Development of an integrated foodweb model for mercury for exposure assessment
J.G. Hunter (Dept. of Biochemistry and Microbiology, Rutgers University);
Y.C. Yang, A. Roy, P.G. Georgopoulos, J. Burger, K. Cooper (EOHSI, UMDNJ - R.
W. Johnson Medical School and Rutgers University)
This work demonstrates the integration of ecological and exposure data and models to provide a coherent framework for improving our understanding of processes that contribute to mercury exposures for both human and ecological receptors. An integrated food web model has been developed for mercury by adapting the basic framework of the CATS (Contaminants in Aquatic and Terrestrial ecoSytems) model of Traas and co-workers (Traas et al. 1997 Env. Sci. & Tech 30 1227-1237). The new mercury CATS model describes the environmental and biological fate and transport of mercury species (unreactive mercury, zero valent mercury, divalent mercury, and methyl mercury) based upon the chemical and physical processes identified by Bale (Bale 2000 Jo. Env. Engr. 26 153-163). These processes include methylation of divalent mercury, photo-oxidation of zero valent mercury, reduction of divalent mercury, adsorption and desorption of divalent and methyl mercury, volatilization of zero valent mercury, and uptake of divalent and methylmercury into the foodweb. The foodweb in the current version of the model represents a lake ecosystem, and consists of phytoplankton, rooted vegetation, zooplankton, crayfish, freshwater clams, amphipods, chironomids, eels, killifish, bass, and ospreys. The model describes the accumulation of biomass and mercury in compartments corresponding to the biota represented in the model as a function of natural growth and mortality processes as well as predator-prey relationships. Human exposure to mercury is estimated using observed mercury concentrations in fish, and fish consumption data: exposure as a function of geographic and demographic factors is estimated and compared for three alternative sets of fish consumption data (Burger et al, 1999; Stern et al., 1996; and the USDA Continuing Survey of Intake by Individuals).
ACKNOWLEDGEMENTS: This research has been partially supported by a grant to the Institute for Responsible Management, Consortium for Risk Evaluation with Stakeholder Participation, from the US Department of Energy, Instrument DE-FG26-00NT 40938. The viewpoints expressed in this report are solely the responsibility of the authors and do not necessarily reflect the views of the US Department of Energy or its contractors.
Additional support was provided by the New Jersey Agricultural Experiment Station, and an APERG Research Fellowship from the Air Pollution Educational and Research Grant (APERG) program administered by the Mid-Atlantic States Section of the Air and Waste Management Association (MASS-A&WMA)