A Deployable Model and Global Dataset on Stormwater Microplastic Concentrations and Drivers

This dataset compiles global measurements of stormwater microplastic concentrations along with their driving factors, serving as a resource for analyzing the extent and variability of microplastic pollution in stormwater systems. The dataset integrates measured microplastic concentrations from diverse locations with environmental, hydrological, meteorological, and land use data, offering a structured foundation for further analysis and modeling. To enhance its utility, three machine learning models were developed and interpreted to examine the relationships between stormwater microplastic concentrations and various hydrometeorological and socioeconomic variables. The dataset is intended to support future modeling efforts, particularly when supplemented with additional empirical studies. The provided model can be deployed in stormwater catchments where cost-intensive sampling and analysis are limited or used as a basis for further refinement and development.

本数据集整合了全球范围内雨水径流微塑料浓度的实测数据及其影响因子，可为分析雨水系统中微塑料污染的程度与变异性提供支撑。本数据集融合了不同区域的微塑料浓度实测数据与环境、水文、气象及土地利用相关数据，为后续分析与建模构建了结构化基础。为提升数据集的实用价值，本研究开发并解析了三款机器学习模型，用以探究雨水径流微塑料浓度与各类水文气象及社会经济变量之间的关联关系。本数据集旨在为后续建模工作提供支撑，尤其可在辅以额外实证研究的场景中发挥作用。本次提供的模型可部署于采样与分析成本高昂、难以开展的雨水汇水区，亦可作为后续优化与开发的基础。