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Comparison of four probabilistic models (CARES®, Calendex™, ConsExpo, and SHEDS) to estimate aggregate residential exposures to pesticides

Journal of Exposure Science & Environmental Epidemiology volume 22, pages 522–532 (2012)Cite this article

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Abstract

Two deterministic models (US EPA's Office of Pesticide Programs Residential Standard Operating Procedures (OPP Residential SOPs) and Draft Protocol for Measuring Children's Non-Occupational Exposure to Pesticides by all Relevant Pathways (Draft Protocol)) and four probabilistic models (CARES®, Calendex™, ConsExpo, and SHEDS) were used to estimate aggregate residential exposures to pesticides. The route-specific exposure estimates for young children (2–5 years) generated by each model were compared to evaluate data inputs, algorithms, and underlying assumptions. Three indoor exposure scenarios were considered: crack and crevice, fogger, and flying insect killer. Dermal exposure estimates from the OPP Residential SOPs and the Draft Protocol were 4.75 and 2.37 mg/kg/day (crack and crevice scenario) and 0.73 and 0.36 mg/kg/day (fogger), respectively. The dermal exposure estimates (99th percentile) for the crack and crevice scenario were 16.52, 12.82, 3.57, and 3.30 mg/kg/day for CARES, Calendex, SHEDS, and ConsExpo, respectively. Dermal exposure estimates for the fogger scenario from CARES and Calendex (1.50 and 1.47 mg/kg/day, respectively) were slightly higher than those from SHEDS and ConsExpo (0.74 and 0.55 mg/kg/day, respectively). The ConsExpo derived non-dietary ingestion estimates (99th percentile) under these two scenarios were higher than those from SHEDS, CARES, and Calendex. All models produced extremely low exposure estimates for the flying insect killer scenario. Using similar data inputs, the model estimates by route for these scenarios were consistent and comparable. Most of the models predicted exposures within a factor of 5 at the 50th and 99th percentiles. The differences identified are explained by activity assumptions, input distributions, and exposure algorithms.

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Acknowledgements

The US Environmental Protection Agency through its Office of Research and Development partially funded and managed the research described here. It has been subjected to Agency administrative review and approved for publication.

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Authors and Affiliations

  1. Bayer CropScience, Research Triangle Park, North Carolina, USA

    Bruce M Young & Curt Lunchick

  2. US EPA, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, North Carolina, USA

    Nicolle S Tulve, Peter P Egeghy, Valerie G Zartarian & Jianping Xue

  3. infoscientific.com, Inc., Manassas, Virginia, USA

    Jeffrey H Driver

  4. Exponent, Washington, DC, USA

    Jason E Johnston

  5. RIVM, National Institute for Public Health and the Environment, Bilthoven, The Netherlands

    Christiaan J E Delmaar

  6. Health Effects Division, US EPA, Office of Pesticide Programs, Washington, DC, USA

    Jeffrey J Evans

  7. Alion Science and Technology, Inc., Research Triangle Park, North Carolina, USA

    Luther A Smith & Graham Glen

  8. infoscientific.com, Inc., Carmichael, California, USA

    John H Ross

  9. Dow AgroSciences, Indianapolis, Indiana, USA

    David E Barnekow

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  1. Bruce M Young
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  2. Nicolle S Tulve
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  3. Peter P Egeghy
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  4. Jeffrey H Driver
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  7. Christiaan J E Delmaar
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  10. Graham Glen
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Correspondence to Nicolle S Tulve.

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Young, B., Tulve, N., Egeghy, P. et al. Comparison of four probabilistic models (CARES®, Calendex™, ConsExpo, and SHEDS) to estimate aggregate residential exposures to pesticides. J Expo Sci Environ Epidemiol 22, 522–532 (2012). https://doi.org/10.1038/jes.2012.54

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