Bayesian model for fate and transport of polychlorinated biphenyl in upper Hudson River

L. J. Steinberg, K. H. Reckhow, R. L. Wolpert

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)341-349
Number of pages9
JournalJournal of Environmental Engineering - ASCE
Issue number5
StatePublished - May 1996
Externally publishedYes

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Environmental Chemistry
  • General Environmental Science


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