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Microplastic distribution and risk assessment in soil environment across Asian regions
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Orientador(es)
Resumo(s)
Plastic pollution has emerged as a growing global environmental problem in recent years. As a major region for plastic production and consumption, Asia is at the forefront of this challenge. Although multiple studies have focused on microplastic (MP) pollution in aquatic systems in the region, understanding of their distribution characteristics and ecological impacts in terrestrial ecosystems remains limited, particularly at an intercontinental scale. In addition, standardized ecological risk assessment methods and predictive frameworks for soil microplastics (MPs) remain lacking. This study investigated the spatiotemporal distribution of MP pollution in Asian countries, focusing on the differences between various regions in terms of quantity density, morphological characteristics (shape, size, and color), and land-use types. By integrating data from 128 studies published between 2018 and 2025, totaling 3370 sampling points, a comprehensive database was constructed to reveal the MP distribution patterns and potential risks. The analysis found significant spatial heterogeneity in Asian regions, with higher concentrations found in South Eastern Asia (8227.55 items/kg), Eastern Asia (3122.73 items/kg), and Southern Asia (2407.07 items/kg). The highest quantity densities of MPs were found in industrial and urban soils (4995.2 and 4359.6 items/kg), followed by agricultural soils (2812.8 items/kg), shedding light on the influence of intensive human activities and plastic inputs. In terms of morphological characteristics, fragments, fibers, and films shaped MPs predominated in most soils, with white, transparent, and black particles being the most common. Moreover, the analysis suggested possible vertical migration and gradual accumulation of MPs within soil profiles. Based on spatial distribution and morphological characteristics, this study evaluated the ecological risk using pollution load index and potential ecological risk index suggesting that certain regions may exhibit comparatively higher reported risk levels under the present assessment framework, particularly in Viet Nam, Indonesia, India, Iran, Bangladesh, and China, based on the currently available dataset. Lastly, machine learning models were applied for preliminary classification of soil MP ecological risk levels, with the random forest model showing the highest accuracy (99.5%), followed by GBDT (98.6%) and KNN (88.4%). This study provides spatial evidence for risk-oriented and predictive assessment of soil MP pollution across Asia and offers data support for future management and policy interventions.
Descrição
Palavras-chave
Plastic pollution Asian soils Spatiotemporal distribution Polymer characteristics Ecological risk assessment
Contexto Educativo
Citação
Editora
Elsevier