选择农药淋失指标,将其纳入农场规模的决策支持系统。

IF 5.8 3区 环境科学与生态学 0 ENVIRONMENTAL SCIENCES
Antonio Finizio, Andrea Tosadori, Andrea Di Guardo
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引用次数: 0

摘要

欧盟最近的农业政策强调通过促进有机实践和负责任的化学品投入(如杀虫剂)管理来提高农业的可持续性。在这种情况下,必须向农民提供可靠的农药风险指标,使其能够纳入决策支持系统,使他们能够确定最佳病虫害管理战略,尽量减少对环境的影响,并监测在提高农场一级可持续性方面取得的进展。本文概述了我们选择最合适的农药风险指标来评估农药进入地下水的潜在淋滤性的方法。对于46种活性物质,我们最初从欧洲食品安全局(EFSA)结论文件中检索了相关数据,包括地下水中预测环境浓度(PECgw)。这些值被认为是高质量的,作为欧盟农药授权环境风险评估程序的参考点。然后,我们将这些PECgw值与从文献中选择的两个指标和一个元模型得出的结果进行了比较:地下水无处不在评分(GUS)指数、衰减因子(AF)指数和欧洲药品管理局用于兽药授权的元模型。分析显示,虽然所有三种方法通常与EFSA文件中报告的PECgw值一致,但AF指数显示出最高的预测能力。此外,AF指数更符合适用的便利性和在不同地理环境下的适用性等标准。因此,AF指数被确定为集成到决策支持系统的最佳选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selecting a pesticide leaching indicator for integration into a decision support system at farm scale

The recent EU agricultural policy emphasises enhancing the sustainability of farming by promoting organic practices and the responsible management of chemical inputs such as pesticides. In this context, it is essential to provide farmers with reliable pesticide risk indicators that can be integrated into decision support systems, enabling them to identify optimal pest management strategies, minimise environmental impact, and monitor progress in improving farm-level sustainability. This paper outlines our approach to selecting the most appropriate pesticide risk indicator for assessing the potential leachability of pesticides into groundwater. For 46 active substances, we initially retrieved relevant data from the European Food Safety Authority (EFSA) Conclusions documents, including Predicted Environmental Concentrations in groundwater (PECgw). These values, considered of high quality, serve as reference points in the EU environmental risk assessment procedures for pesticide authorisation. We then compared these PECgw values with results obtained from two indicators and a metamodel selected from the literature: the Groundwater Ubiquity Score (GUS) index, the Attenuation Factor (AF) index, and the metamodel used by the European Medicines Agency for the authorisation of veterinary pharmaceuticals. The analysis revealed that while all three methods generally aligned well with the PECgw values reported in the EFSA documents, the AF index demonstrated the highest predictive capability. Furthermore, the AF index was more consistent with criteria such as ease of application and applicability across various geographical contexts. Therefore, the AF index was identified as the optimal choice for integration into decision support systems.

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来源期刊
CiteScore
8.70
自引率
17.20%
发文量
6549
审稿时长
3.8 months
期刊介绍: Environmental Science and Pollution Research (ESPR) serves the international community in all areas of Environmental Science and related subjects with emphasis on chemical compounds. This includes: - Terrestrial Biology and Ecology - Aquatic Biology and Ecology - Atmospheric Chemistry - Environmental Microbiology/Biobased Energy Sources - Phytoremediation and Ecosystem Restoration - Environmental Analyses and Monitoring - Assessment of Risks and Interactions of Pollutants in the Environment - Conservation Biology and Sustainable Agriculture - Impact of Chemicals/Pollutants on Human and Animal Health It reports from a broad interdisciplinary outlook.
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