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Enumeration of microparticles on a gridded filter using a stratified random sampling tool

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 t...

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Autores principales: Paterson, Kayli, Silverstan, Michael, Beckingham, Barbara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407279/
https://www.ncbi.nlm.nih.gov/pubmed/37560403
http://dx.doi.org/10.1016/j.mex.2023.102284
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author Paterson, Kayli
Silverstan, Michael
Beckingham, Barbara
author_facet Paterson, Kayli
Silverstan, Michael
Beckingham, Barbara
author_sort Paterson, Kayli
collection PubMed
description 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(Ⓡ) • 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.
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spelling pubmed-104072792023-08-09 Enumeration of microparticles on a gridded filter using a stratified random sampling tool Paterson, Kayli Silverstan, Michael Beckingham, Barbara MethodsX Environmental Science 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(Ⓡ) • 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. Elsevier 2023-07-08 /pmc/articles/PMC10407279/ /pubmed/37560403 http://dx.doi.org/10.1016/j.mex.2023.102284 Text en © 2023 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Environmental Science
Paterson, Kayli
Silverstan, Michael
Beckingham, Barbara
Enumeration of microparticles on a gridded filter using a stratified random sampling tool
title Enumeration of microparticles on a gridded filter using a stratified random sampling tool
title_full Enumeration of microparticles on a gridded filter using a stratified random sampling tool
title_fullStr Enumeration of microparticles on a gridded filter using a stratified random sampling tool
title_full_unstemmed Enumeration of microparticles on a gridded filter using a stratified random sampling tool
title_short Enumeration of microparticles on a gridded filter using a stratified random sampling tool
title_sort enumeration of microparticles on a gridded filter using a stratified random sampling tool
topic Environmental Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407279/
https://www.ncbi.nlm.nih.gov/pubmed/37560403
http://dx.doi.org/10.1016/j.mex.2023.102284
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