Abstract

The proliferation of anthropogenic activities around the Central Iranian Rivers shows a warning alarm of river microplastic (MP) pollution. In the Zayandeh-rood River, the mean abundance of sedimentary MPs trapped at the mouth of 21 modified sub-catchments was 588 items/kg d.w and followed the order: downstream (1701 items/kg d.w) > midstream (269.2 items/kg d.w) > upstream (57.2 items/kg d.w). The widespread distribution of fiber and fragment forms across all stations and the high MP abundance near the discharge of the largest wastewater treatment plant indicate their origin from both point and non-point sources. Using the linear multiple linear regression (MLR) and nonlinear artificial neural network (ANN), we assessed the contribution of three types of variables including the sediment physio-chemical properties, river geometry and land-use characteristics. According to both modeling results, the mean annual number of local people and tourist visitors (0.35 million people) are the most important determinants of river MP pollution whose contribution dominates through the use of plastic products and their direct and indirect release into the environment. The ANN model (R2 = 0.99) outperformed the MLR model (R2 = 0.80) and showed the importance of total organic carbon (TOC)-rich regions as MP hotspots. To alleviate the river MP pollution, suggested measures involve altering plastic usage and disposal practices among visitors and reducing the TOC content in the industrial/municipal wastewater entering the river.

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