A standard analytical approach and establishing criteria for microplastic concentrations in wastewater, drinking water and tap water
Abstract
The ubiquitous presence of microplastics (MPs) in natural water bodies reflects the global issue regarding these micropollutants. The main problem of MPs lies on the difficulty of removing these particles from water during wastewater and drinking water treatments. The release of MPs to the environment in treated wastewater contributed to the dispersion of these micropollutants, which enhances the harmful effect of MPs on fauna and flora. In addition, their presence in tap water entails a potential risk to human health since MPs can be directly consumed. The first step is being able to quantify and characterise these microparticles accurately. In this work, a comprehensive analysis on the presence of MPs in wastewater, drinking water and tap water has been conducted with emphasis on sampling methods, pre-treatment, MP size and analytical methods. Based on literature data, a standard experimental procedure has been proposed with the objective of recommending a methodology that allows the homogenisation of MP analysis in water samples. Finally, reported MP concentrations for influents and effluents of drinking and wastewater treatment plants and tap water have been analysed, in terms of abundance, ranges and average values, and a tentative classification of different waters based on their MP concentrations is proposed.
Read the paper
Related studies
- Green Chemistry: A Framework for a Sustainable Future
- Nano/micro-plastic, an invisible threat getting into the brain
- Emerging contaminants antibiotic resistance genes and microplastics in the environment: Introduction to 21 review articles published in CREST during 2018–2022
- Water Resources and Sustainable Development
- Nano- and microplastics in the workplace
- Water Enclosure and World-Literature: New Perspectives on Hydro-Power and World-Ecology
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.