Tertiary treatment of coke-oven wastewater using suspended and immobilized whole live cells of constructed bacterial-microalgal consortium: modeling and optimization using ANN-GA hybrid methodology

Coke oven wastewater treatment using polymeric and ceramic membranes

This research is aimed to investigate the efficacy of membrane separation technology in treating coke oven wastewater (COW). A comparative study was conducted using three types of membranes: commercial polymeric (CP) membrane, commercial ceramic (CC) membrane, and synthesized ceramic (SC) membrane. The potential of the SC membrane in COW treatment was assessed in comparison to the CC membrane, which had a molecular weight cut-off (MWCO) of 1 Kilo-Dalton. The experiments were conducted under various trans-membrane pressure (TMP) conditions ranging from 1 to 4 bar. Additionally, the effect of the CP membrane on COW treatment was examined at TMP levels ranging from 5 to 25 bar. The research findings revealed that the SC membrane exhibited promising results in terms of permeability and flux compared to the CC membrane. Also, a significant reduction was observed in various water parameters such as TSS decreased by 89.74%, chlorides by 8.24%, nitrogen by 10%, and hardness by 22%. Moreover, the study was carried out by implementing an anti-fouling mechanism to mitigate fouling effects on membrane performance.

Advanced treatment of antibiotic-polluted wastewater by a consortium composed of bacteria and mixed cyanobacteria

This study constructed a cyanobacteria-bacteria consortium using a mixture of non-toxic cyanobacteria (Synechococcus sp. and Chroococcus sp.) immobilized in calcium alginate and native bacteria in wastewater. The consortium was used for the advanced treatment of sulfamethoxazole-polluted wastewater and the production of cyanobacterial lipid. Mixed cyanobacteria increased the abundances of denitrifying bacteria and phosphorus-accumulating bacteria as well as stimulated various functional enzymes in the wastewater bacterial community, which efficiently removed 70.01-71.86% of TN, 91.45-97.04% of TP and 70.72-76.85% of COD from the wastewater. The removal efficiency of 55.29-69.90% for sulfamethoxazole was mainly attributed to the upregulation of genes encoding oxidases, reductases, oxidoreductases and transferases in two cyanobacterial species as well as the increased abundances of Stenotrophomonas, Sediminibacterium, Arenimonas, Novosphingobium, Flavobacterium and Hydrogenophaga in wastewater bacterial community. Transcriptomic responses proved that mixed cyanobacteria presented an elevated lipid productivity of 33.90 mg/L/day as an adaptive stress response to sulfamethoxazole. Sediminibacterium, Flavobacterium and Exiguobacterium in the wastewater bacterial community may also promote cyanobacterial lipid synthesis through symbiosis. Results of this study proved that the mixed cyanobacteria-bacteria consortium was a promising approach for advanced wastewater treatment coupled to cyanobacterial lipid production.

Application of response surface Methodology coupled with Artificial Neural network and genetic algorithm to model and optimize symbiotic interactions between Chlorella vulgaris and Stutzerimonas stutzeri strain J3BG for chlorophyll accumulation

Research on microalgae has surged due to its diverse biotechnological applications and capacity for accumulating bioactive compounds. Despite considerable advancements, microalgal cultivation remains costly, prompting efforts to reduce expenses while enhancing productivity. This study proposes a cost-effective approach through the coculture of microalgae and bacteria, exploiting mutualistic interactions. An engineered consortium of Chlorella vulgaris and Stutzerimonas stutzeri strain J3BG demonstrated biofilm-like arrangements, indicative of direct cell-to-cell interactions and metabolite exchange. Strain J3BG's enzymatic characterization revealed amylase, lipase, and protease production, sustaining mutual growth. Employing Response Surface Methodology (RSM), Artificial Neural Network (ANN), and Genetic Algorithm (GA) in a hybrid modeling approach resulted in a 2.1-fold increase in chlorophyll production. Optimized conditions included a NaNO3 concentration of 128.52 mg/l, a 1:2 (Algae:Bacteria) ratio, a 6-day cultivation period, and a pH of 5.4, yielding 10.92 ± 0.88 mg/l chlorophyll concentration.