Polychlorinated biphenyl (PCB) half-lives in humans: A systematic review.

This manuscript presents a systematic review of PCB half-lives reported in the scientific literature. The review was completed in accordance with PRISMA guidelines and included a review of almost 1000 peer-reviewed publications. In total, 26 articles were found to report half-lives in humans, with the majority of data coming from studies performed in North America on individuals suspected to have been exposed to PCBs. Terminology for reporting PCB half-lives was inconsistent, so we have attempted to consolidate this and recommend using either "apparent half-life" or "intrinsic half-life" in future studies. Within the literature, values for reported half-lives varied considerably for different PCBs. Less chlorinated PCBs generally have shorter half-lives than more chlorinated PCBs. It was interesting to note the large variability of half-lives reported for the same PCB. For example, the reported half-life for PCB 180 varied by nearly 3 orders of magnitude (0.34 years-300 years). Our review identified that the half-lives estimated were largely dependent on the studied cohort. We discuss the importance of PCB body burden, degree of chlorination and PCB structure, gender, age, breastfeeding, BMI, and smoking status on half-life estimations. We also identified significantly shorter half-lives for some PCBs in occupationally exposed individuals compared to results reported from the general population. PCB half-lives are not the same for every PCB or every individual. Therefore, careful consideration is needed when these values are used in human exposure studies.

Source apportionment of polychlorinated biphenyls (PCBs) using different receptor models: A case study on sediment from the Portland Harbor Superfund Site (PHSS), Oregon, USA.

Multivariate modelling techniques are used by a wide variety of investigations in environmental chemistry. It is surprisingly rare for studies to show a detailed understanding of uncertainties created by modelling or how uncertainties in chemical analysis impact model outputs. It is common to use untrained multivariate models for receptor modelling. These models produce a slightly different output each time they are run. The fact that a single model can provide different results is rarely acknowledged. In this manuscript, we attempt to address this by investigating differences that can be generated using four different receptor models (NMF, ALS, PMF & PVA) to perform source apportionment of polychlorinated biphenyls (PCBs) in surface sediments from Portland Harbor. Results showed that models generally had a strong agreement and identified the same main signatures that represented commercial PCB mixtures, however, subtle differences were identified by; different models, same models but with a different number of end members (EM), and the same model with the same number of end members. As well as identifying different Aroclor-like signatures, the relative proportion of these sources also varied. Depending on which method is selected it may have a significant impact on conclusions of a scientific report or litigation case and ultimately, allocation on who is responsible for paying for remediation. Therefore, care must be taken to understand these uncertainties to select a method that produces consistent results with end members that can be chemically explained. We also investigated a novel approach to use our multivariate models to identify inadvertent sources of PCBs. By using a residual plot produced from one of our models (NMF) we were able to suggest the presence of approximately 30 different potentially inadvertently produced PCBs which account for 6.6 % of the total PCBs in Portland Harbor sediments.