Novel satellite based analytical model developed to predict microalgae yields in open pond raceway systems and applied to Canadian sites

A comprehensive review on effective parameters on microalgae productivity and carbon capture rate

Rising carbon emissions caused by population growth and industrialization is a significant environmental challenge in various countries. To combat this issue, Renewable Energy (RE) and Carbon Capture and Storage (CCS) technologies should be commercialized to reduce Greenhouse Gas (GHG) emissions and generate carbon-free energy. One such technology is the use of microalgae, which can directly capture CO2 from the air through photosynthesis and potentially produce biofuels due to their high energy content. However, the carbon capture rate of microalgae varies globally due to numerous parameters and variables affecting microalgae productivity. Additionally, microalgae productivity and carbon capture formulas yield different results worldwide, especially in outdoor industrial-scale cultivation. This research aims to comprehensively review the effective variables and parameters in carbon capture by microalgae based on microalgae productivity and carbon capture formulas. The research also ranked countries based on CO2 production in four different categories to determine whether the biggest carbon producer countries could exhibit suitable weather conditions for microalgae cultivation. Findings reveal optimal ranges of critical variables in the microalgae growth formula, including temperature, solar radiation intensity, Photon Flux Density (PFD), and sunlight duration. The study also analyzes microalgae cultivation, carbon capture, and oxygen production formula in different systems such as Open Ponds (OP), Tubular Photobioreactors (TPBR), and Flat Plate Photobioreactors (FPPBR), while discussing other influential parameters. In conclusion, emphasizing the adjustment and utilization of optimal values of effective parameters in microalgae cultivation not only holds promise for future carbon capture by microalgae but also pushes human beings toward sustainable development goals.

Selection and re-acclimation of bioprospected acid-tolerant green microalgae suitable for growth at low pH

For mass culture of photosynthetic green microalgae, industrial flue gases can represent a low-cost resource of CO₂. However, flue gases are often avoided, because they often also contain high levels of SO₂ and/or NO₂, which cause significant acidification of media to below pH 3 due to production of sulfuric and nitric acid. This creates an unsuitable environment for the neutrophilic microalgae commonly used in large-scale commercial production. To address this issue, we have looked at selecting acid-tolerant microalgae via growth at pH 2.5 carried out with samples bioprospected from an active smelter site. Of the eight wild samples collected, one consisting mainly of Coccomyxa sp. grew at pH 2.5 and achieved a density of 640 mg L^-1. Furthermore, three previously bioprospected green microalgae from acidic waters (pH 3-4.5) near abandoned mine sites were also re-acclimated down to their in-situ pH environment after approximately 4 years spent at neutral pH. Of those three, an axenic culture of Coccomyxa sp. was the most successful at re-acclimating and achieved the highest density of 293.1 mg L^-1 and maximum daily productivity of 38.8 mg L^-1 day^-1 at pH 3. Re-acclimation of acid-tolerant species is, therefore, achievable when directly placed at their original pH, but gradual reduction in pH is recommended to give the cells time to acclimate.

Modelling and multi-objective optimization for simulation of hydrogen production using a photosynthetic consortium

This study was aimed at finding the optimal conditions for hydrogen production based on statistical experiments and using a simulation approach. A Plackett–Burman design and steepest ascent were used to screen the key factors to obtain the best hydrogen concentration. According to the regression analysis, cysteine, acetate, and aeration had the best effect. The optimal conditions, using the method of steepest ascent, were aeration (0.125 L/min), acetate (200 mg/L), cysteine (498 mg/L). Once this was determined, an experiment with more than two factors was considered. The combinations: acetate + cysteine without aeration and cysteine without aeration increased hydrogen concentration. These last two criteria were used to validate the dynamic model based on unstructured kinetics. Biomass, nitrogen, acetate, and hydrogen concentrations were monitored. The proposed model was used to perform the multi-objective optimization for various desired combinations. The simultaneous optimization for a minimum ratio of cysteine-acetate improved the concentration of hydrogen to 20 mg/L. Biomass optimized the concentration of hydrogen to 11.5 mg/L. The simultaneous optimization of reaction time (RT) and cysteine improved hydrogen concentration to 28.19 mg/L. The experimental hydrogen production was 11.4 mg/L at 24 h under discontinuous operation. Finally, the proposed model and the optimization methodology calculated a higher hydrogen concentration than the experimental data.