Retrospective stepwise prioritization of chemicals detected in Great Lakes tributaries (2008-2018).

Abstract

Through the U.S. Great Lakes Restoration Initiative, a 10-year, multiagency chemical monitoring effort was undertaken across the Great Lakes. In this effort, 586 chemicals were monitored and 334 were detected in grab/composite water samples. To help inform potential future actions, a stepwise prioritization framework was used to identify compounds for which publicly accessible water quality guidelines or effects information suggested there was potential aquatic ecotoxicity. Because water quality guidelines were only available for some chemicals, this framework used apical toxicity data collated from publicly accessible databases (e.g., the ECOTOXicology Knowledgebase) and alternative data, including literature-derived non-apical effect concentrations, in vitro bioactivities from high-throughput screening, and modeled ecotoxicity. To account for the diverse levels of confidence in these data, chemicals were prioritized within specific action categories, which suggested potential management or experimental activities that may be considered based on the types of data available for each compound. Overall, 11 detected chemicals were identified as high priority in different action categories. This included four chemicals prioritized for environmental management or targeted risk assessment, three chemicals prioritized for effects-based monitoring, one chemical prioritized for apical effects assessment, and three chemicals targeted for non-apical effects evaluation. This framework also identified 164 low-priority chemicals, among which more than 50% were prioritized based on water quality guidelines or apical effect concentrations (thus could be considered low priority for future risk assessment or management activities). Results aim to help regulatory agencies, environmental managers, and other stakeholders focus available resources on carrying out monitoring, experimental, and risk assessments for the chemicals that display the greatest potential to adversely impact Great Lakes ecosystems.