The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency and sustainability of wastewater treatment plants (WWTPs). This paper explores the application of ANN-based models in WWTPs, focusing on the latest published research work, by presenting the effectiveness of ANNs in predicting, estimating, and treatment of diverse types of wastewater. Furthermore, this review comprehensively examines the applicability of the ANNs in various processes and methods used for wastewater treatment, including membrane and membrane bioreactors, coagulation/flocculation, UV-disinfection processes, and biological treatment systems. Additionally, it provides a detailed analysis of pollutants viz organic and inorganic substances, nutrients, pharmaceuticals, drugs, pesticides, dyes, etc., from wastewater, utilizing both ANN and ANN-based models. Moreover, it assesses the techno-economic value of ANNs, provides cost estimation and energy analysis, and outlines promising future research directions of ANNs in wastewater treatment. AI-based techniques are used to predict parameters such as chemical oxygen demand (COD) and biological oxygen demand (BOD) in WWTP influent. ANNs have been formed for the estimation of the removal efficiency of pollutants such as total nitrogen (TN), total phosphorus (TP), BOD, and total suspended solids (TSS) in the effluent of WWTPs. The literature also discloses the use of AI techniques in WWT is an economical and energy-effective method. AI enhances the efficiency of the pumping system, leading to energy conservation with an impressive average savings of approximately 10%. The system can achieve a maximum energy savings state of 25%, accompanied by a notable reduction in costs of up to 30%.
Conventionally, increasing the yield of microalgal biomass has been the primary focus of research, while the significant protein reserve within this biomass has remained largely unexplored. This protein reserve possesses substantial value and versatility, offering a wide range of prospective applications and presenting an enticing chance for innovation and value enhancement for various sectors. Current study employed an innovative research approach that focused solely on the LCA of protein production potential from microalgal biomass, a lesser-explored aspects within this domain. Most environmental impact categories were shown to be significantly affected by cultivation phase because of the electrical obligation, followed by the harvesting and protein extraction phase. Still, the environmental aspect was seen to yield a minimal impact on global warming potential, i.e., 4 × 10-3 kg CO2, underscoring the ecologically favorable nature of the process. Conversely, the overall energy impact was seen to intensify with NEB of - 39.33 MJ and NER of 0.49, drawing attention to the importance of addressing the energy aspect to harness the full potential of microalgal protein production.
Biohydrogen as one of the most appealing energy vector for the future represents attractive avenue in alternative energy research. Recently, variety of biohydrogen production pathways has been suggested to improve the key features of the process. Nevertheless, researches are still needed to overcome remaining barriers to practical applications such as low yields and production rates. Considering practicality aspects, this review emphasized on anaerobic membrane bioreactors (AnMBRs) for biological hydrogen production. Recent advances and emerging issues associated with biohydrogen generation in AnMBR technology are critically discussed. Several techniques are highlighted that are aimed at overcoming these barriers. Moreover, environmental and economical potentials along with future research perspectives are addressed to drive biohydrogen technology towards practicality and economical-feasibility.
Current study had made a significant progress in microalgal wastewater treatment through the implementation of an economically viable polyethylene terephthalate (PET) membrane derived from plastic bottle waste. The membrane exhibited an exceptional pure water flux of 156.5 ± 0.25 L/m2h and a wastewater flux of 15.37 ± 0.02 L/m2h. Moreover, the membrane demonstrated remarkable efficiency in selectively removing a wide range of residual parameters, achieving rejection rates up to 99%. The reutilization of treated wastewater to grow microalgae had resulted in a marginal decrease in microalgal density, from 10.01 ± 0.48 to 9.26 ± 0.66 g/g. However, this decline was overshadowed by a notable enhancement in lipid production with level rising from 181.35 ± 0.42 to 225.01 ± 0.11 mg/g. These findings signified the membrane's capacity to preserve nutrients availability within the wastewater; thus, positively influencing the lipid synthesis and accumulation within microalgal cells. Moreover, the membrane's comprehensive analysis of cross-sectional and surface topographies revealed the presence of macropores with a highly interconnected framework, significantly amplifying the available surface area for fluid flow. This exceptional structural attribute had substantially contributed to the membrane's efficacy by facilitating superior filtration and separation process. Additionally, the identified functional groups within the membrane aligned consistently with those commonly found in PET polymer, confirming the membrane's compatibility and efficacy in microalgal wastewater treatment.
The capacity to maximize the proliferation of microalgal cells by means of topologically textured organic solid surfaces under various pH gave rise to the fundamental biophysical analysis of cell-surface attachment in this study. The substrate used in analysis was palm kernel expeller (PKE) in which the microalgal cells had adhered onto its surface. The findings elucidated the relevance of surface properties in terms of surface wettability and surface energy in relation to the attached microalgal growth with pH as the limiting factor. The increase in hydrophobicity of PKE-microalgae attachment was able to facilitate the formation of biofilm better. The pH 5 and pH 11 were found to be the conditions with highest and lowest microalgal growths, respectively, which were in tandem with the highest contact angle value at pH 5 and conversely for pH 11. The work of attachment (Wcs) had supported the derived model with positive values being attained for all the pH conditions, corroborating the thermodynamic feasibility. Finally, this study had unveiled the mechanism of microalgal attachment onto the surface of PKE using the aid of extracellular polymeric surfaces (EPS) from microalgae. Also, the hydrophobic nature of PKE enabled excellent attachment alongside with nutrients for microalgae to grow and from layer-by-layer (LbL) assembly. This assembly was then isolated using organosolv method by means of biphasic solvents, namely, methanol and chloroform, to induce detachment.
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.
Changing the growth environment for microalgae can overall lead to the fundamental alteration in cellular biochemicals whilst attaching onto palm kernel expeller (PKE) waste to form adhesion complex in easing harvesting at stationary growth phase. This study had initially optimized the PKE dosage, light intensity and photoperiod in maximizing the attached microalgal productivity being attained at 0.72 g/g day. Lipid content increased progressively from pH 3 to pH 11, with the highest value observed at pH 11. Meanwhile, in terms of protein and carbohydrate contents, the highest values were obtained by cultivation medium of pH 5 with 9.92 g and 17.72 g, respectively followed by pH 7 with 9.16 g and 16.36 g, respectively. Moreover, the findings also suggested that the low pH mediums utilized polar interactions in the formation of complexes between PKE and microalgae, whereas at higher pH levels, the non-polar interactions became more significant. The work of attachment was thermodynamically favourable towards the attachment formation with values greater than zero which was also aligned with the microscopic surface topography, i.e., revealing a clustering pattern of microalgae colonizing the PKE surface. These findings contribute to comprehensive understanding of optimizing growth condition and harvesting strategy of attached microalgae in attaining the cellular biochemical components, facilitating the development of efficient and sustainable bioresource utilization.