Microalgae in a global world: New solutions for old problems?

An experimental investigation and modeling approach of response surface methodology coupled with crow search algorithm for optimizing the properties of jute fiber reinforced concrete

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).

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

Microbially induced carbonate precipitation, an eco-friendly and energy-efficient technology, has attracted many researchers' attention because of its potential use for soil solidification, crack repair and concrete self-repair, etc. In this study, the feasibility of using enhanced co-culture of Chlorella sp. and Sporosaricina pasteurii under mixotrophic conditions to induce carbonate precipitation was investigated. The effects of different growing conditions on microbial growth and their relationship with microbially induced carbonate precipitation were evaluated. The results showed that under optimal growth conditions of algae-bacteria inoculation volume ratio of 3:2 (v/v), initial pH value of 9.0 and glucose concentration of 1 g.L−1, the algae-bacteria co-culture system was able to effectively induce carbonate precipitation and the Chlorella sp. biomass in the co-culture system was significantly improved by 37.74%. The Ca2+ rate was reduced by 60.4% in the co-culture system, which was higher than that in the mono-culture system. The calcification rate constant in the co-culture was 0.3514. The crystalline mineral particles were calcite crystals as determined by X-ray diffraction. It was observed through a scanning electron microscope that mineral particles piled up together and some microbial cells were deposited on the crystal surface. These results suggest that microbially induced carbonate precipitation through Chlorella-Sporosaricina co-culture is feasible, but more studies are necessary to understand mechanisms and optimize the process.

Feasibility of microbially induced carbonate precipitation through a Chlorella-Sporosaricina co-culture system

Carbon capture and storage (CCS) is an attractive area of research in such fields as CO2 mineral carbonation, global warming and sustainable energy systems. In this study, carbonation efficiency for aqueous mineral carbonation (MC) was achieved through two steps, which include leaching of calcium from cement kiln dust (CKD) followed by the reaction of pure CO2 with the calcium hydroxide precipitates formed by the hydroxylation using NaOH. Response surface methodology (RSM) with a Box-Behnken design (BBD) was applied to optimize the calcium leaching yield, while the carbonation efficiency from CKD was assessed using RSM with central composite design (CCD). Optimization of calcium leaching is highly important, as it is a rate-limiting reaction step in MC and also influences and enhances carbonation efficiency. Different parameters including acid concentration (HNO3), leaching temperature, leaching time, and dose of CKD sample were considered in order to optimize the maximum yield of Ca leaching from the CKD sample. In addition, different CO2 flow rates and temperatures were used as parameters for optimizing carbonation efficiency. Two quadratic regression models were developed for each process, i.e. calcium leaching and carbonation. For calcium leaching, a maximum of 98.55% calcium was extracted under the optimal set of acid concentration 4.13 M, 90 °C, 28 min leaching time, and 13.8 g of CKD sample. For carbonation, the maximum carbonation efficiency of 89.2% was achieved for a CO2 flow rate of 1163 cm3/min at 90 °C. Calcium leaching results indicate that the leaching yield was significantly affected by all the input parameters except leaching time. For carbonation, both factors affected the carbonation efficiency, with the effect temperature shown to be greater than that of the CO2 flow rate. Additionally, the predicted results agreed well with the experimental values for both calcium leaching and carbonation processes, with errors of less than 1% and 5%, respectively.

Modeling and Optimization of Aqueous Mineral Carbonation for Cement Kiln Dust Using Response Surface Methodology Integrated with Box-Behnken and Central Composite Design Approaches

F. Sadaf

Papers

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