Blanks and bias in microplastic research: Implications for future quality assurance

Abstract

The prevalence of microplastics has heightened awareness of cross-contamination concerns in recent years, making quality control and assurance critical for the quantitative assessment of microplastics. Environmental scientists dealing with microplastics employ both field and laboratory blanks to determine the extent of cross-contamination in unknown samples (samples of interest) in their analyses, but this source of uncertainty has yet to be assessed and is being overlooked. This paper intends to present: (1) an overview of the approaches for monitoring external contamination; (2) issues related to unwanted variation or bias introduced into the results; and (3) strategies for improving quality assessment procedures. Our analysis of existing evaluations of blanks in the literature revealed that methods for designing, assessing, and correcting blanks, as well as the expression of results, are likely to be inconsistent. From it, we found that blank data are potentially biased and introduce unwanted variation in unknown sample measurements, which is mostly impacted by the method of sampling, type of matrix material and extraction protocol, approximations in the observation operators used to obtain the data, limitations in characterization, and the correction itself. These findings have broad implications for implementing significant changes in future microplastic investigations, emphasizing the necessity of reducing bias in blank settings as early as the protocol design stage.