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Screening for Contaminants of Concern in Surface Water Using an Automated Exposure-Focused Workflow
Citation:
Wall, J., C. Greene, H. Goeden, A. Williams, J. Franzosa, J. Wambaugh, Amar V. Singh, M. Linnenbrink, J. Lambert, AND K. Isaacs. Screening for Contaminants of Concern in Surface Water Using an Automated Exposure-Focused Workflow. Society of Environmental Toxicology and Chemistry (SETAC) Meeting November 2021, Portland (Virtual), Oregon (Virtual), November 14 - 18, 2021. https://doi.org/10.23645/epacomptox.17331743
Impact/Purpose:
Poster presented to the Society of Environmental Toxicology and Chemistry (SETAC) Meeting November 2021 This describes results of a case study for a workflow developed in collaboration with the Minnesota Department of Health (MDH) to automate a chemical exposure screening used for their Contaminants of Emerging Concern (CEC) initiative. The case study provides an example of how the automated workflow can allow MDH scientists to exponentially speed up chemical screening evaluations and expand the number of chemicals assessed, freeing resources to complete the more complex aspects of exposure assessment.
Description:
Characterization of exposure risk for chemicals found in the environment is a task that often exceeds the capacity of government agencies due to the sheer number of chemicals found in the environment. Often, a manual screening process is performed using scientifically sound approaches to prioritize chemicals for further assessment. The Minnesota Department of Health (MDH), under its Contaminants of Emerging Concern (CEC) initiative, uses a standardized process to screen potential contaminants based on exposure potential. Recently, MDH partnered with the U.S. EPA Office of Research and Development (ORD) to accelerate this process via development of an automated workflow to collect and report relevant exposure data, including New Approach Methodologies (NAMs) for exposure from ORD's ExpoCast project and relevant chemical data found on ORD's CompTox Chemicals Dashboard. The workflow pulls from 23 broad data sources, covering five domains: chemical identity and use, properties, emission and disposal, environmental occurrence, and human exposure. The collected data were used to score chemicals on exposure potential and data availability using quantitative algorithms previously developed by MDH (score range of 0-10 for exposure potential; 0-5 for data availability). A validation test, comparing the output to 88 manually screened chemicals, confirmed agreement between the processes in most data domains. Here, the automated workflow was applied to a case study of 1,762 chemicals to identify potential candidates for the CEC program. The case study data was pulled from the U.S. EPA's Multimedia Monitoring Database (MMDB) for all unique chemicals that were detected in surface water samples. The average time for a chemical to complete the workflow (pull relevant data, score, generate report) was approximately five minutes, with the quickest finishing in under two minutes and the longest taking two hours. This is an exponential increase in chemical screening rate compared to the manual process (~1 day to weeks per chemical). Some higher-ranking chemicals (high adjusted exposure score; data availability) included Phenol (6.30; 3.81) and Acetophenone (5.21; 3.79). This case study provides an example of how promising automated workflows can be for accelerating chemical screening and prioritization processes by leveraging existing data structures and NAMs. This abstract does not necessarily reflect U.S. EPA policy.
URLs/Downloads:
DOI: Screening for Contaminants of Concern in Surface Water Using an Automated Exposure-Focused Workflow
SETAC2021_JWALLMDHCECWORKFLOW_20211022 (003)-T.PDF (PDF, NA pp, 2071.574 KB, about PDF)