Modelagem matemática da biossorção dos íons cu(II), ni(II) e zn(II) utilizando resíduo da extração do alginato da alga marinha argassum filipendula - Suzaki, Pedro Yahico Ramos (2017)
Adsorption has been highlighted as a simple and effective operation in the treatment of industrial effluents, especially in the removal of heavy metals at trace level, in which traditional methods are expensive and/or inefficient. One of the most important factors for the success of this operation is the adequate choice of material used as an adsorbent. In this search for efficient and inexpensive adsorbents, marine algae have received special attention. Studies have revealed that algae has potential in the removal of heavy metals. However, it might not be the best way to use this type of biomass, which is found in almost all Brazilian coast. Algae have a large amount of a commercially value biopolymer (alginate) that can be extracted and used in many types of industries. Thus, the objective of this work was to evaluate the use of the Sargassum filipendula algae residue after the extraction process of the alginate biopolymer. This study was carried out by conducting both batch and fixed bed column adsorption tests of Cu (II), Ni (II) and Zn (II) ions, as well as fitting of mathematical models for representation and comprehension of the process, seeking the identification of the mechanisms that control the mass transfer from liquid to solid phase. The adsorption process of the Cu(II), Ni(II) and Zn(II) ions was influenced by the particle size and also by the operating temperature. The granulometric range with the lowest evaluated particle diameter showed the highest removal capacity for the three evaluated metals. However, as the value was close to that obtained for the granulometric mixture, the latter group was used in the experiments. In this way, all biomass could be used in the tests. With respect to the effect of the temperature, the highest evaluated, (45!C ), resulted in the greater removal capacity. Temperatures of 25 and 35!C led to similar removal capacities obtained, so for energy savings, the temperature of 25!C was used in the subsequent experiments. In the investigation of the residue of alginate extraction of Sargassum filipendila (REA) as a biosorbent in a batch process to remove the Cu(II)-Ni(II) binary system, the Langmuir-Freundlich isotherm model adequately represented the equilibrium of metals in the liquid and solid phases. In the competition for the active sites of the biosorbent material, the Cu(II) ions expressed higher affinity with this biomass than the Ni(II) ions. The removal of Cu(II) ions was little affected by the presence of Ni(II) ions, whereas the presence of Cu (II) ions greatly limited Ni(II) ions removal capacity. The mathematical model of internal mass transfer resistance (RTMI) has adequately described process kinetics, indicating that the internal mass transfer is the rate limiting step of binary adsorption. Studies of adsorption in a fixed bed column were also performed. In the monocomponent assays of the Cu(II), Ni(II) and Zn(II) ions, the equilibrium data were appropriately represented by the Langmuir isotherm model. The highest removal was observed by the Cu(II) ions, followed by the Zn(II) and finally Ni(II) ions. The highest Cu(II) removal efficiency was demonstrated by the analysis of the rupture times, which were higher for the Cu (II) ions and very close to Ni(II) and Zn(II) ions. The mathematical model that considers the internal mass transfer resistance as the limiting step of the adsorption process adequately described the dynamic biosorption behavior in fixed bed columns for all the monocomponent systems evaluated. In the multicomponent adsorption systems the same order of removal capacity was observed: Cu(II) > Zn(II)> Ni(II). Overshoots were detected in some Zn(II) and Ni(II) ions rupture curves, confirming the lower biomass selectivity for these ions. The ternary adsorption dynamics of the Cu(II)-Ni(II)-Zn(II) system, as well as the batch binary system and fixed-bed column monocomponent systems, were satisfactorily described by the RTMI model, suggesting that diffusion also controls this adsorption process. Therefore, due to the predictive capacity in the different adsorption systems evaluated, the mathematical modeling described in this work can be applied as a tool for the analysis and design of the heavy metal adsorption process.