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Use of Chemcatcher passive sampler as a watershed-investigation tool to assess first flush polar pesticide pollution in an Eastern Mediterranean River basin

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Abstract

Characterizing first flush pesticide contamination in ephemeral streams within Mediterranean climates poses significant challenges. Quantifying spatial and temporal differences in chemical pollutants is critical to designing strategic watershed-based restoration plans aimed at protecting aquatic ecosystems. In regions with extended dry periods and intensive agricultural activities, new innovative water quality monitoring methods are needed. This study investigated the efficacy of the Chemcatcher passive sampler as a viable complementary method for assessing pesticide concentrations throughout the Kishon river basin, north-west Israel. A new Chemcatcher deployment apparatus was used in 19 tributaries at 25 watershed locations to capture the first winter storm runoff events. Polar pesticides were identified and quantified using a novel LC/MS targeted and non-targeted screening workflow, identifying 120 compounds, including fungicides, herbicides, insecticides, and their metabolites and quantifying 84 compounds. Time-weighted average concentrations ranged from sub-nanogram per liter to >1800 ng L−1. Pesticide concentrations were positively correlated with agricultural land use categories. Results showed the importance of capturing first flush storm flows, revealing some sites with exceedingly high cumulative concentrations (>2500 ng L−1). Diuron, 2,4-D, imidacloprid and tebuconazole were detected at all sites. Multivariate statistical analysis identified pesticides that posed a risk within the catchment. Concentrations of bromacil, diuron, fenamiphos, imidacloprid, and methoxyfenozide were classified as very high risk, based on their probable no-effect concentrations. This study demonstrates a new method for using passive sampling to monitor first flush stormwaters in ephemeral streams and defines a strategic catchment sampling approach for Mediterranean catchments, with new analytic and statistical tools, to advance informed watershed management decision-making.

Original languageEnglish
Article number127234
Number of pages17
JournalJournal of Environmental Management
Volume394
Early online date12 Sept 2025
DOIs
Publication statusPublished - 1 Nov 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Agricultural land use
  • Chemcatcher
  • High-resolution Mass Spectrometry
  • Risk assessment
  • River basin management
  • Water pollution

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