International Journal of Environmental Sciences

Volume 2 Issue 3 2012           Pages: 1344 - 1354

Formulation of kinetic model to predict disinfection of water by using natural herbs

Author Information:

Sunil B. Somani - Department of Environmental Science, The University of Burdwan,
Golapbag 713104, West Bengal, India

Nitin W.Ingole- Department of Environmental Science, The University of Burdwan, Golapbag 713104, West Bengal, India

ABSTRACT
This study investigated the enhancement of disinfection by using natural herbs other than chemical methods in rural/tribal area of India, where peoples are reluctant to use chemical as a disinfectant. The antimicrobial activity of Anjan (Hardwickia Binata), Mutha (Cyperus Rotundus), Ushir (Andropogon Muricatus) and Rajkashtaka (Luffa Cyllindrica) were tested by Disc Diffusion Method (Kirby –Bauer Method) after extracting the dried material powder of natural herbs in 50% alcohol (ethanol). An antibacterial activity was observed in all herbs used. Most effective an antibacterial activity was observed in Anjan. In all herbs maximum removal of E.coli was found at 30 minutes optimum contact time onwards and at 1% optimum concentration of different herbs extract used in study. As the disinfection kinetic models are the basis for assessing the disinfectants performance, the experimental results were used to derive suitable kinetic model. Chick Watson model obtained for Anjan: Log (N/No) = - 0.17Ct was found very close to chlorine which is widely use as a disinfectant.

Keywords : Disinfection, Antibacterial activity, Natural Herbs, Extract, Kinetic Model

DOI: 10.6088/ijes.00202030021


© 2012 Copyright Sunil B. Somani and Nitin W.Ingole, licensee IPA.This is an open access article distributed under the Creative Commons Attribution License (2.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The electronic version of the article can be downloaded below.

Full text pdf

View next article

SocialTwist Tell-a-Friend