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Can Water Constituents Be Used as Proxy to Map Microplastic Dispersal Within Transitional and Coastal Waters?
Summary
Researchers tested whether measurable water quality parameters such as turbidity and chlorophyll could serve as indirect proxies for predicting microplastic distribution in coastal and transitional waters using remote sensing data. Results showed limited predictive power, suggesting that microplastic monitoring cannot reliably be inferred from water clarity measures alone.
Due to high spatiotemporal variability of aquatic ecosystems, relationships between microplastic sources and sinks are highly complex and transportation pathways yet to be understood. Field data acquisitions are a necessary component for monitoring of microplastic contamination but alone cannot capture such complex relationships. Remote sensing is a key technology for environmental monitoring through which extrapolation of spatially limited field data to larger areas can be obtained. We tested whether microplastic distribution follows the same movement pattern as water constituents depictable from Landsat-8, Sentinel-2, and RapidEye satellite images, namely chlorophyll-a, suspended particulate matter, and colored dissolved organic matter, and if they can be utilized as proxies. As rivers are a major source for marine microplastic contamination, we sampled three example river systems: the lower courses and river mouths of the Trave and Elbe estuary in Germany and the Po delta in Italy. For a full quantitative analysis of microplastics (>300 µm), ATR- and FPA-based µFTIR spectroscopy and NIR imaging spectroscopy were utilized. A comparison of water constituents with in-situ data using regression analysis showed no consistent pattern. Only for the Trave river, a positive relationship between microplastics and water constituents was present. Differences in hydrodynamic conditions and spatiotemporal dynamics of water constituents and microplastic emissions among the rivers are possible explanations for the contrary results. The lower detection limit of 300 µm for microplastics could also have influenced relationships as microplastic abundance exponentially increases with decreasing size class. Further studies with improved sampling methods are necessary to assess our proposed method.