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    Field Evaluation of Human Exposure to Pesticides and Comparison with Exposure Assessment Models: Drone and Wide-area Sprayer Applications

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    https://www.riss.kr/link?id=A110233671

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    International agencies have developed guidelines and predictive models to assess human exposure of pesticides during the application. However, these models are typically based on limited empirical data and may not accurately represent real-world spraying conditions. Moreover, they do not account for spraying equipment such as drones or wide-area sprayers, which limits their applicability under current field conditions.
    In this study, we quantified pesticide exposure among operators, residents, and bystanders during applications using drones and wide-area sprayers. Subsequently, the pesticide exposure test results were evaluated using exposure models developed in this study.
    Measured operator exposure was substantially higher during wide-area spraying than during drone-based application, primarily due to reduced working distance and differences in spray delivery mechanisms. Exposure levels among residents and bystanders were also elevated during wide-area spraying, although drone-based applications demonstrated potential for long-distance drift under specific meteorological conditions. Existing models, including EFSA, UK-POEM, BREAM2, and EUROPOEM, did not adequately account for spray aerodynamics or field variability, resulting in frequent underestimation or overestimation of exposure. Despite a limited dataset, this study provides clear insights into exposure patterns associated with both technologies and highlights the need for model refinement to accommodate emerging application methods.
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    International agencies have developed guidelines and predictive models to assess human exposure of pesticides during the application. However, these models are typically based on limited empirical data and may not accurately represent real-world spray...

    International agencies have developed guidelines and predictive models to assess human exposure of pesticides during the application. However, these models are typically based on limited empirical data and may not accurately represent real-world spraying conditions. Moreover, they do not account for spraying equipment such as drones or wide-area sprayers, which limits their applicability under current field conditions.
    In this study, we quantified pesticide exposure among operators, residents, and bystanders during applications using drones and wide-area sprayers. Subsequently, the pesticide exposure test results were evaluated using exposure models developed in this study.
    Measured operator exposure was substantially higher during wide-area spraying than during drone-based application, primarily due to reduced working distance and differences in spray delivery mechanisms. Exposure levels among residents and bystanders were also elevated during wide-area spraying, although drone-based applications demonstrated potential for long-distance drift under specific meteorological conditions. Existing models, including EFSA, UK-POEM, BREAM2, and EUROPOEM, did not adequately account for spray aerodynamics or field variability, resulting in frequent underestimation or overestimation of exposure. Despite a limited dataset, this study provides clear insights into exposure patterns associated with both technologies and highlights the need for model refinement to accommodate emerging application methods.

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