Bioethanol and biobutanol production using algal biomass: pathways and industrial applications

1 Introduction

Nowadays, researchers are more concerned about climate change, rising greenhouse gas emissions and the depletion of fossil fuel reserves caused by the rapid population growth, industrial expansion, and urbanisation, thus resulting in a substantial increase in global energy demand (Wang and Azam, 2024; Wolf et al., 2025). In this context, biofuels derived from renewable biological feedstocks have emerged as viable alternatives to conventional fossil fuels due to their sustainable and low-carbon characteristics, thus reducing dependency on fossil resources (Cherwoo et al., 2023). Consequently, biofuel production is gaining worldwide attention as it can fulfil the future energy needs (El-Araby, 2024). An increase in investments in sustainable biomass technologies and government policies is expected to sustain and expand the market. Worldwide, the United States, Brazil, and the European Union are leading producers, while other countries like India, Switzerland, and Argentina are also making considerable contributions to the growth of this sustainable energy sector (GSR, 2025; Dar et al., 2025). The biofuel production is commonly categorized into four generations, based on the nature of feedstocks used and the underlying technologies (Kant et al., 2025; Mahapatra et al., 2021; Cavelius et al., 2023). The first-generation biofuels are generally produced from feedstocks such as sugarcane, corn, and other starch- or sugar-rich crops. However, the competition for agricultural land and food supply has shifted the search for alternative biomass sources, due to which research focus has moved toward second-generation biofuels, which utilise non-food lignocellulosic materials and agricultural residues as a feedstock. Despite their great promise, the large-scale commercialisation of second-generation biofuels has been hindered by the high production costs and technological complexities involved. These limitations have redirected research efforts toward third-generation biofuels, derived primarily from photosynthetic organisms such as algae and cyanobacteria (Mahmood et al., 2023). Fourth-generation biofuels, in turn, involve the use of genetically modified photosynthetic organisms designed to enhance biomass accumulation and overall biofuel yields through advanced metabolic and synthetic biology approaches (Shokravi et al., 2021).

Among these generations, algal biomass has emerged as one of the most promising feedstocks for sustainable biofuel production due to its high photosynthetic efficiency, rapid growth rates, biochemical versatility and ability to convert sunlight, CO₂, and nutrients into biomass with superior productivity compared with terrestrial plants (Fatima et al., 2025; Jha et al., 2024). Furthermore, they can be cultivated on non-arable land using saline, brackish, or wastewater, thereby preventing competition with food crops and conserving freshwater resources. The feasibility of using microalgae as a feedstock depends on four key factors: (1) selecting robust, high-performing species capable of accumulating high lipids or carbohydrates content; (2) using efficient harvesting techniques; (3) applying effective pretreatment methods to disrupt the cell walls and release fermentable substrates; and (4) optimizing fermentation or conversion processes to enhance overall yield (Ahuja et al., 2026; Anschau et al., 2025; Khan et al., 2023; Konwar et al., 2025). Achieving economic viability requires careful integration of these stages to maximize energy efficiency and product recovery. Furthermore, microalgal biomass can be converted into multiple forms of renewable energy, such as bioethanol, biodiesel, bio-oil, biomethane, biohydrogen, and jet biofuel, underscoring their versatility, scalability, and immense potential as next-generation sustainable energy resources (Koley et al., 2024; Sundaram et al., 2025). The carbohydrate-rich composition of microalgae makes them ideal substrates for microbial fermentation, enabling high production of bioethanol and biobutanol as shown in Figure 1 (Algal Biomass for Bioethanol and Biobutanol Production, 2022). However, despite increasing interest in bioethanol and biobutanol production, large-scale algal biofuel applications have primarily focused on biodiesel production due to the naturally high lipid content in many algal species (Patnaik and Mallick, 2021). Beyond energy generation, algae play a vital role in carbon sequestration, nutrient recycling, and environmental remediation, contributing significantly to global sustainability and circular bioeconomy goals. Their versatility extends to diverse applications such as wastewater treatment, industrial CO₂ mitigation, and the synthesis of high-value biochemicals for human and animal use (Das and Bhattarai, 2025; Omokaro et al., 2025).

Bioethanol and biobutanol are pivotal biofuels in the global transition to low-carbon energy systems. These short-chain alcohols are suitable for both transportation and industrial applications and are compatible with existing fuel infrastructure. In the energy sector, these biofuels serve as sustainable alternatives to gasoline and diesel. Bioethanol, a two-carbon alcohol, is the most widely produced biofuel globally due to its high octane, oxygen content, and reduced vehicular emissions (Kazmi et al., 2025). Ethanol fuel blends such as E10 and E15 are widely used, with policies like India’s National Bio-Energy Mission originally targeting 20% ethanol blending by 2030. However, India has significantly accelerated this process and achieved the E20 milestone in March 2025 (5 years ahead of schedule) and policy efforts are now shifting toward the use of higher blends such as E25 and E30 to further strengthen energy security and reduce carbon emissions (Harde and Ojha, 2025; Pressreleaseshare, 2026). Biobutanol, a four-carbon alcohol, offers complementary advantages, with distinct fuel qualities and energy density (Serrano-Echeverry et al., 2025). Biobutanol is showing strong promise as a high-energy aviation fuel and blending agent that enhances combustion efficiency and reduces carbon emissions (Çelebi et al., 2025). Butanol has emerged as a promising biofuel that can be produced as a co-product from algal biomass residues remaining after lipid extraction for biodiesel production (Razack Sirajunnisa, 2023). Its growing interest is attributed to its comparatively higher energy density, lower volatility, and reduced hygroscopic nature relative to ethanol. Bioethanol is primarily produced via the glycolytic pathway followed by alcoholic fermentation (Tse et al., 2021), whereas biobutanol is produced through anaerobic Acetone-Butanol-Ethanol (ABE) fermentation (Veza et al., 2021). Recent advances in metabolic engineering, synthetic biology, and process optimization have significantly improved yields and reduced process cost. The applications of algal biomass extend across multiple sectors, such as the food and beverage industry, pharmaceuticals, and industrial formulations due to their renewable nature and versatile functionality (Zabochnicka et al., 2022; Sharma and Sharma, 2017). Moreover, integrating algal biofuel production within biorefinery systems through the valorization of waste streams, carbon capture, and the generation of co-products like pigments and fertilizers, ultimately contributes to a sustainable, low-carbon industrial framework (Dutta et al., 2025). In this review, unlike other studies, we have comprehensively focused on optimization of algal biomass for the production of bioethanol and biobutanol, covering key aspects of cultivation, pretreatment, hydrolysis, and fermentation using different microorganisms, rather than focusing solely on cultivation and pretreatment parameters. It uniquely evaluates both bioethanol and biobutanol production from algal biomass, highlighting differences in biochemical pathways (glycolysis vs. ABE fermentation) and titer yields from different strains, along with pretreatment strategies used. It distinctly emphasized the downstream conversion pathways of algal carbohydrates, covering advanced fermentation strategies, scalability challenges and future research directions. Moreover, an insightful comparative analysis of industrial applications, fuel properties, and market feasibility has been attempted successfully. Also, this review highlights the latest technological advancements in conversion strategies that support commercial viability and economic sustainability using algal biomass as a feedstock, thus providing an holistic framework.

2 Algal biomass, pretreatment and hydrolysis

2.1 Algal biomass production

Algal biomass production serves as the basis for biofuel and bioproduct generation, depending on the cultivation of algae under optimized environmental and nutritional conditions to achieve high biomass yield and desirable biochemical composition (Dolganyuk et al., 2020). On the basis of the availability of light and carbon source, algae can be cultivated through autotrophic, heterotrophic, or mixotrophic modes (Abreu et al., 2022; Nicodemou et al., 2022; Yun et al., 2021). Autotrophic cultivation, which utilizes sunlight and CO₂ through photosynthesis, represents the most sustainable approach. In contrast, heterotrophic cultivation depends on organic carbon sources such as glucose in the absence of light and often yields higher biomass productivity. Mixotrophic cultivation integrates both strategies, offering enhanced flexibility and yield potential. Algae can also utilize inorganic carbon for metabolic growth while reducing environmental carbon footprint for producing clean energy (Onyeaka et al., 2021). Their cultivation can be performed in open systems (e.g., raceway ponds), closed systems (e.g., photobioreactors) or hybrid systems (Narala et al., 2016; Banerjee and Ramaswamy, 2019). Open ponds are cost-effective and suitable for large-scale production, although they are prone to contamination and generally yield lower productivity. Conversely, photobioreactors enable precise control of growth conditions, resulting in higher biomass quality and productivity, although at higher operational costs. To improve productivity and reduce costs, optimization through strain selection, genetic engineering, and process design is essential.

The biochemical composition of algal biomass is a determining factor for its suitability in diverse applications (Condor et al., 2022a). Algae are complex photosynthetic organisms that synthesize a diverse array of biomolecules, primarily lipids, carbohydrates, and proteins, along with minor constituents such as pigments, nucleic acids, vitamins, and minerals (Calijuri et al., 2022). The relative proportions of these components vary across species and are strongly influenced by growth conditions such as nutrient availability, light intensity, temperature, and salinity (Ekpan et al., 2025). Lipids are among the most valuable constituents of algal biomass, serving as a precursor for biodiesel and other hydrocarbon fuels. Many microalgae can accumulate lipids up to 5%–30% of their dry weight, but can increase to 40%–70% in oleaginous species under nutrient stress, particularly nitrogen limitation, whereas macroalgae generally contain <10% lipids (Sibi et al., 2016). These lipids mainly consist of triglycerides, phospholipids, and glycolipids, which can be converted into fatty acid methyl esters (FAMEs) for biodiesel production. However, nitrogen limitation that promotes lipid accumulation simultaneously suppresses cell division, reducing overall biomass productivity. Carbohydrates constitute another major fraction (10%–60% of microalgal and 30%–70% of macroalgal dry biomass), and their levels are influenced by different species, cultivation methods and the cell growth phase (higher levels typically observed during the stationary phase) (Markou et al., 2012). They exist as structural polysaccharides (e.g., glycoproteins, cellulose, hemicellulose) and storage polysaccharides (e.g., starch, laminarin, chrysolaminarin) and are found throughout the cell wall, inner layers containing glycoproteins, hemicellulose, and cellulose, and outer layers rich in pectin and alginates. Carbohydrates serve as key substrates for bioethanol and biobutanol production through microbial fermentation, and under stress or nutrient-limited conditions, their accumulation increases significantly, thus improving overall yields. Microalgal species such as Chlorococcum, Chlorella, Scenedesmus, Dunaliella, and Chlamydomonas are especially rich in carbohydrates, making them promising feedstocks for third/fourth-generation biofuels (Khan et al., 2023). Proteins typically constitute 20%–60% of microalgal dry biomass and 5%–30% of macroalgal biomass, with higher levels observed under nitrogen-replete conditions and during exponential growth and are essential for cellular metabolism and growth. Although less directly useful for fuel production, algal proteins contribute to valuable by-products such as animal feed, nutraceuticals, and fertilizers (Wang et al., 2021). Nitrogen availability directly affects protein synthesis, with depletion often triggering a shift toward lipid or carbohydrate accumulation. Overall, the biochemical composition of algal biomass is highly dynamic and tunable, offering opportunities to direct metabolism toward desired products through nutrient management, stress induction, or genetic modification.

The algal growth is affected by several parameters, including light intensity, temperature, pH, nutrient concentration, and CO₂ availability (Chowdury et al., 2020). Essential nutrients such as nitrogen, phosphorus, sulfur, and trace elements play crucial roles in cellular metabolism, and manipulating these factors can redirect carbon fluxes to promote the accumulation of specific biomolecules. Algae have the potential to survive under extremely harsh conditions and acclimate themselves in high saline, high temperature and nutrition-deprived conditions. Several studies have investigated how chemical additives, growth regulators and cultivation strategies can alter the biochemical composition of algae (Sun et al., 2019). For instance, supplementation with sodium acetate (NaAc) under mixotrophic conditions in Micractinium reisseri FM1 enhanced biomass, lipids, and carbohydrates production (Cao et al., 2022). Moreover, fed-batch cultivation outperformed batch culture, yielding higher growth and lipid accumulation. NaAc addition also increased the levels of saturated and polyunsaturated fatty acids, although protein synthesis declined, indicating a metabolic trade-off. One study showed that supplementation with KNO₃ in phosphate-free basal media significantly increased carbohydrate yield in Chlorella minutissima, while K₂HPO₄ and NaHCO₃ enhanced carbohydrate production in Spirulina species (Tourang et al., 2019). Similarly, plant growth regulators such as NAA (naphthalene acetic acid) and PAA (phenylacetic acid) stimulated biomass and monosaccharide synthesis (Yu et al., 2015). Another study showed that nitrates and bicarbonates play crucial roles in enhancing carbohydrate synthesis in Chlorella thermophila, emphasizing the potential of nutrient manipulation to boost biomass production (Sarkar et al., 2022). Nutrient starvation (especially nitrate and phosphate) reduces biomass but increases carbohydrate levels. For instance, Chlorella vulgaris showed a fourfold carbohydrate increase under nutrient-limited conditions (Oraby et al., 2023). Under optimal CO₂ conditions, Chlorella kessleri Bh-2 and Scenedesmus sp. K-7 accumulated >70% carbohydrates, respectively (Bauenova et al., 2024). Similarly, Ettlia texensis showed a 1.3-fold increase in carbohydrate accumulation when grown in wastewater-based media (Samadhiya et al., 2023). Currently, various nanoparticles are being explored to enhance algal biomass and, consequently, ethanol production (Elshobary et al., 2024). Recently, biomass of the green alga Chlorococcum minutum was improved using graphene-oxide-supported platinum–ruthenium (Pt-Ru/RGO) nanoparticles in TAP medium, resulting in a significant increase in ethanol yield through fermentation (Varaprasad et al., 2022).

Strategies like two-stage cultivation providing nitrogen in the first stage to boost growth, followed by nitrogen deprivation to enhance carbohydrate accumulation, have been used as an effective method (Nagappan et al., 2019). Other approaches, such as response surface methodology (RSM) and artificial neural networks (ANN), have been employed to optimize cultivation conditions, achieving up to 59.5% carbohydrate content in Chlorella vulgaris (Condor et al., 2022a). Notably, lysine-supplemented cultures reached optimal carbohydrate levels in a shorter time, and at an initial pH of 9.0, carbohydrate and bioethanol production increased nearly threefold (Chandra et al., 2020). These findings highlight the critical influence of pH and nutrient optimization on enhancing yields and suggest the potential of low-cost lysine sources such as potato peel waste or soya meal to make the process more economical. Similarly, another study on Chlorella vulgaris investigated the use of glycerol and glucose as carbon sources for synergistically enhancing biomass and metabolite production (Yu et al., 2023). While glycerol alone supported growth, combining it with glucose significantly enhanced biomass yield, productivity, and synthesis of lipids and soluble carbohydrates. This synergistic effect demonstrates the potential of mixed carbon substrate combinations as cost-effective feedstocks for sustainable microalgal biofuel production. A study on Desmodesmus sp. CNW-N showed that nitrogen starvation redirected carbon flux from lipid to carbohydrate synthesis by inhibiting acetyl-CoA carboxylase (ACC). Similarly, treatment with the ACC inhibitor clethodim further increased carbohydrate storage, highlighting the role of metabolic regulation in optimizing biofuel precursors (Yeh et al., 2022). In another study, supplementation of growth medium with low concentrations of carbohydrates (0.05 g/L) improved biomass in Chlorella vulgaris, Arthrospira platensis, and Dunaliella salina, with Chlorella vulgaris showing the highest carbohydrate accumulation (16.97%) (Andreeva et al., 2021). These findings underscore the importance of nutrient composition in maximizing carbohydrate accumulation for biofuel production.

The harvesting of algal biomass involves separating and recovering cells from the growth medium and is one of the most cost- and energy-intensive stages of algal bioprocessing due to small cell size, low culture density, and the large volumes of water handled (Deepa et al., 2023; Qin et al., 2023; Singh and Patidar, 2018; Zhu et al., 2024). As this step alone can account for nearly 20%–30% of total production costs, developing efficient and economical harvesting strategies is crucial for ensuring the commercial viability of high-yield biofuel production. Typically, separation is done using flocculation, flotation, or gravity sedimentation and recovery of cells through centrifugation or filtration processes; each approach has its own advantages and limitations. Centrifugation is widely used in industrial microalgae harvesting due to its suitability for large-scale processing and broad applicability across species, achieving recovery efficiencies above 90%. However, its high energy demand and potential for cell damage limit its use mainly to high-value products, although integrating pre-flocculation can significantly reduce energy costs. Filtration using micro- or ultrafiltration membranes having different pore sizes is effective for biomass concentration, yet it faces membrane fouling, frequent cleaning, and high operational costs, which limit its economic feasibility at large scale. Sedimentation is a simple, low-cost, and energy-efficient harvesting method in which microalgae are separated from water through natural gravitational settling in sedimentation ponds or basic tanks. It is particularly suitable for low-value applications such as biofuel production; however, its slow separation rate and low efficiency, especially for small-sized algal cells, often necessitate a preliminary coagulation or flocculation step to improve harvesting performance. Flocculation is one of the most widely used physicochemical methods for harvesting microalgae because of its cost-effectiveness and ability to rapidly aggregate cells by neutralizing their negatively charged surfaces (Matter et al., 2019). This method involves adding flocculants such as multivalent metal salts (e.g., aluminium sulfate and ferric salts) or polymeric agents (e.g., polyacrylamides and chitosan), which help to form dense flocs that can be easily separated by sedimentation (Vu et al., 2020). While inorganic flocculants are efficient, they often lead to biomass contamination and sludge generation, limiting downstream applications. To address these drawbacks, natural polymers such as chitosan are increasingly used as sustainable alternatives. The flocculation performance is highly sensitive to factors such as pH, ionic strength, cell concentration, and cultivation conditions, which continue to pose challenges for large-scale implementation. More recently, biological harvesting approaches such as bioflocculation using plant, bacterial, or fungal-derived biocoagulants have gained attention as sustainable alternatives, offering high recovery efficiencies without compromising biomass quality (Heredia-Martínez et al., 2025). Plant-based biocoagulants, such as Moringa extracts combined with chitosan, have achieved recovery efficiencies of up to 96%, while microbial systems using Bacillus licheniformis and Aspergillus niger report efficiencies above 90% through natural flocculation mechanisms (Badawi et al., 2023). Despite these promising results, further optimization is needed to make these methods economically viable at an industrial large-scale implementation.

2.2 Pretreatment and hydrolysis of algal biomass

Pretreatment and hydrolysis of algal biomass are critical steps that determine the efficiency of downstream bioproduct generation (Pradhan et al., 2023; Megawati et al., 2022; Sultana and Goud, 2026). The structural diversity of algal cell walls, ranging from the highly recalcitrant walls of species such as Scenedesmus to the softer, low-cellulosic walls of Chlorella or certain Ulva species (Popper et al., 2014), requires different pretreatment strategies to effectively disrupt cell wall barriers and release intracellular carbohydrates. Unlike lignocellulosic feedstocks, algal biomass is free of lignin, which simplifies pretreatment and facilitates the release of fermentable sugars (Bhatia et al., 2022). Physical/Mechanical methods such as bead milling, ultrasonication, microwave irradiation and high-pressure homogenization physically disrupt the robust cell wall and are often used for species with resilient walls to reduce the particle size (Samidin et al., 2026). For example, bead milling of Nannochloropsis oculata has been shown to increase reducing sugar yield by 2–3-fold (Montalescot et al., 2015), while ultrasonication of Chlorella vulgaris at 600–1000 W for 30–90 min generates cavitation forces that rupture cells and result in a ∼40–50% increase in carbohydrate release compared with untreated biomass (Liu et al., 2022). Microwave irradiation rapidly heats intracellular water, causing cell wall rupture, and this treatment in Scenedesmus obliquus results in 70% glucose recovery during subsequent hydrolysis (Yirgu et al., 2021). High-pressure homogenization has been effectively applied to Spirulina platensis, achieving over 90% cell disruption in a single pass. Autoclaving is a more aggressive and efficient cell disruption method than conventional mild treatments, as it employs high-pressure steam at temperatures of 110 °C–160 °C for 15–60 min (Phong et al., 2018). Beyond purely physical treatments, physicochemical pretreatment methods combine thermal and mechanical forces to improve the breakdown of the algal biomass. Thermal processes like steam explosion rapidly heat biomass, followed by sudden decompression, thus disrupting cell integrity and depolymerizing polysaccharides, and have been successfully applied to macroalgae such as Laminaria digitata to enhance fermentable sugar release (Garcia-Vaquero et al., 2019). Hydrothermal treatment, or liquid hot water (LHW), solubilizes hemicellulose at high temperatures (160 °C–220 °C), producing hydrolysates rich in glucose and galactose with minimal inhibitor formation, as used for Chlorella pyrenoidosa (Zhang et al., 2013). Supercritical CO₂ pretreatment also shows promise in permeabilizing the cell walls of Nannochloropsis species while maintaining pigment integrity, thus supporting integrated biorefinery applications where multiple products are valorized (Paterson et al., 2025).

Chemical pretreatments further expand the toolbox for algal biomass processing by altering cell wall structures, solubilizing proteins, and converting complex carbohydrates into simpler sugars (Jain and Kumar 2024b). Acid hydrolysis is widely used due to its rapidity, simplicity, and cost-effectiveness compared to other methods. Dilute acids, such as sulfuric, hydrochloric, nitric, or phosphoric acid, are typically used at low concentrations and ambient temperatures to solubilize biomass and release fermentable sugars, whereas concentrated acids are less preferred due to equipment corrosion and the formation of inhibitory byproducts such as furfurals, hydroxymethylfurfural, weak acids, and phenolic compounds and after neutralization, they generate salts which can affect fermentation efficiency adversely (Phwan et al., 2019). Alkaline pretreatment, using reagents such as NaOH, KOH, or Ca(OH)₂, is commonly used for species containing recalcitrant glycoprotein layers or algaenan, as it increases surface area, reduces lignin and hemicellulose content, and facilitates water-mediated separation (Harun et al., 2011). Its effectiveness varies with biomass type, for example, NaOH pretreatment of Scenedesmus quadricauda enhanced carbohydrate accessibility by up to 60%. Alkaline pretreatments are generally milder than acid methods but often result in lower sugar yields and necessitate extensive neutralization. Biological pretreatment provides an environmentally friendly alternative by using enzymes or microbial consortia to degrade cell wall polymers under mild conditions, yielding high glucose levels without producing inhibitory byproducts (Zabed et al., 2019). Enzymes such as cellulase, pectinase, protease, and amylase catalyze the breakdown of cell walls and convert complex carbohydrates into fermentable sugars (Demuez et al., 2015). Nevertheless, the efficiency of biological methods depends on precise control of parameters, including temperature, pH, and enzyme concentration, and scale-up is limited by high costs, long processing times, extensive space requirements, and the need for continuous microbial management. Importantly, integrated strategies that combine physical, chemical, and enzymatic pretreatments have demonstrated notable advantages (Shuai and Ming-Fei, 2026). For instance, sequential acid pretreatment followed by enzymatic hydrolysis enhances fermentable sugar release while reducing chemical usage and minimizing undesirable byproduct formation, illustrating the synergistic potential of combined approaches.

Saccharification of algae-derived carbohydrates is a crucial step in converting algal biomass into fermentable sugars for biofuel production (Abou El-Souod et al., 2021). This process breaks down polysaccharides into simpler sugars via enzymatic or chemical hydrolysis. Thermostable enzymes such as β-glucosidase, cellulase, α-amylase, and amyloglucosidase hydrolyze microalgal biomass, breaking down starch, cellulose, and hemicellulose into fermentable monosaccharides like glucose, xylose, and arabinose to enhance production. Enzymatic hydrolysis converts cellulose into reducing sugars, primarily glucose, through the synergistic action of cellulase enzymes under mild conditions (pH ∼4.8, 45 °C–50 °C), making it more economical than chemical hydrolysis (Al Abdallah et al., 2016). The cellulase complex comprises endoglucanase, exoglucanase, and β-glucosidase, which collectively depolymerize cellulose into glucose. Enzymatic cocktails, including cellulases, hemicellulases, and amylases, are commonly used. For example, cellulase-assisted hydrolysis of Chlorococcum humicola yielded 80%–90% of total fermentable sugars (Harun and Danquah, 2011). Amylase-based hydrolysis is especially effective for starch-rich strains like Chlamydomonas reinhardtii, Chlorella, and Tetraselmis (Peng et al., 2018). Alginate lyases enable efficient saccharification of brown macroalgae, converting alginate into fermentable monosaccharides suitable for bioethanol production (Ravanal et al., 2017). The efficiency of hydrolysis is strongly influenced by substrate properties, including cellulose crystallinity, degree of polymerization, surface accessibility, lignin and hemicellulose content, and pore size. Recent advances in biotechnology and genetic engineering have further improved pretreatment efficiency through cell wall modification of microalgae, enhancing stress tolerance and reducing processing costs. In parallel, emerging technologies, such as heterogeneous catalysts, provide improved substrate–reagent affinity, high thermal and water stability, and increased biomass hydrolysis efficiency, addressing limitations of conventional methods (Arshad N. et al., 2025). Furthermore, microalgae, including Chlamydomonas reinhardtii, Chlamydomonas moewusii, Chlorogonium elongatum, and Chlorella fusca, can ferment intracellular starch into pyruvate, which is further metabolized into acetate, ethanol, glycerol, lactate, H₂, and CO₂ products that vary with species and environmental conditions (Catalanotti et al., 2013). Extremophilic strains, including psychrophilic Chlamydomonas from Antarctic sea ice, tolerate harsh conditions while producing substantial biomass, yielding 156 mg biodiesel and 144 mg bioethanol via combined sonication and enzymatic pretreatment (Kim et al., 2020). The schematic overview of the biofuel production process from algae is shown in Figure 2.

2.3 Biosynthetic pathway for bioethanol and biobutanol production

Bioethanol and biobutanol production begins from central carbon metabolism, which starts with carbohydrate breakdown via the glycolytic pathway (Algal Biomass as a Feedstock for the Sustainable Production of Bioethanol and Biobutanol, 2025) (Figure 3). The process begins with glucose, where enzymes convert it into pyruvate through multiple reactions that generate ATP and NADH. Pyruvate serves as a crucial metabolic hub, directing carbon flow toward various fermentation products depending on the organism’s metabolic profile and enzyme activity. The process of bioethanol production typically begins with the decarboxylation of pyruvate to acetaldehyde by pyruvate decarboxylase (pdc) and ends with the reduction of acetaldehyde to ethanol by alcohol dehydrogenase (adh), also known as the pdc pathway. In an alternative route, pyruvate is first converted to acetyl-CoA through oxidative decarboxylation, after which acetyl-CoA can be further reduced to acetaldehyde and subsequently to ethanol, also known as the Acetyl-CoA pathway (Jain and Kumar 2024a). Yeast and several bacterial systems commonly use these pathways because they need to regenerate NAD⁺ to maintain their glycolytic activity during anaerobic conditions. The biosynthesis of biobutanol proceeds through a complex solventogenic pathway primarily observed in Clostridium species (e.g., Clostridium acetobutylicum). The pathway begins when thiolase catalyses the condensation of two acetyl-CoA molecules to form acetoacetyl-CoA. Acetoacetyl-CoA undergoes reduction as it is processed through intermediates, including 3-hydroxybutyryl-CoA, crotonyl-CoA, and butyryl-CoA. Butyryl-CoA is then converted to butyraldehyde and finally to butanol via a sequential reduction, involving both aldehyde dehydrogenase and Adh. The metabolic pathway requires greater maintenance of redox equilibrium because it consumes more NADH and requires greater metabolic control than ethanol fermentation (Li et al., 2020).

2.4 Process integration

Fermentation of algal biomass represents a promising and innovative route for downstream production. Following hydrolysis, the fermentable sugars are subsequently transformed into bioethanol/biobutanol by microorganisms during fermentation. The major parameters which influence fermentation efficiency are temperature and pH, which directly affect microbial growth and enzyme activity; sugar concentration, where excessive levels can cause osmotic stress and require controlled feeding strategies; and nutrient availability, including nitrogen, vitamins, and minerals, which support microbial metabolism (Tse et al., 2021). Additional factors such as inoculum size, aeration, oxygen levels, and agitation also play important roles in rapid fermentation initiation, suitable microaerobic or anaerobic conditions, and uniform substrate availability. Moreover, the choice of fermentation strategy, whether batch, fed-batch, or continuous, can significantly influence biofuel yield and process scalability.

Generally, fermentation is carried out using two principal approaches: simultaneous saccharification and fermentation (SSF) and separate hydrolysis and fermentation (SHF). In the SSF approach, the pretreatment of algal biomass, enzymatic hydrolysis of polysaccharides, and microbial fermentation are integrated into a single process unit (Olofsson et al., 2008). This integration can reduce processing time, equipment costs, and limit contamination risks; however, it often requires careful optimization of temperature, pH, and enzyme activity to balance both hydrolysis and fermentation. In contrast, the SHF process separates enzymatic hydrolysis and fermentation into distinct steps (Tang et al., 2024). Biomass is first hydrolyzed into sugars, which are then fermented in a separate reactor. This sequential approach allows independent optimization of each step, often resulting in higher overall efficiency. The selection of SSF or SHF depends on algal species, pretreatment strategy, and production objectives. While SSF offers operational simplicity, SHF provides greater process control at the expense of increased complexity. SHF is generally considered more cost-effective for large-scale applications due to its easier parameter control, flexible operation, and reduced residence time per unit operation, despite being a multi-step process. Extensions of these approaches include simultaneous saccharification and co-fermentation (SSCF) and separate hydrolysis and co-fermentation (SHCF) (Marđetko et al., 2025). These methods aim to utilize mixed sugar streams, including both hexoses and pentoses, which are often present in algal biomass. However, many conventional yeast strains are unable to ferment pentose sugars under standard conditions, leading to incomplete sugar utilization, residual biomass, and lower product yields. To address this challenge, recombinant microbial strains capable of fermenting pentose and other complex sugars are being developed (Troiano and Studer, 2025). These engineered strains hold the potential to maximize product generation from diverse carbohydrate sources in algal biomass, making large-scale biofuel production more efficient and economically viable.

3 Bioethanol production from algal biomass

Algae, with their high carbohydrate content, can serve as an effective feedstock for bioethanol production through microbial fermentation (Ho et al., 2013). Efficient ethanol production from algae depends on several interconnected factors: the growth rate and total biomass accumulation, the type and concentration of sugars in the feedstock, and the specific fermentation process used (Tse et al., 2021; Pandit et al., 2025). These factors are strongly influenced by the algal species, as different strains vary in carbohydrate composition and metabolic efficiency. Several researchers have extensively studied the effects of various factors on algal growth and fermentation. Bioethanol can be produced either directly through cellular metabolism in microalgae or indirectly via fermentation of their biomass. Phototrophic microorganisms accumulate polysaccharides and lipids during the light period while carrying out photosynthetic O₂ evolution and CO₂ fixation (Figure 4). Under dark conditions, these organisms switch to fermentation, where stored starch is hydrolyzed by amylases into sugars that are subsequently metabolized to pyruvate through glycolysis (Catalanotti et al., 2013). Notably, certain species such as Chlorococcum littorale have been observed to secrete ethanol directly through their cell walls during dark fermentation, highlighting their potential as efficient bioethanol-producing strains (Ueno et al., 1998).

3.1 Fermentation pathways, conditions and microorganisms

The pathway and microorganisms used for the fermentation of algal-derived sugars critically influence ethanol yield, productivity, and process efficiency. The primary metabolic routes for ethanol production are the glycolytic (Embden–Meyerhof–Parnas, EMP) pathway and the Entner–Doudoroff (ED) pathway. Both pathways metabolize glucose and other fermentable sugars to pyruvate, which is subsequently decarboxylated to acetaldehyde and reduced to ethanol. In microalgae such as Chlamydomonas, pyruvate is reduced to ethanol to maintain intracellular redox balance, via alcohol/acetaldehyde dehydrogenase (ADHI) enzyme catalyzing the conversion of acetyl-CoA to ethanol (Lis et al., 2017). The EMP pathway is the most widely used route by microorganisms like Saccharomyces cerevisiae. In this pathway, one molecule of glucose is converted into two molecules of pyruvate, generating ATP and NADH, and the pyruvate is efficiently transformed into ethanol, making EMP highly suitable for industrial-scale production (Kang and Lee, 2015). In contrast, the ED pathway, employed by bacteria such as Zymomonas mobilis, produces only one ATP per glucose molecule but is more thermodynamically favorable and generates fewer byproducts, which can be advantageous in specific fermentation setups (Flamholz et al., 2013). Different algal species contain varying proportions of glucose, mannose, galactose, and other fermentable sugars, which influence the suitability of specific microorganisms and metabolic routes. A range of native and genetically engineered microorganisms has been explored for algal bioethanol production.

Saccharomyces cerevisiae is the most widely used yeast due to its high ethanol tolerance and efficient fermentation of hexose sugars, although it cannot naturally metabolize pentoses such as xylose or arabinose (Topaloğlu et al., 2023). Saccharomyces cerevisiae, commonly used for algal fermentation, performs optimally at temperatures between 25 °C and 37 °C under anaerobic conditions, producing ethanol up to 14%, with higher concentrations requiring additional distillation. Yeasts such as Pichia stipitis and Kluyveromyces marxianus can ferment a broader spectrum of sugars, including pentoses, making them well-suited for mixed-sugar hydrolysates (Rouhollah et al., 2007). Zymomonas mobilis, a Gram-negative bacterium, exhibits high ethanol productivity, lower biomass yield than yeast, and metabolizes glucose, fructose, and sucrose via the ED pathway; it can also be genetically engineered for pentose utilization (Xia et al., 2019). Engineered strains of Escherichia coli can ferment both hexoses and pentoses and tolerate certain fermentation inhibitors, although their ethanol yields and tolerance are generally lower than yeast or Zymomonas (Kim et al., 2007). Recent advances in synthetic biology have enabled the development of recombinant strains capable of simultaneously metabolizing multiple sugars and withstanding inhibitors present in algal hydrolysates. For example, recombinant Saccharomyces cerevisiae expressing xylose reductase and xylitol dehydrogenase can efficiently ferment both glucose and xylose, improving ethanol yields from complex algal carbohydrate mixtures (Matsushika et al., 2008). Various studies have shown that using feedstocks from Chlamydomonas reinhardtii, Chlorella vulgaris, and Chlorococcum minutum and fermentation at 27 °C with Saccharomyces cerevisiae yielded substantial ethanol, although acidic pH conditions inhibited production for most algal species (Sudha et al., 2021; Varaprasad et al., 2021). Notably, Chlamydomonas exhibited optimal ethanol yields at a near-neutral pH range of 7–8. A comparative summary of bioethanol production from algal biomass, emphasizing the influence of strain selection, pretreatment approaches, and the ethanol titers reported in recent studies are discussed in Table 1. Extensive literature exists on the production of bioethanol from algal biomass, highlighting its potential as a renewable and sustainable biofuel feedstock (Chandrasekhar et al., 2023; Melendez et al., 2026).

TABLE 1. Bioethanol production from algal biomass.

3.2 Metabolic engineering and recent cases

Metabolic engineering has emerged as a pivotal strategy to enhance bioethanol production from microalgae by modifying native metabolic pathways or introducing heterologous genes to increase carbohydrate availability and fermentation efficiency. Microalgae with truncated chlorophyll antenna complexes exhibit better light utilization, leading to enhanced biomass and carbohydrate accumulation (Kumar et al., 2021). Microalgae naturally accumulate carbohydrates, which serve as substrates for fermentable sugar production, but limitations such as low sugar release, incomplete conversion, and ethanol toxicity often restrict yields. To overcome these bottlenecks, targeted engineering approaches redirect carbon flux, overexpress key enzymes, or introduce novel fermentative pathways, which in turn improve ethanol yields during downstream fermentation. For example, modifying carbohydrate metabolism by overexpressing ADP-glucose pyrophosphorylase (AGPase) in Chlorella vulgaris increased carbohydrate content, providing more substrate for saccharification and ethanol fermentation (Saha et al., 2024), while the introduction of pdc and adh genes from Saccharomyces cerevisiae enables direct conversion of pyruvate to ethanol, bypassing native metabolic constraints (Lewicka et al., 2014). Similarly, knockdown of competing pathways, such as starch-degrading enzymes or lipid biosynthesis routes in algae, redirects carbon toward lipid/carbohydrate storage, enhancing ethanol precursor availability (Chintagunta et al., 2024). Ethanol tolerance can be further improved through genetic modifications, including overexpression of heat shock proteins (Hsps), chaperones, or efflux pumps, allowing microalgae or algal-yeast co-cultures to maintain metabolic activity under higher ethanol concentrations. Additionally, synthetic consortia and co-culture systems, where engineered algae supply fermentable sugars to ethanologenic microbes, can significantly improve overall ethanol productivity (Naseema Rasheed et al., 2023). Beyond genetic interventions, bioethanol production can be enhanced by nanotechnology, optimizing cultivation conditions, nutrient availability, photosynthetic efficiency, and carbon fixation (Sridhar et al., 2025). Combining these strategies with advances in genome editing, synthetic biology, and systems-level metabolic modeling offers significant potential to design optimized algal strains for scalable, efficient bioethanol production.

3.3 Ethanol toxicity and tolerance enhancement

Ethanol accumulation during fermentation can be toxic to organisms, including algae, limiting bioethanol yield and productivity. High ethanol concentrations disrupt cell membranes, impair enzyme activity, and interfere with metabolic pathways, ultimately reducing growth and fermentation efficiency (Jiang et al., 2017). Different algal species and fermentative microorganisms exhibit varying levels of intrinsic ethanol tolerance. For example, Saccharomyces cerevisiae can tolerate ethanol concentrations up to ∼14% (Varize et al., 2022), whereas many native algae show sensitivity at much lower levels. Enhancing ethanol tolerance is therefore essential for efficient bioethanol production. Adaptive laboratory evolution (ALE) has been used to gradually expose microorganisms to increasing ethanol levels, selecting for more tolerant strains. For instance, Saccharomyces cerevisiae evolved via ALE has demonstrated improved tolerance to 16%–18% ethanol (Mavrommati et al., 2023). ALE is less studied in algal systems (LaPanse et al., 2021). Genetic engineering strategies have also been employed, including overexpression of stress response genes, modification of membrane lipid composition to maintain membrane integrity, and introduction of efflux pumps to reduce intracellular ethanol accumulation. Stress-adapted strains, such as salt-tolerant, temperature-tolerant, or inhibitor-resistant strains, have been developed to enhance fermentation performance. These adapted strains showed improved sugar uptake, greater ethanol tolerance, and enhanced stress resistance, resulting in higher fermentation efficiency and increased ethanol yields (Ahmad et al., 2021). Engineered strains of Zymomonas mobilis and recombinant Saccharomyces cerevisiae expressing ethanol tolerance genes have shown enhanced productivity under high ethanol conditions (Tang et al., 2022). Process-level strategies can further mitigate ethanol toxicity. In microalgae-based systems, ethanol tolerance enhancement is particularly important for species such as Chlamydomonas reinhardtii or Chlorella vulgaris, which may be used in co-culture fermentations with yeasts.

3.4 Product recovery and process optimization

The efficient recovery of ethanol is a critical step in algae-based bioethanol production, as it directly impacts overall process yield, energy consumption, and economic feasibility (Kumari et al., 2024). Ethanol concentrations obtained from fermentation typically range from 10% to 15%, depending on the algal feedstock and microorganism used. To obtain fuel-grade ethanol (>95% purity), distillation remains the most widely applied method. However, due to its high energy demand, alternative recovery techniques such as vacuum distillation, pervaporation, membrane separation, and azeotropic distillation are increasingly being explored (Zentou et al., 2019). For instance, vacuum distillation has been used to recover ethanol from Chlorella vulgaris hydrolysates with reduced energy consumption (Labbafi et al., 2025), while pervaporation membranes have successfully concentrated ethanol from mixed-sugar algal fermentations. Integrating recovery strategies with fermentation can improve overall efficiency. In situ ethanol removal using techniques such as gas stripping, vacuum extraction, or adsorption mitigates ethanol-induced inhibition by preventing product accumulation in the fermentation medium, thereby sustaining microbial activity and enhancing fermentation rates and overall yields (Kanani et al., 2026). Process optimization also involves a combination of upstream and downstream strategies. Upstream approaches include optimizing algal cultivation to enhance carbohydrate accumulation, improving biomass harvesting, and efficient pretreatment to release fermentable sugars. Downstream strategies focus on optimizing fermentation conditions and integrating ethanol recovery steps. Advanced fermentation strategies, such as fed-batch or continuous fermentation, help maintain optimal sugar concentrations, reduce substrate inhibition, and increase volumetric productivity. Additionally, adopting a biorefinery approach enhances process sustainability. Residual algal biomass after ethanol extraction can be valorized to produce co-products such as proteins, lipids, pigments, biofertilizers, or biogas, which reduces waste and improves overall process economics. For example, lipid-rich residues from Chlorella or Scenedesmus fermentations have been utilized for biodiesel production, while protein fractions have been applied as animal feed (Sharma et al., 2025).

4 Biobutanol production from algal biomass

Carbohydrate-rich algal biomass acts as a sustainable and eco-friendly feedstock for ABE fermentation, enabling efficient biobutanol production (Bajwa et al., 2023). ABE fermentation, also known as the Weizmann process, is a biphasic heterofermentative pathway in which carbohydrates from algal biomass are hydrolyzed and anaerobically fermented by Clostridium species to yield butanol, ethanol, and acetone, typically at a molar ratio of 6:3:1 (Lin et al., 2023a). The process comprises two phases of ABE fermentation, acidogenesis (pH 5.0–6.0) and solventogenesis (pH 4.0–5.0) (Kumar et al., 2023). During acidogenesis, occurring in the exponential growth phase, carbohydrates are converted into organic acids such as acetate and butyrate, generating ATP for cellular growth and maintenance and causing a drop in pH due to acid accumulation. When pH decreases, and undissociated acid levels increase, the culture enters solventogenesis, the stationary phase, in which accumulated acids are reabsorbed and metabolically converted into solvents. The key enzymes causing these conversions are acetoacetate decarboxylase (acetone formation), alcohol/aldehyde dehydrogenases (butanol and ethanol production), and butyrate–acetoacetyl-CoA transferase (acid-to-solvent conversion) (Lin et al., 2023a).

4.1 Pretreatment, fermentation efficiency, and microbial strains

The efficiency of ABE fermentation from algal biomass is strongly influenced by the combined influence of pretreatment strategies, microbial performance, and overall process optimization. Among pretreatment approaches, dilute acid hydrolysis using 2%–6% H₂SO₄ at 121 °C–131 °C for approximately 20 min commonly achieves hydrolysis efficiencies exceeding 80%. For example, Chlorella vulgaris subjected to sequential alkali–acid pretreatment produced 13.1 g/L butanol (Wang et al., 2016), while Gelidium amansii treated with 2% sulfuric acid yielded 3.46 g/L (Hong et al., 2020). Nevertheless, species-specific responses remain significant, as optimized processes enabled Gracilaria edulis to produce 8.56 g/L butanol, wastewater-grown Chlorella sp. DEE006 to reach 6.23 g/L, and Chlamydomonas reinhardtii to achieve 10.8 g/L (Onay, 2022). Sequential alkali–acid hydrolysis of Chlorella species can release up to 88.5% fermentable sugars during the acid step, followed by approximately 75% enzymatic conversion, generating butanol titers comparable to those obtained from freeze-dried biomass (Wang et al., 2016). Process intensification strategies further improve fermentation efficiency and product recovery. In situ extractive fermentation using solvents such as octanol or the application of alginate-immobilized cells effectively alleviates butanol titers and reduces downstream separation costs (Ye et al., 2018). In addition, supplementation with metal ions such as zinc or calcium promotes acid re-assimilation, increasing butanol titers from 11.7 to 16.1 g/L in glucose-based systems, with similar potential observed for algal hydrolysates (Wu et al., 2016). These approaches underscore the importance of integrating optimized pretreatment, immobilized-cell technologies, and refined fermentation control to enhance solvent productivity and overall process sustainability.

Microbial strain selection remains a critical determinant of ABE fermentation performance. Clostridium species remain the most widely used microorganisms, particularly Clostridium acetobutylicum and Clostridium beijerinckii (Jones, 2024). While Clostridium acetobutylicum ATCC 824 produced yields comparable to starch-based controls on diluted-acid and enzymatic hydrolysates of Chlorella vulgaris (Wang et al., 2014b), the wild-type strain ATCC 834 efficiently fermented acid-pretreated Chlorella hydrolysates, yielding 6.23 ± 0.19 g/L butanol within 72 h. Under solvent-rich conditions, immobilization of Clostridium acetobutylicum in alginate–adsorbent beads reduced energy demand to 4–9 MJ/kg butanol and increased solvent productivity by more than 2.5-fold (Ye et al., 2018). Similarly, Clostridium beijerinckii DSMZ 6422 produced 11.88 g/L butanol and 13.89 g/L total ABE from a mixed feed of Dunaliella salina biomass (200 g/L) and glucose (60 g/L) (Tekin et al., 2024), while continuous immobilized-cell cultures of Clostridium beijerinckii NCIMB 8052 maintained solvent concentrations of 10–13 g/L with butanol yields reaching productivities of 0.40 g/L/h over extended operations (Liu et al., 2018). Other promising isolates include Clostridium sp. WK, which produced 3.46 g/L butanol from sulfuric acid-pretreated Gelidium amansii hydrolysate; Clostridium saccharoperbutylacetonicum N1-4 from Sargassum hydrolysate, yielding 1.76 g/L butanol and 3.14 g/L total solvents; and a native mesophilic Clostridium strain HG1, producing 4.47 g/L butanol and 8.60 g/L total ABE (Vamsi Krishna et al., 2022). Beyond clostridia, engineered Bacillus subtilis Grsw2-B1 has achieved up to 2% (w/v) butanol production by leveraging rapid growth and sporulation traits (Kataoka et al., 2011). Co-culture systems integrating Clostridium acetobutylicum with hydrolysate-degrading bacteria further enhance butanol yields and sugar utilization from both algal and lignocellulosic substrates (Du et al., 2020). Metabolic engineering approaches have also improved strain performance (Pugazhendhi et al., 2025). For example, overexpression of bdhA (butanol dehydrogenase), which increases solvent titers in wild-type isolates (Lütke-Eversloh and Bahl, 2011), while deletion of ccpA (Catabolite Control Protein A) in Clostridium acetobutylicum enables the co-utilization of glucose and xylose, significantly improving butanol yields in mixed-sugar fermentations (Ren et al., 2010). Thus, the integration of optimized pretreatment technologies, advanced fermentation strategies, and robust engineered microbial systems is essential for maximizing biobutanol production from algal biomass. Such a holistic approach not only enhances solvent titers and improves process economics but also strengthens the sustainability and scalability of algal biorefineries, positioning algal-derived biofuels as key contributors to the transition toward a low-carbon, bio-based economy. Table 2 provides a comparative summary of biobutanol production from algal biomass, highlighting the diversity of algal feedstocks and process parameters such as biomass pretreatment methods, microorganisms used and the corresponding butanol titers.

TABLE 2. Biobutanol production from algae through ABE fermentation.

4.2 Butanol toxicity and tolerance enhancement

A major limitation in ABE fermentation is butanol toxicity, which significantly constrains solvent yields and microbial viability. Butanol’s lipophilic nature disrupts cellular membranes, denatures proteins, and impairs homeostasis. Excess butanol increases membrane fluidity and permeability, causing ion and metabolite leakage, loss of proton motive force, and ultimately cell lysis. It also interferes with ATP synthesis and nutrient transport, reducing energy metabolism and growth (Ezeji et al., 2010). Most solventogenic Clostridium species cannot tolerate butanol above ∼2% (v/v), with Escherichia coli showing 50% growth inhibition at 0.8% (v/v), and Pseudomonas species tolerating up to 6% (v/v) with slower growth kinetics (Liu et al., 2017). In cyanobacteria, such as Synechocystis PCC 6803, ALE increased tolerance from 0.2% to 0.5% (v/v) through prolonged sublethal exposure, promoting beneficial mutations (Wang et al., 2014a). Recent strategies combining ALE and metabolic engineering have further enhanced tolerance. Modifying membrane lipid composition by increasing saturated fatty acids or adjusting branched-to-straight-chain ratios reduces membrane fluidity and improves solvent resistance (Linney et al., 2023). Overexpression of Hsps, chaperones, and efflux transporters (e.g., AcrAB-TolC) stabilizes proteins and facilitates active solvent export (Zingaro and Eleftherios, 2013). In Clostridium, overexpressing solvent tolerance genes (bld, hsp, groESL) and global regulators (Spo0A, Rex) strengthens stress response and sustains butanol synthesis at high concentrations (Mann et al., 2012). Protoplast fusion between Clostridium strains has generated fusants combining high solventogenic capacity with enhanced tolerance, achieving productivities up to 7.98 g/L butanol (Ferhan et al., 2016). Overall, improving butanol tolerance is critical for industrial-scale ABE fermentation. Integrating evolutionary engineering, metabolic reprogramming, and membrane adaptation offers a powerful approach to overcome toxicity barriers, enabling robust, high-yielding microbial platforms for sustainable biobutanol production from algal biomass.

4.3 Product recovery and process optimization

In situ product recovery technologies significantly enhance ABE fermentation efficiency by reducing product inhibition and increasing overall solvent yield. Among these methods, gas stripping has been widely used at larger scales, achieving ∼59%–67% butanol recovery efficiency with condensed butanol concentrations around 119 g/L in the recovered stream. When coupled with two-stage in situ recovery systems, butanol can be selectively removed and concentrated in the recovery stream to levels of 300–360 g/L, while achieving overall process efficiencies of 70%–80%. However, the actual fermentation broth concentrations remain significantly lower due to product toxicity constraints (Diez-Antolinez et al., 2018). Additionally, coupling gas stripping with continuous fermentation can boost butanol production by up to 9-fold compared to conventional batch operations (Lin et al., 2023b). The ABE fermentation requires careful optimization of substrate loading (50–90 g/L) and pH to achieve maximum yields. Consolidated bioprocessing (CBP) further integrates fermentation, hydrolysis, and pretreatment into a single operation, reducing complexity and operational costs (Zyl et al., 2007). Additional strategies such as green solvent recovery using lipids, ultrasonication for enhanced extraction, and the development of multipurpose strains capable of both hydrolysis and solvent production further enhance process sustainability and resource utilization (Zou et al., 2021).

5 Comparative analysis: bioethanol vs. biobutanol

From an economic and process standpoint, ethanol production from algae is relatively straightforward and scalable because algal carbohydrates can be readily fermented through simple metabolic pathways with minimal downstream processing, making it a cost-effective option for large-scale biofuel production (Ho et al., 2013; Sarwer et al., 2022). In contrast, biobutanol production relies on the ABE fermentation pathway, which involves multiple metabolic stages, making it more complex and costly and hindered by slower microbial growth, lower product titers, increased downstream separation requirements and strong inhibition effects at concentrations exceeding 2% (w/v) (Nabila et al., 2024). Synthetic routes for 1-butanol commonly depend on petrochemical intermediates like propylene, which increases production costs (Choi et al., 2021). Although butanol recovery remains energy-intensive due to processes such as distillation and gas stripping, advances in metabolic engineering, strain development, and in situ product recovery technologies are steadily enhancing yields and improving cost efficiency (Diez-Antolinez et al., 2018; Visioli et al., 2014). Despite these challenges, biobutanol is increasingly recognized as a superior long-term renewable fuel owing to its favorable physicochemical and combustion properties, including higher energy density, excellent miscibility with gasoline and diesel, and improved storage stability (Figure 5). These characteristics enable its direct use in conventional engines with little or no modification and also enhance its versatility as a platform chemical for solvents, plasticizers, and synthetic lubricants (Serrano-Echeverry et al., 2025; Obergruber et al., 2021).

From a fuel performance perspective, ethanol is often favored for maximizing engine power output, whereas butanol enhances combustion quality, which improves overall fuel efficiency and significantly lowers hydrocarbon and CO emissions (Elfasakhany, 2023). Moreover, large-scale algal cultivation enables the co-production of ethanol and butanol, ensuring efficient biomass utilization while supporting carbon sequestration and greenhouse gas mitigation strategies (Gopalakrishnan et al., 2025). In terms of fuel properties, ethanol exhibits lower energy density, higher volatility, and strong hygroscopic behavior compared to gasoline, which reduces fuel efficiency and complicates storage and blending (Gajewski et al., 2025). Its high affinity for water promotes phase separation and limits its role as a true drop-in fuel, while its lower heating value per liter and volatility further restrict transportation through existing petroleum pipelines. One of the key determinants of the large-scale adoption and long-term sustainability of biofuels is their compatibility with existing engines and fuel infrastructure. Ethanol, the most widely used biofuel and commonly blended with gasoline in formulations such as E10 or E20, faces several limitations in this regard (Barua et al., 2023; Hoekman and Broch, 2018). Its high volatility and hygroscopic nature make it prone to moisture absorption, leading to phase separation, reduced combustion efficiency, and increased corrosion in storage and fuel distribution systems (Gajewski et al., 2025). Moreover, ethanol can adversely affect engine lubrication and component durability by diminishing the protective properties of lubricants, particularly those containing additives such as zinc dialkyldithiophosphate (ZDDP). These challenges necessitate the use of additional corrosion inhibitors and specialized materials in pipelines, storage tanks, and vehicle fuel systems, thereby increasing maintenance requirements and infrastructure costs (Costa et al., 2023). In contrast, butanol, particularly n-butanol and isobutanol, offers superior compatibility with current engine and fuel infrastructure (Zhen et al., 2020). Its lower vapor pressure, reduced volatility and hygroscopicity, higher viscosity, and greater energy content confer improved stability during storage and distribution. Its physicochemical characteristics are closely aligned with gasoline properties, minimizing risks during combustion, storage, and transport (Çelebi et al., 2025; Olson et al., 2023). These characteristics allow higher blending ratios with gasoline without phase separation or engine complications (Obergruber et al., 2021). Additionally, butanol’s lower corrosivity allows it to be distributed through existing fuel pipelines with minimal system adjustments. Studies further indicate that butanol causes less degradation of metals and elastomers commonly found in engines and storage systems, underscoring its potential as a stable, more practical, durable and infrastructure-compatible biofuel. A comparison of the fuel properties of bioethanol and biobutanol is shown in Table 3.

TABLE 3. Comparative fuel properties of bioethanol and biobutanol.

From a techno-economic perspective, bioethanol production is currently more cost-effective than biobutanol, with estimated production costs ranging from approximately USD 0.4–0.8 per liter compared to USD 1.2–2.5 per liter for biobutanol (Obiora, 2022; Baral and Shah, 2016; Llano et al., 2023). This difference is primarily attributed to higher fermentation yields (0.45–0.50 g/g sugars) and product titers (50–120 g/L) in ethanol systems, which reduce downstream processing costs (Tavares et al., 2025). In contrast, biobutanol production is limited by lower yields (0.25–0.35 g/g sugars), lower titers (10–20 g/L), and significant product toxicity, necessitating more complex and energy-intensive separation processes (Russmayer et al., 2019). Although biobutanol offers superior fuel properties, its higher production cost and process complexity currently limit its large-scale commercialization compared to bioethanol.

6 Industrial applications and market potential

Fuels derived from algal biomass exhibit favorable physicochemical properties as discussed above, which enhance their efficiency and applicability as alternative fuels (Fatima et al., 2025; Amalapridman et al., 2025). These characteristics position algal bioethanol and biobutanol as competitive candidates within the global renewable fuel market. Among the two, biobutanol can directly compete with gasoline, whereas bioethanol acts as an indirect substitute and is primarily used as a blending component. With the increasing global demand for high-quality biofuels, projected to account for approximately 12% of total oil demand by 2030, bioethanol and biobutanol are expected to expand alongside conventional fuels, which will continue to meet a significant share of global energy needs. The global biofuel market has undergone a rapid transformation, driven primarily by climate change mitigation policies, rising fossil fuel prices, and advances in industrial biotechnology (OECD, 2025). Bioethanol currently dominates the market, supported by strong government mandates such as ethanol blending targets in countries including Brazil, United States, and India (Marketgrowthreports, 2025). It was valued at approximately USD 97.5 billion in 2025 and is projected to reach around USD 141.0 billion by 2033, expanding at a compound annual growth rate (CAGR) of about 4.6% (Ethanol Market Size, Share & Trends, 2033). This growth is primarily driven by increasing demand for renewable and cleaner energy sources, along with supportive government policies such as biofuel blending mandates and decarbonization initiatives. Large-scale deployment of algal biofuels requires not only efficient production technologies but also well-developed infrastructure for transportation, blending, and integration with existing oil markets. For example, the hygroscopic nature of ethanol limits its transport through conventional petroleum pipelines, necessitating blending at distribution terminals (Tu et al., 2023). Consequently, ethanol is typically transported via road tankers, railcars, or barges and blended with gasoline near the point of use. In India’s Ethanol Blended Petrol (EBP) program, ethanol produced at biorefineries is transported to oil depots, where it is blended with petrol to ensure fuel stability and engine compatibility (Valera and Agarwal, 2025). These logistical challenges highlight the need for integrated infrastructure planning supported by appropriate regulatory frameworks to facilitate the seamless incorporation of biofuels into national energy systems.

Although biobutanol is still at a relatively early stage of commercialization, it is gaining global attention as an advanced high-value biofuel and industrial chemical due to its superior fuel properties and solvent versatility (Serrano-Echeverry et al., 2025; Rai et al., 2026). Gasoline–butanol blends in the range of 16%–20% can be used without engine modification, making biobutanol readily adaptable to current transportation systems (Elfasakhany, 2023). Pilot-scale studies in the United States have demonstrated favorable engine performance and emission profiles for butanol–gasoline blends in conventional spark-ignition engines, positioning biobutanol as a promising option for large-scale deployment. The butanol-diesel blends displayed physicochemical properties similar to those of pure diesel and can achieve comparable or slightly improved brake thermal efficiency. Although slight variations in engine performance may occur depending on operating conditions and blend ratios, these blends are considered promising candidates for transportation fuel applications. The process used low-cost substrates to produce butanol at approximately USD 0.8 per litre, demonstrating its potential for economic viability in commercial production (Mukherjee et al., 2020). In parallel, blending approaches involving hydrotreated vegetable oil (HVO), a type of biodiesel, have been evaluated in combination with fossil fuels to assess improvements in combustion behavior, fuel efficiency, and emission characteristics. Studies examining different HVO blending ratios provide valuable insights for designing advanced multi-fuel blending strategies that enable a gradual transition toward cleaner energy systems while maintaining engine performance and fuel reliability (Kuszewski et al., 2025). The global biobutanol market was valued at approximately USD 15.86 billion in 2023 and is projected to reach around USD 29.37 billion by 2030, representing a CAGR of about 9.2%, driven by increasing demand for renewable fuels and stricter environmental regulations (Bio-Butanol Market Size, 2030). Other forecasts predict that the market will grow from about USD 18.42 billion in 2025 to nearly USD 36.73 billion by 2034, resulting in a 7.9% CAGR, reflecting ongoing industrial use and government-sponsored carbon-reduction programs (Mehra and Goel, 2025). Technological advancements will shape future market trends by influencing industry operations.

Beyond their role as transportation fuels, bioethanol and biobutanol function as green solvents and platform chemicals with broad industrial relevance (Maki et al., 2025; Trusted Bioethanol Partner for B2B, 2026; Pandit and Saha, 2025). Their renewable origin, biodegradability, and low toxicity make them attractive alternatives to petrochemical-derived solvents across multiple sectors, as shown in Figure 5. Bioethanol is extensively used in the pharmaceutical and cosmetic industries, where its low toxicity and antimicrobial properties support applications such as disinfectants, hand sanitizers, formulation stabilizers and solvent systems (Anekwe et al., 2023). It also serves as a key chemical intermediate in the production of ethyl acetate, acetic acid, and bio-ethylene, which are subsequently utilized in packaging materials, paints, and biodegradable plastics (Bagde et al., 2026; Carotenuto et al., 2013). The food and beverage sector employs bioethanol in fermentation processes, flavor extraction, and sterilization applications (Siddiqui et al., 2023). Biobutanol serves as a dual-use biofuel because it now serves as a biochemical base for the production of acrylates, solvents, coatings, and plasticisers, all of which serve multiple industrial purposes (Sohani and Ali Hashemikouchaksaraei, 2025). Biobutanol is used in the paints, coatings, and adhesives industries due to its slower evaporation rate, which enhances coating uniformity, durability, and performance (Barrera and Ileana, 2018). It is a key precursor for the synthesis of butyl acrylate, a critical monomer used in the manufacture of emulsions and pressure-sensitive adhesives. The ability of biobutanol to replace petroleum-based solvents makes it particularly attractive to industries aiming to reduce their environmental footprint. Moreover, biobutanol is recognized as a versatile and eco-friendly alcohol within the chemical industry, with strong potential to substitute petroleum-derived propylene in the production of acetone, butyl acetate, plasticizers, and related chemicals. Its low water affinity and low electrical conductivity also enable applications in the electronics industry, including the fabrication of electronic components and semiconductors. Algae synthesize a wide range of secondary metabolites, including pigments (chlorophylls, carotenoids, and phycobiliproteins), polyunsaturated fatty acids (PUFAs), antioxidants, and vitamins, which have substantial commercial value in different markets (Mehariya et al., 2021). Furthermore, algal carbohydrates, characterized by diverse degrees of polymerization, branching, and sulfation, exhibit bioactive properties that extend their applications (Sarkar et al., 2024). Moreover, residual biomass remaining after biofuel extraction can be integrated into biorefineries to produce value-added co-products, thereby minimizing waste and reducing overall production costs (Dutta et al., 2025). The integration of biorefineries with circular economy models and green chemistry principles is expected to unlock the full potential of bioethanol and biobutanol. Owing to their dual roles as renewable fuels and industrial platform chemicals, these biofuels are increasingly recognized as key contributors to the transition toward a low-carbon, bio-based economy.

Policy support plays a decisive role in overcoming technical and infrastructural challenges and accelerating the acceptance of biofuels. National mandates, blending targets, and financial incentive mechanisms are among the key drivers of biofuel production and market penetration. The experience of the BRICS countries (Brazil, Russia, India, China, and South Africa) provide valuable insights into the role of governance in biofuel development as these rapidly developing economies exhibit diverse energy demands and biomass resource availability (Emishyan and Guliev, 2025). Comparative analyses of these countries highlight the importance of legislative frameworks, blending obligations, national action plans, and government support mechanisms, including subsidies and fiscal incentives. Such assessments also identify major implementation barriers and future opportunities, offering a consolidated policy template for advancing biofuel development (Saravanan et al., 2020). Several companies worldwide are actively advancing algal biofuel production through innovative technologies and integrated systems. In the United States, Algenol Biotech utilizes its Direct to Ethanol™ process, a photobioreactor-based system in which sunlight-driven microalgae function as miniature biorefineries to produce ethanol directly (The Pilot-Scale Integrated Biorefinery of Algenol, 2026). Cellana Inc. focuses on cultivating algae for biofuels and high-value co-products (Cellana’s Kona, 2026). Sapphire Energy is known for its “green crude” technology, producing algae-based oil convertible into gasoline, diesel, and jet fuel (Sapphire Energy Produces Crude Oil from Algae, 2008). Startups like Manta Biofuel and OriginClear are developing efficient cultivation and water treatment solutions to enhance algal growth and biofuel yield (Energy Innovation, 2026). Genifuel Corporation converts organic waste, including algae, into renewable fuels via hydrothermal processing (Genifuel - Welcome, 2026), whereas European companies such as Proviron are producing algae-derived biofuels to reduce reliance on fossil fuels. Other notable players include Algaeventure Systems, Algaetech International, and Origin Oils, which focus on algae-based biofuels and oil extraction technologies (Algae University, 2026). Collectively, these companies are driving the industrial development of sustainable algal biofuels, addressing both energy security and environmental concerns.

7 Challenges and future prospects

The large-scale production of algal bioethanol and biobutanol is constrained by a complex interplay of technical, biological, economic, and environmental challenges, which collectively limit its industrial feasibility. Biotechnological bioethanol and biobutanol production is constrained by several challenges, including product toxicity, high substrate costs, low volumetric productivity, and limited understanding of the underlying microbial genomic and regulatory mechanisms (Rao et al., 2026). Despite considerable progress in genetic and metabolic engineering, the development of robust, high-yielding microalgal strains continues to be hindered by low transformation efficiencies, unstable transgene expression, and an incomplete understanding of the intricate metabolic pathways (Gimpel et al., 2015; Kumar et al., 2020). Transgene instability may arise from horizontal gene transfer or natural recombination, resulting in reduced trait retention under large-scale conditions. Furthermore, industrial cultivation of genetically modified strains faces high operational costs, regulatory restrictions, and potential ecological risks associated with environmental release, necessitating stringent biosafety protocols that slow both research progress and commercial deployment (Henley et al., 2013). One of the foremost technical barriers is the structural complexity and heterogeneity of algal cell walls, which hinder the efficient release of fermentable carbohydrates (Jothibasu et al., 2022). The polysaccharide composition of algal biomass varies significantly across species and often contains resistant polymers such as algaenan, cellulose, and glycoproteins. Consequently, pretreatment and hydrolysis require intensive mechanical, chemical, or enzymatic methods; each has its limitations, such as low conversion efficiency, high reagent or energy costs, and the formation of inhibitory by-products (Jain and Kumar 2024b). Mechanical methods can effectively disrupt cell structures but are highly energy-demanding. In contrast, chemical pretreatments can achieve carbohydrate recovery yields up to 88.5%, yet they often generate inhibitory compounds detrimental to downstream microbial fermentation. Enzymatic hydrolysis, while offering greater selectivity and mild reaction conditions, remains costly due to the high price and limited recyclability of enzymes. Hybrid methods, such as ultrasonication combined with alkaline treatment, improve cell disruption and protein release but increase process complexity and operating expenses.

From an economic perspective, integrating cultivation, pretreatment, fermentation, and product recovery into a cohesive process remains cost-prohibitive. However, these interrelated issues affect the commercial viability of scaling up the production of bioethanol and biobutanol from algal biomass. First, the low concentration of algal biomass in cultures (0.5–5 g/L) requires energy-intensive methods like centrifugation or chemical flocculation, which, in some instances, requires more energy than the fuel itself, thus making the harvesting process a major economic constraint, accounting for 20%–30% of total costs (McGrath et al., 2024). One of the primary limitations lies in maintaining high biomass productivity during scale-up, as environmental factors such as light attenuation, temperature fluctuations, and nutrient distribution become difficult to control in large cultivation systems. The production cost of algal biomass alone is substantially estimated at approximately $ 480–500 per ton of dewatered biomass, primarily due to the energy demands of harvesting, drying, and nutrient supply (Kruger et al., 2022). While closed systems like photobioreactors provide superior control and higher productivity, they do so at a capital cost that is five to ten times higher. In contrast, open-pond systems offer lower setup expenses but suffer from contamination risks, inefficient CO₂ utilization, and reduced biomass yields (Novoveská et al., 2023). Downstream fermentation efficiency presents another major bottleneck, especially in ABE processes. Because fermentation broths typically contain only 1%–2% (w/v) butanol, separation is energy-intensive due to its higher boiling point, resulting in a negative energy balance. Additionally, the presence of residual salts, proteins, and inhibitory compounds in algal hydrolysates following pretreatment adversely affects microbial growth and solvent yields (Hong et al., 2021). Conventional distillation of butanol–water mixtures is highly energy-intensive due to azeotrope formation, with studies reporting energy requirements for recovery ranging from approximately 12.6 MJ/kg to over 79.5 MJ/kg of butanol, depending on the initial concentration and process configuration. Some studies indicate that when integrated with alternative techniques such as adsorption on selective resins, pervaporation using PDMS membranes, or in situ gas stripping, the total energy consumption can be as high as 34.2–380 MJ/kg of butanol, but remains costly at scale due to high capital and operational expenditures (Trilokesh and Babu Uppuluri, 2023). Moreover, butanol toxicity remains a critical constraint; concentrations above 8–12 g/L compromise cell membrane integrity, disrupt proton gradients, and impair ATP synthesis, leading to reduced productivity. Although metabolic engineering can enhance butanol tolerance, such modifications frequently lead to trade-offs, including reduced growth rates or by-product accumulation (Liu et al., 2017). From an environmental perspective, large-scale cultivation and processing of microalgae can also result in unintended ecological consequences if not managed properly. Unsustainable cultivation practices may lead to challenges such as water depletion, eutrophication, and habitat disruption (Das and Bhattarai, 2025). Furthermore, several technical and operational hurdles persist, including the inherently low solar-to-biomass conversion efficiency of photosynthesis, high energy demands for cultivation and harvesting, and the considerable costs associated with biomass recovery and downstream processing (Piyatilleke et al., 2025).

Despite significant progress in algal biofuel research, several critical gaps must be addressed to enable large-scale and economically viable production of bioethanol and biobutanol. These gaps can be prioritized based on their impact on process efficiency, scalability, and commercialization potential. Continued advances in synthetic biology, metabolic engineering, and adaptive evolution are expected to play a transformative role in developing next-generation algal biofuel systems (Yadav et al., 2025). These approaches aim to generate robust microalgal strains with enhanced carbon fixation, higher carbohydrate accumulation, and improved tolerance to environmental and product-related stresses, while facilitating the co-production of high-value bioproducts that enhance overall process economics. For biobutanol systems, engineering robust microbial hosts with higher butanol tolerance and yield remains a key bottleneck. The application of precise genome-editing tools such as CRISPR/Cas, TALENs, and zinc-finger nucleases enables targeted modification of genes involved in carbon assimilation, carbohydrate metabolism, and fermentation pathways (Arshad S. et al., 2025). These molecular interventions can redirect metabolic fluxes toward ethanol and butanol biosynthesis, increasing substrate utilization and yield. Synthetic biology strategies such as introducing heterologous bacterial or yeast pathways into algal hosts enable direct photosynthetic conversion of CO₂ into ethanol or butanol, minimizing reliance on external carbon sources. Modular pathway design, codon optimization, synthetic promoter libraries and random mutagenesis further enhance expression efficiency and enzyme performance within photosynthetic systems. A systems-level understanding of algal metabolism, supported by omics technologies such as transcriptomic, proteomic, metabolomic, and fluxomic analyses, is crucial for identifying regulatory bottlenecks (Cunha et al., 2023). Integrating these datasets with computational metabolic modeling and ALE can accelerate rational strain design and optimize flux distribution, leading to the development of high-yielding, stress-tolerant strains suitable for industrial-scale biofuel production.

At the process level, innovations in harvesting, pretreatment, fermentation, and separation technologies are essential to improve process efficiency and reduce costs. For large-scale production, the maintenance of high productivity remains challenging due to light limitation, contamination, and environmental variability. Future research should focus on hybrid cultivation systems, improved reactor designs, and adaptive operational strategies to balance cost and productivity while ensuring culture stability. Scaling up cultivation through hybrid photobioreactor–open pond systems combined with continuous harvesting and real-time process monitoring can lower operational costs while maintaining consistent productivity. Coupling wastewater treatment and flue gas utilization with algal cultivation further supports a circular bioeconomy and near-carbon-neutral energy cycles, providing low-cost nutrient and CO₂ sources while mitigating environmental impacts (Yun et al., 2018). Hybrid autotrophic–heterotrophic cultivation strategies and the exploitation of waste biomass or underutilized algal species can enhance flexibility and productivity under varying conditions. The development of low-energy, scalable harvesting technologies (e.g., bio-flocculation, membrane systems) is essential to improve overall process cost. Cost-effective and energy-efficient techniques for pretreatment, including enzymatic and nanoparticle-assisted hydrolysis, can enhance sugar release while minimizing reagent consumption and environmental burden. Coupling pretreatment with continuous fermentation and in situ product recovery maintains favorable fermentation conditions, mitigates product inhibition, and improves overall productivity (Riaz et al., 2025). Moreover, hybrid separation systems combining pervaporation, gas stripping, and distillation can reduce energy inputs and improve recovery efficiency. Integrating algal biofuel production within a biorefinery framework represents a critical step toward economic feasibility. The developing integrated biorefinery systems that utilize waste streams, optimize resource recycling, and minimize environmental footprints to ensure that algal biofuel production aligns with the principles of a circular and sustainable bioeconomy. Residual biomass can be valorized into pigments, PUFAs, proteins, and bioplastics, enhancing profitability and resource utilization. Recycling fermentation residues via anaerobic digestion can recover nutrients and produce methane, closing material and energy loops (Uma et al., 2022). Incorporating renewable energy sources such as solar or biogas-derived power further decreases the carbon footprint of algal biorefineries (El-Araby, 2024).

There is a lack of comprehensive, real-world data-driven techno-economic and environmental assessments. Future studies should incorporate large-scale data, realistic assumptions, and sensitivity analyses to guide research priorities and facilitate industrial implementation. To ensure sustainable deployment, it is essential to adopt environmentally responsible production strategies supported by integrated life cycle assessment (LCA) and techno-economic analysis (TEA). While LCA evaluates environmental impacts across the entire biofuel production chain, TEA identifies cost bottlenecks and assesses the economic feasibility of process innovations (Figueroa-Torres and Theodoropoulos, 2023). Together, these tools support data-driven decision-making when integrated with process modeling and optimization. LCA studies have shown that algae-based biofuels can significantly reduce greenhouse gas emissions compared to fossil fuels; however, their overall environmental footprint depends on factors such as cultivation conditions, processing technologies, and energy inputs. By systematically examining these variables, these analyses help identify trade-offs and optimize the balance between ecological sustainability and economic viability, thereby strengthening the long-term prospects of algal biofuel systems (Pathania et al., 2025). Furthermore, bridging the gap between laboratory research and industrial deployment requires not only technological advancements but also supportive policy frameworks, infrastructure development, and market incentives. Consideration of regulatory requirements and supply chain logistics is equally important for enabling large-scale implementation. Ultimately, the realization of algal bioethanol and biobutanol as renewable, low-carbon fuels will depend on synergistic advancements in strain engineering, process intensification, biorefinery integration, and supportive policy frameworks (Bolatkhan et al., 2026). The convergence of scientific innovation, circular bioeconomy strategies, and incentive-driven implementation can accelerate the transition of algal biofuels from laboratory-scale research to industrial-scale, sustainable energy solutions contributing to a carbon-neutral future.

8 Conclusion

Algal biomass has emerged as a highly promising and sustainable feedstock for the production of next-generation biofuels, including bioethanol and biobutanol, owing to its rapid growth rates and high carbohydrate content ranging upto 60% of dry biomass under optimized conditions. Its ability to thrive on non-arable land using saline, brackish, or wastewater makes it an ideal candidate for large-scale biofuel production without competing with food crops. The algal carbohydrates, such as starch, cellulose, and other polysaccharides, serve as excellent substrates for microbial fermentation, enabling the production of ethanol and butanol with substantial yields. The conversion of algal biomass into biofuels involves multiple interconnected processes, including biomass harvesting, pretreatment, hydrolysis to release fermentable sugars having sugar recovery efficiencies exceeding 80%–90% in optimized systems, and microbial fermentation. However, economic constraints persist, as biomass harvesting alone can account for approximately 20%–30% of total production costs, due to low culture densities (0.5–5 g/L) and energy-intensive dewatering requirements. Recent advances in metabolic engineering and synthetic biology approaches have significantly improved microbial performance, enabling enhanced mixed-sugar utilization, increased solvent tolerance, and improved product yields. Bioethanol is primarily produced through glycolytic fermentation using yeasts, whereas biobutanol is synthesized via ABE fermentation, often using Clostridium species. Bioethanol remains a major focus due to its higher fermentation efficiency, established market and infrastructure compatibility, while biobutanol is gaining attention because of its superior fuel properties, including higher energy density, lower hygroscopicity, and superior blending compatibility with conventional fuels. Despite significant progress, several challenges remain for large-scale commercialization due to lower productivity, higher downstream processing costs, and greater sensitivity to product toxicity. Overall, bridging the gap between laboratory-scale advancements and industrial deployment will depend on continued improvements in cultivation efficiency, cost-effective harvesting, as well as optimized pretreatment and fermentation processes integrated within biorefinery strategies. Furthermore, TEA and LCA are essential tools for evaluating the sustainability and economic competitiveness of algal biofuel systems and indicate that while algal bioethanol is approaching commercial feasibility, biobutanol production requires further optimization to become competitive. With sustained technological innovation and supportive policy frameworks, algal biofuels have the potential to reduce greenhouse gas emissions by 50%–70% compared to fossil fuels and contribute meaningfully to future global energy demands. Collaborative efforts among academia, industry, and policymakers will be key to overcoming remaining challenges and establishing algal biofuels as a commercially viable and environmentally sustainable energy source.

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Footnotes

Edited by: Ruoyang Yuan, The University of Sheffield, United Kingdom

Reviewed by: Aman Singh Rajpoot, PDPM Indian Institute of Information Technology, Design and Manufacturing, India

Alvina Farooqui, Integral University, India