Using Data-Driven Methods and Aging Information to Quantitatively Identify Microplastic Environmental Sources and Establish a Comprehensive Discrimination Index

The global distribution of microplastics (MPs) acrossvarious environmentalcompartments has garnered significant attention. However, the differencesin the characteristics of MPs in different environments remain unclear,and there is still a lack of quantitative analysis of their environmentalsources. In addition, the inclusion of aging in source apportionmentis a novel approach that has not been widely explored. In this study,we conducted a meta-analysis of the literature from the past 10 yearsand extracted conventional and aging characteristic data of MPs from321 sampling points across 7 environmental compartments worldwide.We established a data-driven analysis framework using these data setsto identify different MP communities across environmental compartments,screen key MP features, and develop an environmental source analysismodel for MPs. Our results indicate significant differences in thecharacteristics of MP communities across environments. The key featuresof differentiation were identified using the LEfSe method and includethe carbonyl index, hydroxyl index, fouling index, proportions ofpolypropylene, white, black/gray, and film/sheet. These features werescreened for each environmental compartment. An environmental sourceidentification model was established based on these features withan accuracy of 75.1%. In order to accurately represent the single/multisourcecase in a more probabilistic manner, we proposed the MP environmentalsource index (MESI) to provide a probability estimation of the samplehaving multiple sources. Our findings contribute to a better understandingof MP migration trends and fluxes in the plastic cycle and informeffective prevention and control strategies for MP pollution. This study reports a quantitative modeland discriminantindex for source analysis at a single sampling point scale.

Automated summary

This study analyzed data from 321 sampling points worldwide and found significant differences in the characteristics of microplastics in different environments. A model for analyzing the environmental sources of microplastics was developed based on key features, providing insights for prevention and control strategies for microplastic pollution.