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Biogeographical Analysis of Chemical Co‐Occurrence Data to Identify Priorities for Mixtures Research

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  • Rogelio Tornero‐Velez
  • Peter P. Egeghy
  • Elaine A. Cohen Hubal

Abstract

A challenge with multiple chemical risk assessment is the need to consider the joint behavior of chemicals in mixtures. To address this need, pharmacologists and toxicologists have developed methods over the years to evaluate and test chemical interaction. In practice, however, testing of chemical interaction more often comprises ad hoc binary combinations and rarely examines higher order combinations. One explanation for this practice is the belief that there are simply too many possible combinations of chemicals to consider. Indeed, under stochastic conditions the possible number of chemical combinations scales geometrically as the pool of chemicals increases. However, the occurrence of chemicals in the environment is determined by factors, economic in part, which favor some chemicals over others. We investigate methods from the field of biogeography, originally developed to study avian species co‐occurrence patterns, and adapt these approaches to examine chemical co‐occurrence. These methods were applied to a national survey of pesticide residues in 168 child care centers from across the country. Our findings show that pesticide co‐occurrence in the child care center was not random but highly structured, leading to the co‐occurrence of specific pesticide combinations. Thus, ecological studies of species co‐occurrence parallel the issue of chemical co‐occurrence at specific locations. Both are driven by processes that introduce structure in the pattern of co‐occurrence. We conclude that the biogeographical tools used to determine when this structure occurs in ecological studies are relevant to evaluations of pesticide mixtures for exposure and risk assessment.

Suggested Citation

  • Rogelio Tornero‐Velez & Peter P. Egeghy & Elaine A. Cohen Hubal, 2012. "Biogeographical Analysis of Chemical Co‐Occurrence Data to Identify Priorities for Mixtures Research," Risk Analysis, John Wiley & Sons, vol. 32(2), pages 224-236, February.
  • Handle: RePEc:wly:riskan:v:32:y:2012:i:2:p:224-236
    DOI: 10.1111/j.1539-6924.2011.01658.x
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    Cited by:

    1. Hong Yao & Xin Qian & Hong Yin & Hailong Gao & Yulei Wang, 2015. "Regional Risk Assessment for Point Source Pollution Based on a Water Quality Model of the Taipu River, China," Risk Analysis, John Wiley & Sons, vol. 35(2), pages 265-277, February.

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