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Examining site intervention efficacy and uncertainties with conceptual Bayesian networks: preventing offsite migration of DNAPL and contaminated groundwater

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Abstract

For contaminated sites, conceptual site models (CSMs) guide the assessment and management of risks, including remediation strategies. Recent research has expanded diagrammatic CSMs with structural causal modeling to develop what are nominally called conceptual Bayesian networks (CBNs) for environmental risk assessment. These CBNs may also be useful for problems of controlling and preventing offsite contaminant migration, especially for sites containing dense nonaqueous phase liquids (DNAPLs). In particular, the CBNs provide greater clarity on the causal relationships between source term, onsite and offsite migration, and remediation effectiveness characterization for contaminated DNAPL sites compared to traditional CSMs. These ideas are demonstrated by the inclusion of modifying variables, causal pathway analysis, and interventions in CBNs. Additionally, several new extensions of the CBN concept are explored including the representation of measurement variables as lines of evidence and alignment with conventional pictorial CSMs for groundwater modeling. Taken as a whole, the CBNs provide a powerful and adaptable knowledge representation tool for remediating subsurface systems contaminated by DNAPL.

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Acknowledgements

Thank you to Katherine Loizos for graphics support and for develo** the pictorial conceptual site model. We also thank Randy Parker and Brian Dyson for providing helpful comments on earlier drafts of the manuscript. The views expressed in this article are those of the author(s) and do not necessarily represent the views or the policies of the U.S. Environmental Protection Agency. Any mention of trade names, manufacturers, or products does not imply an endorsement by the United States Government or the U.S. Environmental Protection Agency. EPA and its employees do not endorse any commercial products, services, or enterprises.

Funding

The authors were supported by the U.S. Environmental Protection Agency during the course of this research.

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Authors and Affiliations

  1. Office of Research and Development, Center for Environmental Solutions and Emergency Response, Land Remediation and Technology Division, US Environmental Protection Agency, Cincinnati, OH, USA

    John F. Carriger, Carolyn Acheson & Ronald Herrmann

  2. Office of Research and Development, Center for Environmental Solutions and Emergency Response, Groundwater Characterization and Remediation Division, US Environmental Protection Agency, Ada, OK, USA

    Michael C. Brooks & Lee Rhea

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Contributions

Conceptualization: MB, JC. Methodology: CA, MB, JC, RH, LR. Writing—original draft: JC. Writing—review and editing: CA, MB, JC, RH, LR. Visualization: CA, MB, JC, RH, LR. All authors read and approved the final manuscript.

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Correspondence to John F. Carriger.

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Carolyn Acheson is retired.

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Carriger, J.F., Brooks, M.C., Acheson, C. et al. Examining site intervention efficacy and uncertainties with conceptual Bayesian networks: preventing offsite migration of DNAPL and contaminated groundwater. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-34340-4

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