Engineered nanomaterials for water treatment and remediation: Costs, benefits, and applicability

By A. Adeleye, J. R. Conway, Kendra L Garner, Yuxiong Huang, Yiming Su, Arturo Keller. Chemical Engineering Journal, 2016

665 citations recorded by the source corpus.

Abstract The application of nanotechnology in drinking water treatment and pollution cleanup is promising, as demonstrated by a number of field-based (pilot and full scale) and bench scale studies. A number of reviews exist for these nanotechnology-based applications; but to better illustrate its importance and guide its development, a direct comparison between traditional treatment technologies and emerging approaches using nanotechnology is needed. In this review, the performances of traditional technologies and nanotechnology for water treatment and environmental remediation were compared with the goal of providing an up-to-date reference on the state of treatment techniques for researchers, industry, and policy makers. Pollutants were categorized into broad classes, and the most cost-effective techniques (traditional and nanotechnology-based) in each category reported in the literature were compared. Where information was available, cost and environmental implications of both technologies were also compared. Case studies were also provided where traditional technologies were directly compared with nanotechnology-based technologies for the similar pollutants. Although nanotechnology-based methods are generally believed to be more expensive, we found instances where they offer cheaper and more effective alternatives to conventional techniques. In addition, nano-based techniques may become extremely important in meeting increasingly stringent water quality standards, especially for removal of emerging pollutants and low levels of contaminants. We also discuss challenges facing environmental application of nanotechnology and offer potential solutions.

Subfields: Biomedical Engineering, Health, Toxicology and Mutagenesis, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/631aea7e6db0746216794c3b4b8396616abfd2e9

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