Microplastics in Freshwater Environments

<p>Plastic pollution in aquatic environments is a recognized environmental threat on a global scale and is fed by the linear economy model of “make-use-dispose,” which underpins both the fossil fuel and plastic industries. This chapter examines the issue of microplastic pollution in different freshwater environments: (i) rivers and tributaries, (ii) lakes, (iii) groundwater sources, (iv) glaciers and ice caps, and (v) deltas. Particular challenges, the geographical coverage of studies, and current knowledge gaps are highlighted for each freshwater category based on the currently available peer-reviewed literature. Sources and distribution of microplastics in freshwater bodies and associated repercussions to freshwater ecosystems and human health are also reviewed. A better understanding of microplastic interactions between human settlements and freshwater environments in different parts of the globe is required to better enact evidence-based mitigation measures that will be able to further limit the spread of microplastic pollution in the natural environment. Therefore, research on microplastic pollution in freshwater bodies around the world must be further supported to provide a reliable global database and compliant monitoring procedures. Additionally, further research can better inform policies and regulations around plastic use and emission into the environment at both the global and local scales.</p&gt

How many microplastics do you need to (sub)sample?

Analysis of microplastics in the environment requires polymer characterization as a confirmation step for suspected microplastic particles found in a sample. Material characterization is costly and can take a long time per particle. When microplastic particle counts are high, many researchers cannot characterize every particle in their sample due to time or monetary constraints. Moreover, characterizing every particle in samples with high plastic particle counts is unnecessary for describing the sample properties. We propose an a priori approach to determine the number of suspected microplastic particles in a sample that should be randomly subsampled for characterization to accurately assess the polymer distribution in the environmental sample. The proposed equation is well-founded in statistics literature and was validated using published microplastic data and simulations for typical microplastic subsampling routines. We report values from the whole equation but also derive a simple way to calculate the necessary particle count for samples or subsamples by taking the error to the power of negative two. Assuming an error of 0.05 (5 %) with a confidence interval of 95 %, an unknown expected proportion, and a sample with many particles (> 100k), the minimum number of particles in a subsample should be 386 particles to accurately characterize the polymer distribution of the sample, given the particles are randomly characterized from the full population of suspected particles. Extending this equation to simultaneously estimate polymer, color, size, and morphology distributions reveals more particles (620) would be needed in the subsample to achieve the same high absolute error threshold for all properties. The above proposal for minimum subsample size also applies to the minimum count that should be present in samples to accurately characterize particle type presence and diversity in a given environmental compartment