Potencial do uso de biossurfactantes no tratamento de água contaminada com metais tóxicos pelo método de extração de fases

Abstract

The advancement of industrial processes has increased the presence of heavy metals in the environment, and the characteristics like toxicity, abundance, prevalence in the environment and non-biodegradability of these elements has provoked the attention of the global society. The technology used to reduce the heavy metals in aquatic environments are of great importance for purpose the removal of these compounds in the environment, because these systems, in most cases, are the receivers of the metals, through industrial effluents and environmental accidents. In this context, the removal of metals based on surfactant emulsion membrane (SEM) proved to be effective in the Pb (II) like as removal of other metals. The present work studied the removal of iron, zinc and manganese metals using SEM produced using Cystofilo basidium and Pseudomonas aeruginosa fermented mediums as source of not purified biosurfactant and different chemical composition of SEM as regarding addition of NaCl, NaOH, HCl and di-(2-ethylhexyl)phosphoric acid. Removals were found to be satisfactory on basic and acid conditions, but in basic conditions part of metal removal was related to not soluble metal compounds. Following the fact the significant removal was related to precipitation in basic membranes it has been chosen to study acid form and a central composite design (CCD) with EDTA, sodium chloride, H2SO4, di-(2-ethylhexyl)phosphoric acid and time as variables, and five levels was proposed for iron and manganese metals, which a maximum removal was 30% to iron and 25% to manganese. An artificial neural network (ANN) descriptive model of removal of metals was studied using artificial bee colony methodology optimization (ABCoptim) found the maximum removal to iron and manganese were, respectively, 48 and 33%. Regarding the conditions found for these removal values, the tests were carried out experimentally for the removal of these metals, for the validation of the model, a value of 36% of removal was obtained for manganese, with a relative error of 10%, being these removals, values higher than those found in the literature for this metal.