Efficient and Scalable Detection of Microplastics in Drinking Water Using Fluorescence High‐Content Imaging

The increasing production and inadequate disposal of plastics have led to widespread microplastic presence in the environment, posing potential health risks. However, existing microplastic detection techniques often face challenges in resolution, sensitivity, speed, and complexity of extraction and microplastic identification. In this study, a rapid, high-throughput approach based on fluorescence microscopy is developed and validated to investigate the prevalence of microplastics in bottled drinking water. By utilizing Nile Red (NR) staining for fluorescence imaging, imaging the entire filtered area, machine learning for automated classification, and thermal treatment to remove false positives, microplastic concentrations up to 1.52 × 10<sup>5</sup> particles/liter and mineral microparticle concentrations up to 4.93 × 10<sup>5</sup> particles/liter are detected. Over 90% of the detected microplastics are within the smallest 1-5 µm size range, a size fraction overlooked by the Delegated Drinking Water Act (DDWA) 2024, which focuses on particles larger than 20 µm. With fewer than 1% of microplastic particles in bottled water exceeding 20 µm, these findings highlight the urgent need for more rigorous regulatory frameworks and advanced detection methods, such as the fluorescence-based approach, to ensure the safety of drinking water.

Authors

Institutions

Publication Details

Journal
Small Methods
Published
2025-05-19
DOI
https://doi.org/10.1002/smtd.202500465
Citations
1
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
0.50

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient and Scalable Detection of Microplastics in Drinking Water Using Fluorescence High‐Content Imaging

Wouter Vandezande, Imran Aslam, Maarten B. J. Roeffaers, Haifeng Yuan et al.
1 citations
Small Methods
Microplastics and Plastic Pollution
0.50
article

Efficient and Scalable Detection of Microplastics in Drinking Water Using Fluorescence High‐Content Imaging

Wouter Vandezande, Imran Aslam, Maarten B. J. Roeffaers, Haifeng Yuan, Quinten Wouters, Iris Van Den Eede
article en
1 citations

Abstract

The increasing production and inadequate disposal of plastics have led to widespread microplastic presence in the environment, posing potential health risks. However, existing microplastic detection techniques often face challenges in resolution, sensitivity, speed, and complexity of extraction and microplastic identification. In this study, a rapid, high-throughput approach based on fluorescence microscopy is developed and validated to investigate the prevalence of microplastics in bottled drinking water. By utilizing Nile Red (NR) staining for fluorescence imaging, imaging the entire filtered area, machine learning for automated classification, and thermal treatment to remove false positives, microplastic concentrations up to 1.52 × 10<sup>5</sup> particles/liter and mineral microparticle concentrations up to 4.93 × 10<sup>5</sup> particles/liter are detected. Over 90% of the detected microplastics are within the smallest 1-5 µm size range, a size fraction overlooked by the Delegated Drinking Water Act (DDWA) 2024, which focuses on particles larger than 20 µm. With fewer than 1% of microplastic particles in bottled water exceeding 20 µm, these findings highlight the urgent need for more rigorous regulatory frameworks and advanced detection methods, such as the fluorescence-based approach, to ensure the safety of drinking water.

Small MethodsVol. 10(2)
KU Leuven (BE)
Agentschap Innoveren en Ondernemen
Clean water and sanitation
Openalex Percentile: Top 40%
Microplastics and Plastic Pollution
0.50
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.