Grantee Research Project Results

Final Report: Building Community Resilience to Natural-disaster-Driven Contaminant Exposures Through System-level Risk Analysis, Management, and Readiness

EPA Grant Number: R840041
Title: Building Community Resilience to Natural-disaster-Driven Contaminant Exposures Through System-level Risk Analysis, Management, and Readiness
Investigators: Borsuk, Mark E.
Institution: Duke University
EPA Project Officer: Aja, Hayley
Project Period: August 1, 2020 through July 31, 2023 (Extended to July 31, 2024)
Project Amount: $799,756
RFA: Contaminated Sites, Natural Disasters, Changing Environmental Conditions and Vulnerable Communities: Research to Build Resilience (2019) RFA Text | Recipients Lists
Research Category: Sustainable and Healthy Communities , Safer Chemicals

Objective:

1. To develop a generalizable and comprehensive risk analysis framework that links natural hazards and changing environmental conditions to the release, fate, and transport of contaminants.

2. To collaborate with community partners to identify factors that may modify exposure and vulnerability of certain populations and include such factors in our framework to holistically assess health risks.

3. To assist communities in translating scientific products into realistic and relevant management and readiness plans that promote community resilience to natural hazards.

Summary/Accomplishments (Outputs/Outcomes):

We forged meaningful and productive working relations with our community partners, which include, in Charleston, SC, the Low Country Alliance for Model Communities (LAMC) and the Charleston Community to Research Action Board (CCRAB) and, in North Carolina, the North Carolina Environmental Justice Network (NCEJN) and Rural Empowerment Association for Community Help (REACH). These partners participated regularly in our team meetings and site visits. We have also formed a representative and active Community Advisory Board (CAB), which met in each year of the project.
To better understand community perspectives on preparedness and resilience to NaTech disasters in our partner communities, we conducted a series of community-mapping and walking exercises. In addition to identifying local containment sources and exposure pathways, we created workshops on using EJSCREEN to (1) assess risk from natural disasters; (2) map disaster resilience; and (3) develop disaster readiness plans across high, medium, and low risk scenarios. Through these workshops, participants were able to assess how pollution risk and population characteristics affect an area’s disaster resilience and vulnerability, how EJ Scores were being used to compare areas’ levels of disaster resilience and vulnerability concern, and how these comparisons are utilized in resilience planning and disaster readiness programming.
We held a full-day focus group in each of our two partner communities (North Charleston, SC, and Duplin County, NC) to discuss key contributors to potential contaminant exposure resulting from extreme weather events. The results were used to develop a wider survey of each population to better quantify key contributors and social vulnerability to potential contaminant exposure resulting above-ground storage tank failure.
We developed the South Carolina Environmental Justice Screen (SC EJSCREEN) Tool utilizing publicly available data, ArcGIS Pro 3.3, and ArcGIS Experience Builder. The state-specific tool identifies environmental pollution and climate disaster risks by categorizing hazards into relevant domains and their constituent indicators, including the domains of Climate Change, Environmental Exposure, Environmental Effects, Socioeconomic Factors, and Health. The tool’s detailed and domain-specific data can support communities and policymakers to allocate resources, craft targeted policies, and make more informed decisions.
We completed development of an original annotated dataset of above-ground storage tanks (ASTs) from high-resolution orthorectified aerial imagery across the contiguous United States and published a manuscript in the journal Nature Scientific Data describing this dataset. The data set contains the geospatial coordinates, border vertices, and imagery of over 130,000 spherical pressure, closed roof, external floating roof, sedimentation tanks, and water towers from 48 states. This dataset is broadly useful for the purposes of large-scale risk and hazard assessment, production and capacity estimation, and infrastructure evaluation and is now publicly available.
We developed a machine-learning (ML) object detection method to automate the process of locating and classifying ASTs, using our annotated AST dataset for training. We are preparing a manuscript that describes this method for submission to a journal.
We performed a systematic analysis of the risk posed by storm surge and flooding hazards to above-ground petroleum storage tanks across the contiguous United States. This involves the application of large-scale simulations of parametric logistic fragility functions, using logistic regression to account for those variables for which data are not available. We then used the constructed parametric functions, structured as a Bayesian network, to make probabilistic predictions of total tank failures across the US that account for the type and accuracy of data that are actually available or that could be estimated. The product is a generalizable framework for tank risk assessment available to a diversity of stakeholders.

Journal Articles on this Report : 1 Displayed | Download in RIS Format

Publications Views
Other project views:	All 5 publications	1 publications in selected types	All 1 journal articles

Publications
Type	Citation	Project	Document Sources
Journal Article	Robinson C, Bradbury K, Borsuk ME. Remotely sensed above-ground storage tank dataset for object detection and infrastructure assessment. Scientific Data. 2024;11(1):67.	R840041 (Final)	Full-text: Full Text HTML Exit Abstract: PubMed Abstract HTML

Supplemental Keywords:

environmental justice, community engagement, vulnerability, object detection, machine learning, Bayesian network, risk analysis, coastal hazards

Relevant Websites:

10th Annual Environmental Justice and Health Disparities Symposium Exit

Above Ground Storage Tank Data Pipeline GitHub Repository Exit

Visualizing Hidden Risks Exit

Progress and Final Reports:

Original Abstract

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.