RESUMO
Polychlorinated biphenyl (PCB) contamination has historically posed constraints on the recreational and commercial fishing industry in the Great Lakes. Empirical evidence suggests that PCB contamination represents a greater health risk from fish consumption than other legacy contaminants. The present study attempts a rigorous assessment of the spatio-temporal PCB trends in multiple species across the Canadian waters of the Great Lakes. We applied a Bayesian modelling framework, whereby we initially used dynamic linear models to delineate PCB levels and rates of change, while accounting for the role of fish length and lipid content as covariates. We then implemented Bayesian hierarchical modelling to evaluate the temporal PCB trends during the dreissenid pre- and post-invasion periods, as well as the variability among and within the water bodies of the Great Lakes system. Our analysis indicates that Lake Ontario is characterized by the highest PCB levels among nearly all of the fish species examined. Historically contaminated local areas, designated as Areas of Concern, and embayments receiving riverine inputs displayed higher concentrations within each of the water bodies examined. The general temporal trend across the Great Lakes was that the high PCB concentrations during the early 1970s followed a declining trajectory throughout the late 1980s/early 1990s, likely as a result of the reductions in industrial emissions and other management actions. Nonetheless, after the late 1990s/early 2000s, our analysis provided evidence of a decline in the rate at which PCB concentrations in fish were dropping, accompanied by a gradual establishment of species-specific, steady-state concentrations, around which there is considerable year-to-year variability. The overall trends indicate that reduced contaminant emissions have brought about distinct beneficial changes in fish PCB concentrations, but past historical contamination along with other external or internal stressors (e.g., invasive species, climate change) continue to modulate the current levels, thereby posing potential risks to humans through fish consumption.
Assuntos
Bifenilos Policlorados/química , Poluentes Químicos da Água/química , Animais , Teorema de Bayes , Peixes , Great Lakes Region , Humanos , Bifenilos Policlorados/análise , Poluentes Químicos da Água/análiseRESUMO
Polychlorinated biphenyls (PCBs) and total mercury (THg) are two of the most prevalent contaminants, resulting in restrictive advisories on consuming fish from the Laurentian Great Lakes. The goal of this study is to examine the temporal trends of the two contaminants in walleye (Sander vitreus) and lake trout (Salvelinus namaycush) for Lake Ontario. We employed Bayesian inference techniques to parameterize three different strategies of time series analysis: dynamic linear, exponential decay, and mixed-order modeling. Our analysis sheds light on the role of different covariates (length, lipid content) that can potentially hamper the detection of the actual temporal patterns of fish contaminants. Both PCBs and mercury demonstrate decreasing temporal trends in lake trout males and females. Decreasing PCB trends are evident in walleye, but the mean annual mercury levels are characterized by a "wax and wane" pattern, suggesting that specific fish species may not act as bio-indicators for all contaminants. This finding may be attributed to the shifts in energy trophodynamics along with the food web alterations induced from the introduction of non-native species, the intricate nature of the prey-predator interactions, the periodicities of climate factors, and the year-to-year variability of the potentially significant fluxes from atmosphere or sediments. Finally, a meaningful risk assessment exercise will be to elucidate the role of within-lake fish contaminant variability and evaluate the potential bias introduced when drawing inference from pooled datasets.
Assuntos
Mercúrio , Percas , Bifenilos Policlorados , Truta , Poluição Química da Água/estatística & dados numéricos , Animais , Teorema de Bayes , Monitoramento Ambiental , Feminino , Cadeia Alimentar , Lagos , Modelos Lineares , Masculino , Método de Monte Carlo , Ontário , Poluentes Químicos da ÁguaRESUMO
A Unit World approach has been used extensively to rank chemicals for their hazards and to understand differences in chemical behavior. Whereas the fate and effects of an organic chemical in a Unit World Model (UWM) analysis vary systematically according to one variable (fraction of organic carbon), and the chemicals have a singular ranking regardless of environmental characteristics, metals can change their hazard ranking according to freshwater chemistry, notably pH and dissolved organic carbon (DOC). Consequently, developing a UWM approach for metals requires selecting a series of representative freshwater chemistries, based on an understanding of the sensitivity of model results to this chemistry. Here we analyze results from a UWM for metals with the goal of informing the selection of appropriate freshwater chemistries for a UWM. The UWM loosely couples the biotic ligand model (BLM) to a geochemical speciation model (Windermere Humic Adsorption Model [WHAM]) and then to the multi-species fate transport-speciation (Transpec) model. The UWM is applied to estimate the critical load (CL) of cationic metals Cd, Cu, Ni, Pb, and Zn, using three lake chemistries that vary in trophic status, pH, and other parameters. The model results indicated a difference of four orders of magnitude in particle-to-total dissolved partitioning (K(d)) that translated into minimal differences in fate because of the short water residence time used. However, a maximum 300-fold difference was calculated in Cu toxicity among the three chemistries and three aquatic organisms. Critical loads were lowest (greatest hazard) in the oligotrophic water chemistry and highest (least hazard) in the eutrophic water chemistry, despite the highest fraction of free metal ion as a function of total metal occurring in the mesotrophic system, where toxicity was ameliorated by competing cations. Water hardness, DOC, and pH had the greatest influence on CL, because of the influence of these factors on aquatic toxicity.