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Source apportionment and spatial drivers of soil microplastics across land-use types revealed by APCS-MLR and Geodetector
Summary
Scientists studying soil in a Chinese industrial city found that microplastic pollution is highest near factories and mines, with everyday human activities (like farming and daily waste) contributing about two-thirds of the contamination and industrial sources making up the rest. Busy roads and factory-dense areas were the biggest culprits, meaning the plastic dust and debris from traffic and manufacturing is settling into the ground we grow food on. Since microplastics in soil can work their way into crops and groundwater, understanding exactly where they come from is a key step toward reducing our long-term exposure to them through food and water.
Accurately identifying and quantifying the sources of soil microplastic pollution, along with its key influencing factors, is crucial for effective prevention and control. Using Jiaozuo, China, as the study area, this research systematically analyzed the occurrence characteristics of microplastics in soil across different land-use types. By combining the APCS-MLR (absolute principal component score-multiple linear regression) and Geodetector, it investigated the sources of pollution and spatial drivers, while also employing Monte Carlo simulation to assess the ecological risks posed by microplastics. The results indicate that microplastic abundance varies significantly across land-use types, with concentrations in industrial and mining areas markedly higher than in agricultural, educational, and residential zones. Source apportionment reveals that a combination of inputs from human daily activities and agricultural practices (65.65%) and emissions from industrial and mining raw materials and transport (34.35%) constitute the primary sources of contamination. Univariate analysis within the Geodetector indicated that road network density (q = 0.601) and factory density (q = 0.488) exerted the greatest influence on microplastic abundance; in the interaction analysis, wind speed-road network density (q = 0.976) and solar radiation-arable land density (q = 0.963) exhibited a synergistic effect. Through statistical analysis, this study identified the contributions of nine natural and anthropogenic factors and their interaction mechanisms, thereby validating the applicability of the Geodetector in revealing the drivers of microplastic spatial distribution. Furthermore, combining APCS-MLR pollution source results with the Geodetector's driving factors provided cross-validation, further confirming the accuracy of pollution source identification.