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An integrated, tiered microplastic workflow, supporting rapid broadscale detection options

MethodsX 2025 Score: 38 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Maddison Carbery, Maddison Carbery, Marina Santana S. Lynch, Marina Santana Maddison Carbery, Maddison Carbery, Maddison Carbery, Maddison Carbery, Maddison Carbery, Maddison Carbery, Marina Santana Marina Santana S. Lynch, Marina Santana Marina Santana Maddison Carbery, Maddison Carbery, Marina Santana Marina Santana Marina Santana Marina Santana Marina Santana Marina Santana Maddison Carbery, Maddison Carbery, Christyl C. Johnson, Christyl C. Johnson, Marina Santana Marina Santana Marina Santana Marina Santana Marina Santana Marina Santana Marina Santana Marina Santana Maddison Carbery, Edwina Foulsham, Marina Santana Edwina Foulsham, Maddison Carbery, Maddison Carbery, Maddison Carbery, Edwina Foulsham, Edwina Foulsham, Christyl C. Johnson, Christyl C. Johnson, Maddison Carbery, Maddison Carbery, Keegan Vickers, Keegan Vickers, Keegan Vickers, Keegan Vickers, Keegan Vickers, Maddison Carbery, Shivanesh Rao, Shivanesh Rao, Marina Santana Maddison Carbery, Marina Santana Maddison Carbery, Marina Santana Keegan Vickers, Jaimie Loa-Kum-Cheung, Maddison Carbery, Marina Santana Marina Santana Keegan Vickers, Jaimie Loa-Kum-Cheung, Jaimie Loa-Kum-Cheung, Keegan Vickers, Jaimie Loa-Kum-Cheung, Maddison Carbery, Edwina Foulsham, Maddison Carbery, Edwina Foulsham, Maddison Carbery, Maddison Carbery, Maddison Carbery, Edwina Foulsham, Edwina Foulsham, Alessandra L. Suzzi, Keegan Vickers, Marina Santana Marina Santana Alessandra L. Suzzi, Keegan Vickers, Alessandra L. Suzzi, Alessandra L. Suzzi, L. S. Hill, L. S. Hill, L. S. Hill, L. S. Hill, Neil Doszpot, Neil Doszpot, Neil Doszpot, Neil Doszpot, Rajitha Athukorala, Rajitha Athukorala, Rajitha Athukorala, Rajitha Athukorala, Uthpala Pinto, Uthpala Pinto, Keegan Vickers, Keegan Vickers, Keegan Vickers, Keegan Vickers, Maddison Carbery, Maddison Carbery, Maddison Carbery, Maddison Carbery, Marina Santana Marina Santana S. Lynch, S. Lynch, Marina Santana

Summary

Researchers developed an integrated, tiered microplastic analytical workflow supporting rapid broadscale detection options, designed to enable coordinated and harmonized large-scale monitoring initiatives that address current limitations in assessing microplastic presence, distribution, and environmental impacts.

With growing concerns regarding microplastic pollution, there is an urgent need to improve understanding of their presence, distribution, and environmental impacts. This necessitates more coordinated and harmonised large-scale microplastic monitoring initiatives. However, such assessments are traditionally expensive, labour-intensive, and hindered by a lack of standardised sampling and analytical protocols, which impede rapid, yet accurate identification of microplastic sources and ecological risks. To improve environmental microplastic contamination estimates, this study proposes a rapid, cost-effective, and bulk-processing approach within a criteria-driven Tiered Microplastics Workflow (TMW). This approach enables the efficient quantification of microplastic contamination in estuarine surface waters, offering adaptable levels of analytical resolution, that is scalable for environmental monitoring. Key features of the TMW include:•: sieving, digestion, density separation, vacuum degassing, size-classed filtration, Nile Red staining, and automated fluorescent particle counts via a Python script, enabling 24 samples to be processed in five days.• Enabling microplastic identification in broadscale monitoring within a 20 % error margin. Script-based microplastic counts align with FTIR results (R² = 0.83).• Sample processing can be paused and switched to other analytical methods while maintaining data comparability ensuring data harmonisation.

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