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Microplastics contamination in water supply system and treatment processes. | LitMetric

Microplastics contamination in water supply system and treatment processes.

Sci Total Environ

Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Viet Nam; Vietnam National University Ho Chi Minh (VNU-HCM), Linh Trung ward, Ho Chi Minh City 700000, Viet Nam. Electronic address:

Published: May 2024

AI Article Synopsis

  • Millions of tons of plastics lead to microplastic particles entering the environment, contaminating water supplies, including bottled water.
  • Current technologies struggle to effectively remove microplastics from drinking water, raising concerns about their potential negative effects on human health.
  • There’s a need for comprehensive management strategies that combine current treatment technologies with approaches like life-cycle assessment and machine learning to tackle the microplastic issue.

Article Abstract

Due to global demand, millions of tons of plastics have been widely consumed, resulting in the widespread entry of vast amounts of microplastic particles into the environment. The presence of microplastics (MPs) in water supplies, including bottled water, has undergone systematic review, assessing the potential impacts of MPs on humans through exposure assessment. The main challenges associated with current technologies lie in their ability to effectively treat and completely remove MPs from drinking and supply water. While the risks posed by MPs upon entering the human body have not yet been fully revealed, there is a predicted certainty of negative impacts. This review encompasses a range of current technologies, spanning from basic to advanced treatments and varying in scale. However, given the frequent detection of MPs in drinking and bottled water, it becomes imperative to implement comprehensive management strategies to address this issue effectively. Consequently, integrating current technologies with management options such as life-cycle assessment, circular economy principles, and machine learning is crucial to eliminating this pervasive problem.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2024.171793DOI Listing

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