A Multi-criteria Geographic Information System Screening Approach for Prioritizing Response Activities Following a Chemical, Biological, or Radiological Incident
Citation:
Blue, J., S. Arden, S. Ratick, M. Rodgers, E. Wexler, E. Rebour, T. Boe, AND W. Calfee. A Multi-criteria Geographic Information System Screening Approach for Prioritizing Response Activities Following a Chemical, Biological, or Radiological Incident. 2023 EPA International Decontamination Research and Development Conference, Charleston, SC, December 05 - 07, 2023.
Impact/Purpose:
The objectives of this project were to identify and process available data sets toinform prioritizing response activities, develop and implement a method to aggregateand analyze disparate data sets, create a tool to conduct analyses to informdecisions, and provide transparent results. PRESTO is a screening tool and provides a flexible, adaptable framework for aggregating large quantities of relevant, often disparate, data. It relies on the availability of relevant input data, so its utility is maximized when data are well-populated for an area of interest. PRESTO results are transparent, accessible, and provided in tabular and graphical formats.
Description:
This presentation describes the development of a decision support tool, the Priority Response Environmental Screening Tool (PRESTO), that was designed to provide a framework for analyzing geospatial information. The objective of a PRESTO analysis is to assist the U.S. Environmental Protection Agency (EPA), in partnership with state and local decision-makers, in informing the prioritization of locations for initial cleanup operations aimed at reducing risks to public health and the environment after a natural disaster or chemical, biological, or radiological (CBR) incident. In the event of a natural disaster or release of CBR contaminants, for example, EPA and its partners would need to determine which locations should be prioritized to prevent the spread of contamination and mitigate long-term risks. Decision makers are often hampered by having too little or too much data, such that it is not obvious how relevant data can be incorporated into a decision-making framework. PRESTO provides a flexible and adaptable framework to address the challenges of aggregating data in a meaningful way to facilitate quickly identifying and understanding the resulting information to inform decisions. Results of a hypothetical analysis of a 10-mile radius study domain centered on Philadelphia, PA will be presented to demonstrate how PRESTO could inform disaster response planning following an incident. The presentation will illustrate how nine data sets measuring a range of issues reflecting risks to human health and the environment were used and show how substantial differences can exist in which locations would be prioritized for response depending upon which data aggregation scheme is applied.