A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A Maximum Entropy Approach to Estimating Emissions
A maximum information entropy method of calculating probabilistic estimates of volatile organic compound (VOC) emissions by the wood furniture and fixture coating industry is presented. The maximum entropy approach is used to produce minimally biased probability distributions for number of firms, coating use, and coating emission factors from existing summary statistics. These distributions are combined to estimate VOC emissions. The maximum entropy emissions estimate provides information to support probabilistic modeling of regional air quality, probabilistic assessment of emission reduction strategies, and risk assessments. Accurate estimation of emission distributions produces more informed regulatory decisionmaking, risk comparisons, and regulatory and scientific priority setting.
A Maximum Entropy Approach to Estimating Emissions
A maximum information entropy method of calculating probabilistic estimates of volatile organic compound (VOC) emissions by the wood furniture and fixture coating industry is presented. The maximum entropy approach is used to produce minimally biased probability distributions for number of firms, coating use, and coating emission factors from existing summary statistics. These distributions are combined to estimate VOC emissions. The maximum entropy emissions estimate provides information to support probabilistic modeling of regional air quality, probabilistic assessment of emission reduction strategies, and risk assessments. Accurate estimation of emission distributions produces more informed regulatory decisionmaking, risk comparisons, and regulatory and scientific priority setting.
A Maximum Entropy Approach to Estimating Emissions
Anex, Robert P. (author) / Lund, Jay R. (author) / Grant, Robert (author)
Journal of the Air & Waste Management Association ; 49 ; 943-950
1999-08-01
8 pages
Article (Journal)
Electronic Resource
Unknown
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