Assessment of Subsampling Strategies in Microspectroscopy of Environmental Microplastic Samples

The analysis of environmental occurrence microplastic (MP) particles has gained notable attention within the past decade. An effective risk assessment MP litter requires elucidating sources particles, their pathways distribution and, ultimately, sinks. Therefore, sampling to be done in high frequency, both spatially and temporally, resulting a number samples analyze. Microspectroscopy techniques, such as FTIR imaging or Raman particle measurements allow an accurate regarding chemical classification size. However, these methods are time-consuming, which gives motivation establish subsampling protocols that require measuring less while still obtaining reliable results. challenge lies heterogeneity types relatively low numbers target particles. Herein, we present comprehensive different proposed on selection real-world from compartments. analyzed compared with respect count errors, eventually allows giving recommendations for staying acceptable error margins. Our results based microspectroscopy, but applicable any other technique. We show subsampling-errors mainly due statistical counting errors (i.e., extrapolation numbers) only edge cases additionally impacted by inhomogeneous filters. Keeping can realized increasing fraction samples.