STUDIES ON THE INHIBITORS, EFFECTING THE BIODEGRADATION OF PHENOL

Abstract

Phenolic wastes are produced in the plastics, coke, and petroleum refining industries. Since phenol bestows an unpleasant taste on drinking water, and moreover is toxic for numerous living organisms, the requirements of the various countries are most rigid as to the phenol content of the final waste discharges. Conventional methods of treatment for phenolic wastes have been largely chemical or physical, but these processes have led to secondary effluent problems. Biological treatment for the bulk removal of these pollutants is therefore generally preferred using various microorganisms. Also, these processes provide reduced cost of operation. However, difficulties arise when both phenol and other chemical pollutants(organic or inorganic) are present simultaneously in industrial wastewaters. These chemicals may have varying inhibition effects on the biodegradation of phenol. Even though a significant amount of information on degradation of phenol and toxicity of organic and inorganic chemicals is available in the literature, there is a need for more research on the phenol biodegradation in the presence of these chemicals. In the present study, heavy metals(chromium, copper, iron and zinc) have been selected as the chemical pollutants to study the inhibition offered by them on the phenol degradation process. In the present work, it has been found that in the presence of the inhibitors, the degradation rate of phenol decreased appreciably. The removals for 0.02% initial iii concentration of phenol decreased from 96%(in the absence of any inhibitor) to 84% in the presence of zinc inhibitor, 54% when chromium was the inhibitor, 50% and 23.5% for iron and copper, respectively. Thus, copper inhibited the biodegradation of phenol the most, followed by iron, chromium and zinc. However, the pathway of degradation of phenol was observed to be the same. Also, the kinetic parameters (Km , Vmax , and K1 ) for the heavy metals were determined using the inhibition models. These matched well with the Lineweaver-Burk plots and V versus V/S plots using the experimental data.