Article Details

Development of Nanomaterial Adsorbent Media and Packed Bed Column for the Arsenic Removal from Water: A Review | Original Article

P. Manasa*, K. Narasimhulu, in Anusandhan | Technology & Management

ABSTRACT:

Metal oxides nanomaterials can be synthesized using multiple synthesis techniques and the resulting media (titanate nanofibers, nanostructured spheres, and nanoparticle impregnated surfaces) can be assessed for their potential to remove an important environmental pollutant in water (arsenate). The hypothesis is that nanotechnology offers the ability to control, characterize, and tailor the fabrication of materials for specific applications. Arsenic is selected as a representative environmental pollutant because of recent regulatory changes to a lower maximum contaminant level and its ability to form strong inner-sphere complexes with metal (hydr) oxides. A comparison of different types of metal (hydr)oxide nanomaterials indicate that titanium, zirconium, and iron (hydr)oxides are the most suitable materials because of their ability to remove arsenic and low toxicity of the base metal, which potentially be released into drinking water. Several metal (hydr)oxide nanomaterial media based upon titanium, zirconium and iron can be synthesized to create hybrid ion exchange media, modified granular activated carbon media, metal (hydr)oxide nanofibers and extremely porous nanostructured spheres. Each synthesis platform produces nanomaterial media capable of being used in a pack-bed continuous flow configuration, including titanate nanofibers because they are fused together by precipitation and drying into strong media. The field of nanotechnology is rapidly evolving, and this work demonstrates how a small mass quantity of nanomaterials can be synthesized and characterized to provide data to scale-up in order to facilitate comparisons against existing technologies. The protocol includes the use of batch arsenic adsorption experiments, short bed adsorber column tests, and calculate pore surface diffusion models.