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AbstractMicroplastic pollution is one of the greatest environmental concerns for contemporary times and the future. In the last years, the number of publications about microplastic contamination has increased rapidly and the list is daily updated. However, the lack of standard analytical approaches might generate data inconsistencies, reducing the comparability among different studies. The present study investigates the potential of two image processing tools (namely the shapeR package for R and ImageJ 1.52v) in providing an accurate characterization of the shape of microplastics using a restricted set of shape descriptors. To ascertain that the selected tools can measure small shape differences, we perform an experiment to verify the detection of pre-post variations in the shape of different microplastic types (i.e., nylon [NY], polyethylene [PE], polyethylene terephthalate [PET], polypropylene [PP], polystyrene [PS], and polyvinylchloride [PVC]) treated with mildly corrosive chemicals (i.e., 10% KOH at 60 °C, 30% H2O2 at 50 °C, and 15% H2O2 + 5% HNO3 at 40 °C; incubation time ≈ 12 h). Analysis of surface area variations returns results about the vulnerability of plastic polymers to digestive solutions that are aligned with most of the acquired knowledge. The largest decrease in surface area occurs for KOH-treated PET particles, while NY results in the most susceptible polymer to the 30% H2O2 treatment, followed by PVC and PS. PE and PP are the most resistant polymers to all the used treatments. The adopted methods to characterize microplastics seem reliable tools for detecting small differences in the shape and size of these particles. Then, the analytic perspectives that can be developed using such widely accessible and low-cost equipment are discussed.

AbstractThe Caspian Sea hosts areas of high ecological value as well as industrial, leisure, and agricultural activities that dump into the water body different kinds of pollutants. In this complex context, a proper description of the origin and potential sources of pollution is necessary to address management and mitigation actions aimed at preserving the quality of the water resource and the integrity of the ecosystems. Here, we aimed at detecting sources of both nitrogen inputs, by N stable isotope analysis of macroalgae, and metals in macroalgae and sediments in two highly anthropized coastal stretches at the Iranian side of the Caspian Sea. Sampling was done near the mouth of rivers and canals draining agricultural and urbanized areas. In the westernmost waters, facing a port city, low macroalgal δ15N signatures indicated industrial fertilizers as the principal source of pollution. By contrast, in the central coastal waters, facing touristic areas, the high macroalgal δ15N indicated N inputs from wastewaters. Here the lowest dissolved oxygen concentrations in waters were associated with excess dissolved inorganic nitrogen. Metal concentrations varied largely in the study areas and were lower in macroalgae than in sediments. Localized peaks of Pb and Zn in sediments were observed in the central coastal sites as probable byproducts of mining activity transported downstream. By contrast, Cr and Ni concentrations were high in all sampling sites, thus potentially representing hazardous elements for marine biota. Overall, macroalgal δ15N coupled with metal analysis in macroalgae and sediments was useful for identifying the main sources of pollution in these highly anthropized coastal areas. This double approach in comprehensive monitoring programs could thus effectively inform stakeholders on major environmental threats, allowing targeted management measures.