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Assessing Contaminants of Emerging Concern in the Great Lakes Ecosystem: A Decade of Method Development and Practical Application
Citation:
Ankley, G., S. Corsi, C. Custer, D. Ekman, S. Hummel, K. Kimbrough, H. Schoenfuss, AND D. Villeneuve. Assessing Contaminants of Emerging Concern in the Great Lakes Ecosystem: A Decade of Method Development and Practical Application. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 42(12):2506-2518, (2023). https://doi.org/10.1002/etc.5740
Impact/Purpose:
Evaluating potential effects of complex mixtures of contaminants long has been one of the greatest challenges facing ecological risk assessors. Although environmental chemists have made stunning advances in detecting ever larger numbers of chemicals in the environment this hasn’t necessarily reduced risk assessment uncertainties. There still is no guarantee that all chemicals of biological significance are measured, and there often are insufficient data to estimate the biological effects of chemicals that are detected. Consequently, it is difficult to establish chemical(s) of greatest potential concern. Further, understanding interactions of chemical mixtures in terms of producing effects remains an inexact science. A critical avenue to addressing these various challenges has been integration of biological effects-based measures (or predictions) with chemical monitoring. Over the past decade there have been notable advances in methods, models, and curated knowledgebases that can be applied to effects-based analysis of complex environmental mixtures. This paper describes a 10+ year multi-agency effort supported through the Great Lakes Restoration Initiative focused on development and practical application of an array of effects-based assessment approaches used in conjunction with extensive chemical monitoring data to provide insights as to the occurrence and management of contaminants of emerging concern in the Great Lakes.
Description:
Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management.
URLs/Downloads:
DOI: Assessing Contaminants of Emerging Concern in the Great Lakes Ecosystem: A Decade of Method Development and Practical Application
https://pubmed.ncbi.nlm.nih.gov/37642300/