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

Lara L. Petschick, Sascha Bub, Jakob Wolfram, Sebastian Stehle and Ralf Schulz
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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
Ralf Schulz: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany

Data, 2019, vol. 4, issue 4, 1-20

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.

Keywords: ecotoxicology; pesticide thresholds; benchmarks; environmental risk assessment; effect database; systematic filter application; exceedance rates (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
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