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Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers
Citation:
Loken, L., S. Corsi, D. Alvarez, G. Ankley, A. Baldwin, B. Blackwell, L. DeCicco, M. Nott, S. Oliver, AND D. Villeneuve. Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 42(2):340-366, (2023). https://doi.org/10.1002/etc.5491
Impact/Purpose:
Commitments under Focus Area 1 (Toxic Substances and Areas of Concern), Objective 2 (Increase knowledge about contaminants in Great Lakes fish and wildlife) include the identification of emerging contaminants and assessing their impacts on Great Lakes fish and wildlife. The current research contributes to an interagency effort to address this commitment. Specifically, it reports on monitoring of over 225 pesticides and pesticide breakdown products in 15 Great Lakes tributary streams. Concentrations of the chemicals detected were compared to toxicity benchmarks compiled from traditional animal studies as well as alternative pathway-based testing approaches. Priority contaminants whose concentrations approach or exceed concentrations reported to produce toxicity or biological activity were identified. Notably, this project employed passive sampling technology that allowed for both time-averaged sampling and was capable of detecting compounds that might not be evident in grab samples. Results of this research help inform Region 5, Great Lakes states and tribes, and other stakeholders about contaminants that may warrant further monitoring and study in Great Lakes fish and wildlife as well as helps identify large numbers that do not appear to be a significant threat to Great Lakes ecosystems at their present concentrations.
Description:
To help meet the objectives of the Great Lakes Restoration Initiative with regard to increasing knowledge about toxic substances, 223 pesticides and pesticide transformation products were monitored in 15 Great Lakes tributaries using polar organic chemical integrative samplers. A screening-level assessment of their potential for biological effects was conducted by computing toxicity quotients (TQs) for chemicals with available US Environmental Protection Agency (USEPA) Aquatic Life Benchmark values. In addition, exposure activity ratios (EAR) were calculated using information from the USEPA ToxCast database. Between 16 and 81 chemicals were detected per site, with 97 unique compounds detected overall, for which 64 could be assessed using TQs or EARs. Ten chemicals exceeded TQ or EAR levels of concern at two or more sites. Chemicals exceeding thresholds included seven herbicides (2,4-dichlorophenoxyacetic acid, diuron, metolachlor, acetochlor, atrazine, simazine, and sulfentrazone), a transformation product (deisopropylatrazine), and two insecticides (fipronil and imidacloprid). Watersheds draining agricultural and urban areas had more detections and higher concentrations of pesticides compared with other land uses. Chemical mixtures analysis for ToxCast assays associated with common modes of action defined by gene targets and adverse outcome pathways (AOP) indicated potential activity on biological pathways related to a range of cellular processes, including xenobiotic metabolism, extracellular signaling, endocrine function, and protection against oxidative stress. Use of gene ontology databases and the AOP knowledgebase within the R-package ToxMixtures highlighted the utility of ToxCast data for identifying and evaluating potential biological effects and adverse outcomes of chemicals and mixtures. Results have provided a list of high-priority chemicals for future monitoring and potential biological effects warranting further evaluation in laboratory and field environments.
URLs/Downloads:
DOI: Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10107608/