Capability of microalgae for local saline sewage treatment towards biodiesel production

Novel application of microalgae platform for biodesalination process: A review

Freshwater demand is rising worldwide due to largely increasing population and industrialization. Latest focus is to explore the Ocean and saline effluent from industries to produce freshwater in a sustainable way via algal desalination. Current physicochemical desalination technology is not only an energy-intensive and expensive process but also gives severe environmental impact from brine and GHGs emissions. Therefore, it is neither environmentally-friendly nor feasible to countries with limited resources. Biodesalination could be an attractive technology with recent breakthroughs in algal bioprocess with fast growth rate under highly saline conditions to effectively remove salts optimally 50-67% from saline water. Algal desalination mainly occurs through biosorption and bioaccumulation which governs by biotic and abiotic factors e.g., strain, temperature, pH, light and nutrients etc. This review provides a current scenario of this novel technology by an in-depth assessment of technological advancement, social impact, possible risks and scope for policy implications.

A pretreatment method of wastewater based on artificial intelligence and fuzzy neural network system

A pretreatment method of industrial saline wastewater based on Artificial Intelligence based fuzzy neural network analysis was proposed to improve the pretreatment accuracy of industrial saline wastewater. This method uses a four-layer AI fuzzy neural network model and proposes a graded fuzzy neural network model for pretreatment method of industrial saline wastewater, it includes input layer, fuzzification layer, fuzzy logical layer and output layer, and designs the framework and calculation mode of the fuzzy function block and the neural network module. Finally, the dynamic simulation experiments of dissolved oxygen control in the fifth zone and nitrate nitrogen control in the second zone are carried out based on the simulation benchmark model (BSM1) platform. The experimental results show that this approach can effectively raise the adaptive control accuracy of the system compared with PID, feed forward neural network and conventional recurrent neural network.

Exploration of green integrated approach for effluent treatment through mass culture and biofuel production from unicellular alga, Acutodesmus obliquus RDS01

This study deals with the open pond (OP) pilot scale treatment of cassava effluent and enhancement of Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) enzyme through CO₂ utilization by the microalga, Acutodesmus obliquus RDS01. The cassava effluent treatment (ET) revealed maximum reduction of ammonia (96.8%), calcium (94.6%), chloride (95.2%), chlorine (98.5%), inorganic phosphate (94.6%), magnesium (96.8%), nitrate (96.89%), organic carbon (95.9%), organic phosphorus (96.3%), potassium (97.9%), sodium (97.1%), and sulfate (95.4%) on 15^th day using A. obliquus. The microalga produced highest RuBisCO enzyme activity (90%), CO₂ utilization efficiency (95%), biomass (8.9 gL^-1), lipid (176.65 mg mL^-1), carbohydrate (96.78 mg mL^-1), biodiesel (4.1 mL g^-1), and bioethanol (3.7 mL g^-1) during OP treatment. The isolated RuBisCO gene (rbcL) was used to construct the protein model by homology modeling. The microalgal-lipid content was analyzed through thin layer chromatography, the biodiesel produced was analyzed using Fourier-transform infrared spectroscopy and gas chromatography mass spectrometry (GCMS). The bioethanol production was confirmed by high performance liquid chromatography and GCMS analyses. A. obliquus produced of 98.75% biodiesel and 96.83% bioethanol in the OP pilot scale treatment A. obliquus. Overall, the microalga A. obliquus could act as an effective CO₂ capturing and bioremediation agent in the cassava ET, and also for the biodiesel and bioethanol can be produced.