The global distribution of microplastics (MPs) across
various environmental
compartments has garnered significant attention. However, the differences
in the characteristics of MPs in different environments remain unclear,
and there is still a lack of quantitative analysis of their environmental
sources. In addition, the inclusion of aging in source apportionment
is a novel approach that has not been widely explored. In this study,
we conducted a meta-analysis of the literature from the past 10 years
and extracted conventional and aging characteristic data of MPs from
321 sampling points across 7 environmental compartments worldwide.
We established a data-driven analysis framework using these data sets
to identify different MP communities across environmental compartments,
screen key MP features, and develop an environmental source analysis
model for MPs. Our results indicate significant differences in the
characteristics of MP communities across environments. The key features
of differentiation were identified using the LEfSe method and include
the carbonyl index, hydroxyl index, fouling index, proportions of
polypropylene, white, black/gray, and film/sheet. These features were
screened for each environmental compartment. An environmental source
identification model was established based on these features with
an accuracy of 75.1%. In order to accurately represent the single/multisource
case in a more probabilistic manner, we proposed the MP environmental
source index (MESI) to provide a probability estimation of the sample
having multiple sources. Our findings contribute to a better understanding
of MP migration trends and fluxes in the plastic cycle and inform
effective prevention and control strategies for MP pollution.