Bayesian model for fate and transport of polychlorinated biphenyl in upper Hudson River
Modelers of contaminant fate and transport in surface waters typically rely on literature values when selecting parameter values for mechanistic models. While the expert judgment with which these selections are made is valuable, the information contained in contaminant concentration measurements should not be ignored. In this full-scale Bayesian analysis of polychlorinated biphenyl (PCB) contamination in the upper Hudson River, these two sources of information are combined using Bayes' theorem. A simulation model for the fate and transport of the PCBs in the upper Hudson River forms the basis of the likelihood function while the prior density is developed from literature values. The method provides estimates for the anaerobic biodegradation half-life, aerobic biodegradation plus volatilization half-life, contaminated sediment depth, and resuspension velocity of 4400 d, 3.2 d, 0.32 m, and 0.02 m/yr, respectively. These are significantly different than values obtained with more traditional methods, and are shown to produce better predictions than those methods when used in a cross-validation study.
Duke Scholars
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Related Subject Headings
- Environmental Engineering
- 4005 Civil engineering
- 4004 Chemical engineering
- 0907 Environmental Engineering
- 0905 Civil Engineering
- 0904 Chemical Engineering
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Environmental Engineering
- 4005 Civil engineering
- 4004 Chemical engineering
- 0907 Environmental Engineering
- 0905 Civil Engineering
- 0904 Chemical Engineering