Mechanistic behaviour of Chlorella vulgaris biofilm formation onto waste organic solid support used to treat palm kernel expeller in the recent Anthropocene

Improvement of N and P ratio for enhanced biomass productivity and sustainable cultivation of Chlorella vulgaris microalgae

Microalgae cultivation could contribute to the achievement of several sustainable development goals (SDGs). However, cultivating Chlorella vulgaris, like any other microalgae, is challenging due to various biotic, abiotic and process related factors that can affect its growth and biomass productivity. Nutrient availability, particularly N and P, and their ratio play a crucial role in building cellular structures and maintaining metabolic processes, determining basically the maximum achievable biomass productivity under given circumstances. The present article aims to improve the N and P ratio to enhance the biomass productivity of Chlorella vulgaris microalgae as well as to characterize the biomass growth kinetics that can be used for prediction purposes. The results showed that the nutrient solutions prepared with increased nitrate concentration (T1 - N:P = 55:1 and T3 - N:P = 28:1) promoted chlorophyll formation and significantly outperformed the control sample (BG-11 - N:P = 35:1) with 192% and 183%, leading to higher biomass productivity with 1160 μg L-1 and 1103 μg L-1, respectively. Moreover, a strong positive correlation was revealed (0.81) between phosphate concentration and microalgae activity rate, indicating the role of phosphorous in energy transfer, resulted in stimulated microalgae activity rates with 71.2% and 70.66% in the phosphate-increased nutrient solutions (T2 - N:P = 14:1 and T3 - N:P = 28:1). In addition, an exponential equation was introduced to characterize the biomass growth kinetics, of which the theoretically achievable maximum chlorophyll concentration (CTAM) and the theoretical cultivation time (tcultivation) were determined for the tested nutrient solutions with variable N:P ratio. It was concluded, that the higher the N:P ratio, the higher the CTAM is, nevertheless the absolute concentration of these nutrients need to be considered as well. The introduced two key parameters could provide valuable information for decision makers regarding the optimization of growth conditions, nutrient supplementation, and harvesting, additionally decreasing the production costs and making the cultivation cycles more effective and sustainable.

Biotreatment of Industrial Wastewater using Microalgae: A Tool for a Sustainable Bioeconomy

Fresh water is one of the essential sources of life, and its requirement has increased in the past years due to population growth and industrialization. Industries use huge quantities of fresh water for their processes, and generate high quantities of wastewater rich in organic matter, nitrates, and phosphates. These effluents have contaminated the freshwater sources and there is a need to recycle this wastewater in an ecologically harmless manner. Microalgae use the nutrients in the wastewater as a medium for growth and the biomass produced are rich in nutrition that can cater growing food and energy needs. The primary and secondary metabolites of microalgae are utilized as biofuel and as active ingredients in cosmetics, animal feed, therapeutics, and pharmaceutical products. In this review, we explore food processing industries like dairy, meat, aquaculture, breweries, and their wastewater for the microalgal growth. Current treatment methods are expensive and energy demanding, which indirectly leads to higher greenhouse gas emissions. Microalgae acts as a potential biotreatment tool and mitigates carbon dioxide due to their high photosynthetic efficiency. This review aims to address the need to recycle wastewater generated from such industries and potentiality to use microalgae for biotreatment. This will help to build a circular bioeconomy by using wastewater as a valuable resource to produce valuable products.

Kinetic model derived from machine learning for accurate prediction of microalgal hydrogen production via conversion from low thermally pre-treated palm kernel expeller waste

The depletion of fossil fuel sources and increase in energy demands have increased the need for a sustainable alternative energy source. The ability to produce hydrogen from microalgae is generating a lot of attention in both academia and industry. Due to complex production procedures, the commercial production of microalgal biohydrogen is not yet practical. Developing the most optimum microalgal hydrogen production process is also very laborious and expensive as proven from the experimental measurement. Therefore, this research project intended to analyse the random time series dataset collected during microalgal hydrogen productions while using various low thermally pre-treated palm kernel expeller (PKE) waste via machine learning (ML) approach. The analysis of collected dataset allowed the derivation of an enhanced kinetic model based on the Gompertz model amidst the dark fermentative hydrogen production that integrated thermal pre-treatment duration as a function within the model. The optimum microalgal hydrogen production attained with the enhanced kinetic model was 387.1 mL/g microalgae after 6 days with 1 h thermally pre-treated PKE waste at 90 °C. The enhanced model also had better accuracy (R2 = 0.9556) and net energy ratio (NER) value (0.71) than previous studies. Finally, the NER could be further improved to 0.91 when the microalgal culture was reused, heralding the potential application of ML in optimizing the microalgal hydrogen production process.

Fundamental alteration of cellular biochemicals from attached microalgae onto palm kernel expeller waste upon optimizing the growth environment in forming adhesion complex

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.