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The study of microplastics (MPs) in soils is impeded by similarities between plastic and non-plastic particles and the misidentification of MP by current analytical methods such as visual microscopic examination. Soil MPs pose serious ecological and public health risks because of their abundance, persistence, and ubiquity. Thus, reliable identification methods are badly needed for scientific study. One possible solution is UV–Vis–NIR spectroscopy, which has the ability to rapidly identify and quantify concentrations of soil microplastics. In this study, a full-range, field portable spectrometer (350–2500 nm) with ultra-high spectral resolution (1.5 nm, 3.0 nm, and 3.8 nm) identified three types of common plastics: low-density polyethylene (LDPE), polyvinyl chloride (PVC), and polypropylene (PP). Three sets of artificially MP-treated vermiculite soil samples were prepared for model prediction testing and validation: 150 samples for model calibration and 50 samples for model validation. A partial least square regression model using the spectral signatures for quantification of soil and MP mixtures was built with all three plastic polymers. Prediction R2 values of all three polymers showed promising results: polypropylene R2 = 0.943, polyvinyl chloride R2 = 0.983, and polyethylene R2 = 0.957. Our study supports previous work showing that combining ultra-high-resolution UV–Vis–NIR spectrometry with quantitative modeling can improve the accuracy and speed of MP identification and quantification in soil. [ABSTRACT FROM AUTHOR]

The New River Basin (NRB) of Tennessee has many rare endemic aquatic communities. One such community is that of freshwater mussels, which are experiencing a precipitous population decline due to the fouling and pollution of their freshwater systems. Silos containing live individuals of the nonnative Asian clams (Corbicula fluminea) were placed in several localities in streams of the NRB that receive mine drainage. This drainage is commonly associated with elevated conductivity typical of pollution that may impair native mussel health. This study of five impacted streams within the NRB, and a control stream of similar ecology, uses a stepwise multiple regression analysis to test this association. After accounting for factors such as temperature, results confirm that growth rates of these sentinel clams are significantly related to conductivity, and that these clams may be useful bioindicators of stream habitat quality for native mussels. KEY WORDS: aquatic ecology, bioindicating species, coal mining, conductivity, conservation, Corbicula fluminea, endemic species, freshwater mussels, invasive species, native species, pollution, sentinel species, stream habitat, INTRODUCTION Coal mining has many impacts on aquatic ecosystems, including acidification, metal loading, and fly ash disposal (Giam et al. 2018). Surface mining can be especially harmful, impairing freshwater resources [...]