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Solving the Nonalignment of Methods and Approaches Used in Microplastic Research to Consistently Characterize Risk
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Researchers proposed and tested methods to rescale microplastic data collected using different sampling and analysis approaches, addressing the lack of standardization that hampers comparisons across studies. They developed correction factors to account for differences in particle size ranges, sampling volumes, and analytical techniques. The study provides practical tools for harmonizing microplastic research data, which could significantly improve global pollution assessments.
The lack of standard approaches in microplastic research limits progress in the abatement of plastic pollution. Here, we propose and test rescaling methods that are able to improve the alignment of methods used in microplastic research. We describe a method to correct for the differences in size ranges as used by studies reporting microplastic concentrations and demonstrate how this reduces the variation in aqueous-phase concentrations caused by method differences. We provide a method to interchange between number, volume, and mass concentrations using probability density functions that represent environmental microplastic. Finally, we use this method to correct for the incompatibility of data as used in current species sensitivity distributions (SSDs), caused by differences in the microplastic types used in effect studies and those in nature. We derived threshold effect concentrations from such a corrected SSD for freshwater species. Comparison of the rescaled exposure concentrations and threshold effect concentrations reveals that the latter would be exceeded for 1.5% of the known surface water exposure concentrations worldwide. Altogether, this toolset allows us to correct for the diversity of microplastic, to address it in a common language, and to assess its risks as one environmental material.
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