Kinetic modelling of microalgae cultivation for wastewater treatment and carbon dioxide sequestration

Comprehensive review of technologies for separate digestate treatment and agricultural valorisation within circular and green economy

Anaerobic digestion (AD) has the potential to catalyse the shift from a linear to a circular economy. However, effective treatment and management of both solid (DSF) and liquid (DLF) digestate fraction treatment and management require adopting sustainable technologies to recover valuable by-products like energy, biofuels, biochar, and nutrients. This study reviews state-of-the-art advanced technologies for DSF and DLF treatment and valorisation, using life cycle assessment (LCA) and techno-economic analysis (TEA) in integrated digestate management (IDM). Key findings highlight these technologies' potential in mitigating environmental impacts from digestate management, but there's a need to improve process efficiency, especially at larger scales. Future research should prioritize cost-effective and eco-friendly IDM technologies. This review emphasizes how LCA and TEA can guide decision-making and promote sustainable agricultural practices. Ultimately, sustainable IDM technologies can boost resource recovery and advance circular economy principles, enhancing the environmental and economic sustainability of AD processes.

General performance, kinetic modification, and key regulating factor recognition of microalgae-based sulfonamide removal

Sulfonamides have been widely detected in water treatment plants. Advanced wastewater treatment for sulfonamide removal based on microalgal cultivation can reduce the ecological risk after discharge, achieve carbon fixation, and simultaneously recover bioresource. However, the general removal performance, key factors and their impacts, degradation kinetics, and potential coupling technologies have not been systematically summarized. To guide the construction and enhance the efficient performance of the purification system, this study summarizes the quantified characteristics of sulfonamide removal based on more than 100 groups of data from the literature. The biodegradation potential of sulfonamides from different subclasses and their toxicity to microalgae were statistically analyzed; therefore, a preferred option for further application was proposed. The mechanisms by which the properties of both sulfonamides and microalgae affect sulfonamide removal were comprehensively summarized. Thereafter, multiple principles for choosing optimal microalgae were proposed from the perspective of engineering applications. Considering the microalgal density and growth status, a modified antibiotic removal kinetic model was proposed with significant physical meaning, thereby resulting in an optimal fit. Based on the mechanism and regulating effect of key factors on sulfonamide removal, sensitive and feasible factors (e.g., water quality regulation, other than initial algal density) and system coupling were screened to guide engineering applications. Finally, we suggested studying the long-term removal performance of antibiotics at environmentally relevant concentrations and toxicity interactions for further research.

Utilizing Mixed Cultures of Microalgae to Up-Cycle and Remove Nutrients from Dairy Wastewater

This study explores the novel use of mixed cultures of microalgae-Spirulina platensis, Micractinium, and Chlorella-for nutrient removal from dairy wastewater (DW). Microalgae were isolated from a local wastewater treatment plant and cultivated under various light conditions. The results showed significant biomass production, with mixed cultures achieving the highest biomass (2.51 g/L), followed by Spirulina (1.98 g/L) and Chlorella (1.92 g/L). Supplementing DW (75%) with BG medium (25%) significantly enhanced biomass and pH levels, improving pathogenic bacteria removal. Spirulina and mixed cultures exhibited high nitrogen removal efficiencies of 92.56% and 93.34%, respectively, while Chlorella achieved 86.85% nitrogen and 83.45% phosphorus removal. Although growth rates were lower under phosphorus-limited conditions, the microalgae adapted well to real DW, which is essential for effective algal harvesting. Phosphorus removal efficiencies ranged from 69.56% to 86.67%, with mixed cultures achieving the highest removal. Microbial and coliform removal efficiencies reached 97.81%, with elevated pH levels contributing to significant reductions in fecal E. coli and coliform levels. These findings suggest that integrating microalgae cultivation into DW treatment systems can significantly enhance nutrient and pathogen removal, providing a sustainable solution for wastewater management.

Pilot-scale microalgae cultivation and wastewater treatment using high-rate ponds: a meta-analysis

Microalgae cultivation in wastewater has been widely researched under laboratory conditions as per its potential to couple treatment with biomass production. Currently, only a limited number of published articles consider outdoor and long-term microalgae-bacteria cultivations in real wastewater environmental systems. The scope of this work is to describe microalgal cultivation steps towards high-rate algal pond (HRAP) scalability and identify key parameters that play a major role for biomass productivity under outdoor conditions and long-term cultivations. Reviewed pilot-scale HRAP literature is analysed using multivariate analysis to highlight key productivity parameters within environmental and operational factors. Wastewater treatment analysis indicated that HRAP can effectively remove 90% of NH4+, 70% of COD, and 50% of PO43-. Mean reference values of 210 W m-2 for irradiation, 18 °C for temperature, pH of 8.2, and HRT of 7.7 are derived from pilot-scale cultivations. Microalgae biomass productivity at a large scale is governed by solar radiation and NH4+ concentration, which are more important than retention time variations within investigated studies. Hence, selecting the correct type of location and a minimum of 70 mg L-1 of NH4+ in wastewater will have the greatest effect in microalgae productivity. A high nutrient wastewater content increases final biomass concentrations but not necessarily biomass productivity. Pilot-scale growth rates (~ 0.54 day-1) are half those observed in lab experiments, indicating a scaling-up bottleneck. Microalgae cultivation in wastewater enables a circular bioeconomy framework by unlocking microalgal biomass for the delivery of an array of products.

A comparative study on the treatment of kitchen grey water using microalgae consortia and microalgae-synthesized silver nanoparticles

Comparative study on the potential of microalgae consortia and green-synthesized silver nanoparticles using microalgae (M-AgNP) consortia for the treatment of kitchen grey water was investigated in this study. The microalgae consortia consisting of four species, viz., Chlorella sp., Scenedesmus sp., Coelastrum sp., and Pediastrum sp. were isolated from a local fish pond and the silver nanoparticles were synthesized with the same. Thus, synthesized silver nanoparticles exhibited a distinctive yellowish-brown colour and spherical morphology. Extensive qualitative and quantitative characterization techniques were employed to determine their size and morphology. Both microalgae consortia and M-AgNP were used separately for the treatment of kitchen grey water under experimental conditions. The synthesized silver nanoparticles demonstrated promising potential for domestic wastewater treatment, leading to substantial reductions in various parameters: total dissolved solids (29.6%), conductivity (49.4%), chemical oxygen demand (64.6%), and heavy metals (arsenic-63.5%, zinc-45.6%, cadmium-88%, copper-60.52%, and lead-80.82%). Notably, microalgae exhibited superior removal efficiency for nitrate (83.1%), sulphate (70.3%), and phosphate (96.5%) compared to microalgae-synthesized silver nanoparticles. This study underscores the effective utilization of both microalgae and microalgae-synthesized silver nanoparticles for wastewater treatment applications.

Effect of macronutrients (carbon, nitrogen, and phosphorus) on the growth of Chlamydomonas reinhardtii and nutrient recovery under different trophic conditions

More stringent discharge standards have led to the development of an alternative nutrient recovery system from wastewater. Microalgae cultivation in wastewater treatment works has presented considerable promise from the perspective of sustainable resource management. Growth kinetics models are useful tools to optimize nutrient recovery from wastewater by algal uptake. Therefore, this research aims to identify the growth kinetics of Chlamydomonas reinhardtii under both heterotrophic and phototrophic conditions with different nutrient concentrations that typify those found in wastewater treatment works. In addition, the effects of macronutrients (C, N, and P) on heterotrophic and phototrophic microalgae growth and nutrient recovery were studied. Greater specific growth rates were achieved under heterotrophic conditions than in phototrophic cultivation. The maximum specific growth rates and nutrient recovery efficiencies were achieved at 5 mg P L-1 under both heterotrophic and phototrophic growth conditions. Nitrate was the preferred form of nitrogen source under heterotrophic conditions, while nitrogen sources did not present any significant influences in the phototrophic cultivation. Specific growth rates reported for both heterotrophic and phototrophic microalgae at lower carbon concentrations (3.10 d-1 and 0.46 d-1, sequentially) were higher than those at higher carbon concentrations (1.95 d-1 and 0.22 d-1, respectively). C. reinhardtii presented an extreme capacity to adapt and grow at all experimental conditions tested in heterotrophic and phototrophic cultivations.

Wastewater treatment by using microalgae: Insights into fate, transport, and associated challenges

The remediation of wastewater with microalgae is a new topic that concentrates on devising a cost-effective and environmentally beneficial method. Multiple microalgae and bacterial consortiums have recently been evaluated to determine if they can purify effluent from various sources. Critical to a system's efficacy is its ability to remove nutrients such as nitrogen (N) and phosphorus (P) and heavy metals such as arsenic (As), lead (Pb), and copper (Cu). This study compared traditional wastewater treatment systems to microalgae-based systems for treating different types of wastewater. The research investigates the potential for microalgae to cleanse wastewater. The research also evaluates wastewater parameters, methods, and scientific techniques for extracting nutrients and heavy metals from polluted water. According to the literature, Microalgae can remove between 98.7% and 100% of nitrogen (N), phosphorous (P), and heavy metals from various effluents. The paper concludes by discussing the difficulties of using microalgae to remediate wastewater. The elimination of nutrients from the effluent is influenced by biomass production, osmotic capacity, temperature, pH, and O2 concentration. Therefore, a "pilot" study is recommended to investigate contaminants.

Exploring resistomes and microbiomes in pilot-scale microalgae-bacteria wastewater treatment systems for use in low-resource settings

Antibiotic resistance genes (ARGs) released into the environment are an emerging human and environmental health concern, including ARGs spread in wastewater treatment effluents. In low-to-middle income countries (LMICs), an alternate wastewater treatment option instead of conventional systems are low-energy, high-rate algal ponds (HRAP) that use microalgae-bacteria aggregates (MABA) for waste degradation. Here we studied the robustness of ARG removal in MABA-based pilot-scale outdoor systems for 140 days of continuous operation. The HRAP system successfully removed 73 to 88 % chemical oxygen demand and up to 97.4 % ammonia, with aggregate size increasing over operating time. Fourteen ARG classes were identified in the HRAP influent, MABA, and effluent using metagenomics, with the HRAP process reducing total ARG abundances by up to 5-fold from influent to effluent. Parallel qPCR analyses showed the HRAP system significantly reduced exemplar ARGs (p < 0.05), with 1.2 to 4.9, 2.7 to 6.3, 0 to 1.5, and 1.2 to 4.8 log-removals for sul1, tetQ, blaKPC, and intl1 genes, respectively. Sequencing of influent, effluent and MABAs samples showed associated microbial communities differed significantly, with influent communities by Enterobacteriales (clinically relevant ARGs carrying bacteria), which were less evident in MABA and effluent. In this sense, such bacteria might be excluded from MABA due to their good settling properties and the presence of antimicrobial peptides. Microalgae-bacteria treatment systems steadily reduced ARGs from wastewater during operation time, using sunlight as the energetic driver, making them ideal for use in LMIC wastewater treatment applications.

Kinetic modeling and experiments on removal of COD/nutrients from dairy effluent using chlorella and co-culture

A sustainable and cost-effective approach of waste water management is biological treatment for reducing organic carbon, nitrate, and phosphate content. Co-culturing of algae with bacteria in wastewater leads to higher biomass yield and improvement in COD/nutrients removal compared to the single strain counterparts. In this study, a mathematical modeling framework is proposed to predict the dynamic behavior of microbial co-culture in dairy waste water. Initially, the model has been developed to predict the biomass growth and COD/nutrients removal with discrete cultures (algae and bacteria). As an extension of the single strain kinetic model, Lotka-Volterra model was formulated to explore the symbiotic relationship between algae and bacteria in a co-culture and the impact of the interactions on the COD/nutrients removal efficiency and growth dynamics. Supporting experiments were carried out in 6 parallel sets (3 sets with triplicates) with standalone algae (Chlorella vulgaris, CV), bacteria (activated sludge), and co-culture in real-time dairy liquid effluent in lab flasks and predicted values from modeling were validated against experimental findings. Statistical analysis confirms reasonably good agreement between the model predictions and experimental findings indicating a positive synergistic effect of the algae-bacterial co-culture on COD removal.

Algae-based treatment of a landfill leachate pretreated by coagulation-flocculation

Landfill leachate (LL) management is an urgent issue at recently closed Sisdol Landfill Site (SLS) used to dispose of solid waste generated in Kathmandu (Nepal) as untreated leachate is flowing directly to the nearby Kolpu River causing environmental and health concerns. This study aims to assess the potential of algae-based treatment of LL pretreated by optimized coagulation-flocculation (CF) for the removal of conventional pollutants such as biological oxygen demand (BOD₅), chemical oxygen demand (COD), ammonia, nitrate, and phosphate. Response Surface Methodology (RSM) was used to optimize the operating variables (dose and pH) during the pretreatment of leachate by the CF process using ferric chloride (FeCl₃.7H₂O), alum (Al₂(SO₄)₃.6H₂O) and commercial poly aluminium chloride (PAC) as coagulants using a jar test apparatus. The pretreated LL was subjected to algal treatment using the mixed microalgae culture isolated and enriched from the wastewater collection pond and grown in artificial light. The combined physicochemical and algal treatment of LL from SLS achieved 62.93-72.43%, 74.93-75.55% and 87.58-93.40% and 73.63-86.73% removal for COD, BOD₅, ammonium-nitrogen and phosphate, respectively. Thus, this research has proven the feasibility of a combined physiochemical and algae-based treatment of LL and also offers an exciting alternative to current treatment practices for LL.

Sustainable treatment of primary and secondary effluent by algal-bacterial flocculent biomass in raceway ponds

Two 5.5-L raceway open ponds were used to evaluate the removal of organic material and nutrients from wastewater. Algal-bacterial flocs were placed in the ponds to treat primary and secondary effluent. The organic loading rate ranged from 29 to 95 and 9 to 38 g sCOD m^-3 d^-1 for the reactor fed with primary and secondary effluent, respectively. The hydraulic retention time (HRT) gradually decreased in both reactors from 5.5 to 2.2 d during a period of 21 days, and after that, both reactors operated at an HRT of 1.1 d. A high biomass concentration of around 2.2 g L^-1 was sustained using primary and secondary effluent after 130 days. The biomass, developed with both substrates was very active and completely removed organic material and nutrients in less than 12 h. The algal-bacteria biomass had excellent settling properties and could settle in less than 10 min.

Biomass and lipid production by the native green microalgae Chlorella sorokiniana in response to nutrients, light intensity, and carbon dioxide: experimental and modeling approach

Introduction: Microalgae are photosynthetic cells that can produce third-generation biofuels and other commercial compounds. Microalgal growth is influenced by two main parameters: light intensity and carbon dioxide concentration, which represent the energy and carbon source, respectively. For photosynthesis, the optimum values of abiotic factors vary among species. Methods: In this study, the microalga Chlorella sorokiniana was isolated from a freshwater lake. It was identified using molecular analysis of the ribosomal internal transcribed spacer. A single-factor design of experiments in 250-mL Erlenmeyer flasks was used to evaluate which concentrations of nitrogen and phosphorus increase the production of biomass and lipids. The response surface methodology was used with a 3²-factorial design (light intensity and CO₂ were used to evaluate its effect on biomass, lipid production, and specific growth rates, in 200-mL tubular photobioreactors (PBRs)). Results and Discussion: Low levels of light lead to lipid accumulation, while higher levels of light lead to the synthesis of cell biomass. The highest biomass and lipid production were 0.705 ± 0.04 g/L and 55.1% ± 4.1%, respectively. A mathematical model was proposed in order to describe the main phenomena occurring in the culture, such as oxygen and CO₂ mass transfer and the effect of light and nutrients on the growth of microalgae. The main novelties of this work were molecular identification of the strain, optimization of culture conditions for the indigenous microalgae species that were isolated, and formulation of a model that describes the behavior of the culture.

Heavy metal tolerance in microalgae: Detoxification mechanisms and applications

The proficiency of microalgae to resist heavy metals has potential to be beneficial in resolving various environmental challenges. Global situations such as the need for cost-effective and ecological ways of remediation of contaminated water and for the development of bioenergy sources could employ microalgae. In a medium with the presence of heavy metals, microalgae utilize different mechanisms to uptake the metal and further detoxify it. Biosorption and the next process of bioaccumulation are two such major steps and they also include the assistance of different transporters at different stages of heavy metal tolerance. This capability has also proved to be efficient in eradicating many heavy metals like Chromium, Copper, Lead, Arsenic, Mercury, Nickel and Cadmium from the environment they are present in. This indicates the possibility of the application of microalgae as a biological way of remediating contaminated water. Heavy metal resistance quality also allows various microalgal species to contribute in the generation of biofuels like biodiesel and biohydrogen. Many research works have also explored the capacity of microalgae in nanotechnology for the formation of nanoparticles due to its relevant characteristics. Various studies have also revealed that biochar deduced from microalgae or a combination of biochar and microalgae can have wide applications specially in deprivation of heavy metals from an environment. This review focuses on the strategies adopted by microalgae, various transporters involved in the process of tolerating heavy metals and the applications where microalgae can participate owing to its ability to resist metals.

Copper multifaceted interferences during swine wastewater treatment in high-rate algal ponds: alterations on nutrient removal, biomass composition and resource recovery

Microalgae cultivation in swine wastewater (SW) allows the removal of nutrients and biomass production. However, SW is known for its Cu contamination, and its effects on algae cultivation systems such as high-rate algal ponds (HRAPs) are poorly understood. This gap in the literature limits the proposition of adequate concentrations of Cu to optimise SW treatment and resource recovery in HRAPs. For this assessment, 12 HRAPs installed outdoors were operated with 800 L of SW with different Cu concentrations (0.1-4.0 mg/L). Cu's interferences on the growth and composition of biomass and nutrient removal from SW were investigated through mass balance and experimental modelling. The results showed that the concentration of 1.0 mg Cu/L stimulated microalgae growth, and above 3.0 mg Cu/L caused inhibition accompanied by an accumulation of H₂O₂. Furthermore, Cu affected the contents of lipids and carotenoids observed in the biomass; the highest concentration was observed in the control (16%) and 0.5 mg Cu/L (1.6 mg/g), respectively. An innovative result was verified for nutrient removal, in which increased Cu concentration reduced the N-NH₄⁺ removal rate. In contrast, the soluble P removal rate was enhanced by 2.0 mg Cu/L. Removal of soluble Cu in treated SW reached 91%. However, the action of microalgae in this process was not associated with assimilation but with a pH increase resulting from photosynthesis. A preliminary evaluation of economic viability showed that the commercialisation of biomass considering the concentration of carotenoids obtained in HRAPs with 0.5 mg Cu/L could be economically attractive. In conclusion, Cu affected the different parameters evaluated in this study in a complex way. This can help managers consort nutrient removal, biomass production, and resource recovery, providing information for possible industrial exploitation of the generated bioproducts.

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.

Microalgae as Raw Materials for Aquafeeds: Growth Kinetics and Improvement Strategies of Polyunsaturated Fatty Acids Production

Studies have shown that ancient cultures used microalgae as food for centuries. Currently, scientific reports highlight the value of nutritional composition of microalgae and their ability to accumulate polyunsaturated fatty acids at certain operational conditions. These characteristics are gaining increasing interest for the aquaculture industry which is searching for cost-effective replacements for fish meal and oil because these commodities are one of the most significant operational expenses and their dependency has become a bottleneck for their sustainable development of the aquaculture industry. This review is aimed at highlighting the use of microalgae as polyunsaturated fatty acid source in aquaculture feed formulations, despite their scarce production at industrial scale. Moreover, this document includes several approaches to improve microalgae production and to increase the content of polyunsaturated fatty acids with emphasis in the accumulation of DHA, EPA, and ARA. Furthermore, the document compiles several studies which prove microalgae-based aquafeeds for marine and freshwater species. Finally, the study explores the aspects that intervene in production kinetics and improvement strategies with possibilities for upscaling and facing main challenges of using microalgae in the commercial production of aquafeeds.

Phycoremediation for carbon neutrality and circular economy: Potential, trends, and challenges

Phycoremediation is gaining attention not only as a pollutant mitigation approach but also as one of the most cost-effective paths to achieve carbon neutrality. When compared to conventional treatment methods, phycoremediation is highly effective in removing noxious substances from wastewater and is inexpensive, eco-friendly, abundantly available, and has many other advantages. The process results in valuable bioproducts and bioenergy sources combined with pollutants capture, sequestration, and utilization. In this review, microalgae-based phycoremediation of various wastewaters for carbon neutrality and circular economy is analyzed scientometrically. Different mechanisms for pollutants removal and resource recovery from wastewaters are explained. Further, critical parameters that influence the engineering design and phycoremediation performance are described. A comprehensive knowledge map highlighting the microalgae potential to treat a variety of industrial effluents is also presented. Finally, challenges and future prospects for industrial implementation of phycoremediation towards carbon neutrality coupled with circular economy are discussed.

Microalgae growth rate multivariable mathematical model for biomass production

Background

The use of microalgae has been emerging as a potential technology to reduce greenhouse gases and bioremediate polluted water and produce high-value products as pigments, phytohormones, biofuels, and bioactive compounds. The improvement in biomass production is a priority to make the technology implementation profitable in every application mentioned before.

Methods

The present study was conducted to explore the use of microalgae from genus Chlorella and Tetradesmus for the generation of substances of interest with UV absorption capacity. A mathematical model was developed for both microalgae to characterize the production of microalgae biomass considering the effects of light intensity, temperature, and nutrient consumption. The model was programmed in MATLAB software, where the three parameters were incorporated into a single specific growth rate equation.

Results

It was found that the optimal environmental conditions for each genus (Chlorella T=36°C, and I<787 μmol/m²s; Tetradesmus T=23°C and I<150 μmol/m²s), as well as the optimal specific growth rate depending on the personalized values of the three parameters.

Conclussion

This work could be used in the production of microalgae biomass for the design and development of topical applications to replace commercial options based on compounds that compromise health and have a harmful impact on the environment.

A techno-economic assessment of nutrient recovery from wastewater using microalgae: scenario in India collected from published literature

The true potential of the microalgae-based wastewater treatment (MWT) process is determined based on whether the process will provide a positive energy output and whether it is economically viable. The objectives of this study are dynamic modelling of microalgae growth based on initial wastewater concentration, temperature, solar radiation and a techno-economic assessment for an MWT scheme for application in a hot, dry climate. Through reference to relevant literature data on MWT in the Indian subcontinent, a selection of appropriate microalgal species Chlorella and Scenedesmus was made. The dynamic model developed was successfully calibrated and validated using independent experimental data collected from the published literature. Cost of production of bio-crude from microalgae grown in a hybrid photobioreactor and pond system in kitchen wastewater of Indian Institute of Technology, Hyderabad was calculated. A break-even selling price (BESP) of US$0.549/kg was obtained for the microalgae biomass. The cost of production of 1 L bio-crude was US$0.96 (Rs 69-74), which is comparable with crude oil cost. The model developed can be used by practising engineers to predict biomass growth and nutrient removal, thereby achieving a break-even point for cost efficiency.

A review of advances in valorization and post-treatment of anaerobic digestion liquid fraction effluent

Traditionally, digestate is considered a waste, which is used as fertiliser in the agriculture industry. Recent studies focus on increasing the profitability of digestate by extracting reusable nutrients to promote biogas plants cost-effectiveness, sustainable management and circular economy. This review focuses on the post-treatment and valorization of liquor which is produced by solid-liquid fractioning of digestate. Nutrient recovery and removal from liquor are possible through mechanical, physicochemical and biological procedures. The processes discussed involve complex procedures that differ in economic value, feasibility, legislative restrictions and performance. The parameters that should be considered to employ these techniques are influenced by liquor characteristics, topography, climate conditions and available resources. These are key parameters to keep in mind during designing and manufacturing a biogas plant. In the following chapters, a discussion on available liquor treatment methods takes place. The present study examines the critical aspects of the available liquor treatment methods.

Continuous antibiotic attenuation in algal membrane photobioreactor: Performance and kinetics

The attenuation of 10 mixed antibiotics along with nutrients in a continuous flow mode by four freshwater microalgae (Haematococcus pluvialis, Selenastrum capricornutum, Scenedesmus quadricauda, and Chlorella vulgaris) was examined in membrane photobioreactors (MPBRs). At lab-scale, consistent removal of both antibiotic and nutrient was shown by H. pluvialis and S. quadricauda, respectively. The system exhibited better performance with enhanced removal at HRT 24 h compared to 12 h and 48 h. The highest removal efficiency of antibiotics was observed in H. pluvialis MPBR, with the mean antibiotic removal values of 53.57%- 96.33%. Biodegradation was the major removal pathway of the antibiotics in the algal-MPBR (AMPBR), while removal by bioadsorption, bioaccumulation, membrane rejection, and abiotic was minor. Then, the bacterial feature was studied and showed significant influence from system hydrodynamics. The kinetics of continuous flow antibiotic removal followed Stover-Kincannon and Grau second-order models, which revealed great potential of AMPBR to withstand antibiotic load. The latter coupled with the computational fluid dynamic simulation was successfully applied for the residual antibiotic prediction and potential system optimization. Overall, these results provide an important reference for continuous flow antibiotic removal using AMPBR.

Sugar Beet Processing Wastewater Treatment by Microalgae through Biosorption

The aim of this study was to investigate the potential of environmental pollution reduction of sugar beet processing factory wastewater by the biorefinery approach and integration of microalgae biomass production. In the present study, Chlorella vulgaris was cultivated in wastewater collected from a sugar beet processing factory at the beginning and at the end of a sugar plant campaign in an aerobic bioreactor on a laboratory scale under controlled conditions, with an air flow of 0.4 L/min, a temperature of 26 °C, and pH = 8. Microalgae showed effective nutrient remediation from wastewater. During wastewater treatment, chemical oxygen demand (COD) and biological oxygen demand (BOD) removal efficiency was 93.7% and 98.1%, respectively; total organic carbon (TOC) content decreased by 95.7%. Nitrites and nitrates decreased by 96%, while the biggest decrease in metal ions was achieved for Ca and Mn (82.7% and 97.6%, respectively). The findings of this study suggest that coupling microalgae cultivation and wastewater treatment has a lot of potential for reducing contamination through biosorption, while also providing environmental advantages.

Smart microalgae farming with internet-of-things for sustainable agriculture

Agriculture farms such as crop, aquaculture and livestock have begun the implementation of Internet of Things (IoT) and artificial intelligence (AI) technology in improving their productivity and product quality. However, microalgae farming which requires precise monitoring, controlling and predicting the growth of microalgae biomass has yet to incorporate with IoT and AI technology, as it is still in its infancy phase. Particularly, the cultivation stage of microalgae involves many essential parameters (i.e. biomass concentration, pH, light intensity, temperature and tank level) which require precise monitoring as these parameters are important to ensure an effective biomass productivity in the microalgae farming. Besides, the conventional practices in the current process equipment are still powered by electricity, thus further development by integrating IoT into these processes can ease the production process. Further to that, many researchers has studied the machine learning approach for the identification and classification of microalgae. However, there are still limited studies reported on applying machine learning for the application of microalgae industry such as optimising microalgae cultivation for higher biomass productivity. Therefore, the implementation of IoT and AI in microalgae farming can contribute to the development of the global microalgae industry. The purpose of this current review paper focuses on the overview microalgae biomass production process along with the implementation of IoT toward the future of smart farming. To bridge the gap between the conventional and microalgae smart farming, this paper also highlights the insights on the implementation phases of microalgae smart farming starting from the infant stage that involves the installation and programming of IoT hardware. Then, it is followed by the application of machine learning to predict and auto-optimise the microalgae smart farming process. Furthermore, the process setup and detailed overview of microalgae farming with the integration of IoT have been discussed critically. This review paper would provide a new vision of microalgae farming for microalgae researchers and bio-processing industries into the digitalisation industrial era.

Global sensitivity and uncertainty analysis of a microalgae model for wastewater treatment

The results of a global sensitivity and uncertainty analysis of a microalgae model applied to a Membrane Photobioreactor (MPBR) pilot plant were assessed. The main goals of this study were: (I) to identify the sensitivity factors of the model through the Morris screening method, i.e. the most influential factors; (II) to calibrate the influential factors online or offline; and (III) to assess the model's uncertainty. Four experimental periods were evaluated, which encompassed a wide range of environmental and operational conditions. Eleven influential factors (e.g. maximum specific growth rate, light intensity and maximum temperature) were identified in the model from a set of 34 kinetic parameters (input factors). These influential factors were preferably calibrated offline and alternatively online. Offline/online calibration provided a unique set of model factor values that were used to match the model results with experimental data for the four experimental periods. A dynamic optimization of these influential factors was conducted, resulting in an enhanced set of values for each period. Model uncertainty was assessed using the uncertainty bands and three uncertainty indices: p-factor, r-factor and ARIL. Uncertainty was dependent on both the number of influential factors identified in each period and the model output analyzed (i.e. biomass, ammonium and phosphate concentration). The uncertainty results revealed a need to apply offline calibration methods to improve model performance.

Arthrospira sp. mediated bioremediation of gray water in ceramic membrane based photobioreactor: process optimization by response surface methodology

Direct discharge of raw domestic sewage enriched with nitrogenous and phosphorous compounds into the water bodies causes eutrophication and other environmental hazards with detrimental impacts on public and ecosystem health. The present study focuses on phycoremediation of gray water with Arthrospira sp. using an innovative hydrophobic ceramic membrane-based photobioreactor system integrated with CO₂ biofixation and biodiesel production, aiming for green technology development. Surfactant and oil-rich gray water collected from the domestic kitchen was used wherein, chloride, sulfate, and surfactant concentrations were statistically optimized using response surface methodology (RSM), considering maximum microalgal growth rate as a response for the design. Ideal concentrations (mg/L) of working parameters were found to be 7.91 (sulfate), 880.49 (chloride), and 144.02 (surfactant), respectively to achieve optimum growth rate of 0.43 g_dwt/L/day. Enhancement of growth rate of targeted microalgae by 150% with suitable CO₂ (19.5%) supply and illumination in the photobioreactor affirms its efficient operation. Additionally, harvested microalgal biomass obtained from the process showed a biodiesel content of around 5.33% (dry weight). The microalgal treatment enabled about 96.82, 87.5, and 99.8% reductions in BOD, COD, and TOC, respectively, indicating the potential of the process in pollutant assimilation and recycling of such wastewater along with value-added product generation.

Progress and challenges of contaminate removal from wastewater using microalgae biomass

The utilization of microalgae in treating wastewater has been an emerging topic focussed on finding an economically sustainable and environmentally friendly approach to treating wastewater. Over the last several years, different types of con microalgae and bacteria consortia have been experimented with to explore their potential in effectively treating wastewater from different sources. The basic features considered while determining efficiency is their capacity to remove nutrients including nitrogen (N) and phosphorus (P) and heavy metals like arsenic (As), lead (Pb), and copper (Cu). This paper reviews the efficiency of microalgae as an approach to treating wastewater from different sources and compares conventional and microalgae-based treatment systems. The paper also discusses the characteristics of wastewater, conventional methods of wastewater treatment that have been used so far, and the technological mechanisms for removing nutrients and heavy metals from contaminated water. Microalgae can successfully eliminate the suspended nutrients and have been reported to successfully remove N, P, and heavy metals by up to 99.6 %, 100 %, and 13%-100 % from different types of wastewater. However, although a microalgae-based wastewater treatment system offers some benefits, it also presents some challenges as outlined in the last section of this paper. Performance in eliminating nutrients from wastewater is affected by different parameters such as temperature, biomass productivity, osmotic ability, pH, O₂ concentration. Therefore, the conducting of pilot-scale studies and exploration of the complexities of contaminants under complex environmental conditions is recommended.

Kinetic modeling of autotrophic microalgae mainline processes for sewage treatment in phosphorus-replete and -deplete culture conditions

A kinetic model of autotrophic microalgal growth in sewage was developed to determine the biokinetic processes involved, including carbon-, nitrogen- and phosphorus-limited microalgal growth, dependence on light intensity, temperature and pH, light attenuation and gas exchange to the atmosphere. A new feature was the differentiation between two metabolic pathways of phosphorus consumption according to the availability of extracellular phosphorus. Two scenarios were differentiated: phosphorus-replete and -deplete culture conditions. In the former, the microalgae absorbed phosphorus to grow and store polyphosphate. In the latter the microalgae used the stored polyphosphate as a phosphorus source for growth. Calibration and validation were performed with experimental data from a pilot-scale membrane photobioreactor (MPBR) fed with the permeate obtained from an anaerobic membrane bioreactor (AnMBR) pilot plant fed with real urban wastewater. 12 of the model parameters were calibrated. Despite the dynamics involved in the operating and environmental conditions, the model was able to reproduce the overall process performance with a single set of model parameters values. Four periods of different environmental and operational conditions were accurately simulated. Regarding the former, light and temperature ranged 10-406 μmol·m^-2·s^-1 and 19.7-32.1 °C, respectively. Concerning the later, the photobioreactors widths were 0.25 and 0.10 m, and the biomass and hydraulic retention times ranged 3-4.5 and 1.5-2.5 days, respectively. The validation of the model resulted in an overall correlation coefficient (R²) of 0.9954. The simulation results showed the potential of the model to predict the dynamics of the different components: the relative proportions of microalgae, nitrogen and phosphorus removal, polyphosphate storage and consumption, and soluble organic matter concentration, as well as the influence of environmental parameters on the microalgae's biokinetic processes. The proposed model could provide an effective tool for the industry to predict microalgae production and comply with the discharge limits in areas declared sensitive to eutrophication.

View on a mechanistic model of Chlorella vulgaris in incubated shake flasks

Kinetic growth models are a useful tool for a better understanding of microalgal cultivation and for optimizing cultivation conditions. The evaluation of such models requires experimental data that is laborious to generate in bioreactor settings. The experimental shake flask setting used in this study allows to run 12 experiments at the same time, with 6 individual light intensities and light durations. This way, 54 biomass data sets were generated for the cultivation of the microalgae Chlorella vulgaris. To identify the model parameters, a stepwise parameter estimation procedure was applied. First, light-associated model parameters were estimated using additional measurements of local light intensities at differ heights within medium at different biomass concentrations. Next, substrate related model parameters were estimated, using experiments for which biomass and nitrate data were provided. Afterwards, growth-related model parameters were estimated by application of an extensive cross validation procedure.

Sensitivity, Equilibria, and Lyapunov Stability Analysis in Droop’s Nonlinear Differential Equation System for Batch Operation Mode of Microalgae Culture Systems

Microalgae-based biomass has been extensively studied because of its potential to produce several important biochemicals, such as lipids, proteins, carbohydrates, and pigments, for the manufacturing of value-added products, such as vitamins, bioactive compounds, and antioxidants, as well as for its applications in carbon dioxide sequestration, amongst others. There is also increasing interest in microalgae as renewable feedstock for biofuel production, inspiring a new focus on future biorefineries. This paper is dedicated to an in-depth analysis of the equilibria, stability, and sensitivity of a microalgal growth model developed by Droop (1974) for nutrient-limited batch cultivation. Two equilibrium points were found: the long-term biomass production equilibrium was found to be stable, whereas the equilibrium in the absence of biomass was found to be unstable. Simulations of estimated parameters and initial conditions using literature data were performed to relate the found results to a physical context. In conclusion, an examination of the found equilibria showed that the system does not have isolated fixed points but rather has an infinite number of equilibria, depending on the values of the minimal cell quota and initial conditions of the state variables of the model. The numerical solutions of the sensitivity functions indicate that the model outputs were more sensitive, in particular, to variations in the parameters of the half saturation constant and minimal cell quota than to variations in the maximum inorganic nutrient absorption rate and maximum growth rate.

Recent Advances in Carbon Dioxide Conversion: A Circular Bioeconomy Perspective

Managing the concentration of atmospheric CO2 requires a multifaceted engineering strategy, which remains a highly challenging task. Reducing atmospheric CO2 (CO2R) by converting it to value-added chemicals in a carbon neutral footprint manner must be the ultimate goal. The latest progress in CO2R through either abiotic (artificial catalysts) or biotic (natural enzymes) processes is reviewed herein. Abiotic CO2R can be conducted in the aqueous phase that usually leads to the formation of a mixture of CO, formic acid, and hydrogen. By contrast, a wide spectrum of hydrocarbon species is often observed by abiotic CO2R in the gaseous phase. On the other hand, biotic CO2R is often conducted in the aqueous phase and a wide spectrum of value-added chemicals are obtained. Key to the success of the abiotic process is understanding the surface chemistry of catalysts, which significantly governs the reactivity and selectivity of CO2R. However, in biotic CO2R, operation conditions and reactor design are crucial to reaching a neutral carbon footprint. Future research needs to look toward neutral or even negative carbon footprint CO2R processes. Having a deep insight into the scientific and technological aspect of both abiotic and biotic CO2R would advance in designing efficient catalysts and microalgae farming systems. Integrating the abiotic and biotic CO2R such as microbial fuel cells further diversifies the spectrum of CO2R.

Novel sequential flow baffled microalgal-bacterial photobioreactor for enhancing nitrogen assimilation into microalgal biomass whilst bioremediating nutrient-rich wastewater simultaneously

A novel sequential flow baffled microalgal-bacterial (SFB-AlgalBac) photobioreactor was designed to cater for the synergistic interactions between microalgal and bacterial consortia to enhance nitrogen assimilation into microalgal biomass from nutrient-rich wastewater medium. The performance of the SFB-AlgalBac photobioreactor was found to be optimum at the influent flow rate of 5.0 L/d, equivalent to 20 days of hydraulic retention time (HRT). The highest microalgal nitrogen assimilation rate (0.0271 /d) and biomass productivity (1350 mg/d) were recorded amidst this flow rate. Further increase to the 10.0 L/d flow rate reduced the photobioreactor performance, as evidenced by a reduction in microalgal biomass productivity (>10%). The microalgal biomass per unit of nitrogen assimilated values were attained at 16.69 mg/mg for the 5.0 L/d flow rate as opposed to 7.73 mg/mg for the 10.0 L/d flow rate, despite both having comparable specific growth rates. Also, the prior influent treatment by activated sludge was found to exude extracellular polymeric substances which significantly improved the microalgal biomass settleability up to 37%. The employment of SFB-AlgalBac photobioreactor is anticipated could exploit the low-cost nitrogen sources from nutrient-rich wastewaters via bioconversion into valuable microalgal biomass while fulfilling the requirements of sustainable wastewater treatment technologies.

Chlorella vulgaris cultivation in simulated wastewater for the biomass production, nutrients removal and CO2 fixation simultaneously

Chlorella vulgaris (C. vulgaris) was promising microalgae to simultaneously achieve biomass production, carbon dioxide (CO₂) fixation, nutrients removal and proteins production especially under different conditions of CO₂ gas and wastewaters. Results presented that maximal specific growth rate of C. vulgaris was 0.21-0.35 d^-1 and 0.33-0.43 d^-1 at 0.038% and 10% CO₂ respectively, and corresponding maximal CO₂ fixation rate was attended with 4.51-14.26 and 56.26-85.72 mg CO₂·L^-1·d^-1. C. vulgaris showed good wastewater removal efficiency of nitrogen and phosphorus at 10% CO₂ with 96.12%-99.61% removal rates. Nitrogen fixation amount achieved 41.86 mg L^-1 when the initial NH₄Cl concentration was set at 60 mg L^-1 at 10% CO₂. Improved total protein (25.01-365.49 mg) and amino acids (24.56-196.44 mg) contents of C. vulgaris biomass was observed with the increasing of added CO₂ and ammonium concentrations. Moreover, the developed kinetic function of C. vulgaris growth depends on both phosphorus quota and nitrogen quota with correlation coefficient (R²) ranged from 0.68 to 0.97. Computed maximal consumed nutrients concentrations (ΔC_max) based on Logistic function are positively related to initial NH₄⁺-N concentrations, which indicated that adding ammonium could stimulate the utilization of both phosphorus and nitrogen.

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.

Phyco-remediation of swine wastewater as a sustainable model based on circular economy

Pork production has expanded in the world in recent years. This growth has caused a significant increase in waste from this industry, especially of wastewater. Although there has been an increase in wastewater treatment, there is a lack of useful technologies for the treatment of wastewater from the pork industry. Swine farms generate high amounts of organic pollution, with large amounts of nitrogen and phosphorus with final destination into water bodies. Sadly, little attention has been devoted to animal wastes, which are currently treated in simple systems, such as stabilization ponds or just discharged to the environment without previous treatment. This uncontrolled release of swine wastewater is a major cause of eutrophication processes. Among the possible treatments, phyco-remediation seems to be a sustainable and environmentally friendly option of removing compounds from wastewater such as nitrogen, phosphorus, and some metal ions. Several studies have demonstrated the feasibility of treating swine wastewater using different microalgae species. Nevertheless, the practicability of applying this procedure at pilot-scale has not been explored before as an integrated process. This work presents an overview of the technological applications of microalgae for the treatment of wastewater from swine farms and the by-products (pigments, polysaccharides, lipids, proteins) and services of commercial interest (biodiesel, biohydrogen, bioelectricity, biogas) generated during this process. Furthermore, the environmental benefits while applying microalgae technologies are discussed.

On-line monitoring of photosynthetic activity based on pH data to assess microalgae cultivation

Microalgae performance of outdoor cultivation systems is influenced by environmental and operating dynamics. Monitoring and control systems are needed to maximise biomass productivity and nutrient recovery. The goal of this work was to corroborate that pH data could be used to monitor microalgae performance by means of data from an outdoor membrane photobioreactor (MPBR) plant. In this system, microalgae photosynthetic activity was favoured over other physical and biological processes, so that the pH data dynamics was theoretically related to the microalgae carbon uptake rate (CUR). Short- and long-term continuous operations were tested to corroborate the relationship between the first derivate of pH data dynamics (pH') and microalgae photosynthetic activity. Short-term operations showed a good correlation between gross pH' values and MPBR performance. An indicator of the maximum daily average microalgae activity was assessed by a combination of on-line pH' measurements obtained in the long-term and a microalgae growth kinetic model. Both indicators contributed to the development of advanced real-time monitoring and control systems to optimise microalgae cultivation technology.

Integration of Microalgae Cultivation in a Biogas Production Process from Organic Municipal Solid Waste: From Laboratory to Pilot Scale

In this study, the feasibility of integrating microalgae cultivation in a biogas production process that treats the organic fraction of municipal solid waste (OFMSW) was investigated. In particular, the biomass growth performances in the liquid fraction of the digestate, characterized by high ammonia concentrations and turbidity, were assessed together with the nutrient removal efficiency. Preliminary laboratory-scale experiments were first carried out in photobioreactors operating in a continuous mode (Continuous-flow Stirred-Tank Reactor, CSTR), to gain preliminary data aimed at aiding the subsequent scaling up to a pilot scale facility. An outdoor experimental campaign, operated from July to October 2019, was then performed in a pilot scale raceway pond (4.5 m2), located in Arzignano (VI), Italy, to assess the performances under real environmental conditions. The results show that microalgae could grow well in this complex substrate, although dilution was necessary to enhance light penetration in the culture. In outdoor conditions, nitrification by autotrophic bacteria appeared to be significant, while the photosynthetic nitrogen removal was around 12% with respect to the inlet. On the other hand, phosphorus was almost completely removed from the medium under all the conditions tested, and a biomass production between 2–7 g m−2 d−1 was obtained.