Stone Zechariah, Chen Sunmao, Trask Jennifer, Terrell Sarah, Cox Megan, Guth Nicholas, Brain Richard
Waterborne Environmental Inc., Leesburg, Virginia, USA.
Syngenta Crop Protection, LLC, Greensboro, North Carolina, USA.
J Environ Qual. 2025 Sep-Oct;54(5):1060-1076. doi: 10.1002/jeq2.70014. Epub 2025 Mar 25.
Surface water monitoring of pesticides ensures adherence to environmental and human health regulatory requirements. This study focuses on an unprecedented monitoring program spanning two decades with daily or near-daily sampling across 13 states in the US Midwest and Southern United States, targeting watersheds in the upper 20th percentile of runoff vulnerability based on the United States Geological Survey watershed regressions for pesticides model. The Atrazine Ecological Monitoring Program (AEMP), mandated by the United States Environmental Protection Agency (USEPA), aims to collect extensive high-frequency atrazine exposure data alongside key environmental parameters to better understand the dynamics of atrazine fate, transport, and concentrations in these watersheds. Note, the AEMP is also referred to by the USEPA as the Atrazine Ecological Exposure Monitoring Program, or AEEMP, though the former is more commonly cited. Analysis of the 322 site-years of data revealed that sampling frequency is paramount in accurately estimating seasonal chemical concentrations and runoff loads in flowing waters. The AEMP has advanced with improved sampling techniques and a focus on increasingly vulnerable watersheds (i.e., currently representing 97th-99th centile runoff vulnerability), as evidenced by analysis of variance results indicating higher atrazine concentrations in later years, particularly post-2012. Factors such as soil conditions and precipitation were significant in influencing atrazine levels in surface water. Regression analyses underscored the interaction between agricultural activity and weather patterns as predictors of atrazine concentrations. The AEMP's detailed dataset has notably contributed to environmental risk assessment and the refinement of regulatory models. This study highlights the value of high-resolution data in vulnerable regions, emphasizing that high-frequency monitoring and inclusion of detailed environmental data significantly enhance our understanding of pesticide fate and transport in surface waters and informs stewardship efforts.
农药地表水监测可确保符合环境和人类健康监管要求。本研究聚焦于一项史无前例的监测计划，该计划跨越二十年，在美国中西部和南部的13个州进行每日或近乎每日的采样，目标是根据美国地质调查局农药流域回归模型，选取径流脆弱性处于前20百分位的流域。美国环境保护局（USEPA）授权的阿特拉津生态监测计划（AEMP）旨在收集广泛的高频阿特拉津暴露数据以及关键环境参数，以更好地了解这些流域中阿特拉津的归宿、迁移和浓度动态。请注意，USEPA也将AEMP称为阿特拉津生态暴露监测计划，即AEEMP，不过前者的引用更为普遍。对322个站点年的数据进行分析后发现，采样频率对于准确估算流动水体中的季节性化学物质浓度和径流负荷至关重要。AEMP随着采样技术的改进以及对日益脆弱的流域（即目前代表径流脆弱性第97 - 99百分位）的关注而不断推进，方差分析结果表明后期年份，尤其是2012年后阿特拉津浓度更高，这证明了这一点。土壤条件和降水等因素对地表水阿特拉津水平有显著影响。回归分析强调了农业活动与天气模式之间的相互作用，将其作为阿特拉津浓度的预测指标。AEMP的详细数据集对环境风险评估和监管模型的完善做出了显著贡献。本研究强调了脆弱地区高分辨率数据的价值，强调高频监测和纳入详细环境数据显著增强了我们对地表水农药归宿和迁移的理解，并为管理工作提供了依据。
