Reconstructing Historical Contamination Events: Use Of Computational Tools To Assist Environmental Engineers And Health Scientists
Free (open access)
M. L. Maslia & M. M. Aral
The Agency for Toxic Substances and Disease Registry (ATSDR) assesses numerous historical and legacy hazardous waste sites as part of its congressionally mandated public health responsibilities. Because historical, sitespecific, contaminant and exposure data may be very limited or non-existent, computational tools (models) are needed to answer environmental and healthrelated questions associated with exposure scenarios and the conduct of public health assessments. This paper summarizes two case studies that demonstrate the effective application and use of computational tools for reconstructing historical contamination and exposure events. The case studies demonstrate the application of an analytical multimedia computational tool—the analytical contaminant analysis transport system (ACTS) and a water-distribution system model (EPANET) that has been coupled with a progressive optimality genetic algorithm (POGA). The resulting application and use of these computational tools have allowed environmental engineers and health scientists at the ATSDR to assess numerous exposure scenarios so that public health managers could address issues related to health risks associated with contaminated public water supplies. These case studies also illustrate the different levels of assessment complexity—probabilistic screening level to research—that can be used to assess the impacts of historical contamination events. Keywords: historical reconstruction, analytical models, probabilistic analysis, ACTS, water-distribution system model, EPANET, genetic algorithm, POGA. 1 Introduction Exposures to toxic environmental contaminants are significant risk factors in human health and disease. To understand and manage these risk factors, environmental and public health managers must have knowledge of the source of
historical reconstruction, analytical models, probabilistic analysis, ACTS, water-distribution system model, EPANET, genetic algorithm, POGA.