PCB Congeners and Dechlorination in Sediments of Lake Hartwell, South Carolina, Determined from Cores Collected in 1987 and 1998

Abstract

Four sediment cores were collected from Lake Hartwell, SC, in 1987 and 1998 and analyzed for polychlorinated biphenyl (PCB) congeners. Total PCBs ranged from -0 to 58 microg/ g. Positive matrix factorization (PMF) was applied to the data sets to determine PCB source profiles. Two factors were determined for each data set. One factor resembled the original estimated PCB mixture of 80% Aroclor 1016 and 20% Aroclor 1254 and the other factor was a dechlorinated version of the mixture. Evidence of a dechlorination plateau is apparent from the PMF loading solutions because the dechlorinated congener profiles do not change from 1987 to 1998, butthe contribution to the profile from the dechlorinated factor increases from 73% (1987) to 87% (1998). PMF source contributions and plots of PCB concentration versus congener for individual samples provide evidence of enhanced dechlorination at high concentrations. After source apportionment an anaerobic dechlorination model was applied to the dechlorinated source profiles to quantify possible dechlorination pathways. It was found that dechlorination process M, extended to target biphenyl rings with up to six chlorines, provided the best fit for an individual process, and M + Q provides the best fit for combined processes, although M + LP also provides a similarfit. Process LP targets the higher chlorinated congeners and appears to dechlorinate PCBs in the sediments initially.

Comparison of a new variant of PMF with other receptor modeling methods using artificial and real sediment PCB data sets

“…For example, SR1-4-SR1-8 have concentrations greater than 50 ppm as do SR4-8-SR4-14. This observation is consistent with a laboratory study by Sokol et al (1998) and a field study of Lake Hartwell sediments (Bzdusek et al, 2005b) that found anaerobic PCB dechlorination occurring at the high PCB concentrations and not at the low PCB concentrations.…”

Nationwide PCB congener pattern analysis in freshwater fish samples in France

“…Moreover the negative eigenvectors sometimes obtained in PCA are not appropriate when looking for source profiles. While there are numerous examples of pattern analysis using models adapted from multivariate statistics in environmental matrices such as air (Logue et al, 2009;Pekney et al, 2006), soil (Skrbic and Durisic-Mladenovic, 2007) or bottom sediment (Bzdusek et al, 2006a;Bzdusek et al, 2006b;Du et al, 2008), there have been fewer attempts to develop this kind of approach on biota. Examples include an exploration of spatial differences in organochlorine chemical loads in herring gull colonies of the Great Lakes (MacDonald et al, 1992), a study of PCB accumulation features, but neither spatial nor source pattern analysis in the Baltic Sea area (Falandysz et al, 2002), an attempt to differentiate local PCB sources in the Hudson River and its estuary Monosson et al, 2003), and a study of PCB pattern variations across species, trophic levels, and wild versus farmed salmon (Yunker et al, 2011).…”

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

“…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.…”

“…In the case of the Henry and Christensen data set, we used their results for UNMIX (the method Henry developed and has used extensively: Henry, et al, 1994;Henry, et al, 2003) and PMF (a method Christensen has published on: Bzdusek, et al, 2006). For PVA, Dr. Glenn Johnson (co-investigator on this research) ran the Henry data set using Matlab code that he wrote and has used in many published studies (Johnson, et al, 2000;Magar, et al, 2005).…”