Source tracking, pollution load, and risk assessment of microplastics pollution in agricultural soils of Bangladesh using machine learning and multi-matrix approaches.
Journal:
Environmental pollution (Barking, Essex : 1987)
Published Date:
Jan 9, 2026
Abstract
Microplastics (MPs) contamination in agricultural soils has emerged as a critical environmental challenge, particularly in Bangladesh, where agriculture underpins food security and trade. This study provides one of the first comprehensive assessments of MPs in agricultural land, highlighting both their prevalence and ecological risks. A total of 64 soil samples were collected from eight areas from January to February 2024. Our findings reveal that MPs are present at concerning levels (2887.81 ± 1027.23 MP/kg dw), with fibres, small-sized particles (0.1-0.5 mm), transparent MPs overwhelmingly dominant and polyethene, polystyrene, and polypropylene identified as the most abundant polymers. Importantly, risk indices such as the Pollution Load Index (PLI) and Nemerow Pollution Index (NPI) consistently indicated medium to severe contamination. At the same time, the Polymeric Hazard Index showed that over 80 % of the study area is exposed to very high polymer-associated ecological risks. The SEM-EDS analysis confirmed the presence of secondary MPs alongside toxic elements such as Hg, Cr, As, and Cd, underscoring the potential for MPs to act as vectors of hazardous substances. Furthermore, multivariate and machine learning approaches (Random Forest and XGBoost)identified agricultural practices-particularly the use of bio-fertilisers and plastic inputs-as the dominant contributors. Soil properties, including electrical conductivity, salinity, pH, and organic carbon, emerged as key controlling factors, demonstrating the utility of data-driven models for risk estimation. By combining traditional risk indices with advanced analytical and predictive tools, this study not only establishes the scale of MPs contamination in Bangladeshi agricultural soils but also provides actionable insights into its drivers and agricultural implications-identifying pollution hotspots, which enhance sustainable farming practices and targeted interventions to mitigate MPs pollution.
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