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Models for Calculating Predicted Environmental Concentrations (PEC) of Pesticides in Surface Waters: Review, Selection Criteria, and Recommendations for Regulatory Applications Cover

Models for Calculating Predicted Environmental Concentrations (PEC) of Pesticides in Surface Waters: Review, Selection Criteria, and Recommendations for Regulatory Applications

Open Access
|Mar 2026

Abstract

Accurate estimation of predicted environmental concentrations in surface waters (PECsw) is central to regulatory environmental risk assessment of plant protection products (PPPs). This review compiles and evaluates computational tools used to derive PECsw, based on the OECD overview of regulatory exposure models and expert appraisal. We synthesise each model’s conceptual design (entry routes via runoff/erosion, drainage, spray drift, atmospheric deposition), hydrological and water-body representations, mandatory inputs, and tiering suitability. Cross-model comparison highlights that parameterisation of sorption and degradation dominates PEC uncertainty; conservative inputs at lower tiers can overpredict exposure, necessitating higher-tier, scenario-realistic simulations. Good practices include documenting parameter sources, using “realistic worst case” scenarios, and reporting both initial and time-weighted PEC metrics. The review provides a clear description of the properties of calculation models and highlights their strengths and weaknesses.

DOI: https://doi.org/10.2478/oszn-2025-0020 | Journal eISSN: 2353-8589 | Journal ISSN: 1230-7831
Language: English
Page range: 1 - 17
Published on: Mar 17, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Related subjects:

© 2026 Marta Gabryszewska, Barbara Gworek, Beata Kubiak, Radosław Kalinowski, Marta Kijeńska-Markuszewska, Adriana Solecka, Magdalena Graniewska, Izabela Samson-Bręk, published by National Research Institute, Institute of Environmental Protection
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.