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IMPROVING EMISSIONS ESTIMATES WITH COMPUTATIONAL INTELLIGENCE, DATABASE EXPANSION, AND COMPREHENSIVE VALIDATION
Citation:
Cleland, J., V. McCormick, H. Waters, J. Youngberg, AND J. Zak. IMPROVING EMISSIONS ESTIMATES WITH COMPUTATIONAL INTELLIGENCE, DATABASE EXPANSION, AND COMPREHENSIVE VALIDATION. U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-97/005 (NTIS PB97-152565), 1997.
Impact/Purpose:
information
Description:
The report discusses an EPA investigation of techniques to improve methods for estimating volatile organic compound (VOC) emissions from area sources. Using the automobile refinishing industry for a detailed area source case study, an emission estimation method is being developed that uses advanced computational techniques and updated, comprehensive, emissions-related information. New computational techniques contributing to the estimation method are fuzzy logic, neural networks, and genetic algorithms. This method development requires a thorough characterization of the area sources, an analysis of current emission estimation methods, the development and execution of a nationwide industry activity survey, and a compilation and analysis of the survey results and other explanatory variables. Results will be captured in a personal-computer-based emissions estimation system called VOCEES (VOC Emissions Estimation System). VOCEES has been developed as a dual-use tool that prepares VOC emissions inventories and analyzes the impact of many factors on emissions. This methodology can be easily extended to other area sources.
