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Partitioning and Bioaccumulation of Polychlorinated Biphenyls and Polybrominated Diphenyl Ethers in the Microbial Food Web of Lake Michigan

A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY

Summer Serena Streets

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE In Water Resources Science

Deborah Swackhamer, Advisor

May 2012

Acknowledgments

First and foremost, I would like to thank my advisor, Deborah Swackhamer. You have never failed to motivate and inspire me, and you have shown tremendous patience with me over the past seven years. You have been an incredible mentor and friend. I cannot begin to express how much I appreciate the opportunities you have given me and the doors you have opened for me.

Matt Simcik, thank you for your guidance and your friendship. You were always there to answer questions and offer advice, and your assistance in the field and in the lab was greatly appreciated.

Jim Cotner, thank you for agreeing to be on my committee, even though you don’t really know me. I hope you find this work interesting and useful.

To everyone who I shared time with in the lab and field, I thank you for your guidance and your friendship. Joan Manzara, I literally could not have done this without you. The innumerable hours you spent finessing data, futzing with GCs, and keeping the lab organized were absolutely essential to the completion of this work. Scott Henderson,

Andy Adams, and Matt Hudson: you made the lab a fun place to be, and taught me a lot in the process. Ramona Caswell, I will always be grateful for your camaraderie in the lab and field. It was great to have someone to commiserate with! I could not have gotten through graduate school without you. Tim Chang, your assistance on my final Lake

Guardian voyage was greatly appreciated.

To the entire crew of the R/V Lake Guardian, my sincerest thanks. My time aboard the Guardian was easily one of the most memorable, enjoyable, and formative

i times of my life. I learned so much from each of you. Captain Robert Christensen, I am honored to call you a friend.

To my coworkers at the Minnesota Pollution Control Agency, thank you for your encouragement, support, and patience. A special thank you goes to Pat Engelking, Char

Byrnes- Gronau, and Jim Behm for providing assistance with formatting.

To my friends and family, your support and encouragement helped get me through the good times, as well as the bad. Mom, you raised me to believe that I could do and be whatever I wanted, and for that I will be forever grateful. Grandma Otterson,

Grandma Lil, and Aunt Paula: each of you inspired me and helped shape who I am today.

Grandpa Otterson, you were a true kindred spirit. I wish you could be here to celebrate my accomplishments with me. I miss you every day.

Last but not least, thank you to Vern Johnson, by far my best friend and biggest supporter for the past eighteen years. You have always believed in me, even when I didn’t believe in myself. I would not be where I am today without you.

Dedication

This thesis is dedicated to my beautiful daughter, Saga.

You are the light and love of my life.

iii

TABLE OF CONTENTS

LIST OF TABLES ...... v LIST OF FIGURES ...... vii INTRODUCTION ...... 1 LITERATURE REVIEW ...... 3 HOCs in the Aquatic Environment ...... 3 Significance of the Microbial Food Web in Contaminant Transfer ...... 5 Research Objectives ...... 11 MATERIALS AND METHODS ...... 12 Field Sampling ...... 12 Water Sample Collection ...... 14 Bacterial Fraction Collection ...... 14 Suspended Particulate Matter and Particulate Organic Carbon Collection ...... 15 Sample Extraction and Cleanup ...... 16 Instrumental Analysis ...... 17 Quality Assurance/Quality Control ...... 19 Background Contamination ...... 19 Precision ...... 19 Equation 1. Relative Percent Difference ...... 20 Accuracy ...... 20 RESULTS AND DISCUSSION ...... 22 Water ...... 22 Bacteria and Particulate Composites ...... 26 REFERENCES ...... 33 APPENDIX A:Partitioning and Bioaccumulation of PBDEs and PCBs in Lake Michigan . 39 APPENDIX B: Data and QA/QC ...... 47

LIST OF TABLES

Table 1. Mean (standard deviation) PBDE Congener Concentrations and ∑PCBs in Bacteria, Total Particulates, and Water in Lake Michigan ...... 24

Table 2. Bacteria log BAFOCs and Particulate log KOCs (standard deviation) for individual PBDE Congeners and PCB Individual Congener Means ...... 3 Table A1. Total PCB concentrations in individual water samples ...... 48

Table A2. Total PCB concentrations, log BAFOC, and log KOC in bacteria samples and total particulate artificial composites ...... 48 Table A3. Dissolved phase PBDE concentrations in individual samples (pg/L) ...... 48 Table A4. Particulate phase PBDE concentrations in individual samples (ng/g) ...... 48 Table A5. PBDE concentrations in dissolved phase artificial composites (pg/L) ...... 49 Table A6. PBDE concentrations in particulate phase artificial composites (ng/g) ...... 49 Table A7. PBDE concentrations in bacteria samples (ng/g OC) ...... 49

Table A8. PBDE bacteria log BAFOC ...... 49

Table A9. PBDE total particulate log KOC in artificial composites ...... 49

Table A10. Congener-specific log BAFoc for PCBs in bacteria at Composite 1 ...... 50

Table A11. Congener-specific log KOC for PCBs in particulates at Composite 1 ...... 51

Table A12. Congener-specific log BAFoc for PCBs in bacteria at Composite 2 ...... 52

Table A13. Congener-specific log KOC for PCBs in particulates at Composite 2 ...... 53

Table A14. Congener-specific log BAFoc for PCBs in bacteria at Composite 3 ...... 54

Table A15. Congener-specific log KOC for PCBs in particulates at Composite 3 ...... 55

Table A16. Average congener-specific log BAFOC for PCBs in bacteria in all samples ...... 56

Table A17. Average congener-specific log KOC for PCBs in particulates in all samples ...... 57 Table A18. Suspended particulate matter (SPM) in artificial composites ...... 58 Table A19. Particulate organic carbon (POC) in artificial composites ...... 58 Table A20. Dissolved phase field replicate ∑PCB relative percent difference (RPD) ...... 58 Table A21. Particulate phase field replicate ∑PCB relative percent difference (RPD) ...... 58 Table A22. Dissolved phase field replicate PBDE congener concentration, average, standard deviation, and relative percent difference (RPD) ...... 58 Table A23 Particulate phase field replicate PBDE congener concentration, average, standard deviation, and relative percent difference (RPD) ...... 59 v

Table A24. PCB surrogate recoveries in water, particulates, bacteria, procedural blanks, and field blanks ...... 60 Table A25 PBDE surrogate recoveries in water, particulates, bacteria, procedural blanks and field blanks ...... 61

LIST OF FIGURES

Figure 1. Schematic view of the food web in aquatic systems ...... 7 Figure 2. Lake Michigan sampling sites and sample grouping for both the bacterial fraction composites and dissolved and particulate phase “artificial composites” ...... 13

Figure 3. Individual PCB and PBDE congener log BAFOC / log KOW and log KOC / log KOW plots for bacteria and total particulate artificial composites...... 25

vii

INTRODUCTION

The bioaccumulation of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) in the microbial food web (also referred to as the “microbial loop”) of Lake Michigan is the subject of this thesis. Data describing the concentrations of PCBs and PBDEs in water, particulates, and bacteria will be presented, along with bioaccumulation factors and partition coefficients. Only a few studies have examined the bioaccumulation of PCBs in the microbial loop in marine systems, and there is only one other known study of

PCBs in the microbial loop in a freshwater system. This is the first time that

PBDEs have been measured in the microbial food web of any aquatic system.

General information regarding PCBs and PBDEs will not be given here, except as it applies to partitioning and uptake in aquatic food webs, as these compounds have been reviewed extensively elsewhere (Swackhamer 1996;

Rahman et al. 2001; Hites 2004; Hornbuckle et al. 2005; Hornbuckle et al. 2006).

Please refer to these reviews for more information regarding PCBs and PBDEs.

Previous work on the partitioning and bioaccumulation of PBDEs in Lake

Michigan will be provided in Appendix A as a supplement to the work presented here (Streets et al. 2006).

All samples in this study were collected as part of the Great Lakes Aquatic

Contaminant Survey (GLACS). The purpose of GLACS is to provide a

comprehensive data set of hydrophobic organic contaminant (HOC) concentrations in Lake Michigan water.

LITERATURE REVIEW

HOCs in the Aquatic Environment

Hydrophobic organic contaminants (HOCs) are toxic, human-made

chemicals that resist degradation and accumulate in water, soils, sediments, biota,

and humans throughout the world, including the Great Lakes region (Swackhamer et al. 1987; Swackhamer 1988; Pearson et al. 1996; Hornbuckle et al. 2006).

HOCs include a broad range of chemicals such as polychlorinated biphenyls

(PCBs), polybrominated diphenyl ethers (PBDEs), organochlorine pesticides, dioxins/furans, and other industrial chemicals and byproducts. In general, HOCs have low water solubilities and high octanol-water partition coefficients (KOW).

Because of their resistance to degradation, HOCs can be transported long

distances in the atmosphere and can be found in remote regions of the world

(Eduljee 2001; Halsall 2001; Simcik 2001). Although many of these contaminants

are now subject to regulation they are still a concern due to their continued

presence in the environment and biota.

HOCs tend to associate with the organic or lipid fraction of particles

because of their lipophilic nature (Karickhoff et al. 1979). The partitioning of

HOCs to particles results in two general fate pathways in aquatic systems:

transport into the food web by zooplankton and protozoan grazing of

contaminated particles, and transport to bottom sediments (Larsson et al. 2000).

Transport of HOCs into the food web has been shown to be a more important fate

in oligotrophic systems, while vertical transport of HOCs to bottom sediments is relatively more important in eutrophic systems (Larsson et al. 2000; Cotner et al.

2002). The larger size and greater biomass of phytoplankton in eutrophic systems results in increased sedimentation, and thus, increased transport, of particle- associated HOCs into the bottom sediments and out of the food web (Larsson et al. 2000). Also, rapid growth of phytoplankton in eutrophic systems results in the dilution of HOCs because growth kinetics limits the amount of pollutant that is transferred to the interior of the organism (Swackhamer et al. 1993). In contrast,

HOCs will become concentrated in the comparatively smaller biomass of oligotrophic systems. Also, the relatively slower settling velocity of these smaller particles allows particle-bound HOCs to remain in the water column for a longer period of time, making a greater relative proportion of HOCs available for accumulation in the food web. As a result, HOCs occur in higher concentrations in the food webs of oligotrophic systems (Larsson et al. 2000).

Bioaccumulation of HOCs in aquatic food webs is governed by partitioning from water to organisms at the primary trophic level. In classical food webs, the primary trophic level includes phytoplankton and other photosynthetic organisms. The uptake of HOCs by phytoplankton is well documented

(Swackhamer et al. 1993; Stange et al. 1994). However, recent research has demonstrated the importance of microbes and the so-called “microbial food web” or “microbial loop” to the uptake and transfer of HOCs, particularly in oligotrophic systems.

Significance of the Microbial Food Web in Contaminant Transfer

Pomeroy (1974) first introduced the concept of a microbial food web as a

way to characterize the role of microbes in aquatic ecosystems. In an influential

study, Azam et al. (1983) used the term “microbial loop” to describe the various

trophic levels within the microbial realm. In the microbial food web, bacteria use

the dissolved organic carbon (DOC) that is excreted by phytoplankton. Bacteria

are consumed by heterotrophic ciliates and flagellates, which are then consumed

by zooplankton, creating a “loop” that returns some of this lost DOC to the

classical aquatic food web (Fig. 1).

The potential importance of microbes in the cycling of nutrients in aquatic

food webs has been recognized for decades (Lindeman 1942). However, the

ability to quantify their importance is a much more recent discovery. Azam et al.

(1983) estimated that bacteria use 10 – 50% of the carbon that is excreted by phytoplankton. Since the flux of carbon and HOCs are coupled (Wallberg et al.

2000), it follows that the incorporation of DOC by bacteria would result in the simultaneous incorporation of HOCs.

The amount and type of particulate matter in aquatic ecosystems has a major impact on the distribution of HOCs in water (Broman et al. 1996). In marine ecosystems, heterotrophic bacteria comprise as much as 50-80% of the particulate biosurface available for sorption (Wallberg et al. 1999). The abundance of bacteria combined with their small size and relatively fast turnover rate makes bacteria the largest particulate biological surface area in natural

waters. Also, pelagic bacteria are carbon-rich and have a large surface-area-to-

volume ratio (Broman et al. 1996) making them potentially important vectors for

the sorption and transfer of contaminants. Heterotrophic bacteria have been

shown to comprise 14 – 58% of the total planktonic carbon in freshwater ecosystems, with the greatest proportion seen in the most oligotrophic waters

(Biddanda et al. 2001).

Fig 1. Schematic view of the food web in aquatic systems. The food web is often divided into a classical (herbivorous) and a microbial part, which vary with nutrient status of the system. The microbial food web is dominant in oligotrophic systems, while the classical food web dominates in eutrophic systems. Drawing: K. Wiklund, Umeå Marine Sciences Center (Larsson et al. 2000).

The role of the microbial loop in HOC transfer has been examined both in situ and in laboratory studies. Wallberg et al. (1997) quantified the sorption and transfer of 14C-PCB congeners (IUPAC # 3, 52, and 153) in a microbial food web in seawater mesocosms under laboratory conditions. Four important fractions were identified: dissolved (<0.2 µm), bacteria (0.2 – 2 µm), flagellate (2 – 10 µm) and phytoplankton and protozoa (>10 µm). Approximately 60-100% of the PCBs added to the mesocosms initially sorbed to bacteria. In contrast, only 0-5% of

PCBs initially sorbed to phytoplankton and protozoa in the >10 µm fraction.

Because initial sorption to the >10 µm fraction was so low, the authors concluded that the subsequent 75% increase in PCB concentrations in the >10 µm fraction over time was due to bacterivory and that protozoan grazing of bacteria is an important pathway in the bioaccumulation of PCBs.

In another laboratory study of seawater mesocosms, Wallberg et al. (1999) performed a time-course experiment to estimate PCB adsorption and absorption to various components of the microbial food web. The same size fractions were used in this study as in the 1997 study described above. The authors found that approximately 80% of the recovered PCBs were loosely adsorbed to cells, and that sorption varied depending on the hydrophobicity of the chemical, the structure of the cell membranes, and the lipid content of the cell. For example,

PCBs from the bacterial fraction were mostly recovered as adsorbed (as opposed to absorbed) because bacteria are coated with hydrophilic polysaccharides which prevents transfer of the PCBs to the inside of the cell.

In a follow-up study, Wallberg et al. (2001) demonstrated that the

accumulation of PCBs in bacteria at the base of a simplified microbial food web

occurred via passive uptake, whereas the uptake of PCBs in flagellates and

ciliates occurred via trophic transfer. PCB-153 was added to seawater mesocosms

and measured in each compartment of the microbial food web over time. The

concentration of PCB-153 in ciliates increased over time, whereas the

concentration in their prey decreased, leading the authors to conclude that the

increase of PCB-153 in ciliates was due to trophic transfer rather than passive

sorption.

There have been only a few in situ studies of HOC bioaccumulation in the microbial food web. Broman et al. (1996) measured PCBs (sum of six congeners) in the bacterial fraction (0.2 – 2 µm) and particulate fraction (2 – 90 µm) in summer and autumn in the Baltic Sea. PCB concentrations in bacteria and particulates were similar (300 ng/g OC and 500 ng/g OC, respectively) in summer. However, PCB concentrations were more than two orders of magnitude higher in the bacterial fraction (2000 ng/g OC) than in particulates (10 ng/g OC) in autumn. Broman et al. suggested that slower bacterial growth rates in autumn resulted in a longer time to equilibrium and thus, greater HOC concentrations in terms of total carbon. As a result, the authors concluded that bacteria are more important vectors of HOC transfer than phytoplankton during times of low productivity or in oligotrophic systems.

An important study by Hudson et al. (2005) measured PCBs in

heterotrophic bacteria and particulates in oligotrophic Lake Superior. This is the

only other known study of PCBs in heterotrophic bacteria in a freshwater

ecosystem. The authors defined the <1 µm fraction as the bacterial fraction, which

is in contrast to the studies described above in which the bacterial fraction was

defined as the 0.2 – 2 µm size fraction. This size fraction was used based on a

previous study that showed that approximately 95% of the organisms in the <1

µm fraction were heterotrophic bacteria (Biddanda et al. 2001). Although the <1

µm fraction does not necessarily sample all of the heterotrophic bacteria in the

water, it does provide a more representative sample than the larger size fractions

used in other studies (Hudson et al. 2005). In the Hudson et al. study, total PCB

concentrations (sum of 128 congeners) in the <1 µm fraction (61 – 337 ng/g OC)

were similar to, but generally higher than, total PCB concentrations in the total particulate fraction (36 – 324 ng/g OC). Hudson et al. (2005) also measured

bioaccumulation factors (BAFs) for PCBs in the bacterial fraction of Lake

Superior and found that the organic-carbon normalized log BAF (7.5 ± 1.9) was

greater in the bacterial fraction than in the total particulate fraction.

Sobek et al. (2006) measured PCBs (14 congeners) in bacteria (0.2 – 2 µm

fraction) and particulates (>0.7 µm) in the Barents Sea. Individual congener

concentrations were 0.5 – 5 ng/g OC in the bacterial fraction. The PCB

concentrations in the bacterial fraction in the Barents Sea were 20 – 300 times

lower than those measured by Broman et al. (1996) in the Baltic Sea when

compared on a congener-to-congener basis. It is difficult to compare the PCB

concentrations measured by Sobek et al. to those measured by Hudson et al. due

to the difference in the size range of the bacterial fraction.

Research Objectives

The objective of this work was to provide further evidence of the

importance of aquatic heterotrophic bacteria to HOC transfer in a freshwater

ecosystem by measuring PCBs and PBDEs in bacteria and particulates in situ. To

our knowledge, PCBs have only been measured in heterotrophic bacteria in a freshwater system in one other study. The data provided in this study are the first known measurements of PBDEs in aquatic heterotrophic bacteria. These data will be valuable in assessing the risk of human exposure to HOCs via the aquatic food web.

MATERIALS AND METHODS

Field Sampling

Water and bacteria were sampled in July, 2005 during stratified conditions aboard the US Environmental Protection Agency (EPA) R/V Lake Guardian at 7

locations along a north-south transect of Lake Michigan (Fig. 2). These sites

represent both open-lake and nearshore stations and were chosen by the EPA

Great Lakes National Program Office (GLNPO) to coincide with sampling locations used in the Lake Michigan Mass Balance Study (LMMBS) in 1994-95.

Sampling was conducted as part of the Great Lakes Aquatic Contaminant Survey

(GLACS) water monitoring program.

LM63 GB17 LM47

LM110

Milwaukee LM18

Chicago

Figure 2. Lake Michigan sampling sites and sample grouping for both the bacterial fraction composites and dissolved and particulate phase “artificial composites”. Bacterial Fraction Composite 1 = ; Bacterial Fraction Composite 2 = ; Bacterial Fraction Composite 3 =

Water Sample Collection

Water samples were collected from a depth of 5 m using a submersible pump at a rate of 30 L/min using methods described by Pearson et al. (1996).

Approximately 800 L of water was pumped through five GF/F glass fiber filter

(0.7 µm nominal pore size; Whatman, Maidstone, England, UK) in parallel and into four 125-L, covered, stainless steel holding tanks. Water was then pumped through a glass column (5 x 30 cm) filled with pre-cleaned XAD-2 microreticular resin (Supelco, Bellefonte, PA). After sampling, the resin was transferred with methanol to pre-cleaned (combusted at 450 ºC) amber jars and stored at 4 ºC until extraction. Dissolved and particulate phase water samples were collected according to methods previously described by Streets et al. (2006) (Appendix A).

Bacterial Fraction Collection

The bacterial fraction (defined as particles <1 µm) was collected by pumping whole lake water through a 1-µm cartridge filter (1µm absolute pore size; Flotrex™, Osmonics Inc., Minnetonka, MN, USA) at a rate of approximately 2 L/min using a peristaltic pump. Flow rate was monitored and recorded at regular intervals using a stopwatch and a graduated cylinder to determine total volume processed. After passing through the cartridge filter the water was pumped through a single, pre-combusted 293 mm GF/F glass fiber filter to collect bacteria and other <1-µm particles. The volume of water collected varied among stations. Individual samples were combined prior to extraction to

form 3 composite samples of similar volume to facilitate detection. The sites contributing to each composite are indicated in Figure 2.

Using the same site grouping as the bacteria samples, contaminant masses in water and particulate samples from each site were added together to form

“artificial” composite samples. Sample volumes were combined in the same manner. Total artificial composite masses were then divided by total artificial composite volumes to give an artificial composite concentration. For ease of reference, the bacteria samples and artificial composites were renamed as follows:

Composite 1= Milwaukee+Chicago+LM18; Composite 2 = LM110+LM47;

Composite 3 = LM63+GB17 (Fig. 2).

Suspended Particulate Matter and Particulate Organic Carbon Collection

Suspended particulate matter (SPM) was collected by passing a known volume of whole lake water (approximately 1 L) through a pre-weighed, 47-mm

NucleporeTM polycarbonate membrane filter (0.4 µm nominal pore size; Poretics®

Products, Osmonics, Livermore, CA, USA) using a vacuum aspirator. The loaded filter was transferred to a plastic Petri dish with forceps, the dish was taped shut, labeled, and stored at 4 ºC until transport back to the lab where it was placed in a desiccator until final weighing. Duplicate samples were collected at every site.

Particulate organic carbon (POC) was collected by passing a known volume of whole lake water (approximately 1 L) through a pre-combusted 25 mm

GF/F glass fiber filter (0.7 µm nominal pore size; Whatman, Maidstone, England,

UK) using a vacuum aspirator. The loaded filter was folded in half with clean

forceps, transferred to combusted aluminum foil, labeled, and stored at 4 ºC until transport back to the lab. Duplicate samples were collected at every site. POC was

measured by drying the filters at 100 ºC to constant weight; dry filters were

combusted using a Costech Analytical Elemental Combustion System (ECS) 4010

(Valencia, California, USA). Prior to analysis, filters were rolled in 30-mm

diameter tin foil discs (Elementar Americas Inc., Mt. Laurel, NJ, USA) and

placed in a 96-well plate for shipping and identification. Analysis was done by the

Ecosystems Analysis Lab at the University of Nebraska (Lincoln, NE, USA)

following EPA methods (Baladino 1995).

Suspended particulate matter (SPM) and particulate organic carbon (POC)

were also combined in the same manner described above for total particulates

prior to calculating the fraction of organic carbon associated with particles (OC)

to form similar artificial composites (Table 1).

Sample Extraction and Cleanup

The XAD-2 resin was transferred to a Soxhlet extractor apparatus and

extracted for 4 h with methanol. The methanol was removed to a separatory

funnel, and 150 mL of NaCl saturated organic-free water was added. This was

extracted with 3 x 50 mL of hexane. The hexane fractions were combined and

held until the final XAD-2 extract was complete. The Soxhlet extractor containing

the XAD was then spiked with surrogate standards (PCB 65, PCB 188, PDBE 71,

and PBDE 118) and extracted with dichloromethane (DCM) for 24 h. The extract was combined with the hexane extract and reduced to approximately 1 mL.

The extracts was then passed through a column (1 x 50 cm) containing 1 g of ashed sodium sulfate, 6 g of 2% deactivated neutral alumina, 1 g of ashed sodium sulfate, 4.5 g of 0% deactivated silica, and topped with 3 g of ashed sodium sulfate. The columns were rinsed before use with 3 x 33 mL 15%

DCM/hexane, 3 x 33mL of 40% DCM/hexane, and 3 x 40 mL of 100% hexane.

The extracts were quantitatively transferred and eluted with 3 x 33 mL of hexane

(F1). The F1 fraction contained the PCBs. The column was then eluted with 3 x

33 mL of 40% DCM in hexane (F2). The F2 fraction contained PBDEs. Both fractions were reduced to approximately 2 mL. The internal standard, PCB 204 was added to F1. The F1 fraction was analyzed for PCBs, and then recombined with the F2 fractions to analyze for PBDEs.

Instrumental Analysis

PCB congeners (110 chromatographic peaks containing individual or groups of coeluting congeners) were analyzed by a Hewlett-Packard 5890 gas chromatograph equipped with a 63Ni electron capture detector, 60m DB-5 column

(J&W Scientific, Folsom, CA, USA), and HP ChemStation data acquisition software. The method is described elsewhere (Pearson et al. 1996). Operating

conditions of the GC were as follows: splitless mode with 1 µL sample injections,

injection port 225 ºC, detector 325 ºC, variable oven temperature program from

100 to 280 ºC over 2 h. The carrier gas was hydrogen and the makeup gas was 5%

methane/95% argon. Chromatograms were carefully reviewed and baselines were

set manually to ensure correct peak identification based and quantitation. PCB

congeners were identified based on column retention time relative to the

calibration standard and quantified by the internal standard method.

Six PBDE congeners (47, 66, 100, 99, 154, 153) and polybrominated

biphenyl (PBB) 153 were analyzed by gas chromatography/mass spectrometry in

electron capture negative ionization mode (GC/MS-ECNI) equipped with a 60 m

DB-5 capillary column, helium carrier gas, and methane reaction gas. The GC/MS

was operated in selective ion monitoring mode for the bromine ions m/z 79 and

81, and for the internal standard using m/z 428 and 430. Operating conditions

were as follows: splitless mode with 2 µL sample injection, injection port 280 ºC,

detector 300 °C. Oven temperature program was as follows: 80 °C to 110 °C at 10

°C/min, 110 °C to 290 °C at 3 °C/min, 290 °C to 300 °C at 1 °C/min. Peak areas

for quantitation and confirmation m/z from the ion chromatograms were integrated and were checked for acceptable ratios and retention times based on

standards of congeners with known concentrations. Analyte concentrations were

determined by internal standard method using PCB 204 as the internal standard.

This method is used to correct for injection error, but is not used to correct for

losses during sample preparation and analysis (which is done using surrogate standards).

Quality Assurance/Quality Control

Several steps were taken to ensure the quality of data for this study from

collection to analysis. Quality assurance/quality control (QA/QC) procedures addressed background contamination, reproducibility, accuracy, and precision.

Background Contamination

Procedural blanks were processed with every extraction set of 4 samples to measure background concentrations of analytes of interest. Each blank was handled in the same manner as a routine sample using the method described above using only solvent and no sample media.

Field blanks were collected by taking clean sampling media into the field

and preparing the media for sampling without introducing the sample matrix. One

to two field blanks were collected for each type of sample (i.e., 1 XAD-2 blank, 1

GF/F blank, 2 POC blanks, and 2 SPM blanks).

Precision

One field replicate of each type of water sample (GF/F and XAD-2) was collected during the sampling cruise by collecting two complete samples at a given site. Field replicates were collected at every site for SPM and POC as part of routine sampling protocol. The relative percent difference (RPD) was calculated to quantify overall precision (Equation 1). Acceptable precision limits were 70 – 130%.

RPD = (X1 – X2) / Xaverage * 100 (1)

Accuracy

The percent recovery of surrogate standards and matrix spikes was determined to quantify analytical recovery. Surrogate standards were added to each sample to assess the analytical recovery of all analytes in the laboratory procedures. To determine the analytical recovery of PCBs, 100 µL of surrogate standard containing PCB 65 (2,3,5,6-tetrachlorobiphenyl; 7.25 ng) and PCB 188

(2,2’,3,4’,5,6,6’-heptachlorobiphenyl; 11.38 ng) was added at the beginning of the extraction of each sample and blank. The acceptable range of recovery was 70 –

130% of the known masses. PCB surrogate recoveries in all samples ranged from

85 – 171% for PCB 65, and 45 – 109% for PCB 188. Mean surrogate recovery (± standard deviation) was 101 ± 22% for PCB 65 and 84 ± 14% for PCB 188.

To measure the analytical recovery of PBDEs, 100 µL of a surrogate containing BDE-71 (2,3,4,6-tetrabromodiphenyl ether; 14.4 ng) and BDE-118

(2,3’,4,4’,5-pentabromodiphenyl ether; 7.2 ng) was added to each sample. The acceptable range of recovery was 70 – 130% of the known masses. PBDE surrogate recoveries in all samples ranged from 67 – 149% for BDE-71 and 84 –

172% for BDE-118. Mean surrogate recovery (± standard deviation) was 100 ±

21% for BDE-71 and 128 ± 26% for BDE-118.

Matrix spikes consisted of XAD-2 resin spiked with a 732 ng/mL PCB matrix spiking solution which contained Aroclors 1232, 1248, and 1262. Matrix spikes were handled in the same manner as routine samples including the addition of surrogate standards and internal standards. A total of 4 matrix spikes were run.

The average recovery for individual congeners ranged from 85-156%. The overall matrix spike recovery was 111 ± 11%.

Response factors of the internal standard, PCB-204, and the relative responses of the analytes of interest were monitored over time to ensure consistency across analyses.

RESULTS AND DISCUSSION

Water

PCBs were measured in both the dissolved and particulate phases (Table

1) at 7 sites in Lake Michigan in 2005 (Fig. 2). Lake Michigan is an oligotrophic

to mesotrophic freshwater ecosystem of oceanic scale. Dissolved phase ΣPCB

(sum of 128 individual and co-eluting congeners represented by 110 chromatographic peaks) concentrations ranged from 25 – 244 pg/L with a mean concentration of 100 pg/L. Particulate phase ΣPCB concentrations ranged from about 6.5 – 301 ng/g with a mean concentration of 75 ng/g.

The results from this study are similar to those from an earlier study

(Henderson 2006) in which water samples were collected from Lake Michigan in

October 2003 and April 2004 and analyzed for PCBs according to the same method used here. Mean dissolved-phase ΣPCB concentrations in that study were

115 pg/L and 129 pg/L in October and April, respectively. Mean particulate-phase

ΣPCB concentrations were 37 ng/g and 63 ng/g in October and April, respectively. The PCB concentrations measured by Henderson were lower than the PCB concentrations measured by Pearson et al. (1996) in 2001. In that study, dissolved phase concentrations of PCBs were 470 pg/L. Henderson’s work demonstrated that the overall mass of PCBs in the water column has decreased substantially since the early 1990s.

Concentrations of 6 PBDE congeners (47, 66, 99, 100, 153, 154) were consistently detected in dissolved water samples. The mean dissolved-phase water concentrations of individual PBDE congeners ranged from 0.48 to 35 pg/L (Table

1). These concentrations are similar to, but slightly greater than, individual PCB congeners (non-detect to 16 pg/L) measured in these samples. Six PBDE congeners were also detected in the particulate phase (Table 1). Mean particulate phase concentrations ranged from 0.06 to 2.4 ng/g. Concentrations of the PBDE congeners in both the dissolved and particulate phase were in the relative order 47

> 99 > 100 > 153 >154 ~ 66.

There are very few PBDE data for water in the Great Lakes. The most recent water samples from Lake Michigan were collected and analyzed in 2004 by

Streets et al. (2006) (see previously published work in Appendix A). PBDE concentrations measured in the dissolved phase in this study were approximately

3.5 times greater than the dissolved phase concentrations measured by Streets et al. in 2004 and are significantly different (p = 0.04).

PBB-153, another brominated flame retardant, was also measured in both the dissolved (0.13 pg/L) and particulate phases (0.11 ng/g).

Table 1. Mean (standard deviation) PBDE Congener Concentrations and ∑PCBs in Bacteria, Total Particulate, and Water in Lake Michigan Individual Water Samples (na = 7) Dissolved Phase (pg/L) Particulate Phase (ng/g OC) BDE-47 35 (21) 2.4 (1.6) BDE-66 04.8x10-1 (4.5x10-1) 7.0x10-2 (9.0x10-2) BDE-99 20 (7.4) 2.9 (2.0) BDE-100 4.3 (1.4) 7.1x10-1 (2.9x10-1) BDE-153 9.9x10-1 (6.6x10-1) 3.0x10-1 (4.2x10-1) BDE-154 5.4x10-1 (3.1x10-1) 6.0x10-2 (1.5x10-1) PBB-153 1.3x10-1 (1.5x10-1) 1.1x10-1 (3.8) ∑PBDE6 61 (29) 6.4 (3.8) ∑PCBs 1.0x10+2 (87) 75 (1.1x10+2) Suspended Particulate Matter (SPM) = 8.3x10-1 (6.0x10-1) mg/L (n = 14) Organic Carbon (OC)b = 4.1x10-1 (2.9x10-1) (n = 14) Bacteria (ng/g OC)c (n = 1) Composite 1 Composite 2 Composite 3 BDE-47 41 14 16 BDE-66 nde nde nde BDE-99 70 nde 34 BDE-100 11 nde nde BDE-153 nde nde nde BDE-154 nde nde nde PBB-153 nde nde nde ∑PBDE6 1.2x10+2 14 50 ∑PCBs 2.1x10+2 1.8x10+2 1.2x10+2 Total Particulate Artificial Composited (ng/g OC) Composite 1 Composite 2 Composite 3 BDE-47 6.5 (3.7) 7.8 (11) 1.9 (1.9) BDE-66 4.0x10-1 (0.22) 2.0x10-1 (0.28) nde BDE-99 8.9 (5.0) 8.3 (12) 5.0 (3.0) BDE-100 2.0 (1.1) 1.9 (2.7) 1.2 (0.76) BDE-153 1.7 (1.2) 1.0 (1.4) nde BDE-154 4.5x10-1 (0.25) nde nde PBB-153 3.8x10-1 (0.21) 5.8x10-1 (0.82) nde ∑PBDE6 21 (12) 9.4 (13) 8.3 (5.0) ∑PCBs 1.6x10+2 (91) 1.4x10+2 (1.9x10+2) 50 (31) Water, Dissolved Phase Artificial Composited (pg/L) Composite 1 Composite 2 Composite 3 BDE-47 1.6x10+2 (1.1x10-2) 47 (8.6x10-3) 39 (8.6x10-3) BDE-66 2.5 (1.0x10-4) 3.3x10-1 (4.5x10-5) 4.7x10-1 (4.5x10-5) BDE-99 74 (2.3x10-1) 35 (7.5x10-3) 28 (7.5x10-3) BDE-100 16 (1.3x10-3) 7.7 (1.1x10-3) 6.2 (1.1x10-3) BDE-153 2.2 (9.0x10-4) 3.1 (7.0x10-4) 1.2 (7.0x10-4) BDE-154 1.6 (5.0x10-4) 1.1 (4.0x10-4) 1.1 (4.0x10-4) PBB-153 5.3x10-1 (3.0x10-4) 2.3x10-1 (3.0x10-4) 1.5x10-1 (3.0x10-4) ∑PBDE6 2.6x10+2 (2.3x10-2) 95 (1.8x10-2) 76 (1.8x10-2) ∑PCBs 1.3x10+2 (27) 22 (22) 98 (22) SPM Artificial Composited (mg/L) Composite 1 Composite 2 Composite 3 1.0 (3.9x10-1) 4.0x10-1 (3.4x10-1) 9.4x10-1 (3.8x10-1) OC Artificial Composited Composite 1 Composite 2 Composite 3 3.1x10-1 (1.2x10-1) 6.0x10-1 (6.7x10-1) 4.3x10-1 (1.9x10-1)

8 9 Site 1 Composite 1 SitCome 1 posite 1 y = 0.4832x + 3.354 2 y = 0.4504x + 3.082 r = 0.69 2 p = 0.02 8 r = 0.32 p = 0.07 7 oc 7 oc log BAF log log K log 6 6

5 5 5678 56789

log Kow log Kow

9 9 Site 2 Composite 2 SiteCom 2 posite 2 y = -0.1233x + 8.129 y = -0.0613x + 7.443 r2 = 0.03 r2 = 0.01 8 p = 0.15 8 p = 0.04 oc oc 7 7 log K log BAF log

6 6

5 5 567856789 log K ow log Kow

8 8 SiteCom 3 posite 3 SiteCom 3 posite 3

y = 0.4839x + 3.585 y = 0.5370x + 2.425 2 r = 0.54 r2 = 0.42 p = 0.10 p = 0.18 7 7 oc oc log K log log BAF 6 6

5 5678 5678 log Kow log Kow

Figure 3. Individual PCB and PBDE congener log BAFoc/log Kow and log Koc/log Kow plots for bacteria and total particulate artificial composites. PCBs are represented by closed circles and PBDEs are represented by open circles. PBDEs were not included in the regression, but are shown for comparison to PCBs.

Bacteria and Particulate Composites

PBDEs, PCBs, and PBB-153 were also analyzed in the composite bacteria

samples, operationally defined here as particles < 1µm in size. ΣPCB concentrations in bacteria ranged from about 121 to 213 ng/g OC (Table 1).

ΣPCB concentrations in total particulates ranged from 50 to 163 ng/g OC, which was similar to, but lower than, ΣPCB concentrations in bacteria. ΣPCBs in dissolved phase artificial composite samples ranged from 22 to 131 pg/L (Table

1).

The results in bacteria are similar to results found by Hudson et al. (2005) and Sobek et al. (2006). Hudson et al. measured PCBs in bacteria and total particulates from Lake Superior in 2002. In that study, PCB concentrations in bacteria (61 – 337 ng/g OC) were greater than those in total particulates (36 – 324 ng/g OC) in 4 of 5 measurements. Sobek et al. measured PCBs in bacteria and particulates collected in the northern Barents Sea in 2001. As in this study and the study by Hudson et al., PCB concentrations in bacteria were greater than in particulates. Only 14 PCB congeners were measured by Sobek et al., so a direct

comparison cannot be made for ΣPCBs. However, when compared on a congener- to-congener basis (for congeners that were detected in both studies), PCB congener concentrations in the bacterial fraction from Lake Michigan were approximately 5 - 20 times higher than in Sobek et al. For example, the average

concentration of PCB-118 in the bacterial fraction of Lake Michigan was 12.5 ng/g OC compared to 0.95 ng/g OC in the bacterial fraction of the Barents Sea.

PCB-153 had an average concentration of 13.5 ng/g OC in Lake Michigan bacteria, whereas the average concentration in Barents Sea bacteria was only 2.1 ng/g OC. The dominant congeners in the Sobek et al. study were the tetra- and penta-CBs 90/101 and 52. In this study, the dominant congeners were 110+77

(tetra- and penta-CBs), 163+138 (hexa-CBs), and 15+17 (di- and tri-CBs). The higher PCB concentrations in Lake Michigan compared to the northern Barents

Sea make sense given the greater degree of industrialization and historical sources of PCBs to Lake Michigan. The dominance of less-chlorinated PCBs in Lake

Michigan water and bacteria also makes sense because the atmosphere is now the major source of PCBs to Lake Michigan (Hornbuckle et al. 2006).

In addition to the difference in the congeners analyzed in these studies,

Sobek et al. defined the bacteria as the fraction of particulates that were between

0.2 and 2 µm, compared to the < 1 µm designation used in this study. The size range used by Sobek et al. would likely include more small phytoplankton than the <1 µm fraction used in this study since the typical linear dimensions for both marine and freshwater bacteria are 0.2 – 1 µm (Scavia et al. 1986). Indeed, Sobek et al. define phytoplankton as particles > 0.7 µm. A sample containing a greater proportion of phytoplankton would likely contain more OC which could result in a longer time to equilibrium between the particles and the water, and thus, lower chemical concentrations.

Three PBDE congeners (47, 99, and 100) were measured in bacteria at concentrations ranging from non-detect to 70 ng/g OC (Table 1). This is the first

time PBDEs have been measured in aquatic heterotrophic bacteria. BDE-99 was

the dominant congener in bacteria, which is in contrast to results in the dissolved

and particulate phases, where BDE-47 was the dominant congener.

Six PBDE congeners were measured in total particulate composite

samples. Concentrations ranged from non-detect to 8.9 ng/g OC (Table 1). PBDE

congener concentrations in the dissolved phase composites ranged from 0.15 –

161 pg/L. BDE-47 was the dominant congener in the dissolved phase composite

samples.

PBB-153 was not detected in any of the bacteria samples, which may be

due to a possible detection issue. The total particulate composite samples had

PBB-153 concentrations of 0.38 and 0.58 ng/g OC at Composites 1 and 2,

respectively. PBB-153 concentrations ranged from 0.15 to 0.53 pg/L in dissolved

phase artificial composites.

Bacterial carbon data collected from Lake Michigan by Cotner et al.

(2000) was used to determine the fraction of organic carbon attributed to bacteria.

A value of 23.9 fg C/cell was used to normalize contaminant concentrations in

bacteria. This is similar to the value (20 fg C/cell) used in a study of PCBs in

bacteria in Lake Superior by Hudson et al. (2005). We assumed a bacterial cell

concentration of 106 cells/mL, which is supported by a previous study of bacterial production in Lake Michigan (Scavia et al. 1987).

Partitioning and Bioaccumulation

Organic-carbon normalized bioaccumulation factors (BAFOC) and organic-

carbon normalized water-particle partition coefficients (KOC) were calculated for

PCBs (mean of individual congeners) and individual PBDE congeners (Table 2).

Log BAFOCs for PCBs in bacteria ranged from 6.7 to 7.4. Log BAFOCs for

individual PBDE congeners in bacteria ranged from 5.4 to 6.1, about an order of

magnitude lower than for PCBs. Log KOCs for PCBs ranged from 5.9 to 6.7. Log

KOCs for individual PBDE congeners ranged from 4.6 to 5.9, also about an order

of magnitude lower than PCBs. Log BAFOCs for both PBDEs and PCBs were

greater than their respective log KOCs. Log BAFOCs for PCBs measured in this

study were very similar to those measured by Hudson et al. (6.9 to 7.3). Log KOCs

measured by Hudson et al. are similar to, or greater than, the log KOCs given here.

Composite 1 generally had higher concentrations of PBDEs and PCBs in water, bacteria, and particulates than Composites 2 and 3. This is consistent with the fact that Composite 1 includes Milwaukee and Chicago nearshore sample sites, as well as the offshore site LM18. There were no clear trends with respect to

PCB or PBDE concentrations at Composites 2 and 3.

Log BAFOC and log KOC were plotted against log KOW to determine

whether partitioning between the water and bacterial or particulate fractions were

at equilibrium (Figure 3). If equilibrium had been achieved, the linear regression

between either log BAFOC or log KOC with log KOW would exhibit a positive

relationship with a slope of 1 (Mackay 1982).

Table 2. Bacteria log BAFOCs and Particulate log KOCs (standard deviation) for Individual PBDE Congeners and PCB Individual Congener Means Bacteria log BAFOC Composite 1 Composite 2 Composite 3 BDE-47 5.4 5.5 5.6 BDE-66 - - - BDE-99 6.0 - 6.1 BDE-100 5.8 - - BDE-153 - - - BDE-154 - - - PBB-153 - - - PCB Individual 6.7 (0.4) 7.4 (0.5) 7.0 (0.5) Congener Mean Particulate log KOC Composite 1 Composite 2 Composite 3 BDE-47 4.6 (1.2) 5.2 (0.8) 4.7 (1.0) BDE-66 5.2 (1.3) 5.8 (0.9) - BDE-99 5.1 (1.3) 5.4 (0.8) 5.3 (1.2) BDE-100 5.1 (1.3) 5.4 (0.8) 5.3 (1.1) BDE-153 5.9 (0.9) 5.5 (0.8) - BDE-154 5.5 (1.4) - - PBB-153 5.9 (1.5) 6.4 (1.0) - PCB Individual 6.2 (1.4) 6.7 (1.6) 5.9 (1.1) Congener Mean

Composite 1 was the closest to equilibrium for both BAFOC and KOC

(Figure 3). Although the regression of KOC with KOW was not significant at 95%, it was significant at 90%. Composite 1 had the lowest OC of any of the three

composites, indicating that the particulates at Composite 1 were dominated by

resuspended sediment. This may explain why Composite 1 was closer to

equilibrium than Composite 2 and 3 since less OC would result in a shorter time

to equilibrium between chemical concentrations in water and particulates.

The regressions at Composite 2 (Figure 3) show no relationship between either BAFOC or KOC and KOW, which stands in contrast with Composite 1 and 3.

OC at Composite 2 was quite high, which may be due to a higher proportion of

phytoplankton in the particulate fraction than in the other composites. It is also

possible that the bacteria sample, Composite 2, contained autotrophic

picoplankton (plankton less than 1 µm in size), which has been shown to be a

potentially important component of the microbial loop in Lake Superior

(Fahnenstiel et al. 1986). This could explain why the BAFOC regression at

Composite 2 is so different compared to Composites 1 and 3, since autotrophic

picoplankton may contain more OC than heterotrophic bacteria and higher OC

could result in a longer time to equilibrium.

For Composite 3, BAFOC and KOC showed more of a relationship with

KOW than for Composite 2, which is consistent with Composite 1. Although the

regression of BAFOC with KOW was not significant at 95%, it was significant at

90%. OC in Composite 3 was elevated compared to Composite 1, though it was

not as high as Composite 2. It is likely that these samples were influenced by a

phytoplankton bloom, resulting in higher OC and a longer time to equilibrium.

This makes sense because Composite 3 includes Green Bay which tends to have

more phytoplankton than the open waters of Lake Michigan.

In all cases, PBDEs BAFOCs are over-predicted by KOW by 1 – 2 orders of

magnitude. This is unexpected since PBDEs and PCBs are compounds with

similar structure and thus are expected to exhibit similar behavior with respect to

partitioning and bioaccumulation behavior in the environment (Rahman et al.

2001; Siddiqi et al. 2003; Streets et al. 2006). Although the BAFs for certain

PBDEs congeners in fish are underpredicted by KOW due to biotransformation

(Stapleton et al. 2004), it is unclear why KOWs underpredict the BAFs in this

study.

In light of the data presented here, it is does not seem prudent to use PCB bioaccumulation data for bacteria to model the bioaccumulation of PBDEs. Using either the PCB BAFOCs or KOCs would likely over predict PBDE concentrations

by at least an order of magnitude. Although PCBs and PBDEs have similar structures and appear to exhibit similar behavior with regard to bioaccumulation in fish, it is clear that these compounds do not behave exactly the same in all biological systems.

REFERENCES

Achman, D. R., K. C. Hornbuckle and S. J. Eisenreich (1993). "Volatilization of polychlorinated biphenyls from Green Bay, Lake Michigan." Environmental Science & Technology 27(1): 75-87. Alaee, M. and R. J. Wenning (2002). "The significance of brominated flame retardants in the environment: current understanding, issues and challenges." Chemosphere 46(5): 579-582. Alaee, M., P. Arias, A. Sjodin and Ã. Bergman (2003). "An overview of commercially used brominated flame retardants, their applications, their use patterns in different countries/regions and possible modes of release." Environment International 29(6): 683-689. Andersson, P., N. Wagman, H. Berg, P. Olsson and M. Tysklind (1999). "Biomagnification of structurally matched polychlorinated and polybrominated diphenylethers (PCDE/PBDE) in zebrafish (Danio rerio)." Organohalogen Compounds 43: 9-12. Azam, F., T. Fenchel, J. G. Field, J. S. Gray, L. A. Meyer-Reil and F. Thingstad (1983). "The ecological role of water-column microbes in the sea." Marine Ecology Progress Series 10(3): 257-263. Baladino, R. (1995). "Outline of Standard Protocols for Particulate Organic Carbon (POC) Analyses." (Revision 1). Baker, J. E. and S. J. Eisenreich (1989). "PCBs and PAHs as tracers of particulate dynamics in large lakes." Journal of Great Lakes Research 15(1): 84-103. Baker, J. E., S. J. Eisenreich and D. L. Swackhamer, Eds. (1991). Organic Substances in Sediments and Water. Chelsea, MI, Lewis Publishers. Baker, R. A. (1991). Organic Substances and Sediments in Water: Processes and Analytical, CRC. Biddanda, B., M. Ogdahl and J. Cotner (2001). "Dominance of bacterial metabolism in oligotrophic relative to eutrophic waters." Limnology and Oceanography 46(3): 730-739. Boon, J. P., W. E. Lewis, M. R. Tjoen-A-Choy, C. R. Allchin, J. Robin, J. De Boer, C. Cato and B. N. Zegers (2002). "Levels of polybrominated diphenyl ether (PBDE) flame retardants in animals representing different trophic levels of the North Sea food web." Environmental Science & Technology 36(19): 4025-4032. Braekevelt, E., S. A. Tittlemier and G. T. Tomy (2003). "Direct measurement of octanol-water partition coefficients of some environmentally relevant brominated diphenyl ether congeners." Chemosphere 51(7): 563-567. Broman, D., C. Naef, J. Axelman, C. Bandh, H. Pettersen, R. Johnstone and P. Wallberg (1996). "Significance of bacteria in marine waters for the distribution of hydrophobic organic contaminants." Environmental Science and Technology 30(4): 1238-1241.

Burkhard, L. P. and M. T. Lukasewycz (2000). "Some bioaccumulation factors and biota-sediment accumulation factors for polycyclic aromatic hydrocarbons in lake trout." Environmental Toxicology and Chemistry 19(5): 1427-1429. Burreau, S., J. Axelman, D. Broman and E. Jakobsson (1997). "Dietary uptake in pike (Esox lucius) of some polychlorinated biphenyls, polychlorinated naphthalenes and polybrominated diphenyl ethers administered in natural diet." Environmental Toxicology and Chemistry 16(12): 2508-2513. Burreau, S., Y. Zebahr, D. Broman and R. Ishaq (2004). "Biomagnification of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) studied in pike (Esox lucius), perch (Perca fluviatilis) and roach (Rutilus rutilus) from the Baltic Sea." Chemosphere 55(7): 1043-1052. Carlson, D. L. and D. L. Swackhamer (2006). "Results from the US Great Lakes fish monitoring program and effects of lake processes on bioaccumulative contaminant concentrations." Journal of Great Lakes Research 32(2): 370- 385. Cotner, J., T. Johengen and B. Biddanda (2000). "Intense winter heterotrophic production stimulated by benthic resuspension." Limnology and Oceanography: 1672-1676. Cotner, J. B. and B. A. Biddanda (2002). "Small players, large role: microbial influence on biogeochemical processes in pelagic aquatic ecosystems." Ecosystems 5(2): 105-121. Darnerud, P. O. (2003). "Toxic effects of brominated flame retardants in man and in wildlife." Environment International 29(6): 841-853. De Vault, D. S., R. Hesselberg, P. W. Rodgers and T. J. Feist (1996). "Contaminant trends in lake trout and walleye from the Laurentian Great Lakes." Journal of Great Lakes Research 22(4): 884-895. DeVault, D. S., J. Milton Clark, G. Lahvis and J. Weishaar (1988). "Contaminants and trends in fall run coho salmon." Journal of Great Lakes Research 14(1): 23-33. Eduljee, G. H. (2001). Budget and source inventories: Issues and challenges. Persistent Organic Pollutants: Environmental Behaviour and Pathways of Human Exposure. S. Harrad, Kluwer Academic Publishers: 1-28. Fahnenstiel, G., L. Sicko-Goad, D. Scavia and E. Stoermer (1986). "Importance of picoplankton in Lake Superior." Canadian Journal of Fisheries and Aquatic Sciences 43(1): 235-240. Gouin, T. and T. Harner (2003). "Modelling the environmental fate of the polybrominated diphenyl ethers." Environment International 29(6): 717- 724. Hale, R. C., M. Alaee, J. B. Manchester-Neesvig, H. M. Stapleton and M. G. Ikonomou (2003). "Polybrominated diphenyl ether flame retardants in the North American environment." Environment International 29(6): 771-779.

Halsall, C. J. (2001). Long-range transport: Implications for polar regions. Persistent Organic Pollutants: Environmental Behaviour and Pathways of Human Exposure. S. Harrad, Kluwer Academic Publishers: 211-232. Henderson, S. A. (2006). Trends in concentration and partitioning of polychlorinated biphenyls in the open water of Lake Michigan. Minneapolis, University of Minnesota. M.S. Hickey, J., S. A. Batterman and S. Chernyak (2006). "Trends of chlorinated organic contaminants in Great Lakes trout and walleye from 1970 to 1998." Archives of Environmental Contamination and Toxicology 50(1): 97-110. Hites, R. A. (2004). "Polybrominated diphenyl ethers in the environment and in people: a meta-analysis of concentrations." Environmental Science & Technology 38(4): 945-956. Hornbuckle, K. C., D. L. Carlson, D. L. Swackhamer, J. E. Baker and S. J. Eisenreich (2005). "Polychlorinated biphenyls in the Great Lakes." The Handbook of Environmental Chemistry 1: 15. Hornbuckle, K. C., D. L. Carlson, D. L. Swackhamer, J. E. Baker and S. J. Eisenreich (2006). Polychlorinated biphenyls in the Great Lakes. Persistent Organic Pollutants in the Great Lakes. R. A. Hites. Berlin Springer. 5N: 13-70. Hudson, M. J., D. L. Swackhamer and J. B. Cotner (2005). "Effect of microbes on contaminant transfer in the Lake Superior food web." Environmental Science and Technology 39(24): 9500-9508. Johnson-Restrepo, B., K. Kannan, R. Addink and D. H. Adams (2005). "Polybrominated diphenyl ethers and polychlorinated biphenyls in a marine foodweb of coastal Florida." Environmental Science & Technology 39(21): 8243-8250. Karickhoff, S. W., D. S. Brown and T. A. Scott (1979). "Sorption of hydrophobic pollutants on natural sediments." Water Research 13(3): 241-248. Kierkegaard, A., A. Bignert, U. Sellstrom, M. Olsson, L. Asplund, B. Jansson and C. De Wit (2004). "Polybrominated diphenyl ethers (PBDEs) and their methoxylated derivatives in pike from Swedish waters with emphasis on temporal trends, 1967 “2000." Environmental Pollution 130(2): 187-198. Larsson, P., A. Andersson, D. Broman, J. NordbÃ¤ck and E. Lundberg (2000). "Persistent organic pollutants (POPs) in pelagic systems." AMBIO: A Journal of the Human Environment 29(4): 202-209. Lindeman, R. L. (1942). "The trophic-dynamic aspect of ecology." Ecology 23(4): 399-417. Litten, S., D. J. McChesney, M. C. Hamilton and B. Fowler (2003). "Destruction of the World Trade Center and PCBs, PBDEs, PCDD/Fs, PBDD/Fs, and chlorinated biphenylenes in water, sediment, and sewage sludge." Environmental Science & Technology 37(24): 5502-5510.

Luross, J. M., M. Alaee, D. B. Sergeant, C. M. Cannon, D. Michael Whittle, K. R. Solomon and D. C. G. Muir (2002). "Spatial distribution of polybrominated diphenyl ethers and polybrominated biphenyls in lake trout from the Laurentian Great Lakes." Chemosphere 46(5): 665-672. Mackay, D. (1982). "Correlation of bioconcentration factors." Environmental Science & Technology 16(5): 274-278. Pearson, R. F., K. C. Hornbuckle, S. J. Eisenreich and D. L. Swackhamer (1996). "PCBs in Lake Michigan water revisited." Environmental Science and Technology 30(5): 1429-1436. Pomeroy, L. R. (1974). "The ocean’s food web, a changing paradigm." BioScience 24(9): 499-504. Rahman, F., K. H. Langford, M. D. Scrimshaw and J. N. Lester (2001). "Polybrominated diphenyl ether (PBDE) flame retardants." Science of the Total Environment 275(1-3): 1-17. Sabljic, A., H. Guesten, J. Hermens and A. Opperhuizen (1993). "Modeling octanol/water partition coefficients by molecular topology: Chlorinated benzenes and biphenyls." Environmental Science & Technology 27(7): 1394-1402. Scavia, D. and G. Laird (1987). "Bacterioplankton in Lake Michigan: dynamics, controls, and significance to carbon flux." Limnology and Oceanography 32(5): 1017-1033. Scavia, D., G. Laird and G. Fahnenstiel (1986). "Production of planktonic bacteria in Lake Michigan." Limnology and Oceanography 31(3): 612-626. Siddiqi, M. A., R. H. Laessig and K. D. Reed (2003). "Polybrominated diphenyl ethers (PBDEs): new pollutants - old diseases." Clinical Medicine & Research 1(4): 281-290. Simcik, M. F. (2001). Atmospheric Fate and Behaviour. Persistent Organic Pollutants: Environmental Behaviour and Pathways of Human Exposure. S. Harrad, Kluwer Academic Publishers: 29-52. Sjodin, A., D. G. Patterson and Ã. Bergman (2003). "A review on human exposure to brominated flame retardants--particularly polybrominated diphenyl ethers." Environment International 29(6): 829-839. Sobek, A., K. Olli and O. Gustafsson (2006). "On the relative significance of bacteria for the distribution of polychlorinated biphenyls in arctic ocean surface waters." Environ. Sci. Technol 40(8): 2586-2593. Song, W., J. C. Ford, A. Li, J. William, D. R. Buckley and K. J. Rockne (2004). "Polybrominated diphenyl ethers in the sediments of the Great Lakes. 1. Lake Superior." Environmental Science & Technology 38(12): 3286-3293. Stange, K. and D. L. Swackhamer (1994). "Factors affecting phytoplankton speciesâ€ specific differences in accumulation of 40 polychlorinated biphenyls (PCBs)." Environmental Toxicology and Chemistry 13(11): 1849-1860.

Stapleton, H. M., R. J. Letcher and J. E. Baker (2004). "Debromination of polybrominated diphenyl ether congeners BDE 99 and BDE 183 in the intestinal tract of the common carp (Cyprinus carpio)." Environmental Science & Technology 38(4): 1054-1061. Stapleton, H. M., N. G. Dodder, J. H. Offenberg, M. M. Schantz and S. A. Wise (2005). "Polybrominated diphenyl ethers in house dust and clothes dryer lint." Environmental Science & Technology 39(4): 925-931. Strandberg, B., N. G. Dodder, I. Basu and R. A. Hites (2001). "Concentrations and spatial variations of polybrominated diphenyl ethers and other organohalogen compounds in Great Lakes air." Environmental Science & Technology 35(6): 1078-1083. Streets, S. S., S. A. Henderson, A. D. Stoner, D. L. Carlson, M. F. Simcik and D. L. Swackhamer (2006). "Partitioning and bioaccumulation of PBDEs and PCBs in Lake Michigan." Environmental Science and Technology 40(23): 7263-7269. Swackhamer, D. L. (1988). Studies of Polychlorinated Biphenyls in the Great Lakes. Chlorinated Organic Micropollutants. R. E. Hester and R. M. Harrison. Cambridge, UK, The Royal Society of Chemistry. 6: 137-153. Swackhamer, D. L. (1996). "Studies of polychlorinated biphenyls in the Great Lakes." Issues in Environmental Science and Technology 6: 137-153. Swackhamer, D. L. and D. E. Armstrong (1987). "Distribution and Characterization of PCBs in Lake Michigan Water." Journal of Great Lakes Research 13(1): 24-36. Swackhamer, D. L. and R. Skoglund (1993). "Bioaccumulation of PCBs by algae: kinetics versus equilibrium." Environmental Toxicology and Chemistry 12(5): 831-838. Tomy, G. T., V. P. Palace, T. Halldorson, E. Braekevelt, R. Danell, K. Wautier, B. Evans, L. Brinkworth and A. T. Fisk (2004). "Bioaccumulation, biotransformation, and biochemical effects of brominated diphenyl ethers in juvenile lake trout (Salvelinus namaycush)." Environmental Science & Technology 38(5): 1496-1504. Vander Zanden, M. J. and J. B. Rasmussen (1996). "A trophic position model of pelagic food webs: impact on contaminant bioaccumulation in lake trout." Ecological Monographs: 451-477. Wallberg, P. and A. Andersson (1999). "Determination of adsorbed and absorbed polychlorinated biphenyls (PCBs) in seawater microorganisms." Marine Chemistry 64(4): 287-299. Wallberg, P. and A. Andersson (2000). "Transfer of carbon and a polychlorinated biphenyl through the pelagic microbial food web in a coastal ecosystem." Environmental Toxicology and Chemistry 19(4): 827-835. Wallberg, P., P.-A. Bergqvist and A. Andersson (1997). "Potential importance of protozoan grazing on the accumulation of polychlorinated biphenyls (PCBs) in the pelagic food web." Hydrobiologia 357: 53-62.

Wallberg, P., P. R. Jonsson and A. Andersson (2001). "Trophic transfer and passive uptake of a polychlorinated biphenyl in experimental microbial communities." Environmental Toxicology and Chemistry 20(10): 2158- 2164. Watanabe, I. and S. Sakai (2003). "Environmental release and behavior of brominated flame retardants." Environment International 29(6): 665-682. Wolkers, H., B. Van Bavel, A. E. Derocher, Ã. Wiig, K. M. Kovacs, C. Lydersen and G. Lindstrom (2004). "Congener-specific accumulation and food chain transfer of polybrominated diphenyl ethers in two Arctic food chains." Environmental Science & Technology 38(6): 1667-1674. Zhu, L. Y. and R. A. Hites (2004). "Temporal trends and spatial distributions of brominated flame retardants in archived fishes from the Great Lakes." Environmental Science & Technology 38(10): 2779-2784.

APPENDIX A

Partitioning and Bioaccumulation of PBDEs and PCBs in Lake Michigan

Reprinted with permission from:

Streets, S. S., S. A. Henderson, A. D. Stoner, D.L. Carlson, M. F. Simcik and D. L. Swackhamer (2006). "Partitioning and bioaccumulation of PBDEs and PCBs in Lake Michigan." Environmental Science and Technology 40(23): 7263-7269.

American Chemical Society

APPENDIX B

Data and QA/QC

Table A1. Total PCB concentrations in individual water samples. Site Dissolved Particulate Avg SPM Avg POC (pg/L) (ng/g) Milwaukee 243.74 97.34 1.43 0.20 Chicago 65.83 12.51 0.90 0.12 LM18 97.31 8.23 1.00 0.01 LM110 24.40 300.70 0.40 0.20 LM47 24.63 6.52 0.37 0.33 LM63 46.07 88.89 0.20 0.18 GB17 196.05 12.20 1.83 0.63

Table A2. Total PCB concentrations, log BAFoc, and log Koc in bacteria samples and total particulate artificial composites. Site Bacteria (ng/g Particulate Bacteria Particulate OC) (ng/g OC) ∑PCBs log ∑PCBs log Koc BAFoc Composite 1 213.44 162.54 6.21 6.21 Composite 2 182.16 136.19 6.92 6.92 Composite 3 120.77 50.21 6.09 6.09

Table A3. Dissolved phase PBDE concentrations in individual samples (pg/L). Site BDE 47 BDE BDE BDE BDE BDE PBB ∑6 66 100 99 154 153 153 BDE Milw 72.32 1.23 4.99 22.60 0.00 0.77 0.40 101.9 1 Chi 31.46 0.32 4.23 19.67 0.59 0.00 0.00 56.27 LM18 57.48 0.98 6.78 32.14 1.02 1.38 0.13 99.78 LM110 18.14 0.04 3.00 13.13 0.39 1.02 0.00 35.71 LM47 29.14 0.29 4.67 22.40 0.67 2.05 0.23 59.22 LM63 25.70 0.36 3.74 18.91 0.47 0.42 0.00 49.59 GB17 13.44 0.11 2.46 9.04 0.64 0.76 0.15 26.45

Table A4. Particulate phase PBDE concentrations in individual samples (ng/g). Site BDE BDE 66 BDE BDE 99 BDE BDE153 PBB ∑6 47 100 154 153 BDE Milw 2.16 0.20 0.59 3.72 0.00 0.93 0.26 7.60 Chi 2.02 0.00 0.63 2.38 0.00 0.00 0.00 5.03 LM18 1.07 0.10 0.41 0.81 0.41 0.34 0.00 3.14 LM110 3.43 0.00 0.91 5.93 0.00 0.00 0.00 10.27 LM47 5.38 0.17 1.27 4.91 0.00 0.85 0.49 12.59 LM63 1.81 0.00 0.71 0.76 0.00 0.00 0.00 3.28 GB17 0.65 0.00 0.47 2.14 0.00 0.00 0.00 3.26

Table A5. PBDE concentrations in dissolved phase artificial composites (pg/L). Site BDE BDE BDE BDE BDE BDE153 PBB ∑6 47 66 100 99 154 153 BDE Composite 1 161.27 2.53 15.99 74.41 1.60 2.16 0.53 257.96 Composite 2 47.28 0.33 7.66 35.53 1.06 3.07 0.23 94.93 Composite 3 39.14 0.47 6.20 27.95 1.11 1.17 0.15 76.03

Table A6. PBDE concentrations in particulate phase artificial composites (ng/g) OC). Site BDE BDE BDE BDE BDE BDE PBB ∑6 47 66 100 99 154 153 153 BDE Composite 1 6.55 0.40 2.00 8.92 0.45 1.74 0.38 21.04 Composite 2 7.79 0.20 1.88 8.29 0.00 1.00 0.58 9.44 Composite 3 1.93 0.00 1.25 5.03 0.00 0.00 0.00 8.30

Table A7. PBDE concentrations in bacteria samples (ng/g OC). Site BDE 47 BDE 99 BDE 100 Composite 1 40.76 70.41 10.96 Composite 2 13.92 0.00 0.00 Composite 3 15.81 33.82 0.00

Table A8. PBDE bacteria log BAFOC. Site BDE 47 BDE 99 BDE 100 Composite 1 5.40 5.98 5.84 Composite 2 5.47 - - Composite 3 5.61 6.08 -

Table A9. PBDE total particulate log KOC in artificial composites. Site BDE BDE BDE BDE BDE BDE PBB ∑6 47 66 100 99 154 153 153 BDE Composite 1 5.06 5.64 5.55 5.53 5.90 6.36 6.30 5.36 Composite 2 5.55 6.11 5.72 5.70 - 5.85 6.73 5.33 Composite 3 4.69 - 5.30 5.25 - - - 5.03

Table A10. Congener-specific log BAFOC for PCBs in bacteria at Composite 1.

Congener Log Congene Log Congener Log Congener Log BAFOC r BAFOC BAFOC BAFO C 1 47+48 85 167 3 65 SSTD 136 185 4+10 44 6.02 110+77 6.71 174 7+9 37 82 177 6 42 151 202+171+156 8+5 41+71 135+144+124+147 173 19 64 107 157+200 30 Old ISTD 40 123+149 204 Old ISTD 12+13 100 118 6.80 172 18 63 134 197 15+17 6.42 74 144+131 180 6.83 24+27 70+76 6.53 188 ISTD 193 16+32 66+95 146 191+199 7.43 29 91 7.00 153 6.88 170+190 26 56+60 132+105 198 25 92 6.65 141 6.94 201 28+31 5.97 84 6.52 137+176 203 21 89 130 196 53+33 6.15 101 163+138 6.97 189 51 99 6.72 158 208+195 22 119 129+178 207 45 83 175 194 46 97 187+182 6.93 205 52 81 183 206 43+49 87 128 209

Table A11. Congener-specific log KOC for PCBs in particulates at Composite 1.

Congener Log Congener Log Congener Log Congener Log KOC KOC KOC KOC 1 47+48 6.99 85 6.89 167 3 65 SSTD 136 185 4+10 44 110+77 6.54 174 7.12 7+9 37 82 5.40 177 7.02 6 42 6.29 151 7.10 202+171+156 6.68 8+5 41+71 7.13 135+144+124+147 6.72 173 19 64 6.72 107 6.66 157+200 30 Old 40 6.29 123+149 6.58 204 Old ISTD ISTD 12+13 6.31 100 118 6.56 172 6.63 18 3.02 63 6.83 134 7.63 197 15+17 6.37 74 144+131 7.88 180 24+27 70+76 6.10 188 ISTD 193 6.86 16+32 5.94 66+95 6.55 146 6.94 191+199 6.96 29 91 6.49 153 6.82 170+190 7.39 26 56+60 6.82 132+105 6.89 198 7.06 25 5.74 92 6.75 141 7.00 201 7.25 28+31 5.98 84 4.96 137+176 6.96 203 21 89 130 6.86 196 7.14 53+33 5.84 101 6.48 163+138 6.83 189 51 6.93 99 6.67 158 7.15 208+195 22 5.96 119 129+178 6.74 207 7.36 45 6.56 83 175 194 7.99 46 8.00 97 6.56 187+182 6.81 205 52 6.34 81 183 6.91 206 6.75 43+49 6.41 87 6.59 128 6.89 209

Table A12. Congener-specific log BAFOC for PCBs in bacteria at Composite 2.

Congener Log Congener Log Congener Log Congener Log BAFOC BAFOC BAFOC BAFOC 1 47+48 85 167 3 65 SSTD 136 185 4+10 44 6.85 110+77 7.91 174 7+9 37 82 177 6 42 151 202+171+156 8+5 41+71 135+144+124+147 173 19 64 7.15 107 157+200 30 Old 40 123+149 204 Old ISTD ISTD 12+13 100 118 6.86 172 18 63 134 197 15+17 7.76 74 7.41 144+131 180 7.87 24+27 70+76 6.87 188 ISTD 193 16+32 66+95 146 191+199 29 7.76 91 8.03 153 6.83 170+190 26 56+60 132+105 198 25 7.53 92 6.95 141 201 28+31 84 137+176 203 21 8.13 89 130 196 53+33 101 163+138 7.06 189 51 7.51 99 158 208+195 22 119 129+178 207 45 83 175 194 46 97 187+182 6.93 205 52 81 183 206 43+49 87 7.68 128 209

Table A13. Congener-specific log KOC for PCBs in particulates at Composite 2.

Congener Log Congener Log Congener Log Congener Log KOC KOC KOC KOC 1 47+48 85 7.19 167 3 65 SSTD 136 6.80 185 7.07 4+10 44 6.56 110+77 7.43 174 7+9 37 7.08 82 177 6.86 6 42 6.81 151 6.95 202+171+156 7.02 8+5 41+71 6.20 135+144+124+147 8.20 173 6.32 19 64 7.22 107 6.65 157+200 6.94 30 Old ISTD 40 123+149 5.87 204 Old ISTD 12+13 100 7.29 118 6.62 172 7.01 18 63 134 6.90 197 6.61 15+17 74 7.42 144+131 6.64 180 7.73 24+27 6.83 70+76 6.98 188 ISTD 193 16+32 7.44 66+95 146 6.91 191+199 29 91 7.49 153 6.60 170+190 26 8.15 56+60 132+105 198 6.83 25 6.22 92 6.56 141 6.69 201 6.62 28+31 7.11 84 137+176 8.72 203 21 89 7.79 130 196 7.45 53+33 101 7.80 163+138 6.77 189 6.88 51 7.19 99 6.12 158 6.23 208+195 22 7.03 119 7.22 129+178 207 45 7.54 83 175 194 46 6.81 97 7.15 187+182 6.45 205 52 6.79 81 6.38 183 6.54 206 43+49 87 7.08 128 7.43 209

Table A14. Congener-specific log BAFOC for PCBs in bacteria at Composite 3.

Congener Log Congener Log Congener Log Congener Log BAFOC BAFOC BAFOC BAFOC 1 47+48 85 167 3 65 SSTD 136 185 4+10 44 110+77 6.57 174 7+9 37 82 177 6 42 151 202+171+156 8+5 41+71 135+144+124+147 173 19 7.84 64 107 157+200 30 Old 40 6.49 123+149 204 Old ISTD ISTD 12+13 100 118 6.74 172 18 63 134 7.56 197 15+17 6.67 74 144+131 180 24+27 70+76 188 ISTD 193 16+32 66+95 146 7.33 191+199 29 91 6.97 153 7.00 170+190 26 56+60 132+105 198 25 92 141 201 28+31 5.92 84 137+176 203 21 89 130 196 53+33 101 163+138 7.03 189 51 99 158 7.54 208+195 22 119 129+178 207 45 83 175 194 46 97 187+182 7.18 205 52 81 183 206 43+49 87 128 209

Table A15. Congener-specific log KOC for PCBs in particulates at Composite 3.

Congener Log Congener Log Congener Log Congener Log KOC KOC KOC KOC 1 47+48 85 167 3 65 SSTD 136 185 4+10 44 110+77 5.35 174 7+9 37 82 177 6 42 151 6.19 202+171+156 8+5 41+71 135+144+124+147 173 19 6.79 64 107 6.02 157+200 30 Old ISTD 40 123+149 204 Old ISTD 12+13 100 118 6.21 172 18 63 134 6.51 197 15+17 5.88 74 5.75 144+131 6.51 180 24+27 70+76 5.69 188 ISTD 193 16+32 5.63 66+95 5.20 146 6.59 191+199 29 91 153 6.54 170+190 26 56+60 5.99 132+105 6.04 198 25 92 6.33 141 6.10 201 28+31 84 137+176 203 21 89 130 6.39 196 53+33 101 163+138 5.95 189 51 6.60 99 5.81 158 208+195 22 5.54 119 6.33 129+178 207 45 83 175 194 46 6.87 97 187+182 6.91 205 52 5.46 81 183 6.69 206 43+49 5.32 87 128 209

a Table A16. Average congener-specific log BAFOC for PCBs in bacteria in all samples .

Congener Log Congener Log Congener Log Congener Log BAFOC BAFOC BAFOC BAFOC 1 47+48 85 167 3 65 SSTD 136 185 4+10 44 110+77 7.06 174 7+9 37 82 177 6 42 151 202+171+156 8+5 41+71 135+144+124+147 173 19 64 107 157+200 30 Old 40 123+149 204 Old ISTD ISTD 12+13 100 118 6.80 172 18 63 134 197 15+17 6.95 74 144+131 180 24+27 70+76 188 ISTD 193 16+32 66+95 146 191+199 29 91 153 6.91 170+190 26 56+60 132+105 198 25 92 141 201 28+31 84 137+176 203 21 89 130 196 53+33 101 163+138 7.02 189 51 99 158 208+195 22 119 129+178 207 45 83 175 194 46 97 187+182 7.01 205 52 81 183 206 43+49 87 128 209 a Averages were only calculated where there was a log BAFOC for any given congener at all three sites.

Table A17. Average congener-specific log KOC for PCBs in particulates in all samples.

Congener Log Congener Log Congener Log Congener Log KOC KOC KOC KOC 1 47+48 85 167 3 65 SSTD 136 185 4+10 44 110+77 6.44 174 7+9 37 82 177 6 42 151 202+171+156 8+5 41+71 135+144+124+147 173 19 64 107 157+200 30 Old ISTD 40 123+149 204 Old ISTD 12+13 100 118 6.47 172 18 63 134 7.01 197 15+17 74 144+131 7.01 180 24+27 70+76 6.25 188 ISTD 193 16+32 66+95 146 6.82 191+199 29 91 153 6.65 170+190 26 56+60 132+105 198 25 92 141 6.60 201 28+31 84 137+176 203 21 89 130 196 53+33 101 163+138 6.52 189 51 6.91 99 6.20 158 208+195 22 6.18 119 129+178 207 45 83 175 194 46 7.23 97 187+182 6.72 205 52 6.20 81 183 206 43+49 87 128 209 a Averages were only calculated where there was a log KOC for any given congener at all three sites.

Table A18. Suspended particulate matter (SPM) in artificial composites. Site Total mg Total volume Total SPM (mL) Composite 1 2.98 2980 1.00 Composite 2 1.15 3000 0.38 Composite 3 1.75 1830 0.94

Table A19. Particulate organic carbon (POC) in artificial composites Site Total µg C Total volume µg C/mL (mL) Composite 1 914 2980 0.31 Composite 2 857.95 3000 0.60 Composite 3 804.65 1830 0.40

Table A20. Dissolved phase field replicate ∑PCB relative percent difference (RPD) LM18 XAD LM18 XAD Dup Average RPD ∑PCB (pg/L) ∑PCB (pg/L) ∑PCB (pg/L) % 86.21 108.35 97.31 23

Table A21. Particulate phase field replicate ∑PCB relative percent difference (RPD) LM18 GF/F LM18 GF/F Dup Average RPD ∑PCB (pg/L) ∑PCB (pg/L) ∑PCB (pg/L) % 9.15 7.34 8.24 22

Table A22. Dissolved phase field replicate PBDE congener concentration, average, standard deviation and relative percent difference (RPD) LM18 XAD LM18 XAD Average Standard RPD % (pg/L) Dup (pg/L) (pg/L) Deviation BDE-47 53.2 61.8 57.5 6.1 15 BDE-66 1.0 1.0 0.98 0.03 5 BDE-100 6.2 7.3 6.78 0.8 16 BDE-99 28.4 35.9 32.1 5.3 23 BDE-154 0.8 1.2 1.02 0.3 42 BDE-153 1.0 1.7 1.38 0.5 53 PBB-153 0 3.0 0.13 0.2 200 ∑PBDE6 90.6 108.9 99.8 13.0 18

Table A23. Particulate phase field replicate PBDE congener concentration, average, standard deviation and relative percent difference (RPD) LM18 GF/F LM18 GF/F Average Standard RPD % (pg/L) Dup (pg/L) (pg/L) Deviation BDE-47 1.9 0.4 1.13 1.1 137 BDE-66 0.1 0.1 0.10 0.02 33 BDE-100 0.5 0.4 0.43 0.03 10 BDE-99 1.7 0 0.86 1.2 200 BDE-154 0.3 0.5 0.43 0.1 39 BDE-153 0.4 0.3 0.36 0.05 21 PBB-153 0 0 0 0 - ∑PBDE6 4.9 1.7 3.31 2.2 96

Table A24. PCB surrogate recoveries in water, particulates, bacteria, procedural blanks and field blanks Sample Name Sample Date PCB 65 PCB 188 % Recovery % Recovery LM63 XAD 7.29.05 98 81 LM18 XAD 7.25.05 98 92 LM18 XAD Dup 7.25.05 107 91 Procedural Blank 5.01.06 106 83 Field Blank GF/F 7.30.05 98 84 Milwaukee GF/F 7.25.05 171 87 Procedural Blank 8.21.06 96 90 LM18 GF/F 7.25.05 92 88 LM18 GF/F Dup 7.25.05 98 101 LM47 GF/F 3 Sets 7.28.05 91 85 Procedural Blank 9.13.06 114 88 Milwaukee XAD 7.25.05 88 90 GB17 XAD 7.30.05 98 95 Procedural Blank 11.13.06 98 93 LM63 GF/F 7.29.05 - 81 LM110 XAD 7.29.05 - 71 LM47 XAD 1st Column 7.29.05 - 70 Chicago GF/F 7.26.05 - 79 Procedural Blank 4.30.07 - 79 LM47 XAD 2nd Column 7.29.05 - 74 LM110 GF/F 7.30.05 - 65 GB17 GF/F 1st & 2nd 7.30.05 - 72 Chicago XAD 7.26.05 - 45 Procedural Blank 5.13.07 - 75 LM63+GB17 7.29.05 85 91 LM110+LM47 7.29.05 98 109 Milw+Chi+LM18 7.25.05 95 109 Procedural Blank 6.26.06 101 95 Average (Standard Deviation) Percent Recovery PCB 65 PCB 188 Samples 101 (22) 84 (15) Procedural Blanks 102 (6) 87 (8)

Table A25. PBDE surrogate recoveries in water, particulates, bacteria, procedural blanks and field blanks Sample Name Sample Date PBDE 71 PBDE 118 % Recovery % Recovery LM63 XAD 7.29.05 149 148 LM18 XAD 7.25.05 120 155 LM18 XAD Dup 7.25.05 134 156 Procedural Blank 5.01.06 121 151 Field Blank GF/F 7.30.05 94 110 Milwaukee GF/F 7.25.05 108 124 Procedural Blank 5.20.06 97 123 LM18 GF/F 7.25.05 93 126 LM18 GF/F Dup 7.25.05 89 141 LM47 GF/F 3 Sets 7.28.05 76 130 Procedural Blank 9.13.06 98 125 Milwaukee XAD 7.25.05 116 131 GB17 XAD 7.30.05 67 84 Procedural Blank 9.20.06 96 102 LM63 GF/F 7.29.05 87 96 LM110 XAD 7.29.05 83 136 LM47 XAD 1st Column 7.29.05 92 159 Chicago GF/F 7.26.05 114 172 Procedural Blank 4.30.07 78 102 LM47 XAD 2nd Column 7.29.05 88 97 LM110 GF/F 7.30.05 107 126 GB17 GF/F 1st & 2nd 7.30.05 90 97 Chicago XAD 7.26.05 74 88 Procedural Blank 5.13.07 88 86 LM63+GB17 7.29.05 128 77 LM110+LM47 7.29.05 124 94 Milw+Chi+LM18 7.25.05 142 145 Procedural Blank 6.26.06 98 96 Average (Standard Deviation) Percent Recovery PBDE 71 PBDE 118 Samples 104 (23) 125 (28) Procedural Blank 96 (14) 115 (23)