A mathematical model for carbon fixation and nutrient removal by an algal photobioreactor

Modeling of carbon dioxide fixation by microalgae using hybrid artificial intelligence (AI) and fuzzy logic (FL) methods and optimization by genetic algorithm (GA)

In this study, we are reporting a novel prediction model for forecasting the carbon dioxide (CO₂) fixation of microalgae which is based on the hybrid approach of adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA). The CO₂ fixation rate of various algal strains was collected and the cultivation conditions of the microalgae such as temperature, pH, CO₂ %, and amount of nitrogen and phosphorous (mg/L) were taken as the input variables, while the CO₂ fixation rate was taken as the output variable. The optimization of ANFIS parameters and the formation of the optimized fuzzy model structure were performed by genetic algorithm (GA) using MATLAB in order to achieve optimum prediction capability and industrial applicability. The best-fitting model was figured out using statistical analysis parameters such as root mean square error (RMSE), coefficient of regression (R²), and average absolute relative deviation (AARD). According to the analysis, GA-ANFIS model depicted a greater prediction capability over ANFIS model. The RMSE, R², and AARD for GA-ANFIS were observed to be 0.000431, 0.97865, and 0.044354 in the training phase and 0.00056, 0.98457, and 0.032156 in the testing phase, respectively, for the GA-ANFIS Model. As a result, it can be concluded that the proposed GA-ANFIS model is an efficient technique having a very high potential to accurately predict the CO₂ fixation rate.

Analysis of the Emergent Climate Change Mitigation Technologies

A climate change mitigation refers to efforts to reduce or prevent emission of greenhouse gases. Mitigation can mean using new technologies and renewable energies, making older equipment more energy efficient, or changing management practices or consumer behavior. The mitigation technologies are able to reduce or absorb the greenhouse gases (GHG) and, in particular, the CO₂ present in the atmosphere. The CO₂ is a persistent atmospheric gas. It seems increasingly likely that concentrations of CO₂ and other greenhouse gases in the atmosphere will overshoot the 450 ppm CO₂ target, widely seen as the upper limit of concentrations consistent with limiting the increase in global mean temperature from pre-industrial levels to around 2 °C. In order to stay well below to the 2 °C temperature thus compared to the pre-industrial level as required to the Paris Agreement it is necessary that in the future we will obtain a low (or better zero) emissions and it is also necessary that we will absorb a quantity of CO₂ from the atmosphere, by 2070, equal to 10 Gt/y. In order to obtain this last point, so in order to absorb an amount of CO₂ equal to about 10 Gt/y, it is necessary the implementation of the negative emission technologies. The negative emission technologies are technologies able to absorb the CO₂ from the atmosphere. The aim of this work is to perform a detailed overview of the main mitigation technologies possibilities currently developed and, in particular, an analysis of an emergent negative emission technology: the microalgae massive cultivation for CO₂ biofixation.

Enhancement of CO2 biofixation and lipid production by Chlorella vulgaris using coloured polypropylene film

Chlorella vulgaris was cultivated with light at different wavelengths (λ_max) and irradiation intensities (I) by applying a coloured tape (CT) as a simple, inexpensive light filter. C. vulgaris was cultivated in a standard medium using blue (CT_B), green (CT_G), red (CT_R), yellow (CT_Y) and white (CT_W) CT to filter the light, as well the unfiltered light (U). The influence of λ_max and I on specific growth rate (μ), nutrient removal efficiency (% RE of total nitrogen, TN, and phosphorus, TP), CO₂ fixation rate (RC) and lipid productivity (P_lipid) were evaluated. The highest biomass concentration X_max of 2.26 g L^-1 was measured for CT_W with corresponding μ, TN and TP RE, RC and P_lipid values of 0.95 d^-1, 92% and 100%, 0.67 g L^-1 d^-1 and 83.6 mg L^-1 d^-1, respectively. The normalised μ and P_lipid for U were significantly lower than in CT_W of 33-50% and 75%, respectively. The corresponding non-normalised parameter values for CT_B were significantly lower at 0.45 d^-1, 0.18 g L^-1, 15% and 37%, 0.03 g L^-1 d^-1 and 1.2 mg L^-1 d^-1. Results suggest a significant impact of I and λ_max, with up to a 50% increase in growth and nutrient RE from optimising these parameters.

Impact of CO2 concentration and ambient conditions on microalgal growth and nutrient removal from wastewater by a photobioreactor

The increase in atmospheric CO₂ concentration and the release of nutrients from wastewater treatment plants (WWTPs) are environmental issues linked to several impacts on ecosystems. Numerous technologies have been employed to resolves these issues, nonetheless, the cost and sustainability are still a concern. Recently, the use of microalgae appears as a cost-effective and sustainable solution because they can effectively uptake CO₂ and nutrients resulting in biomass production that can be processed into valuable products. In this study single (Spirulina platensis (SP.PL) and mixed indigenous microalgae (MIMA) strains were employed, over a 20-month period, for simultaneous removal of CO₂ from flue gases and nutrient from wastewater under ambient conditions of solar irradiation and temperature. The study was performed at a pilot scale photo-bioreactor and the effect of feed CO₂ gas concentration in the range (2.5-20%) on microalgae growth and biomass production, carbon dioxide bio-fixation rate, and the removal of nutrients and organic matters from wastewater was assessed. The MIMA culture performed significantly better than the monoculture, especially with respect to growth and CO₂ bio-fixation, during the mild season; against this, the performance was comparable during the hot season. Optimum performance was observed at 10% CO₂ feed gas concentration, though MIMA was more temperature and CO₂ concentration sensitive. MIMA also provided greater removal of COD and nutrients (~83% and >99%) than SP.PL under all conditions studied. The high biomass productivities and carbon bio-fixation rates (0.796-0.950 g_dw·L^-1·d^-1 and 0.542-1.075 g_C·L^-1·d^-1 contribute to the economic sustainability of microalgae as CO₂ removal process. Consideration of operational energy revealed that there is a significant energy benefit from cooling to sustain the highest productivities on the basis of operating energy alone, particularly if the indigenous culture is used.

Identification of the pollutants' removal and mechanism by microalgae in saline wastewater

This study investigated the growth dynamics of a freshwater and marine microalgae with supported biochemical performance in saline wastewater, the pollutants assimilation by a developed method, and the mechanism of salinity's effect to pollutants assimilation. Maximal biomass yield was 400-500 mg/L at 0.1-1% salinity while the TOC, NO₃^--N, PO₄^3--P were eliminated 39.5-92.1%, 23-97.4% and 7-30.6%, respectively. The biomass yield and pollutants removal efficiencies reduced significantly when salinity rose from 0.1 to 5%. The freshwater Chlorella vulgaris performed its best with a focus on TOC removal at 0.1% salinity. The marine Chlorella sp. was prominent for removing NO₃^--N at 0.1-1% salinity. Through the developed method, the freshwater C. vulgaris competed to the marine microalgae referring to pollutants assimilation up to 5% salinity. This study unveiled the mechanism of salinity's effect with evidence of salt layer formation and salt accumulation in microalgae.

A critical review on designs and applications of microalgae-based photobioreactors for pollutants treatment

The development of the photobioreactors (PBs) is recently noticeable as cutting-edge technology while the correlation of PBs' engineered elements such as modellings, configurations, biomass yields, operating conditions and pollutants removal efficiency still remains complex and unclear. A systematic understanding of PBs is therefore essential. This critical review study is to: (1) describe the modelling approaches and differentiate the outcomes; (2) review and update the novel technical issues of PBs' types; (3) study microalgae growth and control determined by PBs types with comparison made; (4) progress and compare the efficiencies of contaminants removal given by PBs' types and (5) identify the future perspectives of PBs. It is found that Monod model's shortcoming in internal substrate utilization is well fixed by modified Droop model. The corroborated data also remarks an array of PBs' types consisting of flat plate, column, tubular, soft-frame and hybrid configuration in which soft-frame and hybrid are the latest versions with higher flexibility, performance and smaller foot-print. Flat plate PBs is observed with biomass yield being 5 to 20 times higher than other PBs types while soft-frame and membrane PBs can also remove pharmaceutical and personal care products (PPCPs) up to 100%. Looking at an opportunity for PBs in sustainable development, the flat plate PBs are applicable in PB-based architectures and infrastructures indicating an encouraging revenue-raising potential.

Urban wastewater photobiotreatment with microalgae in a continuously operated photobioreactor: growth, nutrient removal kinetics and biomass coagulation-flocculation

The aim of this study was to investigate the growth, nutrient removal and harvesting of a natural microalgae bloom cultivated in urban wastewater in a bubble column photobioreactor. Batch and continuous mode experiments were carried out with and without pH control by means of CO₂ dosage. Four coagulants (aluminium sulphate, ferric sulphate, ferric chloride and polyaluminium chloride (PAC)) and five flocculants (Chemifloc CM/25, FO 4498SH, cationic polymers Zetag (Z8165, Z7550 and Z8160)) were tested to determine the optimal dosage to reach 90% of biomass recovery. The maximum volumetric productivity obtained was 0.11 g SS L^-1d^-1 during the continuous mode. Results indicated that the removal of total dissolved nitrogen and total dissolved phosphorous under continuous operation were greater than 99%. PAC, Fe₂(SO₄)₃ and Al₂(SO₄)₃ were the best options from an economical point of view for microalgae harvesting.

Multi-factor kinetic modelling of microalgal biomass cultivation for optimised lipid production

This paper presents a new quadruple-factor kinetic model of microalgal cultivation considering carbon and nitrogen concentration, light intensity and temperature, developed in conjunction with laboratory-scale experiments using the well-studied chlorophyte microalgal species Chlamydomonas reinhardtii. Multi-parameter quantification was exploited to assess the predictive capabilities of the model. The validated model was utilized in an optimization study to determine the optimal light intensity and temperature for achieving maximum lipid productivity while using optimal acetate and nitrogen concentrations (2.1906 g L^-1 acetate and 0.0742 g L^-1 nitrogen) computed in a recent publication. It was found that the optimal lipid productivity increased by 50.9% compared to the base case, and by 13.6% compared to the previously computed optimal case. Optimization results were successfully validated experimentally. Such comprehensive modelling approaches can be exploited for robust design, scale-up and optimization of microalgal oil production, reducing operating costs and bringing this important technology closer to industrialization.