|Fausey, Norman - Norm|
Submitted to: Journal of Natural and Environmental Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/3/2010
Publication Date: 11/20/2010
Publication URL: http://handle.nal.usda.gov/10113/54050
Citation: Plappally, A., Soboyejo, A., Fausey, N.R., Soboyejo, W., Brown, L. 2010. Stochastic modeling of filtrate alkalinity in water filtration devices: Transport through micro/nano porous clay based ceramic materials. Journal of Natural and Environmental Science. 1(2):96-105. Interpretive Summary: Clay based ceramic filters are used around the world by millions of people for water filtration and purification. These filters produce filtered water that is very hard or alkaline during early stages of the filtering process depending upon the characteristics of the unfiltered source water and the ratio of clay to wood used in manufacturing the filters. Based on experiments conducted with six filters made from unique clay to wood ratios, a model was developed for predicting alkalinity irrespective of the ceramic material and time of filtering. Additionally, a relationship was developed to estimate pH of the filtered water based on the turbidity, temperature, and electrical conductivity of the source water; the time in use; and the flow rate through the filter. This information is useful to filter manufacturers and water treatment plant operators.
Technical Abstract: Clay and plant materials such as wood are the raw materials used in manufacture of ceramic water filtration devices around the world. A step by step manufacturing procedure which includes initial mixing, molding and sintering is used. The manufactured ceramic filters have numerous pores which help in water filtration. These filters fare well in microbial filtration but are plagued with alkalinity of filtrate during early use. Change in alkalinity between the water influent and effluent is defined by the difference in their corresponding pH. The development of alkalinity is a function of filtration time and the material property of the ceramic filtration devices discussed in this article. Macroscopic parameters such as degree of change in turbidity, electrical conductivity and temperature between the filter influent and effluent are the electro kinetic variables also used in the prediction of alkalinity. Flow rate through porous filtration devices influence alkalinity. The electro kinetic variables, flow and time are interdependent on each other. Multivariate stochastic regression technique is used to demonstrate the individual effect of these predictor variables.