Ensuring representative sample volume predictions in microplastic monitoring
Abstract A large body of literature is available quantifying microplastic contamination in freshwater and marine systems across the globe. “Microplastics” do not represent a single analyte. Rather, they are usually operationally defined based on their size, polymer and shape, dependent on the sample...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Microplastics and Nanoplastics |
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| Online Access: | https://doi.org/10.1186/s43591-024-00109-2 |
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| author | Richard K. Cross Sarah L. Roberts Monika D. Jürgens Andrew C. Johnson Craig W. Davis Todd Gouin |
| author_facet | Richard K. Cross Sarah L. Roberts Monika D. Jürgens Andrew C. Johnson Craig W. Davis Todd Gouin |
| author_sort | Richard K. Cross |
| collection | DOAJ |
| description | Abstract A large body of literature is available quantifying microplastic contamination in freshwater and marine systems across the globe. “Microplastics” do not represent a single analyte. Rather, they are usually operationally defined based on their size, polymer and shape, dependent on the sample collection method and the analytical range of the measurement technique. In the absence of standardised methods, significant variability and uncertainty remains as to how to compare data from different sources, and so consider exposure correctly. To examine this issue, a previously compiled database containing 1603 marine observations and 208 freshwater observations of microplastic concentrations from across the globe between 1971 and 2020 was analysed. Reported concentrations span nine orders of magnitude. Investigating the relationship between sampling methods and reported concentrations, a striking correlation between smaller sample unit volumes and higher microplastic concentrations was observed. Close to half of the studies reviewed scored poorly in quality scoring protocols according to the sample volume taken. It is critical that sufficient particles are measured in a sample to reduce the errors from random chance. Given the inverse relationship with particle size and abundance, the volume required for a representative sample should be calculated case-by-case, based on what size microplastics are under investigation and where they are being measured. We have developed the Representative Sample Volume Predictor (RSVP) tool, which standardises statistical prediction of sufficient sample volumes, to ensure microplastics are detected with a given level of confidence. Reviewing reports in freshwater, we found ~ 12% of observations reported sample volumes which would have a false negative error rate > 5%. Such sample volumes run the risk of wrongly concluding that microplastics are absent in samples and are not sufficient to be quantitative. The RSVP tool also provides a harmonised Poisson point process estimation of confidence intervals to test whether two observations are likely to be significantly different, even in the absence of replication. In this way, we demonstrate application of the tool to evaluate historic data, but also to assist in new study designs to ensure that environmental microplastic exposure data is relevant and reliable. The tool can also be applied to other data for randomly dispersed events in space or time, and so has potential for transdisciplinary use. Graphical Abstract |
| format | Article |
| id | doaj-art-5af920f09bfe4d47b785f0f107f32e46 |
| institution | Kabale University |
| issn | 2662-4966 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Microplastics and Nanoplastics |
| spelling | doaj-art-5af920f09bfe4d47b785f0f107f32e462025-01-26T12:13:27ZengSpringerOpenMicroplastics and Nanoplastics2662-49662025-01-015111410.1186/s43591-024-00109-2Ensuring representative sample volume predictions in microplastic monitoringRichard K. Cross0Sarah L. Roberts1Monika D. Jürgens2Andrew C. Johnson3Craig W. Davis4Todd Gouin5UK Centre for Ecology and HydrologyUK Centre for Ecology and HydrologyUK Centre for Ecology and HydrologyUK Centre for Ecology and HydrologyExxonMobil Biomedical Sciences, IncTG Environmental ResearchAbstract A large body of literature is available quantifying microplastic contamination in freshwater and marine systems across the globe. “Microplastics” do not represent a single analyte. Rather, they are usually operationally defined based on their size, polymer and shape, dependent on the sample collection method and the analytical range of the measurement technique. In the absence of standardised methods, significant variability and uncertainty remains as to how to compare data from different sources, and so consider exposure correctly. To examine this issue, a previously compiled database containing 1603 marine observations and 208 freshwater observations of microplastic concentrations from across the globe between 1971 and 2020 was analysed. Reported concentrations span nine orders of magnitude. Investigating the relationship between sampling methods and reported concentrations, a striking correlation between smaller sample unit volumes and higher microplastic concentrations was observed. Close to half of the studies reviewed scored poorly in quality scoring protocols according to the sample volume taken. It is critical that sufficient particles are measured in a sample to reduce the errors from random chance. Given the inverse relationship with particle size and abundance, the volume required for a representative sample should be calculated case-by-case, based on what size microplastics are under investigation and where they are being measured. We have developed the Representative Sample Volume Predictor (RSVP) tool, which standardises statistical prediction of sufficient sample volumes, to ensure microplastics are detected with a given level of confidence. Reviewing reports in freshwater, we found ~ 12% of observations reported sample volumes which would have a false negative error rate > 5%. Such sample volumes run the risk of wrongly concluding that microplastics are absent in samples and are not sufficient to be quantitative. The RSVP tool also provides a harmonised Poisson point process estimation of confidence intervals to test whether two observations are likely to be significantly different, even in the absence of replication. In this way, we demonstrate application of the tool to evaluate historic data, but also to assist in new study designs to ensure that environmental microplastic exposure data is relevant and reliable. The tool can also be applied to other data for randomly dispersed events in space or time, and so has potential for transdisciplinary use. Graphical Abstracthttps://doi.org/10.1186/s43591-024-00109-2Exposure assessmentRisk assessmentQualityEnvironmental samplingReviewAquatic environment |
| spellingShingle | Richard K. Cross Sarah L. Roberts Monika D. Jürgens Andrew C. Johnson Craig W. Davis Todd Gouin Ensuring representative sample volume predictions in microplastic monitoring Microplastics and Nanoplastics Exposure assessment Risk assessment Quality Environmental sampling Review Aquatic environment |
| title | Ensuring representative sample volume predictions in microplastic monitoring |
| title_full | Ensuring representative sample volume predictions in microplastic monitoring |
| title_fullStr | Ensuring representative sample volume predictions in microplastic monitoring |
| title_full_unstemmed | Ensuring representative sample volume predictions in microplastic monitoring |
| title_short | Ensuring representative sample volume predictions in microplastic monitoring |
| title_sort | ensuring representative sample volume predictions in microplastic monitoring |
| topic | Exposure assessment Risk assessment Quality Environmental sampling Review Aquatic environment |
| url | https://doi.org/10.1186/s43591-024-00109-2 |
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