Arsenic Separation by a Membrane-Integrated Hybrid Treatment System: Modeling, Simulation, and Techno-Economic Evaluation

A modeling and simulation study along with economic analysis was carried out for arsenic separation by a membrane-integrated hybrid treatment system that consisted of an oxidation unit integrated with a cross flow nanofiltration membrane module. About 96–98% arsenic removal efficiency was achieved in the membrane module after pre-oxidation. When pH was increased from 3 to 10, arsenic rejections reached as high as 98.5%. The dynamic mathematical model developed for the system used Extended Nernst-Plank equation as the basis for the nanofiltration model. A linearized approach in modeling was adopted that reduced the computation time significantly. Model predictions were found to corroborate very well with the experimental findings as indicated in the small relative errors of the order of only 0.003 and Willmott d-index of 0.993 reflecting very good model performance. Thus the developed model is expected to be very useful in scale-up, design and optimization of the membrane-integrated hybrid treatment system for removal of arsenic from contaminated groundwater.

[1]  P. Pal,et al.  Treatment of arsenic-contaminated groundwater by a low cost activated alumina adsorbent prepared by partial thermal dehydration , 2009 .

[2]  W. Giger,et al.  Arsenic contamination of groundwater and drinking water in Vietnam: a human health threat. , 2001, Environmental science & technology.

[3]  L. Dresner.  Some remarks on the integration of the extended Nernst-Planck equations in the hyperfiltration of multicomponent solutions , 1972 .

[4]  S. Maity,et al.  Metal contents in the groundwater of Sahebgunj district, Jharkhand, India, with special reference to arsenic. , 2005, Chemosphere.

[5]  W. Richard Bowen,et al.  Diafiltration by nanofiltration: Prediction and optimization , 1998 .

[6]  F. Pontius.  New horizons in federal regulation , 1998 .

[7]  S. Z. Ahammad,et al.  Removal of Arsenic from Drinking Water by Chemical Precipitation – A Modeling and Simulation Study of the Physical‐Chemical Processes , 2007, Water environment research : a research publication of the Water Environment Federation.

[8]  B. Van der Bruggen,et al.  Application of nanofiltration for removal of pesticides, nitrate and hardness from ground water: rejection properties and economic evaluation , 2001 .

[9]  Parimal Pal,et al.  ARSEPPA: A Visual Basic software tool for arsenic separation plant performance analysis , 2007 .

[10]  T. Urase,et al.  Modeling of arsenic rejection considering affinity and steric hindrance effect in nanofiltration membranes , 2000 .

[11]  A. P. Padilla,et al.  Effect of operating conditions in removal of arsenic from water by nanofiltration membrane , 2005 .

[12]  Eric M. Vrijenhoek,et al.  Arsenic removal from drinking water by a “loose” nanofiltration membrane , 2000 .

[13]  W. Richard Bowen,et al.  Modelling the performance of membrane nanofiltration - critical assessment and model development , 2002 .

[14]  G. Hagmeyer,et al.  Modelling the rejection of nanofiltration membranes using zeta potential measurements , 1999 .

[15]  Parimal Pal,et al.  Removal of arsenic from contaminated groundwater by solar-driven membrane distillation. , 2010, Environmental pollution.

[16]  Parimal Pal,et al.  Contamination of groundwater by arsenic: a review of occurrence, causes, impacts, remedies and membrane-based purification , 2009 .

[17]  Parimal Pal,et al.  Removal of arsenic from contaminated groundwater by membrane-integrated hybrid treatment system , 2010 .

[18]  A. Mohammad,et al.  Analysis of the Salt Retention of Nanofiltration Membranes Using the Donnan–Steric Partitioning Pore Model , 1999 .

[19]  A. Foissy,et al.  Retention of mineral salts by a polyamide nanofiltration membrane , 2003 .