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Environmental condition-dependent effects of aquatic humic substances on the distribution of phenanthrene in microplastic-contaminated aquatic systems
Summary
This study examined how varying concentrations and types of aquatic humic substances influence the distribution of phenanthrene between microplastics and water, finding that humic substance composition significantly modulates contaminant partitioning in microplastic-contaminated systems.
Numerous studies have focused on the interaction between microplastics (MPs) and phenanthrene (PHE) in aquatic environments. However, the intricate roles of aquatic humic substances (HS), which vary with environmental conditions, in influencing PHE-MP interactions are not yet fully understood. This study investigates the variable and environmentally sensitive roles of HS in modifying the interactions between PHE and polyethylene (PE) MPs under laboratory-simulated aquatic conditions with varying solution chemistry, including pH, HS types, HS concentrations, and ionic strength. Our findings show that the presence of HS significantly reduces the adsorption of PHE onto both pristine and aged PE MPs, with a more pronounced reduction observed in aged PEs. This effect is highlighted by a notable decrease in the partitioning coefficient (K) of PHE, which falls from 2.60 × 10 to 1.30 × 10 L/kg on MPs in the presence of HS. The study also demonstrates that alterations in the net charge of HS solutions are crucial in modifying PHE distribution onto PEs. An initial decrease in K values at higher pH levels is reversed when HS is introduced. Furthermore, an increase in HS concentrations is associated with lower K values. In conditions of higher ionic strength, the retention of PHE by HS is intensified, likely due to an enhanced salting-out effect. This research highlights the significant role of aquatic HS in modulating the distribution of PHE in MP-polluted waters, which is highly influenced by various solution chemistry factors. The findings are vital for understanding the fate of PHE in MP-contaminated aquatic environments and can contribute to refining predictive models that consider diverse solution chemistry scenarios.
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