AI Article Synopsis

  • * Current ILCs often struggle with variability due to the difficulty of producing identical samples, which complicates uncertainty measurement.
  • * The authors propose a filtration-immobilization technique that allows the same sample to be measured across different labs, showing a 77% reduction in measurement uncertainty compared to traditional ILC methods, with potential applications for archiving and creating reference samples in other areas of research.

Article Abstract

Microplastics have gained importance as pervasive environmental particulate pollutants. Their analysis demands precise quantification methods, with interlaboratory comparisons (ILCs) being crucial for performance assessment. Typically, ILCs follow a parallel design: participants each analyze their own sample specimen, often with significant variability due to challenges in producing identical subsamples of the particulate analyte, inseparably masking the relevant uncertainty sources the ILC intends to measure. We provide a filtration-immobilization approach for particles ≤100 μm, creating permanently immobilized microplastics samples. This enables serial ILC designs where participants sequentially measure the same sample. Demonstrating the concept using 5 polymers immobilized on 10 μm pore-sized silicon filters, we expose the specific measurement uncertainty being 77% lower than the total combined uncertainty observed in a parallel ILC (relative standard deviations: 5 and 23%, respectively). Particle immobilization opens further applications in sample archiving and creation of durable reference samples also for other fields of particulate matter research beyond microplastics.

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Source
http://dx.doi.org/10.1021/acs.est.4c09427DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11656703PMC

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