Literature DB >> 17489270

Removal of arsenic from drinking water by chemical precipitation--a modeling and simulation study of the physical-chemical processes.

Parimal Pal1, Sk Ziauddin Ahammad, Abhinandan Pattanayak, Pinaki Bhattacharya.   

Abstract

A dynamic mathematical model was developed for removal of arsenic from drinking water by chemical coagulation-precipitation and was validated experimentally in a bench-scale set-up. While examining arsenic removal efficiency of the scheme under different operating conditions, coagulant dose, pH and degree of oxidation were found to have pronounced impact. Removal efficiency of 91-92% was achieved for synthetic feed water spiked with 1 mg/L arsenic and pre-oxidized by potassium permanganate at optimum pH and coagulant dose. Model predictions corroborated well with the experimental findings (the overall correlation coefficient being 0.9895) indicating the capability of the model in predicting performance of such a treatment plant under different operating conditions. Menu-driven, user-friendly Visual Basic software developed in the study will be very handy in quick performance analysis. The simulation is expected to be very useful in full-scale design and operation of the treatment plants for removal of arsenic from drinking water.

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Year:  2007        PMID: 17489270     DOI: 10.2175/106143006x111754

Source DB:  PubMed          Journal:  Water Environ Res        ISSN: 1061-4303            Impact factor:   1.946


  2 in total

1.  Purifying arsenic and fluoride-contaminated water by a novel graphene-based nanocomposite membrane of enhanced selectivity and sustained flux.

Authors:  Madhubonti Pal; Mrinal Kanti Mondal; Tapan Kanti Paine; Parimal Pal
Journal:  Environ Sci Pollut Res Int       Date:  2018-03-29       Impact factor: 4.223

2.  Arsenic removal from contaminated groundwater by membrane-integrated hybrid plant: optimization and control using Visual Basic platform.

Authors:  S Chakrabortty; M Sen; P Pal
Journal:  Environ Sci Pollut Res Int       Date:  2013-11-28       Impact factor: 4.223

  2 in total

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