Biossorção utilizando alga marinha (sargassum sp.) aplicada em meio orgânico

Abstract

In this work, biosorption process was used to remove heavy metals from used automotive lubricating oils by a bus fleet from Natal-RN-Brazil. This oil was characterized to determine the physical-chemistry properties. It was also characterized the used oil with the aim of determining and quantifying the heavy metal concentration. Fe and Cu were the metals existent in large concentration and these metals were choused to be studied in solubilization process. For the biosorption process was used the seaweed Sargassum sp for the study of influencing of the metals presents separately and with other metals. It was also studied the effect of the protonation treatment of alga with the objective to know the best efficiency of heavy metals removal. The study of the solubilization showed that the presence of more than a metal favors the solubilization of the metals presents in the oil and consequently, it favors the biosorption process, what becomes interesting the perspective application in the heavy metals removal in lubricating oils used, because the presence of more than a heavy metal favors the solubility of all metals present. It was observed that the iron and copper metals, which are present in large concentration, the protonated biosorbtent was more effective. In this study we used as biomass the marine alga Sargassum sp to study the influence of agitation velocity, temperature and initial biomass concentration on the removal of iron and copper from used lubricant oils. We performed an experimental design and a kinetic study. The experiments were carried out with samples of used lubricant oil and predetermined amounts of algae, allowing sufficient time for the mixture to obtain equilibrium under controlled conditions. The results showed that, under the conditions studied, the larger the amount of biomass present, the lower the adsorption capacity of the iron and of the copper, likely due to a decrease in interface contact area. The experimental design led us to conclude that a function can be obtained that shows the degree of influence of each one of the system variables