Porta G M, Casse L, Manzoni A, Riva M, Maggi F, Guadagnini A
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
Environmental Engineering, School of Civil Engineering, The University of Sydney, Sydney, New South Wales, Australia.
Sci Data. 2025 May 1;12(1):725. doi: 10.1038/s41597-025-05031-7.
Our work targets mapping of pesticides application rates within the European Union at a 250 m spatial resolution. Source data include global estimates of pesticide inputs, high resolution crop maps and pesticide usage reported by EUROSTAT official figures. Previously published global pesticide application rates in PEST-CHEMGRIDS are used as first guess estimates. These are then adjusted using a calibration dataset gathered from pesticide use in agriculture. The estimation of the applied mass by country and crop type is then combined with high resolution crop maps. The procedure explicitly accounts for data quality and uncertainty through a Maximum Likelihood estimation procedure. This data product features detailed spatial distributions of pesticide inputs, facilitating evaluation of pesticide fate and transport, biogeochemical transformations as well as environmental risk assessment.
我们的工作目标是绘制欧盟范围内空间分辨率为250米的农药施用量图。源数据包括农药投入的全球估计值、高分辨率作物地图以及欧盟统计局官方数据报告的农药使用情况。先前在PEST-CHEMGRIDS中公布的全球农药施用量被用作初步估计值。然后，使用从农业农药使用中收集的校准数据集对这些估计值进行调整。随后，将按国家和作物类型估算的施用量与高分辨率作物地图相结合。该程序通过最大似然估计程序明确考虑了数据质量和不确定性。该数据产品具有农药投入的详细空间分布，便于评估农药的归宿和迁移、生物地球化学转化以及环境风险评估。
