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开发并应用一种先进的算法,用于评估农业土壤中农药残留的环境风险和进行安全管理:监测旱地土壤中目前使用的农药。

Development and application of an advanced algorithm for environmental risk assessment and safety management of pesticide residues in agricultural soils: Monitoring of currently used pesticide in upland soils.

机构信息

Department of Energy System Engineering, Gyeongsang National University, Republic of Korea.

Residue Research Department, Hanearl Science, Seongnam, Republic of Korea.

出版信息

Environ Int. 2024 Aug;190:108865. doi: 10.1016/j.envint.2024.108865. Epub 2024 Jul 2.

Abstract

This study conducted the development of an advanced risk assessment algorithm system and safety management strategies using pesticide residue monitoring data from soils. To understand the status of pesticide residues in agricultural soils, monitoring was performed on 116 types of pesticides currently in use across 300 soil sites. The analysis of the monitoring results, alongside the physicochemical properties of the pesticides, led to the selection of soil half-life as a critical component in residue analysis. The use of Toxicity Exposure Ratio (TER) and Risk Quotient (RQ) for environmental risk assessment, based on monitoring data, presents limitations due to its single-component, conservative approach, which does not align with actual field conditions. Therefore, there is a necessity for a risk assessment process applicable in real-world scenarios. In this research, an efficient and accurate risk assessment algorithm system, along with a safety management model, was developed. Using the physicochemical properties of pesticides (such as soil half-life), monitoring results, and toxicity data, cluster analysis and Principal Component Analysis (PCA) validation identified four pesticides: boscalid, difenoconazole, fluquinconazole, and tebuconazole. The k-mean cluster analysis selected three priority management sites where the contribution of these four pesticides to the RQ was between 94-99 %, showing similar results to the RQ calculated for all pesticides. Predictions made with the developed model for the time required for soil half-life based RQ to drop below 1 at these priority sites showed only a 1-9 day difference between the four pesticides of concern and all pesticides, indicating comparable outcomes. The scenario of replacing high-risk pesticides with those of lower risk demonstrated that the RQ could be consistently maintained at about 50 % level. The results of this study suggest that through monitoring, evaluation, and management, effective and accurate environmental safety management of pesticides in soil can be achieved.

摘要

本研究旨在利用土壤中农药残留监测数据开发先进的风险评估算法系统和安全管理策略。为了了解农业土壤中农药残留的状况,对当前使用的 116 种农药在 300 个土壤点进行了监测。通过对监测结果及农药理化性质的分析,选择土壤半衰期作为残留分析的关键组成部分。基于监测数据,利用毒性暴露比(TER)和风险商(RQ)进行环境风险评估具有局限性,因为其采用单一成分的保守方法,与实际田间条件不符。因此,需要开发适用于实际情况的风险评估流程。本研究开发了一种高效、准确的风险评估算法系统和安全管理模型。利用农药理化性质(如土壤半衰期)、监测结果和毒性数据,通过聚类分析和主成分分析(PCA)验证,确定了 4 种农药:唑菌胺酯、烯唑醇、氟环唑和戊唑醇。k-均值聚类分析选择了 3 个重点管理点,这 4 种农药对 RQ 的贡献在 94-99%之间,与计算所有农药的 RQ 结果相似。使用所开发的模型对这些优先站点的土壤半衰期 RQ 降至 1 以下所需时间进行预测,结果表明,这 4 种关注农药与所有农药之间仅相差 1-9 天,结果相当。用低风险农药替代高风险农药的情景表明,RQ 可稳定保持在约 50%的水平。本研究结果表明,通过监测、评估和管理,可以实现土壤中农药的有效、准确的环境安全管理。

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