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Seasonally driven dynamics of microplastic–heavy metal composite pollutants: a systematic review of cross-media processes and fates across the freshwater-to-ocean continuum
Summary
Microplastics in rivers and oceans often team up with toxic heavy metals, sticking together like tiny pollution packages, and this review of existing research shows that how much they combine, travel, and become dangerous actually changes with the seasons, based on factors like water temperature and rainfall. This matters because current pollution safety assessments typically use fixed, year-round estimates, which means they could be underestimating risk during certain seasons when these combined contaminants are more likely to build up in waterways that eventually supply our drinking water and seafood. The researchers call for smarter, season-aware monitoring to better protect both ecosystems and the people
Microplastics (MPs) and heavy metals (HMs) frequently co-occur in aquatic environments, forming binary complexes via adsorption. The environmental behavior and associated risks of these MP–HM assemblages are not static; rather, they are dynamically shaped by natural seasonal cycles. This review provides a systematic synthesis of current knowledge on how seasonal variations—governed by key physicochemical drivers such as temperature, hydrology, salinity, and light, alongside biological factors—modulate the fate, transport, and ecological impacts of MP-HM combined pollution across the critical river–estuary–ocean continuum. We examine the seasonally varying dynamics of adsorption–desorption equilibria, cross-interface transport, and transformation processes, which collectively govern pollutant source–sink patterns and risk differentiation along the continuum. The review underscores the limitations of conventional static risk assessment paradigms in capturing such spatiotemporal variability. Finally, we propose a framework for developing dynamic, seasonally informed risk models and adaptive management strategies, thereby facilitating more accurate prediction and effective life-cycle control of composite pollution under evolving environmental conditions.