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The potential contribution of citizen science data in the study of coastal microplastic and mesoplastic distributions

Environmental Monitoring and Assessment 2025 Score: 38 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
David M. Jones, Jonathan Potts, Michelle S. Hale

Summary

Researchers analyzed citizen science data from the Big Microplastic Survey to assess the potential contribution of volunteer-collected observations to understanding coastal microplastic and mesoplastic distribution patterns, evaluating data quality and spatial coverage relative to conventional scientific monitoring.

Plastic pollution in marine environments is an escalating global issue, particularly in coastal regions where geomorphic processes and relatively high waste input can lead to significant accumulation. In this study, we analysed citizen science (CS) data from the Big Microplastic Survey (BMS), collected by volunteers across 39 countries between March 2018 and April 2024. The BMS project provided information about microplastic (MP) and mesoplastic (MEP) distributions from coastlines around the world. Using descriptive statistics, we examined volunteer participation and engagement, as well as the geographical distribution of MPs and MEPs based on characteristics and colour. Our analysis highlighted some of the challenges associated with CS projects and the importance of organisational affiliations in influencing data submission. There was substantial variability in the geographical distributions of plastics, suggesting regional pollution dynamics that were influenced by both anthropogenic and natural coastal processes. In this study, our analysis of global, regional, and localised data underscored the value of CS in augmenting traditional scientific methods, providing critical insights into coastal plastic pollution, and potentially engaging communities in environmental stewardship. We also discovered that engaging with non-governmental organisations (NGOs) was particularly effective in facilitating data collection. We advocate for a strategic focus on organisational participation in CS projects, to improve data collection and assess spatial and temporal trends more fully.

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