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DECISION SUPPORT SYSTEM TO ENHANCE AND ENCOURAGE SUSTAINABLE CHEMICAL PROCESS DESIGN
Citation:
Saxe**, J. K., T M. Martin**, AND D M. Young*. DECISION SUPPORT SYSTEM TO ENHANCE AND ENCOURAGE SUSTAINABLE CHEMICAL PROCESS DESIGN. Presented at 22nd Annual Meeting, Society of Environmental Toxicology and Chemistry, Baltimore, MD, 11/11-15/2001.
Description:
There is an opportunity to minimize the potential environmental impacts (PEIs) of industrial chemical processes by providing process designers with timely data nad models elucidating environmentally favorable design options. The second generation of the Waste Reduction (WAR) algorithm is a software decision support system (WAR DSS) for use in conjunction with commercial chemical process design software. The WAR algorithm includes indicators for chemicals PEIs ranging from global to local, including global warming, ozone depletion, acid rain production, smog formation, nutrification of water bodies, and toxicity to humans and animals. chemical process designers work with a wide array of chemicals, and therefore, WAR DSS provides data and models for nearly 5000 chemicals. Indicators for human and ecological toxicity ideally require empirical data for chronic and acute toxicity and other effects in several species. Since these data are not available for many of the WAR DSS-supported chemicals, QSARs and cross-species toxicological models were developed to provide estimated data to determine PEIs. Generalized environmental fate models were also tailored for the WAR DSS, providing information on chemicals likely persistence and bioconcentration while providing the option to add site-specific data for more refined predictions. The use of several toxicity and fate measures for each chemical in assessing the human and ecological toxicity PEIs allows consideration of the most pertiment information available for the large list of chemicals supported in the WAR DSS.