Evidence for photochemical and microbial debromination of polybrominated diphenyl ether flame...

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1 Evidence for photochemical and microbial debromination of polybrominated 1 diphenyl ether flame retardants in San Francisco Bay sediment 2 3 Lisa A. Rodenburg 1* , Qingyu Meng 2 , Don Yee 3 , and Ben K. Greenfield 3,4 4 1 Department of Environmental Sciences, Rutgers University, 14 College Farm 5 Road, New Brunswick, NJ 08901, USA 6 2 School of Public Health, Rutgers University, Piscataway, New Jersey 08854, United States 7 3 San Francisco Estuary Institute, 4911 Central Avenue, Richmond, CA 94804 8 4 Current affiliation: Environmental Health Sciences Division, School of Public Health, 9 University of California, Berkeley, 50 University Hall #7360, Berkeley, CA 94720-7360 10 *Corresponding author. Phone 732-932-9800 x 6218, Fax 732-932-8644, email 11 [email protected] 12 13

description

ABSTRACTBrominated diphenyl ethers (BDEs) are flame retardant compounds that have been classified as persistent organic pollutants under the Stockholm Convention and targeted for phase-out. Despite their classification as persistent, PBDEs undergo debromination in the environment, via both microbial and photochemical pathways. We examined concentrations of 24 PBDE congeners in 233 sediment samples from San Francisco Bay using Positive Matrix Factorization (PMF). PMF analysis revealed five factors, two of which contained high proportions of congeners with two or three bromines, indicating that they are related to debromination processes. One of the factors included PBDE 15 (4,4’-dibromo diphenyl ether, comprising 20% of the factor); the other included PBDE 7 (2,4-dibromo diphenyl ether; 12%) and PBDE 17 (2,2’,4-tribromo diphenyl ether; 16%). The debromination processes that produce these congeners are probably photochemical debromination and anaerobic microbial debromination, although other processes could also be responsible. Together, these two debromination factors represent about 8% of the mass and 13% of the moles of PBDEs in the data matrix, suggesting that PBDEs undergo measurable degradation in the environment. Key words: photolysis, debromination, monitoring, factor analysis, California, flame retardant

Transcript of Evidence for photochemical and microbial debromination of polybrominated diphenyl ether flame...

Page 1: Evidence for photochemical and microbial debromination of polybrominated diphenyl ether flame retardants in San Francisco Bay sediment

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Evidence for photochemical and microbial debromination of polybrominated 1

diphenyl ether flame retardants in San Francisco Bay sediment 2

3

Lisa A. Rodenburg1*, Qingyu Meng2, Don Yee3, and Ben K. Greenfield3,4 4

1 Department of Environmental Sciences, Rutgers University, 14 College Farm 5

Road, New Brunswick, NJ 08901, USA 6

2School of Public Health, Rutgers University, Piscataway, New Jersey 08854, United States 7

3San Francisco Estuary Institute, 4911 Central Avenue, Richmond, CA 94804 8

4Current affiliation: Environmental Health Sciences Division, School of Public Health, 9

University of California, Berkeley, 50 University Hall #7360, Berkeley, CA 94720-7360 10

*Corresponding author. Phone 732-932-9800 x 6218, Fax 732-932-8644, email 11

[email protected] 12

13

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ABSTRACT 14

Brominated diphenyl ethers (BDEs) are flame retardant compounds that have been classified as 15

persistent organic pollutants under the Stockholm Convention and targeted for phase-out. 16

Despite their classification as persistent, PBDEs undergo debromination in the environment, via 17

both microbial and photochemical pathways. We examined concentrations of 24 PBDE 18

congeners in 233 sediment samples from San Francisco Bay using Positive Matrix Factorization 19

(PMF). PMF analysis revealed five factors, two of which contained high proportions of 20

congeners with two or three bromines, indicating that they are related to debromination 21

processes. One of the factors included PBDE 15 (4,4’-dibromo diphenyl ether, comprising 20% 22

of the factor); the other included PBDE 7 (2,4-dibromo diphenyl ether; 12%) and PBDE 17 23

(2,2’,4-tribromo diphenyl ether; 16%). The debromination processes that produce these 24

congeners are probably photochemical debromination and anaerobic microbial debromination, 25

although other processes could also be responsible. Together, these two debromination factors 26

represent about 8% of the mass and 13% of the moles of PBDEs in the data matrix, suggesting 27

that PBDEs undergo measurable degradation in the environment. 28

29

Key words: photolysis, debromination, monitoring, factor analysis, California, flame retardant 30

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1 INTRODUCTION 32

Brominated diphenyl ethers (BDEs) are flame retardant compounds that have been 33

widely used in consumer products since the 1970s, exhibit elevated concentrations in seafood 34

and indoor dust, and may pose human health hazards at environmentally relevant concentrations 35

(Domingo, 2012). As a result, PBDEs have been classified as persistent organic pollutants 36

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(POPs) under the Stockholm Convention and are targeted for phase-out (United Nations 37

Environment Program, 2009). Despite their classification as persistent, PBDEs undergo 38

debromination via microbial and photochemical pathways that have been studied under 39

laboratory conditions, but as yet there is little understanding of their importance for the 40

environmental fate of PBDEs. 41

The photolysis of PBDEs, studied with multiple light sources and media, exhibits 42

characteristic pathways and breakdown products (Sanchez-Prado et al., 2006; Fang et al., 2008; 43

Sanchez-Prado et al., 2012; Wei et al., 2013 and references therein). Several researchers (Fang 44

et al., 2008; Sanchez-Prado et al., 2012; Wei et al., 2013) have demonstrated that during 45

photolysis, removal of bromines in the ortho position predominates. PBDE 15 (4,4’-46

dibromodiphenyl ether) is a major photolysis product, with PBDE 17 (2,2',4-tribromodiphenyl 47

ether) sometimes reported as a minor product (Sanchez-Prado et al., 2012; Wei et al., 2013). 48

Ahn et al. (2006) studied PBDE photolysis on clays, metal oxides, and sediments and concluded 49

that the photolysis pathways were largely matrix independent. 50

Although the regiospecificity of microbial debromination of PBDEs is more complicated, 51

certain breakdown products are observed. Using a biomimetic system, Tokarz et al. (2008) 52

noted that PBDEs 17 (2,2’,4-tribromo diphenyl ether) and 28 (2,4,4’-tribromo diphenyl ether) 53

were major microbial debromination products of high molecular weight PBDEs in anaerobic 54

sediment. Tokarz et al. (2008) also indicated that although microbial debromination at the ortho 55

positions is possible, removal of the meta and para bromines predominates, especially for heavy 56

congeners. Similarly, Robrock et al. (2008) and Ding et al. (2013) found that debromination of 57

PBDEs by several cultures preferentially removed bromines at the meta and para positions, with 58

formation of PBDE 17 as a major product. La Guardia et al. (2007) observed evidence of 59

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microbial debromination of PBDEs in sewage sludge and near wastewater outfalls. They 60

measured PBDE 17 but could not detect PBDE 15 in sewage sludge. Davis et al. (2012) also 61

detected PBDE 17 in biosolids. In contrast, Lee et al. (2011) studied the debromination of PBDE 62

by a coculture consisting of Dehalococcoides and Desulfovibrio species, and found that 63

debromination at the ortho position is preferred, with significant amounts of PBDE 15 formed. 64

This echoes the regiospecificity of the microbial dechlorination of polychlorinated biphenyls 65

(PCBs): dechlorination at the meta and para positions is preferred, but chlorines at the ortho 66

position can be removed by some strains of bacteria (Bedard, 2003). For the PBDEs, it is not 67

clear which set of pathways predominates in the environment, and indeed different 68

regiospecificity might be observed in different environments. 69

The purpose of this work was to use factor analysis to examine the importance of these 70

debromination processes in the environment. Data collected by the Regional Monitoring 71

Program for Water Quality in the San Francisco Estuary (RMP) were analyzed using Positive 72

Matrix Factorization (PMF) (Paatero and Tapper, 1994). The RMP data set is a good choice for 73

this investigation because it includes measurements of 50 PBDE congeners using high-resolution 74

mass spectrometry in hundreds of sediment samples collected in San Francisco Bay (Oram et al., 75

2008; Klosterhaus et al., 2012). PMF is an advanced factor analysis method, described in detail 76

by Paatero and Tapper (1994). Briefly, PMF defines the sample matrix as product of two 77

unknown factor matrices with a residue matrix: 78

EGFX += (1) 79

The sample matrix (X) includes n observed samples and m chemical species. F is a matrix of p 80

chemical profiles. The G matrix describes the contribution of each factor to any given sample, 81

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while E is the matrix of residuals. The PMF solution (i.e., G and F matrices) is obtained by 82

minimizing the objective function Q through the iterative algorithm: 83

2

1 1

)/(∑∑= =

=n

i

m

jijij seQ (2) 84

Q is the sum of the squares of the difference (i.e., eij) between the observations (X) and the model 85

(GF), weighted by the measurement uncertainties (sij). 86

PMF has several advantages over simpler factor analysis tools such as Principle 87

Components Analysis (PCA). PMF allows only positive correlations, and because the model 88

input includes a point-by-point uncertainty estimate, PMF allows the inclusion of missing or 89

below detection limit data points, which are assigned an arbitrary concentration and then 90

associated with a high uncertainty. PMF and other similar factor analysis methods have been 91

used to investigate the dehalogenation of PBDEs (Zou et al., 2013) as well as other POPs, 92

including polychlorinated biphenyls (PCBs) (Magar et al., 2005; Bzdusek et al., 2006b; 93

Rodenburg et al., 2010) and polychlorinated dibenzo-p-dioxins and polychlorinated 94

dibenzofurans (PCDD/Fs) (Barabas et al., 2004; Rodenburg et al., 2012). Like all factor analysis 95

methods, however, PMF can only isolate the factors that make up the data set. It is up to the user 96

to use her best judgment to understand what these factors mean. 97

2 METHODS 98

2.1 Study site 99

San Francisco Bay (the Bay, Figure 1) is one of the largest urbanized estuaries in the 100

world, with a surrounding population of 7 million people. Bay hydrology is driven primarily by 101

the tidal influence from the Pacific Ocean and the freshwater inflow from the Sacramento and 102

San Joaquin Rivers, which drain an area of about 150,000 km2 (Cloern, 1996), and enter the Bay 103

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at its northern end in Suisun Bay (Figure 1). As a result of freshwater inflow and tidal mixing, 104

the northern Bay (Suisun and San Pablo Bays) is relatively well flushed, whereas South Bay is 105

less well flushed (Conomos, 1979). Treated wastewater discharge is released via 31 permitted 106

outfalls distributed Baywide, totaling a dry weather permitted flow into the Bay of 788 MGD. 107

Concentrations of many pollutants, including PBDEs, are highest in Central Bay, South Bay, and 108

Lower South Bay sediment and tend to decline moving northward towards San Pablo and Suisun 109

Bays (Oros et al., 2005; Davis et al., 2007; Klosterhaus et al., 2012). 110

The Regional Monitoring Program for Water Quality in the San Francisco Estuary (RMP) 111

is an ongoing monitoring partnership established in 1993 between a regulatory agency, over 70 112

local regulated entities, and other local stakeholders (e.g., environmental NGOs), administered 113

by an independent scientific organization (Hoenicke et al., 2003). RMP sediment monitoring 114

employs a stratified design, in which eight probabilistic sites are collected annually from each of 115

five Bay segments following a rotating panel design, with seven additional samples collected 116

from fixed monitoring stations (Lowe et al., 2004). Every sample incorporates two to three 117

homogenized subsamples, each collected by 0.1 m2 Kynar ® coated stainless steel Young-118

modified Van Veen grab. Trace clean techniques are employed, including quadruple rinsing of 119

all equipment between each sampling event (SFEI, 2012). Beginning in 2002, fifty PBDE 120

congeners were measured in the sediment by Axys Analytical Services (British Columbia, 121

Canada) using high resolution gas chromatography/mass spectrometry methods equivalent to 122

EPA method 1614A (EPA, 2007). 123

2.2 Data matrix 124

Of the 50 congeners measured, only 24 were above the detection limit in more than 50% 125

of the 403 sediment samples. These 24 congeners were retained for PMF analysis. Only samples 126

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with fewer than four non-detects were included in analysis. This resulted in 24 congeners 127

measured in 233 samples, with adequate detection limits only occurring in sampling years 2005 128

through 2010. 129

2.3 PMF analysis 130

The data were analyzed using Positive Matrix Factorization (PMF), employing PMF2 131

software (YP-Tekniika KY Co., Helsinki, Finland). 132

PMF computes the error estimate (sij) for each data point (xij) based on the data point and 133

its original error estimate. The present study utilizes the error model (EM) = -14 (Paatero, 2003): 134

),max(),max( ijijijijijijijij yxvyxutS ++= (3) 135

where t is the congener- and sample-specific detection limit, u is the Poisson distribution (here 136

designated as 0), v is the measurement precision, x is the observed data value, and y is the 137

modeled value. The uncertainty matrix was constructed by assigning an uncertainty of 15% to all 138

congeners except those below detection. For values below detection, a value of one-half the 139

detection limit was assigned, and the uncertainty was set to 166% (Brown and Hafner, 2003). 140

Congener and sample-specific detection limits were used to construct the detection limit matrix. 141

142

3 RESULTS AND DISCUSSION 143

In the 233 samples analyzed by PMF, Σ24BDE congener concentrations ranged from 0.16 144

to 54 µg/kg (mean = 4.3 µg/kg; median = 3.3 µg/kg). PBDE 209 was the most abundant 145

congener in 216 of the 233 samples. Congeners with four or fewer bromines comprised between 146

0.3% and 28% of Σ24BDEs (mean = 9.9%; median = 9.5%). These low molecular weight 147

congeners (for example, PBDEs 17 and 28) constitute less than 1% of penta PBDE formulations 148

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and are not detectable in octa and deca formulations (La Guardia et al., 2006). Their abundance 149

in the majority of samples suggests that debromination processes significantly impact PBDE 150

congener patterns in Bay sediments. 151

A matrix of Pearson’s correlation coefficients (Supporting Information Table S1) reveals 152

that PBDE 209 is correlated with PBDEs 206 and 207, indicative of the commercial deca PBDE 153

formulation. PBDEs 47, 99, and 100 are also correlated, indicative of the penta formulation (La 154

Guardia et al., 2006). PBDEs 15 and 17 are uncorrelated, indicating that they arise from 155

different sources, processes, or locations. 156

3.1 Positive Matrix Factorization 157

Determining the correct number of factors is always a central challenge of factor analysis. 158

A weight of evidence approach, described in the Supplemental Information Text, determined that 159

five factors were appropriate; remaining interpretations focus on the five factor solution. 160

3.2 PMF congener patterns 161

Examining congener patterns, factor 5 is dominated by PBDE 209 with smaller 162

contributions from PBDEs 206, 207, and 208 (Figure 2). PBDE 209 is also dominant in factor 2, 163

present but not dominant in factors 3 and 4, and a minor contributor to factor 1. Factors 1 164

through 4 contain tetra- or less- brominated congeners which are not abundant in commercial 165

PBDE formulations; these likely represent debromination products of higher molecular weight 166

PBDE congeners. 167

Based on comparison with the congener patterns of the commercial PBDE formulations 168

(La Guardia et al., 2006), factor 4 represents penta-BDE formulations such as DE-71 and 169

Bromkal 70-5DE, because it is dominated by PBDEs 47, 99, and 100 (Figure 2). However, 170

factor 4 contains higher proportions of PBDEs 17 (1.8% of total Σ24BDEs in the factor) and 28 171

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(2.6%) than would be expected from the technical mixtures, since Bromkal 70-5DE contains less 172

than 0.2% of these congeners. This elevated proportion may indicate either debromination or 173

weathering (for example, preferential transport of lower molecular weight congeners). 174

Factor 5 contains 82% of all of the PBDE 209 mass in the data set and more than 75% of 175

the PBDEs 206, 207, and 208 masses (Figure 2), and thus represents the technical deca mixtures, 176

such as Saytex 102E and Bromkal 82-0DE (La Guardia et al., 2006). Factors 2 and 4 contain 177

moderately high proportions of PBDE 209 (Figure 2), accounting for 14% and 4% of the PBDE 178

209 mass, respectively. Notably absent from the resolved factors is anything resembling the 179

technical octa-BDE mixtures. 180

Factor 2 contains congeners that are not present in any of the commercial PBDE 181

mixtures, including dibromo congeners PBDEs 7 and 8 (Figure 2), and 12% of PBDE 17 (as 182

compared to less than 0.1% within the commercial mixtures), suggesting debromination of heavy 183

congeners. However, the major constituents of this factor are PBDE 47, 99, and 100, which are 184

associated with the commercial penta PBDE mixtures, and PBDE 209. We hypothesize that 185

factor 2 represents the weathered PBDE background in the sediments, with traces of both major 186

commercial formulations (penta and deca) and some evidence of debromination. Weathering is a 187

generic term that encompasses many processes, including debromination as well as physical 188

processes such as mixing, partitioning, and preferential transport. The PMF factor analysis 189

identifies congener patterns that co-vary. This can mean that they are produced from the same 190

location or process, or that they are merely transported together. Thus factor 2 may represent 191

BDE congeners that have been transported together despite the fact that they come from several 192

sources and have undergone debromination as well as preferential transport, both of which may 193

alter the original (source) congener patterns. This might indicate that factor 2 is associated with 194

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an aggregate or secondary source, such as storm water or treated wastewater. Alternatively, it 195

could indicate PBDEs that entered the bay long ago and have had time to undergo a lot of 196

mixing, transport, and degradation. 197

Factors 1 and 3 contain lower molecular weight PBDE congeners that are not present in 198

the commercial PBDE mixtures. Factor 3 represents 5.4% of the mass and 7.8% of the moles of 199

PBDEs in the data set, and contains high proportions of PBDE 17 (16% of Σ24BDEs), PBDE 7 200

(12%) and PBDE 49 (11%) (Figure 2). PBDEs 17 and 49 have been reported as products of 201

microbial debromination of PBDE technical mixtures (Robrock et al., 2008; Tokarz et al., 2008), 202

suggesting that factor 3 indicates microbial debromination. The abundance of PBDE 47 in factor 203

3 is inconclusive, as PBDE 47 is both a major congener in many commercial formulations (La 204

Guardia et al., 2006) and a microbial debromination product (Robrock et al., 2008; Tokarz et al., 205

2008). 206

Factor 1 represents about 3.1% of the mass and 4.9% of the moles of PBDEs in the data 207

set. It contains 20% PBDE 15, which is mostly absent from the other factors (Figure 2), 208

consistent with the lack of correlation between PBDE 15 and 17. Factor 1 also contains PBDEs 209

47, 49, and 66. 210

BDE 15 in Factor 1 has not been reported as a measurable constituent of the commercial 211

formulations, and therefore likely indicates either photochemical or microbial debromination. 212

The case for photolysis rests on the observations of several researchers (Fang et al., 2008; 213

Sanchez-Prado et al., 2012; Wei et al., 2013) who noted PBDE 15 as a major product of 214

photochemical debromination of heavier congeners. PBDEs 47, 49, and 66, present in Factor 1, 215

are all important in the photochemical degradation pathway. Although photolysis is expected to 216

be negligible within surface sediment, it can occur during transport while PBDEs are sorbed to 217

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suspended clay minerals (Ahn et al., 2006), or while in the gas phase or dissolved in water. In 218

the sediments of the Daliao River Estuary, China, PBDE 15 was abundant at concentrations 219

which were not well correlated with other congeners (Zhao et al., 2011). The authors suggested 220

PBDE 15 formation during atmospheric transport, with atmospheric deposition as the main 221

source to surface sediment. The interpretation of factor 1 as photochemical debromination is 222

also supported by its relatively even distribution across the Bay, as described below. 223

It is also possible that factor 1 indicates microbial debromination that occurs with 224

different regiospecificity than in factor 3. This would imply different bacterial populations and/or 225

environmental conditions for each factor. Since PBDE 15 is the major product of this process, 226

ortho debromination would have to be prevalent in this pathway. As noted above, there is no 227

correlation between PBDEs 15 and 17 across the data matrix. If both congeners represent 228

debromination, this lack of association suggests different locations or transport processes. Since 229

microbial debromination is most likely an anaerobic process, this implies that there are two sets 230

of anaerobic zones distributed throughout the Bay, each producing a very different congener 231

pattern. This seems unlikely. If debromination was observed to occur in a few hot spots, this 232

explanation would be more plausible. 233

A third possibility is that factor 1 or 3 (or both) could indicate debromination by aquatic 234

animals (Stapleton et al., 2004), plants (Wang et al., 2012; Huang et al., 2013), or aerobic 235

bacteria (Deng et al., 2011). For many of these processes, the products have not been measured, 236

or at least the regiospecificity has not been reported, so it is unknown whether they could 237

produce PBDE 15, which requires ortho debromination. Like PBDEs, PCBs can also be 238

degraded in fish, plants, and by aerobic bacteria (Buckman et al., 2006; Field and Sierra-Alvarez, 239

2008; Van Aken et al., 2010), sometimes resulting in dramatic changes in congener patterns. To 240

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date, however, none of these altered congener patterns has been observed in sediment (Imamoglu 241

et al., 2004; Bzdusek et al., 2006a; Bzdusek et al., 2006b; Soonthornnonda et al., 2011; Praipipat 242

et al., 2013). The total biomass of aquatic animals and plants is likely to be relatively low, 243

compared to microbes, suggesting that they would have limited impact on PCB and PBDE 244

congener patterns on an ecosystem-wide basis. In contrast, microbial dechlorination of PCBs is 245

known to alter PCB congener patterns in sediment (Bzdusek et al., 2006a; Bzdusek et al., 246

2006b). 247

Based on this evidence, we speculate that the most likely explanation of the PMF2 results 248

is that factor 1 indicates photochemical debromination, and factor 3 indicates debromination by 249

anaerobic bacteria, which either occurs in the sediments themselves or in sewers or other 250

environments, with the products transported into and mixed throughout the Bay. Additional 251

evidence is needed to confirm this conjecture, however. Factor analysis alone cannot 252

definitively distinguish between photochemical and microbial debromination because both 253

processes can produce BDEs 15 and 17. 254

3.3 Spatial distribution of factors 255

Factor 1 (photolysis or ortho debromination) concentrations ranged from below detection 256

limits (ND) to 0.61 ng/g (figure 3 panel 1A). The relative contribution of factor 1 to the total 257

(figure 3 panel 1B) was higher for the less urbanized northern Bay segments (San Pablo Bay and 258

Suisun Bay; average 9% contribution to total) than southern Bay segments (Lower South, South, 259

and Central Bays; averaging 2 to 3% contribution to total). This distribution is consistent with 260

the hypothesis that factor 1 results from photolysis in the gas phase and subsequent atmospheric 261

deposition. Specifically, the mass of photodebrominated PBDEs contributed from atmospheric 262

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deposition would be similar across the Bay, but the relative contribution would be reduced by 263

greater inputs of PBDEs in the southern Bay. 264

Factor 2 exhibited variable concentrations ranging from ND to 4.2 ng/g (Figure 3 panel 265

2A). The fractional contribution of factor 2 was greatest in San Pablo Bay and Central Bay 266

(Figure 3 panel 2B), consistent with our hypothesis that this factor represents a weathered PBDE 267

background. Specifically, the largest PBDE sources likely occur in the South Bay region, with 268

increased mixing and weathering with transport and dispersion away from original sources. 269

Factor 3 (microbial debromination) maximum concentrations were 1.1 ng/g (21% of the 270

total PBDE mass; Figure 3 panels 3A and 3B). The highest fraction of factor 3 was generally 271

seen in South Bay and the lowest fraction in San Pablo Bay. South Bay receives a high 272

proportion of stormwater and treated sewage outfalls, mostly via Lower South Bay, whereas the 273

majority of inflow to San Pablo Bay originates from riverine input (Sacramento and San Joaquin 274

Rivers, via Suisun Bay, and to a lesser extent Napa and Petaluma Rivers). The sewage outfall 275

inputs and lower flushing rates may increase sediment anoxia in the South Bay (Cloern, 1996), 276

potentially promoting microbial dehalogenation. Elevated factor 3 concentrations were not 277

observed in Lower South Bay (where the major outfalls are located), suggesting that 278

debromination prior to discharge within the sewers draining into Lower South Bay may not be a 279

major contributor to microbial debromination products. 280

Concentrations of factor 4 ranged up to 3.8 ng/g and 76% of the Σ24BDEs (Figure 3 panel 281

4A). Concentrations displayed no obvious spatial trend in the Bay, in keeping with the 282

ubiquitous sources of fresh penta-BDE throughout the urban area. However, the fraction of total 283

PBDEs contributed by factor 4 generally increased moving northward from Lower South Bay 284

through Suisun Bay and the Rivers (Figure 3 panel 4B). 285

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Factor 5 (deca-BDE) concentrations ranged up to 12.4 ng/g (Figure 3 panel 5A). Factor 5 286

was the predominant factor in 138 of the 233 samples, and was most abundant in the Lower 287

South Bay (Figure 3 panel 5B). This distribution was opposite that determined by loading 288

estimates. Oram et al. (2008) considered loads of PBDEs 47 and 209 from the Sacramento-San 289

Joaquin Delta, local tributaries, municipal wastewater, and atmospheric deposition. Oram et al. 290

suggested that PBDE 47 (generally corresponding to factor 4) loads were dominated by 291

wastewater, while PBDE 209 (corresponding to factor 5) loads were dominated by runoff from 292

the Sacramento and San Joaquin Rivers. There are several possible reasons for the discrepancy 293

between the PMF results and the mass budget of Oram et al. First, Oram et al. did not consider 294

some PBDE sources that might be significant, including storm water runoff. More importantly, 295

the PMF analysis considered the PBDE concentrations prevailing in the sediment during 2005-296

2010. These are likely to reflect decades of inputs, while the mass budget considered inputs over 297

only a limited time period (water years 2005 and 2006). Changes in the use patterns of the 298

various technical PBDE formulations and/or greater persistence of some PBDE congeners could 299

account for some of the discrepancy. The rates of degradation of PBDEs in the environment are 300

not well known. Oram et al. assumed that the degradation rates for PBDEs 47 and 209 were the 301

same, with half-lives of 150 days in water and 578 days in sediment. The PMF results indicate 302

that for PBDEs that have presumably resided in the sediment for several years, only about 13% 303

of the detected moles of BDEs are products of debromination, and much of that debromination 304

may have happened in the atmosphere. Thus the PMF results suggest that the half-lives invoked 305

by Oram et al. are either too fast, or that the products of these degradation processes were not 306

measured in the data set used for PMF analysis (i.e. either degradation processes other than 307

debromination, or complete debromination to diphenyl ether). 308

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3.4 Debromination and its implications 309

This analysis suggests that congener patterns indicative of debromination of PBDEs are 310

apparent in San Francisco Bay. It is not certain where or how the debromination occurred. It 311

may be the result of photolysis occurring in the gas, dissolved, or suspended sediment phases, 312

microbial debromination under anaerobic conditions, or even debromination by other biota. 313

Debromination products are associated with factors representing 8% of the mass and 13% of the 314

moles of PBDEs in the data matrix, suggesting that PBDEs undergo measurable degradation in 315

the environment. Also, the dibromo congeners PBDE 7, 8, 12, and 15 were detected as 316

debromination products, indicating that debromination has proceeded to an advanced stage. 317

Several other researchers have observed evidence of PBDE debromination in sediments 318

and other environmental compartments. La Guardia et al. (2007) reported PBDEs debromination 319

in sewage sludge and near sewage outfalls. Wei et al. (2012) reported debromination in 320

sediments from Arkansas, but identified the products only by homologue. Salvado et al. (2012) 321

noted decreasing sediment PBDE 209 concentrations and increasing lower molecular weight 322

PBDEs with distance from the probable site of release (Gulf of Lion, Mediterranean Sea). Zhao 323

et al. (2011) found that congeners that were believed to come from photolysis were the most 324

abundant congeners in the sediments of the Daliao River Estuary, China. 325

In a study similar to the present investigation, Zou et al. (2013) used PMF combined with 326

eigenspace projection to investigate PBDE congener patterns in sediments cores from the Great 327

Lakes. Using a data matrix of 10 congeners in 93 samples, they resolved five factors, thought to 328

represent the commercial penta, octa, and deca formulations, and two factors thought to represent 329

debromination products. The first of these was characterized by large contributions from PBDEs 330

66 and 85, while the other was characterized by a high proportion of PBDE 28. Unlike the 331

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present work, their study did not include congeners 7, 8, 12, 15, and 17, so it is difficult to 332

compare their factors with those resolved in the present study. Nevertheless, it is noteworthy 333

that two studies, one in a freshwater system and one in an estuary, identified two distinct 334

debromination signals in sediment. In the future, we recommend that PBDEs 7, 15, and 17 be 335

routinely monitored, since they appear to be markers for debromination processes. The present 336

analysis did not find an octa signal in San Francisco Bay. PBDE 183, the major congener in the 337

octa formulation, was not included in the data matrix because it was below detection in a 338

majority of samples. However, the maximum contribution of PBDE 183 to the sum of PBDEs 339

was 10%. PBDE 183 comprised more than 2% of the sum of PBDEs in only 11 of 344 samples. 340

In addition, the data matrix did include PBDEs 153, 154, and 155, which are prominent in the 341

octa formulation, yet PMF analysis did not resolve an octa factor. Thus we conclude that the 342

octa formulation is not a major source of PBDEs to San Francisco Bay, possibly due to lower 343

production of octa relative to penta and deca BDE formulations in the Americas (Birnbaum and 344

Staskal, 2004). Also, both the octa and penta BDE formulations have undergone a gradual 345

production bad in California, which was approved in 2003 and fully implemented in 2008. 346

Anaerobic microbial debromination, which we speculate is associated with Factor 3, may 347

have occurred in Bay sediments. Such a process has been shown to debrominate octa mixtures in 348

laboratory microcosms (Lee and He, 2010). It is instructive to consider the similar process of 349

bacterial dechlorination, since in both cases, anaerobic bacteria use the halogenated compound as 350

an electron acceptor. Bacteria capable of dechlorination have been isolated from Bay sediments 351

(Sun et al., 2000; He et al., 2006). Although some researchers have suggested that the threshold 352

concentration for PCB dechlorination is around 40 ppm (Cho et al., 2003), well above the 353

maximum of about 50 ppb reached in Bay sediments, others have shown evidence of PCB 354

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17

dechlorination with an enriched culture under substrate concentrations as low as 1 to 5 ppm 355

(Royal et al., 2003; Krumins et al., 2009; Payne et al., 2011). It is also possible that the threshold 356

concentration for PBDE debromination is lower than the threshold for PCBs. Previous studies 357

indicate microbial dechlorination in sewers (Rodenburg et al., 2010; Rodenburg et al., 2012), 358

raising the possibility of microbial debromination in San Francisco Bay area sewers, with 359

debromination products emitted to the Bay via stormwater or treated wastewater outfalls. As 360

noted above, several researchers have seen evidence of PBDE debromination in sewage sludge 361

and near sewage outfalls (La Guardia et al., 2007; Davis et al., 2012). The location of 362

degradation is important. If microbial debromination occurs in Bay sediments, then PBDEs will 363

be less persistent in the long run and will have less tendency to accumulate in sediments. In 364

contrast, if microbial debromination occurs primarily in sewers (i.e., prior to discharge), then 365

both the parent compounds and the debromination products would accumulate in sediments and 366

become problematic in the long term. Based on the increased percent contribution of factor 3 367

from Lower South Bay to South Bay, we hypothesize that the majority of microbial 368

debromination occurs in Bay sediments. Examination of congener ratios in wastewater and 369

treatment plant sludge would aid in confirming this. 370

Regardless of the location of dehalogenation, the results indicate that PBDEs undergo 371

measurable debromination in the environment. We cannot rule out the possibility that 372

debromination leads to the fully debrominated diphenyl ether or to bromophenols (Bendig and 373

Vetter, 2013), which were not measured in this data set. Thus our estimate that about 13% of the 374

moles of PBDEs in the Bay have undergone debromination is a lower bound. This is a relatively 375

large degree of transformation. By comparison, POPs such as PCBs and PCDD/Fs show no 376

evidence of degradation in most aquatic systems. Rodenburg et al. (2010) demonstrate that as 377

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much as 19% of the PCBs emitted by permitted dischargers in the Delaware River, USA, basin 378

were subject to dehalogenation, but the dechlorination products (primarily PCBs 4 and 19) are 379

barely detectable in Delaware River sediments (Praipipat et al., 2013). These lower chlorinated 380

congeners may be prevented from accumulating in sediments in part due to volatilization, 381

aerobic degradation, or dissolution and advective export. PCBs 4 and 19 have lower octanol-382

water partition coefficients (log Kow = 4.84 for PCB 4 and 5.16 for PCB 19) (Hansen et al., 1999) 383

than PBDE 17 (ranging 5.4 to 6.6) or PBDE 15 (reported at 5.48) (Wania and Dugani, 2003). 384

Thus, dehalogenated PBDE congeners are more likely to accumulate in sediments than the more 385

hydrophilic dehalogenated PCB congeners. The relative toxicity of PBDEs 7, 15, and 17 vs. 386

parent compounds is poorly characterized. If the debromination products have equal or greater 387

toxicity, this would be compounded by the greater environmental mobility and potential 388

exposure to aquatic life associated with lower hydrophobicities (Arnot and Gobas, 2003). For 389

example, PBDE 47 has a greater biota-sediment accumulation factor (BSAF) than PBDE 209 (La 390

Guardia et al., 2012), so debromination of PBDE 209 to PBDE 47 will result in greater 391

bioaccumulation of PBDEs in some organisms. This work has demonstrated that debromination 392

is an important process affecting the fate of PBDE formulations, and that the debromination 393

products accumulate in sediments. Further research is needed to determine the toxic impacts of 394

the debromination products. 395

396

6 ACKNOWLEDGMENTS 397

Sediment PBDE collection and analysis was performed by Applied Marine Sciences, SFEI, the 398

East Bay Municipal Utility District, and Axys Analytical Services, and supported by the 399

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Regional Monitoring Program for Water Quality in the San Francisco Estuary. BG is supported 400

by a USEPA STAR Fellowship. 401

402

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Figure 1. Map of the San Francisco Bay showing municipal wastewater outfalls.

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Factor 1 (Microbial or

photochemical debromination)

Factor 2 (PBDE

background)

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debromination)Factor 4

(Penta-BDE)

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!( Fraction of total

!( 0.00 - 0.05!( 0.06 - 0.10!( 0.11 - 0.20!( 0.21 - 0.40!( 0.41 - 0.60!( 0.61 - 0.80!( 0.81 - 1.00

Factor 5 (Deca-BDE)

Fraction of total Conc. (ng/g)

Conc. (ng/g)

Conc. (ng/g)

Conc. (ng/g)

Conc. (ng/g)

Fraction of total

Fraction of total

Fraction of total

Fraction of total

Suisun BaySan Pablo Bay

South Bay

Lower South

Bay

2A 2B1A 1B

3A 3B 4A 4B

5A 5B

Page 27: Evidence for photochemical and microbial debromination of polybrominated diphenyl ether flame retardants in San Francisco Bay sediment

Photolytic and microbial debromination of brominated diphenyl ether flame retardants in San

Francisco Bay sediment

Lisa A. Rodenburg1*, Qiyun Meng2, Don Yee3, and Ben K. Greenfield3,4

1 Department of Environmental Sciences, Rutgers University, 14 College Farm

Road, New Brunswick, NJ 08901, USA

2School of Public Health, Rutgers Biomedical and Health Sciences, Piscataway, New Jersey 08854, United

States

3San Francisco Estuary Institute, 4911 Central Avenue, Richmond, CA 94804

4Current affiliation: Environmental Health Sciences Division, School of Public Health, University of

California, Berkeley, 50 University Hall #7360, Berkeley, CA 94720-7360

*Corresponding author. Phone 732-932-9800 x 6218, Fax 732-932-8644, email

[email protected]

Supplemental Information 1 Table Supplemental Text: Determination of the correct number of factors 1 Figure

Page 28: Evidence for photochemical and microbial debromination of polybrominated diphenyl ether flame retardants in San Francisco Bay sediment

Table S-1. Pearson’s correlation coefficients (r) between the 24 congeners included in the data matrix for PMF analysis.

Determination of the correct number of factors

The number of factors was determined by a weight of evidence approach based on several criteria. First, the relative standard deviation of nine runs of the G matrix using different seed values increased from 1.1% when five factors were requested to 56% when six factors were requested. This is an indication that the PMF2 software cannot find a reproducible (stable) solution when six factors are requested. To determine whether rotation of the five factor solution was necessary, the F peak value was adjusted from -0.3 to 0.3 in 0.1 increments. The resulting Q values changed by less than 0.1%. An F peak value of 0.1 yielded the lowest Q value, but the factors were nearly identical to those generated when F Peak = 0 and the change in the Q value was negligible: Q equaled 3378.40 at F Peak = 0 and 3378.29 when F Peak = 0.1. Furthermore, G-space plots indicated that the five factors were independent of each other (Figure S-1). Thus rotation of the factors was not necessary. In contrast, two of the factors derived when six factors were requested were not independent of each other, as indicated by G-space plots.

This solution provided a good fit to 17 of the 24 congeners, based on an R2 value for the measured versus modeled concentrations of 0.7 or greater, with no more than one outlier discarded per congener. The congeners that were not well described by the five-factor solution were BDE 12 (R2 = 0.57), BDE 35 (0.41), BDE 37 (0.43), BDE 71 (0.44), BDE 85 (0.56), BDE 155 (0.49), and BDE 208 (0.69). BDEs 12, 35, 37, 71, and 155 were below detection limits in between 25 and 59 samples, partially explaining the discrepancy between the measured and modeled concentrations. None of these congeners was crucial to the interpretation of the factors.

BDE 007

BDE 008

BDE 012

BDE 015

BDE 017

BDE 028

BDE 035

BDE 037

BDE 047

BDE 049

BDE 051

BDE 066

BDE 071

BDE 085

BDE 099

BDE 100

BDE 153

BDE 154

BDE 155

BDE 203

BDE 206

BDE 207

BDE 208

BDE 209

BDE 007 0.81 0.33 0.01 0.72 0.55 0.48 0.24 0.52 0.65 0.73 0.51 0.17 0.30 0.45 0.42 0.32 0.57 0.56 0.12 0.37 0.39 0.36 0.19BDE 008 0.60 0.08 0.76 0.59 0.53 0.27 0.44 0.81 0.78 0.51 0.11 0.31 0.34 0.27 0.27 0.45 0.50 0.20 0.48 0.49 0.43 0.26BDE 012 0.37 0.31 0.36 0.44 0.27 0.22 0.53 0.62 0.33 0.01 0.22 0.06 0.22 0.15 0.25 0.28 0.29 0.18 0.19 0.12 0.08BDE 015 0.02 0.36 0.00 0.28 0.19 0.19 0.27 0.35 0.05 0.16 0.04 0.30 0.02 0.17 0.04 0.06 0.08 0.09 0.08 0.03BDE 017 0.78 0.75 0.38 0.68 0.84 0.64 0.64 0.15 0.26 0.48 0.48 0.38 0.63 0.71 0.17 0.54 0.55 0.44 0.34BDE 028 0.61 0.60 0.78 0.79 0.65 0.82 0.14 0.33 0.49 0.64 0.37 0.66 0.68 0.15 0.43 0.43 0.39 0.26BDE 035 0.42 0.65 0.59 0.52 0.50 0.06 0.25 0.36 0.52 0.33 0.61 0.75 0.18 0.55 0.53 0.47 0.49BDE 037 0.56 0.44 0.49 0.73 0.34 0.36 0.32 0.52 0.45 0.49 0.64 0.40 0.25 0.33 0.33 0.11BDE 047 0.68 0.67 0.83 0.20 0.57 0.81 0.92 0.54 0.89 0.73 0.13 0.36 0.39 0.40 0.18BDE 049 0.81 0.80 0.19 0.41 0.52 0.51 0.39 0.64 0.63 0.19 0.48 0.50 0.46 0.25BDE 051 0.72 0.20 0.44 0.49 0.60 0.34 0.63 0.57 0.14 0.28 0.31 0.32 0.12BDE 066 0.22 0.56 0.64 0.76 0.50 0.79 0.70 0.19 0.40 0.46 0.44 0.19BDE 071 0.12 0.21 0.18 0.11 0.20 0.17 0.02 0.10 0.10 0.10 0.08BDE 085 0.83 0.68 0.54 0.76 0.47 0.12 0.22 0.26 0.27 0.08BDE 099 0.81 0.61 0.87 0.56 0.10 0.29 0.33 0.32 0.13BDE 100 0.54 0.93 0.67 0.06 0.20 0.23 0.23 0.08BDE 153 0.65 0.70 0.83 0.34 0.56 0.33 0.18BDE 154 0.78 0.18 0.35 0.42 0.40 0.16BDE 155 0.62 0.46 0.58 0.59 0.22BDE 203 0.38 0.62 0.38 0.35BDE 206 0.92 0.74 0.87BDE 207 0.82 0.73BDE 208 0.40BDE 209

Page 29: Evidence for photochemical and microbial debromination of polybrominated diphenyl ether flame retardants in San Francisco Bay sediment

Figure S-1. G-space plots for the five resolved factors