The study investigates the potential of utilizing banana trunk-derived porous activated biochar enriched with SO3H- as a catalyst for eco-friendly biodiesel production from the microalga Chlorella vulgaris. An extensive analysis, employing advanced techniques such as XRD, FTIR, TGA, XPS, NH3-TPD, BET, SEM-EDX, and TEM, was conducted to elucidate the physicochemical properties of BT-SO3H catalysts. The synthesized catalyst demonstrated its efficiency in converting the total lipids of Chlorella vulgaris into biodiesel, with varying concentrations of 3%, 5%, and 7%. Notably, using a 5% BT-SO3H concentration resulted in remarkably higher biodiesel production about 58.29%. Additionally, the fatty acid profile of C. vulgaris biodiesel indicated that C16:0 was the predominant fatty acid at 24.31%, followed by C18:1 (19.68%), C18:3 (11.45%), and C16:1 (7.56%). Furthermore, the biodiesel produced via 5% BT-SO3H was estimated to have higher levels of saturated fatty acids (SFAs) at 34.28%, monounsaturated fatty acids (MUFAs) at 30.70%, and polyunsaturated fatty acids (PUFAs) at 24.24%. These findings highlight the promising potential of BT-SO3H catalysts for efficient and environmentally friendly biodiesel production from microalgal species.
Municipal wastewater is ubiquitously laden with myriad pollutants discharged primarily from a combination of domestic and industrial activities. These heterogeneous pollutants are threating the natural environments when the traditional activated sludge system fails sporadically to reduce the pollutants' toxicities. Besides, the activated sludge system is very energy intensive, bringing conundrums for decarbonization. This research endeavoured to employ Chlorella vulgaris sp. In converting pollutants from municipal wastewater into hydrogen via alternate light and dark fermentative process. The microalgae in attached form onto 1 cm3 of polyurethane foam cubes were adopted in optimizing light intensity and photoperiod during the light exposure duration. The highest hydrogen production was recorded at 52 mL amidst the synergistic light intensity and photoperiod of 200 μmolm-2s-1 and 12:12 h (light:dark h), respectively. At this lighting condition, the removals of chemical oxygen demand (COD) and ammoniacal nitrogen were both achieved at about 80%. The sustainability of microalgal fermentative performances was verified in recyclability study using similar immobilization support material. There were negligible diminishments of hydrogen production as well as both COD and ammoniacal nitrogen removals after five cycles, heralding inconsequential microalgal cells' washout from the polyurethane support when replacing the municipal wastewater medium at each cycle. The collected dataset was finally modelled into enhanced Monod equation aided by Python software tool of machine learning. The derived model was capable to predict the performances of microalgae to execute the fermentative process in producing hydrogen while subsisting municipal wastewater at arbitrary photoperiod. The enhanced model had a best fitting of R2 of 0.9857 as validated using an independent dataset. Concisely, the outcomes had contributed towards the advancement of municipal wastewater treatment via microalgal fermentative process in producing green hydrogen as a clean energy source to decarbonize the wastewater treatment facilities.