Bayesian spatial modeling of Lavaca Bay pollutants.

abstract

• Locational risk of increased mercury and PAH concentrations in Lavaca Bay, Texas sediments and eastern oysters (Crassostrea virginica) harvested from Lavaca Bay, Texas were analysed. Chemical analysis results were evaluated utilizing Bayesian geo-statistical methods for comparison of the model fit of a random effects model versus a convoluted model which included both random and spatial effects. For those results fit best with the convoluted model, continuous surface maps of predicted parameter values were created. Sediment and oyster concentrations of mercury and the majority of measured PAHs were fit best with the convoluted model. The locational risks of encountering elevated concentrations of these pollutants in Lavaca Bay sediments and oysters were highest in close proximity to industrial facilities.

authors

• Bissett, Wesley
• Phillips, Timothy
• Scott, Harvey
• Wade, Terry

published proceedings

• Mar Pollut Bull

author list (cited authors)

• Bissett, W., Garry Adams, L., Field, R., Moyer, W., Phillips, T., Morgan Scott, H., ... Thompson, J. A.

complete list of authors

• Bissett, Wesley||Garry Adams, L||Field, Robert||Moyer, William||Phillips, Tim||Morgan Scott, H||Wade, Terry||Sweet, Steve||Thompson, James A

publisher

• Elsevier  Publisher

published in

• MARINE POLLUTION BULLETIN  Journal

keywords

• Animals
• Bayes Theorem
• Geologic Sediments
• Mercury
• Models, Theoretical
• Oceans And Seas
• Ostreidae
• Polycyclic Aromatic Hydrocarbons
• Texas
• Water
• Water Pollutants

PubMed Central ID

• 18662818

Digital Object Identifier (DOI)

• 10.1016/j.marpolbul.2008.06.010

start page

• 1781

end page

• 1787

volume

• 56

issue

• 10