Optimization of CO2 Biofixation by Chlorella vulgaris Using a Tubular Photobioreactor

Hybrid support vector regression and crow search algorithm for modeling and multiobjective optimization of microalgae-based wastewater treatment

Microalgae-based wastewater treatment (and biomass production) is an environmentally benign and energetically efficient technique as compared to traditional practices. The present study is focused on optimization of the major treatment variables such as temperature, light-dark cycle (LD), and nitrogen (N)-to-phosphate (P) ratio (N/P) for the elimination of N and P from tertiary municipal wastewater utilizing Chlorella kessleri microalgae species. In this regard, a hybrid support vector regression (SVR) technique integrated with the crow search algorithm has been applied as a novel modeling/optimization tool. The SVR models were formulated using the experimental data, which were furnished according to the response surface methodology with Box-Behnken Design. Various statistical indicators, including mean absolute percentage error, Taylor diagram, and fractional bias, confirmed the superior performance of SVR models as compared to the response surface methodology (RSM) and generalized linear model (GLM). Finally, the best SVR model was hybridized with the crow search algorithm for single/multi-objective optimizations to acquire the global optimal treatment conditions for maximum N and P removal efficiencies. The best-operating conditions were found to be 29.3°C, 24/0 h/h of LD, and 6:1 of N/P, with N and P elimination efficiencies of 99.97 and 93.48%, respectively. The optimized values were further confirmed by new experimental data.

Novel Pilot-Scale Technology for Refinery Flare Flue Gas Carbon Capture and Storage Using Cost-Effective Adsorbents

This paper introduced the use of two new adsorbents, Akrosorb soda-lime and Bentonite clay, for refinery flare flue gas capture and storage. This study also developed a novel pilot plant model with 409.7149 kg/h capacity refinery flare emission capture with a novel adsorption column configuration using Akrosorb soda-lime and Bentonite clay adsorbents. The flare flue gas adsorption unit was designed, fabricated, test run, and commissioned. The adsorption column temperature is 28 ± 10 °C and has a pressure of 131.7 kPa. The novel plant RSM optimization result shows that 93.24% of CO2 and 62.18% of CO were absorbed, while 86.14% of NOx and 55.87% of HC were absorbed. The established optimum conditions of CO2, NOx, HC, and CO removal efficiency are 22 °C, 2 atm, and 60 min. The variation in flare gas emission could impact the removal efficiency of the plant. The results show the maximum adsorption ability or capacity of 314.30 mg/g, and 68.90 mg/g was reached at 60 min for Akrosorb soda-lime and molded Bentonite adsorbents. Therefore, the developed novel technology for CO2 and other GHG capture is technically feasible and friendly. The combined usage of both adsorbents will enhance the capture of GHG at a low cost compared to using Akrosorb alone as an adsorbent.

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

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CKD with microalgae sp. Chlorella kessleri is investigated for maximum bio-cement yields.

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A predictive quadratic model was developed for CaCO₃ yield with R² value of c.a. 92%.

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Low temperature and high pH were found to be important parameters in RSM study.

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Under optimal set, a maximum of 96% Ca was extracted experimentally from CKD.

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FTIR, XRD and EDS analysis confirmed the produced bio-cement compound.

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.