Performance evaluation and optimization of flocculation process for removing heavy metal
[Display omitted] •Dual-functional flocculant with pH resistant is synthesized and used to remove heavy metals.•Flocculation conditions for reaching high removal efficiencies are optimized.•Optimal operation modulus was identified using 8 Key performance indicators by 3E triangle model.•Multi-object...
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Veröffentlicht in: | Chemical engineering journal (Lausanne, Switzerland : 1996) Switzerland : 1996), 2020-04, Vol.385, p.123911, Article 123911 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | [Display omitted]
•Dual-functional flocculant with pH resistant is synthesized and used to remove heavy metals.•Flocculation conditions for reaching high removal efficiencies are optimized.•Optimal operation modulus was identified using 8 Key performance indicators by 3E triangle model.•Multi-objective programming optimization model was also established to evaluate Operation strategies.•Flocculation for heavy metal removal is superior in terms of engineering performance.
Carboxymethyl chitosan (CMCTS) with active hydroxyl and amino groups is easily modified for chelating and capturing heavy metal, thus showing great potential for application in heavy metal-contaminated wastewater treatment. In this work, a dual-functional MACA copolymer [CMCTS-graft-P(AM-TGA)] with pH resistant was successfully designed and prepared by grafting acrylamide and thioglycolic acid onto CMCTS through UV-initiated graft polymerization. The spectroscopy characterization of functional groups and apparent morphology confirm the successful preparation of MACA. Flocculation conditions for reaching high removal efficiencies and investigating chelation capacity are optimized. A multiobjective evaluation model and a triangular environmental impact, economic benefit, and energy consumption (3E) evaluation model were established and employed to assess the 3E performance of MACA in heavy metal-contaminated wastewater flocculation. Optimal operation modulus is identified using 8 Key performance indicators by 3E triangle model. This work enriches knowledge about flocculation and provides guidance for flocculation parameter control. |
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ISSN: | 1385-8947 1873-3212 |
DOI: | 10.1016/j.cej.2019.123911 |