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Modeling Regulatory Threshold Levels for Pesticides in Surface Waters from Effect Databases

Author

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  • Lara L. Petschick

    (iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany)

  • Sascha Bub

    (iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany)

  • Jakob Wolfram

    (iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany)

  • Sebastian Stehle

    (iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany
    Eusserthal Ecosystem Research Station, University of Koblenz-Landau, D-76857 Eusserthal, Germany)

  • Ralf Schulz

    (iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany)

Abstract

Regulatory threshold levels (RTL) represent robust benchmarks for assessing risks of pesticides, e.g., in surface waters. However, comprehensive scientific risk evaluations comparing RTL to measured environmental concentrations (MEC) of pesticides in surface waters were yet restricted to a low number of pesticides, as RTL are only available after extensive review of regulatory documents. Thus, the aim of the present study was to model RTL equivalents (RTLe) for aquatic organisms from publicly accessible ecotoxicological effect databases. We developed a model that applies validity criteria in accordance with official US EPA review guidelines and validated the model against a set of manually retrieved RTL (n = 49). Model application yielded 1283 RTLe (n = 676 for pesticides, plus 607 additional RTLe for other use types). In a case study, the usability of RTLe was demonstrated for a set of 27 insecticides by comparing RTLe and RTL exceedance rates for 3001 MEC from US surface waters. The provided dataset enables thorough risk assessments of surface water exposure data for a comprehensive number of substances. Especially regions without established pesticide regulations may benefit from this dataset by using it as a baseline information for pesticide risk assessment and for the identification of priority substances or potential high-risk regions.

Suggested Citation

  • Lara L. Petschick & Sascha Bub & Jakob Wolfram & Sebastian Stehle & Ralf Schulz, 2019. "Modeling Regulatory Threshold Levels for Pesticides in Surface Waters from Effect Databases," Data, MDPI, vol. 4(4), pages 1-20, December.
  • Handle: RePEc:gam:jdataj:v:4:y:2019:i:4:p:150-:d:298044
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    References listed on IDEAS

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    1. Sascha Bub & Jakob Wolfram & Sebastian Stehle & Lara L. Petschick & Ralf Schulz, 2019. "Graphing Ecotoxicology: The MAGIC Graph for Linking Environmental Data on Chemicals," Data, MDPI, vol. 4(1), pages 1-17, February.
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