Ghosh Saikat, Crist Kevin
Pacific Northwest National Laboratory, United States of America.
Chemical and Biomolecular Engineering, Ohio University, United States of America.
Heliyon. 2022 Nov 24;8(12):e11810. doi: 10.1016/j.heliyon.2022.e11810. eCollection 2022 Dec.
Pesticides can volatilize from treated soil to the atmosphere causing increased environmental pollution and human exposure. Exposure assessment to airborne pesticides requires reasonable predictions of pesticide emissions. Understanding the volatilization behavior due to changes in environmental conditions can help in assessing the risk uncertainty and designing better mitigation strategies. In this study, we developed a mechanistic model that can be used to predict the hourly volatilization emissions from pesticide-treated soil at different environmental conditions. Pesticide properties and local environmental conditions drive the transport processes at the soil-air interface within the model. The numerical model simultaneously calculates the soil fluxes of heat, moisture, and pesticide at the soil-air interface with inputs of hourly meteorological data. The initial condition of pesticide concentration in soil is obtained from the applied mass during treatment. The numerical model was compared with an analytical model and with field observations for a soil injected fumigant and two surface applied pesticides. The model performance of 14 pesticides under stagnant conditions against the Jury's analytical model showed reasonable agreement with values for the coefficient of determination (R) ranging from 0.76 to 0.99. The model was a good predictor of the field-scale volatilization of a fumigant (1,3-dichloropropene) application when compared to observations (R ). Both the timing of the peak and the temporal variability of the measured volatilization of the fumigant were captured by the model when the fumigant was incorporated at a depth of 46 cm in the soil column. The model also showed reasonable agreement with the measured volatilization of two surface-treated pesticides, though site-specific meteorological data was unavailable for these observations. The results indicate that the modeling approach could be a useful tool to evaluate the impact of location-specific meteorological conditions on the field volatility of pesticides and determine the emissions for risk assessment.
农药可从施药土壤挥发至大气中,导致环境污染加剧和人类接触风险增加。对空气中农药的暴露评估需要对农药排放进行合理预测。了解环境条件变化导致的挥发行为有助于评估风险不确定性并设计更好的缓解策略。在本研究中,我们开发了一个机理模型,可用于预测不同环境条件下农药处理土壤的每小时挥发排放量。农药特性和当地环境条件驱动模型中土壤 - 空气界面的传输过程。该数值模型利用每小时气象数据输入,同时计算土壤 - 空气界面处的热量、水分和农药的土壤通量。土壤中农药浓度的初始条件通过处理期间施用的质量获得。该数值模型与一个分析模型以及针对土壤注射熏蒸剂和两种地表施用农药的现场观测结果进行了比较。在静止条件下,14种农药的模型性能与 Jury 的分析模型相比,决定系数(R)值在0.76至0.99之间,显示出合理的一致性。与观测结果相比,该模型是熏蒸剂(1,3 - 二氯丙烯)田间尺度挥发的良好预测器(R )。当熏蒸剂在土柱中46厘米深度处施入时,模型捕捉到了熏蒸剂挥发峰值的时间以及测量挥发的时间变化。该模型与两种地表处理农药的测量挥发结果也显示出合理的一致性,尽管这些观测没有特定地点的气象数据。结果表明,该建模方法可能是评估特定地点气象条件对农药田间挥发性影响并确定用于风险评估的排放量的有用工具。