Quantifying microplastics and other microparticles is a matter of interest in the field of environmental science. Stereomicroscopy is one of the most common methods to identify and enumerate micro-size particles. However, the process of enumerating an entire environmental sample can be tedious and time-consuming, especially when target particles are abundant. Here we present a method to develop a subsampling strategy and spreadsheet-based tool to speed up the process of microparticle enumeration while maintaining particle count accuracy. We first identified the pattern in which tire road wear particles (TRWPs) from environmental samples were distributed on a filter when vacuum-plated, then used particle abundance within relatively homogeneous subsection arrangements to establish stratified random subsampling schemes. We describe a repeated sampling experiment using count data to test the stratified design and illustrate the relationship between the fraction of the filter counted (sample size) with accuracy and variance in the extrapolated total sample count and the corresponding analyst time savings when applied to analyzing TRWPs isolated from sediments. Based on the results, a particle enumeration tool was created in Microsoft Excel Visual BasicⓇ configured using a 47 mm gridded filter, and the source is available for free modification under the same open license.•Vacuum-plated microparticles are often highly abundant and not homogenously distributed across a filter.•A random sampling selection data tool was created using knowledge of particle distribution.•Method describes how to structure and use partial filter counts to extrapolate for total particle enumeration.
Keywords: Filter; Method for the enumeration of microparticles on a gridded filter using a stratified random sampling tool; Microparticles; Microplastics; Microscopy; Particle distribution; Particle enumeration; Patterned distribution; Stereomicroscopy; Stratified random sampling; Tire particles.
© 2023 The Authors. Published by Elsevier B.V.