Effect of light/dark cycle on nitrate and phosphate removal from synthetic wastewater based on BG11 medium by Scenedesmus sp

Microalgal consortium tolerance to bisphenol A and triclosan in wastewater and their effects on growth, biomolecule content and nutrient removal

Amongst the many treatments available for the removal of emerging contaminants in wastewater, microalgal cultures have been shown to be effective. However, the effectiveness of exposure of a native microalgal consortium to emerging contaminants such as bisphenol-A (BPA) and triclosan (TCS) to determine the half-maximum effective concentrations (EC₅₀) has not yet been determined. The effect on growth and nutrient removal of such a treatment as well as on the production of biomolecules such as carbohydrates, lipids, and proteins are, at present, unknown. In this study, the EC₅₀ of BPA and TCS (96-hour experiments) was determined using a consortium of native microalgae (Scenedesmus obliquus and Desmodesmus sp.) to define the maximum tolerance to these contaminants. The effect of BPA and TCS in synthetic wastewater (SWW) was investigated in terms of microalgal growth, chlorophyll a (Chl-a), carbohydrate, lipid, and protein content, as well as nutrient removal. Assays were performed in heterotrophic conditions (12/12 light/dark cycles). EC₅₀-96 h values of 17 mg/L and 325 µg/L for BPA and TCS, respectively, were found at 72 h. For an initial microalgal inoculum of ≈ 300 mg TSS/L (total suspended solids per litre), growth increased by 16.1% when exposed to BPA and 17.78% for TCS. At ≈ 500 mg TSS/L, growth increased by 8.25% with BPA and 9.92% with TCS, respectively. At the EC₅₀-96 h concentrations determined in the study, BPA and TCS did not limit the growth of microalgae in wastewater. Moreover, they were found to stimulate the content of Chl-a, carbohydrates, lipids, proteins, and enhance nutrient removal. AVAILABILITY OF DATA AND MATERIAL: Data sharing not applicable to this article as no datasets were generated or analysed during the present study.

Evaluation of the effects of input variables on the growth of two microalgae classes during wastewater treatment

Wastewater treatment carried out by microalgae is usually affected by the type of algal strain and the combination of cultivation parameters provided during the process. Every microalga strain has a different tolerance level towards cultivation parameters, including temperature, pH, light intensity, CO2 content, initial inoculum level, pretreatment method, reactor type and nutrient concentration in wastewater. Therefore, it is vital to supply the right combination of cultivation parameters to increase the wastewater treatment efficiency and biomass productivity of different microalgae classes. In the current investigation, the decision tree was used to analyse the dataset of class Trebouxiophyceae and Chlorophyceae. Various combinations of cultivation parameters were determined to enhance their performance in wastewater treatment. Nine combinations of cultivation parameters leading to high biomass production and eleven combinations each for high nitrogen removal efficiency and high phosphorus removal efficiency for class Trebouxiophyceae were detected by decision tree models. Similarly, eleven combinations for high biomass production, nine for high nitrogen removal efficiency, and eight for high phosphorus removal efficiency were detected for class Chlorophyceae. The results obtained through decision tree analysis can provide the optimum conditions of cultivation parameters, saving time in designing new experiments for treating wastewater at a large scale.

Determination of photoautotrophic growth and inhibition kinetics by the Monod and the Aiba models and bioenergetics of local microalgae strain

The usage of fossil fuels results in a high amount of greenhouse gas (GHG) emissions and renewable green energy requirements entail saving ecological balance. Therefore, microalgae cultivation is widespread as a suitable raw material to produce renewable and sustainable fuel. Mathematical models are useful tools for the estimation of different conditions of a system. In this study, mathematical models were developed for monitoring the cultivation of local species of microalgae based on the chlorophyll-a and biomass concentration. Coefficients that were calculated from the Monod kinetic model were μmax; 0.03 day^-1, K_S, C_i; 0.53 mM with an R² value of 0.93 and from the Aiba inhibition kinetic model was μmax and K_S, C_i 1.48 day^-1 and 0.08 mM with an R² value of 0,73. According to the literature, there was no model was developed for the determination of kinetic coefficients based on chlorophyll-a production due to the inorganic carbon consumption. While both growth and inhibition models were developed for the inorganic carbon consumption, chlorophyll-a concentration was used for the growth model and biomass concentration was used for the inhibition model which caused and directly affected by the decrease of light penetration. The maximum biomass and chlorophyll-a concentrations were found as 1.2 g/L and 27.8 mg/L respectively with 10.24 mg/L. day^-1 nitrogen and 1.19 mg/L.day^-1 phosphorus uptake rate.

Hybrid support vector regression and crow search algorithm for modeling and multiobjective optimization of microalgae-based wastewater treatment

Microalgae-based wastewater treatment (and biomass production) is an environmentally benign and energetically efficient technique as compared to traditional practices. The present study is focused on optimization of the major treatment variables such as temperature, light-dark cycle (LD), and nitrogen (N)-to-phosphate (P) ratio (N/P) for the elimination of N and P from tertiary municipal wastewater utilizing Chlorella kessleri microalgae species. In this regard, a hybrid support vector regression (SVR) technique integrated with the crow search algorithm has been applied as a novel modeling/optimization tool. The SVR models were formulated using the experimental data, which were furnished according to the response surface methodology with Box-Behnken Design. Various statistical indicators, including mean absolute percentage error, Taylor diagram, and fractional bias, confirmed the superior performance of SVR models as compared to the response surface methodology (RSM) and generalized linear model (GLM). Finally, the best SVR model was hybridized with the crow search algorithm for single/multi-objective optimizations to acquire the global optimal treatment conditions for maximum N and P removal efficiencies. The best-operating conditions were found to be 29.3°C, 24/0 h/h of LD, and 6:1 of N/P, with N and P elimination efficiencies of 99.97 and 93.48%, respectively. The optimized values were further confirmed by new experimental data.

Cultivation of microalgae on unhydrolysed waste molasses syrup using mass cultivation strategy for improved biodiesel

High cultivation cost and low lipid yield are framed as a major bottleneck for the production of microalgae biodiesel. Hence, we first and foremost highlight a trophic mode transition, coupled with a combinatorial effect of organic carbon, nitrogen and light (C/N/L) on an isolated microalga Chlorococcum sp. SVF in a one pot tri-phasic intermittent feeding system by developing a lab scale Raceway tank (40L). Hitherto, waste molasses syrup without hydrolysis is unexplored in algal bioenergy arena. The direct utilisation capability of sucrose, served by waste unhydrolysed molasses syrup (WUMS), effectively modulates the intrinsic biochemical and physiological characteristics towards microalgae biomass and lipid assimilation. Response surface methodology-central composite design (RSM-CCD) tool has been employed to observe the cumulative impact of light irradiation and nutrient sources (carbon and nitrogen) on cellular stoichiometric analysis. Experimental results exhibit a potentially achievable biomass (18.88 g L^-1) and lipid accumulation (80.34%) under the light intensity of 75.5 µmol m^-2 s^-1 with stepwise light attenuation strategy. Characterisation of fatty acid methyl esters (FAME) reveals the dominance of oleic acid (32.72%) and palmitic acid methyl esters (32.49%) in mixotrophic condition, which are considered as the upmost indicators of quality biodiesel. The biofuel properties were obtained in acquiescence with American and European standard. These findings are therefore a way forward towards the effective growth of Chlorococcum sp. SVF in sucrose rich inexpensive industrial waste stream that positively influences the lipid yield for large scale sustainable biodiesel production.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02823-7.