Bayesian statistics in environmental engineering planning
Today's engineer must be able to quantify both uncertainty due to information limitations, and the variability of natural processes, in order to determine risk. Nowhere is this emphasis on risk assessment more evident than in environmental engineering. The use of Bayesian inference for the rigorous assessment of risk based on available information is reviewed in this paper. Several example environmental engineering planning applications are presented: (1) assessment of losses involving the evaluation of proposed revisions to the South Florida Building Code after Hurricane Andrew; (2) development of a model to predict oil spill consequences due to proposed changes in the oil transportation network in the Gulf of Mexico; (3) studies of ambient concentrations of perchloroethylene surrounding dry cleaners and of tire particulates in residential areas near roadways in Miami, FL; (4) risk assessment from contaminated soils at a cleanup of an old transformer dump site.
- Research Organization:
- Univ. of Miami, Coral Gables, FL (US)
- OSTI ID:
- 20014775
- Resource Relation:
- Conference: ASCE-CSCE 1999 National Conference on Environmental Engineering, Norfolk, VA (US), 07/25/1999--07/28/1999; Other Information: PBD: 1999; Related Information: In: Environmental engineering 1999, by Schafran, G.C. [ed.], 936 pages.
- Country of Publication:
- United States
- Language:
- English
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