Long-Term Recovery of PCB-Contaminated Sediments at the Lake Hartwell Superfund Site:  PCB Dechlorination. 1. End-Member Characterization

Abstract

Under anaerobic conditions, such as those typically found in buried sediments, the primary metabolic pathway for polychlorinated biphenyls (PCBs) is reductive dechlorination in which chlorine removal and substitution with hydrogen by bacteria result in a reduced organic compound with fewer chlorines. Vertical sediment cores were collected from Lake Hartwell (Pickens County, SC) and analyzed in 5-cm intervals for 107 PCB congeners in a total of more than 280 samples from 18 sediment cores and surface samples. This paper reports on extensive PCB dechlorination measured in Lake Hartwell sediments and the characterization of dechlorination end-member (EM) patterns using chemical forensic methods. PCB congener fingerprinting and a multivariate receptor modeling method, polytopic vector analysis (PVA), were used for identification and characterization of weathered and dechlorinated PCB congener patterns. Dechlorination resulted in a substantial shift in buried sediments from tetra- through decachlorobiphenyl congeners to mono- through trichlorobiphenyl congeners. Mono- through trichlorobiphenyls comprised approximately 80% of the PCBs in buried sediments that underwent maximum dechlorination as compared to approximately 20% in surface sediments. The major concentration decreases were seen in the tetra- through hexachlorobiphenyl homologues, which accounted for over 90% of the dechlorination. Octa- through decachlorobiphenyl congeners also were dechlorinated, but their overall contribution to dechlorination was relatively small due to their low initial concentrations (< 5%). The net accumulation of 2-CB, 2,2'/2,6-DCBs, 2,4'-DCB, 2,2',4-TCB, and 2,2',6-TCB at Lake Hartwell matched characteristic PCB dechlorination products reported in the literature, such as those for Processes M, Q, and C; and the persistence of tetrachlorobiphenyls (TeCBs) that contained 24- and 25-congener groups resembled dechlorination Processes H or H'. Although dechlorination tended to be very extensive in most of the cores, it was not always consistent from core to core or at various depth intervals within a single core. The reason for this variability in dechlorination extent could not be determined from the existing data and did not appear to correlate with such factors as PCB concentration, total organic carbon, or age. The authors used fingerprinting analysis and a PVA multivariate receptor model as exploratory data analysis tools to characterize PCB sources and their alteration patterns. Dominant sources and alteration patterns were determined in this large data set by comparing PVA EM patterns with known source patterns (i.e., Aroclors or Aroclor mixtures) and literature-reported alteration patterns. PVA also afforded an opportunity to characterize the vertical and lateral distributions of the weathered and unweathered PCB source patterns and dechlorination patterns, a task that would have been much more difficult to accomplish through comparison of chromatograms alone.

Evaluation of Comprehensive 2D Gas Chromatography-Time-of-Flight Mass Spectrometry for 209 Chlorinated Biphenyl Congeners in Two Chromatographic Runs

“…Because we have examined all PCB congeners, this study has included all those that were found to be ubiquitous, toxic, or potentially toxic. This study considered all congeners that would result from all possible routes: intentional, or incidental, chlorinated biphenyl syntheses, for example, coupling reactions, and as byproducts, and environmental alteration products by selective vaporization or absorption, and reductive dechlorination during metabolism, photochemical reaction, combustion, and chemical remediation [44][45][46][47]. Rather than relying on the common method of total or combined PCB quantification, or the electron capture detector (for high sensitivity), this study employed technology that provided excellent separation of 196 PCB congeners that were either present in or absent from Aroclor formulations.…”

Integrated Forensics Approach to Fingerprint PCB Sources in Sediments using Rapid Sediment Characterization (RSC) and Advanced Chemical Fingerprinting (ACF)

“…RSC can suggest "where" potential sources are located by following concentration gradients while ACF can confirm "what" potential source fingerprints are present. As described in previous PCB forensic studies (Johnson et al, 2000;Magar et al,2005), both source fingerprints as well as weathering patterns (due to differences in solubility, dechlorination, etc.) can often be discerned using these statistical analyses.…”

“…PCBs also behave quite differently in the environment and many factors need to be considered in addition to the most common weathering factors; interpretation methods need to be modified and new data interpretation and analysis considerations need to be developed (Johnson et al, 2006). Emerging PCB fingerprinting techniques have successfully been applied at a few sites in the US (Johnson et al, 2000;Emsbo-Mattingly and Durell, 2003;Magar et al, 2005;Johnson et al, 2007), but there is a need to more fully develop, demonstrate, and validate the utility of fingerprinting PCB contamination. Additional discussions and comparisons for some analytical techniques (both RSC and ACF) are presented in Section 8, and comparisons for some statistical interpretation techniques (receptor models) are shown in Section 6.…”

“…Multivariate receptor models have been used increasingly for the characterization of sources and alteration patterns of chlorinated organic compounds in sediments of complex environmental settings (Jarman, et al, 1997;Johnson, et al, 2000;Barabas, et. al., 2004;Imomoglu, et al, 2002;Magar, et al, 2005;Bzdusek, et al, 2006). A review of these methods, with a focus on PCB forensic application, is provided by Johnson et al, 2007.…”

“…literature reported dechlorination methods - Bedard and Quensen, 1995). We discuss PVA in this effort, because it is a method known well by the authors, and has been applied extensively in PCB forensics applications (Jarman, et al, 1997;Johnson, et al, 2000;Magar, et al, 2005;Johnson, et al, 2007). We also have access to other receptor modeling methods (ALS, PMF, UNMIX -see discussion of their applications in Johnson, et al, 2007) and we ran comparative analyses using all these methods for a performance assessment test in Section 6.…”