Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm.

This study investigates the use of microalgae as a biosorbent to eliminate heavy metals ions from wastewater. The Chlorella kessleri microalgae species was employed to biosorb heavy metals from synthetic wastewater specimens. FTIR, and SEM/XRD analyses were utilized to characterize the microalgal biomass (the adsorbent). The experiments were conducted with several process parameters, including initial solution pH, temperature, and microalgae biomass dose. In order to secure the best experimental conditions, the optimum parameters were estimated using an integrated response surface methodology (RSM), desirability function (DF), and crow search algorithm (CSA) modeling approach. A maximum lead(II) removal efficiency of 99.54% was identified by the RSM-DF platform with the following optimal set of parameters: pH of 6.34, temperature of 27.71 °C, and biomass dosage of 1.5 g L-1. The hybrid RSM-CSA approach provided a globally optimal solution that was similar to the results obtained by the RSM-DF approach. The consistency of the model-predicted optimum conditions was confirmed by conducting experiments under those conditions. It was found that the experimental removal efficiency (97.1%) under optimum conditions was very close (less than a 5% error) to the model-predicted value. The lead(II) biosorption process was better demonstrated by the pseudo-second order kinetic model. Finally, simultaneous removal of metals from wastewater samples containing a mixture of multiple heavy metals was investigated. The removal efficiency of each heavy metal was found to be in the following order: Pb(II) > Co(II) > Cu(II) > Cd(II) > Cr(II).

Optimization of bio-cement production from cement kiln dust using microalgae.

The main aim of this study was to maximize bio-cement (CaCO3) production through a waste feedstock of cement kiln dust (CKD) as a source of calcium by deployment of microalgae sp. Chlorella kessleri. The effect of process parameters such as temperature, pH and time-intervals of microalgae cultivation, were set as criteria that ultimately subscribe to a process of optimization. In this regard, a single factor experiments integrated with response surface methodology (RSM) via central composite design (CCD) was considered. A quadratic model was developed to predict the maximum CaCO3 yield. A ceiling of 25.18 g CaCO3 yield was obtained at an optimal set of 23 °C, pH of 10.63 and day-9 of microalgae culture. Under these optimized conditions, maximum 96% calcium was extracted from CKD. FTIR, XRD and EDS analyses were conducted to characterize the CaCO3 precipitates. Compressive modes of mechanical testing seemed to hold conventional cement complimented by CaCO3 co-presence markedly superior to mere cement performance as far as compressive strength is concerned. The latter criterion exhibited further increase in correspondence with rise in cement to bio-cement ratio. This investigative endeavour at hand offers a simple pivotal platform on the basis of which a scale-up of microalgae-infested bio-cement production might be facilitated in conjunction with the added benefit of alleviation in environmental pollution through cement waste utilization.