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Assessment, characterization, and quantification of microplastics from urban rivers (Zarjub and Goharrood), Rasht, Iran
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Scientists found extremely high levels of tiny plastic bits, mostly from clothing fibers, in two city rivers in Iran after rainfall, with the worst pollution near factories and busy neighborhoods. This matters because these rivers likely feed into water supplies and ecosystems, meaning these plastics could eventually end up in our drinking water or food chain.
Abstract Microplastic (MP) pollution is an emerging environmental concern that affects aquatic ecosystems worldwide, with rivers acting as important pathways for the transport of plastic debris. This study investigated the concentration and characteristics of MPs in the two main urban rivers of Rasht City, northern Iran: the Zarjub and Goharrood rivers. Surface water samples were collected as single‑event, non‑replicated grab samples during one winter day following a rainfall event, aiming to provide an event‑based characterization of MP occurrence under post‑rainfall, high‑runoff conditions. MPs were extracted using density separation followed by hydrogen peroxide digestion, visually identified under a stereomicroscope, and polymer types were determined using micro‑Raman spectroscopy. MP abundances ranged from 53,700 to 82,200 items m⁻³ in the Zarjub River and from 66,900 to 111,100 items m⁻³ in the Goharrood River, with mean concentrations being higher in the Goharrood River. In both rivers, MPs were predominantly colorless, followed by black and blue, and fibers represented the most common shape, followed by fragments. The two smaller size classes (< 0.5 and 0.5–1 mm) accounted for more than 80% of the detected MPs. Polyamide was the most abundant polymer type, followed by polypropylene, polyethylene, polystyrene, and polyvinyl chloride. Higher MP abundances were observed at sampling stations located near industrial areas, densely populated residential zones, and commercial activities; however, these spatial patterns are interpreted as indicative associations rather than definitive source attribution, as no direct source apportionment was performed.
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