Mariana Diaconu

Experimental analysis and mathematical prediction of Cd(II) removal by biosorption using support vector machines and genetic algorithms

We investigated the bioremoval of Cd(II) in batch mode, using dead and living biomass of Trichoderma viride. Kinetic studies revealed three distinct stages of the biosorption process. The pseudo-second order model and the Langmuir model described well the kinetics and equilibrium of the biosorption process, with a determination coefficient, R(2)>0.99. The value of the mean free energy of adsorption, E, is less than 16 kJ/mol at 25 °C, suggesting that, at low temperature, the dominant process involved in Cd(II) biosorption by dead T. viride is the chemical ion-exchange. With the temperature increasing to 40-50 °C, E values are above 16 kJ/mol, showing that the particle diffusion mechanism could play an important role in Cd(II) biosorption. The studies on T. viride growth in Cd(II) solutions and its bioaccumulation performance showed that the living biomass was able to bioaccumulate 100% Cd(II) from a 50 mg/L solution at pH 6.0. The influence of pH, biomass dosage, metal concentration, contact time and temperature on the bioremoval efficiency was evaluated to further assess the biosorption capability of the dead biosorbent. These complex influences were correlated by means of a modeling procedure consisting in data driven approach in which the principles of artificial intelligence were applied with the help of support vector machines (SVM), combined with genetic algorithms (GA). According to our data, the optimal working conditions for the removal of 98.91% Cd(II) by T. viride were found for an aqueous solution containing 26.11 mg/L Cd(II) as follows: pH 6.0, contact time of 3833 min, 8 g/L biosorbent, temperature 46.5 °C. The complete characterization of bioremoval parameters indicates that T. viride is an excellent material to treat wastewater containing low concentrations of metal.

Rhizobacteria and plant symbiosis in heavy metal uptake and its implications for soil bioremediation

Certain species of plants can benefit from synergistic effects with plant growth-promoting rhizobacteria (PGPR) that improve plant growth and metal accumulation, mitigating toxic effects on plants and increasing their tolerance to heavy metals. The application of PGPR as biofertilizers and atmospheric nitrogen fixators contributes considerably to the intensification of the phytoremediation process. In this paper, we have built a system consisting of rhizospheric Azotobacter microbial populations and Lepidium sativum plants, growing in solutions containing heavy metals in various concentrations. We examined the ability of the organisms to grow in symbiosis so as to stimulate the plant growth and enhance its tolerance to Cr(VI) and Cd(II), to ultimately provide a reliable phytoremediation system. The study was developed at the laboratory level and, at this stage, does not assess the inherent interactions under real conditions occurring in contaminated fields with autochthonous microflora and under different pedoclimatic conditions and environmental stresses. Azotobacter sp. bacteria could indeed stimulate the average germination efficiency of Lepidium sativum by almost 7%, average root length by 22%, average stem length by 34% and dry biomass by 53%. The growth of L. sativum has been affected to a greater extent in Cd(II) solutions due its higher toxicity compared to that of Cr(VI). The reduced tolerance index (TI, %) indicated that plant growth in symbiosis with PGPR was however affected by heavy metal toxicity, while the tolerance of the plant to heavy metals was enhanced in the bacteria-plant system. A methodology based on artificial neural networks (ANNs) and differential evolution (DE), specifically a neuro-evolutionary approach, was applied to model germination rates, dry biomass and root/stem length and proving the robustness of the experimental data. The errors associated with all four variables are small and the correlation coefficients higher than 0.98, which indicate that the selected models can efficiently predict the experimental data.

Comparison of Rhodotorula sp. and Bacillus megaterium in the removal of cadmium ions from liquid effluents

Abstract This study compares the capacity of Rhodotorula sp. and Bacillus megaterium for Cd(II) removal considering the influence of operating parameters (pH, biosorbent dosage, contact time, temperature, initial metal concentration in solution). The highest Cd(II) uptake of 14.2 mg/g by Rhodotorula sp. was exhibited at 30°C, when working at pH 6 and with 5 g/l biosorbent dosage, after 48 h of contact time. In these conditions, a removal efficiency of 85% was obtained. Similar outcomes were obtained for B. megaterium (15.1 mg/g, 90%) at 35°C, pH 4 and 3 g/l biosorbent dosage, considered as the optimum set of parameters, equilibrium being achieved for a contact time of 20 min. The possible interaction mechanisms between the biosorbents and Cd(II) were evaluated through point of zero charge (pHpzc), Fourier transform infrared (FTIR), spectroscopy and scanning electron microscopy coupled with energy dispersive X-ray microanalysis (SEM-EDX). Data were modeled using pseudo-first and pseudo-second order kinetic models and Langmuir and Freundlich isotherms models. Further studies considered a modeling approach based on linear regression with Durbin-Watson statistics, while the accuracy and precision of experiments were evaluated by ANOVA.