WeeereQuality in the Grand Calumet RiverjIndiana Harbor Canal. U.S. EPA, Chicago, IL. 149 p. Environmental Protection Agency. 1985b. Sediment Quality Critegia Qeyelopment Workshop. U.S. EPA, Office of Water Regulations and Standards, Criteria and Standards Division, Washington, DOC. Ziegenfuss, P.S., W.J. Renoudette and W.J. Adams. 1986. Methodology for assessing the acute toxicity of chemicals sorbed to sediments: testing the equilibrium partitioning theory. In, Ageatic Toxicology end Environmengel Fate, ASTM STP 921. American Society for Testing and Materials, Philadelphia, PA” pp. 479- 493. CHAPTER 1 A Field Evaluation of Equilibrium Partitioning in Sediments from the Grand Calumet River and Indiana Harbor, Indiana 11 Introduction Currently, great interest exists among regulators, legislators and the scientific community in the development of sediment quality criteria (1). Numerous approaches have been proposed for the development of these criteria (2), including the use of the equilibrium partitioning theory (EqP) (3,4). Empirical observations from various studies (4-10) support the hypothesis that non-polar organic chemical (NPOC) bioavailability, toxicity and bioaccumulation are more closely related to pore water (interstitial water) or organic carbon-normalized bulk sediment chemical concentrations of contaminants than to total (bulk) sediment concentrations. These observations engendered and continue to fuel the interest in the EqP as a mechanism for predicting potential exposure to, or bioaccumulation of, NPOCs by benthic biota. The equilibrium partitioning theory predicts contaminant bioavailability in pore water by assuming that a thermodynamic equilibrium is established between the solid phase sediment and pore water concentrations of NPOCs (4). According to the theory, pore water concentrations and tissue residues of these compounds should be predictable based on the bulk sediment concentration of the compound and the physical and chemical properties of the sediment and compound of interest (3,4,11). For NPOCs, the equilibrium concentration in pore water is a result of partitioning between the solid and dissolved phases. This partitioning 12 13 process is primarily controlled by the concentration of the NPOC of interest in the bulk sediment, the fractional organic carbon content of the sediment and the proportionality constant for distribution of the NPOC between water and organic matrices. This constant is approximated by the octanol-water partition coefficient (K for the compound of interest ow) (4,11). It should theoretically be possible to estimate the pore water concentration of a neutral organic chemical based on ‘the following relationship between the solid (bulk) phase and pore water concentrations, C8 and Cp, respectively (Equation 1), Cs 2 foc Kow Cp (1) where foc = fractional organic carbon content of the sediment and Kow = the octanol-water partition coefficient for the chemical of concern. If C is defined as the solid phase concentration of the NPOC of soc interest normalized to the fractional organic carbon content of the sediment (Equation 2), CSOC z foc (2) then the concentration of NPOC in the pore water can be estimated from the concentration in the bulk sediment normalized to the fractional organic carbon content of the sediment and the Kow for the NPOC (Equation 3). p 0.. (3) However, determination of chemical concentrations in pore'water, and thus quantification of potential chemical exposure via one of the major exposure routes for benthic organisms in contaminated sediments (5,12,13), may not be this simple. Numerous authors have proposed that a third phase, dissolved organic carbon (DOC), plays an important role in the partitioning behavior of NPOCs with a 10910 Kow > 3.0 (14-20). Because DOC complexation is related to NPOC hydrophobicity, complexation will increase with an increase in the Kow' and thus Koc and KDOC' of the NPOC. This phenomenon will result in a greater total concentration of NPOC in the pore water than would be estimated from equation 3. An in-depth discussion of the ramifications of DOC-binding of NPOCs in sediment pore water is presented by DiToro et a1. (4). The essence of the problem, however, involves the distribution of measured NPOC concentrations in pore water, i.e., what proportion of the total NPOC concentration is "dissolved" or "free" and what proportion is bound to DOC. This distinction is important because NPOC complexed to DOC may be partially or totally unavailable to cause effects on biota (21-22). Thus "dissolved" NPOC concentrations in pore water may most accurately reflect the true chemical exposure for benthic biota. The relative concentrations of free and bound, soluble NPOC in pore water should be related to the organic carbon-normalized sediment concentration (Csoc) (Equations 4-6): ow p (4) 15 and, Cd = C (6) 1 + mDoc KDoc if, Cd = "dissolved" NPOC concentration in pore water CDOC = DOC-bound NPOC concentration in pore water mDOC = DOC concentration in pore water KDOC = DOC partition coefficient for NPOC Knowledge of these values would permit an initial examination of the potential importance of DOC-binding of NPOCs in the field and provide a better understanding of the potential problems in the application of EqP for the development of sediment quality criteria. If EqP can be verified, sediment quality criteria could be developed by applying water quality criteria to chemical concentrations in pore water and back-calculating permissible sediment concentrations based on sediment organic carbon content. This method of developing sediment quality criteria is frequently referred to as the equilibrium partitioning theory/water quality criteria (EqP/WQC) approach. To date, attempts to verify EqP have been restricted to laboratory evaluations of the behavior of a few NPOCs in sediments containing a limited range of organic carbon concentrations (8,10) or field evaluations with an equally restrictive number of compounds and sampling locations (9,11,23). The objective of this study was to measure bulk sediment and pore water concentrations of a suite of NPOCs in samples collected from 10 16 locations on the Grand Calumet River near Gary, IN and to evaluate the potential ramifications of DOC-binding of NPOCs on the EqP by examining two general types of field data: 1) apparent versus estimated theoretical partition coefficients for NPOCs as a direct test of the Csoc = Kow CP relationship, independent of DOC and 2) actual versus estimated theoretical partition coefficients for NPOCs when DOC-binding is accounted for by using the relationship Csoc = Kow (Cd + CDOC” Materials and Methods Chemical Analysis Sediment samples were collected with a Ponar grab sampler from 10 locations along the Grand Calumet River in the northwestern corner of Indiana (Figure 1) between 1 September 1988 and 1989. The sample from each location was a composite of approximately 80-100 L of wet sediment from multiple Ponar grabs. Each sample was placed in coolers or plastic buckets lined with food-grade plastic bags, immediately transported to the laboratory and placed in 4°C storage. Sediment samples were dried and percent moisture determined for each sample. Ten grams of dried sample were mixed with 10 g of anhydrous sodium sulphate and Soxhlet extracted for 24 h with pesticide-grade acetone/hexane (1:1, v/v). The extract was passed over a drying column containing anhydrous sodium sulphate and the column rinsed with approximately 100 ml of the acetone/hexane 1mixture to complete ‘the transfer. The extract was transferred to a Kuderna-Danish concentrator and extract volume reduced to 1 ml. The final extract volume was adjusted to 10 ml with the acetone/hexane mixture. These procedures and all other l7 mcmwpcm .uonumm mcmecH pom um>em usesamo pcmuo one as mcoflumooH ocHHQEmm 1|..in 222. o... 3 00 Sex Ewen—mo pesto I‘ll/‘2) no: 0.: 0.2 at e: 0.2 . e. ox \/\> m=o=:=_ 18 aspects of sediment sample preparation followed U.S. EPA,Method 3540 (24). Pore waters were prepared by centrifuging 275-325 g of wet sediment in acid-rinsed 250 m1 polycarbonate centrifuge tubes for 45 min at 6800 xg. Supernatants were filtered though a Whatman glass fiber filter (GF-F, 0.7 p nominal pore size) in a Millipore stainless steel filtering funnel. Multiple centrifuge tubes were necessary to provide sufficient sample volume for all analyses. One liter of filtered pore water was collected, preserved with 5 ml/L of a 1 g/L solution of HgClz to prevent microbial degradation, and stored in the dark at 4°C until required for analysis. One liter of pore water was adjusted to a Ph of >11 with concentrated NaOH, extracted with three successive 60 ml portions of pesticide-grade)methylene chloride in a separatory funnel and the extracts combined for analysis of NPOCs. If a large emulsion was observed, continuous liquid-liquid extraction was used to complete the sample extraction. Extracts were passed over an anhydrous sodium sulphate drying column and reduced to 1 ml in a Kuderna-Danish concentrator. Final extract volumes were adjusted to 10 ml with methylene chloride. Pore water extraction followed the protocols outlined in U.S. EPA Method 3510 or, for emulsions, U.S. EPA Method 3520 (24). Cleanup procedures for both sediment and pore water extracts followed the protocols outlined in U.S. EPA Methods 3620, 3630 or 3660 (24) and were dictated by the class of compounds quantified in subsequent analyses. Identification and quantitation of chemical analytes were performed with gas chromatography/mass spectroscopy (GC/MS) techniques. U.S. EPA 600 Series methods (25) were used for CC analyses while compound confirmation was conducted with U.S. EPA GC/MS Methods 8240 and 8250 (24). GC/MS operating conditions were as follows for all analyses: electron 19 energy 70 eV, mass range 35-550 amu, scan time 1 sec/scan, transfer line temperature 250°C, source temperature 200-250°C, injector temperature 250- 350°C, injector on column or Grob splitless, sample volume 1 p1 and carrier gas He at 15 psi. Analytical detection limits for all analysis have been presented elsewhere (26). Bulk sediment and pore water chemical concentrations are reported as mg/kg and pg/L, respectively. Bulk sediment total organic carbon (TOC) was measured with a LECO carbon analyzer dry combustion technique and the results reported as 8 TOC on a dry wt. sediment basis. Dissolved organic carbon (DOC) in the pore water was operationally defined as the material passing a 0.7 pm filter and was measured with an IO Corporation, Inc. Model 700 TOC analyzer after sample acidification. Pore water DOC is reported on a mg/L basis. Equilibrium Partitioning Calculations Apparent partition coefficients, Kp', for NPOCs were calculated from measured chemical concentrations (Equation 7): Kp = Csoc (7) Cp where: CSOC = C8 foc while actual partition coefficients K were calculated from Equation 8, P: p soc (8) where: Cd = Cp 1 + mDoc KDoc and; Cp = measured total NPOC concentration in pore water C8 = measured NPOC concentration in bulk sediment CSOC = organic carbon-normalized NPOC concentration in bulk sediment f0c = decimal fraction organic carbon in bulk sediment Cd = calculated dissolved NPOC concentration in pore water mDOC = measured DOC concentrations in pore water KDOC = DOC partition coefficient for NPOC Theoretical partition coefficients, Kt were calculated*with the fractional organic carbon content of the sediment and the Kow for the NPOC of interest (Equation 9). Kt = foc Kow (9) For all NPOCs, the loglo Koc (i.e., pKOC) was calculated (Equation 10) [27]. loglo Koo = 0.00028 + 0.983 loglo K (10) CW 21 Measured pKow values, if available, were used in all calculations of pKoc. Estimated pKow values were used if necessary, however, all values, either measured or estimated (Table l), were obtained from the AQUIRE database (28). In calculations of potential DOC-binding by NPOCs and dissolved NPOC concentrations in pore water, KDOC was assumed to be equal to Koc' Results A total of 29 NPOCs analyzed for were present in both Grand Calumet River bulk sediments and pore waters (Table 1). Measured or estimated pKow values from AQUIRE and calculated pKoc values for each chemical also are reported in Table 1. As a point of interest, the original organic chemistry analytical suite for both bulk sediments and pore waters was composed. of 106 discrete compounds (26). The compounds ‘present in sediments and pore waters from the study area included phenolic compounds, industrial solvents and degreasers, pesticides and polycyclic aromatic hydrocarbons (PAHs). The concentrations of 29 NPOCs which were present in both bulk sediment and pore water samples from the study area are presented in Table 2. TOC and DOC concentrations in bulk sediment and pore water, respectively, are presented in Table 2, as well as calculated ”dissolved" concentrations of the 29 NPOCs in pore water. Measured concentrations of the NPOCs in bulk sediment ranged from 10 pg/kg for tetrachloroethylene to over 100 mg/kg for benzo(a)pyrene. Measured total concentrations of the NPOCs in pore water ranged from 0.1 pg/L for some of the chlorinated pesticides (p,p'-DDT, dieldrin, lindane, chlordane) and industrial chemicals (e.g., hexachlorobenzene) to greater than 450 pg/L for the PAH, 22 naphthalene. The pKt, which represents the loglo (f0c x Kow) was calculated for each NPOC and compared. with the ‘pK .,which represents the apparent P partition coefficient loglo (Csoc/Cp) between the organic carbon- normalized sediment and total pore water chemical concentrations and the pr, which represents the actual partition coefficient loglo (Csoc/Cd) based on the calculated "dissolved" chemical concentration in the pore water (Table 3). These results indicate that under the operationally defined conditions of KDOC = K0C and DOC = <0.7 pm, the binding of NPOCs to DOC was an important factor determining the distribution of NPOCs in pore waters from the Grand Calumet River. As the pKow of a compound increased, so did the importance of DOC-binding in determining the pore water distribution of a given NPOC. Di-octyl phthalate was the NPOC with the greatest pKow in the data set. Calculations based on measured total pore water DOC and di-octyl phthalate concentrations indicated that less than .01% of the measured total concentration of di-octyl phthalate in pore water (1.7-27.7 pg/L) was actually present as "dissolved", un-bound chemical. To assess the influence of DOC in the pore water on concentrations of all 29 NPOCs in pore water, pr. was plotted as a function of pKt (Figure 2). A similar relationship was developed for only those NPOCs with a measured or estimated pKow value <3.0 (Figure 3) or >3.0 (Figure 4). Each point with confidence limits represents the mean value i one standard deviation from 5-10 samples (see Table 3) for an individual chemical. Little relationship was observed between pr and pKt since pKt accounts for only approximately 9% (r=0.29, R=0.09) of the variance in 23 Table 1. Non-polar organic compounds analyzed for and present in Grand Calumet River sediments and pore waters. Measured (M) or estimated (E) octanol-water partition coefficients (Kow) from the AQUIRE database were used to calculate estimated organic carbon partition coefficients (Koc) with the following equation: loglo Koc = 0.00028 + 0.983 10910 Kow (27). Compound CAS No. 10910 Kow (M/E) loglo Koo Phenol 108-95-2 1.46(M) 1.44 2,4-Dinitrotoluene 121-14-2 1.98(M) 1.95 1-Chloro-2-nitrobenzene 88-73-3 2.24(M) 2.20 1,2,3-Trichloropropene 96-19-5 2.36(E) 2.32 1,1,1-Trichlorethane 71-55-6 2.49(M) 2.45 Chlorobenzene 108-90-7 2.84(M) 2.79 Styrene 100-42-5 2.95(M) 2.90 Ethylbenzene 100-41-4 3.15(M) 3.09 Naphthalene 91-20-3 3.30(M) 3.25 p-Chlorotoluene 106-43-4 3.33(M) 3.28 o-Dichlorobenzene 95-50-1 3.38(M) 3.33 Tetrachloroethylene 127-18-4 3.40(M) 3.35 Lindane 58-89-9 3.61(M) 3.55 Biphenyl 92-52-4 4.09(M) 4.02 Dieldrin 60-57-1 4.32(M) 4.25 Phenanthrene 85-01-8 4.46(M) 4.39 Heptachlor 76-44-8 4.61(E) 4.53 Pentachloronitrobenzene 82-68-8 4.64(M) 4.56 Table 1. (cont.) 24 Compound CAS No. 10910 Kow (M/E) loglo Koc Pyrene 129-00-0 4.88(M) 4.80 Fluoranthene 206-44-0 4.95(E) 4.87 Pentachlorophenol 87-86-5 5.24(M) 5.15 Hexachlorobenzene 118-74-1 5.31(M) 5.22 Chlordane 57-74-9 5.54(E) 5.45 Chrysene 218-01-9 5.66(E) 5.57 Benzo(a)anthracene 56-55-3 5.66(E) 5.57 Benzo(a)pyrene 50-32-8 5.97(M) 5.87 p,p'-DDT 50-29—3 6.36(M) 6.25 p,p'—DDE 72-55-9 6.51(M) 6.40 Di-octyl phthalate 117-81—7 8.71(M) 8.56 25 o.mm m.mH v.v~ m.ha v.m m.Hm m.m o.oH m.m N.HH 60 3a H.0m o.mm m.~m m.mm m.mH N.mm m.o N.MH N.¢ m.va mo 3m we.o me.m -.H eo.m He.o am.m mH.o mq.H AN.H om.o mm uscmcaam m.mmm N.®Nm m.mNN 0.50H H.hom 0.0mm m.hm m.oma n.0m H.0NN CU 3m m.mmm m.omm m.mmm m.noH a.nom o.wmm m.>m m.mmH m.om H.mmm do So OH.m no.0 Hm.o mm.a em.o mo.v mm.o mv.o mm.o mm.o mm Hocmcm n.o m.m n.~ m.m m.H m.H m.o m.H v.H m.m p0 3m m.vm m.wH m.vH m.NH m.HH m.ma m.m o.ofl ¢.o m.ma QU 3m mm.v mo.m vo.m mo.m OO.N om.v no.0 mo.N Ho.v 0H.N mm HocmnmouOHnumucmm Ema ozwm Tam 9mm 73 0.3 New NSm mam men do 335 com e.mH w.ma m.mm >.va m.mH m.va m.ma m.> v.v H.mm mm Au3 who we OOH OHIUD mIOD mIUD >103 QIOD mIOD v10: MIOD NIOD HID: umumEmumm uwnESZ COHumoOA um>em umEzamU pcmuo .>Hm>fiuummmwu .A\mE pom .u3 >up w mm pmuuommu mum UOQ umum3 whom ppm 008 ucmeflpwm pcm q\01 mm pmusommu mum .po .zmv mc0aumuucmocou UOmz umum3 whom =pm>aommepz pmumHsonu .Ammv ucwEMpmm xasn um>qm amasamo pcmuu ca mcowumuucmucoo Auomzv amusemcu oscmouo umaomncoc pwusmmwz .A\ml .AQU .zm v mumumB upon new .mx\mE .m magma 26 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 do 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 00000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000-.0.0 .. 0000.0 0000.0 u- in 0000.0 0000.0 u- 0000.0 0000.0 00 30 n- 0.0 0.0 -- i- 0.0 0.0 in 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000-.0.0 00.000 00 000 0 000 00.000 00.000 00.00 00.000 00.000 00.00 00.000 00 30 0.000 0.000 0.000 0.000 0 000 0.00 0.000 0.000 0.00 0.000 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 00000000002 00.0 00.0 00.0 00.0 I- 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 0.0 I- 0.0 0.0 0.0 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 0:00:0nouo0nu0x00 00-00 0:00 0:00 0:00 0:00 0:00 0-00 0-00 0-00 0-00 000020000 umbEsz codumuoa um>0m umESHmo pcmuo 0.00000 .0 00000 27 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 0000000000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 0000000000 00.0 00.0 00.0 - - I- 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 - - - 0.0 0.0 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000000000 00.0 - 00.0 00.0 - 00.0 I- I- I- 00.0 00 30 0.0 - 0.0 0.0 - 0.0 - - - 0.0 00 20 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 0000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 00-00 0-00 0-00 0-00 0-00 0-00 0-00 0-00 0-00 0I00 000000000 “@3552 COHUflUOQ H0>Hm HOESHMU UCflHU 0.0000. .0 00000 28 009652 c00u0000 um>0m umESHMU 6:000 v.N m.m 0.0 «.0 0.0 m.o 0.0 «.0 «.0 0.0 no km 00.0 No.0 I: «0.0 00.0 I: 00.0 I: II «0.0 mm 0c00>£u00000numuume mm.>0 mm.m0 mh.m hm.0 mo.m 0N.M0 om.0 m>.m oo.m O0.m 00 Ba m.h0 o.m0 m.m 0.0 m.m m.M0 m.0 m.m 0.m N.m mo Sm mm.o 00.0 mm.0 00.0 mo.o mw.o mv.o >>.N 00.0 hH.v mm wcmu>um om.00 m0.m0 ma.w 00.00 0v.o mo.00 mm.o mn.m Nb.N hm.m U0 3m N.N0 w.m0 m.m m.00 m.o m.m0 ¢.o m.m m.m m.m Q0 3m mm.00 mo.o vm.0 oo.v m¢.v Ho.m vm.m Np.v hH.N ma.v mm mcmucwnaxnum I: I: mm.o I: II vm.o 00.0 mm.o mm.o 00.0 U0 3m :: m.o 0.0 I: I: 0.0 m.o 0.0 m.o N.o mu Sm 0m.m :: mv.0 mm.m 00.N 0m.m 00.0 mm.m o~.¢ om.m mm 0:00:000000no0ouo mm.m0 om.M0 0m.0m 0m.00 mm.v 0m.v0 00.0 00.00 mm.m 00.mm 00 km 0.0m 0.00 o.vm ¢.N0 v.m v.00 o.m 0.00 0.00 «.mm mo 30 hm.m 00.0 mm.b vm.00 mm.m mm.m or.m 00.0 mm.m m¢.0m mm mcms0ououo0no:m 00:03 0:03 0:03 0:0: 0:0: 0:0: 0:0: m:o: ~:0: 0:00 000020000 0.00000 .0 00009 29 00.0 00.00 00.00 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.00 0.00 0.00 0.0 0.0 0.00 0.00 0.00 0.00 0.00 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000000000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 20 0.00 0.00 0.00 0.0 0.0 0.00 0.0 0.0 0.0 0.00 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 00 30 mcmucmnouuflc 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 mm :00000000000 :: 0000.0 000.0 0000.0 0000.0 0000.0 ::.Nooo.o 0000.0 0000.0 00 30 0.0 0.0 0.00 0.0 0.m 0.00 0.0 0.0 0.0 0.0 00 30 :: 00.0 00.0 00.0 00.0 00.0 :: 00.0 00.0 00.0 00 000000000 00000:00 00.0 00.0 :: 00.0 0m.o :: 00.0 :: :: 00.0 00 30 00:00 0:00 0:00 5:00 0:00 mloa vuua mlwa NIUD 0:00 000080000 002632 00000000 00>0m 0050000 0:000 0.00000 .0 00000 3O 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.00 0.00 0.00 0.0 0.00 0.00 0.0 0.0 0.0 0.0 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000000000000000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.00 0.0 0.0 0.00 0.0 0.0 0.0 0.0 00 20 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 00000000 00.000 00.000 00.000 «0.00 00.00 00.00 00.00 00.000 00.00 00.000 00 30 0.000 0.000 0.000 0.00 0.00 0.000 0.00 0.000 0.00 0.000 00 30 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 000000000000 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00.0 00 30 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 00 30 00.00 00.000 00.00 00.0 00.0 00.00 00.0 00.00 00.00 00.00 00 00000000000000 00:00 0:00 0:00 0:00 0:00 0:00 0:00 0:00 0:00 0:00 000000000 002602 000u0000 00>0m 0080000 0:000 0.00000 .m 00009 31 no.0 mm.H mN.N Mb.H ov.H mm.H mo.N mw.N NH.N MN.N Ho.m mm.o ax mw.o mm.H ¢N.N H5.H mm.H om.H oo.N mm.N OH.N HN.N mm.N om.o ~mx MN.O mv.N m¢.N hm.N mo.N 5v.m Om.N mv.N O¢.N mH.N vm.H mh.N ox mamamcunmmz eh.o hm.¢ mm.m ¢¢.m mo.m mm.¢ II om.v 0N.v mo.m mm.m Hm.¢ QM mb.o Ho.m vm.m mm.~ Hm.N mb.m II hm.m Hm.m @N.¢ ON.m om.m .mx mN.o vv.v v¢.¢ mm.¢ mo.v mv.v II b¢.v H¢.¢ ha.¢ mm.m mh.¢ ox mcwucmnOHOHnomxmm Hh.0 H0.H hH.N 00.0 0N.H mm.a Hv.H ¢O.N om.H mm.H oo.N mH.H ax Hb.o HQ.H hH.N 00.0 0N.H mm.H fl¢.H ¢O.N mm.H mm.H oo.N MH.H ~Q¥ MN.O mm.o mm.o mu.o Hm.o no.0 00.0 No.0 mm.o mm.o OH.o Hm.o ox Hocwsm H¢.o mm.m oh.m bv.m ¢Q.m om.m mm.m wN.v mm.m ha.v Hw.¢ mv.n ax av.o NN.m mH.m hh.N om.N 5H.m mo.m ¢m.m mm.m m¢.m ma.¢ mh.m .mx MN.O hm.v hm.¢ Hm.v mm.¢ H¢.v v¢.v O¢.¢ ¢m.v OH.v mm.m mo.v ox Hocm£QOHOHnumucmm cm H x Caluo mIUD mIUD bio: oIUD mIUD «IUD MIUD NIUD HIUD uanUHmmwOU HmumEMHmm HWQEDZ GOHUMOO‘H Hm>flm “med-HMO UCMHU .mumumz whom 0cm mucmeflcmm um>wm umeaamo venue cw cmusmmme AmUOmz. mHMOfiEmso vacmmuo unaomlcoc yew Azox x UOMV ax mucmaowmwmoo noduauumm Hmoaumuomnu can Auo\oomov .mx mucmwowmumoo ceauauuum_caowu Hmsuom “Amo\uomuv .mx .mucmwowummoo acauwuummnvamwu ucmummmm oflmoq .m manna 32 mp.o -.e n¢.e m~.v ~m.n nu nu nn mm.~ mm.c oo.m pm.c umx m~.o om.< sm.v mm.v mm.v nn nn nn co.e o¢.v mH.e mm.¢ ox mcauuoaso o~.o nm.m Ho.¢ un m>.m H~.¢ nn mh.m nu nu nn ma.v ax Hm.o mm.m hm.m nn o>.m mH.¢ nn H>.m nn nn nn mo.¢ .mx vH.o mm.m «p.m nn om.~ mn.m nn hn.~ nn nn nn mo.m ox mcmccqq «H.H mm.m mH.¢ av.¢ ¢n.H m>.¢ mo.¢ mm.~ Hm.~ co.v mm.m h~.m ax mH.H no.m mo.v mm.¢ mm.H mo.v n>.¢ Fo.~ om.~ mm.m em.m oH.m .mx m~.o mv.m mv.m mm.m no.m m¢.m mm.m m¢.m me.m mfl.m om.m hn.m ox cwunamfla me.o om.m m~.m mm.m «H.m m¢.m ma.m mn.m mm.v ¢m.m mH.o «o.m ax mm.o mo.m ¢m.m mm.m pm.m Ho.m mm.m mo.m mo.m ~H.¢ mm.v ¢n.m .mx m~.o ¢m.m vo.m mh.m om.m mo.m an.m no.m Hm.m nm.m ma.m mm.m ox mann.m.m mm.o ¢>.m nn om.m «m.m nn nn m>.m vm.m un om.o mm.m ax mm.o mm.m nn mm.m m¢.m nn nn nb.m cm.v nu mH.m Ho.m .mx a~.o mm.m nu mo.m Hp.m nn nn mm.m ov.m nu oo.m Hm.m ox soon-m.m am a m oanus anus one: fine: onus mums «no: mums wuuo anon ucmfiofluumoo umumemumm umnszz cowumuoq um>wm umEaamo ncmuw .n odnma 33 m~.o m~.m m~.~ ~¢.~ om.~ mm.~ mm.~ Hm.m m~.~ Ho.~ mp.fl oo.~ ox ocmucmnaxnum ov.o ~m.e nn nn mo.¢ nn un mm.v v~.v eo.m mo.m mu.¢ mm oe.o mm.¢ nu nn mo.v nn nn mm.¢ mm.v Ho.m no.m H>.¢ .mx om.o hv.~ nn nn m>.~ nn nn em.~ m¢.m em.~ No.~ mm.m ox mcmucmnouoHnoqano o¢.o hm.m Hm.m mm.m om.~ >>.m mm.m mm.m mm.m mm.m oH.v em.m mm o¢.o qm.m mm.m om.~ mn.m m>.m m>.m em.m om.m om.m mo.e mm.m .mx mm.o o¢.~ oe.m oo.~ mm.m om.m mm.m mv.~ mv.m ma.~ hm.H mp.~ ox mcmsaououoHnonm oo.o mm.e ¢m.m Ha.v Ho.v mm.m HH.¢ mh.m hm.m mm.¢ mn.m mm.m ax 00.0 >~.¢ «m.n oH.e Ho.¢ hm.m mo.¢ fib.m no.m mo.¢ mh.m mm.m .mx m~.o >m.a hm.a HH.~ mfl.~ Ho.m «o.m oo.~ «m.fi on.H m¢.fl m~.m ox mcmucmnouoanu mh.o mh.m o¢.m mm.¢ mm.~ mo.m om.m Hm.q mo.m pH.m mo.¢ hfl.m ax «5.0 v¢.m mm.m om.¢ vm.m om.m mm.~ on.m mm.m hm.v mn.m mm.m .mx mm.o «h.m mh.m mm.m mm.m pp.m Hm.m op.m o>.m o¢.m m~.m mo.¢ ox uoanumummm mm.o oa.m o~.m m~.m om.q nn un nn on.m mm.m oo.o nm.m ax am a m. canes onus mums pnuo one: mnua enoo muoo mnoo anus unmaoauumoo umumemumm amassz cowumuoq um>wm possamu vcmuo ..u:oo. .m manna 34 m>.o pH.~ uu nn an.~ nn ~m.m nn nn mm.H mm.~ oH.H ax mh.o ha.m In In an.~ nu mm.m II II mm.H om.~ mH.H .mx em.o mm.a nn nn vm.a nn mm.a nu nn mm.“ mH.H vm.H ox mcmnumouodcofluanfl.a.fl um.o oo.v nn un nn om.¢ mH.m mp.m «o.v om.¢ mm.¢ sn.m mx um.o oo.¢ nn nn nu om.v mH.m ms.m vo.e om.q mm.v hh.m .mx mammoum om.o mv.H nu nn H>.H mm.H om.H mm.a ov.fl mm.H oo.H om.H ox n0u0asowuanm.m.fi mv.o mo.m Hm.H Ho.a nn mm.m vm.~ un mm.~ nn nu mo.~ ax om.o >o.~ m¢.H mm.H nn mm.m o~.m nn om.m nn nn Ho.m .mx mH.o No.~ mm.m ho.m nu sm.m oo.~ nn om.m nn un mm.m ox mcmaasumouoHnomuume Hq.o H¢.m >e.m mm.m mH.m mm.m o~.m mm.~ mm.m mm.m mm.m o¢.m ax m¢.o o¢.m >¢.m ¢m.m mH.m mm.m mH.m mm.~ Hm.m Hm.m pm.m ov.m .mx m~.o mo.m mo.m mm.~ om.m NH.N mH.m HH.~ mo.m Hw.a mm.H ov.~ ox mcmuxum co.H mm.m Hm.m v~.H wm.~ mv.m mh.¢ mm.m mm.q hm.¢ m~.v mo.m ax vo.H mm.m om.m m~.H «m.~ Hv.m m>.¢ Hm.m so.v mm.v m~.v mw.m .mx am a m. onnuo anon anon hue: mum: mnoo vnua mnua mum: Hump ucmfluflmmmoo umumemumm umnESZ COaumooa um>wm umESHmo ocmuo A.ucoo. .n manna 35 m~.o Ho.e Ho.¢ ma.c m~.¢ mo.¢ mo.e eo.e mm.n vh.n ~m.m mm.v ox mcmuam Hm.o mm.m am.~ op.n m~.¢ om.m om.e on.m mm.m mm.v ho.m m~.m ax mo.o cm.m mo.~ oe.n om.m mm.m em.m hm.H mo.m oo.v hm.m mm.~ .mx m~.o ph.m h~.m Hm.m mm.m Hm.m «m.m om.m ¢~.m cm.m mm.m mo.¢ ox mcmucmnouufi: louoHnomucmm mm.o hm.m oo.m mh.~ nn mm.~ m~.m mm.~ nu mm.m om.m m~.m ax mm.o nm.~ oo.~ mr.~ nn mm.m m~.m am.~ un mm.m om.m mm.m .mx m~.o mo.H HH.H mN.H nu mH.H mH.H ¢H.H nn ¢m.o No.0 mv.H ox mcmsaououuficflonv.m up.o ov.~ nn cm.H Hm.m NH.~ mm.m mm.H mv.m mm.m nn mm.H ax “5.0 oq.~ nu om.H Hm.~ ~H.N mm.~ mm.H m¢.m mm.m nn mm.H .mx mH.o ¢¢.H nn Hm.H mm.H H¢.H vq.H oq.H ¢m.fi oH.H nn mo.H ox mcmucmnouuqc umnouoanonfi oo.o mo.“ nn vv.o 55.0 Ho.h mm.“ om.o nu mm.“ mm.“ ”H.m ax oo.o mm.~ nn Hq.~ mo.~ m~.~ mm.m ou.~ nu om.m nm.m mH.~ nag p~.o ¢m.h nn mm.“ oo.m pm.“ Hm.” om.“ nn om.“ mm.h oa.m ox mymamnunm axuoonfla am “ x cane: one: one: fine: one: mnoo «no: mnoo «no: Hue: acmfloflummoo umumemumm umnEsz cowumooq um>am umESHMU ucmuu ..ucoo. .n manna 36 mm.o ¢m.¢ om.¢ vm.v mm.m mm.v Hm.¢ Hv.v om.v mm.m mm.m Ho.v QM ¢m.o mv.m Hm.m m¢.m mm.N mm.m mm.m 0H.m mm.n mm.v mm.v mm.N .mx mm.o om.v mh.¢ Gm.¢ Ho.m mm.¢ hm.¢ Nm.v 05.? Nm.¢ Hm.v HH.m 0% mammauno Hm.o ov.N hH.N bH.N mm.H 0H.m H¢.N oh.m mH.N vm.N HN.m Mb.H ax Hm.o NN.N HO.N cm.H ab.H mm.~ mo.m o¢.m mm.d om.N oo.m om.H .mx mm.o mm.m mm.m mn.m Hm.m mm.m ®®.m No.m mm.m Nm.m OH.m Hm.m 0% mcwunucmcmnm vb.o mH.® HH.0 mm.o ma.w OH.® om.m om.m mm.o hm.¢ ma.h HN.® ax mm.o NH.m vm.v HN.m Hm.¢ om.¢ hm.v oh.v mm.m ho.m mm.m vm.v .Qx mm.o OH.m OH.m «N.m mm.m ¢H.m ha.m ma.m ho.m mm.¢ Ho.¢ Nv.m ox mcmhhmavaNcwm Hm.o mh.N em.m ON.N mo.N vm.N mN.N hm.m om.N om.m mm.m mo.N ax mm.o vN.N hv.m HB.H Hm.H @H.N mm.H 0N.N Hm.N mh.m m>.N oo.H .mx mm.o mo.¢ mo.¢ NN.v om.v NH.¢ mH.v HH.v mo.v Hm.m mm.m ov.v 0% mcmcucmuosam Hm.o mm.m mm.m mm.m mo.m mo.¢ mm.v mw.m no.m mm.¢ Nm.¢ mm.m ax Om.o Nv.m NN.m mo.m N®.N mo.m mh.m mm.m hm.m mm.m 0¢.v HH.m -mx mm H x OHIGD mIUD mIOD hIUD wIOD mIOD ¢IOD MIUD NIUD HIUD #:0H0Huwm00 kuwfimumm umnEDZ codumooa um>wm amasamo unnuu .m manna 37 vm.o mm.m mm.N ¢N.m mm.N mm.N Mb.N bo.m N¢.N mm.m vm.m mN.N fix vm.o ¢D.N mN.N ma.m MN.N mn.N mm.m mm.m Nm.N Om.m fim.m vH.N .mx mm.o NN.m NN.m wm.m ¢v.m mm.m mN.m mN.m mH.m mm.N mn.N mm.m ox H>cmnmwm mo.o vH.¢ mo.N mh.m mh.m om.v 0N.v mo.v mm.v mm.¢ vm.¢ mo.v ax Nm.o mH.m mh.H mh.N mo.N mh.v oo.m Nh.N mm.m Nw.m Nm.m mm.N .mm mm.o om.v mh.¢ cm.¢ Ho.m mm.¢ hm.¢ mm.¢ oh.v mm.¢ Hm.¢ HH.m 0& mcmumunucmamvoncmm mm H x OHIUD mIOD mIUD hIUD oIUD mIUD files MIUD NIUD HIOD ucmwowmmmoo umumfimumm umnEsz newumooq um>wm umEnHmo ncmuo A.ucoo. .m manna .o.H u u and: manageauaawu anodumuomnu a nucmnoumau ccaa uAHOu 0:» adds: ceaumsvm mnu ca :3onu can «mafia vacancy umuuon ma nuuv .mM and ax com3umn manageaumHou may .muwuu3 whom can mucmEHumm .322 umesauo venue 5.. ucmumum can ham canaamcu mucsomeou cacmmuo umaomncoc Add new ~30300qu .mx camau ucmudmmu onOA usuuo> .Azoa x.00uv .ux onoq” .N muSOMm $3. x 3s .c. Bassoofi 28.. 38 m m n o m v m N w o q 4 . d d u . . 60.0 1. O a m .. 8.. o a a a H w 0 o .a 3 a. m M . 2.4.1.. .H .85 w nunnnwnmnuu :0. o n. O O ._. .3 a _ m J: o m D. a W m H u 86 m can nc..o2..u+cx 23:826.} 203 my 0 u avg. ”w nu ”w oogw 39 .o.H u u nu“: was macauuawu Hmoaumuomnu m mucmmmummu mafia nwaom mnu v. maan3 newumsww mnu ca csocm van “mafia umnmmuv cmuuon ma mumu .mx 0cm ax cmmzumn manmmo«umHmu 0:9 .mumum3.wuom can mucweacmm um>wm amasamo ncmuu.:« ucmmmum new new cmu>amcu o.mv mmsam>.3ox oHooH muw3 mncsomeou oacmouo unaomnco: Ham Ham .AQU\UOmUV .m x namwu ucmummmm oaooH msmum> .Azox x ocuv ax OHOOA 38. x 8: .3. .aozeoofi Sufi m m n o m v m N w o a u q q q q q _ 00.0 1. O 3 x m . . . . x J 8; 0 33 o n a 33 o n 5. 93:33” P u .3. 98.. ._. ‘H‘ W 0 ns 5‘3. m u o a A ‘\ .b n owgw N f ‘ mw \ H w p \s 1 00.? W s s \\ O \\ 1 CV.@ O \s I nu nu ‘n Mw n‘ 004w .m musoflm .o.« u u nua3 awnmcoauuamu Huuuuouomnu m nucmnoummu mafia uHHOm may mafia: cauumsvu may ea czocn one .ocaa cannon. umuuon ma «you .mx can ax cmm3umn manocoaunamu was .mumum3.muom can mucosavmm uo>am umEnHuo ccmuo ca ucmmmum can uOu uuuhadcm o.mA umsao>_3ox camoH nua3 mucsomeou uwcmvuo unaomnco: aam uOu .Amo\oouuv .mx camau ucmuamma onoH unnum> .A3ox x OOMV ax camoq .v muzmam 33. x 8: .3. 32.285 033 40 a m N o m m N p o d d d d a q u °°.° 1 0 any. . o m a .8? W 3 m. m 'l e nnnnnnnnnnnunnn us. a. DU 4. 4 D. a m . 83‘ m m bowed I m .oaood + 2x opoocvhood .. .Qx opoo.‘ % 48.0 M 3 MW cod 41 pxp'. This is also indicated by the divergence of the dashed line which best fits the data from the solid line representing unity or perfect correspondence between pKP' and pKt. When only the data for NPOCs with pKow values (3.0 were plotted (Figure 3), better agreement was observed between theoretical predictions and observed results. The line which best fits the data has an intercept of 0.99 and a slope of 1.35. The relationship pKt accounts for 48% of the variance in pr. (r=0.69, R=O.48). The NPOCs with pKow values >3.0 exhibited little relationship I between pKt and pr since pKt explained (3% of the variance in pr. (r=0.16, R=0.03). If the data for NPOCs with PKow values >3.0 are corrected for binding to DOC and plotted, there is much better concordance between pKt and the actual partition coefficient, pr (Figure 5). After correction, pKt accounted for 58% of the variance in pr (r=0.76, R=0.58) as opposed to accounting for only <3.0% of the variance in pr' before correction for binding to DOC. If the original data for NPOCs with pKow values <3.0 are added back into the data set, the relationship between pKt and pK further improves and approximately 62% of the variance in pr can P be accounted for by pKt (Figure 6). I The original data on pr versus pKt from this study as well as similar data from other field studies on PAHs (18, 23) and laboratory sediment-spiking studies with industrial chemicals and pesticides (29) are compared in Figure 7. These data fit the general pattern observed for the Grand Calumet River data presented here, however, it appears that binding to DOC was potentially more important in determining NPOC distribution in pore waters from the studies by Socha and Carpenter (18) and Oliver (29) than in the study by Kadeg and Pavlou (23). This should be the case since 42 ..mx use ax consume mesmGOAuuamw any uncommwm umcuoo anode uw3oH may ca scaumsvo 0:» mafia: awesomaoo omen» haw ax can ax comzuwn manuso«uuaou on» nucuumum umcuou puma human as» c« sawumsvm one .muoumz whom 0cm mucosaumn um>wm umEsHmo ucmuu cw peonmum pom ecu pmnaaucm o.mA mmsHm> 30& camoH nuwz mpcsomeoo oflcmmuo unaomnco: Ham ecu Ammumsvu pmmoHo .Apo\oomov .9: Hmsuom Ucm Ammumsvm ammo .Amo\oomov .QM name“ ucmummmm OHUOH msmum> .A3ox x UOMV .ux onoq 38. x 8: .6. 30:28.: 39: « . q a a _ _ A 00.0 \u of “H \\\ .sfl..-.......-... cud \\\ .—. n. 00.? ‘\\ \\\\\\ F H .—u \\ fled n a .«S: + 3. 28:33... . 3. 28.1 93 (no I ooso) 'dx PIGH Ianuov on601 ooaw .m musmflm 43 uOm pmuhamcm mucsomeoo vacuouo unaomnco: dam Ham .ADU\OOuo. .mx camoH usmu0> .A3ox x can. .u& onoq .uumuuz whom use avowedvmu u0>wm umEsamo cacao ca accumum new 33. x 8: .c. 30:28.: OBS J... ooxu 00.? oma" oméw ovgw 005w (no I 0080) 'dx PIOH Iannov Guam .0 wusmam 44 ..uo:oeuee some .mn. um>eao pom Amundsen ammo .mav noucmmuuo can mnuom .Anoamcmauu ammo .mu. 50H>mm can mmpmx .Aumauuwo pomoHo. husun menu Scum dump Amo\uonov .mx came“ acmummme usmuo> .A3ox x OOHV .ux onoH 0>wumummeoo .n musmwm .38. x 83 .3. .3322...» 033 m m h o m v m N w o d — u d d u _ — ooao 1 O m. 0 8 . 1 00.—. V .mr e “M e on e m e em”. 0&3 8 e omd we 0 e e 0.0 s co. m e e e. e m” a a o . 86 Am 4 o .- < MW m u oegw o 0 MW oogw 45 Kadeg and Pavlou (23) determined "dissolved" concentrations of PAHs in pore water. Discussion The potential for binding of NPOCs to DOC in pore water is an issue of importance in the development of exposure models for the effects of NPOCs on aquatic organisms and, in particular, benthic macroinvertebrates. If DOC-bound NPOCs are unavailable to cause effects on biota as proposed by McCarthy and Jimenez (21) and Landrum et al (22), then these exposure models must account for DOC-binding of NPOCs in pore water to accurately predict exposure concentrations for NPOCs. Currently, equilibrium partitioning theory (EqP) is being proposed as the theoretical basis for the development of sediment quality criteria (SQC). Draft SQC criteria documents have been prepared by the U.S. Environmental Protection Agency (EPA) for five NPOCs, endrin, dieldrin, phenanthrene, fluoranthene and acenaphthene. These criteria development efforts have made no effort to account for DOC-binding of NPOCs in pore water because, to date, there has been little empirical field evidence conclusively demonstrating the importance of DOC-binding in determining the distribution, and thus bioavailability, of NPOCs in pore waters from contaminated sediments. NPOC binding to DOC may be of the greatest importance in attempts to extrapolate SQC which are reported on an organic carbon-normalized bulk sediment concentration basis (pg NPOC/gm organic carbon) to permissible concentrations of NPOCs in pore water. Binding to DOC could increase NPOC concentrations in pore water to values greater than permissible based on extrapolation from SQC while the "dissolved" (i.e, bioavailable) 46 concentration of the NPOC in pore water could actually be acceptable if binding to DOC was accounted for in the calculation of acceptable NPOC concentrations in pore water. A major strength of EqP as an exposure model and potential basis for the development of SQC is that including a correction for DOC-binding of NPOC requires only a simple extension of the partitioning theory to DOC and is consistent with the thermodynamic principals underlying EqP (4). Current EqP models are best described as two phase because they account for NPOC partitioning between two sorbent phases, sediment organic carbon and pore water. The existence of a third sorbent phase, DOC, also would explain the particle concentration effect which has been reported by some researchers (26, 30). Experimental limitations make it difficult to measure empirically the "dissolved" and DOC-bound concentrations of NPOCs in pore water, however, Voice et al (14) and Gschwend and Wu (15) have previously proposed that dissolved ligands and colloids, respectively, were the agents causing the observed particle concentration effects. The results of this investigation of the DOC-binding of NPOCs in pore waters from the Grand Calumet River has demonstrated the potential importance of this phenomenon in determinations of the bioavailable fraction of NPOCs in pore water. Frequently, critics of the EqP method of predicting exposure concentrations have decried the lack of relationship between predicted and measured pore water concentrations of NPOCs. This conclusion would follow after a cursory examination of the data presented in Figure 2. This observation is made even more apparent for NPOCs with values 10910 Row >3.0 if the data are divided into NPOCs with 10910 Kow <3.0 (Figure 3) and >3.0 (Figure 4). The importance of NPOC binding to DOC in pore water has previously 47 been reported for two limited groups of NPOCs, PCB congeners (16) and Pass (18), respectively. Both studies reported that NPOC concentrations in pore waters from field collected sediments were greater than predicted due to partitioning to DOC. Correction for DOC-binding resulted in "dissolved" NPOC concentrations in pore waters which were in better agreement with predicted values. Chiou et al. (17) also have reported that the apparent water solubilities of organic chemicals, including pesticides, increased linearly with an increase in DOC (DOM) concentration while Brusseau (31) reported the enhanced sorption of three non-ionic compounds to two aquifer materials of low organic carbon content. The mechanism for this effect appeared to be increased DOC concentration as a result of experimental additions of tetrachloroethane. This study demonstrates the applicability of the EqP predictions to a much greater range of compounds, if DOC-binding is taken into account. However, one of the criticisms of our approach to determining the "dissolved" concentrations of NPOCs in Grand Calumet River pore waters may be the assumption that KDOC = Koc’ Most studies have reported Koc values < K values but few studies have evaluated KDOC values in relationship to OW K Although several studies have reported KDOC values (Koc' several oc‘ also have reported that NPOCs bind to organic sorbents in particulate and dissolved form to a similar extent (32, 34). An important factor in these evaluations may be determining that the sediment organic matter and the pore water dissolved organic matter are of the same origin (i.e. terrestrial, aquatic plant, etc.) and physical/chemical characteristics (i.e. hydrophobicity, CHNO composition, etc). Numerous examples exist of altered partitioning of NPOCs to different types of organic matter which was due to differences in the chemical composition of the organic matter 48 Although NPOCs with pK >3.0 are generally of the greatest interest ow because of their propensity to resist environmental degradation and to be bioconcentrated by biota, the behavior of the NPOCs with pKow <3.0 also is of interest in the Grand Calumet River data set. Based on the data presented in Table 2 and Figure 3, it appears that these NPOCs either occurred at greater than expected concentrations in sediments from the study sites or at concentrations less than expected in the study site pore waters. The former possibility was reported by Boyd and Sun (36) for soils and was hypothesized to be due to residual petroleum hydrocarbons and polychlorobiphenyl oils acting as a sorptive phase with approximately 10 times the partitioning strength of native soil organic matter. Sediments from the Grand Calumet River do contain significant amounts of petroleum hydrocarbons (26). However, based on our unpublished comparisons of measured versus predicted pore water concentrations of the NPOCs in pore water, it appears that a much more plausible explanation is that these compounds may be volatilized from the pore water preferentially by the vacuum filtration step during pore water preparation. Equilibrium partitioning theory appears to be a viable basis for predicting the partitioning behavior of NPOCs under field conditions if consideration is given to the potential for DOC-binding of NPOC. Based on comparison of actual partition coefficients, pr, versus estimated partition coefficients, pKt, for the NPOCs measured in Grand Calumet River sediments and pore waters, binding to DOC in pore water is not important for NPOCs with pKow values <3.0. NPOCs with pKow values >4.0 can be expected to demonstrate significant potential for binding to DOC in pore water. If SQC are to be based on water quality criteria extrapolated to 49 "dissolved" pore water chemical concentrations, binding to DOC in pore water must be accounted for in determining "dissolved" pore waters concentrations of the chemicals of interest, otherwise the application of SQC to determine permissible concentrations of NPOCs in pore water will overestimate the potential for adverse effects. Acknowledgements This research was funded by a grant from the U.S. Environmental Protection Agency, Great Lakes National ProgramnOffice. JPrevious versions of the manuscript were typed by Debra Williams and Jane Norlander. Russ Erickson and Gary Ankley provided insightful review comments which inproved the final version of the manuscript. 50 Literature Cited Shea, D. Environ. Sci. Technol. 1988, 22, 1256. U.S. EPA. Sediment Quality Criteria Development Workgggp. U.S. Environmental Protection. Agency, Office of Water Regulations and Standards, Criteria and Standards Division, Washington, D.C. 1985. Pavlou, S.P. In Fate and Effects of Sediment-Bound Chemicals in Aquatic Systems, Dickson, K.L.; Maki, A.W.; Brungs, W.A. Eds; Permagon Press: Elmsford, NY, 1987; pp 388-412. DiToro, D.M.; Zarba, C.S.; Hansen, D.J.; Berry, W.J.; Swartz, R.C.; Cowan, C.E.; Pavlou, S.P.; Allen, H.E; Thomas, N.A.; Paquin, P.R. Environ. Toxicol. Chem. 1991, 10, 1541. Adams, W.J.; Kimerle, R.A.; Mosher, R.G. In Aquatic Toxicology and Hazard Assessment. STP 854, Cardwell, R.D.; Purdy R.; Bahner, R.C. Eds; American Society for Testing and Materials: Philadelphia, PA, 1985; pp 429-453. Ziegenfuss, P.S.; Renaudette W.J.; Adams, W.J. In, .Aggatic Toxicology and Environmental Page. Ninth gymposium, ASTM STP 921, Poston, T.M.; Purdy, R. Eds., American Society for Testing and Materials: Philadelphia, PA, 1986; pp 479-493. 51 52 7. Adams, W.J. In Fate and Effects of Sediment-Bound Chemicals in Aquatic Systems, Dickson, R.L.; Maki, A.W.; Brungs, W.A. Eds., Permagon Press: Elmsford, NY, 1987; pp 219-244. 8. Connell, D.W.; Bowman, M.; Hawker, D.W. Ecotoxicol. Environ. Safety. 1988, 16, 293. 9. Lake, J.L.; Rubinstein, N.I.; Lee II, H.; Lake, C.A.; Heltshe, J.; Pavignano, S. Environ. Toxicol. Chem. 1990, 9, 1095. 10. Swartz, R.C.; Schults, D.W.; Dewitt, T.H.; Ditsworth, G.R.; Lamberson. J.O. Environ. Toxicol. Chem. 1990, 9, 1071. 11. DiToro, D.M.; Allen, H.E.; Cowan, C.E.; Hansen, D.J.; Paquin, P.R.; Pavlou, S.P.; Steen, A.E.; Swartz, R.C.; Thomas, N.A.; Zarba, C.S. EPA 440/5-89-002. U.S. Environmental Protection Agency, Criteria and Standards Division, Washington, D.C. 1989. 12. Knezovich, J.P.; Harrison, F.L. Ecotox. Environ. Safety. 1988, 15, 226. 13. Eadie, B.J.; Landrum, P.F.; Faust, W. Chemosphere. 1982, 11(9), 847. 14. Voice, T.C.; Rice, C.P.; Weber Jr., W.J. Environ. Sci. Technol. 1983. 17, 513. 15. Gschwend, P.M.; Wu, 8. Environ. Sci. Technol. 1985, 19, 90. 16. Brownawell, B.J.; Farrington, J.W. Geochemica et Cosmochemica Acta. 1986, 50, 157. 17. Chiou, C.T.; Malcolm, R.L.; Brinton, T.I.; Kile, D.E. Environ. Sci. Technol. 1986, 20, 502. 18. Socha, S.B.; Carpenter, R. Geochemica et Cosmochemica Acta. 1987, 51, 1237. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 53 Eadie, B.J.; Morehead, N.R.; Landrum, P.F. Chemosphere. 1990, 20(1- 2), 161. Capel, P.D.; Eisenreich, S.J. J. Great Lakes Res. 1990, 16(2), 245. McCarthy, J.F.; Jimenez, B.D. Environ. Toxicol. Chem. 1985, 4, 511. Landrum, P.F.; Nihart, S.J.; Eadie, B.J.; Herche, LJR. Environ. Toxicol. Chem. 1987, 6, 11. Kadeg, R.D.; Pavlou, S.P. Reconnaissance Field Study for yarification of Equilibrium Partitioning: Nonpolag Hydrophobic Organic Chemicals. U.S. EPA, Criteria and Standards Division, Washington, D.C. 1987. U.S. EPA. Test Methods for Evaluating Solid Waste. Vbl. 1B: Laboratory Maqqal. Physical/Chemical Methoda. U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, Washington, D.C. 1986. U.S. EPA. Federal Register 40 CFR 136. 1984, 209 p. Hoke, R.A.; Giesy, J.P.; Zabik, M.; Unger, 1L Ecotox. Environ. Safety. 1992, (In Press). DiToro, D.M. Chemosphere. 1985, 14(10), 1503. AQUIRE. aqqatic Toxicity Information Rgtrieval Database. U.S. Environmental Protection Agency, ERL-Duluth, Duluth, MN. 1991. Oliver, B.G. Environ. Sci. Technol. 1987, 21, 785. O’Connor, D.J.; Connolly, J. Water Resources 1980, 14, 1517. Brusseau, M.L. Environ. Sci. Technol. 1991, 25(10), 1747. Garbarini, D.R.; Lion, L.W. Environ. Sci. Technol. 1986, 20(12), 1263. 33. 34. 35. 36. Rutherford, D.W.; Chiou, 1992, 26(2), Carter, G.W.; Kukkonen, J.; Environ. Boyd, S.A.; 336. 1989, Sun, S. 79, 197. Environ. C.T.; 54 Oikari, A.; Johnsen, Sci. Kile, D.E. Suffet, I.H. Environ. Sci. Technol. Environ. Sci. Technol. 1982, 16, 735. Sci. Total 8.; Gjessing, E.T. Technol. 1990, 24, 142. CHAPTER 2 Toxicity of Sediments and Sediment Pore Waters from the Grand Calumet River-Indiana Harbor, IN Area of Concern. 55 Introduction The sediments of many rivers, harbors and connecting channels of the Great Lakes contain a wide array of chemical compounds, including organic xenobiotics (Pranckevicius 1986, Fallon and Horvath 1985) and metals (Pranckevicius 1986, Fallon and Horvath 1985, Hamdy and Post 1985). Due to municipal, industrial and non-point source waste discharges and the tendency of many chemicals to become associated with sediments, contaminated sediments are particularly problematic near densely populated, industrialized urban areas, such as the area surrounding the Grand Calumet River-Indiana Harbor (GCR-IH) in northwest Indiana. Due to contaminants and nutrients in the water and sediments from this area, it has been designated an Area of Concern (AOC) by the International Joint Commission (IJC 1985). The environmental status, relative to anthropogenically-introduced chemical contamination, in these areasuof the Great Lakes has been summarized elsewhere (Rodgers et al. 1985). The severely contaminated condition of the GCR-IH AOC is based on water quality problems with conventional pollutants, metals, and organic chemicals; contaminated sediments, impacted aesthetics and biota, and fish consumption advisories (IDEM 1988). The presence of a wide variety of in- place chemical contaminants in sediments from the AOC and their potential effects on biota were the primary focus of this study. Assessing the degree of contamination of sediments consists of basically two aspects: 1) determination of which contaminants are present 56 57 and 2) evaluation of the potential effects of these contaminants on biota (Bishop 1987). The potential toxicity of sediments to benthic organisms can. be determined by surveying 'the number and types of indigenous organisms present in a sediment (Chapman 1986). However, the absence of a particular macroinvertebrate species in a sediment does not necessarily indicate that the sediment is toxic. Toxicity of sediment to benthic invertebrates also can be estimated by quantifying all of the toxic compounds and elements associated with the sediment by analyzing: 1) bulk sediment, 2) sediment pore water (Jenne et al. 1980, Batley and Giles 1980), 3) an elutriate of the sediment (Brannon et al. 1980, Laskowski- Hoke and Prater 1980), or 4) various organic or acid extracts designed to selectively remove particular classes of toxic substances (Samoiloff et al. 1983). The potential toxicity of a sediment to benthic organisms then can be predicted by comparing the observed concentrations of chemicals in 1, 2, 3, or 4 above to dose-response relationships determined under laboratory conditions for each individual toxicant. However, a number of parameters, such as organic carbon content and particle size distribution, can affect the availability of both metals and organic chemicals in sediments to benthic organisms (Babich and Stotzky 1977, Laxen 1985, Oliver 1985). In addition, potential interactions due to the presence of a complex chemical mixture in a sediment are not known. Toxicity tests, however, can be used to provide a direct assessment and to integrate the effects of the biologically active fraction of all of the toxic chemicals present in a sediment, pore water, elutriate or organic solvent extract. If laboratory toxicity data are available for specific chemicals present in the samples, the results of toxicity tests can be compared with measured chemical concentrations in a "toxic units" (TU) approach (Sprague 58 and Ramsay 1965) to help determine potential causes of the observed toxicity. This investigation tested the relative sensitivities of several simple toxicity tests with bacteria and invertebrates in order to provide a framework for conducting rapid, comprehensive surveys of potentially toxic sediments and to conduct an assessment of sediment toxicity in the Grand Calumet River, IN. The tests chosen for use in the toxicity assessment of sediment pore waters were the Microtoxo test and 48 h acute tests with Daphnia maqna and Ceriodaphnia dubia while a 10-d test with Chironomus tentans was chosen to assess the toxicity of solid phase sediments. The Microtox® test is a bacterial luminescence toxicity test developed by Beckman, Inc. in 1977 (Bulich 1984) as a rapid screening alternative to standard acute toxicity testing with fish or invertebrates. This test is based on the reduction in bioluminescence of the marine bacterium (Photobacterium phoaphoraqm) (NRRL B-11177) by toxic chemicals. Comparisons of the Microtox® test and acute toxicity tests with both fish and invertebrates for a large number of pure compounds and complex mixtures has demonstrated good general agreement between the fathead minnow, Pimephales promelas, and. Daphnia. maqna acute ‘tests and 'the Microtox® test, both within- and among-laboratories (Green et a1. 1985). The use of both sucrose and NaCl osmotic adjustment techniques in the MicrotoxO test also has been demonstrated to be of use in determining the nature of the compound causing the toxicity when testing complex mixtures (Hinwood and McCormick 1987, Ankley et al. 1990a, Hoke et al. 1992a). Cladoceran species have numerous advantages for aquatic S9 toxicity testing, including their sensitivity to a wide variety of environmental contaminants (Maki 1979, LeBlanc 1980). Daphnia maqna and D. pulex have been most frequently used in aquatic toxicity tests and a large data base exists for the effects of pure compounds on D. maqga (Hunter et al 1990). In addition, the response of D. maqna has been correlated with the responses of other species to toxicants (Nebeker et al. 1983, Nebeker et a1. 1986). Acute lethality tests with D. maqna also seem appropriate for use in sediment pore water toxicity tests because it is one of the species used to establish surface water quality criteria (U.S. EPA 1980a). Ceriodaphnia dubia occurs in natural zooplankton assemblages of the Great Lakes and has recently gained wide—spread acceptance as a test species for acute and chronic toxicity testing of effluents and various other types of aqueous extracts (Mount and Norberg 1984, DeGraeve and Cooney 1987, Mount and Anderson-Carnahan 1988a, b; Mount 1989, Ankley et al. 1990b, Oris et al. 1991, Kszos and Stewart 1991). Several investigations have evaluated of the comparative sensitivity of C. dqbia and other daphnid species to water quality variables and pure chemicals (Cowgill et al. 1985, Takahashi et al. 1987, Winner 1988, 1989; Mokry and Hoaglund 1990, Cowgill and Milazzo 1990, 1991a, b). The sensitivity of Q; dubia also has been compared with the response of the MicrotoxO test to different wastewater fractions (Mazidji et al. 1990), with the responses of natural zooplankton and benthos communities to chronic copper stress (Moore and Winner 1989), with the response of fathead minnow tests for evaluating in-stream toxicity dynamics (Stewart et al. 1990) and with the responses of the Microtox® and fathead minnow tests to sediment elutriates (Hoke et al. 1990). Because the comparison of relative species 60 sensitivities to pore water from contaminated sediments was of interest, acute toxicity tests of sediment pore waters were conducted with both _D_y maqna and C. dubia. Chironomus tentans (Diptera:Chironomidae) is a representative of a group of insects known as the midges, which are widely distributed in freshwater sediments during their larval stage of development. This species spends almost all of its life cycle in a tunnel in the upper few centimeters of sediments (Sadler 1935). Chironomids often comprise a significant proportion of the benthic biomass and are important in the cycling of oxygen, nutrients and contaminant residues into and from the sediments due to bioturbation (Graneli 1979, Hargrave 1975, Matisoff et al. 1985). Chironomus tentans can be satisfactorily reared in the laboratory and has previously been used as a sediment toxicity test organism (Wentzel et al. 1977, 1978, Batac-Catalan and White 1982, Mosher and Adams 1982, Mosher et al. 1982, Giesy et al. 1988, 1990). In previous studies of Great Lakes sediments (Giesy et al. 1988), a reduction in Q; tentans dry weight, relative to control, of approximately 30-40% in the whole sediment toxicity tests was observed for sediments which did not support viable communities of benthic invertebrates in the field. The objectives of this study were as follows: 1) To evaluate the toxicity of sediments and sediment pore waters from 13 locations in the Grand Calumet River, IN (Figure 8) with the following toxicity tests and endpoints, i) Photobacterium pmosphoreum, Microtoxo, inhibition of bioluminescence in 5, 15, and 30 minute incubations with sediment pore water in assays using two forms of osmotic protection (NaCl, sucrose) for the bacteria. ii) Daphnia maqna and gariodaphnia dubia, survival of 24 h old neonates during 48 h exposures to sediment pore water. 61 iii) Chironomus tentans, survival and inhibition of dry wt. gain, relative to control, following 10-d exposures to whole sediments. 2) To test the hypothesis that the toxicity of whole sediments or pore waters as determined by laboratory toxicity tests can be predicted from toxic units calculated based on the concentrations of individual or classes of compounds and known dose-response relationships. 3) To determine whether sediment toxicity is better predicted from concentrations of chemical residues in pore‘water than residues in bulk sediments. Materials and Methods Sample Collection Sediment samples were collected from the Grand Calumet River, IN on 11 October and 22 November 1988; 10 March, 24 May, 30 October and 13 November 1989; and 12 May 1990. A Ponar grab sampler was used to collect sediment samples from 10 locations along the Grand Calumet River and three locations in the Indiana Harbor ship canal (Figure 8). At the time of sample collection, study sites were located by triangulation of local landmarks. The sample from each location was a composite of approximately 80-100 L of wet sediment from multiple Ponar grabs. Multiple grab samples were collected and composited to ensure sufficient sample volume for all necessary sub-sample collection. Compositing and homogenization of composite samples were done in a large stainless steel pan with stainless steel tools. Large debris was removed from the composite samples and two, 1-L aliquants (sub-samples) for quantification of metals and organic compounds in bulk sediments were placed in l-L glass jars capped with washed aluminum foil under the lid. Samples for toxicity testing or pore water extraction were placed in coolers or plastic buckets lined with 62 msmeCH .uonumm mcewpsm ecu uo>wm umEsamO Ocauo «nu ca acoeumooH mcwamemm 8.: GEM-UC— od o; 0.0 Be: Eoeamo 655 we: «a: «0: v0: 3.! 3.2 3.9 e: 3.2 . 9. as \/ oo 9. on . :0: I s «'0: 2883 8.3.8 2.5.8.... .4 \ 3 2.: 32m - _ 90 3 .83.. «5.2. mafia;£$ 20:...— .m musmwm 63 food-grade plastic bags. Prior to sample collection, sample bottles were washed and solvent rinsed with hexane. .After collection, sediment samples were placed on ice in coolers and transported to the laboratory, where they were maintained in a walk-in cooler at 4° C until processing and analysis. Pore Water Extraction Pore water was extracted from sediments by a combination of centrifugation and filtration as described by Hoke et al (1992a). The pore water extracts were placed in glass bottles, the bottles capped with aluminum foil-lined lids, and the pore water maintained in the dark at 4° C until used for assays (< seven days) or until extracted for subsequent chemical analysis. Pore water samples for metals analysis were preserved with a sufficient amount of concentrated HNO3 to lower the sample pH to S 2.0. Samples for quantification of organic compounds were preserved with 5 ml/L of a 1 g/L solution of HgC12 to prevent microbial degradation. The cleaning procedure for pore water sample bottles was identical to the procedure used for sediment sample bottles. Subsamples of sediments and pore water extracts were archived at 4° C. Chemical Analysis Organics Organic chemical analyses were only conducted.on samples collected from the 10 locations on the Grand Calumet River (Figure 8). In general, the analytical methods for the quantification of non-polar organic compounds in sediment and pore water followed the scheme presented below. Subsamples of sediment were dried at 105°C for 24 h and percent moisture determined for each sample. Ten grams of dried sample were mixed with 10 64 g of anhydrous sodium sulphate and Soxhlet extracted for 24 h with pesticide-grade acetone/hexane (1:1, v/v). The extract was passed over a drying column containing anhydrous sodium sulphate and the column rinsed with approximately 100 ml of the acetone/hexane mixture to complete the transfer. The extract was transferred to a Kuderna-Danish concentrator and extract volume reduced to 1 ml. The final extract volume was adjusted to 10 ml with the acetone/hexane mixture. These procedures and all other aspects of sediment sample preparation followed U.S. EPA.Method 3540 (0.8. EPA 1986). One liter of pore water was adjusted to a pH of >11, extracted with three successiveu60 ml portions of pesticide-gradenmethylene chloride in a separatory funnel and the extracts combined for analysis of neutral organic compounds. If a large emulsion was observed, continuous liquid- liquid extraction was used to complete the sample extraction. Extracts were passed over an anhydrous sodium sulphate drying column and reduced to 1 ml in a Kuderna-Danish concentrator. Final extract volumes were adjusted to 10 ml with methylene chloride. Pore water extraction followed the protocols outlined in U.S. EPA Method 3510 or, for emulsions, U.S. EPA Method 3520 (U.S. EPA 1986). Cleanup procedures for both sediment and pore water extracts followed the protocols outlined in U.S. EPA Methods 3620, 3630 or 3660 (U.S. EPA 1986) and were dictated by the class of compounds quantitated in subsequent analyses. Identification and quantitation of chemical analytes were performed with gas chromatography/mass spectroscopy (GC/MS) techniques. U.S. EPA 600 Series methods (U.S. EPA 1984) were used for CC analyses while compound confirmation was conducted with U.S. EPA.GC/MS Methods 8240 and 8250 (U.S. EPA 1986). GC/MS operating conditions were as follows for 65 all analyses: electron energy 70 eV, mass range 35-550 amu, scan time 1 sec/scan, transfer line temperature 250 °C, source temperature 200-250 °C, injector temperature 250-350 °C, injector on column or Grob splitless, sample volume 1 pl and carrier gas He at 15 psi. Compounds were identified by comparison to library spectra and confirmed by comparison to authentic standards. Metals Concentrations of metals in whole sediments and pore waters were determined by a combination of inductively-coupled argon plasma (ICP) and atomic absorption (AA) spectroscopy. Whole sediments were digested in concentrated HNO3 (Plumb 1981, APHA 1985). Standard additions were used to avoid matrix effects. Miscellaneous parametera A number of parameters were determined by standard techniques. Acid volatile sulphides (AVS) were measured in bulk sediments with a gravimetric technique (Di Toro et al. 1990, 1991). Total oil and grease was measured by the freon extraction method followed by gravimetric quantitation (Plumb 1981). Sediment TOC was measured with a LECO carbon analyzer dry combustion technique. Selected contaminants (CN, H28, NH3), total organic (TOC) and total inorganic carbon (TIC) in pore water were measured when samples were prepared for toxicity tests. Concentrations of cyanide and hydrogen sulfide were determined by standard methods (APHA 1985). Total ammonia was measured with an Orion® Model 701A ionanalyzer and an OrionO Model 95-12 ammonia electrode. TOC and TIC were measured with an 10 Corporation, Inc. Model 700 TOC analyzer. Hardness, alkalinity, conductivity and Ph were measured in the 100% pore water concentration 66 during cladoceran toxicity tests. Reported values are the maximum values observed during the course of the 48 h toxicity tests. Toxicity Tests Photobacterium phosphoreum The Microtox' bacterial luminescence assay' was performed. on sediment pore waters with the standard procedure (Bulich et al. 1981) and the alternate osmotic adjustment procedure developed by Hinwood and McCormick (1987). Reduction in bioluminescence of the bacterium £_. phosphoreum was used as a measure of the toxicity of the sediment pore waters. A Microtox® Model 2055 Toxicity Analyzer (Microbics Co., Carlsbad, CA.) was used for all measurements. The calculated ratio of corrected light emitted to emitted light remaining after 5, 15 or 30 minutes was determined for each sample dilution and all results reported as the percent pore water causing a 50% inhibition of bioluminescence (ECSO). ECSO values were calculated with the linearized gamma distribution. Daphnia maqna andygariodaphnia dubia Initial C. dubia cultures were obtained from the Eli-Lilly Co. (Greenfield, IN) while D. maqna originated from laboratory cultures maintained by the Michigan Department of Natural Resources (East Lansing, MI). In the laboratory, C. dubia were either maintained in mass cultures in 1000 ml beakers containing 900 ml of culture water or in a brood board as previously described by Hoke et a1 (1990). Daphqia maqqa were maintained in mass cultures contained in 1000 ml beakers. Mass cultures of both species were initiated with one gravid female and maintained in a Scientific Products incubator at 25° C with a 16L:8D photoperiod (light 67 levels - 200 pE/m2 sec). Brood boards were initiated with 60 gravid females and were maintained in the same incubator as the mass cultures. Feeding consisted of daily additions of Selenastrum capricornugum (200,000 cells/m1 culture water) and Yeast-Cerophyl-Trout chow (YCT, 3 ml/1000 ml culture water). Thinning of the mass cultures was performed weekly by removing approximately 90% of the existing organisms and water with replacement of an equal volume of fresh culture water. Cultures were maintained for 14-d (brood boards) and 21-d (mass cultures) prior to initiation of new cultures for C. dubia and D. ma na, respectively. Culture, control and diluent waters for all assays was 10% Perrier mineral water prepared as described by Hoke et a1 (1990). Two pg/L of cyanocobalamin (vitamin 812) and selenium (as sodium selenate) were added to the 10 % Perrier water mixture. The aerated 10% Perrier water mixture had the following chemical characteristics over the entire study period (mean i SD): DO-7.9 i 0.4 mg/l, Ph-8.1 i 0.4, specific conductance-105 : 26 ymhos/cmz, hardness-60.3 ¢_9.6 mg/L as CaCO3 and alkalinity-59.3 i 11.7 mg/L as CaCO3. The sediment pore water was prepared 24-48 h prior to assays and allowed to equilibrate to 25° C immediately before starting a test. Twenty mL of each test solution were dispensed into 10 replicates for each pore water dilution concentration or control using a device developed by Mount and Norberg (1984) for this purpose. Chemical characteristics of the initial pore water dilutions were measured at test initiation. All assays were conducted in a Scientific Products incubator at the same temperature, photoperiod and light level regimes used for culturing the test organisms. 68 Ceriodaphnia dubia neonates, < 12 hr old and not more than 8 h different in age, from the third brood of the originally isolated neonates were used to begin all assays. D. maqna neonates <12 h old were collected by screening all neonates from the mass cultures and then again screening all neonates from ‘the unass cultures ‘within 12 11. Observations of mortality (lack of movement or respiration) were made at the termination of the 48 h tests with both cladoceran species. Acute 48 h LCSO values were calculated with the TOXCALC program. 'This programnoriginated at U.S. EPA and was modified for use in the laboratory at Michigan State University. Unless noted above, all other culture and assay methods followed those presented by Mount and Norberg (1984) and U.S. EPA (1985a). Chironomus tentans Chironomus tentans were originally obtained from Dr. David White of the University of Michigan and have been continuously cultured in the laboratory at MSU for over five years. Cultures were maintained using the methods of Giesy et a1 (1988). Second instar individuals (12 d post-hatching) were used for all tests. Culture records indicate second instar C. tentans had a mean dry wt. of 0.503 mg (n=7, SD=0.136 mg); while recent historical test data from the laboratory indicate that individual control organisms had a mean dry wt. of 6.98 mg (n=20, SD=0.94 mg) at test termination (22 d post-hatching). Tests were conducted with individual second instar C. tentans using the methods of Giesy et al. (1988) except that a 9:1 mixture of HPLC-grade deionized water and Perrier mineral water was used in each test instead of distilled water. Tests were conducted for 10 d at 22 1 1° C with a 16L:8D photOperiod. At test termination, surviving larvae were recovered, rinsed with deionized laboratory water and placed in aluminum 69 weigh boats. Larvae were dried at 80° C for 24 h and each larvae weighed on a Mettler Model H54AR analytical balance. Results of C. tentans tests are reported as mean percent inhibition in dry wt. gain at each station relative to a control sediment. Statistical Analysis LCSO values from the toxicity tests were used for correlation analyses with the chemical data. Statistical Analysis System (SAS 1988) software was used to perform univariate Pearson product moment correlations among the results of toxicity tests and chemical analyses of sediments and pore waters. Correlation analysis results are reported only if they were significant at the P s 0.05 level. Results Chemical Analysis Organics Analyses were conducted to determine solid phase sediment concentrations for a total of 104 organic chemicals. Forty-one of these 104 compounds were not present in GCR sediments at concentrations above the limit of detection (LOD). Analyses were subsequently conducted to determine pore water concentrations of the 63 compounds observed at concentrations greater than the LOD in the sediments. Of these 63 compounds, only 44 were observed in pore water samples at concentrations greater than the LOD (Table 4). Concentrations of organic chemical analytes detected in either whole sediment or pore water are listed in Tables 5 and 6, respectively. 70 Table 4. Organic compounds analyzed for but not detected in sediments or sediment pore waters from the Grand Calumet River, IN. The limit of detection (LOD) is given for the matrix in which the compound was not detected. Parameter Sediment LOD Pore water LOD mglkg ug/L m-Chlorophenol 0.1 m-Cresol 0.01 p-Cresol 0.01 2,3-Dichlorophenol 0.01 2,5-Dichlorophenol 0.01 2,6-Dichlorophenol 0.1 3,4-Dichlorophenol 0.01 3,5-Dichlorophenol 0.01 2,3-Dibromophenol 0.01 2,4-Dibromophenol 0.01 2,5-Dibromophenol 0.01 2,6-Dibromophenol 0.01 3,4-Dibromophenol 0.01 3,5-Dibromophenol 0.01 2,3,4,5-Tetrachlorophenol 0.01 2,3,4,6-Tetrachlorophenol 0.01 2,3,5,6-Tetrachlorophenol 0.1 2,3,4-Trichlorophenol 0.01 2,3,5-Trichlorophenol 0.01 Table 4. (continued). 71 Parameter Sediment LOD Pore water LOD mg/kg ug/L 2,3,6-Trichlorophenol 0.01 2,4,S-Trichlorophenol 0.01 2,4,6-Trichlorophenol 0.1 3,4,5-Trichlorophenol 0.01 Mercaptobenzothiazole 0.1 1,2,3,4-Tetrachlorobenzene 0.01 1,2,3,S-Tetrachlorobenzene 0.01 1,2,4,5—Tetrachlorobenzene 0.01 Benzidine 0.01 3,4-Dichloroaniline 0.1 3,3-Dichlorobenzidine 0.1 p,p'-DDD 0.1 Aldrin 0.01 Methoxychlor 0.01 m-Dichlorobenzene 0.1 p-Dichlorobenzene 0.1 1,2-Dichloropropane 0.1 1,3-Dichloropropane 0.01 1,3-Dichloropropene 0.1 Hexachloro-1,3-butadiene Hexachloroethane 0.01 Pentachloroethane 0.1 1,2,3—Trichlorobenzene 0.1 Table 4. (continued). 72 Parameter Sediment LOD Pore water LOD mg/kg ug/L 1,2,4-Trichlorobenzene 0.1 1,3,5-Trichlorobenzene 0.01 1,2,3-Trichloropropane 0.1 Trichloroethene 0.01 Butylbenzylphthalate 0.02 Diethylphthalate 0.02 Dimethylphthalate 0.02 Di-n-butylphthalate 0.5 Di-n-octylphthalate 0.02 1-Chloro-2,4-dinitrobenzene 0.01 1-Chloro-2,6-dinitrobenzene 0.01 1-Chloro-3,4-dinitrobenzene 0.01 1-Chloro-4-nitrobenzene 0.01 2,6-Dinitrotoluene 0.01 Nitrobenzene 0.01 Cresyldiphenyl phosphate 0.01 Trixylene phosphate 0.01 2,3,7,8-Dibenzo-p-dioxin 1 2.0 Dimethyl nitrosamine 0.3 1 - units for TCDD LOD = pg/L 73 30.0 03.3 30.0 33.0 33.0 03.0 33.0 03.3 33.0 00.0 mcoc3svouomm 33.3 30.3 30.3 03.3 33.3 03.3 00.3 30.3 30.3 33.3 3ocmndouu3c30u0.3 33.3 30.3 03.0 30.0 00.0 33.0 33.0 33.3 33.0 30.0 3ommuononouu3c30n0.0 33.0 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 3ocmcaouo33030n0.3 33.0 33.3 30.3 33.3 03.3 30.3 30.3 33.3 33.3 00.3 3ocmnmouo3no3an0.3 30.0 .93;0 33.0 33.0 30.0 33.0 30.0 30.0 33.0 03.0 3ommuono 30.0 03.0 33.0 33.0 30.0 33.3 33.0 33.0 30.0 30.0 3ocmcaouo3nonm 30.0v 30.0v 30.0 03.0 30.0 33.0 30.0v 30.0v 33.0 30.0 30cmnnouo3none 03.3 30.0 33.0 33.0 03.0 33.0 00.0 30.0 30.0 33.0 3ocmznoMO3nono 3.3 3.0 3.33 3.3 3.0 3.3 0.3 3.0 3.3 3.0 .u: 330 30 mmmmuo 3 330 0.33 3.33 3.33 3.03 3.33 3.03 3.33 3.3 0.0 3.33 .33 330 3. 003330 0303030 03n00 mnoa 3n00 3n00 one: muos 0n00 3n00 3n00 3n00 ummemuma umnEsz mUHm um>3m 3083330 pcmuo ..ox\003 c3xo30n0n030mn30n3.3.3.3 pcm A.u3 >30 xv mmmmum com 330 .conumu 03cmmuo u0w ummoxm ..u3 zen mx\OE mm pmuuommu mum muaswmm .zH .uw>3m u0533mo cameo 0:» 803m mucmEHGmm @3023 30 xasn ca mHmU3Emno uacmmwo no uc03umuucmucou .m manme 74 00.0 30.0 30.0 00.0 03.0 33.0 03.0 33.0 33.0 33.0 00333cmouu3zn0 30.0v 30.0v 30.0v 30.0v 30.0v 33.0 30.0v 30.0v 30.0v 30.0v mc3o3ucmnouo33030n3.3 30.0 30.0v 00.0 33.0 30.0 00.0 30.0 33.0 00.0 30.0 3:333cmouo3no3ou0.3 30.3 33.0 03.3 33.0 33.3 33.33 00.0 03.3 00.3 33.3 .3033. 3300003nouo3cua3o0 03.3 33.3 33.3 33.3 03.3 30.0 33.3 33.3 33.3 30.3 00033300032 33.0 03.3 33.3 30.3 03.3 00.3 33.3 30.3 03.3 33.3 m3oum3nuoncmnouamuumzn3 30.0 03.0 03.0 30.0 33.0 33.3 00.0 00.3 33.3 30.0 mcmucmnouo3cumxmm 33.0 30.3 33.3 00.3 33.0 33.3 33.0 00.3 33.3 33.0 33003033 00.3 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 30.0v 3ocmgaouo3co3uau3.0.3 30.0v 30.0v 30.0 30.0 30.0 30.0 30.0 30.0v 00.0 30.0 3ocmnnouo3comuumen3.3.3.3 03.3 30.0 30.0 33.3 03.0 30.0 33.0 30.0 03.0 33.0 300030 33.0 00.3 03.3 03.3 00.3 33.0 30.0 30.3 30.0 33.3 30003003033003000 0300 0n00 3n00 3n00 330 muoe 0nos 330 3n00 3n00 3323330 330552 333m um>3m qusHmu 0:330 .AmeC3ucoov .3 33939 75 30.0 30.0v 00.0 33.3 33.0 33.0 30.0 30.0 33.0 30.0 000000003030030us 33.3 30.0v 00.3 00.3 03.3 30.3 33.3 30.3 03.0 33.3 000000003030030no 33.3 03.3 33.3 03.03 33.3 33.3 03.3 30.3 33.3 30.33 00003ououo3sonm 30.3 33.3 33.3 33.3 33.3 30.0 00.3 00.3 30.3 30.3 0000000030300 33.0 00.0 00.0 33.3 33.0 03.3 03.3 03.3 03.3 33.3 0333030033300 03.0 33.3 00.0 33.3 33.0 03.3 33.0 33.3 30.0 30.0 0030000000 30.3 33.3 33.3 33.3 03.3 33.3 33.3 30.0 00.3 30.3 000000xoe 03.3 33.3 30.3 03.3 03.3 00.0 30.0 33.3 00.0 00.3 000000300 33.0 33.3 03.0 03.0 33.0 03.0 30.3 33.3 33.0 03.0 0000033 03.3 33.3 00.0 33.0 30.0 30.0 00.0 33.0 33.0 33.0 03303030 30.0v 30.0 33.0 30.0 33.0 33.0 30.0v 30.0v 30.0 00.0 000n.0.0 33.3 33.0 33.3 00.3 33.0 33.3 33.0 00.3 30.3 30.3 300n.0.0 00.0 33.3 33.0 33.0 30.3 33.0 33.0 00.3 33.0 33.0 eaon.0.0 03n00 0n00 3n00 3n00 3n00 3u00 0u00 3n00 3n00 3n00 000020000 umnEsz 003m um>3m 3083300 0:030 .30000330000 .3 03003 76 30.0v 30.0 33.0 30.0v 30.0 30.0v 30.0v 30.0 00.0 30.0 000030030300333:3.3.3 30.03. 30.3 00.3 03.3 00.0 00.3 00.3 30.3 00.3 00.3 000003003030033a:n.3.3 00.0 00.3 30.0 00.3 30.3 03.3 33.3 00.0 00.0 03.0 0000o3mo3o300333:n.3.3 00.3 00.0 00.3 03.0 00.3 30.3 33.3 33.3 30.3 00.3 000300003030033a:0.3.3 30.0 30.0 03.0 00.0 30.0 30.0v 30.0 00.0 00.0 30.0 000300003o300333:m.3.3 30.0 30.0 30.0v 30.0 30.0 30.0v 30.0 30.0v 30.0v 30.0 00033030o3o30u03303 00.0 00.0 00.3 00.3 00.0 00.0 00.0 33.3 00.3 33.0 0003330 30.0v 33.0 30.0 03.0 03.0 30.0 03.0 33.0 03.0 03.0 00003003030003000 00.0 03.0 00.0 00.0 03.0 30.0 03.0 03.0 00.0 33.0 000300300:m.3:o3o3000300 03.03 00.0 00.3 00.0 00.0 30.0 00.3 33.0 33.3 03.0 000300033030 03.3 03.0 00.0 30.0 03.0 00.0 33.0 00.0 00.0 30.0 0000o3003o30030:m.3 00.0 33.0 30.0 00.0 03.0 00.0 03.0 30.0 03.0 03.0 0000o30o3o30030:3.3 00.0 30.0 00.3 00.3 03.3 00.0 30.0 00.0 00.3 33.3 0003000o3o30030:0 03:00 0:00 0:00 3:00 0:00 0:00 0:00 3:00 3:00 3:00 303050300 umnE:z 033m 3w>3m 3053300 60030 .300003ucouv .m 0320a 77 00.3 30.3 03.0 33.0 03.0 03.0 33.3 03.3 00.0 00.0 000000030033:0:03000 03.0 03.3 00.0 03.0 00.0 00.0 00.3 03.0 03.0 03.0 000000030033:x:03000 30.3 33.0 00.3 00.3 03.3 33.0 00.0 00.0 00.0 00.3 00003300 00.3 00.0 03.3 30.0 03.3 03.0 00.0 00.0 30.0 00.3 000300000000 3m.3m33.003 30.00 00.3 00.0 00.00 00.0 00.03 03.03 33.33 000330:0:03000 00.0 30.0 00.0 03.0 00.0 00.0 30.0 33.3 00.0 00.0 000000030030 03.0 00.0 33.3 00.0 00.0 03.0 00.3 30.0 33.0 00.0 000330 00.0 00.0 33.0 00.3 03.3 00.3 00.0 30.0 03.3 00.3 000000000 330030333 30.0 00.0 00.3 03.0 33.0 00.0 33.0 00.0 00.3 03.0 00030000303003030000000 30.0 30.0 30.0v 30.0 00.0 00.0 30.0v 00.0 00.0 00.0 00003000303030:0.3 30.0v 30.0 03.0 00.0 00.0 30.0 00.0 30.0 30.0v 00.0 000300003030:3:o3o300:3 30.0v 30.0 30.3 03.0 33.3 00.3 30.0v 03.3 03.0 03.0 000300000 33000:0:30 30.0 30.0v 33.0 30.0v 00.0 30.0v 30.0v 00.0 03.0 00.0 000300000 33000:0:30 03:09 0:03 0:00 3.10: 0:03 mI0D 0:0: m..0: NI0D 3:0: 300080300 HmQEn—z mflflm “ms/wax HNESHMU UCMHU .3000030000» .m 03009 78 ON.O 30.0V mm.o bN.O 30.0V 00.3 30.0v 30.0v 03.0 HN.O mCHEMmOHUHC AhnumEHD Om.b om.b om.m 00.3V Om.m ov.N3 oo.N oo.mv OO.NV ON.0 C3XOAUIQIONC0£3QIm~F.M.N 03.0 mo.3 00.N mm.o 00.3 m¢.3 mm.o 03.N mm.3 mw.N mcwumu£UCMI0IONcmm OHIUD mIUD mIUD NIOD 0:0: mIUD wlwb MIUD NIUD alUD 30908030m 303852 0030 3w>3m 0065300 00030 .AUmsc3ucou. .m @3n09 79 m.¢m m.ma m.vH m.NH m.aH m.ma m.m o.oH ¢.o m.NH HoconmouOHnouucmm m.m >.~H o.ma H.m m.v m.~H H.H N.¢ h.m m.m meccwnvouvhm 9.0m m.vm H.vm m.¢H w.mH v.¢m m.h- o.wm v.mH H.m~ Hocmzmouuwcwnlc.w m.H o.H H.ov h.¢ o.H m.oa 0.0 h.m H.H ¢.¢ HommMOIOIouuacwalo.v o.vm m.mm >.m~ H.5a m.¢fl ¢.> m.ma o.¢a >.m m.oa HocmnmouoHnowalv.N m.¢m m.oH H.m o.N m.m N.oH m.m m.o m.o m.m acmmuolm m.om o.mm N.OH m.¢ m.o m.ma h.m m.¢ o.v h.v HOmmuUIo m.hH m.mH b.m o.m m.H m.m N.o 0.0 5.0 ¢.H HochQOMOHSOIm m.mm «.ooa m.oe N.mH w.m «.mo N.m o.am m.ma m.mm HocmnmouoHnono h.mH o.mm m.Hm m.wm H.0v. m.mm N.¢N m.om m.mm o.mm conumu oacmmuo Hmuoe m.¢h b.mm ¢.vma N.hm m.mma v.Hh m.vm H.0N v.¢m m.mn conumo UflcmmuocH Hmuoa OaIOD mle mIoD hi0: QIUD mIUD VIOD MIUD NIUD HIQD umumEMHmm quESZ wuflm um>flm umEsHmo Ucmuo .A\OE mm vmuuommu mum sownz ~conumu cacmmuo ncm cacmmuocw Hmuou new ummoxm .A\ml mm vmuuommu mum muazmmm .zH .um>wm umESHmu Undue 0:» Eouw muc¢anmm mo mumum3 whom cw mamoasmno cacmwuo mo mcowumuucmocoo .o manna 80 m.hN wcosmaxoa mcuouOAco mcmvcwq saunamao moou.m.m scon.m.m mcwawcmOHUaZIm Amcmfl uoaooua mmv mazcmnmwn vmumcau0H50>aom mcwamnunmmz mcmucmnouoHsumme Hzcmnmflm Hocmnm umnESZ muam um>wm umEsHmo @lUD ocmuo umumEmumm .Anmscwucoo. .w manna 81 04 «.0 «A «.0 «.0 «A «.0 0.0 «.0 «.0 mcmgououflfioue.« «.0 «A 0.0 «.0 «A H.« 04 «.0 m0 04 mcmuconouficuTouoEoL 0.0 0.0 «.3 «A 0.0 0.: «.« m.« 0.0 0.0. 330500 «33.3 0.0 «.0v 0.« 0.0 0.0 0.0« m; «.00 04 0.0 mcmnumouoasoflaufiqé H.0v «.0v «.0v 0.0 04 «A 04 «A 0.0 «A mammoumouozofianm§J 0.« 0.« 0.0 «.0 0.0 0.0 0.0 «.H «.0 «.0 0032000320303 0.: 0.2 0.0 04 0.« 0.3 04 0.m «.0. «.m 00330 «.«H 0.3 0.0 92 m0 0.2 0.0 0.« 0.« 0.0 00303150 «.9 0.0 0.0 H.0v «.0v 0.0 0.0 0.0 0.0 «.0 00303032300 0.0« 0.3 0.00 0.3 0.... 0.0« 0.0 «.2 0.0« «.m« 0533802010 0.0 m.« «.0 m.« 0.0 a; 0.0 0.0 H0 0.0 30233020 «A 04 «.0 «.0 «.3 «.0 «A «.3 0.0 «.0 0333332 0.0 0.0 0.0 «.0 0.0 m; 0.0 0.0 «A 0.0 330303 0700 0-00 0-00 700 0-00 AT00 0:00 «-00 «-00 T00 $00533 umn€=z muflm um>wm umEsHmo vcmuo .Avmacwucouv .0 manna 82 0.«« «.«« «.0 0.0 0.0 0.0« «.0 0.0 0.« 0.0 mcmnucmuos«munu0ucmm 0.0 «.m 0.« «.« 0.0 0.« 0.0 0.« «.0 «.« mcmnucmuos«uuxuoucmm 0.0 0.0 0.«m 0.0 «.« m.m« 0.« m.« 0.0 0.0 mammauno 0.00« 0.00« «.00« 0.«« 0.00 0.00« «.mm m.0«« «.00 0.0m« mcmucucmcmnm «.« «.« 0.m «.0 0.« 0.m «.0 «.0 0.0 0.« mcmummumuoucmm 0.«« «.«m 0.00 0.0 0.0 «.mm m.0« 0.«« m.m« 0.0m mcmsucmuos«m 0.0« 0.0« 0.0« 0.0 «.0 «.0« 0.0 0.0 0.0 «.0« mcmumm «.0 0.0 m.0 0.0 0.0 m.« «.0 0.«« m.«« m.«« mumnmmocm «ammuo«ue «.« «.0 m.« «.0 «.0 m.« «.0 0.0 «.0 0.0 mcmucmnouu«:ouo«nomucmm 0«-00 0:00. 0:00 «-00 0-00. 0.00 0-00 «:00 «-00 «-00 «mumEmumm umnssz mu«m um>fim umESHmu ncmuw .«vmscwucoo. .o manna 83 Concentrations of the various compounds present in sediments varied greatly. Chemicals such as m-chlorophenol; 2,6-dichlorophenol; 2,4,6- trichlorophenol; 2,3,5,6-tetrachlorophenol; 3,4—dichloroaniline; 3,3- dichlorobenzidine; p,p'-DDD; tetrachloroethylene; 1,2,3-trichlorobenzene; 1,1,1-trichloroethane; di-Q-butyl phthalate; l-chloro-2-nitrobenzene and 2,4-dinitrotoluene were generally present in the low ug/kg (ppb) range (Table‘S). Compounds exhibiting the greatest sediment concentrations were the various polycyclic aromatic hydrocarbons (PAHs), total polychlorinated biphenyls (PCBs, as Aroclor 1248), p,p’-DDE, toxaphene, p-chlorotoluene, ethylbenzene and p-dichlorobenzene. These compounds were generally present in the 2-20 mg/kg range although several of the PAHs were present at concentrations as great as 100 mg/kg (Table 5). Percent TOC ranged from 4.4 to 28.1% in the sediments while percent oil and grease ranged from 1.6 to 13.5% (Table 5). Most compounds observed in sediment pore waters were present in the low ug/L range (i.e., 0-10 ug/L, Table 6). Notable exceptions included phenol and the PAHs, phenanthrene and naphthalene. These compounds were present at concentrations in pore water as great as 326, 245 and 452 ug/L, respectively (Table 6). Several other compounds such as p-chlorotoluene, fluoranthene, pyrene, 2,4-dichlorophenol, 2,4-dinitrophenol, pentachlorophenol and biphenyl were observed in pore water at concentrations in the 10—100 ug/L range. Pore water TOC concentrations ranged from 18.7 to 52.8 mg/L (Table 6). Metals Detectable concentrations of most metals analyzed for were present in all study site sediments (Table 7). Iron, magnesium and manganese were 84 «.0 «.0 0.0 m..« min 0.00 m6 m.« ~43." «.ov a m><\«uuoz 0.03 0.000 0023 3.00 mm.0« 0mg... 00.0 00.: «0.0 0.02 « m>¢ «mm 00.0 mmé 0.70m 00.0..” 3.0 mwém 2.: 3.0a 2.4 so“; 0m~.«. OM06 mead m00.~ «mm.m «mmé ~¢~.m 0004 mama oom.m «550950: 30.0 000.0” 0«¢.m mmm.m «m~.m vmm.~ «004 «00.0 0006 «00.0 mmmcmmcmz 02.0 00.0.0 M000 omw.m 000.0 m«m.o «003 000.0 0m0.~ mo«.o 0:..«N mm0.0 «00.0 0mm.0 00H.0 mmo.0 00H.0 H0m.0 $3.0 $0.0 0m0.0 meoaz oomé 0H0.H 0006 mam...” 0mm.a m00.0 0mm.0 m0¢.0 20.0 «90.0 momma bmm.0 «30.0 «.0m.0 20.0 :VN.0 N¢m.0 000.0 mma.0 0NN.0 000.0 uwmmoo 000.0 h«50.0 mmmé 0.8.0 mm0.0 mmv.0 03.10 m0m.0 «00.0 000.0 ESMEOHSU 0H0.0 Nm0.0 000.0 000.0 000.0 NH0.0 N00.0 Nm0.0 000.0 0N0.0 0.54.550 m.NN 010..” v.0N 0.0 0.0.” 0.0«. ¢.N «.«. 0.0 0.0 memomunuCMIMIONcmm OHIUD 0IUD wIUD hi0: QIUD mIUD club MIG: N100 HIUD MmumEmumm umnEsz wuHm um>«m umE:«mo pamuo .u3 auu 50\m 21 mm pmuuommu m..« suit: .m>< ummuxm . 203 56 9180 mm pmuuommu mum muasmmm .zH 3.53m 005300 0:30 map so: 3095.000 ««.« $2: 32030 03.00.35. 300 0:0 230.: «0 00030308000 .0 2nt 8S «.03 «no 20\0 :1. \ «03 «00 50\c« + «z + 00 + so + 00 210 mmc«00«sm m««um«o> 0«o¢ N H .Apmscqucou. .0 manna 86 generally present in high mg/kg to low gm/kg concentrations in solid phase sediments (Table 7). Of the metals of toxicological concern in aquatic systems, zinc, lead and chromium were present at concentrations as great as 5.23, 3.94 and 1.22 gm/kg, respectively. Copper, nickel and cadmium concentrations were generally below 500 mg/kg. Sediment AVS concentrations also are presented in Table 7 along with the molar metals (Cd + Cu + Pb + Ni + Zn)/Avs ratios for each sediment. The concentrations of metals in sediments used in the calculation of the molar metals/AVS ratios were not determined by sequential extraction during the AVS analysis as recommended by Di Toro et al. (1991). The molar metal/AVS ratios for the sediments ranged from <0.l (i.e. no free metal) at site UG-l to 144.2 (potentially a large amount of free metal) at site UG-Z. Only three sites, UG—2,4 and 5 had molar metal/AVS ratios >2.0. Although the metals concentrations reported here were not determined by the sequential extraction (cold, weak acid; Di Toro et al. 1992), the harsher extraction technique used in the analyses reported here would result in conservative, worst case estimates of metal bioavailability. Copper and zinc were the only metals of toxicological concern typically present in pore waters at concentrations greater than the ICP LOD for these metals (0.005 mg/L) (Table 8). Aluminum and arsenic were the only other two metals or metalloids of concern observed in any pore water sample at concentrations greater than their respective LODs of 0.100 and 0.050 mg/L (Table 8). 87 000.0v 000.0v 000.0v 000.0V 000.0v 000.0v 000.0v 000.0V 000.0V 000.0V can. 0m0 . CV 00 . m." 00H .0v 00H .0v mmo . 0 0m0.0v 00H .0v 00H .0v 00H .0v ONH . 0 Essa—55¢ mm0.0 GHH.0 «00.0 H00.0 00v.0 000.0 ¢MH.0 m~0.0 00.10 0H0.0 Dawn 0N.H 300.0 00N.0 043.0 00N.0 00H.0V 00H.0V 00.70 H.230 0MN.0 msuonmmonm 0No.0v 0m0.0v 0N0.0v «no.0 0N0.0V 0N0.0v mm0.0 0N0.0v VHH.0 0HH.0 Encwnnadoz 000.0 N06 mON.0 00H.0 000.0 0H0.0v 000.0 H0010 0H0.0V 00.70 009.8932 0m.0m 0m.00 00.00 0H.va 0m.0m 00.0w om.mm 00.0w 0N.v 0N.m¢ Esammcmmx 0m0.0 0H.0m m0.H 000.0 000.H NOH.0 0mm.0 m0m.0 0N0.0 0m¢.0 COMH 0H0.0v 0H0.0v 0H0.0V 0H0.0V 0H0.0V 0H0.0v 0H0.0V 0H0.0V 0H0.0v 0H0.0v uHmnOO m00.0v mN0.0 000.0 000.0 000.0 0H0.0 H00.0 00H.0 000.0 000.0v uwmmoo 0m.0m 0.00m 0.mwN 0N.H0 0.mva no.0 00.00 0.HHa 0¢.HN o.m¢H Endoamo mvN.0 0vm.o vmm.0 mam.0 N¢N.0 000.0 000.H NON.0 H00.0 00m.0 Eadhmm mam.o 0NN.0 0N0.o mvN.O mma.o NmH.0 mam.0 me.0 00H.O 000.0 COuOm 0700 0-00 0:00 To: 0:00 0-00 700 «-00 «:00 «:00 300633 umnEsz muHm um>«m umEsamo pcmuo .zH .um>«m umfisamo ccmuo mzu Eouu mucmEHUom mo mumum3 whom ca .A\0EV madame mo macaumuucmocoo «mace .0 manna 88 vmukamcm no: u dz « 00« . 0v 00« . 0v 00« . 0v 00« .0v 00« . 0v 00« . 0v 00« .0v 00« .0v 00« .0v 00« . 0v «9.32 02 0m.«m 00.00 00.0 00.0 « <2 00.2 00.00 00.0« 00.«0 2300300 0.««« 0.00« 0.03 00.00 00.00 0«.«m 00.00 0.0«« 00.3 0.0«« 53.000 03.3 000.0v 80.3 80.3 00.0.0v 000.0v 000.0v 000.0v 0m0.0v ««m.0 3000.3 03.3 000.0v 000.0v 000.0v 000.0v 000.0v 00«.0v 000.0v 00«.0v 00« .0v 530300 0«0.0v 0«0.0v «00.0 03.0 0«0.0v 0«0.0v 0«0.0v ««0.0 30.0 0«0.0v 003 000.0v 000.0v 00.0.0v 000.0v 000.0v 000.0v 000.0v 00.0.0v 0m0.0v 000.0v .«usoumz 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0.00.0v 0«0.0v 000.0v 000.0v 23.500 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 0«0.0v 2350.20 000.0v 000.0v 000.0v 000.0v 000.0v 000.0v 00......0v 000.0v 00m .0v 000.0v 23:05 0700 0:00 0:00 700 0:00 0:00 «7.00 0:00 «:00 «:00 0302030 umnEsz muam um>«m umESHmo venue .Avmsswucoo. .0 manna 89 000.0v 000.0v 000.0v 0«0 00«.0v 00«.0v 00«.0v ssc«sa«¢ «n«.0 000.0 000.0 uc«« 00«.0 00«.0v 00«.0v mauonmuogm 00«.0 0«0.0v ««0.0 sacmun««oz 0««.0 000.0 000.0 000000002 0«.«« 0«.¢0 00.0« e:«mmcomz 0«0.0 ««.0 «00.0 000« 0«0.0v 0«0.0v 0«0.0v 0«unoo 000.0v 000.0v 000.0v ummmou 00.00 0.mm« 0.«0« ss«u«mo 000.0 «0«.0 mem.0 e=«umm 00«.0 0««.0 00«.0 couom m«|00 ««-0: ««100 umumEmumm umnEsz mu«m um>flm umEsamo Ucmuo .Auoscwucouv .0 wanna 9O vouaamcm no: u £2 « 00«.0v 00«.0v 00«.0v «mxowz 00.m« 0«.0« om.0 Es«mmmuom 0m.0m 00.00 0.00m Eswvom omo.ov omo.ov omo.ov 0«cmmu0 00«.0v 00«.0v 00«.0v Echmamm 0«0.0v 0«0.0v 0«0.0v 00mg 000.0v 000.0v 08.3 «.398: 000.0v 000.0v 000.0v Esaevmo 0H0.0v 0H0.0v 0H0.0v Esdfiouno oom.ov 00m.ov oom.ov Es«««mna male: NHIOD «anon umumEmumm umnEsz muflm umEsamo pcmuo .Acmscwucouv .0 manna nmuxamcm you n 42 «.« m.« 0.« 0.0 «.« «.« 0.0 0.0 0.0 «.0 do: 03030 0003000 00« 00« 00« «S 00« 00 00« 00« 00« 0«« do: .0333 0.0 0.0 0.0 0.« 0.0 0.0 m.m 0.« «.0 «.0 1:00 003570: .002 «.« 0.0 0.0 0.0 0.0 02 «.0 0.0 0.0 «.0 00 m 0000 000m 000m 0«0« 0«0« <2 03 0«0m 0«0 0«0« «530251 .>u«>«0000:oo 00« 000« 00.....« 000 00« «z 0«0 000 00 000 m«0000 dos $303002 00...« 000« 00«« 000 00«« «02 02 000 00« 000 m0000 dos 60000000 0700 0:00 0:00 700 0-00 700 0-00 700 «:00 700 03050000 umnEsz muam uw>«m quDHMU Ucmuu cause may scum mucmEaumm no mumum3 whom CH mvcsomeoo .zH .um>«m umEDHMU «MUHEwno msomcmaamumae mo mcoflumuucmucoo .0 manna 92 vmnaamcm no: u dz H «2 £2 £2 A\ml .mkuasm ammouv>m 0N om ow A\01 .mnw:m>o 0.0 0.0 04 dog 6323.5: .002 m.m m.h h.h Em mmh ooHN Ommm NEu\mo:EI .huw>wuusvcou 00m 003 0% moomo doe £303me 000 000 03 moumo doe .mmmcnumm malwa NHIUD HHIUD umumemumm umnEDZ anm um>am umEsamo 6cmuw .Aumscwucoov .m manna A an ICU» ' ‘l 5‘: (D ift ran: 4 ass: 0f t [95“ COQf 93 Miscellaneous parameters Alkalinity and hardness in several of the samples were elevated (1040-1500 mg/L as CaCO3, Table 9) above the values commonly reported for surface waters while conductivity and Ph were within the ranges reported for surface waters (Cole 1988). Cyanide and H28 were present in detectable, although relatively low, concentrations but unionized N83 concentrations ranged from 0.2-8.1 mg/L (Table 9). Toxicity Tests Photobacterium phosphoreum Five, 15 and 30 minute ECSO values were calculated for sediment pore waters osmotically adjusted with both NaCl and sucrose (Table 10). Fifteen minute E050 values for NaCl- and sucrose adjusted pore waters ranged from 0.3-93.8 % and O.2-39.5 %, respectively; Pore waters osmotically adjusted with sucrose were generally equitoxic or less toxic than NaCl adjusted pore waters with the exception of pore waters from sediments collected at sites UG—7, 8, 9, and 10. Pore waters at these sites were from 1.3-2.4 times more toxic when osmotically adjusted with sucrose (Fig 9). Both sucrose and NaCl-adjusted.Microtoxo tests generally exhibited similar ECSO values at 5, 15 and 30 minutes. However, pore water from sites UG-2, 4 and 6 became more toxic with time in both sucrose- and NaCl—adjusted tests while pore water from sites 06-9 and 11 became more toxic with time only in the sucrose-adjusted tests. Several significant correlations were observed between the results of the Microtoxo pore water tests osmotically adjusted with NaCl and the results of the pore water organic chemical analyses. Correlation coefficients (r) between the Microtox® tests and 9:, and p-chlorophenol, 94 0.00 0.5 0.00 0.00 00a 00H «.00 00a 03 sun 03.00003 a 05'3qu m.m 00? 007 0.3 «.3 03A 002 0.0m 0000 a we .3 ~.m 00? 0.5 0.0m 0.00 0.3 00? 0.0m 0000 a we .qumvwlqw 0.: mém 0.3 «.0 0.0 0.2 Tm 0.0 H0 .800 Es om 9x333: 0.00 0.0« TE «.0 0.0 0.0« 0.0 0.0 an .0000 fie 3 03033: 5.00 0.3 0.0.0. 0.0 T0 0.3 0.2 mg am .800 52 0 0x333: 0.0m p.00 TS m.0 0.0 5.: 0.0 0.m Hz .0000 5.2 0m 0.80332 0.0« 0.00 W3 m.0 0.0 T3 0.0 0.0 Hz .0000 5.5 3 9x333: ~.m~ 0.3V 0.0« 0.0 E «.3 0.3 0.0 Hz .0000 5.2 m @0803on 0-00 7.00 0:00 0:00 0:00 0:00 «:00 T00 mmmmc umnEsz wuflm um>flm umEsHmo ccmuo .Aaouucoo ou m>wumHmH :Hmm #3 >uc mo coManflncw mmmmmMMIdw .m.mv mucommmu a no .umumB whom w umnuflm mm vwmmmumxm mum sumo Had .zH .um>wm amenamo vamuo Gnu Scum mucmswvmm mo muwum3 muom no madeHUmm xasn nufl3 Dmuosvcou mummu huflowxou mo muasmmm .OH manna 95 mmouosm u m .0002 u z 0 000 000 0.00 0.00 0.00 03 000 000000000 0 30% 0.00 0.00 000A 0.00 0.00 0000 0 00 .00000140 0.00 0.00 000A 0.00 0.00 0000 n 00 .mwmmmujw 0.00 0.0 0.00 0.00 0.00 00 .0000 005 00 exououo0z 0.00 0.0 000A 0.00 0.00 00 .0000 005 00 exououo0: 0.00 0.0 000A 0.00 000A 00 .0000 505 0 exououo0x 0.00 0.0 0.00 0.00 000A 02 .0000 005 00 000000002 0.00 0.0 0.00 0.00 0.00 02 .0000 005 00 exououo0z 0.00 0.0 0.00 0.00 0.00 02 .0000 :05 0 000000002 MHIUD N010: Halo: 00:0: mum: >Mmmm umnESZ 000m Hm>0m umEsamo 6:000 .00000000000 .00 00000 96 .000003 0000 0000 >0000 mo whammm 0x000000x 000 00500> 000m C08100 :0 ucmEumsmcm 0000800 0000030 0300m> 0002 no 0000000 «>0um0mmeou .m 003000 0030000 mp Nw FF or m m A m m v m N P b 0 b o 00 T .................................................. m .Rmv 9 .0 v. .................. A ............................................................... % ....00 M .l ............................................................................... v. M . . . W v0 0 :mow Saw I mTZ § 97 g-cresol, PCBs (as Aroclor 1248), p,p’-DDE, chloro- and ethylbenzene and benzo(k)fluoranthene ranged from 0.64-0.81. The results of sucrose- adjusted tests were also correlated with these same compounds in pore water. However, the total number of significant correlations was less for the sucrose-adjusted tests and the observed correlations were generally with ECSO values calculated after 15 and 30 minute exposures. The significance of these correlations was questionable due to the fact that if increasing chemical concentrations were related to greater toxicity (i.e., smaller ECSO value) the correlations should have been negative rather than ‘positive. bk: biologically' or statistically significant correlations were observed between the results of MicrotoxO test results and the results of the ICP metals or the miscellaneous chemical analyses of the pore waters. Toxic units (Sprague and Ramsey 1965) were calculated for pore water concentrations of unionized ammonia, Q- and p-chlorophenol, Q-cresol, ethylbenzene, Chlorobenzene, 2,4-dinitrophenol, 1,1,l-trichloroethylene, pentachlorophenol, phenol and naphthalene by dividing the pore water concentration by the 15—min ECSO value from NaCl~adjusted Microtoxo tests of the pure chemical (Kaiser and Ribo, 1988). Ammonia, naphthalene and phenanthrene were the only compounds present at >0.1 TU in the pore water samples. The calculated TU units for these three compounds were then summed and compared to the measured TU units for each sample (Table 11). Measured TU were calculated by dividing 100% by the lS-min EC50 from NaCl- adjusted pore water Microtox® tests. The total calculated TU for the pore water samples ranged from 0.2 — 4.6 while the measured TU ranged from 1.1 - 333.3. Comparison of calculated versus measured TU for sucrose-adjusted 98 .00003 000m «00800 no 0000 vouusn00|000z TH... 00000002 8000 00003 000m a 00 0000 008:00 + 00003 000m «000 o 0 .00008030 0030 no 0000 pmuusnu0nao0z 000000002 8000 000m 008:00 + .0000 000080no 00003 0000 v ovmhfiflflme HOG 0H03 mCOfiUflhuch—hoo HMOflemSU HQUM3 whom mmflmumfl QHQMHdM>fl HOG fl ‘2 M Hmmfl MUHHQMHMQ UCM HOWHMM N 0000 o000 000 000000 0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.0 0.000 0.00 0.0 0.00 0.00 000 00000002 00000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 000 0000000000 00000 02 02 02 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 000 000000000000 02 02 000 .0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0000 00000000002 0.0 0.0 0.0 0.0 030 0.0 0.0 0.0 0:0 0.0 0.0 0.0 0.0 00.0000 0000550 000000000 00 N0 00 00 0 0 0 0 0 0 m 0 0 00\00. 000050000 0000 005 00 0mn85z 0000103 0m>0m 0080000 00000 000080n0 00:0 0059 0:0 000003 000m no 00000 00003 000m so nmm0n 0000080009 00000000 000 0:9. 000cs 00x00 00003 000% 00050008 0:0 0000050000 .0002 £003 pmumsno0 >0000000800 0003 00000 x0000002 .000008020 000000000: 8000 00«—00> omom 9.08:3” U000 0.000000000000000 00008020 .HH manmfi 99 tests was not conducted due to the paucity of data for sucrose-adjusted tests of pure chemicals. D. magna and C. dubia Pore water ECSO values for D. magna ranged from 5.5% pore water for site 06-8 to >100% pore water at sites 06-2, 6 and 7 (Table 10). _griodaphniaggubia 48 h ECSO values ranged from 3.2% pore water at site 06-8 to >100% at sites UG-2 and 7 (Table 10). With the exception of sites 06-3 and 4, where pore water was approximately 3-4 times more toxic to Q; maggg than to C. dubia, ECSO values indicated C. dubia were always as sensitive or more sensitive than D. magna to the toxic effects of the sediment pore waters. Daphnia magna 48 h ECSO values were negatively correlated (r = - 0.65) with concentrations of dieldrin in pore water while C. dubia 48 h ECSO values were negatively correlated with pore water concentrations of 2, 4-dinitrophenol, dieldrin, fluoranthene, phenanthrene and benzo(k)fluoranthene (r = -0.70, -0.67, -0.72, -0.74 and -O.65, respectively). No significant correlations were observed between concentrations of metals measured by ICP in pore water and the results of the acute daphnid tests. However, significant correlations were observed between pore water concentrations of unionized ammonia and alkalinity and the 48 h ECSO values for both D. magna (r = -O.69, -O.6l) and C. dubia (r = -0.60, -O.74). In a manner analogous to that used for the MicrotoxO tests, TU were calculated for pore water concentrations of unionized ammonia, alkalinity (bicarbonate ion), copper, zinc, naphthalene and phenanthrene based on 48 h LCSO values for tests with the pure compounds (Table 12). Forty-eight 100 a.“ m.m o.Hv ¢.H m.a «.mH o.Hv o.Hv m.H N.o o.Hv o.av m.n woe vmusmmmz Hmuoa m.o N.¢ m.H a.m m.m >.¢ m.m o.H 0.0 h.m o.v ¢.H v.v has .uHmo Hmuoa £2 £2 tz m.o ¢.o m.o o.o H.o «.0 H.o m.o H.o m.o moon mcmunucmcmnm £2 «2 «z N.o N.o H.o «.0 H.o 0.0 H.o H.o 0.0 m.o mooam mamamnunmmz «.0 H.o H.o 0.0 ~.o H.o H.o v.0 o.o N.o 0.0 «.0 0.0 mmmo ++cu H.o H.o H.o H.o v.0 H.o H.H H.o N.o m.o m.m 0.0 H.o vmo ++so m.o m.H 5.0 m.o H.H o.H m.o m.o mcz ¢.o m.o H.o v.0 NoooHNm amoom H.o ¢.~ e30 m.H m.H m.~ 0.0 m.o m.o o.m m.o H.o H.m Hoomm macoeem cmuflcofica 2 NH S 2 m m n o m e m N a 333 umpmfimumm cmoq n we umnE:z muflmlua um>flm umEsHmU Ucmuo HMUHEan musm mmmmaldm .mamanmno musm vcm mumumz whom no mumwu auwowxou mason mwmmmldw 0cm mammaldm scum mmsHm> omoq n we cam mcoHumuucmocoo Hmowemcu umumz whom no vwmmn mumumemumm vmuomamm no“ ADHV mafia: uflxou umums whom umuammme 0cm vmumHsuamo .NH manna lOl .moomo ma q\me can no unoccuun umumz causaxoummu no omoq a we .oomma ¢mm .m.o .qmmH .Hu um cavemaaaz o m .nooao an q\me oo~ mo unocoumn umumz «unswxoummm um omoq a me .nomma «an .m.a ¢ .omcwgmumn mm3 omoq on no omuaumme no: mm3 mcowumuucmucoo amu,.nEmno umum3 whom musmomn 0.333625 no: u m2 m nNmmH .Hm um 9.02 N ammma can .m.: H in wé oév v...” mé mém 04v m4 £2 “UH H6 04v H6 was omusmmmz 130m. N.N $6 mé win 0.2» N6 w.~ H6 £2 N.m o.m 0.0 0.0 hon. .oamo Hmuoa ¢.H ad ad H.o N.H m.o m.o N...“ <2 v4 m.o HQ «.0 m.um> ++:N 0.0 «.0 «.0 N6 «.0 0.0 ¢.o 0.0 <2 m.o m.o m.o 0.0 m..um> ++so 0.0 mé m.o N.o m4 mé 0.0 To m2 m.o 0.0 H.o m.o Noooomn Imoom «.0 iv m.o 5m o.m m.m m.o m.o <2 o.m m.o H.o o.m m.um> mwcog nmuflcofis ma NH Ha 0H m m b m m e m m H Aa\mav “mumEmumm cmoq a we umnfisz muwmlus um>am umEsHmo Ucmuw Hmowemno musm midi .Anmscflucoov .NH magma 102 .Aaomfi .Hm um >maxcmv uchcmmmU mm mum sown: mmSHm> mHQMflum> u .Hm> m .umumz muom mHmEMm mo umwu huwuaxou mason mwmmml4w uo mammaldm scum umuma muom w mm emoq : mv + uwumz whom wooa m .Hmowemno musm mo ummu huwoaxou musum mwmmmldw uo mammaldm Eon“ omoq : me + .ocou Hmoaemso umum3 muom h .Avmscflucoov .NH manna 103 hour C. dubia and D. magna LCSO values for unionized ammonia were obtained from U.S. EPA (1991) and U.S. EPA (1985b), respectively. Ceriodaphnia dubia LCSO values for unionized ammonia used for TU calculations were pH- specific based on the greatest pH value measured during the test of each pore water sample (U.S. EPA 1991) while the D. magna LCSO value was the mean of five separate L050 values from tests conducted at an approximate pH of 8.0 (U.S. EPA 1985b). Forty-eight hour LCSO values for alkalinity (bicarbonate ion), copper and zinc, and the PARS used in TU calculations were obtained from Hoke et al. (1992b), U.S. EPA (1980b,c); and Millemann et al. (1984), respectively. LCSO values for the metals were at an approximate water hardness of 200 mg/L as CaCo3. Based on the pure chemical data for the two cladoceran species, the total calculated TU for the pore water samples ranged from 0.4 - 6.9, while the measured TU ranged from 1.0 - 18.2 (Table 12). Unionized ammonia and bicarbonate ion accounted for the greatest proportion of the total TU calculated for both D. magna and C. dubia (Table 12). Chironomus tentans Percent inhibition in dry weight gain in C. tentans exposed to sediments from the Grand Calumet River ranged from 37% at 06-7 to 100% at sites UG-l, 3 and 4. Only one site, UG-7, exhibited a % inhibition of dry weight gain of less than 90%. Because the range of response for C_. tentans was very small if the data from site UG-7 were excluded from the analysis, no further attempts were made to correlate results with the results of chemical analyses or to calculate TU based on observed chemical concentrations. Discussion The sediments and sediment pore waters from a number of sites in the Grand Calumet River system of northwest Indiana contained detectable concentrations of a wide variety of organic chemicals and metals. Simple visual inspection of sediments from the system, however, led to the conclusion that one of the primary contaminants in the system was oil and grease. The concentrations of this broad category of petroleum hydrocarbons ranged from 1.6-13.5% on a sediment dry weight basis and undoubtedly, even in the absence of other contaminants, would exert a strong influence on the presence and/or distribution of benthic macroinvertebrates in the system. Previous studies have reported on the depauperate nature of the benthic’macroinvertebrate community in theeGrand Calumet River (IDEM 1988). The oil and grease content of the sediment also was likely at least partially responsible for the high mortality and inhibition of dry weight gain observed in the C. tentans test. Petroleum hydrocarbons are a major contaminant of aquatic systems with as much as 6 million metric tons of these products introduced into aquatic ecosystems worldwide on a yearly basis (NAS 1975). Petroleum hydrocarbons are a mixture of hydrocarbons and trace elements which can effect almost all aquatic macroinvertebrates by direct exposure (Petrakis and Weiss 1980, Hoehn et al. 1974). Petroleum hydrocarbons may affect macroinvertebrates by coating gills or other body surfaces responsible for cutaneous respiration thus limiting oxygen exchange, by direct toxic action, by bioaccumulation of hydrocarbons or by blanketing the substrate and preventing colonization. The impact of a massive crude oil spill on 104 105 macroinvertebrate fauna in a stream system*was described by Crunkilton and Duchrow (1990). A three orders of magnitude decrease in expected numbers of organisms was observed for a month after the spill. Species diversity and the number of sensitive species (mayflies, stoneflies) were decreased for almost a year after the spill. The authors observed that the visible presence of petroleum hydrocarbons in the stream substratum was an effective predictor of effects on the benthic macroinvertebrate community and that total flow volume and occurrence of scouring due to floods were the major factors controlling recovery. Schloesser et al. (1991) also observed that the visible presence of petroleum hydrocarbons in sediments was a good indicator of effects on Hexagenia limbata abundance in the upper Great Lakes connecting channels. In a study of the effects of oil/gas field produced.water on the benthic macroinvertebrate community in a small gradient estuary, Nance (1991) reported that sediment oil content was a more important determinant of population abundance than salinity. A sediment hydrocarbon concentration of 2.5 mg/gm dry weight sediment (0.25%) was observed to cause a minor depression of macroinvertebrate abundance while 5.0 mg/gm (0.5%) was observed to cause major effects on abundance. Assuming the presence of no other contaminants, the observed oil and grease content of sediments in the Grand Calumet River (1.6-13.5%) alone appears to have been sufficient to prohibit the development of a viable benthic macroinvertebrate community in the sediments. Based on personal observations made by the authors during field sampling on the Grand Calumet River, it also appeared that petroleum hydrocarbon inputs to the system were a continuing, rather than simply a historical, problem. Although petroleum hydrocarbons in sediments from the study area appeared to affect the results of the C. tentans bulk sediment tests, the 106 physical effects of this suite’ of compounds should have» been less important in determining the results of the pore water tests with 2. phgspgoreum, D. magna and C. dubia. The limited water solubility of most petroleum hydrocarbons and the filtration step (Whatman GF-F, 0.7 pm nominal pore size) used in the preparation of sediment pore waters could have removed all but the most water soluble petroleum hydrocarbons (i.e. naphthalene, phenanthrene) from the pore waters. Therefore, the results of the pore water tests provided information on the toxicity of water soluble compounds which likely was not provided by the C. tentans test results due to the confounding presence of large amounts of insoluble petroleum hydrocarbons in the sediments. The results of separate sucrose and NaCl osmotically-adjusted MicrotoxO tests on a sample may be helpful in determining the causes of observed sample toxicity (Hinwood and McCormick 1987, Ankley et al. 1990a, Hoke et al. 1992a). Changes in sample toxicity over the 30-min course of the full Microtoxo test also may be helpful in identifying potential toxicants. Several ionic chemicals (certain metals, ammonia) have been observed to be more toxic in Microtoxo tests osmotically adjusted with sucrose (Hinwood and McCormick 1987, Ankley et al. 1990a) while chlorine was more toxic in NaCl-adjusted tests (Ankley et al. 1990a). Some metals also exhibit a pattern of increasing toxicity with time while the toxicity of ammonia and many organic chemicals is constant over time. In general, little difference was observed in the toxicity of GCR pore waters in Microtoxm tests osmotically-adjusted with sucrose or NaCl. This may indicate that ionic toxicants in the pore water were not responsible for the majority of the observed toxicity. Pore waters from UG-7, 8, 9 and 10 were more toxic in tests osmotically-adjusted with sucrose while pore 107 waters from UG-ll and UG-13 were more toxic in tests osmotically adjusted with NaCl. Measurable concentrations of Cu and Zn were present and pH and unionized ammonia also were greater in pore waters from site 06-? through 10 (Tables 8, 9). Zn is known to be more toxic at higher pH (Ankley et al. 1991) and higher pH also shifts the ammonia equilibrium towards greater prOportions of unionized ammonia which is the more toxic form of ammonia to most aquatic species (U.S. EPA 1985b). No increase in toxicity with time was observed in any Microtox‘ID test conducted on these pore waters. These observations coupled with the known presence of municipal wastewater treatment plant discharges on this section of the GCR (IDEM 1988) strongly implicate unionized ammonia as one of the principal contaminants causing the effects observed in Microtoxo tests of pore*water from sites UG-7 through 10. Greater concentrations of metals in pore water (i.e., UG-2,3,4) or greater concentrations of ammonia (i.e., UG-1,4) were observed but pore water from these sites also generally had lesser pH values. The increase in toxicity with time observed over the course of both NaCl-and sucrose- adjusted Microtoxo tests of pore waters from sites UG-2,4 and 6 suggests, however, that metals were responsible for at least part of the observed toxicity. No explanation is evident for the greater toxicity in NaCl- adjusted tests of pore waters from sites UG-ll and 13 because complete chemical analyses were not conducted on sediments or pore waters from these sites. Based on the calculated versus measured TU from Microtoxo lS-min E050 values for the study site pore waters, a large proportion of the observed toxicity was unaccounted for at most sites, except sites UG-7 through 06-10. The contribution of the PAH, phenanthrene, to the total 108 calculated TU for a given site was generally equal to or greater than the contribution of ammonia. Naphthalene TU were generally equal to or less than the unionized ammonia TU at each site. Copper and zinc TU from NaCl- adjusted MicrotoxO tests were generally 5 0.1 TU for each site (data not shown) and it was not possible to calculate fluoranthene TU because no Microtoxo toxicity data exist for this compound. Calculated TU exceeded measured TU at sites UG-8,9 and 10, however, when the contribution of the PAHs was dropped from the calculated TU there was much better agreement between total calculated and measured TU. An additional factor (i.e., pore water bicarbonate ion concentration) discussed below appeared to cause toxicity in the cladoceran pore water assays. However, no effect on the Microton test was observed in a series of experiments designed to evaluate the effects of water hardness and alkalinity at concentrations up to 3000 mg/L as CaCO3, respectively (data not shown). At sites UG-l through UG-6 and UG-ll through UG—13, it appeared that unidentified compounds caused a large portion of the observed effects in the MicrotoxO tests. In 48 h pore water tests, C. dubia was, with the exception of site UG-4, always equally or more sensitive to the effects of pore waters than was D. maqna. The difference in response between the two species was generally small, perhaps indicating that the cladocerans were responding to the same contaminants with C. dubia being slightly more sensitive. At sites UG-3,5,6 and 9, however, C. dubia.was approximately 1.3-6 times more sensitive to the effects of the pore waters than was D. magna. This variability also could have been the result of the effect of pH on the relative species sensitivity to chemicals. C. dubia sensitivity to unionized ammonia exhibits a greater pH dependence than does that of Q; 109 maqna (Ankley et al. 1991, U.S. EPA 1985b). Lack of sensitivity to pH effects on ammonia toxicity also has been observed for Hyalella agtgca (Ankley et al. 1991). Sensitivity to some metals may exhibit a similar pattern since the zinc 48 h LCSO for C. dubia tested in very hard reconstituted water at a pH of 8.0-8.5 was 95 pg/L (Ankley et al. 1991) while the 48 h LCSO for D. magna tested under similar conditions was 655 pg/L (U.S. EPA 1980c). This factor alone could explain a large portion of the variation in the responses of the cladoceran tests, especially in light of the observations that the pore water pH values at sites UG-3,6 and 9 were 8.4, 8.0 and 8.4, respectively (pH was not measured on site UG- 5 pore water) while pore water zinc concentrations were 28, 490 and 114 pg/L, respectively. Total calculated TU for D. magna and C. dubia exceeded the measured TU at 8 and 10 of the 13 sites, respectively. However, total calculated TU for both species assumed that measured pore water concentrations of copper and zinc were present as the bioavailable free ion. This is unlikely due to the pH dependent nature of chemical speciation and the probable presence of many inorganic and organic ligands which could bind free metal ions in pore waters. A decrease in TU attributable to copper and zinc would result in a decrease in the total calculated TU for each pore *water and bring total calculated and. measured TU into closer agreement. Toxic units attributable to phenanthrene and naphthalene in W pore water tests were less than TU attributable to unionized ammonia and bicarbonate ion” The TU attributable to unionized ammonia and bicarbonate ion also accounted for the greatest proportion of the total calculated TU units in the C. dubia tests. Pore water concentrations of unionized 110 ammonia and alkalinity also were negatively correlated with the 48 h ECSO values from the cladoceran tests, which indicates that greater concentrations of these chemicals caused greater toxicity (lesser LCSO value) of the pore waters to the cladocerans. Ammonia is known to be toxic to cladocerans (U.S. EPA 1985b) and several authors have recently reported on the effects of carbonate alkalinity on cladocerans (Cowgill and Milazzo 1991, Hoke et al. 1992b). In an investigation of the toxicity and potential mode of action of the bicarbonate ion, Hoke et al. (1992b) demonstrated that bicarbonate ion was toxic to both D. magna and C. dubia and that sufficient bicarbonate ion was present in several GCR-IHC pore waters to cause a large portion of the observed toxicity of the pore waters to these species. These observations reinforce the importance of unionized ammonia and alkalinity in the TU calculations for the cladocerans. It was not possible to calculate the potential contribution of naphthalene and phenanthrene to the total measured TU for g&_ggbi§ tests because no 48 h reference toxicant LCSO data for these chemicals were available for C. dubia. The total calculated and measured TU for both cladoceran species at each site were generally observed to be in good agreement with the exception of site UG-8 where the total calculated TU for both species were much less than the total measured TU. One or more chemicals not measured during this study must have been present in the pore water from this site at concentrations sufficient to affect both cladoceran species. The relative sensitivities of the tests used during this study were very different. The C. tentans test appeared to be affected primarily by the physical presence of petroleum hydrocarbons in the sediments, which 111 also obscured any potential impacts on this species of contaminants in the sediment pore waters. The cladoceran tests appeared to be affected primarily by concentrations of unionized ammonia and bicarbonate ion in the pore water. Unionized ammonia and the PAHs naphthalene and phenanthrene also were possibly important determinants of the toxicity of sediment pore waters in the Microtoxo test. However, at several sites, observed toxicity in both the Microtoxo and cladoceran tests could not be accounted for solely on the basis of the concentrations of the chemicals used in the TU calculations presented here. Reference toxicant data necessary for calculation of TU for a wide variety of chemicals are not available for either the MicrotoxO or the Q; m tests. The chemical analysis of study site sediments and pore waters included only 104 analytes. Although a large number of compounds were analyzed for in the samples, the potential for additional compounds to be present in the samples is great. Both of these factors limit the application of the TU approach, without a concurrent toxicity identification evaluation (TIE) effort Ankley et al. 1991), for determining the compounds causing the observed toxicity in tests of whole sediments and sediment pore waters. In addition, the TU approach assumes additivity of chemical effects and complete bioavailability of all measured analytes, which may or may not be a valid assumptions in complex environmental matrices, depending on the chemicals under consideration. Antagonism and synergism are equally plausible consequences for the expression of the toxicity of chemical mixtures. If chemicals exhibit their effects via different modes of action, the assumption of additivity of effects will not be met and calculated TU could be over-estimates of chemical effects. This 112 phenomenon, in addition to the various factors affecting chemical bioavailability, the lack of reference chemical toxicity data and the incomplete nature of the chemical analyses previously discussed, contribute to the observed discrepancy between calculated and measured TU. The results of the study presented here highlight the necessity and importance of the battery of tests approach for toxicity assessments which has been previously advocated by other investigators (Slooff et al. 1983, Millemann et al. 1984, Williams et al. 1986, Dutka and Kwan, 1988, Giesy and Hoke 1989). Each test responded in a unique way which emphasized the intrinsic sensitivity of the test, the differences in exposure routes among tests and the fate of individual chemicals or classes of chemicals in the samples. The study also demonstrated the advantages and limitations of a toxic units approach by itself for evaluating the potential causes of the observed toxicity in the various assays. A more utilitarian approach to assessments of contaminated sediments could incorporate the battery of assays approach and sediment TIE, including the evaluation of calculated versus measured TU, to identify and confirm the causes of observed sediment and pore water toxicity and, ultimately, guide site remediation efforts (Ankley et a1. 1991). Acknowledgements Inductively-coupled argon ;plasma spectroscopy and sediment, TOC analyses were conducted by the MSU Animal Health Diagnostics Laboratory and the MSU Soil Testing Laboratory, respectively; G. Ankley, V. Mattson, T. Burton, R. Merritt and several anonymous reviewers provided helpful comments which improved the final version of the manuscript. Jane Norlander, Debra Williams and Jane Thompson typed various drafts of the manuscript. Funding for this research was provided by the U.S. Environmental Protection Agency, Great Lakes National Program Office, Chicago, IL. 113 Literature Cited American Public Health Association/American Water Works Association/Water Pollution Control Federation (APHA). 1985. Standard Methods for the Examination of Water and Wast ater, 16th ed., APHA, Washington, D.C. pp. 615-714. Ankley, G.T., Peterson, G.S., Amato, J.R. and Jenson, J.J. 1990a. Evaluation of sucrose as an alternative to sodium chloride in the Microtox® assay: comparison to fish and cladoceran tests with freshwater effluents. Environ. Toxicol. Chem. 9:1305- 1310. Ankley, G.T., Katko A. and Arthur, J.W. 1990b. Identification of ammonia as an important sediment-associated toxicant in the lower Fox River and Green Bay, Wisconsin. Environ. Toxicol. Chem. 9:313-322. Ankley, G.T., Schubauer-Berigan, M.K., Dierkes, J.R. and Lukasewycz, M.T. 1991. Sediment Toxicity Identification Evaluation: Phase I (Characterization), Phase II (Identification) and Phase III (Confirmation) Modification§,of Effluent Procedures. Draft Technical Report 08-91, U.S. Environmental Protection Agency, Environmental Research Laboratory-Duluth, MN. Babich, H. and Stotsky, G. 1977. Reductions in the toxicity of cadmium to microorganisms by clay minerals. Appl. Environ. Microbiol. 33:696-705. 114 115 Batac-Catalan, z. and White, D.S. 1982. Effect of chromium on larval chironomidae as determined by the optical fiber light- interruption biomonitoring system. ZEntomological News 93:54- 58. Batley, G.E. and Giles, M.S. 1980. A solvent displacement technique for the separation of sediment interstitial waters. In, Contaminants andagadimenta, Vol. II, Baker, R.A., ed., pp. 101-117. Ann Arbor Science, Ann Arbor, MI. Bishop, J. 1987. The In-Place Pollutants Program: Backgrgund and Theoretical Concepts-Volume II. Ontario Ministry of Environment, Toronto, Canada. Brannon, J.M., Plumb, R.H. and Smith, I. 1980. Long term release of heavy metals from sediments. In, Contaminants and Sadimegta, Vol. II, Baker, R.A., ed., pp. 221-226. Ann Arbor Science, Ann Arbor, MI. Bulich, A.A. 1984. Microtox® - A bacterial toxicity test with several environmental applications. In, Toxicity Screening Procedures Using Bagterial Systema, Liu, D. and Dutka, B. J., eds., pp 55-64. Marcel Dekker, New York, NY. Bulich, A.A, Greene, M.W. and Isenberg, D.L. 1981. Reliability of the bacterial luminescence assay for determination of the toxicity of pure compounds and complex effluents. In, at c Toxicology and Hazard Assessmentl Pearson, J.G, Foster, R.B. and Bishop W. E., eds., pp 338-347. ASTM STP 737. American Society for Testing and Materials, Philadelphia, PA. Chapman, P.M. 1986. Sediment quality criteria from the sediment quality triad: An example. Environ. Toxicol. Chem. 5:957-964. 116 Cole, G.A. 1988. Textbook of limnology, 3rd. Edition. C.V. Mosby Co., St. Louis, MO 426 p. Cowgill, U.M. Takahashi, I.T. and Applegath, S.L. 1985. A comparison of the effect of four benchmark chemicals on Daphnia magga and Ceriodaphnia gabia-affinis tested at two different temperatures. Environ. Toxicol. Chem. 4:415-422. Cowgill, U.M. and Milazzo, D.P. 1990. The sensitivity of two cladocerans to water quality variables: salinity and hardness. Arch. Hydrobiol. 120(2):185-196. Cowgill, U.M. and Milazzo, D.P. 1991a. The sensitivity of Cegiodaphgia dubia and Daphnia magna to seven chemicals utilizing the three-brood test. Arch. Environ. Contam. Toxicol. 20:211-217. Cowgill, U.M. and Milazzo, D.P. 1991b. The sensitivity of two cladocerans to water quality variables: alkalinity. Arch. Environ. Contam. Toxicol. 21:224-232. Crunkilton, R. L. and Duchrow, R.M. 1990. Impact of a massive crude oil spill on the invertebrate fauna of a Missouri Ozark stream. Environmental Pollution 63:13-31. DeGraeve, G.M. and Cooney, J.D. 1987. Ceriodaphnia: an update on effluent toxicity testing and research needs. Environ. Toxicol. Chem. 6(5):331-333. Di Toro, D.M., Mahony, J.D., Hansen, D.J., Scott, K.J., Hicks, M.B., Mayr, S.M. and Redmond, M.S. 1990. Toxicity of cadmium. in sediments: the role of acid volatile sulfide. Environ. Toxicol. Chem. 9:1387-1502. Di Toro, D.M., Mahony, J.D., Hansen, D.J., Scott, K.J., Carlson, A.R. and Ankley, G.T. 1991. Acid volatile sulfide predicts the acute 117 toxicity of cadmium and nickel in sediments. Environ. Sci. Technol. 26:96-101. Dutka, B.J. and Kwan K.K. 1988. Battery of screening tests approach applied to sediment extracts. Tox. Assess. 3:303-314. Fallon, M.E. and Horvath, F.J. 1985. Preliminary assessment of contaminants in soft sediments of the Detroit Rivemu J. Great Lakes Res. 11:373-387. Giesy, J.P. and Hoke, R.A. 1989. Freshwater sediment toxicity bioassessment: rationale for species selection and test design. J. Great Lakes Res. 15(4):S39—569. Giesy, J.P, Graney, R.L., Newsted, J.L., Rosiu, C.J., Benda, A., Kreis, R.C., Jr. and Horvath, F.J. 1988. Comparison of three sediment bioassay' methods using lDetroit River sediments. Environ. Toxicol. Chem. 7:483-498. Giesy, J.P., Rosiu, C.J., Graney, R.L. and Henry, M.G. 1990. Benthic invertebrate bioassays with toxic sediment and pore water. Environ. Toxicol. Chem. 9(2):233-248. Graneli, W. 1979. The influence of Chironomus plumosus larvae on the exchange of dissolved substances between sediment and water. Hydrobiologia 66(2):l49-159. Greene, J.C., Miller, W.E., Debacon, M.K., Long, M.A. and Bartels, C.L. 1985. A comparison of three microbial assay procedures for measuring toxicity to chemical residues. Arch. Environ. Contam. Toxicol. 14:659-667. Hamdy, Y. and Post, L. 1985. Distribution of mercury, trace organics and other heavy metals in Detroit River sediments. J. Great Lakes Res. 11:353-365. 118 Hargrave, B.T. 1975. Stability in structure and function of the mud- water interface. Verh. Internat. Verein. Limnol. 19:1073- 1079. Hinwood, A.L. and McCormick, M.J. 1987. The effect of ionic strength of solutes on EC-SO values measured during the MicrotoxO test. Tox. Assess. 2:449-461. Hoehn, R.C., Stauffer, J.R., Masnik, M.T. and Hocutt, C.H. 1974. Relationships between sediment oil concentrations and the macroinvertebrates present in a small stream following an oil spill. Environ. Letters 7:345-352. Hoke, R.A., Giesy, J.P., Ankley, G.T., Newsted, J.L. and Adams, J.R. 1990. Toxicity of sediments from western Lake Erie and the Maumee River at Toledo, Ohio, 1987: implications for current dredged material disposal practices. .1. Great Lakes Res. 16:457-470. Hoke, R.A., Giesy, J.P. and Kreis, R.G., Jr. 1992a. Sediment pore water toxicity identification in the lower Fox River and Green Bay, Wisconsin, using the Microtox® assay. Ecotoxicol. Environ. Safety. (In press). Hoke, R.A., Gala, W.R., Drake, J.B., Giesy, J.P. and Flegler, S. 1992b. Bicarbonate as a potential confounding factor in cladoceran toxicity assessments of pore water from contaminated sediment. Can. J. Fish Aquatic. Sci. (In press). Hunter, R., Niemi, G., Pilli, A. and Veith. G. 1990. Aquatic information and retrieval (AQUIRE) database system. In, Computer Applications for Envirpamental Impact Analysis, Pillman, W., 119 ed., pp. 42-48. International Society for Environmental Protection, Vienna, Austria. Indiana Department of Environmental Management (IDEM). 1988. Northwest Indiana Environmental Action Plan. Draft Area of Concern Remedial Action Plan. IDEM, Indianapolis, IN. 183 p. International Joint Commission. 1985. Report of Great Lakes Water Quality. IJC, Great Lakes Water Quality Board, Kingston, Ontario, Canada. Jenne, E.A., Kennedy, V.C., Burchard, J.M. and Ball, J.W. 1980. Sediment extraction and processing for selective extraction and for total trace element analyses. In, Contaminants and Sedimentsl Vol. 11., Baker, R.A. ed., pp. 169-190. Ann Arbor Science, Ann Arbor, MI. Kaiser, K.L.E. and Ribo, J.M. 1988. Photobacterium phosphogeum toxicity bioassay. II. Toxicity data compilation. Tox. Assess. 3:195- 237. Kaiser, K.L.E. and Palaerica v.5. 1991. Photobacterium phosphoreum toxicity index. Water Poll. Res. J. Can. 26:361-431. Kszos, L.A. and Stewart, A.J. 1991. Effort-allocation analysis of the seven-day fathead minnow (Pimephales promelas) and Ceriodaphnia dubia toxicity tests. Environ. Toxicol. Chem. 10:67-72. Laskowski-Hoke, R.A. and Prater, BJL. 1980. Relationship of percent mortality of four species of aquatic biota from 96-hour sediment bioassays of five Lake Michigan harbors and.elutriate chemistry of the sediments. Bull. Environ. Contam. Toxicol. 25:394-399. 120 Laxen, D.P.H. 1985. Trace metal adsorption/coprecipitation on hydrous ferric oxide under realistic conditions: role of humic substances. Water Res. 19:1229-1236. LeBlanc, G. A. 1980. Acute toxicity of priority pollutants to water flea (QaphniaLmaqnaj, Bull. Environ. Contam. Toxicol. 21:684-691. Maki, A.W. 1979. Correlations between Daphnia magaa and fathead minnow (Pimephales promelas) chronic toxicity values for several classes of test substances. J. Fish. Res. Bd. Can. 36:411- 421. Matisoff, G., Fisher, J.B. and Matis, S. 1985. Effects of benthic macroinvertebrates on the exchange of solutes between sediments and freshwater. Hydrobiologia 122:19-33. Mazidji, C.N., Koopman, B., Bitton, G. and Voiland, G. 1990 Use of Microtox® and Ceriodaphnia bioassays in wastewater fractionation. Tox. Assess. 5:265-277. Millemann, R.E., Birge, W.J., Black, J.A., Cushman, R.M., Daniels, K.L., Franco, P.J., Giddings, J.M., McCarthy, J.F. and.Stewart, A.J. 1984. Comparative acute toxicity to aquatic organisms of components of coal-derived synthetic fuels. Trans. Amer. Fish. Soc. 113:74-85. Mokry, L.E. and Hoaglund, K.D. 1990. Acute toxicities of five synthetic pyrethroid insecticides to Daphnia magaa and Ceriodaphnia gapia. Environ. Toxicol. Chem. 9(8):1045-1051. Moore, M.V. and Winner, R.W. 1989. Relative sensitivity of Ceriodapgnia gapia laboratory tests and pond communities of zooplankton and benthos to chronic copper stress. Aquat. Toxicol. 15:311- 330. 121 Mosher, R.G. and Adams, W.J. 1982. Method for Conducting Acute Toxicity Tests with the Midge Chironorm tentans. Monsanto Environmental Sciences Report No. EAS-82—AOP-44, St. Louis, MO. Mosher, R.G., Kimerle, R.A. and Adams, W.J. 1982. MIC Environmental Assessment Method for Conducting 14-Dav Partial Life Cygle Flow-Through and Static Sediment Exposure Toxicity Tespa wish the Midqe Chironomus tentans. Monsanto Environmental Sciences Report No. ES-82-M-10, St. Louis, MO. Mount, D.I. 1989. Methode for Aquatic Toxicity Ideatifigagipn Evaluatione: Phase III Toxicity Confirmation ProcJLdgreg. EPA/600-3-88/036. U. S. Environmental Protection Agency, Duluth, MN. Mount, D.I. and Norberg, T.J. 1984. A seven-day life—cycle cladoceran toxicity test. Environ. Toxicol. Chem. 3:425-434. Mount, D.I. and Anderson-Carnahan, L. 1988a. Methods for Agpatic Toxicity Identification Evaluatione: Phase I ox' Characteriaation Proceduree. EPA/600-3-88/034. U.S. Environmental Protection Agency, Duluth, MN. Mount, D.I. and Anderson-Carnahan, L. 1988b. Methods or A t c Toxicity Identification Evaluatione: Phase I To c t Characterization Proceduree. EPA/600-3-88/035. U. S. Environmental Protection Agency, Duluth, MN. Nacci, D., Jackim, E. and Walsh, R. 1986. Comparative evaluation of three rapid marine toxicity tests: sea urchin early embryo growth test, sea urchin sperm cell toxicity test and Microtox®. Environ. Toxicol. Chem. 5:521-525. 122 Nance, J.M. 1991. Effects of oil/gas field produced water on the macrobenthic community ix: .a small gradient estuary. Hydrobiologia. 220:189-204. National Academy of Sciences (NAS). 1975. Petroleum in the Magine Environment. National Academy Press, Washington, DC. Nebeker, A.V., McCrady, J.K., Shar, R.M. and McAuliffe, C.K. 1983. Relative sensitivity of Daphnia ma na, rainbow trout and fathead minnows to endosulfan. Environ. Toxicol. Chem. 2:69- 72. Nebeker, A.V., Onjukka, S.T., Cairns, M.A. and Krawczyk, D.P. 1986. Survival of Daphnia ragga and Hyalella azteca in cadmium spiked water and sediment. Environ. Toxicol. Chem. 5:933- 938. Oliver, B.A. 1985. Desorption of chlorinated hydrocarbons from spiked and anthropogenically contaminated sediments. Chemosphere 14:1087-1106. Oris, J.T., Winner, R.W. and Moore, M.V. 1991. A four-day survival and reproduction toxicity test for Ceriodaphnia QBQLQ- Environ. Toxicol. Chem. 10:217-224. Petrakis, L. and Weiss, F.T. 1980. Petroleum in the Marine Environment. Advances in Chemistry Series 185. American Chemical Society, Washington, DC. 371 p. Plumb, R.B., Jr. 1981. Procedure for Handling and Chemical Apalyeie gf Sediment and Water Samplee. Technical Report EPA/CE-Bl-l, U.S. EPA/ACOE Technical Committee on Criteria for Dredged and Fill Material, U.S. ACOE, Waterways Experiment Station, Vicksburg, MS. 403 p. 123 Pranckevicius, P.E. 1986. 1982 Detroit Michigan Area Survey. EPA Report No. 905-4-86-002, U.S. Environmental Protection Agency, Chicago, IL. Rodgers, P.W., Kieser, M.S. and Peterson, GUW. 1985. Summer 0 he Existing Status of the Upper Great Lakes Connecting Chanpele Data. Limno-Tech Inc., Ann Arbor, MI. Sadler, W.O. 1935. Biology of the midge Chironomus tentane Fabricius and methods for its propagation. Cornell Univ. Agric. Exp. Sta. Mem. 173:25 p. Samoiloff, M.R., Bell, J., Birkholz, D.A., Webster, G.R.B., Arott, E.G., Pulak, R. and Madrid, A. 1983. Combined bioassay-chemical fractionation scheme for the determination and ranking of toxic chemicals in sediments. Environ. Sci. Technol. 17:329- 334. SAS. 1988. SAS/STAT Guide for Personal Computers, Version 6.03. SAS Institute, Cary, NC. Schloesser, D.W., Edsall, T.A., Manny, B.A. and Nichols, S.J. 1991. Distribution of Hexagenia nymphs and visible oil in sediments of the Upper Great Lake Connecting Channels. Hydrobiologia 219:345-352. Slooff, W., Canton, J.H. and Hermens, J.L.M. 1983. Comparison of the susceptibility of 22 freshwater species to 15 chemical compounds. 1. (Sub) Acute toxicity tests. Aquat. Toxicol. 4:113-128. Sprague, J.B. and Ramsey, B.A. 1965. Lethal levels of mixed copper-zinc solutions for juvenile salmon. J: Fish. Res. Bda Can. 22(2):425-432. 124 Stewart, A.J., Kszos, L.A., Harvey, B.G., Wicker, L.F., Haynes, G.J. and Bailey, R.D. 1990. Ambient toxicity dynamics: assessments using Ceriodaphnia gapia and fathead minnow (Pimephales promelas) larvae in short-term tests. ZEnviron. Toxicol. Chem. 9(3):367-379. Takahashi, I.T., Cowgill, U.M. and Murphy, P.G. 1987. Comparison of ethanol toxicity to Daphnia m and Ceriodaphnia Mia tested at two different temperatures: static acute toxicity test results. Bull. Environ. Contam. Toxicol. 39:229-336. U. S. Environmental Protection Agency. 1980a. Water ual t its a Documents Availability. Federal Register. Washington, DC 45:79318—79379. U. 8. Environmental Protection Agency. 1980b. Ambient Wage; Qpality Criteria for Copper. EPA 440/5-80-036, U.S. EPA, Office of Water, Criteria and Standards Division, Washington, DC. U. S. Environmental Protection Agency. 1980c. Ambient Wat 1: a1 t Criteria for Zinc. EPA 440/5-80-079, U.S. EPA, Office of Water, Criteria and Standards Division, Washington, DC. U.S. Environmental Protection Agency. 19841 Guidelines establishing test procedures for the analysis of pollutants under the Clean Water Act; Final rule and interim final rule and proposed rule. Federal Register 40 CFR. U. 8. Environmental Protection Agency. 1985a. Eethodegfor Measuring the Acute Toxicity of _ffluents to Freshwater and Magine Organisms. IEPA/600/4-85/013, U.S. EPA, ORD, EMSL, Cincinnati, OH. 125 U. S. Environmental Protection Agency. 1985b. Ambient Water a t Qpitepia for Ammonia- 1985. EPA 440/5-85-001, Office of Water, Criteria and Standards Division, Washington, DC. U.S. Environmental Protection Agency. 1986. Tests Methods for Evaluatipg Solid Waste. Vol. 1B: Laboratory ManualI PhysicalZChemica; Methods. U.S. Environmental Protection, Office of Solid Waste and Emergency Response, Washington, D.C. U.S. Environmental Protection Agency. 1991. Methods for Aggapic ngicity Identification Evaluatione: Phase I Toxicity Characterization Procedures. Second Edition. EPA-600/60-91/003. Environmental Research Laboratory-Duluth, MN. Wentsel, R., McIntosh, A. and Atchison, G. 1977. Sublethal effects of heavy metals contaminated sediment of midge larvae (Chironomus tentans). Hydrobiologia 56:153-156. Wentsel, R., McIntosh, A., and McCafferty, W.P. 1978. Emergence of the midge Chironomus tentans when exposed to heavy metal contaminated sediment. Hydrobiologia 57:195-196. Williams, L.G., Chapman, P.M. and Ginn, T.C. 1986. A comparative evaluation of marine sediment toxicity using bacterial luminescence, oyster embryo and amphipod sediment bioassays. Mar. Environ. Res. 19:225-249. Winner, R.W. 1988. Evaluation of the relative sensitivities of four day Daphnia. magga and Ceriodaphnia: ggpia_ toxicity tests for cadmium and sodium pentachlorophenate. Environ. Toxicol. Chem. 7:153-160. 126 Winner, R.W. 1989. Multigeneration life-span tests of the nutritional adequacy of several diets and culture waters for Ceriodaphnia dubia. Environ. Toxicol. Chem. 8(6):513-520. CHAPTER 3 Bicarbonate as a Potential Confounding Factor in Cladoceran Toxicity Assessments of Pore Water from Contaminated Sediments 127 Introduction Toxicity assessment of contaminated sediments has become de rigueur in planning for remedial actions at International Joint Commission (IJC) Great Lakes "Areas of Concern" (AOC) (Hileman 1988) and at many U.S. EPA Superfund sites (Warren-Hicks et a1. 1989). Sediments contaminated by a wide array of metals and organic chemicals are an acknowledged legacy of the explosive post-World War II growth in the chemical industry and the continued reliance on fossil fuels for energy production. Approaches traditionally used to evaluate contaminated sediments include: 1) chemical analyses for total sediment concentrations of compounds or elements of concern, 2) toxicity tests of bulk sediments or aqueous extracts of sediments using benthic and upper water column test species, respectively, and 3) field surveys of in-situ effects such as changes in benthic macroinvertebrate community structure or the occurrence of histopathological lesions in benthic fish species (for reviews see Giesy and Hoke 1989, Chapman et al. 1987). In the present study, we focus on the potential implications of, and one of the problems involved in, the use of pore water (interstitial water) toxicity tests with cladocerans as surrogates for bulk sediment tests with benthic invertebrates. Pore water from contaminated sediment is used as an exposure medium for toxicity tests (Giesy and Hoke 1989). Comparisons have been made of the results of tests which evaluated the toxicity to Hyalella azteca and 128 129 Lumbriculus variegatus of bulk sediment, pore water and elutriate from the same samples (Ankley et al. 1991). These comparisons and the results of other studies (Nebeker et a1. 1984, van de Guchte and Maas-Diepeveen 1988, Knezovich and Harrison 1988) suggest that pore water exposures with benthic species are good surrogates for bulk sediment exposures. The underlying assumption in the use of pore water exposures as a surrogate for bulk sediment exposures is that organisms receive most of their exposure to toxic substances in sediments through contact with the pore water (Nebeker et al. 1984, Ankley et al. 1991). The relationship between pore water and bulk sediment exposures has not been clearly established (Cairns et al. 1984, Nebeker et a1. 1984) and many physico— chemical processes can be expected to affect the partitioning of metals and xenobiotics from the solid phase into the pore water (Sinex et al. 1980, Knezovich et al. 1987, U.S. EPA 1989, Di Toro et al. 1990). Additional assumptions inherent in the use of pore water as a test medium are that basic chemical properties of pore water, such as major ion concentrations and/or ratios, are within the physiologically tolerated ranges of the test species and that the pore water extraction technique does not cause artifacts in the pore water chemistry. Recent reviews of the advantages and disadvantages associated with various methods of pore water preparation can be found in Adams (1991) and Schults et al. (1992). During an assessment of the toxicity of sediments at the Grand Calumet River-Indiana.Harbor Canal (GCR-IHC) IJC4AOC, several observations caused concern over the effects of chemical properties of the pore waters on the results of toxicity tests with cladocerans. Elevated pore water alkalinity values (Table 13), gas bubble formation, white crystalline residue on the inside of test chambers and increases in pore water pH in 130 m.m H.o m.m oemm Ommm oo.w onus m.h H.o e.> own 0mm om.m e10: ~.m «.0 N.m owe omen on.h MIOD N.H o.o N.H 00H mmv om.m NIOD H.ma m.o N.ma ovw 05mm oo.w HIOD AA\mOHOEEV AA\mOHOEEV Aq\wmev AmOOmO .NEo\m0261v mm cowumooa -moom immune Noo 323912 33.5 sflfiuosocoo mmmcoumm mmsHm> pmumHsono mmsam> pmmmmmwr .m2mmmm cmuOOOpmHo wnu Eouw AOova musumummsmu paw .wuwcwamxam .mm pwusnmme co pmmmn umum3 whom ca macsumuucmosoo nmoom pcm NOO menu pmumHsuHmo mm Ham3 mm .coaumooH comm uOm ucmEummuu musnomxm swam: muom wooa was Eouw pmuuommu mum huwcwamxam ocm mmmcpumc .>u«>auospcoo .mm omusnmoe ESEHXMZ .mwmmm 4M can mmmma.4m cua3 mummnm mason nlmv cw pmumwu 00m ooH Hmcmo uonwnm mcmwchlum>wm umfisamo venue on» Bonn mumumz whom uCOEwpmm mo nmnxamsm HmOHEmco mcwusou mo nuasmmm .MH manna 131 m.HN m.H ¢.NN och OOHN 00.5 NHIOD m.NH m.o «.ma ovo OMNN vh.h Hale: m.m 5.0 m.m comm owes mo.h OHIO: m.om 5.0 m.0m ovoH Omen om.» one: m.m~ m.H 0.0m omam come mo.n mIOD 0.0H 0.0 o.oH oven omvH 00.5 plus AA\mmHOEEV Aq\meOEEV Aq\vmev Amoomo ANEO\mOnEIV mm cofiumooq nmoom immune ~00 .333me 33:: >33 uosocoo mmmcpwmm mmsHm> pmumHsono mmswm> omusmmmz .Apmscaucoov .mH manna 132 test vessels during cladoceran toxicity tests led to the hypothesis that the test results might be affected by the altered character of the carbonate-bicarbonate buffer system in the pore waters. At the time the investigation was begun, no information existed in the literature concerning the toxicity of bicarbonate ion to cladocerans although some information was available on the toxicity of C02 (Mount and Anderson- Carnahan 1988). It also was known that C02 could be used to anesthetize zooplankton prior to preservation (Gannon and Gannon 1975). Limited information also was available on the toxicity of bicarbonate ion to fish (Beatty 1959, Mitchum 1960). This investigation was conducted to examine the toxicity of the bicarbonate ion to D. magna and C. dubia. The specific objectives of the study were: 1) to determine the effects of bicarbonate ion concentrations on D. magna and C. dubia using NaHCO3 and NaCl as reference toxicants, 2) to compare calculated concentrations of HCO3' in sediment pore*waters from the AOC study area to concentrations shown to cause adverse effects on Q; magpa and C. dubia in laboratory exposures, and, if HCO3'-induced toxicity was observed, 3) to propose potential mechanisms for the observed HCO3'- induced effects. X—ray dispersivexnicroanalysis previously has been used to study the role of various invertebrate tissues in metal storage and the effects of different environmental levels of metals on metal localization in invertebrates (Krantzberg and Stokes 1990, Ballan-Dufrancaisiet al. 1985). Investigations also have been conducted.on diffusible ions in invertebrate osmoregulatory systems (Marshall and Wright 1973, Roomans 1988a), and in bulk specimens of skeletal muscle (Zierold and Schafer 1978). Because of its previous use in the examination of physiological levels of diffusible 133 ions, X-ray dispersive microanalysis was chosen as the simplest and most «direct method for monitoring the potential effects of bicarbonate ion on ‘the relative concentrations of several physiologically important elements in D. magna. Materials and Methods Toxicity of Na+ and HCO3‘ Forty-eight hour, acute tests (U.S. EPA 1985) were conducted with Baker'reagent-grade NaHCO3 and NaCl to establish the toxicity of HCO3' and Na+ to D. magna and C. dubia. These exposures were initiated with <24 h old.neonates from laboratory cultures of each species and also with six or seven-day old, sub-adult D. magna. Six or seven-day old D. magga were initially necessary to provide specimens of sufficient size for manipulation in the preparation procedures for the x-ray microanalysis and were specifically selected for further x-ray microanalysis because of their larger size. Test organisms were not fed and the temperature and photoperiod were maintained at 25°C and 16L:8D, respectively, during all tests. New NaHCO3 and NaCl stock solutions were prepared for each test (3000 mg/L and 8000 mg/L nominal concentrations, respectively). A 0.56X dilution series was used to prepare dilutions of the stock solutions for testing. A minimum of five toxicant concentrations and a control were prepared for each test. Five replicates, each containing five organisms, wwere tested for each toxicant concentration or control. The laboratory 0 mineral culture/diluent water was prepared by mixing bottled Perrier water and HPLC-grade laboratory water (1:9 v/v) followed by vigorous aeration for 24 h to ensure equilibration of gases prior to culture or 134 test use (U.S. EPA 1989). Two pg/L each of cyanocobalamin (Vitamin 812) and selenium, as sodium selenate, also were added to the culture/diluent water (Lanno 1989). Control survival in toxicity tests was always greater than 90%. Forty-eight hour LCSO values were calculated using the binomial test and are reported as nominal HCO3' or Na+ concentrations in mmoles/L (Table 14). Calculation of Free 002 and HCO3_ A series of twenty-six, 48-h acute pore water tests were performed xwith D. magna and C. dubia as part of the original AOC sediment toxicity .assessment (Hoke et. al 1992). Data from these exposures subsequently \were used to calculate theoretical equilibrium concentrations of free 002 {and HCO3' in the pore waters for comparison with effects concentrations :from the literature or the reference toxicant tests described above. Free <302 and HCO3' concentrations at equilibrium were calculated using ‘temperature (25°C), pH and alkalinity values measured in the 100% pore ‘water exposure treatment from the cladoceran tests (Table 13). Alkalinity ‘was measured using a Hach kit (accuracy = t 0.4 meq/L) and pH was measured tasing an Orion Model 701A ionanalyzer equipped with. a glass Ross CHDmbination pH probe. The following equations (Harvey 1957) were used to calculate free 002 and HCO3' concentrations, respectively. H2 (1) KIN-I + 2K2) «B; where p = X ll aarxci 2H (2) H+2K2 135 where: H = [H‘] a = [HC03'] + 2 [CO,’] = Measured alkalinity x = [HZC'O3] , includingfree CO2 y = [HC03‘] [HCO3'] [H‘] R; = [H2C03] CO'Z 0 K2 = [ 3 H.111 [HC'03] X-ray Dispersive Microanalysis To investigate the effects of HCO3' on the internal ion balance (Na, Si, Cl, Ca) of D. magna, several 48-h tests in which NaHCO3 was used as a toxicant were initiated with 6 or 7-d old, sub-adult D. magna. Three experiments were conducted with NaHCO3. Additional experiments were conducted with pore water collected from one of the original AOC sediment samples (Location UG-9) due to its high alkalinity and calculated HCO3' Concentration, and with NaSCN, a metabolic inhibitor of Cl' uptake (Epstein et a1. 1973). Live D. magna were removed from the tests for Subsequent X-ray analysis after 16-20 h exposure to NaHCO3 or Location UG- 9 pore water. Organisms were removed for analysis after 2 h of exposure to NaSCN. Forty—eight hour exposures to the highest concentrations of either NaHCO3 or pore water were lethal to D. magna. Organisms to be analyzed by X-ray microanalysis were exposed for a shorter period of time because the variable of interest was change in elemental peak to lba-Cflmround (P/B) ratios in living organisms as a result of exposure to Ncho3, pore water or NaSCN. l A 136 Table 14. Toxicity to D. magna and C. dubia of Na+ as NaCl or NaHCO3 and of HCO3' as NaHCO3. Mean 1 SD 48 h LCSO LC50 Species Age Compound (mmoles/L) (mmoles/L) D. magna <24 h NaCl 85.7 81.3 t 6.2 D. magna1 <24 h NaCl 76.9 D. magna2 4th instar/ NaCl 57.9 -- adult C. dubia <24 h NaCl 14.3 13.5 t 1.2 C. dubia <24 h NaCl 12.6 D. magna <24 h NaHCO3 16.6 15.1 1 2.2 D. magna <24 h NaHCO3 13.5 D. magna 6 d NaHCO3 21.2 -- D. magna 7 d NaHCO3 26.3 20.6 i 8.1 D. magna 7 d NaHCO3 14.9 C. dubia <24 h NaHCO3 13.8 12.8 i 1.5 C. dubia <24 h NaHCO3 11.7 Mount and Anderson-Carnahan 1988. 2 Dowden 1961. 137 Whole D. magna (generally 5 per treatment) were removed from the tests and mounted on carbon planchets. A 1:1 (v/v) mixture of Tissue Tek and graphite was used to mount the daphnids on the carbon planchets and to attach the carbon planchets to electron microscopy stubs. The Tissue Tek- graphite mixture did not interfere with subsequent X-ray analysis of D. magna (R. Hoke, unpublished data). For preliminary experiments with post-NaHCO3 exposure organisms, traditional cryogenic preparation and fracturing techniques (EM Scope 2000) were used with etching at -20°C for 15 min if ice crystals were present in the sample (Boekestein et al. 1980, Marshall 1988). Because these fracturing techniques were cumbersome and frequently displaced organisms from the planchets, in subsequent experiments organisms were mounted on planchets and then plunged into liquid nitrogen for 15 sec. The carapace of each D. magna was then gently sliced away with a razor blade to reveal the internal body structure and facilitate penetration of the X-ray beam. X-ray microanalyses were performed with a JEOL JSM-3SC scanning electron microscope equipped with a cryostage and a Tracor Northern Series II X-ray microanalysis system with software. Each measurement was acquired at an accelerating voltage of 20.0 Kev for a preset scanning time of 60 s. Results are reported as P/B ratios (Boekestein et al. 1980, Marshall 1988, Roomans 1988b). Elemental measurements were conducted at five randomly chosen locations within the head and upper body area for each of five D. nmgna from control and either, low and high, or low, medium and high experimental treatments. .Absolute peak height or emission intensity data were not used due to the lack of analytical standards in an appropriate matrix. The same analytical constraints were operative among 138 all measurements conducted as part of each experiment; therefore, P/B ratios and changes in these ratios as a result of experimental treatments, relative to controls, were the data of interest in all experiments. Data Analysis X-ray dispersive microanalysis results were analyzed with a nested, fixed effects ANOVA design (Petersen 1985) using the Statistical Analysis System (SAS 1985) software. For the ANOVA, the x-ray microanalysis measurements were nested within experimental units (i.e. individual Daphnia magna). In the variance component analysis, three separate aspects of experimental variance were examined: 1) treatment variance, 2) organism (among daphnid within treatment) variance and measurement (among measurement within daphnid) variance. Results Toxicity of Na+ and Hco3' Forty-eight hour LC50 values for D. magna and C. dubia tests with NaHCO3 and NaCl are presented in Table 14. Based on mean LC50 values, Qeriodaphnia dubia neonates (< 24-h old) were approximately six times more sensitive to Na+ as NaCl than D. magna neonates of similar age. However, 24-h old C. dubia neonates were only slightly more sensitive (~ 1.2 X) than D. magna neonates to Na+ as NaHCO3. Little difference was observed in the toxicity of the two compounds to <24-h old C. dubia neonates. Daphnia magna neonates were approximately 5.4 x more sensitive to Na+ as NaHCO3 than as NaCl. Based on literature values for adults (Dowden 1961), 139 D. magna neonates were approximately 1.4 X less sensitive than adults to NaCl while adults were approximately 1.4 X less sensitive to NaHCO3 (Table 14). Calculation of Free C02 and HCO3' The results of theoretical equilibrium concentration calculations for C02 and HCO3' in the AOC sediment pore water samples are presented in Table 13. Calculated concentrations of C02 ranged from 0.0-1.5 mmoles/L while calculated HCO3' concentrations ranged from 1.2-29.9 mmoles/L. X-ray Dispersive Microanalysis Mean P/B ratios (1 SD) for Na+, Si+4, Cl", and Ca+2 in daphnids analyzed from each experiment are presented in Table 15. Within an experiment and within the individual treatments comprising an experiment, +2 relative levels of Ca were the most variable parameter measured based on standard deviation of the means while Si+4 was the least variable. The variability of relative levels of Na’r and Cl' among experiments was similar but Cl‘ levels were generally more variable within an experiment. The results of variance component analyses from the ANOVA’s of the x-ray microanalysis data are presented in Table 16. The proportion of the total variance accounted for by among treatment effects is presented as well as the variance accounted for by among organism (among daphnid) effects within an experimental treatment and the among measurement (measurements within an individual daphnid) variance. Variation in the Cl" P/B ratio among treatments was statistically significant in each experiment. P/B 140 100.00 mm.” .h0.0. .00.0 Amfi.0v 00.0 .0~.00 50.0 umoom a\zs m.mm .efl.a0 00.0 10~.00 ~>.0 100.00 H~.0 10H.0. e¢.0 nmoom q\:s m.HH .mm.a. 00.0 Ama.00 H0.0 ima.0. m~.0 .0H.0. mm.0 -moom a\zs 0.0 m.m incommz u m .oz Ame.00 00.0 .00.00 .nm.0 10H.00 m~.0 .mH.00 H0.0 umoom s\xs 0.0m 100.00 00.0 AHH.00 .mm.0 .00.00 00.0 ims.0. .mm.0 -moom a\zs m.HH 100.00 m0.0 .-.00 50.0 100.00 m~.0 100.0. 0m.0 souucoo H.m amoommz u H .oz N+mo IHO v+wm +m2 ucmEumme ucmEummuH umm mowcnmmo moflumm m\m cmmz .Oz .pwcnmma umm mucmemwsmmmz .02 uucmowxoel.oz ucmeuwmxm .ucmEummuu HmucmEmemxm umm3OH so Howucoo On» umnuflm Eowm mocmwmmmap pcmoamwcmem m cmuMOflpce £0H£3 ummulu acowumwcom 2n pm3OHaom 30.0 n 3 ucmemam HmsBZofi was .30 «>92 “00033030 0 :0 ommmn mums menus.” m? Hmucmemam mdhm . sow E . sum sues meanness: museums acmeummuu unmouwcmflm ucmEummuu Hmucmefiummxm some now MOE 0km 0 0 . . mowumu m\m Ann» C U uh QOH mOSHm> _mcmme. Q cuw3 mucmswummxm mwanmcmouo E xmulx_uo muasmmm .mH manna 141 100.0. no.0 .5H.00 «00.0 .HH.00 0H.0 .HH.0. m~.0 zommz u\sa 0000 .mm.0. 0m.0 15H.00 .00.0 Ap0.00 0H.0 AHH.0V m~.0 zommz s\sa ooma Amm.00 vm.0 imfl.00 .mm.0 .ma.00 0H.0 AmH.0. 0H.0 zommz u\s: 00m 100.0. 00.0 ANN.0. 05.0 .0H.00 HH.0 ANH.0. 00.0 Houucoo 0.0 “zommz I m .02 10N.H0 00.N AHH.00 .mm.0 20H.00 5H.0 Ama.00 0~.0 umumz muom woos .mfi.mv 00.~ Amm.00 «mm.0 .00.00 .n0.0 10H.00 0m.0 umumz muom wmm m.m rumpus muom .00.H0 «0.0 imm.00 00.0 10H.00 0H.0 100.0v m~.0 Houucoo 0:00 I 0 .oz Amm.H0 .m0.~ Am¢.00 .0».0 100.00 0H.0 Ame.00 0m.0 -moom a\zs m.HH 200.0e 00.0 10H.00 >~.0 100.00 NH.0 AHH.00 0H.0 umoom q\zs 0.0 200.0v 00.0 20H.00 mm.0 AHH.0V ms.0 iefl.0v 00.0 Houucoo m.m “moommz u m .02 N+mo IHO v+am +m2 ucmEummue ucmEummue emu moaccmmo modumm m\m cmmz .02 .pwccmma Mme mucmEmusnmmx .02 “unmoexosg.0z bemefiummxm / .aomsseucoot .me seams 142 experiment 1 due to inadequate replication. * denotes a significant ANOVA F value at a = Variance component analysis was not possible on the 0.05. Table 16. Variance component analyses of results from analysis of variance of X-ray microanalysis data. % Total Variance2 Experiment No.1, Toxicant Source df Na+ Si+4 Cl’ a+2 No. 2, Total 29 100.0 100.0 100.0 100.0 NaHCO3 Treatment 2 9.8 0.1 86.9* 7.3 Organism 3 0.0 0.0 0.6 10.1 Measurement 24 90.2 99.9 12.5 82.6 No. 3 Total 74 100.0 100.0 100.0 100.0 NaHCO3 Treatment 2 18.7* 0.0 40.5* 21.5* Organism 12 19.3* 19.5* 24.6* 11.6 Measurement 60 62.0 80.5 34.9 66.9 No. 4 Total 74 100.0 100.0 100.0 100.0 UG-9 Pore Treatment 2 1.1 19.3* 24.8* 0.0 Water Organism 12 5.4 0.0 18.3* 40.2* Measurement 60 93.5 80.7 56.9 59.8 No. 5 Total 99 100.0 100.0 100.0 100.0 NaSCN Treatment 3 13.8 0.0 53.2* 5.2 Organism 16 17.5* 44.9* 8.3* 0.0 Measurement 80 68.7 55.1 38.5 94.8 1 results of 143 ratios for Na+ and Ca++ also were significantly different among treatments in the No. 3- NaHCO3 experiment, as was the Si+4 P/B ratio in the Location UG-9 pore water experiment. Variation among organisms treated alike also was significantly different for Na+, Si+4 and C1' in the No.3- NaHCO3 and NaSCN experiments and for C1" and Ca++ in the Location UG-9 pore water experiment" Treatment effects accounted for 1.1-18.7, 0.0-19.3, 24.8-86.9 and 0.0-21.5 % of the total experimental variation in P/B ratios for Na+, ++, respectively. With the exception of experiment No. 4 Si+4, Cl' and Ca with the UG-9 pore water, treatments effects accounted for the majority of the observed variation in each experiment. Among daphnid variation in P/B ratios within a given experimental treatment always was the smallest component of the observed experimental variation. Variance due to differences in measured P/B ratios within an individual daphnid generally accounted for 12-57% of the total observed experimental variation in P/B ratios. Discussion Sediment pore water has been hypothesized to be the primary route of exposure to sediment contaminants for benthic macroinvertebrates (Nebeker et al. 1984, Knezovich and Harrison 1988). Pore water also has been demonstrated to be a reasonable surrogate test fraction for the assessment 550 mg/L) and alkalinity (>600 mg/L as CaCO3) were hypothesized to be responsible for the lack of fish and benthic macroinvertebrates of the orders TrichOptera, Lepidoptera, Megaloptera and 148 Anisoptera. Limited collections of benthic macroinvertebrates in the orders Chironomidae and Ephemeroptera were attributed to the same phenomenon (Blinn and Sanderson 1989). Planktonic rotifers and cladocerans also were absent from this ecosystem (Dehdashti and Blinn 1991). Additional field studies in the Intermountain Region of the U.S. Forest Service concluded that the number of macroinvertebrate taxa in 164 samples from 20 different streams was inversely correlated (r = -0.67, p = 0.001) with ambient stream alkalinity as CaCO3 (Winget and Mangum 1979). Similarly, McCarraher and Thomas (1968) observed that in alkaline lakes of Nebraska, fathead minnows (Pimephales promelas) flourished when carbonate alkalinity was below 800 ppm and total alkalinity was below 1,800 ppm. However, carbonate or total alkalinity in excess of these values was reported to greatly impair reproduction and abundance of this species. The proposed existence in D. magna of an actively-regulated exchange process for HCO3' and Cl' and the hypothesis that disruption of this process is the mode of action for bicarbonate toxicity have several practical implications. Bicarbonate concentrations should be routinely measured during toxicity tests of aqueous samples, such as pore waters or effluents. If’ bicarbonate concentrations are sufficient. to jproduce toxicity, this observation should be considered when interpreting the test results. The importance of bicarbonate toxicity also needs to be addressed in toxicity identification evaluation (TIE) procedures (Mount and Anderson-Carnahan 1988, 1989, Mount 1989), both for effluents and sediment pore waters, because current TIE methodology would not identify high bicarbonate concentrations as the specific cause of observed toxicity. Instead, the observed toxicity could be wrongly ascribed to the effects of total dissolved solids (TDS). This would implicate cations or 149 cation ratios in the sample as the cause of observed effects when, in fact, the effects were due to the anion HCO3'. Finally, since active regulatory processes for HCO3'-Cl‘ also exist in freshwater fish and amphibians, and may exist for other aquatic invertebrates, TIE procedures performed with these species also may be affected by high bicarbonate concentrations in the test solution. Acknowledgements Jane Thompson, Jane Norlander and Debra Williams typed various drafts of the manuscript. Mary Schubauer-Berigan, Teresa Norberg-King, Gary’ Ankley, Howard. McCormick, Don. Mount and an anonymous reviewer provided helpful comments on earlier versions of the manuscript. 150 Literature Cited Adams, D.D. 1991. Sediment pore water sampling. Chapter 7 in Q_Q flangbook of TechniqueLfor Aquatic SedirLent Sam lin , A. Mudroch and S.D. MacKnight, eds. CRC Press, Boca Raton, FL. 210 p. Ankley, G.T., M.K. Schubauer-Berigan and J.R. Dierkes. 1991. Predicting the toxicity of bulk sediments to aquatic organisms with aqueous test fractions: pore water versus elutriate. Environ. Toxicol. Chem. 10:1359-1366. Ballan-Dufrancais, C., A. Jeantet, C. Feghali and S. Halpern. 1985. Physiological features of heavy metal storage in bivalve digestive cells and amoebocytes. Electron probe microanalysis and factor analysis of correspondence. Biol. Cell 53:283-292. Beatty, D.D. 1959. An experimental study of the toxicity of sodium bicarbonate, sodium chloride and sodium sulphate to rainbow trout. Master's Thesis, University of Wyoming, Laramie, WY. Blinn, D.W. and M.W. Sanderson. 1989. Aquatic insects in Montezuma Well, Arizona, USA: a travertine spring mound with high alkalinity and dissolved carbon dioxide. Great Basin Naturalist 49(1):85-88. Boekestein A., A.L.H. Stols and A.M. Stadhouders. 1980. Quantitation in X-ray microanalysis of biological bulk specimens. Scanning Elect. Microsc. II, Sem Inc., AMF O'Hare, Chicago, IL. pp 321-333. 151 152 Cairns, M.A., A.V. Nebeker, J.H. Gakstatter, and W. Griffis. 1984. Toxicity of copper-spiked sediments to freshwater invertebrates. Environ. Toxicol. Chem. 3:435-446. Chapman, P.M., R.N. Dexter, and E.R. Long. 1987. Synoptic measures of sediment contamination, toxicity and infaunal community composition (the sediment quality triad) in San Francisco Bay; Mar. Ecol. Prog. Ser. 37:75-96. Cowgill, U.M. and D.P. Milazzo. 1991. The sensitivity of two cladocerans to water quality variables: alkalinity. Arch. Environ. Contam. Toxicol. 21:224-232. Dehdashti, B. and D.W. Blinn. 1991. Population dynamics and production of the pelagic amphipod Eyalella,montezuma in a thermally constant system. Freshwater Biol. 25:131-141. de Renzis, G. and J. Maetz. 1973. Studies on the mechanism of chloride absorption by the goldfish gill: relation with acid-base regulation. J. Exp. Biol. 59:339-358. de Renzis, G. and M. Bornancin. 1977. A Cl/HCO3-ATPase in the gills of Carassius auratus: its inhibition by thiocyanate. Bioch. Biophys. Acta. 467:192-207. Di Toro, D.M., J.D. Mahony, D.J. Hansen, K.J. Scott, M.E. Hicks, S.M. Mayr and M.S. Redmond. 1990. Toxicity of cadmium in sediments: the role of acid volatile sulphide. Environ. Toxicol. Chem. 9:1487- 1502. Dowden, B.F. 1961. Cumulative toxicities of some inorganic salts to Daphnia magna as determined by median tolerance limits. Proc. La. 153 Epstein, F.H., J. Maetz and G. de Renzis. 1973. Active transport of chloride by the teleost gill: inhibition by thiocyanate. Amer. J. Physiol. 224(6):1295-1299. Gannon, J.E. and S.A. Gannon. 1975. Observations on the narcotization of crustacean zooplankton. Crustaceana. 28(2):220-224. Garcia-Romeu, F. and J. Maetz. 1964. The mechanism of sodium and chloride uptake by the gills of a freshwater fish gapaggiga_ag;agg§. I. Evidence for an independent uptake of sodium and chloride ions. J. Gen. Physiol. 47:1195-1207. Garcia-Romeu, F., A. Saliban and S. Pezzani-Hernandez. 1969. The nature of the in vivo sodium and chloride uptake mechanisms through the epithelium of the (Halean frog Calyptocephalella gay; (Dum. and Bibr. 1841): Exchanges of hydrogen against sodium and of bicarbonate against chloride. J. Gen. Physiol. 53:816-835. Giesy, J.P. and R.A. Hoke. 1989. Freshwater sediment toxicity bioassessment: rationale for species selection and test design. J. Great Lakes Res. 15(4):539-569. Gulley, D.D., H.L. Bergman, J.R. Hockett, and D.R. Mount. 1991. A statistical model to predict toxicity of saline discharges to freshwater organisms. Poster Session, 12th Annual Meeting, Society of Environmental Toxicology and Chemistry; Seattle, WA. Harvey, H.W. 1957. Chemistry and Fertility of Sea Waters, 2nd Ed. Cambridge Univ. Press. New York, NY. Hileman, B. 1988. The Great Lakes cleanup effort. Chem. Eng. News 66(6): 22-39. Hoke, R.A., J.P. Giesy and M. Zabik. 1992. Acute toxicity of sediments and sediment pore waters from the Grand Calumet River - “iii-var ’ _I 1“; “fifi. Fae Kai Kr 154 Indiana Harbor, Indiana International Joint.Commission.Area.of Concern. Ecotox. Environ. Safety (Submitted). Knezovich, J.P. and F.L. Harrison. 1988. The bioavailability of sediment-sorbed Chlorobenzenes to larvae of the midge, gpiggpgmga decorus. Ecotoxicol. Environ. Safety 15:226-241. Knezovich, J.P., F.L. Harrison and R.G. Wilhelm. 1987. The bioavailability of sediment-sorbed organic chemicals: A review. Water, Air, Soil Pollut. 32:233-245. Krantzberg, G. and P.M. Stokes. 1990. Metal concentrations and tissue distribution in larvae of Chironomus with reference to x-ray microprobe analysis. Arch. Environ. Contam. Toxicol. 19:84-93. Lanno, R.P. 1989. Nutritional Considerations in Toxicity leaping. Short Course, 10th.Annual Meeting, Society of Environmental Toxicology and Chemistry, Toronto, Ontario, Canada. Maetz, J. and F. Garcia-Romeu. 1964. The mechanism of sodium and chloride uptake: by the gills of a freshwater fish, Caraesipa auratus. II. Evidence for NH4+/Na+ and HCO3'/C1' exchanges. J. Gen. Physiol. 47: 1209-1227. Marshall, A.T. 1988. Progress in quantitative X-ray microanalysis of frozen-hydrated bulk biological samples. J. Elect. Microsc. Tech. 9:57-64. Marshall, A.T. and A. Wright. 1973. Detection of diffusible ions in insect osmoregulatory systems by electron probe X-ray microanalysis using scanning electron microscopy and a cryoscopic technique. Micron 4:31-45. 155 McCarraher, D.B. and R. Thomas. 1968. Some ecological observations on the fathead minnow, Pimephales promelas, in the alkaline waters of Nebraska. Trans. Am. Fish. Soc. 97:52-55 Mount, D.I. 1989. Methods for Aquatic Toxicity Identification Evaluations. Phase III Tbxicity Confirmation Procedures. EPA/600/3-88/036. Environmental Research Laboratory-Duluth, MN. Mount, D.I. and L. Anderson-Carnahan. 1988. Methods for Aquatic Toxicity Identification Evaluations: Phase I Toxicity Characterization Procedures. EPA/600/3-88/034. Environmental Research Laboratory-Duluth, MN. Mount, D.I. and L. Anderson-Carnahan. 1989. Methods for Aquatic Toxicology Identification Evaluations. Phase II Toxicity Identification Procedures. EPA/600/3-88/035. Environmental Research Laboratory-Duluth, MN. Nebeker A.V., M.A. Cairns, J.H. Gakstatter, K.W. Malueg, G.S. Schuytema and D.F. Krawczyk. 1984. Biological methods for determining toxicity of contaminated freshwater sediments to invertebrates. Environ. Toxicol. Chem. 3:617-630. Payan, P. 1978. A study of the Na+/NH4+ exchange across the gill of the perfused head of the trout (Salmo gairdneri). J. comp. Physiol. 124:181-188. Petersen, R.G. 1985. Design and Analysis of Experiments. Marcel Dekker, Inc., New York, NY. 429 p. Potts, W.T.w. and G. Fryer. 1979. The effects of pH and salt content on sodium balance in Daphnia _magfl and Acantholeberis curvirostgis (Crustacea:Cladocera). J. comp. Physiol. 129:289-294. 156 Roomans, G.M. 1988a. Introduction to X-ray microanalysis in biology. J. Elect. Microsc. Tech. 9:3-17. Roomans, G.M. 1988b. Quantitative x-ray microanalysis of biological specimens. J. Elect. Microsc. Tech. 9:19-43. SAS. 1985. SAS/STAT User's Guide. Version 6.03 Edition. SAS Institute, Cary, NC. 1028 p. Schults, D.W., L.M. Smith, S.P. Ferraro, F.A. Roberts and C.K. Poindexter. 1992. A comparison of methods for measuring trace organic compounds and metals in interstitial water. Water Res. (In Press) Sinex, S.A., A.Y. Cantillo, and G.R. Helz. 1980. Accuracy of acid extraction methods of trace metals in sediments. Anal. Chem. 52:2341-2346. Stobbart, R.H., J. Keating and R. Earl. 1977. A study of sodium uptake by the water flea Daphnia magna. Comp. Biochem. Physiol. 58A:299- 309. U.S. Environmental Protection Agency. 1985. Methods for Measuring the Acute Toxicity of Effluents to Freshwater and Marine Organisms. EPA/600/4-85/013. U.S. EPA, ORD, EMSL, Cincinnati, OH. 216 p. U.S. Environmental Protection Agency. 1989. Short-term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Freshwater Organisms. EPA/600/4-89/001, U.S. EPA, ORD, EMSL, Cincinnati, OH. 248 p. van de Guchte, C. and J.L. Maas-Diepeveen. 1988. Screening sediments for toxicity: A water-concentration related problem. 14th Annual Aquatic Toxicity Workshop. November 1-4, 1987. Toronto, Ontario, Canada. 157 Warren-Hicks, W., B.R. Parkhurst and 5.5. Baker, Jr., Eds. 1989. Ecological Assessment of Hazardous Waste Sites: A Field and Laboratory Reference. EPA/600/3-89/013, U.S. Environmental Protection Agency, ERL-Corvallis, OR. Winget, R.N. and R.A. Mangum. 1979. Biotic condition index: integrated biological, physical and chemical stream parameters for management. U.S. Government Printing Office, Report No. 1980-0-677-133/F, Department of Agriculture, U.S. Forest Service, Intermountain Region. 51 p. Zierold, K. and D. Schafer. 1978. Quantitative X-ray microanalysis of diffusible ions in the skeletal muscle bulk specimen. J. Microsc. 112:89-93. CHAPTER 4 Mutagenicity and 2,3,7,8-Tetrachlorodibenzo-p-dioxin Equivalents in Organic Solvent Extracts of Sediments from the Grand Calumet River, Indiana 158 3‘ Introduction The importance of sediments as both a sink and source for chemicals of environmental concern has become obvious during the preceding 20 years. As a result, an increasing amount of research effort has been devoted to investigations of the fate and effects of chemicals in sediments. Most research on the effects of chemicals in sediments has focused on the potential acute toxicity of in-place pollutants to benthic species. A lesser amount of research effort has been devoted to the potential for chronic toxicity or bioaccumulation of sediment-associated chemicals and the potential mutagenicity of bulk sediments or various extracts of sediments. The driving force behind research on the mutagenic effects of pure chemicals or complex environmental mixtures in the past has been the potential for human health effects. Although humans have little direct exposure to sediments or extracts of sediments, we are potentially exposed to these complex Inixtures indirectly via, aquatic food chains (i.e. ingestion of aquatic species exposed to contaminated sediments). Therefore, any chemical in sediments which is mutagenic and can be bioaccumulated could potentially cause both ecological and human health effects. Research also has been completed or is on-going which suggests that, for certain chemicals, concentrations of mutagenic chemicals in the environment which may be protective of human health may produce mutagenic effects in aquatic biota and organisms which consume aquatic biota. 159 160 Chemical analysis can only provide a limited idea of the potential effects (i.e. toxicity, mutagenicity, etc.) of exposure to a complex mixture such as a bulk sediment or extract of a sediment, due to the potential for interactive effects (antagonism, synergism); the potential for effects at concentrations of chemicals which are below the detection limits for the analytical method; and the incompleteness of the chemical analysis (i.e. it is not possible to analyze for all chemical compounds potentially present in a sample). Therefore, the best. measure of potential biological effects is a direct measure of some form of biological activity after exposure to the complex mixture (Durant et al. 1992, Tillett et al. 1991). Evaluations of the mutagenicity of extracts of soils or bulk sediments have been conducted with the Ames assay (Donnelly et al. 1991, Maccubbin et al. 1991, Ersing 1987, Maccubbin 1986, West et al. 1986 a,b, 1988, Durant et al. 1992, Fabacher et al. 1988, Sabo et al. 1983 and Maccubbin and Ersing 1991), a human lymphoblast assay (Durant et al. 1992) and the MutatoxO assay (Kwan et al. 1990, Dutka et al. 1991). The study by Durant et al. (1992) compared mutagenicity of organic extracts of sediments in both the Ames and human lymphoblast assays. To date, no comparison of mutagenicity in complex environmental samples such as organic extracts of sediments has been made between the Ames and Mutatoxo assays although Johnson (1992) investigated the relative mutagenicity of pure chemicals in the two assays. The Ealmonella typhimurium mutagenicity assay, more commonly known as the Ames assay (Ames et al. 1975, Maron and Ames 1983) is a rapid method of screening for potential mutagenicity, and thus carcinogenicity, of chemicals and complex mixtures. The Ames assay is based upon the use 161 of selected mutant strains of the bacterium S. typhimugium and the particular vulnerability of these strains to mutations at the histidine locus. These bacteria carry a mutation for histidine dependency and are reverted back to histidine prototropy by the mutagenic chemical. The inclusion of liver microsomes containing biochemically induced enzymes is required for activation of certain chemicals to their reactive forms. Bacterial strains TA-98 (sensitive to frame-shift mutations) and TA-100 (sensitive to base-pair substitution) have separate: mutations which increase the assay sensitivity to a greater range of chemical agents when a sample is tested with both bacterial strains (Maron and Ames 1983). The Mutatox® assay employs a dark mutant of the luminescent marine bacterium, Photobacterium phosphoreum which undergoes a forward mutation after exposure to a variety of mutagenic compounds. The MutatoxO assay is based on a similar assay developed by Ulitzur (1986) and is capable of detecting base substitutions (point mutations), base additions or deletions (frameshift mutations), intercalations of DNA, or the inhibition of DNA synthesis. Over 100 compounds representing a dozen chemical classes, including volatile chemicals and complex mixtures, have been tested using the dark mutant strain of E. phosphoreum (Ulitzur 1986). A number of these compounds also have been tested and categorized by the National Toxicology Program (Tennant et al. 1987). For these chemicals, correlative data from long-term animal studies and four short-term assays (Ames assay, Chinese hamster ovary chromosome aberrations and sister chromatid exchange, mouse lymphocyte assay) exist for comparative purposes. As in the Ames assay, it also is possible to conduct the Mutatox‘ID procedure with and without metabolic activation to compare mutagenic activity of parent compounds and potential metabolic products. EL. .._ 4' ; A- - s 21.—_— a u 162 Although analytical techniques exist for the detection of minute quantities of polychlorinated hydrocarbons (PCH), these procedures can be extremely costly and time-consuming, particularly when samples may theoretically contain up to 209 different polychlorinated biphenyl (PCB) congeners and 75 different polychlorinated dibenzodioxin (PCDD) or dibenzofuran (PCDF) isomers and congeners (Safe 1987). Thermost toxic PCB and PCDD congeners are those which are planar, or nearly planar (Greenlee and Neal 1985). The toxic properties of different planar PCH compounds appear to be expressed via a common mode of action, and therefore, it is possible to calculate the biological potencies of complex mixtures of PCHs by expressing their toxicity relative to the most toxic PCH known, 2,3,7,8-TCDD (Bradlaw and Casterline 1979, Eadon et al. 1986, Safe 1987). TCDD-equivalents can be assigned to complex mixtures of PCBs by measuring the ability of the PCH mixture to induce cytochrome p-450-dependent ethoxyresorufin-o-deethylase (EROD) activity in H4IIE rat hepatoma cell cultures and expressing the magnitude of the response relative to induction observed with TCDD (Bradlaw and Casterline 1979, Casterline et al. 1983, Safe 1987). The H4IIE rat hepatoma cell assay is also useful because it serves as both a qualitative check and a supplement to the results of the Ames assay. Several investigators have reported a suppression of mutagenic potential in the Ames assay between PAHs and other components of crude oil (Hermann et al. 1981, Hermann 1980, Petrilli et al. 1981, Carver et al. 1985, Haugen and Peak 1983). The cause of the suppression of mutagenic potential was demonstrated to be inhibition of the hepatic microsomal monooxygenase (MO) system (Carver et al. 1985). Therefore induction of 163 EROD activity would preclude suppression of mutagenic potential due to M0 inhibition in samples also tested in the Ames assay. The objectives of this study were: 1) to compare the mutagenicity of organic solvent extracts of bulk sediments with the Ames and Mutatoxo assays, 2) to evaluate the mutagenicity of aqueous extracts of sediments in the MutatoxO assay, 3) to evaluate EROD induction in the H4IIE assay after exposure to organic solvent extracts of bulk sediments and 4) to compare assay results to a limited set of organic chemical analyses of bulk sediment. Materials and Methods Sample Collection Sediment samples were collected from the Grand Calumet River, IN on 11 October and 22 November 1988; 10 March, 24 May, 30 October and 13 November 1989; and 12 May 1990. A Ponar grab sampler was used to collect sediment samples from 10 locations along the Grand Calumet River and three locations in the Indiana Harbor ship canal (Figure 10). At the time of sample collection, study sites were located by triangulation of local landmarks. The sample from each location was a composite of approximately 80-100 L of wet sediment from multiple Ponar grabs. Multiple grab samples were collected and composited to ensure sufficient sample volume for all necessary sub-sample collection. Compositing and homogenization of composite samples were done in a large stainless steel pan with stainless 164 scsHUcH .wonuem someocm use u0>am uoEsHso venue 0:» ca ncoeuuooH mcaamEmm 3... scene. od o; 0.0 32¢ 08528 056 PO: «0: 003 a: . . 0 Nr . . . 0». 0p. 00, 0. . 2883 882.8 205.80 .4 .52 sex . _ / 522.. mass miquoz, «.05.: .oH shaman 165 steel tools. Large debris was removed from the composite samples and two, 1-L aliquants (sub-samples) for quantification of metals and organic compounds in bulk sediments were placed in clean l-L glass jars capped with solvent rinsed aluminum foil under the lid. Samples for toxicity testing or pore water extraction were placed in coolers or plastic buckets lined with food-grade plastic bags. After collection, sediment samples were placed on ice in coolers and transported to the laboratory, where they were maintained in a walk-in cooler at 4° C until processing and analysis. Pore Water Extraction Pore water was extracted from sediments by a combination of centrifugation and filtration as described by Hoke et al (1992a). The pore water extracts were placed in clean, solvent-rinsed glass bottles, the bottles capped with aluminum foil-lined lids, and the pore water maintained in the dark at 4° C until used for assays (< seven days). Ames Assay The Ames test was conducted according to the methods and procedures described by Maron and Ames (1983). The complete sample extraction and Ames test methods used in this study have previously been described by Maccubbin and Ersing (1991), however, a brief summary is presented below. A subsample of each sediment sample was air-dried at 80° C to determine moisture content. A wet sediment sub-sample was homogenized and a 30-50 9 sample mixed with anhydrous sodium sulphate to absorb the water from the sample. The sample was then placed in a cellulose extraction thimble and extracted for two successive 24 h periods with 300 mL isopropyl alcohol 166 and dichloromethane, respectively; The extracts were combined, the volume reduced to 50 mL and residue content determined by drying three, one mL aliquants of the combined extracts in tared aluminum weigh boats. An appropriate amount of extractant was then solvent-exchanged into dimethyl sulfoxide (DMSO) to give a final organic residue content of 10 mg/ml (Maccubbin and Ersing 1991). Sediment extracts were diluted to provide a dose series of 1000 pg, 600 pg, 200 pg, 100 pg and 60 pg residue per plate for testing. One hundred pl of organic extract from each sediment were mixed with 100 pl of an overnight culture of bacteria (tester strain TA98 or TA100) and 2 ml of melted agar containing 5 mM histidine and biotin (Ames et al. 1975, Maron and Ames 1983). Molten top agar was then poured onto a minimal glucose agar base plate and the plates incubated at 37° C for 2 days. The existence of compounds requiring metabolic activation was evaluated by adding 0.5 ml of buffer solution containing rat liver homogenate (89 from Aroclor treated rats, Litton Bionetics, Charleston, SC.) and co-factors to the top agar prior to plating. Spontaneous mutation rates, solvent,and S9 effects were evaluated with plates containing bacteria only, DMSO only, and DMSO + $9 only as negative controls. Tester strain sensitivity was monitored with benzo(a)pyrene, sodium azide and daunomycin as positive controls. Each extract and control treatment was tested in triplicate. The number of His + revertant colonies/pg residue were determined after incubation and converted to His+ revertants/mg dry weight sediment based on the residue content of each sediment. Toxic effects were evaluated by decreases in mutagenicity with increases in dosage and loss of the background "lawn" of cell growth that occurred due to the small amount of histidine present in the culture media. Dose response data were evaluated 167 over the linear portion of the dose response curve according to the two- fold rule (Chu et al. 1987). Sediment was classified for mutagenic potential based on dose dependent increases in the reversion rate. Mutatox® Assay The Mutatox® assay was conducted on aliquots of the organic sediment extracts tested in the Ames and H4IIE tests. The dry MutatoxO medium was reconstituted with distilled water and the pH adjusted to 6.8 with 5 N KOH. Direct test medium was prepared by adding one mL of the reconstituted dark mutant P. phosphoreum to 100 mL of reconstituted medium. TWenty-six cuvettes (10 sample plus 3 control X 2 replicates each) were set-up, labelled from 1-13 (A and B) and one mL of test medium added to each number one tube. One-half (0.5) mL of test medium was added to each tube numbered 2-13. A 0.2 mL aliquot of the organic sediment extract was added to the number 1 tubes, the solution mixed and serially diluted by transferring 0.5 mL of mixed solution from cuvette 1 through cuvette 10 for each set of replicates. The samples were then placed on a rotary shaker set at 70 i 10 rpm and incubated at 23 t 2° C for 16 h. Light output of the dark mutant (i.e. mutagenesis) was measured at 16, 18 and 20 h for both the direct and S9-activated mutagenesis tests. The measurements of light emission used the same methods as those described for the Microtox® test (Bulich 1981). A positive mutagenic response was classified as a light peak of 100 or more at three times the reagent control light output. A non-reactive chemical also was expected to exhibit a negative response in both direct and S9-activated tests. 168 H4IIE Assay The H4IIE rat hepatoma cells were obtained from the American Type Culture Collection (ATCC No. CRL 1548). The cell culture medium used was a supplemented Dulbecco's Modified Eagle's Medium (D-MEM) (Tillett et al. 1991). Phenol red was not used in the medium because it may adversely affect liver cell cultures and may potentiate induction in the H4IIE cells. H4IIE cells were kept in continuous culture in the laboratory and the cultures regularly restarted from frozen cells to insure the cultures were not altered. Standard sterile tissue culture techniques were used to maintain the integrity of the cell line and prevent contamination of the cells. Cell culturing and harvesting were performed according to the procedures described in Tillitt et al. (1991). The cells were dosed with aliquots of the same organic extracts of the sediment samples used in the Ames and Mutatox® assays. DMSO was used as the carrier solvent with the same quantity (mass) of extract delivered to separate plates in different volumes (<100 pl) of DMSO. There was no effect on the basal EROD activity of the H4IIE cells of DMSO volumes between 10 and 100 pL/plate. Triplicate plates were tested at each of 4-5 doses of the sediment extracts along with a concurrent TCDD standard curve (4 doses in triplicate). Bioassay to bioassay variations in experimental technique were taken into account with a standard TCDD curve analyzed with the sediment extracts. The calculation of TCDD-equivalents does not reflect these among-experiment variations (Tillitt et al. 1991). Plates were incubated for 72 hours and the cells rinsed with PBS and scraped from the plates while in a Tris-sucrose (0.05 - 0.2 M) buffer. The collected cells were centrifuged for 10 minutes, resuspended in the Tris-sucrose buffer, 169 and duplicate analyses performed of protein content (Lowry et al. 1951) and enzyme induction. The indirect EROD assay was chosen to monitor induction of cytochrome P-4501A1 monooxygenase activity (Pohl and Fouts 1980). The EROD assay has good sensitivity, is specific for the induction of P-4501A, and correlates well to aryl hydrocarbon hydroxylase (AHH) activity in this cell line (Bandiena et al. 1984). EROD assays were conducted in polycarbonate tubes in. a shaking' water* bath incubator maintained at 37° C. The assay protocol followed that described by Tillitt et al. (1991). Fluorescence of samples was determined on a SLM 4800 spectrofluorometer at emission and excitation wavelengths of 585 and 550 nm, respectively. The machine was calibrated with a standard rhodamine B solution and fluorescence in samples read relative to this internal standard. Each reading was an average of 20 automatic scans. A resorufin standard was also run on each experiment for calibration to a resorufin standard curve and calculation of specific enzyme activities. EROD activity was calculated and reported as pdcomoles resorufin/mg protein/minute for each treatment combination. Chemical Analysis A suite of 106 organic chemical compounds and metals were analyzed for in sediments from the Grand Calumet River and Indiana Harbor, IN. The complete analytical methods and results for all analytes have previously been reported by Hoke et al. (1992). 170 Statistical Analysis All data analyses were performed with SAS statistical software (SAS 1985). Relative potencies of the samples were estimated with the slope- ratio assay (Finney 1978). The relative potency was derived from the slope on the linear portion of the dose-response curve for the sample in comparison to the slope of the TCDD standard curve. Sample potency was calculated as: Sample Slope/TCDD Slope (l) with final units of pg TCDD/uL of extract. TCDD-equivalents (E9) on a pg/gm dry wt sediment basis were estimated based on the known mass of residue extract on a dry wt sediment basis. TCDD-EQ attributable to measured total PCBs (as Aroclor 1248) and TCDD in each sediment sample were calculated and compared to EROD TCDD-EQ. For calculation purposes, one pg of total PCBs (as Aroclor 1248) was assumed to be equivalent to 10 pg TCDD-EQ (Tillitt et a1. 1991). Pearson product moment correlation analysis (SAS 1985) was used to compare the results of both the Ames and Mutatox® mutagenicity assays with the results of chemical analyses of bulk sediments. Results Mutatox® Assay Mutagenicity in the Mutatox test without 59 activation only occurred in the organic extract of sediment from site UG-l and was equivocal in the extract from site UG-3 (Table 17). Organic extracts of sediments from all a. 171 sites were umtagenic when tested with S9 activation (Table 17). The extracts from sites UG-3 and UG-7 were the most and least mutagenic with S9 activation, respectively. In general, organic extracts of sediments from the western branch of the Grand Calumet River were less mutagenic when tested with S9 activation than were extracts from the eastern branch. No mutagenicity was observed in any sample when aqueous extracts (pore O assay with waters) from study site sediments were tested in the Mutatox and without S9 activation. The relationship of the results of the MutatoxQ assays of organic solvent extracts of sediments also was evaluated in the relationship to the results of the organic chemistry of the sediments which have previously been presented elsewhere (Hoke et al. 1992). No significant correlations were observed between the results of the Mutatox® assay and the organic chemical analyses of the sediments. Ames Assay Organic extracts of sediments from sites UG-3 and 8 were mutagenic when analyzed. without 59 activation using tester strain. TA98 while extracts from sites UG-3 and 5 were mutagenic without S9 activation when analyzed with tester strain TA100 (Table 17). Organic extracts of sediments from all sites were mutagenic when analyzed with S9 activation using both tester strains TA98 and TA100 (Table 17). With metabolic activation, the number of strain TA98 revertants per mg dry wt sediment ranged from 1 at site UG—4 to 102 at site UG-3 while the number of TA100 revertants ranged from 10 per mg dry wt sediment at site UG-4 to 1710 at site UG-3 (Table 17). A number of statistically significant correlations (p S 0.05) were observed between the Ames assay results and the organic chemical analyses 0.0 :2 «an 22 00 22 0.0 N.H0 0H:00 00.H :2 002 :2 0 :2 0.Ha 0.00 0:00 00.0 22 000 :2 00 m n.0a 0.00 0:00 00.0 :2 00 :2 0 22 0.p 0.00 0:00 00.0 :2 he 22 00 :2 0.0 0.00 0:00 00.0 :2 0es 00 00 :2 ~.HH 0.00 0:00 00.0 :2 00 :2 H :2 0.0 0.00 0:00 00.0 mm 0HOH mm 00H 0 0.0 0.Hm 0:00 W 00.0 :2 00 :2 0 22 H.m 0.00 0:00 0H.0 0.0 000 22 0a 022 0.» 0.00 Hu00 00+ 00: 00+ 00: 00+ 00: 203 0000 H00000002 0 .02 00000000 02010000 oosme 0000 Hmsnmuomuuxmw exoumusx Nmucmuwm>mm .02 I mmE4 .mhmmmm cuon ca coflum>euom Oaaonmume mm usocuHB 0cm :uw3 pmumwu mum3 muomsuxm .2H .wonsmz mcmHocH 0cm s0>wm umEsHMO pcmwo 0:0.80um musmEapmm mo muomuuxw ucm>H00 owcmouo no 020000 xoumusz_ocm mead «O muHsnOm .hd manna 173 .COHHflHUCGUCOU 0HQMUO0UQU Hm03OH fl UQA m .ecoo 902 0 .009000 00000 um Odsmmmuse #02 m .mucmuum>mu nsomcmucomm uOu omuomwsoo msoflmmu manmuomsuxm ml\mucmuum>mw .02 :0 0.0003 ucmepmn #3 >00 mE\mucmuwm>mu «O .02 N .mCOHUMCHEumumo mumoeamwwu no one: H oz oz m 22 02 DZ 02 Dz MHIOD oz 02 so 22 m 22 oz 02 NHIUD oz oz m 22 22 22 02 oz . HHIUD mm+ 0m: 00+ mm: mm+ mm: 293 >000 amusemeoz w .02 cowumooq 033000 0020. 0000. 00330000500 exoumusz Nmucmuwm>mm .02 I 0064 .Apmscwusoo. .hfl manna 174 of the sediment (Table 18). No significant correlations were observed between the results of the Ames assays and concentrations of metals in bulk sediment (data not shown). H4IIE Assay Based on EROD induction, the greatest number of TCDD-EQ (pg/gm dry wt sediment) were observed for extracts of sediments from sites UG-l, 3 and 8 (Table 19). TCDD-EQ for other sites were generally an order of magnitude less. Concentrations of TCDD-EQ in bulk sediments from the study sites ranged from approximately 4,700 to greater than 500,000 pg/gm dry wt sediment. The proportion of the total TCDD-EQ from the H4IIE assay attributable to measured concentrations of total PCBs (as Aroclor 1248) and TCDD in bulk sediments from the study sites was small (i.e. <0.5%). Pearson product moment correlation analysis of TCDD-EQ and results of chemical analyses of the bulk sediments indicated significant correlations existed between TCDD-EQ and bulk sediment concentrations of 2,4-and 2,6- dichlorophenols (r == 0.70, 0.66); 2,4,6-trichlorophenol (r as 0.66); acrylonitrile (r == 0.66); p-dichlorobenzene (r == 0.66); 1,3- dichloropropene; ethylbenzene (r = 0.76) and fluoranthene (r = 0.69). Discussion Although investigations of the mutagenicity of sediments from the Great Lakes have been limited, several authors have reported that organic solvent extracts of sediments from various locations were mutagenic when tested in the Ames assay (Maccubbin 1986, Maccubbin and Ersing 1991, ‘0 '0 Table 18. 175 Pearson product moment correlation coefficients from analyses of Ames assays with S9 activation and organic chemical analyses of sediment from the Grand Calumet River, IN. Correlations reported were statistically significant at p S 0.05. Parameter Tester Strain TA98 + TA100+ Hydroquinone -- 0.83 Mercaptobenzothiazole 0.64 0.79 3,4-Dichloroaniline 0.86 0.91 Heptachlor 0.62 0.82 p-Dichlorobenzene 0.68 -- 1,2—Dichloropropane -- 0.74 2,4-Dinitrotoluene 0.63 0.68 176 nmom 00000 03 use ml\OMIooOB on 00 newssmnd H 0.000.00 0.0 0.00 00.0 0.000.00 00:00 N.mom.0N 0.0 0.00 00.0 0.0No.HN mloo 0.000.000 0.0 0.00 00.0 0.000.000 0:00 m.mme.mm o.o 0.Nv 0N.v 0.000.0m 0:0: 0.000.00 0.0 0.00 00.0 0.000.00 0:00 0.000.00 0.00 0.000 00.00 0.000.00 0:00 0.000.0 0.0 0.0 00.0 0.000.0 0:00 0.000.000 0.0 0.00 00.0 0.000.000 0:00 0.000.00 0.0 0.00 00.0 0.000.00 0:00 0.000.000 0.0 0.00 00.0 0.000.000 0:00 “So Em\omv A30 Eo\mmv A30 Em\mmv AEm\OIV A30 Em\mmv .02 sceumooq 00:0ooe 000 0009 H0000 0000 00:0oos pmucsouomco H0009 mm sOHOOw¢ mm comm 00:0000 0000 00000 .20 .uonumm monaocH 0cm uw>dm umesamo compo ecu Eowm mucmEHpmm £032 :0 once pom AquH HOHOOw< mmv mmom H0000 mo macaumuucmocoo 00000008 co pmmmn omloooe 00 cOmawmmEoo ca 00000 mHva 0:0 Eoum Ominous .ma manna 177 Maccubbin et al. 1991, West et al. 1986a,b, 1988, Fabacher et al. 1988). Several authors also have reported that solvent extracts of sediments were mutagenic in the Mutaton assay (Kwan et al. 1990, Dutka et al. 1991) but, to date, little or no comparative data exist for results of Ames and MutatoxO assays performed on solvent extracts of the same sediments. The data from this study indicate that both the Ames and MutatoxO assays yield similar results when organic solvent extracts of sediments are tested with S9 microsomal metabolic activation. Correlation of the number of TA98 or TA100 revertants with the Mutatox® results in samples tested with S9 activation was weak (r = -O.35 to -O.40). Little concordance was observed in the determination of mutagenicity for solvent extracts of sediments tested without 89 activation in both assays although the extract from site UG-3 was mutagenic in all direct assays. Ames assays using tester strains TA98 and TA100 without activation indicated extracts from sites UG—3 and 8, and UG-3 and 5 were mutagenic, respectively. MutatoxQ assays without activation indicated the extract from site UG-l was mutagenic while the results for the extract from site UG-3 was equivocal. Differences in observed results among assays and tester strains during assays without metabolic activation are most likely due to the individual strain or assay sensitivity to different chemicals and the type of genetic mutation caused by the chemical. Ames assay tester strain TA98 detects mutagens which cause frameshift mutations while tester strain TA100 detects those causing point mutations (Maron and Ames 1983). The Mutatox® assay detects compounds which cause frameshift or point.mutations as well as compounds which inhibit DNA synthesis and DNA-intercalating agents (Johnson 1992). 178 Previous investigations have reported the detection of direct acting mutagens in complex mixtures by the MutatoxQ assay (Kwan et al. 1990). In the only direct comparison of the Ames and Mutatoxo assays conducted to date, Johnson (1992) tested the sensitivity of the two assays with metabolic activation to eight progenotoxins. Both assays exhibited similar sensitivities to the eight compounds with lowest detected concentrations in the low microgram range for both assays. However, pyrene was not detected by the Ames assay but caused a strong positive response in the Mutatox® assay (Johnson 1992). Interestingly, no statistical correlations were observed between the results of the Mutatox® assay' with activation and. organic chemical analyses of sediments from the study sites. However, a number of statistically significant correlations were observed between the organic chemical analyses and the results of Ames assays with tester strains TA98 and/or TA100. Chemicals for which concentrations in bulk sediments were significantly correlated with Ames assay results with tester strain TA98 included mercaptobenzothiazole; 3,4-dichloroaniline, heptachlor, p- dichlorobenzene and 2,4-dinitrotoluene. Ames assay results with tester strain TA100 were significantly correlated to chemical concentrations in bulk sediments of hydroquinone; mercaptobenzothiazole; 3,4- dichloroaniline; heptachlor; 1,2-dichloropropane and 2,4-dinitrotoluene. In pure compound assays, mercaptobenzothiazole, hydroquinone; 2,4- dichlorophenol and heptachlor have been reported as non-mutagenic in Ames assay while 1,2-dichloropropane and 2,4-dinitrotoluene have been reported to be mutagenic in the assay (Ashby and Tennant 1991, Tennant and Ashby 1991). 179 Extracts of sediments from the Detroit River (Maccubbin.et al. 1991), the Buffalo River (Ersing 1987) and the Black River (Fabacher et al. 1988, West et al. 1986a,b, 1988) within the Great Lakes basin have previously been reported to elicit mutagenicity in the Ames assay. PAHs have been the most frequently implicated compounds in the observed mutagenicity. West et al. (1986a,b) identified polycyclic aromatic hydrocarbons (PAH), nitrogen heterocycles of PAHs (PANH) and alkylated forms of both PAH and PANHs as the primary causes of the observed mutagenicity. Maccubbin et al. (1991) also indirectly implicated PAHs as the potential cause of mutagenicity observed in organic solvent extracts of sediment from the Detroit River tested with the Ames assay. When these investigators fractionated the solvent extracts of the samples and then tested the individual fractions of the original extract, they observed a higher total number of revertants for the fractions than for the original extract. This phenomenon suggests that mutagenicity was inhibited or suppressed, possibly due to the presence of other PAHs (Hermann et al. 1981, Hermann 1980, Haugen and Peak 1983, Petrilli et al. 1981, Carver et al. 1985). The mechanism for this suppression or inhibition was demonstrated to be related to inhibition of the hepatic microsomal MO system in the s9 (Carver et al. 1985). Additional S9 was recommended for Ames assays of complex mixtures containing petroleum hydrocarbons to ensure adequate metabolic activation of PAHs (Carver et a1. 1985). The Ames assay protocol used to test solvent extracts of sediments from the Grand Calumet River and Indiana Harbor, IN included the addition of a large volume of S9 mixture to each extract (Maron and Ames 1983). Therefore, suppression of mutagenicity due to PAI-Is should have been minimal. Hoke et a1. (1992) reported that individual PAH concentrations a . i '- 180 in the bulk sediments were as great as 100 mg/kg. This may account for the large number of revertants observed for the samples. Solvent extracts of other sediments from the Great Lakes have been reported to cause 80-12,000 revertants/gm dry wt of sediment (Ersing 1987, Maccubbin et al 1991) while extracts of Grand Calumet River sediments tested with metabolic activation caused from 1000-1,710,000 revertants/gm dry wt sediment. Direct acting mutagens in Grand Calumet River sediments caused 2000-45,000 revertants/gm dry wt sediments. The importance of PAHs in the Grand Calumet River and Indiana Harbor, IN. can also be observed in the results of the H4IIE assays. Significant amounts of TCDD-EQ'were detected in solvent extracts of sediments from the study area. Measured concentrations of other compounds which can cause EROD induction in environmental samples (e.g., PCDDs, PCDFs, PCBs) did not account for the observed TCDD—EQ from the H4IIE assay (i.e. <0.5%). It must be noted, however, that total PCBs as Aroclor 1248 and TCDD were the only representatives of the PCDDs, PCDFs and PCBs measured in bulk sediments from the Grand Calumet River. .A stronger, albeit circumstantial, case can be made that PAHs in bulk sediments from the study area were responsible for the observed TCDD-EQ. PAHs are known to cause EROD induction in the H4IIE assay (Whitlock et al. 1974, Xu and Bresnick 1990, Corcos and Weiss 1988) and large concentrations of several PAHs have been measured in sediments from the study area (Hoke et al. 1992). It is also likely that large concentrations of both unmeasured parent PAHs and their degradation products exist in sediments from the study area. PAHs also are likely responsible for a portion of the mutagenicity observed in the Ames and Mutatoxo assay even though no 181 statistically significant correlations were observed between assay results and PAH concentrations in bulk sediments. As evidenced in the results of the Ames and MutatoxO assays, numerous mutagenic compounds exist in sediments from the Grand Calumet River and Indiana Harbor, IN. Black et al (1985) demonstrated that neoplasia in fish could be induced by repeated applications of solvent extracts of sediments from the Buffalo River, NY which contained numerous mutagens including PAHs. However a long latency period was necessary to demonstrate evidence of carcinoma. Thus a need arose for short-term tests of genotoxicity such as the Ames and Mutaton tests. Although these assays can provide an indication of the potential mutagenicity of complex environmental mixtures, more research needs to .be conducted. on ‘the representativeness of the exposure route used in these assays (solvent extracts). The absence of mutagenicity in Mutatox® assays of pore waters from the study site sediments indicates that short—term direct human exposure to mutagens in pore waters and sediments are likely to be non- problematic. Greater concern is required for the potential for both ecological and human health effects due to bioaccumulation (bioconcentration and biomagnification) of mutagenic compounds present in sediments from the Grand Calumet River and Indiana Harbor, IN. Acknowledgements Mutatox® assays were conducted by Dr. Jim Tung of Microbics, Inc., Carlsbad, California and Ames assays were conducted by Dr. Lex Maccubbin of the Grace Cancer Research Institute, Buffalo, New York. G. Ankley and several anonymous reviewers provided comments which improved earlier versions of the manuscript. 182 Literature Cited Ames, B.N., McCann, J. and Yamasaki, E. 1975. Methods for detecting carcinogens and nmtagens with the Salmonella/mammalian microsome mutagenicity test. Muta. Res. 31 347-364. Ashby, J. and R.W. Tennant. 1991. Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP. Muta. Res. 257:229-306. Bandiera, S., T. Sawyer, M. Romkes, B. Zmudka, L. Safe, G. Mason, B. Keys and S. Safe. 1984. Imnychlorinated dibenzofurans (PCDFs): effects of structure on binding to the 2,3,7,8-TCDD cytosolic receptor protein, AHH induction and toxicity. Toxicology 32: 131-144. Bannister, R. and 8. Safe. 1987. Synergistic interactions of 2 , 3, 7, 8-TCDD and 2, 2 ’ , 4, 4 ' , 5, S ' , -hexachlorobiphenyl in C57BL/GJ and DBA/ZJ mice: role of the Ah receptor. Toxicology 44:159-169. Bartsch H., Malaville, C., Camw, A.M., Martel-Planche, G., Brun, G., HauteFenille, A.,Sabadie, N., Barbin, A., Kuroki, T., Drevon, C., Piccoli, C., and Montesano, R. 1980. Validation and comparative studies in 180 chemicals with S. typhimurium strains and V79 Chinese hamster cells in the presence of various metabolizing systems. Muta. Res. 76:1-50. 183 .‘F— 184 Black, J., H. Fox, P. Black and F. Bock. 1985. Carcinogenic effects of river sediment extracts 5J1 fish and ndce. jpp. 415-427, in Water Chlorination, Vol. 5, R.L. Jolley, R.J. Bull, W.P. Davis, S. Katz, M.E. Roberts, Jr. and V.A. Jacobs. Lewis Publishers, Chelsea, MI. Bradlaw, J.A. and J.L. Casterline. 1979. Induction of enzyme activity in cell culture: rapid screen for detection of planar polychlorinated organic compounds. J. Assoc. Off. Anal. Chem. 62:904—916. Carver, J.H., M.L. Machado and J.A. MacGregor. 1985. Petroleum distillates suppress in vitro’metabolic activation: Ihigher (S- 9) required in the Salmonella/microsome mutagenicity assay. Environ. Muta. 7:369-379. Casterline, J.L., J.A. Bradlaw, B.J. Puma and Y. Ku. 1983. Screening of freshwater fish extracts for enzyme-inducing substances by an aryl hydrocarbon hydroxylase induction bioassay technique. J. Assoc. Off. Anal. Chem. 66:1136-1139. Chu, R.C. R.M. Patel, A.H. Lin, J.M. Petrone, M.S. Linhart and V.C. Dunkel. 1981. Evaluating statistical analyses and reproducibility of microbial mutagenicity assays. Muta. Res. 85:119-132. Corcos, L. and M.C. Weiss. 1988. Phenobarbital, dexamethasone and benzanthracene induce several cytochrome P450 MRNAs in rat hepatoma cells. FEBS Letters. 233(1):37-40. Donnelly, K.C., K.W. Brown, C.S. Anderson and J.C. Thomas. 1991. Bacterial mutagenicity and acute toxicity of solvent and 185 aqueous extracts of soil samples from an abandoned chemical manufacturing site. Environ. Toxicol. Chem. 10:1123-1131. Durant, J.L., B.F. Hemond and W.G. Thilly. 1992. Determination of mutagenicity in sediments from the Aberjona watershed using human lymphoblast and Salmonella typhimurium mutation assays. Environ. Sci. Tech. 26:599-608. Dutka, B.J., K.K. Kwan, S.S. Rao, A. Jurkovic and D. Liu. 1991. River evaluation using ecotoxicological and microbiological procedures. Environ. Monitor. Assess. 16:287-313. Eadon, G., L. Kaminsky, J. Silkworth, K. Aldous, D. Hilker, P. O'Keefe, R. Smith, J. Gierthy, J. Hawley, N. Kim and A. DeCaprio. 1986. Calculation of 2,3,7,8-TCDD equivalent concentrations of complex environmental contaminant mixtures. Environ. Health Perspect. 70: 221-227. Ersing, N. 1987. Mutagenic and Carcinogenic Potential of Chemically- Contaminated Sediments from the Buffalo River. M.S. Thesis, University of Buffalo, Buffalo, NY. 48 p. Fabacher, D.L., C.J. Schmitt, J.M. Besser and M.J. Mac. 1988. Chemical characterization and mutagenic properties of polycyclic aromatic compounds in sediment from tributaries of the Great Lakes. Environ. Toxicol. Chem. 7:529-543. Finney, D.J. 1978. §_§tistical Method in Biological Agggy. Third Ed. Charles Griffin and Company, LTD. London. Greenlee, W.P. and R.A. Neal. 1985. The Ah receptor: a biochemical and biologic perspective. pp. 89-129, in The Receptors Vol. II. 186 Haugen, D.A. and M.J. Peak. 1983. Mixtures of polycyclic aromatic compounds inhibit mutagenesis in the Salmonella/microsome assay by inhibition of metabolic activity. Mutation Res. 116:257- 269. Hermann, M. 1981. Synergistic effects of individual polycyclic aromatic hydrocarbons on the mutagenicity of their mixtures. Muta. Res. 90:399-409. Hermann, M., Chaude, 0., Weill, N., Bedouelle, H. and Hofnung, M. 1980. Adaptation of the Salmonella/mammalian microsome test to the determination of the mutagenic properties of mineral oils. Muta. Res. 77:327-339. Hoke, R.L., J.P. Giesy, M.J. Zabik and M. Unger. 1992. Toxicity of sediments and sediment pore waters from the Grand Calumet River-Indiana Harbor, Indiana Area of Concern. Ecotoxicol. Environ. Safety. (submitted). Johnson, B.T. 1992. An evaluation of a genotoxicity assay with liver S9 for activation and luminescent bacteria for detection. Environ. Toxicol. Chem. 11:473-480. Keys, 8., J. Piskorska-Pliszczynska and S. Safe. 1986. Polychlorinated dibenzofurans as 2,3,7,8-TCDD antagonists: in*vitro inhibition of monooxygenase induction. Toxicol. Lett. 31:151. Kwan, K.K., B.J. Dutka, S.s. Rao and D. Liu. 1990. Mutatox test: a new test for monitoring environmental genotoxic agents. Environ. Pollut. 65:323-332. 1).-Tar 187 Lowry, O.H., N.J. Rosenbrough, A.L. Farr, and R.J. Randall. 1951. Protein measurement with Folin phenol reagent. J. Biol. Chem. 193:265. Maccubbin, A.E. 1986. Mutagenicity of sediments from the Great Lakes ecosystem. Abstract, in Proceedings of the 29th Conference of the International Association of Great Lakes Research, Scarbourgh, Ontario, Canada. Maccubbin, A.E. and N. Ersing. 1991. Mutagenic potential of sediments from the Grand Calumet River. Bull. Environ. Toxicol. Chem. Maccubbin, A.E., N. Ersing and M.E. Frank. 1991. Mutagenicity of sediments from the Detroit River. .1. Great Lakes Res. 17(3):314-321. Maron, D.M. and Ames, B.N. 1983. Revised methods for the Salmonella mutagenicity test. Muta. Res. 113:173-215. Mason, G., T. Sawyer, B. Keys, S. Bandiera, M. Romkes, J. Pislorska-Pliszczynska, B. Zmudzka and 8. Safe. 1985. Polychlorinated dibenzofurans (PCDFs): correlation between in vivo and in vitro structure-activity relationships. ‘Toxicology 37:1-12. McCann, J., Choi, E., Yamasaki, E., and Ames, B.N. 1975. Detection of carcinogens» as mutagens in the Salmonella/microsome test: assay of 300 chemicals. PNAS, USA 72:5135-5139. Petrilli, F.L., G.P. de Renzi and S. De Flora. 1980. Interaction between polycyclic aromatic hydrocarbons, crude> oil, and. oil dispersants in the Salmonella mutagenesis assay. Carcinogenesis 1:51-56. 188 Pohl, R.J. and J.R. Fouts. 1980. A rapid method for assaying the metabolism of 7—ethoxyresorufin by microsomal subcellular fractions. Analyt. Biochem. 107:150-158. Poland, A. and J.C. Knutson. 1982. 2,3,7,8-Tetrachlorodibenzo-p—dioxin and related halogenated aromatic hydrocarbons: examination of the mechanism of toxicity. Ann Rev. Pharmacol. Toxicol. 22: 517-554. Rinkus, S.J. and Legator, M.S. 1979. Chemical characterization of 465 known or suspected carcinogens and their correlation with mutagenic activity in the Salmonella typhimurium system. Cancer Res. 39:3289-3310. Safe, S. 1987. Determination of 2,3,7,8—TCDD toxic equivalent factors (TEFs): support for the use of the in vitro AHH induction assay. Chemosphere 16:791-802. SAS. 1985. SAS/STAT Guide for Personal Computers, Version Edition. SAS Institute, Cary, North Carolina. Sato, T., T. Momma, Y. Ose, T. Ishikawa and K. Kato. 1983. Mutagenicity of Nagara River sediment. Muta. Res. 118:257-267. Sawyer, T. and S. Safe. 1982. PCB isomers and congeners: induction of aryl hydrocarbon hydroxylase and ethoxyresorufin O-deethylase enzyme activities in rat hepatoma cells. Toxicol. Lett. 13: 87-94. Sawyer, T.W., A.D. Vatcher and 8. Safe. 1984. Comparative aryl hydrocarbon hydroxylase induction activities of commercial PCBs in Wistar rats and rat hepatoma H-4—II E cells in culture. Chemosphere, 13:695-701. 189 Tennant, R.W., B. H. Margolin, M.D. Shelby, E. Leiger, J.K. Haseman, J. Spalding, W. Caspary, M. Resnick, S. Stasiewicz, B. Anderson and R. Minor. 1987. Prediction of chemical carcinogenicity in rodents from in-vitro genetic toxicity assays. Science 236: 933-941. Tennant, R.W. and J. Ashby. 1991. Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 39 chemicals tested for carcinogenicity by the U.S. National Toxicology Progranu Muta. Res. 257:209-227. Tillitt, D.E., J.P. Giesy and G.T. Ankley. 1991. Characterization of the H4IIE rat hepatoma cell bioassay as a tool for assessing toxic potency' of planar halogenated. hydrocarbons (PHHs) in environmental samples. Environ. Sci. Tech. 25:87-92. Ulitzur, S. 1986. Bioluminescence test for genotoxic agents. pp. 264- 274, in Biolumineacence and Chemoluminescence in Mathodaain Enzvmoloqy, Vol. 133. M. DeLuca and W. McElroy, eds. Academic Press, NY. West, W.R., P.A. Smith, G.M. Booth, S.A. Wise and M.L. Lee. 1986a. Determination of genotoxic polycyclic aromatic hydrocarbons in a sediment from the Black River (Ohio). Arch. Environ. Contam. Toxicol. 15:241-249. West, W.R., P.A. Smith, G.M. Booth and M.A. Lee. 1986b. Determination and genotoxicity of nitrogen heterocycles in a sediment from the Black River. Environ. Toxicol. Chem. 5:511-519. 190 West, W.R., P.A. Smith, G.M. Booth and M.L. Lee. 1988. Isolation and detection of genotoxic components in a Black River sediment. Environ. Sci. Tech. 22:224-228. Whitlock, J.P., Jr., H. Miller and H.V. Gelboin. 1974. Induction of aryl hydrocarbon (benzo-a-pyrene) hydroxylase and tyrosine aminotransferase in hepatoma cells in culture. J. Cell. Biol. 63:136-145. Xu, L.C. and E. Bresnick. 1990. Induction of cytochrome P4SOIA1 in rat hepatoma cell by polycyclic hydrocarbons and a dioxin. Biochem. Pharmacol. 40(6):1399-1403. Zeiger, E. 1987. Carcinogenicity of mutagens: predictive capability of the Salmonella mutagenesis assay for rodent carcinogenicity. Cancer Res. 47: 1287-1296. SUMMARY At the present time, the GCR—IHC system has severely degraded sediments which contain a multitude of chemicals. The most important acute toxicity problems for benthic macroinvertebrates within the system appear to be petroleum hydrocarbons, metals, ammonia and PAHs. Remedial action plans for the area which propose to foster the development of healthy instream communities of invertebrates and fish must of necessity provide a strategy for dealing with both source control and existing concentrations of these contaminants in sediments. 191