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Article

Screening Microalgae for Producing Biofuel Precursors from Industrial Off-Gases

by
Giannis Penloglou
1,*,
Alexandros Pavlou
1 and
Costas Kiparissides
1,2
1
Chemical Process and Energy Resources Institute (CPERI), Centre for Research and Technology Hellas (CERTH), Thermi, 57001 Thessaloniki, Greece
2
Department of Chemical Engineering, Aristotle University of Thessaloniki (AUTH), 54124 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(7), 2964; https://doi.org/10.3390/su17072964
Submission received: 24 February 2025 / Revised: 24 March 2025 / Accepted: 25 March 2025 / Published: 27 March 2025
(This article belongs to the Topic Biomass: Advanced Strategies for Renewable Chemicals and Energy Production)
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Abstract

:
The capture and conversion of industrial off-gases into valuable biomass using microalgae represents a promising strategy for CO2 mitigation and sustainable production of biofuels and biochemicals. In this study, fifteen (15) microalgal strains were screened and evaluated for their growth performance and the accumulation of macromolecules like polysaccharides and lipids under CO2-enriched conditions, simulating the off-gas composition of an operational 2G biorefinery producing bioethanol from wastes. It was found that Stichococcus sp. exhibited the highest polysaccharides accumulation (33% w/w) in biomass, while Chlorella vulgaris demonstrated superior lipids content (34% w/w). Both strains (coded as wild-AUTH) displayed robust growth, each achieving biomass concentrations of 1.5 g/L of Dry Cell Weight (DCW), while maintaining tolerance to the gas feedstock. The protein contents of the strains further support their potential integration into a 3G biorefinery framework, where advanced biofuels could be one of multiple valorization pathways. These findings underline the feasibility of using microalgae as a retrofitting solution for bioethanol and other bioenergy plants, enhancing CO2 capture while enabling biofuel production. The top-performing species provide a basis for optimizing bioprocess parameters and scaling up the cultivation in industrial photobioreactors (PBRs) to improve productivity and commercial applicability.

1. Introduction

Globally, climate change and increasing levels of CO2 in the atmosphere are closely linked to the rise in anthropogenic activities, particularly the combustion of fossil fuels [1]. One of the key sectors contributing to this problem is transportation, with road, aviation, and maritime subsectors being all significant contributors [2]. According to the European Environment Agency (EEA), despite all the current measures in place, emissions—particularly from international traffic, including aviation and maritime transport—are expected to continue rising [3].
A sustainable and cost-effective approach to reduce CO2 emissions is to capture and reuse this greenhouse gas (GHG) for microalgae cultivation, producing biomass that can then be transformed into advanced biofuels [4]. This approach fully aligns with initiatives like the European Green Deal and, specifically, with the package ‘Fit for 55’—The EU’s plan for a green transition [5]. Given these developments, microalgae today present a promising solution for the production of sustainable biofuels across various transportation sectors, while simultaneously fixing substantial amounts of CO2 through photosynthesis [6]; they are up to 50 times more effective than terrestrial plants, especially when cultivated in high-end photobioreactors [7]. Furthermore, microalgal biomass is a key renewable resource for producing sustainable aviation fuels (SAF), as well as biofuels for maritime transport, heavy-duty vehicles, and other transportation modes, through the transformation of lipids and other intracellularly produced biochemical compounds (macromolecules) within the framework of 3rd generation (3G) biorefineries [8]. Studies have shown that enriching microalgal cultures with gas mixtures or effluents containing high CO2 levels can, to a certain extent, enhance their growth rate and biomass yield [9].
While in recent decades CO2 bioconversion via microalgae has gained significant attention for the production of biofuels and mainly nutritional products, challenges remain, such as impurities in CO2-laden streams that can hamper their growth, as well as the high energy demands of cultivation systems and downstream processing [10,11]. Additionally, microalgae often require stress conditions, such as nutrient(s) limitation, to accumulate valuable biochemicals like polysaccharides and/or lipids, which at the same time reduces the overall biomass productivity [12]. Combined with technological and economic barriers, including high production costs related to both Capital (CAPEX) and Operational (OPEX) Expenditures, as well as significant land use requirements for open (mainly) and closed systems, these hurdles have hindered the sustainable, large-scale deployment and widespread commercialization of this technology [13,14]. Despite these challenges, bioconversion of CO2 through microalgae for reducing emissions and producing advanced biofuels remains a promising approach. Integrating individual production stages along the entire value chain—linking CO2-emitting industries with the microalgae bioconversion process, while focusing on efficiently reducing energy, water, and land use requirements—is expected to create economically viable processes [15]. This integration is one of the primary goals for the future of the microalgae-based industry.
Within the vast diversity of microalgal species, which includes both eukaryotic genera such as Chlorella and Stichococcus, and prokaryotic genera like Arthrospira, significant potential for CO2 capture and biomass production has been demonstrated. Chlorella vulgaris, for instance, has been extensively studied for its capacity to assimilate CO2 and synthesize biomass rich in lipids, serving as precursors for biodiesel and other advanced biofuels [16]. In general, Chlorella sp. are historically among the most studied microalgae and are known for their robustness. They can be manipulated by adjusting nutritional conditions to accumulate either proteins or lipids; typically, nitrogen limitation is applied to induce lipids accumulation [17]. Following this principle, CO2-rich gas streams are expected to enhance lipids production in Chlorella cultures. Similarly, species from the genus Stichococcus have been investigated for their CO2 fixation capabilities. They are well-known for their ability to produce polysaccharides through a growth-associated mechanism [18], and have demonstrated resilience in cultures under non-ideal conditions, such as high CO2 content in the gaseous feed stream [19]. This feature makes them suitable candidates for the bioremediation of industrial biogenic or fossil-based emissions. Arthrospira species, commonly known as Spirulina, have also been explored for CO2 capture. These cyanobacteria are recognized for their high growth rates and ability to produce substantial biomass under CO2-enriched conditions, serving here as model strains to study their behavior under varying CO2 concentrations [20]. The produced biomass also contains valuable co-products such as proteins and pigments, adding economic value to the bioprocess due to their nutraceutical and cosmetic applications, among others [21]. Similarly, species from the order Chlamydomonadales are efficient at photosynthesis in diverse environments [22], while other Chlorophyta sp. are highly resilient and capable of accumulating substantial amounts of lipids, making them excellent candidates for biofuel production. Komarekiella species are known for the simultaneous production of primary and secondary metabolites, making them ideal for biorefining applications [23]. In addition, microalgal species like Scenedesmus, and Nannochloropsis, among many others, have been studied for their dual role in CO2 sequestration and biofuel production. Their tolerance to varying environmental conditions makes them suitable for integration with industrial processes where CO2 emissions are prevalent [24,25,26,27].
The present work aims to build upon this existing knowledge by evaluating a selection of microalgal species for their efficiency in accumulating polysaccharides and/or lipids under conditions that mimic industrial CO2 emissions. Along with these two macromolecules, accumulated proteins are also quantified to provide a comprehensive characterization of the strains. To this end, focus is placed not only on assessing the biofuel potential of these microalgae but also on evaluating their performance in environments reflective of real-world industrial settings. By doing so, we seek to identify strains that are not only effective in CO2 capture and biofuel production but also resilient to the challenges posed by industrial effluents. Thus, screening experiments are conducted under industrially relevant conditions considering the source and composition of the CO2-containing stream. The study focuses on the specific adaptation of microalgae to industrial CO2-enriched off-gases, particularly from a 2nd generation (2G) bioethanol plant, and offers a detailed assessment of strain performance under real-world conditions, which is critical for the development of large-scale, sustainable biofuel production systems.

2. Materials and Methods

2.1. Microalgal Species

A comprehensive list of fifteen (15) microalgal strains (see Table 1) was prepared for screening and evaluation, based on their performance in the presence of industrial off-gases, specifically those from an operating 2G bioethanol plant. The selection criteria for these strains included viability, robustness, and tolerance to the GHG-laden gaseous feedstock, growth rate (expressed in biomass production and its maximum concentration), and the ability to accumulate polysaccharides and/or lipids.
All microalgal strains selected for screening were graciously provided by collaborating scholars from the Schools of Chemical Engineering and Biology at Aristotle University of Thessaloniki, as well as the School of Chemical and Environmental Engineering at the Technical University of Crete, and the Department of Biology at the National and Kapodistrian University of Athens, Greece. Upon receipt, the strains were immediately re-cultivated in 100 mL flasks to prepare precultures for further experimentation and analysis. Previous tests had been performed with all species to qualify them for inclusion in the shortlist of this study.

2.2. Microalgae Cultivation

All strains were cultivated in 500 mL conical (Erlenmeyer) flasks, placed in an orbital shaking incubator (GFL 3031, Burgwedel, Germany) at a controlled temperature below 25 °C, regulated by a cooling system (chiller) that circulated air inside the incubator. A gentle stirring frequency of 80 rpm was applied to ensure adequate mixing. Each flask was initially loaded with 185 mL of Bold Basal Modified (3N-BBM+V) cultivation medium, followed by inoculation with 15 mL from a mature preculture of each strain, resulting in an initial biomass concentration of approximately 0.1 g/L per flask. Note that 3N-BBM+V is a widely used chemically defined nutrient solution, designed to support the growth of various microalgal species by providing essential macro- and micro-nutrients in optimal and excess concentrations, promoting both cellular proliferation and metabolic activity. By using this medium, the effects of CO2-laden conditions can be clearly assessed, as other nutritional factors that could potentially limit the growth of the selected strains are effectively ruled out. However, the cultivation conditions in the shaken flasks may not have excluded all potential growth-limiting factors due to the small volume and scale. The detailed chemical composition of 3N-BBM+V can be found in Table 2.
Artificial illumination was provided to the flasks by eight (8) LED T8 lamps (11 W, 950 lumens, with an illumination intensity of 100 µmol/(m2·s)), mounted in a custom-designed lighting box, with a 16:8 h light/dark cycle to mimic natural photoperiods. To evaluate the tolerance of each strain to elevated CO2 concentrations and other inhibitory compounds, a gaseous stream simulating the bioethanol production off-gases was continuously supplied to each culture at a flow rate of 80 mL/min. The composition of the gaseous stream (contained in a 50-bar pressurized cylinder procured from BUSE Gas S.A., Thessaloniki, Greece) was (v/v): 9.5% CO2, 0.24% O2, 100 ppm SOx (as SO2) and 20 ppm NOx (as NO2), balanced with N2. This mixture reflects the composition of off-gases generated during bioethanol production at the Perseo Biotechnology S.L biorefinery (Valencia, Spain), diluted tenfold to reduce the concentration of CO2 below the 10% v/v tolerance threshold [28]. Before entering the system, the gas mixture was sterilized via a 0.2 μm filter (Whatman plc, Maidstone, UK). The incubation period lasted 15 days, during which the growth rate of each culture was monitored by measuring its optical density (OD), as described in the subsequent section.

2.3. Monitoring and Analytical Measurements

Microalgae growth in all flask experiments was monitored by periodically collecting 2 mL from each culture for OD measurements at 600 nm using a UV-Vis spectrophotometer (U-1800, Hitachi, Tokyo, Japan). The chosen wavelength of 600 nm ensures minimal absorption from the nutrient medium, allowing for a more accurate representation of the microalgal biomass. If necessary, samples were diluted in cuvettes to ensure that the absorbance values fell within the linear response range and precision of the instrument (i.e., <1). Despite OD measurement being a quick and efficient method for estimating biomass growth and potentially concentration, it is important to note that OD readings may be influenced by changes in cell size and morphology throughout the growth phases, especially in high cell concentrations, or by the level of produced chlorophyll. This limits the direct correlation between OD and cell concentration or Dry Cell Weight (DCW). In this work, the OD values remained at relatively low-to-moderate values ensuring that it served as a reliable indicator of culture progression; a significant drop in OD often signaled cell inhibition or even death.
Biomass concentration of microalgal cultures was quantified as DCW using a gravimetric method. Specifically, culture samples (2–10 mL, depending on the density) were filtered through pre-weighed glass microfiber filters (934-AH, 1.5 μm pore diameter; Whatman plc, Maidstone, UK) to capture the cellular biomass. The filters were first washed with deionized water to remove excess salts from the nutrient medium and then dried overnight in an oven at a controlled temperature of 45 °C to ensure complete moisture removal. After drying, the filters were re-weighed, and the dry biomass was determined by calculating the difference.
Lipids quantification in microalgal biomass followed the Folch method [29]. 1 mL of a 2:1 v/v chloroform/methanol solution was added to approximately 6–7 mg of freeze-dried biomass. The suspension was placed in an ice bath and sonicated (Vibra Cell VC-505 Sonicator, Sonics & Materials, Inc., Newtown, CT, USA) for 10 min using a 1/8-inch diameter tip, set to 40% amplitude (45 s pulses followed by 15 s pauses to prevent overheating). After sonication, the suspension was centrifuged (10 min, 8000× g) and the lipids-containing supernatant was transferred to a separate container. The remaining sediment underwent 2-3 re-extractions to maximize lipids recovery. Next, 1 mL of a 0.88% w/v KCl solution was added to the pooled supernatants, followed by centrifugation to remove residual solids. A small volume (0.3–0.9 mL) of an upper-phase solvent (chloroform/methanol/water in an 8:4:3 ratio), was added to the lipids-rich supernatant, followed by centrifugation and solvent removal. If needed, pure methanol was added to adjust the final volume to 4.5 mL. The lipids extract was placed on a pre-weighed glass plate and dried overnight at 45 °C. The plate was then re-weighed, and the lipids content was determined gravimetrically.
To determine the intracellular polysaccharides content, 1 mL of a 2.5 mol/L HCl solution was added to 2–3 mg of freeze-dried biomass sample, which was then incubated at 100 °C for 3 h. This acid hydrolysis process effectively ruptures microalgae cell walls, releasing the polysaccharides contained within. After incubation, the solution was allowed to cool before neutralizing with an equal volume of 2.5 mol/L. Following neutralization, the well-established phenol-sulfuric acid method [30] was employed to quantify the monomeric saccharides (sugars) content, expressed as glucose equivalents. The absorbance of the solution was measured at 483 nm using a UV-Vis spectrophotometer. D-glucose solutions of known concentrations served as reference standards.
For protein quantification, a freeze-dried biomass sample (2–3 mg) was initially dispersed in 10 mL of a 0.05 M phosphate buffer (PB) (pH = 7.4) and 0.5 N NaOH mixture containing 5% v/v methanol (MeOH) (R1). Ultrasonication using again the same apparatus (1/2 inch tip, 50% amplitude, 40 s pulses with 20 s pauses to avoid excess heat buildup) was then applied in an ice-water bath to disrupt cell walls [31]. After sonication, 5 mL of R1 was added, bringing the total volume to 15 mL. The suspension was then heated at 100 °C for 30 min with constant stirring (280 rpm) to ensure complete protein extraction. The lysate was centrifuged (20,000× g, 10 min), and the protein-containing supernatant was analyzed via the micro-BCA (bicinchoninic acid) method, by reducing Cu2+ to Cu+ and forming a purple complex with BCA, which is measured at 562 nm using the UV-Vis spectrophotometer. Protein concentration was determined using bovine serum albumin (BSA) standards (0.5–200 μg/mL) in 1% MeOH, 0.1 N NaOH.
The combined analysis of lipids, polysaccharides, and proteins enabled finally the calculation of total biochemical products (also mentioned in this study as total macromolecules = lipids + polysaccharides + proteins) and residual biomass in the microalgal cultures. To ensure accuracy and reproducibility, each strain was cultivated in duplicate flasks, with measurements performed on two technical replicates per biological replicate, resulting in a total of n = 4 replicates per condition (unless otherwise specified). Results are presented as mean values ± standard errors (including error bars), calculated from these four independent samples for each measured variable.

3. Results

3.1. Microalgae Growth

To perform an initial evaluation of the fifteen (15) microalgal species, cell growth was monitored by periodically measuring the optical density (OD). These OD measurements allowed for indirect estimation of microalgae growth and biomass production throughout the cultivation period and also served as an indication of the cells’ survivability. For the majority of the species, OD was successfully tracked and evaluated. However, for both Arthrospira species, accurate measurements could not be obtained due to non-homogeneous growth observed under high CO2 concentration (9.5% v/v CO2). Specifically, the cells of these two strains significantly aggregated, which is an unusual behavior for Spirulina. This uneven distribution of cells in the culture likely impacted the accuracy of OD measurements, rendering them unreliable for this particular strain. The OD curves of the remaining species, colored by strain(s) groups, are presented in Figure 1. This figure provides a comparative overview of the growth dynamics under the given experimental conditions, highlighting the variability in CO2 tolerance and biomass productivity across the different microalgal species.
Among the microalgal strains evaluated, Stichococcus sp. wild-AUTH exhibited the highest final OD, reaching a peak value of approximately 14 after 15 days of cultivation, demonstrating robust growth under the experimental conditions. Following closely were three Chlorella vulgaris strains, i.e., Chlorella vulgaris wild-AUTH, Chlorella vulgaris TAU-MAC 1110, and Chlorella vulgaris TAU-MAC 3210, with OD values ranging between 10 and 12, indicating strong growth performance. Lower OD values were observed for the remaining Stichococcus sp. strains. Wild-TUC and TAU-MAC 0119 both exhibited steady growth and reached approximately an OD of 7. The final two Stichococcus sp. strains, namely EMS1-TUC and EMS3-TUC, displayed delayed and slower growth patterns. It is important to note that the latter two strains had been subjected to random evolution before being supplied/delivered for cultivation. This process may have negatively affected their tolerance and adaptability to stressful cultivation conditions, such as the ones applied here.
The two other Chlorella strains examined, Chlorella sp. ASP17 and Chlorella sp. ASP14, reached moderate values of OD, around 7. These strains appeared to enter the stationary phase after just one week of cultivation, suggesting slower adaptation to the high CO2 content of the feedstock or early stagnation in their growth. This early transition to the stationary phase may have limited their overall biomass accumulation compared to the more robust strains. For the remaining species, generally low OD values were recorded, with most strains remaining below 2. Notably, Chlamydomonadales sp. TAU-MAC 3510 exhibited more robust growth compared to Chlorophyta sp. TAU-MAC 3917 and Komarekiella sp. TAU-MAC 0117, yet it still only reached a maximum OD value of approximately 1.6. The high CO2 concentration clearly inhibited the growth of these strains, indicating unsuitability to strive in CO2-enriched environments like the industrial effluents studied in this work.

3.2. Biomass Production

A more accurate indication of microalgae viability and physiological state than OD measurements is biomass growth, which is quantified as DCW. Figure 2a illustrates the maximum DCW per strain, recorded at the point of peak growth for each of the investigated microalgal strains, as shown in the growth curves of Figure 1. The color groups in the figure provide a clearer comparison of the strain performance with similar characteristics, making it easier to assess the influence of species-specific traits on biomass production under the given cultivation conditions.
Several of the investigated strains, including some Stichococcus sp., all Chlorella sp. and Chlorella vulgaris strains, as well as Arthrospira and Chlamydomonadales sp. TAU-MAC 3510, exhibited no significant growth inhibition in response to elevated CO2 levels. Notably, two Stichococcus strains, wild-TUC and TAU-MAC 0119, demonstrated the ability to accumulate more than 1 g/L of biomass, with Stichococcus sp. wild-AUTH achieving the highest biomass concentration of approximately 1.5 g/L (average productivity of 0.1 g/(L·day)). These findings are consistent with the discussion on OD measurements. On the other hand, the growth of Stichococcus sp. EMS1-TUC and EMS3-TUC appeared to be inhibited by the excess CO2 during cultivation, leading to lower biomass accumulation. Moreover, all Chlorella strains demonstrated robust growth, with biomass concentrations exceeding 1 g/L. Chlorella vulgaris wild-AUTH achieved the highest biomass concentration in this group with approximately 1.5 g/L (average productivity of 0.1 g/(L·day)). As with the discussion on OD results, this again provides a second clear indication that this particular species may be sufficiently tolerant and robust for potential application in industrially relevant conditions.
As for the remaining microalgal species, Arthrospira cf. fusiformis TAU-MAC 0113 produced a notable biomass concentration of approximately 0.9 g/L (average productivity of 0.06 g/(L·day)), while Arthrospira maxima TAU-MAC 0213 reached slightly lower levels of around 0.75 g/L (average productivity of 0.05 g/(L·day)). However, a challenge with these strains was the formation of non-homogeneous cultures during cultivation, which may have impacted the consistency of their growth and measurement accuracy. This may affect both OD and DCW measurements, possibly due to inadequate or non-representative sampling of the entire culture, leading to inconsistencies and inaccurate correlations between these values. Of the remaining strains, Chlamydomonadales sp. TAU-MAC 3510 was the only one to achieve a biomass concentration close to 1 g/L. In contrast, Chlorophyta sp. TAU-MAC 3917 and Komarekiella sp. TAU-MAC 0117 exhibited poor growth, with final biomass concentrations below 0.5 g/L (average productivity of 0.033 g/(L·day)).
It should be noted that in all cultures, the medium pH was not controlled but was measured dynamically and remained constant at 6.5 ± 0.2. This stable pH is primarily due to the excess supply of CO2, which minimized the effect on the equilibrium between the gas and liquid phases, as well as the phosphate buffer present in the cultivation medium. The buffer system ensured that any pH variation due to CO2 addition was minimal. Consequently, pH had little impact on microbial growth, as it remained within the suitable range for all the microalgal strains tested. Additionally, while nitrate utilization can also cause pH shifts, the buffering capacity of the medium ensured that microbial growth was not hindered by any potential alkalinity changes resulting from nitrogen assimilation.

3.3. Biochemical Products Accumulation

Following the preliminary screening of the species for their growth and biomass production performance under elevated CO2 conditions, a similar comparison was conducted to assess their ability to accumulate polysaccharides, lipids, and proteins. While polysaccharides and lipids are more relevant to biofuel production, protein accumulation was also analyzed as a complementary aspect of this study. Initially, Figure 2b presents the content (% w/w) of polysaccharides in the biomass of the investigated microalgal strains cultivated under excess CO2 conditions. All Stichococcus strains demonstrated a strong ability to accumulate polysaccharides, with a relevant content ranging between approximately 30% and 40% w/w of biomass concentration. Notably, Stichococcus sp. TAU-MAC 0119 and Stichococcus sp. EMS3-TUC exhibited the highest polysaccharide accumulation, reaching 35.78% w/w and 39.02% w/w, respectively. In contrast, the majority of the other microalgal strains (including all Chlorella strains, Arthrospira maxima, Chlorophyta sp., and Komarekiella sp.) showed more moderate polysaccharides accumulation, with values ranging between 20% and 25%, while Arthrospira cf. fusiformis TAU-MAC 0113 and Chlorophyta sp. TAU-MAC 3917 only accumulated around 15% w/w.
In terms of lipids accumulation, all studied Chlorella strains demonstrated a strong ability to accumulate lipids in their biomass (ranging from 30% to 35% w/w), except for Chlorella vulgaris TAU-MAC 3210, which contained approximately 26% w/w (Figure 2c). Additionally, several other microalgal strains exhibited comparable or even higher lipids accumulation, e.g., Stichococcus sp. EMS3-TUC with around 32% w/w lipids, and Chlorophyta sp. TAU-MAC 3917 and Komarekiella sp. TAU-MAC 0117 with approximately 41% and 32% w/w content, respectively. Among the Stichococcus strains, most showed a relatively low lipids content of around 25% w/w, except for EMS3-TUC, which interestingly stood out.
With regard to protein content, several of the studied microalgal strains exhibited notable accumulation patterns. As expected, Arthrospira cf. fusiformis TAU-MAC 0113, Arthrospira maxima TAU-MAC 0213, but also Chlamydomonadales sp. TAU-MAC 3510 were the top performers, with protein levels reaching approximately 49%, 40%, and 36% w/w, respectively (Figure 2d). Even under these less favorable conditions, clearly Spirulina is an adequate producer of valuable proteins. Among the Stichococcus strains, protein content ranged between 22–27% w/w, with the exception of EMS3-TUC, which produced approximately 33% w/w in the cells. As for the Chlorella strains, they consistently reached protein accumulation in the range of 27% to 30% w/w. Chlorophyta sp. TAU-MAC 3917 and Komarekiella sp. TAU-MAC 0117 also demonstrated moderate protein accumulation, each reaching around 27% w/w.
With the above findings, the total percentage of major biochemical/macromolecular products (polysaccharides, lipids and proteins) accumulated by the microalgae can be calculated, along with the residual biomass content (which includes ash, chlorophylls and other pigments, other bioactive compounds, absorbed water, etc.). This allows evaluation of both biomass composition and total titers of each compound in the culture, which is crucial for several reasons. While compositions provide insights into the relative distribution of biochemical compounds within the microalgal biomass, concentration data offer a more practical perspective for large-scale applications. Concentrations directly indicate the absolute amount of each biochemical product that can be harvested per unit of culture volume, which is a key factor in determining the overall productivity and economic viability of any microalgal cultivation system. Table 3 presents respectively the concentrations of the targeted measured biochemical products.
Upon examining the concentrations of polysaccharides accumulated by the investigated microalgae strains, three cultures demonstrated significant polysaccharides production, reaching concentrations of approximately 0.4–0.5 g/L, namely Stichococcus sp. wild-AUTH (0.5 g/L), Stichococcus sp. wild-TUC culture (0.45 g/L), and Stichococcus sp. TAU-MAC 0119 (0.4 g/L). In contrast, the remaining two Stichococcus strains produced significantly lower amounts of polysaccharides per culture, accumulating less than half the values achieved by the top three strains.
On the other hand, all of the studied Chlorella cultures demonstrated consistent polysaccharide production, with concentrations around 0.3 g/L. Specifically, Chlorella sp. ASP14 culture reached approximately 0.32 g/L of polysaccharides, followed by Chlorella vulgaris TAU-MAC 3210 and Chlorella sp. ACA17 cultures, which accumulated 0.3 g/L and 0.29 g/L, respectively. The other two Chlorella cultures, wild-AUTH and C. vulgaris TAU-MAC 1110 achieved slightly lower concentrations, with values of approximately 0.28 g/L and 0.26 g/L, respectively. However, none of these could match the three top-performing Stichococcus sp. Of the remaining microalgal strains only Komarekiella sp. TAU-MAC 0117 was able to accumulate polysaccharides at a concentration exceeding 0.2 g/L. The other four cultures did not surpass this concentration, indicating more limited polysaccharides production potential, coupled with poor biomass growth performance.
Among the strains studied for lipids production, Chlorella vulgaris wild-AUTH culture is the only one producing approximately 0.5 g/L of lipids. The other Chlorella cultures demonstrated lower lipids accumulation, achieving concentrations only up to 0.4 g/L. Specifically, C. ASP14, ACA17, and vulgaris TAU-MAC 1110 produced 0.43, 0.41, and 0.38 g/L of lipids, respectively. Finally, C. vulgaris TAU-MAC 3210 culture reached a lower lipids concentration of only 0.28 g/L. All remaining microalgal cultures accumulated low levels of lipids, with concentrations below 0.3 g/L.
In the interest of providing a comprehensive characterization of the studied microalgal strains, protein concentration in the culture of each species was also calculated. The results revealed three strains that were able to accumulate over 0.4 g/L of proteins: A. cf. fusiformis TAU-MAC, C. vulgaris wild-AUTH, and C. ACA17. Several other cultures reached protein concentrations ranging from 0.3 to 0.37 g/L, including S. wild-AUTH and wild-TUC, C. ASP14 and C. vulgaris TAU-MAC 1110, and C. sp. TAU-MAC 3510. The cultures of the remaining strains had protein concentrations below 0.3 g/L.

4. Discussion

Each microalgal species and variant investigated in this study demonstrated unique growth characteristics when exposed to CHG-laden conditions, which can be leveraged to meet biofuel production objectives. This resilience is a hallmark of microalgae, which can acclimate to diverse environments and efficiently capture and convert CO2 into valuable biomass [32]. The strains were selected based on key criteria such as final biomass concentration, maximum polysaccharides and lipids contents, and the general ability to thrive in CO2-enriched environments, reflecting industrial off-gases.
The comparative results are shown in the bubble graphs of Figure 3, which display species capable of efficiently accumulating polysaccharides (Figure 3a) and lipids (Figure 3b), alongside adequate biomass production in the top-right quadrant. Among the strains tested, Stichococcus sp. wild-AUTH emerged as the top performer for biomass production, reaching a concentration of approximately 1.5 g/L DCW. This strain also accumulated significant amounts of polysaccharides (around 33% w/w), which is essential for biofuel production, as polysaccharides can be converted into fermentable sugars for bioethanol production [33]. Additionally, Chlorella vulgaris wild-AUTH exhibited the highest lipids concentration (approximately 34% w/w), making it an ideal candidate for biofuels derived from lipids, such as biodiesel and advanced biofuels based on hydrocarbons [34].
A key finding from this study is that several microalgal strains, including Stichococcus sp., Chlorella sp., and Arthrospira sp., showed minimal growth inhibition in response to elevated CO2 concentrations and other greenhouse gases, supporting their potential for cultivation in industrial environments. These results align with previous studies demonstrating the adaptability of certain microalgal strains to high CO2 concentrations [35,36,37]. Notably, Stichococcus sp. wild-AUTH stood out as the best candidate for polysaccharides production, while Chlorella vulgaris wild-AUTH excelled in lipids accumulation. While Arthrospira and Chlamydomonadales sp. TAU-MAC 3510 also performed well under CO2-enriched conditions in terms of biomass production [38], their lower polysaccharides and lipids contents suggest limited potential for biofuel applications. Instead, they may serve as valuable producers of proteins [39]. Interestingly, strains like Chlorophyta sp. and Komarekiella sp. exhibited lower biomass yields, yet their moderate protein accumulation (20–30% w/w) highlights their potential for other biotechnological applications [40].
The results of this study underscore also the importance of optimizing cultivation conditions for each microalgal strain to maximize both biomass yield and the accumulation of target biochemical products. They indicate that polysaccharides and lipids accumulation varied significantly between species, which can be attributed to the specific stress conditions applied during cultivation. Strains like Stichococcus sp. and Chlorella vulgaris performed exceptionally well in terms of polysaccharides and lipids accumulation, respectively. However, the need for further optimization of cultivation conditions, particularly nutrient stress and/or light exposure, remains evident [41]. The application of multiple stress factors—such as elevated CO2 concentrations, light intensity, and N/P limitations—has been shown to be beneficial in enhancing lipids production in Chlorella sp. This result aligns with studies suggesting that high CO2 concentrations can act as a form of stress, driving metabolic shifts that favor lipids accumulation [42].
However, it is crucial to note that optimizing conditions for one macromolecule (e.g., lipids) may inadvertently compromise the accumulation of another (e.g., polysaccharides), thereby affecting the overall efficiency of the bioprocess. This trade-off needs to be carefully considered when developing biorefinery strategies. An optimized cultivation strategy for lipids production could involve the simultaneous application of multiple stress factors, which may enhance lipids yield but require balancing with other biochemical product yields [43]. Moreover, polysaccharides are typically of lower priority for microalgae producers, often ranked third after proteins and lipids, or even fourth after pigments or other bioactive compounds. As a result, cultivation conditions are rarely optimized specifically for polysaccharide production [44]. Our study demonstrates that the accumulation of polysaccharides in Stichococcus sp. strains significantly contributes to the overall biomass composition, highlighting its potential for biofuel applications and other processes that utilize sugars. This characteristic is particularly valuable when considering the validated growth-associated mechanism of polysaccharide production in this species, which enables maximum sugar production rates during bioprocess intensification.
While numerous studies have already investigated the potential of microalgae to capture CO2 from various gas streams, such as those from coal power plants or other industrial facilities [20,45], this work focused specifically on bioethanol plant off-gases, a significant source of industrial biogenic emissions. Previous studies have demonstrated the high CO2 tolerance of certain microalgal strains like Chlorella and Arthrospira under flue gas conditions [46,47]. However, this research expanded on this by evaluating growth rates and also quantifying the accumulation of key biochemical products such as polysaccharides and lipids, which are critical precursors for biofuel production. Additionally, the complexities of optimizing cultivation for both lipids and polysaccharides are overcome [48], by specifically addressing the challenges of maximizing these macromolecules within two different industrially relevant strains under CO2 excess. Thus, a deeper insight into the interactions between elevated CO2 and other potential stressors (e.g., NOx, SOx) is provided, under industrial gas emissions.
Although the findings above highlight the strains’ potential for industrial-scale cultivation under real-world conditions with multiple off-gases, a unified biorefinery approach that aims to optimize the simultaneous extraction of both polysaccharides and lipids simultaneously from a single strain, presents clear challenges. This is reflected in the biomass composition distribution for the two selected species, as can be determined from the results of Figure 2, which presents contrasting levels of polysaccharides and lipids in each strain (data in % w/w of DCW): polysaccharides 32.16%, lipids 24.84%, proteins 24.48% and residual biomass 18.52% for Stichococcus sp., and polysaccharides 19.18%, lipids 33.56%, proteins 28.77% and residual biomass 18.49% for Chlorella vulgaris. This reinforces the notion that specialized approaches are often necessary, where different strains are assigned to distinct value chains: polysaccharides-producing strains can be used for bioethanol production through sugars fermentation while lipids-producing strains can be processed for biodiesel and advanced biofuels production via esterification or hydroprocessing. While the flask-scale experiments conducted in this study provided valuable insights, it is expected that the yields of both polysaccharides and lipids will be further optimized in photobioreactor (PBR) systems. PBRs provide better-controlled conditions, which should enhance overall biomass yield and the accumulation of biochemical products [49]. Scaling up the cultivation process using PBRs should lead to improved efficiency and product concentration, further supporting the industrial feasibility of these strains.
In the context of a biorefinery, it may seem ideal to streamline the upstream cultivation process by focusing on a single species capable of producing both polysaccharides and lipids. However, as shown in this study, this approach presents significant challenges in both upstream and downstream processing. Achieving a global optimum for both macromolecules is often not feasible, and cascade extraction and purification steps for both products may compromise the integrity of either polysaccharides or lipids [50]. Moreover, in a biorefinery setting where multiple high-value biochemical products are targeted, the inherent trade-offs between lipids and polysaccharides production and recovery can affect overall efficiency and yield. Optimizing conditions for one product may inhibit the accumulation of the other, complicating the balance necessary for an efficient bioprocess.
Undoubtedly, the strains Stichococcus sp. and Chlorella vulgaris show the greatest potential for biofuel applications. Their ability to accumulate significant amounts of polysaccharides and lipids, respectively, under CO2-enriched conditions makes them ideal candidates for industrial-scale applications. However, further optimization of cultivation conditions and scaling up to PBRs will be necessary to unlock their full potential for large-scale CO2 capture and biofuel production.

5. Conclusions

Microalgae’s ability to thrive in GHG-enriched environments, combined with their capacity to accumulate valuable biochemical products, positions them as a critical asset for sustainable biofuel production and CO2 emission reduction. The primary objective of this study was to identify microalgal species suitable for producing polysaccharides and lipids when cultivated in off-gases from a 2G biorefinery dedicated to bioethanol production. Among the 15 strains tested, Stichococcus sp. wild-AUTH emerged as the best-performing strain for polysaccharide accumulation, reaching more than 30% in biomass, while Chlorella vulgaris wild-AUTH exhibited the highest lipids content (34%), making it an excellent candidate for biofuel applications. Notably, both strains demonstrated robust growth and resilience to the high CO2 concentrations in the off-gas mixture, highlighting their suitability for industrial-scale cultivation in CO2-rich environments.
The findings demonstrate that Stichococcus sp. and Chlorella vulgaris wild-AUTH are not only capable of accumulating the desired macromolecules but also show high tolerance to the complex off-gas mixture, making them ideal candidates for large-scale CO2 capture and biofuels production. These strains have the potential to contribute to the development of efficient and sustainable biofuel production systems. Moreover, the comprehensive analysis of the strains’ biochemical content provides valuable insights for future efforts to optimize microalgal cultivation conditions in photobioreactors and biorefinery systems.

Author Contributions

Conceptualization, G.P., A.P. and C.K.; methodology, G.P. and A.P.; validation, G.P. and A.P.; formal analysis, G.P. and A.P.; investigation, G.P. and A.P.; resources, G.P. and C.K.; data curation, G.P. and A.P.; writing—original draft preparation, G.P. and A.P.; writing—review and editing, G.P.; visualization, A.P.; supervision, G.P. and C.K.; project administration, G.P.; funding acquisition, G.P. and C.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work has been developed within the framework of the “FUELGAE—Innovative sustainable on-site technologies for using microalgae to capture CO2 and produce advanced biofuels” research project, funded by the European Union’s Horizon Europe research and innovation program under grant agreement number 101122151. The views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data will be made available upon request.

Acknowledgments

The authors sincerely thank Spyros Gkelis, at the School of Biology, Aristotle University of Thessaloniki (AUTH), Greece; Dimitris Hatzinikolaou, at the Department of Biology, National and Kapodistrian University of Athens (NKUA), Greece; Nicolaos Kalogerakis, at the School of Chemical and Environmental Engineering, Technical University of Crete (TUC), Greece; and Christos Chatzidoukas, at the School of Chemical Engineering, Aristotle University of Thessaloniki (AUTH), for providing the screened microalgal strains from their proprietary collections. The authors sincerely thank Perseo Biotechnology S.L., in Valencia, Spain, for providing the composition of bioethanol off-gases.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Optical Density (OD) results for the 15 microalgal species under study, cultivated in Erlenmeyer flasks with 9.5% v/v CO2. Species numbers and names (corresponding also to Table 1): #1 Stichococcus sp. wild-TUC; #2 Stichococcus sp. TAU-MAC 0119; #3 Stichococcus sp. EMS1-TUC; #4 Stichococcus sp. EMS3-TUC; #5 Stichococcus sp. wild-AUTH; #6 Chlorella sp. ACA17; #7 Chlorella sp. ASP14; #8 Chlorella vulgaris TAU-MAC 1110; #9 Chlorella vulgaris TAU-MAC 3210; #10 Chlorella vulgaris wild-AUTH; #11 Arthrospira fusiformis TAU-MAC 0113; #12 Arthrospira maxima TAU-MAC 0213; #13 Chlamydomonadales sp. TAU-MAC 3510; #14 Chlorophyta sp. TAU-MAC 3917; and #15 Komarekiella sp. TAU-MAC 0117.
Figure 1. Optical Density (OD) results for the 15 microalgal species under study, cultivated in Erlenmeyer flasks with 9.5% v/v CO2. Species numbers and names (corresponding also to Table 1): #1 Stichococcus sp. wild-TUC; #2 Stichococcus sp. TAU-MAC 0119; #3 Stichococcus sp. EMS1-TUC; #4 Stichococcus sp. EMS3-TUC; #5 Stichococcus sp. wild-AUTH; #6 Chlorella sp. ACA17; #7 Chlorella sp. ASP14; #8 Chlorella vulgaris TAU-MAC 1110; #9 Chlorella vulgaris TAU-MAC 3210; #10 Chlorella vulgaris wild-AUTH; #11 Arthrospira fusiformis TAU-MAC 0113; #12 Arthrospira maxima TAU-MAC 0213; #13 Chlamydomonadales sp. TAU-MAC 3510; #14 Chlorophyta sp. TAU-MAC 3917; and #15 Komarekiella sp. TAU-MAC 0117.
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Figure 2. Screening results for all investigated microalgal strains, cultivated in Erlenmeyer flasks with 9.5% v/v CO2: (a) Biomass concentration (as Dry Cell Weight, DCW) on the day of highest OD value; (b) Polysaccharides content (% w/w) in DCW; (c) Lipids content (% w/w) in DCW; and (d) Proteins content (% w/w) in DCW.
Figure 2. Screening results for all investigated microalgal strains, cultivated in Erlenmeyer flasks with 9.5% v/v CO2: (a) Biomass concentration (as Dry Cell Weight, DCW) on the day of highest OD value; (b) Polysaccharides content (% w/w) in DCW; (c) Lipids content (% w/w) in DCW; and (d) Proteins content (% w/w) in DCW.
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Figure 3. Bubble graphs for: (a) Polysaccharides; and (b) Lipids; accumulation contents (% w/w) with respect to biomass concentration (as Dry Cell Weight, DCW—g/L), for all investigated microalgae strains, cultivated in Erlenmeyer flasks with excess CO2 (9.5% v/v). Notice that in Figure 3b, the data points for Stichococcus sp. EMS1-TUC and Komarekiella sp. TAU-MAC 0117 coincide.
Figure 3. Bubble graphs for: (a) Polysaccharides; and (b) Lipids; accumulation contents (% w/w) with respect to biomass concentration (as Dry Cell Weight, DCW—g/L), for all investigated microalgae strains, cultivated in Erlenmeyer flasks with excess CO2 (9.5% v/v). Notice that in Figure 3b, the data points for Stichococcus sp. EMS1-TUC and Komarekiella sp. TAU-MAC 0117 coincide.
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Table 1. Shortlist of microalgal species screened and evaluated as potential polysaccharides and/or lipids producers in industrially relevant conditions.
Table 1. Shortlist of microalgal species screened and evaluated as potential polysaccharides and/or lipids producers in industrially relevant conditions.
Number (#), Microalgal Species,
and Reference Code
#1 Stichococcus sp.
wild-TUC		#6 Chlorella sp.
ACA17		#11 Arthrospira fusiformis
TAU-MAC 0113
#2 Stichococcus sp.
TAU-MAC 0119		#7 Chlorella sp.
ASP14		#12 Arthrospira maxima
TAU-MAC 0213
#3 Stichococcus sp.
EMS1-TUC		#8 Chlorella vulgaris
TAU-MAC 1110		#13 Chlamydomonadales sp.
TAU-MAC 3510
#4 Stichococcus sp.
EMS3-TUC		#9 Chlorella vulgaris
TAU-MAC 3210		#14 Chlorophyta sp.
TAU-MAC 3917
#5 Stichococcus sp.
wild-AUTH		#10 Chlorella vulgaris
wild-AUTH		#15 Komarekiella sp.
TAU-MAC 0117
Table 2. Detailed composition of the chemically defined nutrient medium 3N-BBM+V used for cultivating the selected microalgal strains.
Table 2. Detailed composition of the chemically defined nutrient medium 3N-BBM+V used for cultivating the selected microalgal strains.
Major ComponentsConcentration (g/L)Traces and VitaminsConcentration (g/L)
NaNO30.75DiNa-EDTA0.0045
K2HPO4·3H2O0.075FeCl3·6H2O0.000582
KH2PO40.175MnCl2·4H2O0.000246
NaCl0.025ZnCl20.00003
MgSO4·7H2O0.075CoCl2·6H2O0.000012
CaCl2·2H2O0.025Na2MoO4·2H2O0.000024
Vitamin B10.00012
Vitamin B120.0001
Table 3. Concentrations per culture of all individual and total biochemical products (total macromolecules: polysaccharides, lipids, and proteins) produced by the 15 studied strains.
Table 3. Concentrations per culture of all individual and total biochemical products (total macromolecules: polysaccharides, lipids, and proteins) produced by the 15 studied strains.
Microalgal
Species		Polysaccharides
(g/L)		Lipids
(g/L)		Proteins
(g/L)		Total Macromolecules
(g/L)
Stichococcus sp.
wild-TUC		0.44 ± 0.0130.35 ± 0.0390.34 ± 0.0431.13 ± 0.095
Stichococcus sp.
TAU-MAC 0119		0.39 ± 0.0160.30 ± 0.0250.29 ± 0.0360.98 ± 0.077
Stichococcus sp.
EMS1-TUC		0.13 ± 0.0200.11 ± 0.0090.14 ± 0.0160.38 ± 0.045
Stichococcus sp.
EMS3-TUC		0.16 ± 0.0320.13 ± 0.0110.09 ± 0.0090.38 ± 0.052
Stichococcus sp.
wild-AUTH		0.48 ± 0.0360.36 ± 0.0400.36 ± 0.0451.2 ± 0.121
Chlorella sp.
ACA17		0.29 ± 0.0330.41 ± 0.0340.40 ± 0.0441.1 ± 0.111
Chlorella sp.
ASP14		0.32 ± 0.0380.43 ± 0.0390.37 ± 0.0461.12 ± 0.123
Chlorella vulgaris
TAU-MAC 1110		0.26 ± 0.0280.38 ± 0.0320.33 ± 0.0370.97 ± 0.097
Chlorella vulgaris
TAU-MAC 3210		0.30 ± 0.0100.28 ± 0.0260.28 ± 0.0350.86 ± 0.071
Chlorella vulgaris
wild-AUTH		0.28 ± 0.0110.49 ± 0.0610.42 ± 0.0471.19 ± 0.119
Arthrospira fusiformis
TAU-MAC 0113		0.08 ± 0.0370.21 ± 0.0210.44 ± 0.0400.73 ± 0.098
Arthrospira maxima
TAU-MAC 0213		0.10 ± 0.0490.17 ± 0.0220.30 ± 0.0330.57 ± 0.104
Chlamydomonadales sp.
TAU-MAC 3510		0.12 ± 0.0160.19 ± 0.0190.34 ± 0.0340.65 ± 0.069
Chlorophyta sp.
TAU-MAC 3917		0.18 ± 0.0200.21 ± 0.0230.14 ± 0.0160.53 ± 0.059
Komarekiella sp.
TAU-MAC 0117		0.24 ± 0.0530.13 ± 0.0140.11 ± 0.0090.48 ± 0.076
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Penloglou, G.; Pavlou, A.; Kiparissides, C. Screening Microalgae for Producing Biofuel Precursors from Industrial Off-Gases. Sustainability 2025, 17, 2964. https://doi.org/10.3390/su17072964

AMA Style

Penloglou G, Pavlou A, Kiparissides C. Screening Microalgae for Producing Biofuel Precursors from Industrial Off-Gases. Sustainability. 2025; 17(7):2964. https://doi.org/10.3390/su17072964

Chicago/Turabian Style

Penloglou, Giannis, Alexandros Pavlou, and Costas Kiparissides. 2025. "Screening Microalgae for Producing Biofuel Precursors from Industrial Off-Gases" Sustainability 17, no. 7: 2964. https://doi.org/10.3390/su17072964

APA Style

Penloglou, G., Pavlou, A., & Kiparissides, C. (2025). Screening Microalgae for Producing Biofuel Precursors from Industrial Off-Gases. Sustainability, 17(7), 2964. https://doi.org/10.3390/su17072964

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