Pesticide hotspot probability model

A high density of shallow pore water screening samples taken for a pesticide contamination study were applied to the development of a probability model spreadsheet. The JAGG model 1.5, developed by the Danish Environmental Protection Agency, was modified to pore water sampling instead of soil gas, to output the number of pore water samples necessary to detect a pesticide hotspot with a defined level of certainty. The spreadsheets calculate the grid size (representing one pore water sample per grid cell) required to detect a pesticide of a defined concentration at a defined certainty. In this study, the probability model was run for several concentration levels of two dominant pesticides, desphenyl choridazone (DPC) and mechloroprop (MCPP). The results of the spreadsheet provide a starting point for similar studies to locate and delineate pesticide contamination areas, and investigate the conceptual understanding of the contamination area.

为农药污染研究采集的具有高孔隙水含量样本的筛选工作，被应用于概率模型电子表格的开发。丹麦环境保护局开发的 JAGG 模型 1.5 版本，经过修改后，将孔隙水采样替代土壤气体采样，以输出检测农药热点所需孔隙水样本的数量，并确保达到一定的置信水平。该电子表格计算了检测在指定置信水平下特定浓度农药所需的网格尺寸（每网格单元代表一个孔隙水样本）。在本研究中，概率模型针对两种主要农药，即脱苯基氯代酮（DPC）和甲氧基丙酸（MCPP）的多个浓度级别进行了运行。该电子表格的结果为类似研究提供了定位和划界农药污染区域，以及探究污染区域概念理解的起点。