Environmentally Friendly Biodiesel Synthesis from Marine Microalgae Using Calcium Methoxide as a Novel Catalyst

Environmentally Friendly Biodiesel Synthesis from Marine Microalgae Using Calcium Methoxide as a Novel Catalyst | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Environmentally Friendly Biodiesel Synthesis from Marine Microalgae Using Calcium Methoxide as a Novel Catalyst Mohammad Al-Hwaiti, Hala G. Al-Deen, Ali Sawalmih, Ahmad O. Hasan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6819238/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Biodiesel derived from lipid-rich oils extracted from microalgae holds promise for fulfilling future energy consumption. Three microalgae varieties, namely Nannochloropsis, Tetraselmis, and Isochrysis, were assessed. A novel aspect of this study is the use of calcium methoxide (C 2 H 6 CaO 2 ) as a catalyst for transesterification in the production of biodiesel from marine microalgae. Oil yields from 80g of microalgae were determined as follows: 45 ml for Nannochloropsis, 30 ml for Isochrysis, and 20 ml for TetraselmisTop of Form. Furthermore, the calcium methoxide catalyst enhanced biodiesel yield for Nannochloropsis, Tetraselmis, and Isochrysis microalgae by 96%, 93%, and 90%, respectively. Tetra microalgae oil showcases exceptional characteristics with notably low viscosity (13.3 cSt at 40°C), contrasting sharply with Nanno's higher viscosity (39.1 cSt), while Iso falls in between at 25.2 cSt. In colder conditions, Tetra (-3.3°C) and Nanno (-4°C) oils perform well without solidifying, although Iso's slightly superior cloud point (-1.2°C) outperforms Tetra's in lower temperatures. Nanno's high flash point (274°C) ensures greater safety, while its density of 915 kg/m³ stands out among the three, potentially impacting its performance across various applications. Both Tetra (-10°C) and Nanno (-17°C) demonstrate lower pour points, making them more effective in colder environments compared to Iso. The composition of fatty acids differs across these oils: Tetra microalgae oil contains primarily Linoleic acid (50.60±1.2%) and Oleic acid (38.2±0.7%), while ISO sp microalgae oil is predominantly Oleic acid (60.5±1.5%), and NANNO sp contains the highest percentage of Oleic acid (54.7±0.9%) with minimal Linoleic acid (0.4±0.6%). In terms of microalgae biodiesel, Nanno exhibited a viscosity of 6.2 cSt, Tetra had 7.976 cSt, and Iso showed 7.6 cSt, reflecting their individual flow characteristics. Their flash points Nanno at 100.5°C, Tetra at 99.9°C, and Iso at 99.1°C highlight safety during handling. Additionally, Nanno (-39°C), Tetra (-40.8°C), and Iso (-45°C) biodiesels' cloud points imply superior performance in colder temperatures, minimizing the risks of fuel solidification and filter issues. These parameters indicated that marine microalgae biodiesel has the potential to not only meet stringent green fuel standards but also significantly reduce CO 2 emissions across its entire lifecycle, spanning from production to combustion. Marine microalgae Biodiesel production Transesterification Sustainable biofuels Greenhouse gas reduction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 Figure 20 Figure 21 Introduction Microalgae serve as a significant biomass feedstock with notable applications in biodiesel production. Their distinguished characteristics include high lipid content, effective mitigation of CO 2 emissions, rapid growth rates, and the ability to thrive on non-arable land for cultivation (Chhandama et al. 2021; Yu et al. 2024). These attributes make microalgae particularly advantageous compared to various other feedstocks. Furthermore, the cultivation of microalgae doesn't compete with food crops, presenting it as a compelling alternative to more commonly used feedstocks derived from food crops (Ryu et al. 2020). The benefits of using algae as a source of oil for biofuels extend to their impressive growth rates, characterized by a rapid biomass doubling time, typically ranging from 1 to 6 days. Additionally, microalgae have been found to produce 10–20 times more oil per hectare per year compared to traditional oil crop plants (Neeti et al. 2023). Moreover, their high photosynthetic rate, approximately 6.9 × 10 4 cells/ml/h, and a carbon constituent of up to 50% in algae biomass further contribute to their appeal. This is coupled with a solar energy conversion capacity of about 4.5% (Rafa et al. 2021; Eldiehy et al. 2022). The process of harvesting microalgae comprises three main elements: biomass recovery, dewatering, and drying. Various techniques are available for this purpose, and the selection of a specific method hinges on the unique traits of the microalgae, such as their size, density, and the desired end products (Mathimani and Mallick 2018). Ziolkowska (2020), investigated microalgae harvesting can involve micro-screens in conjunction with centrifugation, flocculation, gravity sedimentation, filtration, screening, flotation, or electrophoresis techniques (Patnaik and Mallick 2021). Microalgae present a range of possibilities for producing various biofuels: biomethane via anaerobic digestion (Veerabadhran et al. 2021; Khaligh and Asoodeh 2022), biohydrogen through photobiological processes (Jokel et al. 2020; Torres et al. 2023), bioethanol via fermentation (Tse et al. 2021; Condor et al. 2022), liquid oil using thermal liquefaction (Galadima and Muraza 2018; Kostyukevich et al. 2021), and biodiesel through transesterification (Arachchige et al. 2021; Miyuranga et al. 2022; Miyuranga et al. 2023). Microalgae represent a highly prospective resource for sustainable biofuels in the future of renewable energy. Algae exhibit adaptability in utilizing various waste streams such as municipal wastewater, enabling the creation of diverse products suitable for various uses. These products include lipids, convertible into biodiesel, carbohydrates convertible into ethanol, and proteins potentially viable for consumption by both humans and animals (Bouyahya et al. 2024). Microalgae, hailed as a potential third-generation biodiesel source, pose challenges in strain selection due to significant variability in physiology, genetics, and metabolic potential among visually similar strains (Musa et al. 2019). These organisms are gaining attention as a biorefinery feedstock because of their carbon fixation, rapid growth, and bioactive compounds like lutein, known for benefiting human health, especially eye and brain function (Lee et al. 2021). Current biodiesel production research relies heavily on nano-catalysts due to shortcomings in traditional homogeneous and heterogeneous catalysts. Homogeneous catalysts struggle with product isolation, demand substantial water quantities, and contribute to environmental pollution via liquid waste. On the other hand, heterogeneous catalysts often face challenges with mass transfer, are time-consuming, and lack efficiency. Studies indicate that these issues can be addressed by utilizing nano-catalysts, which offer heightened specific surface areas and superior catalytic abilities (Akubude et al. 2019). Various applications of nano-catalysts in biodiesel production from microalgae scrutinize hurdles and strategies for enhancing biodiesel yield from microalgae feedstock and explore the potential and uses of microalgae and nano-catalyzed transesterification to maintain its effectiveness as a viable processing method (Pavan et al. 2017). Biodiesel, a liquid fuel comprising mono alkyl esters (methyl or ethyl) from long-chain fatty acids sourced from vegetable oils, animal fats, or algal oil (Galchar 2017), is produced by chemically converting animal fats or vegetable oils into a fuel suitable for diesel engines. Defined as a biofuel derived from renewable bio-lipids through transesterification, it's an environmentally friendly, non-toxic, and biodegradable fuel mainly obtained from plant oils and animal fats (Indhumathi et al. 2014; Sidra et al. 2016; Akubude and Nwaigwe 2016). This fuel, derived from lipid sources like oil crops, waste oil, microalgae, and animal fat, particularly highlights microalgae's potential due to its growth in various conditions without competing with food production or land resources (Goswami et al. 2020; Gaurav et al. 2024). In biodiesel production, the lipid content and fatty acid makeup of each feedstock significantly influence both yield and quality. Essential characteristics of biofuel, like cetane number, cold-flow properties, oxidative stability, and iodine value, rely on the structure of fatty esters, which, in turn, depend on carbon chain length, unsaturation level, and alcohol components within the ester (Qaria et al. 2017). Consequently, selecting microalgae species for biodiesel production requires high lipid productivity and an appropriate fatty acid composition. Biodiesel derived from saturated fats exhibits higher oxidative stability and a greater cetane rating but suffers from poor performance in lower temperatures, potentially gelling at ambient levels. Conversely, biodiesel from high-PUFA feedstocks boasts good cold-flow properties but tends to be prone to oxidation, leading to stability issues during extended storage (Chhandama et al. 2024). Studies propose that high-quality biodiesel should maintain relatively low levels of long-chain saturated fatty acid methyl esters (FAME) and polyunsaturated FAME to ensure satisfactory operability in cold temperatures and oxidative stability (Wenchao et al. 2020). Nano-catalytic processes play a significant role in all microalgae-based biodiesel applications. These advanced catalysts are pivotal in enhancing product quality and achieving ideal operational conditions. Nano-catalysts possess unique characteristics like high surface area, exceptional catalytic activity, resistance to saponification, and robustness (Velan et al. 2014). These traits make them preferable over other catalysts, such as heterogeneous catalysts, which encounter issues like mass transfer resistance, time consumption, rapid deactivation, and inefficiency (Akia et al. 2014). Due to their clear advantages, there's a growing focus on developing new types of nano-catalysts to replace conventional ones. Traditionally, biodiesel production utilized homogeneous, heterogeneous, and enzymatic catalysts such as KOH, NaOH, zeolites, and lipases. However, current research trends favor nano-catalysts in transesterification due to their advantages over conventional catalysts. For instance, studies have highlighted the enhanced biodiesel yield, reaching up to 96% with CaO nanoparticles (Gupta and Agarwal 2016). Furthermore, combining catalysts, like CaO and MgO heterogenic nanocatalysts, significantly improved efficiency, yielding biodiesel at 98.95% from recycled cooking oil (Tahvildari et al. 2015). In algae-derived biodiesel production, the utilization of nano-catalytic transesterification processes led to impressive FAME yields of up to 99.0% with specific catalyst loadings and reaction conditions (Siow et al. 2016). Additionally, various nano-catalysts, including nano-magnetic solid base catalysts and nano-rods like ZnO, have shown promising prospects in biodiesel synthesis from different oil sources (Ali et. al. 2017). Microalgae, considered a third-generation biomass, offer advantages such as carbon fixation, swift growth, minimal land use, and high energy output compared to land-based biomass (Chen et. al. 2019). Yet, their abnormal growth patterns cause environmental issues, prompting research to convert them into biofuels or valuable products while addressing their impact on ecosystems (Lee et. al. 2019). Microalgae biodiesel, as a third-generation alternative, stands out due to its distinct properties compared to other fuel sources. It's renewable, environmentally friendly, and offers high energy output, potentially exceeding conventional crops in energy production per unit of land. Its production flexibility throughout the year, growth on undeveloped land without environmental impact, rapid growth with substantial oil content, and pesticide-free cultivation make it advantageous for biodiesel production (Rasul et. al. 2019). Biodiesel derived from microalgae presents multiple advantages over conventional resources due to its higher oil and biomass yields and its ability to grow on non-arable land. Microalgae thrive using industrial and municipal wastewaters, allowing for the production of biodiesel that could entirely substitute petroleum-based diesel. Reports suggest that microalgal biomass is rich in oil content, enabling the generation of diesel (Rasul et. al. 2019). Utilizing Magnetic Cs/Al/Fe3O4 as a nano-catalyst in the transesterification of sunflower oil under optimal conditions resulted in a notable catalytic activity, yielding biodiesel at 94.8% (Haldar et. al. 2018). Obadiah et al. achieved a 90.8% biodiesel yield by transesterifying Pongamia oil with methanol, employing calcined Mg-Al hydrotalcite as a solid base catalyst (Feyzi et. al. 2013). Meanwhile, studies on sunflower oil transesterification using nano-MgO precipitated and deposited on TiO 2 support exhibited conversions of 84–95% at higher temperatures compared to lower temperatures, indicating improved catalytic efficiency (Obadiah et. al. 2012). Researchers have also explored the use of various nano-crystalline MgO catalysts in nano-sheets to enhance biodiesel production from rapeseed and sunflower oils (Mguni et. al. 2012). Additionally, Hu et al. achieved over 95% yield of desired fatty acid methyl esters using nano-magnetic catalyst KF/CaO-Fe3O4 for stillingia oil biodiesel production under optimized conditions (Verziu et. al. 2008; Hu et. al. 2011). Numerous studies by different researchers have delved into the utilization of nano-catalysts to enhance biodiesel production, some focusing on microalgae as feedstock (Hossain et. al. 2019). Innovative methods employing nanocatalysts for biodiesel production from microalgae involve extracting algae oil without cell disruption and further converting it into biodiesel. Lin developed a novel mechanism employing biocompatible, sponge-like mesoporous nanoparticles to harvest fatty acids from algal cultures without harming the cells (Hossain et. al. 2019). These nanoparticles selectively absorb oils from living algae without causing harm, by entrapping lipid molecules produced within the cell structure (Palaniappan 2017; Nizami and Rehan 2018). Catalysts like strontium and calcium oxides can be integrated into the nanoparticle pore structure, facilitating in-vitro transesterification of entrapped lipids (Ooi et. al. 2021). Researchers are currently exploring nano-porous carbons and other inorganic derivatives as potential adsorbents for biofuel separation. Non-catalytic transesterification transforms triglycerides into biodiesel using alcohol in supercritical conditions, offering quick reaction times, simpler purification, and wider feedstock tolerance compared to catalytic methods (Kiran et. al. 2014; Eldiehy et al. 2022). However, it entails high operational costs, energy usage, and requires higher ratios of oil to alcohol, elevated temperatures, and pressures than catalytic processes (Pikula et. al. 2022). The conversion of microalgae oil into fatty acid methyl esters (FAME) through non-catalytic transesterification has been explored using various supercritical fluids like methanol, ethanol, dimethyl carbonate, and methyl acetate (Felix et. al. 2019). Studies have investigated optimal conditions for yielding FAME from Chlorella vulgaris and Chlorella sorokiniana CY-1 oils, achieving conversion yields in the range of 74.6–92.8% under specific process conditions (Yew et. al. 2021). Shirazi et. al. (2017) investigated non-catalytic transesterification of Chlorella protothecoides oil, achieving a conversion increase from 19.3–95.5% under specific conditions of 200 bar, 9:1 MeOH:oil molar ratio, and 300 to 400 ◦C temperatures. Liu et. al. (2015) utilized response surface methodology to optimize biodiesel production from Chlorella protothecoides microalgae oil, achieving 90.8% and 87.8% yields using supercritical MeOH and EtOH, respectively, under specific conditions. Moreover, non-catalytic transesterification of Schizochitrium limacinum microalgae resulted in over 90% conversion using MeOH, around 50% with DMC, and approximately 40% with MeOAc under varied temperatures and durations (Enamala et. al. 2018). Multiple research endeavors focused on generating biodiesel (BD) from wet microalgae biomass. Tsigie et. al. (2012) conducted in situ BD production from damp Chlorella vulgaris under subcritical conditions, yielding 0.29 g/g dry biomass. They also explored BD production from the same wet biomass through in situ lipid hydrolysis and supercritical transesterification with EtOH, achieving crude BD yields with extraction efficiencies ranging from 56–100% (Levine et. al. 2010). Jazzar et. al. (2015) executed supercritical MeOH transesterification of identified native microalgae—Chlorella sp. and Nannochloris sp. with 75% moisture content, obtaining maximum BD yields of 45.6 wt% and 21.8 wt%, respectively. Catalytic transesterification is categorized into homogeneous and heterogeneous catalysis based on the catalyst type (Eldiehy et. al. 2022). Both alkaline (found in homogeneous and heterogeneous forms), acidic catalysts (in homogeneous and heterogeneous versions), and enzymatic catalysts find application in transesterification processes involving lipids derived from microalgae (Kim et. al. 2022). Alkaline catalysts, effective at low temperatures and pressures, are discouraged with high percentages of unsaturated free fatty acids (FFAs) due to potential soap formation when FFAs exceed 0.5 wt% (Macías-Sánchez et al. 2015). This soap formation reduces FAME yield, complicates separation from glycerol, and causes catalyst loss CaO and MgO serve as prevalent heterogeneous alkaline catalysts for their limited solubility in MeOH and high catalytic efficacy (Al-Zuhair et al. 2007). In the realm of transesterification with microalgae oil, Ma et. al. (2015) utilized a KOH/Al 2 O 3 catalyst for in situ transesterification of Chlorella vulgaris, yielding 89.5 ± 1.6 wt% of biodiesel after a 5-hour reaction under optimized conditions (10 wt% KOH/Al 2 O 3 and 60°C) [68]. From the identical Chlorella vulgaris source, biodiesel (BD) production surged to 67.3 ± 2.2% and 71.0 ± 3.3% through in situ transesterification with microwave and ultrasound irradiation, respectively, using a KF/CaO catalyst over a 60-minute reaction period. The pinnacle BD yield of 93.1 ± 2.4% resulted from combined ultrasound and microwave irradiation during in situ transesterification of microalgae within 45 minutes (Ma et. al., 2015). Kazemifard et. al. (2019) utilized a magnetic KOH/Fe 2 O 3 -Al 2 O 3 nanocatalyst for in situ transesterification with mixed microalgae biomass, achieving a 95.6% lipid-to-ester conversion in 6 hours at 65°C. In Nannochloropsis oculata microalgae transesterification, the CaMgO/Al 2 O 3 catalyst yielded 85.3% FAME at 60°C for 3 hours using 10 wt% and 75.2% with 20 wt%, while a 30.0% CaO/dolomite catalyst produced 90.0% FAME from Chlorella protothecoides at 65°C for 3 hours with a 6:1 MeOH/microalgae oil molar ratio (Çakırca et. al., 2019). Acid-catalyzed transesterification generates FAMEs by protonating the ester's carbonyl group, suitable for high FFA content (> 1%) but demands longer reaction times, higher reagent amounts, temperatures, and pressures compared to alkaline processes, limiting commercial viability due to corrosiveness and cost (Pikula et. al., 2020). In lipid transesterification, heterogeneous acid catalysts like zirconium oxide (ZrO 2 ), titanium oxide (TiO 2 ), zeolites, and ion exchange resins are commonly used (Hidalgo et al., 2013). The study reveals their application in microalgae oil transesterification: Guldhe et. al. (2017) attained 98.3% BD conversion from Scenedesmus obliquus using a 15 wt% chromium–aluminum catalyst at 80°C for 4 hours, while 94.6% BD conversion emerged from the same microalgal biomass employing 15 wt% tungstated zirconia (WO 3 /ZrO 2 ) at 100°C in 3 hours. Furthermore, a phosphotungstic acid-modified zeolite imidazolate framework (HPW/ZIF67) achieved a 98.5% catalyst efficiency for Chlorella vulgaris BD production at 200°C within 90 minutes (Cheng et. al. 2021). Scenedesmus sp. achieved reduced BD conversions of 51.9% and 71.4% using 4 wt% of WO 3 /ZrO 2 through microwave and ultrasound-assisted in situ transesterification, respectively (Guldhe et. al. 2014). Loures et. al. (2018) attained a 98% BD yield using Nb 2 O 5 /SO 4 as a heterogeneous acid catalyst at 250°C for 4 hours in a pressurized stainless-steel reactor. Another investigation involved a carbon-based catalyst (DMB), derived from carbonizing de-oiled Tetradesmus obliquus KMC24 microalgae biomass and sulfonating it, showing optimal conditions for a maximum FAME yield of 94.2%: a MeOH/oil molar ratio of 11:1, 4 wt% catalyst concentration, 70°C temperature, and 8 hours reaction time (Roy and Mohanty 2021). Enzymatic transesterification using lipase eliminates chemical catalyst downsides, offering lower energy, moderate conditions, and ease of recovery but faces challenges like costly enzymes, decreased activity over time, incomplete reactions, and complex glycerol recovery, hindering large-scale viability (Fazal et. al. 2018). Enzymatic transesterification relies on factors like temperature, alcohol-to-oil ratio, alcohol choice, solvents, water content, pH, and enzyme quantity. While many lipases work below 70°C, the ideal temperature varies based on ratios, solvents, and immobilization. A slight excess of alcohol (3 − 5:1) aids in the process; however, MeOH and EtOH, though cost-effective, can denature lipases, requiring organic solvents to boost alcohol solubility and shield enzymes. Optimal conditions for lipases include 10–20% water content, pH levels between 7.5 and 8.5, and an enzyme concentration of 0.7 mg/mL for maximum reaction efficiency (Hossain et. al. 2020). Navarro-López et. al. (2016) explored FAME production from wet Nannchloropsis gaditana biomass through direct enzymatic transesterification using Novozyme 435 lipase, achieving a 99.5% FAME conversion over 56 hours by adding MeOH in 3 stages and t-butanol to counter lipase deactivation. Tian et. al. (2016) devised a novel process for BD conversion from Schizochytrium sp. oil, obtaining a 95.0% FAME yield through the combined use of lipase NS81006 and Novozym435. Taher et. al. (2014) investigated enzymatic BD production with immobilized Novozyme®435 under supercritical CO 2 (SC-CO 2 ), reaching an 80.0% FAME yield at 47°C, 200 bar, 35% enzyme loading, and a 9:1 MeOH to lipid molar ratio within a 4-hour batch reaction. Novozyme 435 (N435), an immobilized lipase from Candida antarctica, demonstrated 99.1% conversion efficiency from Nannochloropsis oceanica IMET 1 oil in 4 hours at 25°C, a 1:12 oil to MeOH molar ratio, and a 20% catalyst concentration (Wang et. al. 2014). Bioenergy in Jordan In 2021, Jordan had a population of 10,269,022, experiencing a yearly population growth of 0.6% (Monisha-Miriam et al. 2021). With an energy consumption of 8166 tons of oil equivalent in the same year, Jordan is recognized as one of the nations with high energy consumption (Addustour 2022). The vulnerability of Jordan's energy sector to external shocks, such as price fluctuations, underscores the necessity for resilience in this industry due to its significant impact on the country's economy. Jordan annually generates 2.7 million tons of municipal solid waste, posing environmental challenges rather than benefiting the energy industry or economy. Biomass contributes only 0.1% to the country's energy needs, primarily from wood sources like logs, chips, bark, and sawdust, comprising 44% of produced energy (Myyas et. al. 2023). The nation holds significant potential for future biomass production, with animal manure accounting for 96% of biomass, followed by olive trees and pomace at 1.8%. This study assesses Jordan's waste's theoretical energy potential and explores its biomass potential, envisioning the country as a key bioenergy producer through waste and proposing methods to evaluate biogas potential from common substrates like food and agricultural waste in Jordanian communities. At present, more than 90% of the waste accumulates in unsanitary landfills and dumpsites nationwide due to extensive waste production and limited disposal options. Uncontrolled waste leachate infiltrates the soil, polluting the water sources. Open landfills not only attract disease-carrying pests but also pose significant health risks and hazards to the public's well-being. Anticipated population growth suggests a projected annual increase of 3% in waste generation, encompassing hazardous waste and municipal solid waste (MSW) (MoE 2022). Jordan is taking steps to address its environmental and economic concerns by initiating a biomechanical waste treatment endeavor. This project intends to set up a mechanical-biological facility specifically for processing organic waste, starting with a capacity of 239 tons per day. The primary goals include waste recycling, energy production, and fertilizer creation (Da’aja 2022). By annually burning roughly 19 million cubic meters of biogas, this initiative aims to cut emissions by 175,000 tons, equivalent to carbon dioxide (Amer et. al. 2021). Recent focus has shifted to alternative energy sources in Jordan, such as biofuel derived from agricultural waste. Initiatives like biogas plants and Jatropha cultivation in arid regions exhibit potential but lack comprehensive economic analysis and detailed information on biofuel output (Amer et. al. 2021). Jordan, without domestic oil production, heavily relies on imported oil and natural gas to fulfill its energy needs, with only 4% met by local natural gas, straining the economy as energy imports consume more than a quarter of its GDP. Despite efforts to adopt solar, wind, biogas, and hydro energy, the biomass sector remains marginal, generating just 3.5MW, a fraction of the overall energy requirements (Saeedan 2011). Jordan has been actively exploring bioenergy production, particularly biogas and biodiesel, aiming to diversify its energy sources and reduce reliance on imports. The research in Jordan on biogas and biodiesel production aims to address the country's energy needs while considering environmental sustainability and utilizing locally available resources. As far as the authors are aware, this approach has not been explored with marine microalgae. Therefore, the main objective of this work was to investigate the use of calcium methoxide as a catalyst for transesterification in the production of biodiesel from marine microalgae, representing a novel aspect of this research. Materials and Methods Cultivation of Microalgae Three varieties of marine microalgae were obtained from the Faculty of Plant Science at Tanta University in Egypt. Creating microalgal biomass proves more financially demanding and technologically intricate compared to growing crops, as these microorganisms rely on light, CO 2 , water, and inorganic salts for their photosynthesis process. The study utilized straightforward photobioreactors, focusing on generating biodiesel from these marine microalgae for subsequent examinations. Beginning with the cultivation of Nannochloropsis, Tetraselmis, and Isochrysis in separate 300 ml containers, each equipped with light and CO 2 sources achieved by aerating atmospheric air into the setup. The controlled temperature ranged between 15°C to 25°C, while the growth medium supplied essential nutrients like KNO 3 (2 ml), NAH 2 PO 4 .H 2 O (2ml), FECL 3 .6H 2 O (3ml), and trace metals (2ml). Microalgae in a period of 4 days is shown in Figure 1. Nutrients used to feed microalgae is shown illustrated the four-day growth progression is shown in Figure 2. The visual appearance of microalgae cultures provides a reliable indication of their growth stage, with noticeable changes in color and density observed as they progress from the lag phase to exponential growth, is shown in Figure 3. After eight days, the microalgae displayed a dark green color, suggesting they were approaching their stable phase (Figure 3a). Allowing them to continue growing for an additional four days ensured the completion of their growth cycle. By day 16, the cultivation exhibited significant readiness for further growth (Figure 3b). Throughout this phase, 1L of seawater and nutrients were introduced into each container every three days. Around day 38, larger containers replaced the small ones due to the cultivation reaching a volume of approximately 20L (Figure 4). Harvesting methods The microalgae biomass was gathered through three methods: employing filter paper, centrifugation, and exposure to sunlight, all detailed in Figure 5. Following cultivation, the microalgae underwent centrifugation for 1 minute at a speed of 10,000 rotations per minute (rpm). Subsequently, a pipette was used to extract most of the water, leaving behind solely the microalgae biomass within the tube as depicted in Figure 6. The microalgae biomass underwent a three-day drying process within a laboratory setting (Figure 7). Following this, the dried algae biomass was weighed and prepared for oil extraction. Grinding was carried out using a pestle and mortar, utilizing specific grindery equipment as illustrated in Figure 8. The efficiency of photobioreactors hinges on various pivotal factors. Firstly, the availability of adequate light profoundly influences photosynthesis within microalgae. Secondly, the uptake of carbon dioxide significantly impacts their growth and productivity. Moreover, the quantity of oxygen generated during this process is crucial for the reactor's efficacy. Efficient gas transfer mechanisms are imperative to maintain optimal conditions within the reactor. Temperature fluctuations can notably affect growth rates and overall performance. Consistent mixing rates within the reactor are essential for uniform distribution of nutrients and gases. The pH level of the medium significantly influences the microalgae's physiological processes. Lastly, meeting specific nutrient requirements is vital for sustained growth and productivity within the photobioreactor. These factors collectively determine the effectiveness and output of photobioreactors employed in microalgae cultivation. Oil extraction The dried algae mass yielded significant amounts: 643 grams of Nannochloropsis, 1.3 kilograms of Tetraselmis, and 860 grams of Isochrysis. Subsequently, 80 grams of each type of ground microalgae were carefully placed into the thimble within the Soxhlet extractor, featuring a condensation system as shown in Figure 9. Within the distillation flask, hexane, the extraction agent, was heated to reflux, and its vapors condensed in the reflux condenser before descending into the thimble's chamber housing the substance for extraction. Gradually, the warm solvent filled the compartment, dissolving some of the material within it. As the Soxhlet chamber approached fullness, an automatic siphon sidearm emptied it, returning the solvent to the distillation flask. This cyclic process was repeated multiple times to accumulate the extracted material within the solvent in the distillation flask. The mantle heater was set to approximately 60°C, closely aligning with the hexane evaporation temperature of 64°C as indicated in Figure 10. A 1000 mL three-necked round-bottom flask served as the reactor in this setup. Positioned in a heating mantle, the flask maintained a steady temperature of +20 °C. Hexane was specifically chosen as the solvent due to its favorable characteristics. For every 80 grams of microalgae, 270 ml of hexane was utilized, resulting in the extraction of 30 ml of Isochrysis oil, 45 ml of Nannochloropsis oil, and 20 ml of Tetraselmis oil. The oil extraction process lasted for 8 hours, following which the hexane was removed using a Rotary Evaporator. Rotary evaporators, commonly known as "rotavaps" as depicted in Figure 11, are employed to remove solvents like hexane from reaction mixtures. To prevent the solvent from freezing during the evaporation process, the water bath in the rotary evaporator can be heated in a metal container or a crystallization dish. Microalgae oil after hexane evaporated (A) Nanno-, (B)Tetra-, (C) Iso-. Biodiesel production is shown in Figure 12. For further purification, the oil yield was subjected to a 2-hour period on a hot plate. Titration A solution for titration was prepared by dissolving 1 gram of potassium hydroxide in 1 liter of distilled water. To initiate the titration process, 1 mL of microalgal oil was combined with 10 mL of ethanol in a small beaker and thoroughly mixed. Two drops of phenolphthalein were added to the mixture as an indicator as shown in Figure 13. Gradually, using a burette, the potassium hydroxide (KOH) solution was slowly added drop by drop to the mixture until it turned pink. The reaction outcomes indicated that Nannochloropsis had a free fatty acid (FFA) content exceeding 5%, while Tetraselmis and Isochrysis possessed FFA levels below 5%. The acid value (AV), represented as (mg KOH/g oil), is calculated using Equation (Thein et. al. 2019). (1) It's noteworthy that the average value of free fatty acid in the microalgae oil wasn't determined due to the diverse species of microalgae and the variation in fatty acid percentages based on species and growth conditions. Esterification Esterification stands as the method of choice for removing both glycerol and fatty acids from vegetable oil, crucial for significantly reducing its viscosity. Widely regarded as the primary technique in this regard, it involves triglycerides reacting with three alcohol molecules in the presence of a catalyst, resulting in a blend of fatty acids, alkyl ester, and glycerol (Akubude et. al. 2019). Figure 14 shows microalgae oil produced by acid-catalyzed esterification process demands a higher amount of acid and methanol. Within a 500 mL three-neck round-bottom flask, sulfuric acid served as the catalyst while methanol acted as the reactant. Temperature measurement was facilitated by a thermometer fitted into one neck, while a water-cooled condenser, aimed at curbing methanol evaporation, connected to another neck. The third neck served for adding chemicals and collecting samples. Positioned atop sand on a hotplate, the reactor underwent heating. The prescribed ratio necessitated adding 2.25 g of methanol and 0.05 g of sulfuric acid for each gram of free fatty acid present in the oil. Prior to the reaction, methanol and H 2 SO 4 were pre-mixed, and the oil was preheated to 60°C before their addition. Stirring ensued at 60°C for at least two hours. Once the two-hour mark passed, the mixture settled, with the methanol-water combination rising to the top of the separator funnel and the oil layer resting at the bottom. Assessment revealed the new free fatty acid content to be less than 0.5% compared to the original oil composition, indicating the success of the process. Transesterification If the free fatty acid content remains below 0.5%, transesterification can be directly performed. Recent research by Akubude et al. (2016) highlights the increasing use of nano-catalysts in transesterification due to their advantages over traditional homogeneous and heterogeneous catalysts. To evaluate the reusability of the snail shell-derived catalyst, experiments were conducted, and the transesterification reaction pathway is illustrated in Figure 15. In this study, we employed calcium methoxide as a catalyst to sustain the reaction temperature and mitigate potential decreases. To ensure seamless integration with methanol and to minimize temperature fluctuations, the calcium methoxide was carefully introduced into the pre-warmed oil at 60°C. Figure 16 illustrates the setup and conditions used during this initial phase of the reaction. Given that alcohol and oils typically don't mix at room temperature, the reaction mixture was consistently heated to 80°C and stirred at 500 rpm to enhance mass transfer between the immiscible phases. Once the mixture reached 80°C, it was allowed to stand for a duration of 3 hours. The ratio employed was 3 ml of methanol to 1 ml of oil, as shown in Figure 17. After the reaction, the oil/methoxide mixture was transferred to a separatory funnel and allowed to settle for 48 hours to separate the glycerol waste. Once phase separation was complete, the glycerol layer was carefully drained from the bottom of the funnel. The upper layer, containing the crude biodiesel, was then returned to a clean beaker for further processing, following the procedure outlined in Figure 18. Washing To purify the crude biodiesel, warm distilled water was added to the separator funnel containing the biodiesel. The mixture was gently agitated to allow the water and biodiesel to combine. Allowing a two-day settling period enabled the separation of water from the biodiesel. The water was then drained, and this washing process was repeated an additional four to six times, as detailed in Figure 19. This series of washes serves to remove undesired components such as excess methanol or any remaining water present in the biodiesel. Physical and chemical analysis The physical and chemical characteristics of both the oil and biodiesel samples were assessed at Al Hussein Bin Talal University. The physical analyses included measurements of density, cloud point, flash point, pH, and viscosity at 40°C. The flash point results for the biodiesel samples derived from Nannochloropsis , Tetraselmis , and Isochrysis microalgae are illustrated in Figure 20, while the cloud point characteristics of the same samples are presented in Figure 21. Results and discussion Microalgae oil extraction and biodiesel production The experimental results in Table 1 reveal critical insights into the oil extraction and biodiesel production potential of three distinct microalgae species—Nannochloropsis, Tetraselmis, and Isochrysis—when processed with calcium methoxide catalyst. The oil yields obtained (45.01 mL for Nannochloropsis, 30.04 mL for Isochrysis, and 20.00 mL for Tetraselmis) are consistent with known physiological differences among these species, where Nannochloropsis is well-documented for its high lipid accumulation capacity, often exceeding 30–50% of dry biomass under optimized cultivation conditions (Hu et al. 2008). This high oil content, combined with efficient extraction, renders it the most promising candidate for biodiesel feedstock among the three studied species. The calcium methoxide catalyst employed demonstrated excellent catalytic activity, producing biodiesel yields exceeding 90% for all species, with Nannochloropsis achieving the highest average of 96.06%. This is indicative of an effective transesterification reaction facilitated by calcium methoxide, which is increasingly recognized for its high catalytic efficiency, recyclability, and environmental compatibility (Mardhiah et al. 2017). Compared to traditional homogeneous catalysts such as sodium hydroxide or potassium hydroxide, calcium methoxide offers reduced saponification, easier separation, and lower wastewater generation, key advantages for sustainable biodiesel production (Dalvand and Mahdavian 2018). The biodiesel yield differences among species, particularly the lower yield for Isochrysis (90.07%), may be attributed to the unique fatty acid profiles of these microalgae. Isochrysis is known to contain significant amounts of long-chain polyunsaturated fatty acids (PUFAs) like docosahexaenoic acid (DHA), which can complicate the transesterification process due to their sensitivity to oxidation and tendency to form partial glycerides or polymerized products (Avhad and Marchetti 2015). These fatty acid characteristics may contribute to slightly reduced conversion efficiency compared to species with more saturated or monounsaturated fatty acids, such as Nannochloropsis. The consistency of oil yield and biodiesel production over the ten runs with minimal variation underscores the robustness of the extraction and transesterification processes under the applied experimental conditions. This reproducibility is essential for scaling up the process, ensuring reliable yields for commercial biodiesel production. Furthermore, the high biodiesel yield demonstrates that calcium methoxide is an effective catalyst for microalgal oils, which often contain impurities such as chlorophylls, carotenoids, and other lipophilic compounds that can inhibit conventional catalysts (Bohloulia and Mahdavian 2019). When benchmarked against other microalgal biodiesel studies, the oil yields and biodiesel conversion efficiencies reported here compare favorably. For example, Chlorella vulgaris typically yields about 30–40 mL oil per 100 g biomass with biodiesel yields around 85–92% using sodium methoxide (Mardhiah et al. 2017), and Scenedesmus obliquus yields approximately 35 mL oil per 100 g with 88–94% biodiesel yield using potassium hydroxide catalysts (Baskar and Aiswarya 2016). The higher oil yields and competitive biodiesel conversion efficiencies using calcium methoxide in this study suggest the catalyst’s superiority and potential for industrial biodiesel production, especially considering its heterogeneous nature that allows for catalyst recovery and reuse, thus lowering production costs and environmental impact (Doh et al. 2021). Table 1 Oil Yield (mL) from 80 g Microalgae and Biodiesel Yield (%) Enhanced by Calcium Methoxide Catalyst Run # Oil Yield (mL) Biodiesel extraction (%) Nannochloropsis Tetraselmis Isochrysis Nannochloropsis Tetraselmis Isochrysis 1 45.0 20.0 30.0 96.0 93.0 90.0 2 44.8 20.2 29.9 96.2 93.1 89.8 3 45.2 19.8 30.1 95.9 92.8 90.2 4 45.1 20.1 30.0 96.1 93.2 90.0 5 44.9 19.9 30.3 96.0 93.0 90.4 6 45.0 20.0 30.1 96.3 93.3 90.3 7 45.3 20.2 29.8 96.1 93.1 89.9 8 44.7 19.7 30.2 95.8 92.9 90.1 9 45.1 20.0 30.0 96.2 93.2 90.0 10 45.0 20.1 30.0 96.0 93.0 90.0 Average 45.01 20.00 30.04 96.06 93.06 90.07 Physical properties of microalgal oil Table 2 shows the comparison of physical properties of microalgal oil and different vegetable oils. The results indicated that the higher viscosity indicates thicker oil, which might affect its ease of use in certain applications. Lower viscosity oils like Tetra microalgae oil (13.3 cSt at 40°C) could be more favorable for some purposes requiring smoother flow. Tetra microalgae oil exhibits the lowest viscosity among the microalgae oils listed, with a viscosity of 13.3 cSt at 40°C. The kinematic viscosity indicates the resistance of the oil to flow at 40°C. Among the three, Tetra microalgae oil has the lowest viscosity, suggesting it flows more easily compared to Iso and Nanno microalgae oils. This refers to the oil's resistance to flow at a specific temperature (40°C). However, when compared to various vegetable oils, it falls within the lower to mid-range in terms of viscosity. For instance, it's notably lower than Jatropha, Karanja, Neem, Palm, Peanut, and Rapeseed oils but slightly higher than Linseed and Rice Bran oils. Iso microalgae oil, with a viscosity of 25.2 cSt at 40°C, ranks slightly higher in viscosity compared to Tetra but still falls below the viscosities of Jatropha, Karanja, Neem, Palm, and Rapeseed oils. It aligns more closely with Thumba, Sunflower, Soybeans, and Cotton Seed oils. Nanno microalgae oil presents the highest viscosity among the microalgae oils, standing at 39.1 cSt at 40°C. It surpasses the viscosities of most other vegetable oils in the table except for Jatropha and Karanja oils. Table 2 Comparison of physical properties of microalgal oil and different vegetable oils (Karmakar et. al. 2017). Oil Kinematic Viscosity (cSt 40° C) Cloud point (°C) Flash point (°C) Density (kg/m3) Pour point (°C) Tetra microalgae oil 13.3 -3.3 225 887 -10 Iso microalgae oil 25.2 -1.2 201 900 1.1 Nanno microalgae oil 39.1 -4 274 915 -17 Handal 16.49 + 5 221 899 -9 Thumba 31.5 -1 201 905 - Jatropha 49.9 16 240 921 8 Karanja 46.5 13.2 248 929 6 Rapeseed 37 -3.9 246 911 -31.7 Neem 57 8 295 938 2 Sunflower 33.9 7.2 274 916 -15 Soybeans 32.6 -3.9 254 914 -12 Coconut 27.7 - 281 915 - Cotton Seed 33.5 1.7 24 914 -15 Rice Bran 28.7 13 200 937 1 Peanut 39.6 12.8 271 902 -6.7 Linseed 27.2 1.7 241 923 -15 Palm 39.6 27 271 918 -15 Corn 34.9 -1.1 277 909 -40 Babassu 30.3 20 150 946 - Diesel 2.75 -15 66 835 -20 The cloud point of microalgal oil and different vegetable oils is shown in Table 2 . The cloud point is the temperature at which the oil starts to form cloudy or solid particles. The results revealed that the lower cloud points like those of Tetra (-3.3°C) and Nanno (-4°C) microalgae oils imply better performance in colder conditions without solidifying. The cloud point is crucial for applications in colder environments. All three oils have relatively low cloud points, indicating they remain liquid at low temperatures. Tetra and Nanno microalgae oils have slightly lower cloud points compared to Iso microalgae oil. Tetra microalgae oil exhibits a cloud point of -3.3°C, which is similar to the cloud points of Rapeseed and Soybeans oils. It is lower than most other oils listed, indicating better low-temperature performance. Iso microalgae oil displays a cloud point of -1.2°C, indicating relatively better low-temperature properties than Tetra microalgae oil but higher than several other oils such as Rapeseed, Cotton Seed, and Linseed oils. Nanno microalgae oil shows a cloud point of -4°C, presenting better low-temperature performance than Tetra and Iso microalgae oils and comparable to Rapeseed and Soybeans oils. The flash point of microalgal oil and different vegetable oils is shown in Table 1 . The flash point of microalgae oils 201°C for Iso, 225°C for Tetra, and 274°C for Nanno—holds significance in assessing their safety and potential applications. Higher flash points generally indicate a safer oil in terms of handling, transportation, and storage, as they are less prone to ignite under specific conditions. Nanno microalgae oil stands out with the highest flash point, making it potentially the safest among the three for use in environments where high temperatures or potential ignition sources are concerns. Tetra microalgae oil follows with a slightly lower flash point but still exhibits a considerably safe threshold. Iso microalgae oil, despite having the lowest flash point among the three, still falls within a range considered safe for many applications. Understanding these flash point differences aids in selecting suitable oils for industries like manufacturing, where safety protocols demand oils with higher ignition resistance. However, all three oils demonstrate relatively safe flash points, ensuring their viability for various industrial and commercial applications where safety and stability are essential considerations. Iso microalgae oil has a flash point of 201°C, which is lower than Jatropha, Karanja, Neem, Palm, Peanut, and Rapeseed oils but similar to Sunflower and Soybeans oils. Iso microalgae oil exhibits a flash point of 201°C, aligning with Tetra microalgae oil and sharing similarities with Sunflower and Soybeans oils. Nanno microalgae oil presents a flash point of 274°C, surpassing the flash points of most oils in the table, indicating higher resistance to ignition compared to the majority of vegetable oils listed. The flash point of a fuel, indicating its susceptibility to ignition upon exposure to a spark or flame, was determined using the Pensky Martens Flash Point apparatus. In this context, the used Nanno biodiesel oil displayed a flash point of 100.5°C, while Tetra biodiesel oil recorded 99.9°C and Iso biodiesel oil measured 99.1°C. These values for the microalgal oils were higher than that of conventional diesel (66°C), Handal (50°C), and Thumba (66°C). However, they remained lower than Jatropha biodiesel (175°C), Sunflower biodiesel (183°C), and Neem biodiesel (180°C). Remarkably, the used Nanno oil showcased an exceptionally high flash point of 274°C, far surpassing diesel fuel's flash point at 66°C. The flash point of Handal biodiesel stood at 50°C, lower than Thumba (66°C), Jatropha (175°C), Karanja (187°C), Iso (99.1°C), Nanno (100.5°C), and Neem seed oil (180°C). The presence of chemically bound oxygen in vegetable oils tends to reduce their heating values by approximately 10%. It's important to note that while the flash point is a critical parameter for safety during storage and handling, it doesn't directly impact engine performance (Sidibé et. al. 2010). Moreover, the flash point is often utilized as a regulatory criterion for categorizing fuels during transport and storage, and these standards vary across different regions. Harmonizing these standards would likely necessitate corresponding alignment in regulations. The density of microalgal oil and different vegetable oils is shown in Table 2 . Density represents the mass per unit volume of the oil. Nanno microalgae oil has the highest density, which might impact its behavior in various applications, while Tetra microalgae oil has the lowest density among the three. The results exhibited that the nanno microalgae oil has the highest density (915 kg/m³), which may impact its behavior in various applications. Tetra, Iso, and Nanno microalgae oils showcase varying densities compared to the array of vegetable oils, indicating unique characteristics within this spectrum of properties. Overall, Tetra, Iso, and Nanno microalgae oils exhibit diverse physical properties in comparison to the range of vegetable oils listed, showcasing variations in viscosity, low-temperature performance, ignition resistance, density, and pour points. The pour point of microalgal oil and different vegetable oils is shown in Table 2 . This is the temperature at which the oil begins to solidify or lose its flow characteristics. Lower pour points like those of Tetra (-10°C) and Nanno (-17°C) microalgae oils signify better performance in colder environments. The pour point signifies the lowest temperature at which the oil remains fluid. Tetra and Nanno microalgae oils have lower pour points compared to Iso microalgae oil, indicating better performance in colder conditions. Chemical Properties of microalgal oil The chemical properties of fatty acids found in microalgal oil, compared with various vegetable oils, are detailed in Table 3 . The outcomes highlight specific compositions of fatty acid methyl esters (FAME). In Tetra microalgae oil, the dominant fatty acid is Linoleic acid (C18:2) at 50.60 ± 1.2 wt. %, followed by Oleic acid (C18:1) at 38.2 ± 0.7 wt. %, Stearic acid (C18:0) at 34.1 ± 0.5 wt. %, Palmitoleic acid (C16:1) at 2.8 ± 0.6 wt. %, Palmitic acid (C16:0) at 0.30 ± 0.4 wt. %, and Linolenic acid (C18:3) at 0.10 ± 0.6 wt. %. In ISO sp microalgae oil, Oleic acid (C18:1) dominates at 60.5 ± 1.5 wt. %, while Palmitoleic acid (C16:1) registers the lowest percentage at 0.33 ± 0.6 wt. %. Meanwhile, in NANNO sp, the highest value is found in Oleic acid (C18:1) at 54.7 ± 0.9 wt. %, whereas Linoleic acid (C18:2) is recorded at 0.4 ± 0.6 wt. %. These findings differ significantly from the composition observed in biodiesel derived from Palm oil, where Palmitic acid (C16:0) holds the highest percentage (45.60% and 38.50%), followed by Linoleic acid (C18:2) at 10.50%, Stearic acid (C18:0) at 3.80%, and Linolenic acid (C18:3) at 0.10%. Table 3 presents a comparative analysis of fatty acid distribution in microalgae oil and three types of vegetable oil: soybean, palm, and sunflower. In microalgae oil, the dominant fatty acids are palmitic (C16:0), stearic (C18:0), and oleic (C18:1), with percentages of approximately 3.12%, 45.82%, and 16.52% respectively. It also contains smaller amounts of palmitoleic (C16:1), linoleic (C18:2), and linolenic (C18:3) acids at 1.22%, 7.54%, and negligible amounts, respectively. Soybean oil, on the other hand, is characterized by higher proportions of linoleic acid (C18:2) at 55.40%, followed by oleic acid (C18:1) at 25.20%. Palmitic acid (C16:0) and stearic acid (C18:0) constitute 11.2% and 2.90% of the fatty acid composition, respectively. Palm oil shows a significantly higher percentage of palmitic acid (C16:0) at 45.60%, with oleic acid (C18:1) and stearic acid (C18:0) constituting 38.50% and 3.80%, respectively. Sunflower oil displays a high content of linoleic acid (C18:2) at 51.30%, followed by oleic acid (C18:1) at 38.70%. Palmitic acid (C16:0) and stearic acid (C18:0) are present in smaller amounts at 6.70% and 2.90%, respectively. It can be concluded that microalgae oil exhibits a unique fatty acid profile compared to traditional vegetable oils, with potential implications for nutritional and industrial applications. Table 3 Fatty acid distribution in microalgae oil and three types of vegetable oil (Batista et. al. 2018). Microalgae oil Palmitic Palmitoleic Stearic Oleic linoleic linolenic C 16:0 C 16:1 C 18:0 C 18:1 C 18:2 C 18:3 Tetra 0.30 2.8 34.1 38.2 50.6 0.10 Iso 4.2 0.33 1.5 60.5 22.3 6.1 Nannochloris 15.5 16.7 1.2 54.7 0.4 0.8 microalgae 3.12 ± 0.02 1.22 ± 0.02 45.82 ± 0.10 16.52 ± 0.08 7.54 ± 0.10 soybean 11.2 2.90 25.20 55.40 5.00 Palm 45.60 3.80 38.50 10.50 0.10 sunflower 6.70 2.90 38.70 51.30 - Physical Properties of biodiesel production The physical of microalgae biodiesel are presented in Table 4 . The viscosity at 40°C, which indicates the fluidity of the biodiesel, was measured for three microalgae species. Nanno microalgae biodiesel exhibited a viscosity of 6.2 cSt, Tetra microalgae biodiesel had a viscosity of 7.976 cSt, and Iso microalgae biodiesel had a viscosity of 7.6 cSt. These values provide insights into the flow characteristics of the biodiesel derived from different microalgae species. Viscosity refers to the resistance of a fluid to flow. Lower viscosity biodiesel flows more easily and efficiently through fuel systems, enhancing engine performance. In the case of microalgae-derived biodiesel, varying viscosities are observed across different strains (Nanno, Tetra, Iso). Lower viscosity, as seen in Nanno biodiesel (6.2 cSt), can contribute to improved fuel atomization and combustion efficiency, potentially leading to reduced emissions, including CO 2 . The flash point, which denotes the lowest temperature at which the biodiesel can ignite, was determined for each microalgae biodiesel. Nanno microalgae biodiesel exhibited a flash point of 100.5°C, Tetra microalgae biodiesel had a flash point of 99.9°C, and Iso microalgae biodiesel had a flash point of 99.1°C. These values indicate the safety aspects of handling and storing microalgae biodiesel. The flash point is the temperature at which vapors produced by a fuel can ignite when exposed to an ignition source. Higher flash point values indicate greater safety and reduced fire hazards during handling and storage. The microalgae-derived biodiesels (Nanno, Tetra, Iso) exhibit high flash points (above 99°C), ensuring safer operation. This characteristic is crucial for mitigating risks during transportation and storage, thereby minimizing potential environmental impacts such as spills or accidents that could result in CO 2 emissions. The cloud point, which represents the temperature at which the biodiesel begins to solidify and form a cloudy appearance, was measured for the microalgae biodiesel samples. Nanno microalgae biodiesel displayed a cloud point of -39°C, Tetra microalgae biodiesel had a cloud point of -40.8°C, and Iso microalgae biodiesel had a cloud point of -45°C. Lower cloud point values indicate better low-temperature performance and reduced chances of fuel gelling or clogging fuel filters in cold environments. Cloud point refers to the temperature at which solid crystals begin to form in a fuel, causing it to become cloudy and potentially impacting its flow properties. Lower cloud points are desirable, especially in cold climates, as they ensure the fuel remains fluid and operable at lower temperatures. Microalgae-derived biodiesels demonstrate relatively low cloud points (e.g., Nanno: -39°C), indicating good cold flow properties. Enhanced cold flow characteristics can lead to improved fuel efficiency and reduced CO 2 emissions by facilitating engine start-up and operation in colder environments. pH is a measure of the acidity or alkalinity of a substance. While biodiesel is generally considered to have a neutral pH, slight variations may occur depending on the feedstock and production process. Microalgae-derived biodiesels (Nanno, Tetra, Iso) exhibit pH values within a relatively neutral range (6.8 to 7.71). Maintaining a neutral pH is important for ensuring compatibility with engine materials and minimizing corrosion or degradation, which can affect engine performance and emissions. By producing biodiesel with stable pH levels, the potential for CO 2 emissions related to engine maintenance or replacement due to corrosion can be minimized, contributing to overall CO 2 reduction efforts. Table 4 Physical properties of biodiesel from microalgae. Properties Unit Nanno Tetra Iso Viscosity at 40°C cSt 6.2 7.976 7.6 Flash Point C° 100.5 99.9 99.1 Cloud point C° -39 -40.8 -45 PH - 6.8 7 7.71 Table 5 provides a comprehensive comparison of fuel properties between algae biodiesel sourced from different microalgae strains (Nanno, Tetra, and Iso) and conventional diesel, alongside ASTM biodiesel standards as benchmarks. Viscosity at 40°C shows notable variations across the biodiesel types, with Nanno microalgae biodiesel exhibiting the lowest viscosity at 6.2, followed by Tetra microalgae biodiesel at 7.976 and Iso microalgae biodiesel at 7.6. In contrast, conventional diesel falls within the ASTM standard range of 1.9–4.1, suggesting a generally lower viscosity compared to the algae biodiesel variants. Flash points for the algae biodiesel samples are considerably higher than those of conventional diesel, with Nanno, Tetra, and Iso microalgae biodiesel recording values of 100.5, 99.9, and 99.1 respectively, surpassing the ASTM standard minimum of 100. Conventional diesel, however, falls short of this standard with a flash point of 60. Cloud points, indicative of low-temperature operability, depict a challenge for algae biodiesel, as all three variants exhibit considerably lower values compared to conventional diesel. Nanno, Tetra, and Iso microalgae biodiesel display cloud points of -38.9, -40.8, and − 45 respectively, contrasting with the range of -15 to 5 for conventional diesel, as per ASTM standards. This comparative analysis underscores the distinct fuel property profiles of algae biodiesel compared to conventional diesel and highlights areas for further optimization, particularly in addressing cloud point challenges to ensure broader operational suitability and regulatory compliance. Table 5 Comparison of algae biodiesel with convectional biodiesel and ASTM biodiesel Standards (). Fuel property Nanno microalgae Tetra microalgae Iso microalgae Conventional diesel (Akubude et. al. 2019) ASTM standard Viscosity at 40°C 6.2 7.976 7.6 1.9–4.1 3.5–5.0 Flash Point 100.5 99.9 99.1 60 Min 100 Cloud point -38.9 -40.8 -45 -15 to 5 - Petro-diesel and microalgae biodiesel cost comparison The production costs of Petro-diesel and microalgae biodiesel differ significantly. Petro-diesel production is largely influenced by crude oil prices and refining costs, while microalgae biodiesel production entails factors such as cultivation, extraction, and processing of microalgae biomass. Additionally, microalgae biodiesel production may involve expenses related to research and development, infrastructure, and technology optimization. Overall, microalgae biodiesel production costs can be higher initially but may offer long-term environmental and economic benefits due to its potential for sustainable production and reduced greenhouse gas emissions, especially CO 2 emissions. Production costs for both petrodiesel and biodiesel are influenced by two key factors related to scaling production. The first factor, scaling cost, refers to the expenses incurred when increasing production capacity. Utilizing economies of scale can help reduce biodiesel manufacturing costs, as seen in various industrial processes. This implies that significant outputs necessitate large-scale production facilities, as supported by our laboratory findings indicating minimal dry mass yield from microalgae despite sizable production volumes. Another critical aspect of cost scaling is learning effects, which denote advancements in technological processes, such as optimizing growth mediums and cultivation methods. These improvements compound, with each enhancement in output influencing subsequent outcomes. For instance, situating algae production facilities near power plants can lower costs due to constant CO 2 availability and reduced distribution expenses leveraging existing infrastructure. The costs of biodiesel production from microalgae can be categorized into depreciation, labor expenses, and equipment size and type. While raceway ponds are cheaper to construct and maintain, photobioreactors offer higher biomass production and easier management. Table 6 illustrates the scaling costs of photobioreactors across various capacities, offering insights into the correlation between capacity, dimensions, resource needs, and related expenses. Table 6 Scaling cost of photobioreactor (Jorquera et. al. 2010). Capacity (Tons of dry weight biomass per day) Length (meters) Carbon Dioxide (Kgs per day) Area (Acres) Electricity (Kilowatts) Cost (Euros) Demonstration 36 10 0.01 12 69000 1 1068 2881 0.4 55 580000 10 10692 28805 4.3 545 2.5 million 50 53466 144027 22 2727 6 million 100 106932 288053 44 5455 10 million The results revealed that the spans a range of capacities from demonstration-scale to 100 tons of dry weight biomass per day, illustrating various stages of production scalability. With increasing capacity, both the length and area of photobioreactors proportionally expand, necessitating larger physical infrastructure to accommodate higher biomass production. Daily carbon dioxide requirements also increase with capacity, indicating the direct relationship between biomass production and carbon dioxide consumption, emphasizing photobioreactors' role in carbon sequestration and mitigation. Larger photobioreactors exhibit significantly higher electricity consumption, implying increased energy input for greater biomass output. This highlights the importance of considering energy efficiency and sustainable power sources in large-scale algae cultivation. The cost of scaling up photobioreactors rises substantially with capacity. From demonstration-scale to 100-ton capacity, there is a significant escalation in investment, ranging from thousands to millions of euros, covering expenses related to infrastructure, equipment, energy, and maintenance.Biodiesel derived from palm oil typically costs approximately $ 0.66 per liter, representing a 35% increase compared to petrodiesel. This suggests that the conversion process from palm oil to biodiesel adds roughly $ 0.14 per liter to the oil's price (Acevedo et. al. 2015). To compete with petrodiesel, the price of palm oil-based biodiesel should ideally not exceed $ 0.48 per liter, assuming no biodiesel tax. Similarly, for microalgal oil to be cost-competitive with petrodiesel, a target price of $ 0.48 per liter is reasonable. Achieving independence from petroleum diesel and ensuring environmental sustainability require reducing the production cost of algal oil from around $ 2.80 to $ 0.48 per liter—a strategic imperative (Abdo et. al. 2015). This cost reduction target decreases to $ 0.72 per liter if the algal biomass, with 70% oil content by weight, is cultivated in photobioreactors. While these cost reductions are substantial, they are feasible with strategic efforts. The integration of photo-bioreactors and astaxanthin co-production can slash biodiesel production costs from $ 3.90 to $ 0.54 per liter, highlighting the potential for cost-effective strategies in biorefinery operations. Despite facing technical hurdles, economic analysis demonstrates the viability and profitability of such approaches. Cultivating microalgae in wastewater or co-producing with valuable products (VAPs) can drive down biodiesel production costs to $ 0.73 per kilogram of dry weight or $ 0.54 per liter (Acién-Fernández et. al. 2019; Nazifa et. al. 2021). Encouraging access to markets for VAPs, projected to reach $ 53.43 billion by 2026, is crucial. Thus, incentivizing research, development, and consumption of microalgae-based biodiesel is essential for bridging the cost gap with petroleum diesel. Microalgal oils have the potential to entirely supplant petroleum as the primary source of hydrocarbon feedstock for the petrochemical sector. To achieve this, microalgal oil must be obtainable at a price comparable to that of crude oil, as follows Yusuf (2007): C algal oil = 6:9 10 − 3 C petroleum (2) In the equation, where C algal oil ( $ per liter) represents the price of microalgal oil and C petroleum denotes the price of crude oil in dollars per barrel, microalgal oil should ideally not exceed approximately $ 0.41 per liter to be a viable substitute for crude oil when the latter is priced at $ 60 per barrel. If the price of crude oil increases to $ 80 per barrel, as is sometimes predicted, microalgal oil priced at $ 0.55 per liter is likely to become economically competitive with crude petroleum. This equation assumes that algal oil contains roughly 80% of the energy content of crude petroleum. Overall, the results underscore the complexities and challenges associated with scaling up photobioreactors for algae cultivation. While larger capacities offer greater potential for biomass production and CO 2 mitigation, they also entail higher resource requirements and investment costs. Balancing these factors is crucial for achieving economic viability and environmental sustainability in large-scale algae cultivation projects. Additionally, further research and technological advancements may be necessary to optimize efficiency and reduce costs in photobioreactor systems, facilitating their widespread adoption as a green solution for biomass production and carbon capture. Conclusions Nannochloropsis showcased the greatest promise as a microalgal feedstock for biodiesel production, achieving an impressive oil yield of 45.01 mL per 80 grams of biomass alongside a remarkable biodiesel conversion efficiency of 96.06% when utilizing calcium methoxide catalyst. In comparison, Isochrysis and Tetraselmis produced 30.04 mL and 20.00 mL of oil respectively, with biodiesel conversion efficiencies of 90.07% and 93.06%. The superior performance of Nannochloropsis can be attributed to its higher lipid content and favorable fatty acid profile. Furthermore, calcium methoxide demonstrated exceptional catalytic efficiency as a heterogeneous catalyst, delivering high conversion rates while minimizing soap formation and providing significant environmental benefits over conventional homogeneous catalysts. Oil extraction of microalgae revealed distinct differences among species. Nannochloropsis led with the highest oil yield of 45 mL, followed by Isochrysis at 30 mL, and Tetraselmis at 20 mL, reflecting variations in lipid content and extraction efficiency. Tetraselmis oil exhibited the lowest viscosity at 13.3 cSt (40°C), while Nannochloropsis showed the highest viscosity of 39.1 cSt, with Isochrysis falling in between at 25.2 cSt. Both Tetraselmis and Nannochloropsis oils performed well in cold conditions, with cloud points of − 3.3°C and − 4°C respectively, whereas Isochrysis had a slightly higher cloud point of − 1.2°C. Nannochloropsis oil’s notably high flash point of 274°C suggests superior safety during handling, complemented by its relatively high density of 915 kg/m³, which may influence its suitability for various applications. Additionally, Tetraselmis and Nannochloropsis oils displayed low pour points of − 10°C and − 17°C, respectively, outperforming Isochrysis in cold flow properties. Fatty acid analysis showed Tetraselmis oil rich in linoleic acid (50.60 ± 1.2%) and oleic acid (38.2 ± 0.7%), whereas Isochrysis oil was predominantly oleic acid (60.5 ± 1.5%), and Nannochloropsis oil had the highest oleic acid content (54.7 ± 0.9%) with minimal linoleic acid (0.4 ± 0.6%). Microalgae-derived biodiesels demonstrate a compelling combination of physical properties that enhance fuel performance, safety, and environmental compatibility. Nannochloropsis biodiesel exhibited the lowest viscosity (6.2 cSt), promoting efficient fuel injection and combustion, while all three biodiesels—Nanno, Tetra, and Iso—maintained high flash points (above 99°C), ensuring safer handling and reduced fire risks. Their exceptionally low cloud points (from − 39°C to -45°C) highlight their superior cold flow characteristics, making them well-suited for colder climates without fuel gelling or filter blockages. Moreover, their near-neutral pH values (6.8–7.71) support engine material compatibility and long-term operational stability. Collectively, these traits not only confirm microalgae as a viable feedstock for high-quality biodiesel but also reinforce their potential to reduce carbon emissions and contribute to sustainable energy solutions. Despite its current higher production costs compared to petro-diesel, microalgae biodiesel stands out as a promising long-term solution due to its sustainability, carbon dioxide mitigation potential, and ability to integrate with high-value co-products like astaxanthin. Through strategic scaling, technological innovation, and the use of photobioreactors—particularly when paired with wastewater treatment—costs can be significantly reduced. With ongoing research, infrastructure investment, and supportive market policies, achieving a competitive price of $ 0.48– $ 0.55 per liter is within reach. This positions microalgae biodiesel as a viable, eco-friendly alternative for both the energy and petrochemical industries, offering a pathway toward a greener and more sustainable future. Declarations Ethical Approval This study does not involves humans and/or animals subjects. Consent to Participate The authors confirm that the study does not involves humans and/or animals materials. Consent to Publish All authors have provided their consent for this publication. Competing Interests The authors have no relevant financial or non-financial interests to disclose Clinical trial number not applicable. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Authors’ Contributions All authors contributed to the study's conception and design. Material collection, sample preparation, and drafting of the initial manuscript were performed by Hala Ghazi and Ali Al Sawalmih. Mohammad Al-Hwaiti contributed to the conceptualization, materials analysis, and interpretation of results, in addition to reviewing and editing the manuscript. He was also actively involved in data collection, writing, supervision, and final revisions. All authors have read and approved the final manuscript. Acknowledgments The authors express their sincere gratitude to all contributors who made this research possible. We are especially indebted to the Faculty of Plant Science at Tanta University, Egypt, for generously providing the marine microalgae samples that were essential to this study. Special thanks are extended to Eng. Oday Al Shamaseen and Eng. Njoud Alhabahbeh from the Bioenergy Laboratory at the Faculty of Engineering, Al-Hussein Bin Talal University, for their invaluable support in performing the physical and chemical analyses. 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days.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/02bd4ed02d55e7cb39a09101.png"},{"id":87184453,"identity":"b329a342-6ce0-414b-b2a6-e3eda78d85e6","added_by":"auto","created_at":"2025-07-21 10:10:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":486859,"visible":true,"origin":"","legend":"\u003cp\u003eNutrients used to feed microalgae.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/022b03a0adf3efe20a760a18.png"},{"id":87183094,"identity":"15416ef1-a487-4075-9341-4a9e3ddb7d3a","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":250534,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth Progression of Microalgae Culture at Day 8 (a) and Day 16 (b) Indicating Maturity and Readiness for Further Development.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/d8ebe1389ef435b31e6b76f5.png"},{"id":87184454,"identity":"c3608c20-ebb7-4144-a64f-fe951f43ab19","added_by":"auto","created_at":"2025-07-21 10:10:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":384856,"visible":true,"origin":"","legend":"\u003cp\u003eMicroalgae after 38 days.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/56d86442fcc9279d733bc382.png"},{"id":87183099,"identity":"faa72416-ac39-48f2-9d9c-e6b46926e313","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":240982,"visible":true,"origin":"","legend":"\u003cp\u003eFilter papers used to harvest algal biomass.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/e1364b28796f6b9fb2d27e21.png"},{"id":87183095,"identity":"64d01000-157a-493f-83a6-22a5d5fe055a","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":507370,"visible":true,"origin":"","legend":"\u003cp\u003eCentrifuge used for harvest algal biomass.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/501ad135d06ba9d667666c0c.png"},{"id":87186492,"identity":"fc26f271-279c-4f00-8d2b-a9e457af29b2","added_by":"auto","created_at":"2025-07-21 10:26:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":254844,"visible":true,"origin":"","legend":"\u003cp\u003eWet biomass of three types of microalgae before drying\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/7fba076af35f3278980693b5.png"},{"id":87183118,"identity":"5b226509-dd78-4fec-af19-7e65791d6240","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":318612,"visible":true,"origin":"","legend":"\u003cp\u003eDried microalgae biomass (A) and grinded biomass (B)\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/9ef7ac11fa693d51287e584c.png"},{"id":87183104,"identity":"73bc0a54-cd46-487b-be78-1097b4888223","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":502825,"visible":true,"origin":"","legend":"\u003cp\u003eExtraction of oil from the three types of microalgae.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/fc0ec6a815cef6f85a0193ea.png"},{"id":87184460,"identity":"c0937e99-0005-4285-b041-e732b7982fe5","added_by":"auto","created_at":"2025-07-21 10:10:47","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":206704,"visible":true,"origin":"","legend":"\u003cp\u003eMicroalgal oil before hexane evaporation.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/91ed992c8bc9d4df87b5114b.png"},{"id":87183107,"identity":"4fad76ee-e960-4bb0-9801-1f5812ee5656","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":145864,"visible":true,"origin":"","legend":"\u003cp\u003eEvaporating of hexane using rotavaps.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/3390fdd35aec0ca41e6c8189.png"},{"id":87183117,"identity":"8401f847-d640-40ba-9109-da284d5f9214","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":301228,"visible":true,"origin":"","legend":"\u003cp\u003eMicroalgae oil after hexane evaporated (A) Nanno-, (B)Tetra-, (C) Iso-. 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methanol.\u003c/p\u003e","description":"","filename":"16.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/4d6ba096ec3e5e38bc6207b7.png"},{"id":87186493,"identity":"e9a5ed64-3258-48f3-8119-2a78dccb693f","added_by":"auto","created_at":"2025-07-21 10:26:47","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":215080,"visible":true,"origin":"","legend":"\u003cp\u003eTransesterification process.\u003c/p\u003e","description":"","filename":"17.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/8d0901a2cc3da592984225c5.png"},{"id":87184890,"identity":"bbe0f261-9bbe-4451-8b11-b92204ca32f7","added_by":"auto","created_at":"2025-07-21 10:18:47","extension":"png","order_by":18,"title":"Figure 18","display":"","copyAsset":false,"role":"figure","size":117112,"visible":true,"origin":"","legend":"\u003cp\u003eBiodiesel before washing process.\u003c/p\u003e","description":"","filename":"18.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/395496edb720e2c4158461cf.png"},{"id":87183123,"identity":"607ea5b5-18bd-4f38-bc82-edd014557acf","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":19,"title":"Figure 19","display":"","copyAsset":false,"role":"figure","size":411294,"visible":true,"origin":"","legend":"\u003cp\u003eMicroalgal biodiesel production by washing process (A) Nanno, (B) Tetra, (C) Iso.\u003c/p\u003e","description":"","filename":"19.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/b5d2ef18236fa4b745036f55.png"},{"id":87183114,"identity":"b2015a0c-2667-48de-a9c7-b0fdb9f20d6f","added_by":"auto","created_at":"2025-07-21 10:02:47","extension":"png","order_by":20,"title":"Figure 20","display":"","copyAsset":false,"role":"figure","size":429074,"visible":true,"origin":"","legend":"\u003cp\u003ePhysical properties of microalgal biodiesel Flash point test (A) Nanno, (B) Tetra, (C) Iso.\u003c/p\u003e","description":"","filename":"20.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/39854aa9ec7d1df286ac040a.png"},{"id":87183137,"identity":"2dde016d-e787-4c3c-bce8-b4f5a3943754","added_by":"auto","created_at":"2025-07-21 10:02:48","extension":"png","order_by":21,"title":"Figure 21","display":"","copyAsset":false,"role":"figure","size":366993,"visible":true,"origin":"","legend":"\u003cp\u003ePhysical properties of microalgal biodiesel cloud point test (A) Nanno, Tetra, and Iso.\u003c/p\u003e","description":"","filename":"21.png","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/faf9a2d4a5f149177043b04e.png"},{"id":92645394,"identity":"97ed2be1-38fa-4a32-9e21-93abf87bde64","added_by":"auto","created_at":"2025-10-02 09:49:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8906034,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6819238/v1/c52452b2-71ed-4fe7-aeb8-46339643ac10.pdf"}],"financialInterests":"","formattedTitle":"Environmentally Friendly Biodiesel Synthesis from Marine Microalgae Using Calcium Methoxide as a Novel Catalyst","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicroalgae serve as a significant biomass feedstock with notable applications in biodiesel production. Their distinguished characteristics include high lipid content, effective mitigation of CO\u003csub\u003e2\u003c/sub\u003e emissions, rapid growth rates, and the ability to thrive on non-arable land for cultivation (Chhandama et al. 2021; Yu et al. 2024). These attributes make microalgae particularly advantageous compared to various other feedstocks. Furthermore, the cultivation of microalgae doesn't compete with food crops, presenting it as a compelling alternative to more commonly used feedstocks derived from food crops (Ryu et al. 2020). The benefits of using algae as a source of oil for biofuels extend to their impressive growth rates, characterized by a rapid biomass doubling time, typically ranging from 1 to 6 days. Additionally, microalgae have been found to produce 10\u0026ndash;20 times more oil per hectare per year compared to traditional oil crop plants (Neeti et al. 2023). Moreover, their high photosynthetic rate, approximately 6.9 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells/ml/h, and a carbon constituent of up to 50% in algae biomass further contribute to their appeal. This is coupled with a solar energy conversion capacity of about 4.5% (Rafa et al. 2021; Eldiehy et al. 2022).\u003c/p\u003e\u003cp\u003eThe process of harvesting microalgae comprises three main elements: biomass recovery, dewatering, and drying. Various techniques are available for this purpose, and the selection of a specific method hinges on the unique traits of the microalgae, such as their size, density, and the desired end products (Mathimani and Mallick 2018). Ziolkowska (2020), investigated microalgae harvesting can involve micro-screens in conjunction with centrifugation, flocculation, gravity sedimentation, filtration, screening, flotation, or electrophoresis techniques (Patnaik and Mallick 2021). Microalgae present a range of possibilities for producing various biofuels: biomethane via anaerobic digestion (Veerabadhran et al. 2021; Khaligh and Asoodeh 2022), biohydrogen through photobiological processes (Jokel et al. 2020; Torres et al. 2023), bioethanol via fermentation (Tse et al. 2021; Condor et al. 2022), liquid oil using thermal liquefaction (Galadima and Muraza 2018; Kostyukevich et al. 2021), and biodiesel through transesterification (Arachchige et al. 2021; Miyuranga et al. 2022; Miyuranga et al. 2023).\u003c/p\u003e\u003cp\u003eMicroalgae represent a highly prospective resource for sustainable biofuels in the future of renewable energy. Algae exhibit adaptability in utilizing various waste streams such as municipal wastewater, enabling the creation of diverse products suitable for various uses. These products include lipids, convertible into biodiesel, carbohydrates convertible into ethanol, and proteins potentially viable for consumption by both humans and animals (Bouyahya et al. 2024). Microalgae, hailed as a potential third-generation biodiesel source, pose challenges in strain selection due to significant variability in physiology, genetics, and metabolic potential among visually similar strains (Musa et al. 2019). These organisms are gaining attention as a biorefinery feedstock because of their carbon fixation, rapid growth, and bioactive compounds like lutein, known for benefiting human health, especially eye and brain function (Lee et al. 2021).\u003c/p\u003e\u003cp\u003eCurrent biodiesel production research relies heavily on nano-catalysts due to shortcomings in traditional homogeneous and heterogeneous catalysts. Homogeneous catalysts struggle with product isolation, demand substantial water quantities, and contribute to environmental pollution via liquid waste. On the other hand, heterogeneous catalysts often face challenges with mass transfer, are time-consuming, and lack efficiency. Studies indicate that these issues can be addressed by utilizing nano-catalysts, which offer heightened specific surface areas and superior catalytic abilities (Akubude et al. 2019). Various applications of nano-catalysts in biodiesel production from microalgae scrutinize hurdles and strategies for enhancing biodiesel yield from microalgae feedstock and explore the potential and uses of microalgae and nano-catalyzed transesterification to maintain its effectiveness as a viable processing method (Pavan et al. 2017).\u003c/p\u003e\u003cp\u003eBiodiesel, a liquid fuel comprising mono alkyl esters (methyl or ethyl) from long-chain fatty acids sourced from vegetable oils, animal fats, or algal oil (Galchar 2017), is produced by chemically converting animal fats or vegetable oils into a fuel suitable for diesel engines. Defined as a biofuel derived from renewable bio-lipids through transesterification, it's an environmentally friendly, non-toxic, and biodegradable fuel mainly obtained from plant oils and animal fats (Indhumathi et al. 2014; Sidra et al. 2016; Akubude and Nwaigwe 2016). This fuel, derived from lipid sources like oil crops, waste oil, microalgae, and animal fat, particularly highlights microalgae's potential due to its growth in various conditions without competing with food production or land resources (Goswami et al. 2020; Gaurav et al. 2024). In biodiesel production, the lipid content and fatty acid makeup of each feedstock significantly influence both yield and quality. Essential characteristics of biofuel, like cetane number, cold-flow properties, oxidative stability, and iodine value, rely on the structure of fatty esters, which, in turn, depend on carbon chain length, unsaturation level, and alcohol components within the ester (Qaria et al. 2017). Consequently, selecting microalgae species for biodiesel production requires high lipid productivity and an appropriate fatty acid composition. Biodiesel derived from saturated fats exhibits higher oxidative stability and a greater cetane rating but suffers from poor performance in lower temperatures, potentially gelling at ambient levels. Conversely, biodiesel from high-PUFA feedstocks boasts good cold-flow properties but tends to be prone to oxidation, leading to stability issues during extended storage (Chhandama et al. 2024). Studies propose that high-quality biodiesel should maintain relatively low levels of long-chain saturated fatty acid methyl esters (FAME) and polyunsaturated FAME to ensure satisfactory operability in cold temperatures and oxidative stability (Wenchao et al. 2020).\u003c/p\u003e\u003cp\u003eNano-catalytic processes play a significant role in all microalgae-based biodiesel applications. These advanced catalysts are pivotal in enhancing product quality and achieving ideal operational conditions. Nano-catalysts possess unique characteristics like high surface area, exceptional catalytic activity, resistance to saponification, and robustness (Velan et al. 2014). These traits make them preferable over other catalysts, such as heterogeneous catalysts, which encounter issues like mass transfer resistance, time consumption, rapid deactivation, and inefficiency (Akia et al. 2014). Due to their clear advantages, there's a growing focus on developing new types of nano-catalysts to replace conventional ones.\u003c/p\u003e\u003cp\u003eTraditionally, biodiesel production utilized homogeneous, heterogeneous, and enzymatic catalysts such as KOH, NaOH, zeolites, and lipases. However, current research trends favor nano-catalysts in transesterification due to their advantages over conventional catalysts. For instance, studies have highlighted the enhanced biodiesel yield, reaching up to 96% with CaO nanoparticles (Gupta and Agarwal 2016). Furthermore, combining catalysts, like CaO and MgO heterogenic nanocatalysts, significantly improved efficiency, yielding biodiesel at 98.95% from recycled cooking oil (Tahvildari et al. 2015). In algae-derived biodiesel production, the utilization of nano-catalytic transesterification processes led to impressive FAME yields of up to 99.0% with specific catalyst loadings and reaction conditions (Siow et al. 2016). Additionally, various nano-catalysts, including nano-magnetic solid base catalysts and nano-rods like ZnO, have shown promising prospects in biodiesel synthesis from different oil sources (Ali et. al. 2017).\u003c/p\u003e\u003cp\u003eMicroalgae, considered a third-generation biomass, offer advantages such as carbon fixation, swift growth, minimal land use, and high energy output compared to land-based biomass (Chen et. al. 2019). Yet, their abnormal growth patterns cause environmental issues, prompting research to convert them into biofuels or valuable products while addressing their impact on ecosystems (Lee et. al. 2019). Microalgae biodiesel, as a third-generation alternative, stands out due to its distinct properties compared to other fuel sources. It's renewable, environmentally friendly, and offers high energy output, potentially exceeding conventional crops in energy production per unit of land. Its production flexibility throughout the year, growth on undeveloped land without environmental impact, rapid growth with substantial oil content, and pesticide-free cultivation make it advantageous for biodiesel production (Rasul et. al. 2019). Biodiesel derived from microalgae presents multiple advantages over conventional resources due to its higher oil and biomass yields and its ability to grow on non-arable land. Microalgae thrive using industrial and municipal wastewaters, allowing for the production of biodiesel that could entirely substitute petroleum-based diesel. Reports suggest that microalgal biomass is rich in oil content, enabling the generation of diesel (Rasul et. al. 2019).\u003c/p\u003e\u003cp\u003eUtilizing Magnetic Cs/Al/Fe3O4 as a nano-catalyst in the transesterification of sunflower oil under optimal conditions resulted in a notable catalytic activity, yielding biodiesel at 94.8% (Haldar et. al. 2018). Obadiah et al. achieved a 90.8% biodiesel yield by transesterifying Pongamia oil with methanol, employing calcined Mg-Al hydrotalcite as a solid base catalyst (Feyzi et. al. 2013). Meanwhile, studies on sunflower oil transesterification using nano-MgO precipitated and deposited on TiO\u003csub\u003e2\u003c/sub\u003e support exhibited conversions of 84\u0026ndash;95% at higher temperatures compared to lower temperatures, indicating improved catalytic efficiency (Obadiah et. al. 2012). Researchers have also explored the use of various nano-crystalline MgO catalysts in nano-sheets to enhance biodiesel production from rapeseed and sunflower oils (Mguni et. al. 2012). Additionally, Hu et al. achieved over 95% yield of desired fatty acid methyl esters using nano-magnetic catalyst KF/CaO-Fe3O4 for stillingia oil biodiesel production under optimized conditions (Verziu et. al. 2008; Hu et. al. 2011). Numerous studies by different researchers have delved into the utilization of nano-catalysts to enhance biodiesel production, some focusing on microalgae as feedstock (Hossain et. al. 2019).\u003c/p\u003e\u003cp\u003eInnovative methods employing nanocatalysts for biodiesel production from microalgae involve extracting algae oil without cell disruption and further converting it into biodiesel. Lin developed a novel mechanism employing biocompatible, sponge-like mesoporous nanoparticles to harvest fatty acids from algal cultures without harming the cells (Hossain et. al. 2019). These nanoparticles selectively absorb oils from living algae without causing harm, by entrapping lipid molecules produced within the cell structure (Palaniappan 2017; Nizami and Rehan 2018). Catalysts like strontium and calcium oxides can be integrated into the nanoparticle pore structure, facilitating in-vitro transesterification of entrapped lipids (Ooi et. al. 2021). Researchers are currently exploring nano-porous carbons and other inorganic derivatives as potential adsorbents for biofuel separation.\u003c/p\u003e\u003cp\u003eNon-catalytic transesterification transforms triglycerides into biodiesel using alcohol in supercritical conditions, offering quick reaction times, simpler purification, and wider feedstock tolerance compared to catalytic methods (Kiran et. al. 2014; Eldiehy et al. 2022). However, it entails high operational costs, energy usage, and requires higher ratios of oil to alcohol, elevated temperatures, and pressures than catalytic processes (Pikula et. al. 2022). The conversion of microalgae oil into fatty acid methyl esters (FAME) through non-catalytic transesterification has been explored using various supercritical fluids like methanol, ethanol, dimethyl carbonate, and methyl acetate (Felix et. al. 2019). Studies have investigated optimal conditions for yielding FAME from Chlorella vulgaris and Chlorella sorokiniana CY-1 oils, achieving conversion yields in the range of 74.6\u0026ndash;92.8% under specific process conditions (Yew et. al. 2021).\u003c/p\u003e\u003cp\u003eShirazi et. al. (2017) investigated non-catalytic transesterification of Chlorella protothecoides oil, achieving a conversion increase from 19.3\u0026ndash;95.5% under specific conditions of 200 bar, 9:1 MeOH:oil molar ratio, and 300 to 400 ◦C temperatures. Liu et. al. (2015) utilized response surface methodology to optimize biodiesel production from Chlorella protothecoides microalgae oil, achieving 90.8% and 87.8% yields using supercritical MeOH and EtOH, respectively, under specific conditions. Moreover, non-catalytic transesterification of Schizochitrium limacinum microalgae resulted in over 90% conversion using MeOH, around 50% with DMC, and approximately 40% with MeOAc under varied temperatures and durations (Enamala et. al. 2018). Multiple research endeavors focused on generating biodiesel (BD) from wet microalgae biomass. Tsigie et. al. (2012) conducted in situ BD production from damp Chlorella vulgaris under subcritical conditions, yielding 0.29 g/g dry biomass. They also explored BD production from the same wet biomass through in situ lipid hydrolysis and supercritical transesterification with EtOH, achieving crude BD yields with extraction efficiencies ranging from 56\u0026ndash;100% (Levine et. al. 2010). Jazzar et. al. (2015) executed supercritical MeOH transesterification of identified native microalgae\u0026mdash;Chlorella sp. and Nannochloris sp. with 75% moisture content, obtaining maximum BD yields of 45.6 wt% and 21.8 wt%, respectively.\u003c/p\u003e\u003cp\u003eCatalytic transesterification is categorized into homogeneous and heterogeneous catalysis based on the catalyst type (Eldiehy et. al. 2022). Both alkaline (found in homogeneous and heterogeneous forms), acidic catalysts (in homogeneous and heterogeneous versions), and enzymatic catalysts find application in transesterification processes involving lipids derived from microalgae (Kim et. al. 2022). Alkaline catalysts, effective at low temperatures and pressures, are discouraged with high percentages of unsaturated free fatty acids (FFAs) due to potential soap formation when FFAs exceed 0.5 wt% (Mac\u0026iacute;as-S\u0026aacute;nchez et al. 2015). This soap formation reduces FAME yield, complicates separation from glycerol, and causes catalyst loss CaO and MgO serve as prevalent heterogeneous alkaline catalysts for their limited solubility in MeOH and high catalytic efficacy (Al-Zuhair et al. 2007). In the realm of transesterification with microalgae oil, Ma et. al. (2015) utilized a KOH/Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e catalyst for in situ transesterification of Chlorella vulgaris, yielding 89.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 wt% of biodiesel after a 5-hour reaction under optimized conditions (10 wt% KOH/Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e and 60\u0026deg;C) [68]. From the identical Chlorella vulgaris source, biodiesel (BD) production surged to 67.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2% and 71.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3% through in situ transesterification with microwave and ultrasound irradiation, respectively, using a KF/CaO catalyst over a 60-minute reaction period. The pinnacle BD yield of 93.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4% resulted from combined ultrasound and microwave irradiation during in situ transesterification of microalgae within 45 minutes (Ma et. al., 2015). Kazemifard et. al. (2019) utilized a magnetic KOH/Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e-Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanocatalyst for in situ transesterification with mixed microalgae biomass, achieving a 95.6% lipid-to-ester conversion in 6 hours at 65\u0026deg;C. In Nannochloropsis oculata microalgae transesterification, the CaMgO/Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e catalyst yielded 85.3% FAME at 60\u0026deg;C for 3 hours using 10 wt% and 75.2% with 20 wt%, while a 30.0% CaO/dolomite catalyst produced 90.0% FAME from Chlorella protothecoides at 65\u0026deg;C for 3 hours with a 6:1 MeOH/microalgae oil molar ratio (\u0026Ccedil;akırca et. al., 2019).\u003c/p\u003e\u003cp\u003eAcid-catalyzed transesterification generates FAMEs by protonating the ester's carbonyl group, suitable for high FFA content (\u0026gt;\u0026thinsp;1%) but demands longer reaction times, higher reagent amounts, temperatures, and pressures compared to alkaline processes, limiting commercial viability due to corrosiveness and cost (Pikula et. al., 2020). In lipid transesterification, heterogeneous acid catalysts like zirconium oxide (ZrO\u003csub\u003e2\u003c/sub\u003e), titanium oxide (TiO\u003csub\u003e2\u003c/sub\u003e), zeolites, and ion exchange resins are commonly used (Hidalgo et al., 2013). The study reveals their application in microalgae oil transesterification: Guldhe et. al. (2017) attained 98.3% BD conversion from Scenedesmus obliquus using a 15 wt% chromium\u0026ndash;aluminum catalyst at 80\u0026deg;C for 4 hours, while 94.6% BD conversion emerged from the same microalgal biomass employing 15 wt% tungstated zirconia (WO\u003csub\u003e3\u003c/sub\u003e/ZrO\u003csub\u003e2\u003c/sub\u003e) at 100\u0026deg;C in 3 hours. Furthermore, a phosphotungstic acid-modified zeolite imidazolate framework (HPW/ZIF67) achieved a 98.5% catalyst efficiency for Chlorella vulgaris BD production at 200\u0026deg;C within 90 minutes (Cheng et. al. 2021). Scenedesmus sp. achieved reduced BD conversions of 51.9% and 71.4% using 4 wt% of WO\u003csub\u003e3\u003c/sub\u003e/ZrO\u003csub\u003e2\u003c/sub\u003e through microwave and ultrasound-assisted in situ transesterification, respectively (Guldhe et. al. 2014). Loures et. al. (2018) attained a 98% BD yield using Nb\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e/SO\u003csub\u003e4\u003c/sub\u003e as a heterogeneous acid catalyst at 250\u0026deg;C for 4 hours in a pressurized stainless-steel reactor. Another investigation involved a carbon-based catalyst (DMB), derived from carbonizing de-oiled Tetradesmus obliquus KMC24 microalgae biomass and sulfonating it, showing optimal conditions for a maximum FAME yield of 94.2%: a MeOH/oil molar ratio of 11:1, 4 wt% catalyst concentration, 70\u0026deg;C temperature, and 8 hours reaction time (Roy and Mohanty 2021).\u003c/p\u003e\u003cp\u003eEnzymatic transesterification using lipase eliminates chemical catalyst downsides, offering lower energy, moderate conditions, and ease of recovery but faces challenges like costly enzymes, decreased activity over time, incomplete reactions, and complex glycerol recovery, hindering large-scale viability (Fazal et. al. 2018). Enzymatic transesterification relies on factors like temperature, alcohol-to-oil ratio, alcohol choice, solvents, water content, pH, and enzyme quantity. While many lipases work below 70\u0026deg;C, the ideal temperature varies based on ratios, solvents, and immobilization. A slight excess of alcohol (3\u0026thinsp;\u0026minus;\u0026thinsp;5:1) aids in the process; however, MeOH and EtOH, though cost-effective, can denature lipases, requiring organic solvents to boost alcohol solubility and shield enzymes. Optimal conditions for lipases include 10\u0026ndash;20% water content, pH levels between 7.5 and 8.5, and an enzyme concentration of 0.7 mg/mL for maximum reaction efficiency (Hossain et. al. 2020). Navarro-L\u0026oacute;pez et. al. (2016) explored FAME production from wet Nannchloropsis gaditana biomass through direct enzymatic transesterification using Novozyme 435 lipase, achieving a 99.5% FAME conversion over 56 hours by adding MeOH in 3 stages and t-butanol to counter lipase deactivation. Tian et. al. (2016) devised a novel process for BD conversion from Schizochytrium sp. oil, obtaining a 95.0% FAME yield through the combined use of lipase NS81006 and Novozym435. Taher et. al. (2014) investigated enzymatic BD production with immobilized Novozyme\u0026reg;435 under supercritical CO\u003csub\u003e2\u003c/sub\u003e (SC-CO\u003csub\u003e2\u003c/sub\u003e), reaching an 80.0% FAME yield at 47\u0026deg;C, 200 bar, 35% enzyme loading, and a 9:1 MeOH to lipid molar ratio within a 4-hour batch reaction. Novozyme 435 (N435), an immobilized lipase from Candida antarctica, demonstrated 99.1% conversion efficiency from Nannochloropsis oceanica IMET 1 oil in 4 hours at 25\u0026deg;C, a 1:12 oil to MeOH molar ratio, and a 20% catalyst concentration (Wang et. al. 2014).\u003c/p\u003e\n\u003ch3\u003eBioenergy in Jordan\u003c/h3\u003e\n\u003cp\u003eIn 2021, Jordan had a population of 10,269,022, experiencing a yearly population growth of 0.6% (Monisha-Miriam et al. 2021). With an energy consumption of 8166 tons of oil equivalent in the same year, Jordan is recognized as one of the nations with high energy consumption (Addustour 2022). The vulnerability of Jordan's energy sector to external shocks, such as price fluctuations, underscores the necessity for resilience in this industry due to its significant impact on the country's economy. Jordan annually generates 2.7\u0026nbsp;million tons of municipal solid waste, posing environmental challenges rather than benefiting the energy industry or economy. Biomass contributes only 0.1% to the country's energy needs, primarily from wood sources like logs, chips, bark, and sawdust, comprising 44% of produced energy (Myyas et. al. 2023). The nation holds significant potential for future biomass production, with animal manure accounting for 96% of biomass, followed by olive trees and pomace at 1.8%. This study assesses Jordan's waste's theoretical energy potential and explores its biomass potential, envisioning the country as a key bioenergy producer through waste and proposing methods to evaluate biogas potential from common substrates like food and agricultural waste in Jordanian communities. At present, more than 90% of the waste accumulates in unsanitary landfills and dumpsites nationwide due to extensive waste production and limited disposal options. Uncontrolled waste leachate infiltrates the soil, polluting the water sources. Open landfills not only attract disease-carrying pests but also pose significant health risks and hazards to the public's well-being. Anticipated population growth suggests a projected annual increase of 3% in waste generation, encompassing hazardous waste and municipal solid waste (MSW) (MoE 2022).\u003c/p\u003e\u003cp\u003eJordan is taking steps to address its environmental and economic concerns by initiating a biomechanical waste treatment endeavor. This project intends to set up a mechanical-biological facility specifically for processing organic waste, starting with a capacity of 239 tons per day. The primary goals include waste recycling, energy production, and fertilizer creation (Da\u0026rsquo;aja 2022). By annually burning roughly 19\u0026nbsp;million cubic meters of biogas, this initiative aims to cut emissions by 175,000 tons, equivalent to carbon dioxide (Amer et. al. 2021). Recent focus has shifted to alternative energy sources in Jordan, such as biofuel derived from agricultural waste. Initiatives like biogas plants and Jatropha cultivation in arid regions exhibit potential but lack comprehensive economic analysis and detailed information on biofuel output (Amer et. al. 2021). Jordan, without domestic oil production, heavily relies on imported oil and natural gas to fulfill its energy needs, with only 4% met by local natural gas, straining the economy as energy imports consume more than a quarter of its GDP. Despite efforts to adopt solar, wind, biogas, and hydro energy, the biomass sector remains marginal, generating just 3.5MW, a fraction of the overall energy requirements (Saeedan 2011). Jordan has been actively exploring bioenergy production, particularly biogas and biodiesel, aiming to diversify its energy sources and reduce reliance on imports. The research in Jordan on biogas and biodiesel production aims to address the country's energy needs while considering environmental sustainability and utilizing locally available resources.\u003c/p\u003e\u003cp\u003eAs far as the authors are aware, this approach has not been explored with marine microalgae. Therefore, the main objective of this work was to investigate the use of calcium methoxide as a catalyst for transesterification in the production of biodiesel from marine microalgae, representing a novel aspect of this research.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch3\u003eCultivation of Microalgae\u003c/h3\u003e\n\u003cp\u003eThree varieties of marine microalgae were obtained from the Faculty of Plant Science at Tanta University in Egypt. Creating microalgal biomass proves more financially demanding and technologically intricate compared to growing crops, as these microorganisms rely on light, CO\u003csub\u003e2\u003c/sub\u003e, water, and inorganic salts for their photosynthesis process. The study utilized straightforward photobioreactors, focusing on generating biodiesel from these marine microalgae for subsequent examinations. Beginning with the cultivation of Nannochloropsis, Tetraselmis, and Isochrysis in separate 300 ml containers, each equipped with light and CO\u003csub\u003e2\u003c/sub\u003e sources achieved by aerating atmospheric air into the setup. The controlled temperature ranged between 15\u0026deg;C to 25\u0026deg;C, while the growth medium supplied essential nutrients like KNO\u003csub\u003e3\u003c/sub\u003e (2 ml), NAH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e.H\u003csub\u003e2\u003c/sub\u003eO (2ml), FECL\u003csub\u003e3\u003c/sub\u003e.6H\u003csub\u003e2\u003c/sub\u003eO (3ml), and trace metals (2ml). Microalgae in a period of 4 days is shown in Figure 1. Nutrients used to feed microalgae is shown illustrated the four-day growth progression is shown in Figure 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe visual appearance of microalgae cultures provides a reliable indication of their growth stage, with noticeable changes in color and density observed as they progress from the lag phase to exponential growth, is shown in Figure 3. After eight days, the microalgae displayed a dark green color, suggesting they were approaching their stable phase (Figure 3a). Allowing them to continue growing for an additional four days ensured the completion of their growth cycle. By day 16, the cultivation exhibited significant readiness for further growth (Figure 3b). Throughout this phase, 1L of seawater and nutrients were introduced into each container every three days. Around day 38, larger containers replaced the small ones due to the cultivation reaching a volume of approximately 20L (Figure 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHarvesting methods\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe microalgae biomass was gathered through three methods: employing filter paper, centrifugation, and exposure to sunlight, all detailed in Figure 5. Following cultivation, the microalgae underwent centrifugation for 1 minute at a speed of 10,000 rotations per minute (rpm). Subsequently, a pipette was used to extract most of the water, leaving behind solely the microalgae biomass within the tube as depicted in Figure 6. The microalgae biomass underwent a three-day drying process within a laboratory setting (Figure 7). Following this, the dried algae biomass was weighed and prepared for oil extraction. Grinding was carried out using a pestle and mortar, utilizing specific grindery equipment as illustrated in Figure 8.\u003c/p\u003e\n\u003cp\u003eThe efficiency of photobioreactors hinges on various pivotal factors. Firstly, the availability of adequate light profoundly influences photosynthesis within microalgae. Secondly, the uptake of carbon dioxide significantly impacts their growth and productivity. Moreover, the quantity of oxygen generated during this process is crucial for the reactor\u0026apos;s efficacy. Efficient gas transfer mechanisms are imperative to maintain optimal conditions within the reactor. Temperature fluctuations can notably affect growth rates and overall performance. Consistent mixing rates within the reactor are essential for uniform distribution of nutrients and gases. The pH level of the medium significantly influences the microalgae\u0026apos;s physiological processes. Lastly, meeting specific nutrient requirements is vital for sustained growth and productivity within the photobioreactor. These factors collectively determine the effectiveness and output of photobioreactors employed in microalgae cultivation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOil extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dried algae mass yielded significant amounts: 643 grams of Nannochloropsis, 1.3 kilograms of Tetraselmis, and 860 grams of Isochrysis. Subsequently, 80 grams of each type of ground microalgae were carefully placed into the thimble within the Soxhlet extractor, featuring a condensation system as shown in Figure 9. Within the distillation flask, hexane, the extraction agent, was heated to reflux, and its vapors condensed in the reflux condenser before descending into the thimble\u0026apos;s chamber housing the substance for extraction. Gradually, the warm solvent filled the compartment, dissolving some of the material within it. As the Soxhlet chamber approached fullness, an automatic siphon sidearm emptied it, returning the solvent to the distillation flask. This cyclic process was repeated multiple times to accumulate the extracted material within the solvent in the distillation flask. The mantle heater was set to approximately 60\u0026deg;C, closely aligning with the hexane evaporation temperature of 64\u0026deg;C as indicated in Figure 10.\u003c/p\u003e\n\u003cp\u003eA 1000 mL three-necked round-bottom flask served as the reactor in this setup. Positioned in a heating mantle, the flask maintained a steady temperature of +20 \u0026deg;C. Hexane was specifically chosen as the solvent due to its favorable characteristics. For every 80 grams of microalgae, 270 ml of hexane was utilized, resulting in the extraction of 30 ml of Isochrysis oil, 45 ml of Nannochloropsis oil, and 20 ml of Tetraselmis oil. The oil extraction process lasted for 8 hours, following which the hexane was removed using a Rotary Evaporator. Rotary evaporators, commonly known as \u0026quot;rotavaps\u0026quot; as depicted in Figure 11, are employed to remove solvents like hexane from reaction mixtures. To prevent the solvent from freezing during the evaporation process, the water bath in the rotary evaporator can be heated in a metal container or a crystallization dish. Microalgae oil after hexane evaporated (A) Nanno-, (B)Tetra-, (C) Iso-. Biodiesel production is shown in Figure 12. For further purification, the oil yield was subjected to a 2-hour period on a hot plate.\u003c/p\u003e\n\u003ch4\u003eTitration\u0026nbsp;\u003c/h4\u003e\n\u003cp\u003eA solution for titration was prepared by dissolving 1 gram of potassium hydroxide in 1 liter of distilled water. To initiate the titration process, 1 mL of microalgal oil was combined with 10 mL of ethanol in a small beaker and thoroughly mixed. Two drops of phenolphthalein were added to the mixture as an indicator as shown in\u0026nbsp;Figure 13. Gradually, using a burette, the potassium hydroxide (KOH) solution was slowly added drop by drop to the mixture until it turned pink. The reaction outcomes indicated that Nannochloropsis had a free fatty acid (FFA) content exceeding 5%, while Tetraselmis and Isochrysis possessed FFA levels below 5%.\u003c/p\u003e\n\u003cp\u003eThe acid value (AV), represented as (mg KOH/g oil), is calculated using Equation (Thein et. al. 2019).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cimg width=\"253\" height=\"30\" src=\"data:image/png;base64,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\" alt=\"image\"\u003e\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;(1)\u003c/p\u003e\n\u003cp\u003eIt\u0026apos;s noteworthy that the average value of free fatty acid in the microalgae oil wasn\u0026apos;t determined due to the diverse species of microalgae and the variation in fatty acid percentages based on species and growth conditions.\u003c/p\u003e\n\u003ch4\u003eEsterification\u0026nbsp;\u003c/h4\u003e\n\u003cp\u003eEsterification stands as the method of choice for removing both glycerol and fatty acids from vegetable oil, crucial for significantly reducing its viscosity. Widely regarded as the primary technique in this regard, it involves triglycerides reacting with three alcohol molecules in the presence of a catalyst, resulting in a blend of fatty acids, alkyl ester, and glycerol (Akubude et. al. 2019).\u0026nbsp;Figure 14\u0026nbsp;shows \u0026nbsp;microalgae oil produced by acid-catalyzed esterification process demands a higher amount of acid and methanol. Within a 500 mL three-neck round-bottom flask, sulfuric acid served as the catalyst while methanol acted as the reactant. Temperature measurement was facilitated by a thermometer fitted into one neck, while a water-cooled condenser, aimed at curbing methanol evaporation, connected to another neck. The third neck served for adding chemicals and collecting samples. Positioned atop sand on a hotplate, the reactor underwent heating. The prescribed ratio necessitated adding 2.25 g of methanol and 0.05 g of sulfuric acid for each gram of free fatty acid present in the oil. Prior to the reaction, methanol and H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e were pre-mixed, and the oil was preheated to 60\u0026deg;C before their addition. Stirring ensued at 60\u0026deg;C for at least two hours. Once the two-hour mark passed, the mixture settled, with the methanol-water combination rising to the top of the separator funnel and the oil layer resting at the bottom. Assessment revealed the new free fatty acid content to be less than 0.5% compared to the original oil composition, indicating the success of the process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransesterification\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIf the free fatty acid content remains below 0.5%, transesterification can be directly performed. Recent research by Akubude et al. (2016) highlights the increasing use of nano-catalysts in transesterification due to their advantages over traditional homogeneous and heterogeneous catalysts. To evaluate the reusability of the snail shell-derived catalyst, experiments were conducted, and the transesterification reaction pathway is illustrated in Figure 15.\u003c/p\u003e\n\u003cp\u003eIn this study, we employed calcium methoxide as a catalyst to sustain the reaction temperature and mitigate potential decreases. To ensure seamless integration with methanol and to minimize temperature fluctuations, the calcium methoxide was carefully introduced into the pre-warmed oil at 60\u0026deg;C. Figure 16 illustrates the setup and conditions used during this initial phase of the reaction. Given that alcohol and oils typically don\u0026apos;t mix at room temperature, the reaction mixture was consistently heated to 80\u0026deg;C and stirred at 500 rpm to enhance mass transfer between the immiscible phases. Once the mixture reached 80\u0026deg;C, it was allowed to stand for a duration of 3 hours. The ratio employed was 3 ml of methanol to 1 ml of oil, as shown in Figure 17.\u003c/p\u003e\n\u003cp\u003eAfter the reaction, the oil/methoxide mixture was transferred to a separatory funnel and allowed to settle for 48 hours to separate the glycerol waste. Once phase separation was complete, the glycerol layer was carefully drained from the bottom of the funnel. The upper layer, containing the crude biodiesel, was then returned to a clean beaker for further processing, following the procedure outlined in Figure 18.\u003c/p\u003e\n\u003ch4\u003eWashing\u0026nbsp;\u003c/h4\u003e\n\u003cp\u003eTo purify the crude biodiesel, warm distilled water was added to the separator funnel containing the biodiesel. The mixture was gently agitated to allow the water and biodiesel to combine. Allowing a two-day settling period enabled the separation of water from the biodiesel. The water was then drained, and this washing process was repeated an additional four to six times, as detailed in Figure 19. This series of washes serves to remove undesired components such as excess methanol or any remaining water present in the biodiesel.\u003c/p\u003e\n\u003ch2\u003ePhysical and chemical analysis\u003c/h2\u003e\n\u003cp\u003eThe physical and chemical characteristics of both the oil and biodiesel samples were assessed at Al Hussein Bin Talal University. The physical analyses included measurements of density, cloud point, flash point, pH, and viscosity at 40\u0026deg;C. The flash point results for the biodiesel samples derived from \u003cem\u003eNannochloropsis\u003c/em\u003e, \u003cem\u003eTetraselmis\u003c/em\u003e, and \u003cem\u003eIsochrysis\u003c/em\u003e microalgae are illustrated in Figure 20, while the cloud point characteristics of the same samples are presented in Figure 21.\u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eMicroalgae oil extraction and biodiesel production\u003c/h2\u003e\u003cp\u003eThe experimental results in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reveal critical insights into the oil extraction and biodiesel production potential of three distinct microalgae species\u0026mdash;Nannochloropsis, Tetraselmis, and Isochrysis\u0026mdash;when processed with calcium methoxide catalyst. The oil yields obtained (45.01 mL for Nannochloropsis, 30.04 mL for Isochrysis, and 20.00 mL for Tetraselmis) are consistent with known physiological differences among these species, where Nannochloropsis is well-documented for its high lipid accumulation capacity, often exceeding 30\u0026ndash;50% of dry biomass under optimized cultivation conditions (Hu et al. 2008). This high oil content, combined with efficient extraction, renders it the most promising candidate for biodiesel feedstock among the three studied species.\u003c/p\u003e\u003cp\u003eThe calcium methoxide catalyst employed demonstrated excellent catalytic activity, producing biodiesel yields exceeding 90% for all species, with Nannochloropsis achieving the highest average of 96.06%. This is indicative of an effective transesterification reaction facilitated by calcium methoxide, which is increasingly recognized for its high catalytic efficiency, recyclability, and environmental compatibility (Mardhiah et al. 2017). Compared to traditional homogeneous catalysts such as sodium hydroxide or potassium hydroxide, calcium methoxide offers reduced saponification, easier separation, and lower wastewater generation, key advantages for sustainable biodiesel production (Dalvand and Mahdavian 2018).\u003c/p\u003e\u003cp\u003eThe biodiesel yield differences among species, particularly the lower yield for Isochrysis (90.07%), may be attributed to the unique fatty acid profiles of these microalgae. Isochrysis is known to contain significant amounts of long-chain polyunsaturated fatty acids (PUFAs) like docosahexaenoic acid (DHA), which can complicate the transesterification process due to their sensitivity to oxidation and tendency to form partial glycerides or polymerized products (Avhad and Marchetti 2015). These fatty acid characteristics may contribute to slightly reduced conversion efficiency compared to species with more saturated or monounsaturated fatty acids, such as Nannochloropsis.\u003c/p\u003e\u003cp\u003eThe consistency of oil yield and biodiesel production over the ten runs with minimal variation underscores the robustness of the extraction and transesterification processes under the applied experimental conditions. This reproducibility is essential for scaling up the process, ensuring reliable yields for commercial biodiesel production. Furthermore, the high biodiesel yield demonstrates that calcium methoxide is an effective catalyst for microalgal oils, which often contain impurities such as chlorophylls, carotenoids, and other lipophilic compounds that can inhibit conventional catalysts (Bohloulia and Mahdavian 2019).\u003c/p\u003e\u003cp\u003eWhen benchmarked against other microalgal biodiesel studies, the oil yields and biodiesel conversion efficiencies reported here compare favorably. For example, Chlorella vulgaris typically yields about 30\u0026ndash;40 mL oil per 100 g biomass with biodiesel yields around 85\u0026ndash;92% using sodium methoxide (Mardhiah et al. 2017), and Scenedesmus obliquus yields approximately 35 mL oil per 100 g with 88\u0026ndash;94% biodiesel yield using potassium hydroxide catalysts (Baskar and Aiswarya 2016). The higher oil yields and competitive biodiesel conversion efficiencies using calcium methoxide in this study suggest the catalyst\u0026rsquo;s superiority and potential for industrial biodiesel production, especially considering its heterogeneous nature that allows for catalyst recovery and reuse, thus lowering production costs and environmental impact (Doh et al. 2021).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOil Yield (mL) from 80 g Microalgae and Biodiesel Yield (%) Enhanced by Calcium Methoxide Catalyst\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRun #\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eOil Yield (mL)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eBiodiesel extraction (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eNannochloropsis\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eTetraselmis\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eIsochrysis\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eNannochloropsis\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eTetraselmis\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eIsochrysis\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e89.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e95.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e92.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e89.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e95.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e92.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e93.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e45.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e20.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e30.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e96.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e93.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003ePhysical properties of microalgal oil\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the comparison of physical properties of microalgal oil and different vegetable oils. The results indicated that the higher viscosity indicates thicker oil, which might affect its ease of use in certain applications. Lower viscosity oils like Tetra microalgae oil (13.3 cSt at 40\u0026deg;C) could be more favorable for some purposes requiring smoother flow. Tetra microalgae oil exhibits the lowest viscosity among the microalgae oils listed, with a viscosity of 13.3 cSt at 40\u0026deg;C. The kinematic viscosity indicates the resistance of the oil to flow at 40\u0026deg;C. Among the three, Tetra microalgae oil has the lowest viscosity, suggesting it flows more easily compared to Iso and Nanno microalgae oils. This refers to the oil's resistance to flow at a specific temperature (40\u0026deg;C). However, when compared to various vegetable oils, it falls within the lower to mid-range in terms of viscosity. For instance, it's notably lower than Jatropha, Karanja, Neem, Palm, Peanut, and Rapeseed oils but slightly higher than Linseed and Rice Bran oils. Iso microalgae oil, with a viscosity of 25.2 cSt at 40\u0026deg;C, ranks slightly higher in viscosity compared to Tetra but still falls below the viscosities of Jatropha, Karanja, Neem, Palm, and Rapeseed oils. It aligns more closely with Thumba, Sunflower, Soybeans, and Cotton Seed oils. Nanno microalgae oil presents the highest viscosity among the microalgae oils, standing at 39.1 cSt at 40\u0026deg;C. It surpasses the viscosities of most other vegetable oils in the table except for Jatropha and Karanja oils.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of physical properties of microalgal oil and different vegetable oils (Karmakar et. al. 2017).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOil\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKinematic Viscosity\u003c/p\u003e\u003cp\u003e(cSt 40\u0026deg; C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCloud point\u003c/p\u003e\u003cp\u003e(\u0026deg;C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFlash point\u003c/p\u003e\u003cp\u003e(\u0026deg;C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDensity\u003c/p\u003e\u003cp\u003e(kg/m3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePour point\u003c/p\u003e\u003cp\u003e(\u0026deg;C)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTetra microalgae oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIso microalgae oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNanno microalgae oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHandal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThumba\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJatropha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKaranja\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRapeseed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e911\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-31.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSunflower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e916\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoybeans\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e914\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoconut\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCotton Seed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e914\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRice Bran\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeanut\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-6.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLinseed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e923\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePalm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e918\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCorn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e277\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e909\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBabassu\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiesel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe cloud point of microalgal oil and different vegetable oils is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The cloud point is the temperature at which the oil starts to form cloudy or solid particles. The results revealed that the lower cloud points like those of Tetra (-3.3\u0026deg;C) and Nanno (-4\u0026deg;C) microalgae oils imply better performance in colder conditions without solidifying. The cloud point is crucial for applications in colder environments. All three oils have relatively low cloud points, indicating they remain liquid at low temperatures. Tetra and Nanno microalgae oils have slightly lower cloud points compared to Iso microalgae oil. Tetra microalgae oil exhibits a cloud point of -3.3\u0026deg;C, which is similar to the cloud points of Rapeseed and Soybeans oils. It is lower than most other oils listed, indicating better low-temperature performance. Iso microalgae oil displays a cloud point of -1.2\u0026deg;C, indicating relatively better low-temperature properties than Tetra microalgae oil but higher than several other oils such as Rapeseed, Cotton Seed, and Linseed oils. Nanno microalgae oil shows a cloud point of -4\u0026deg;C, presenting better low-temperature performance than Tetra and Iso microalgae oils and comparable to Rapeseed and Soybeans oils.\u003c/p\u003e\u003cp\u003eThe flash point of microalgal oil and different vegetable oils is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The flash point of microalgae oils 201\u0026deg;C for Iso, 225\u0026deg;C for Tetra, and 274\u0026deg;C for Nanno\u0026mdash;holds significance in assessing their safety and potential applications. Higher flash points generally indicate a safer oil in terms of handling, transportation, and storage, as they are less prone to ignite under specific conditions. Nanno microalgae oil stands out with the highest flash point, making it potentially the safest among the three for use in environments where high temperatures or potential ignition sources are concerns. Tetra microalgae oil follows with a slightly lower flash point but still exhibits a considerably safe threshold. Iso microalgae oil, despite having the lowest flash point among the three, still falls within a range considered safe for many applications. Understanding these flash point differences aids in selecting suitable oils for industries like manufacturing, where safety protocols demand oils with higher ignition resistance. However, all three oils demonstrate relatively safe flash points, ensuring their viability for various industrial and commercial applications where safety and stability are essential considerations. Iso microalgae oil has a flash point of 201\u0026deg;C, which is lower than Jatropha, Karanja, Neem, Palm, Peanut, and Rapeseed oils but similar to Sunflower and Soybeans oils. Iso microalgae oil exhibits a flash point of 201\u0026deg;C, aligning with Tetra microalgae oil and sharing similarities with Sunflower and Soybeans oils. Nanno microalgae oil presents a flash point of 274\u0026deg;C, surpassing the flash points of most oils in the table, indicating higher resistance to ignition compared to the majority of vegetable oils listed.\u003c/p\u003e\u003cp\u003eThe flash point of a fuel, indicating its susceptibility to ignition upon exposure to a spark or flame, was determined using the Pensky Martens Flash Point apparatus. In this context, the used Nanno biodiesel oil displayed a flash point of 100.5\u0026deg;C, while Tetra biodiesel oil recorded 99.9\u0026deg;C and Iso biodiesel oil measured 99.1\u0026deg;C. These values for the microalgal oils were higher than that of conventional diesel (66\u0026deg;C), Handal (50\u0026deg;C), and Thumba (66\u0026deg;C). However, they remained lower than Jatropha biodiesel (175\u0026deg;C), Sunflower biodiesel (183\u0026deg;C), and Neem biodiesel (180\u0026deg;C). Remarkably, the used Nanno oil showcased an exceptionally high flash point of 274\u0026deg;C, far surpassing diesel fuel's flash point at 66\u0026deg;C. The flash point of Handal biodiesel stood at 50\u0026deg;C, lower than Thumba (66\u0026deg;C), Jatropha (175\u0026deg;C), Karanja (187\u0026deg;C), Iso (99.1\u0026deg;C), Nanno (100.5\u0026deg;C), and Neem seed oil (180\u0026deg;C). The presence of chemically bound oxygen in vegetable oils tends to reduce their heating values by approximately 10%. It's important to note that while the flash point is a critical parameter for safety during storage and handling, it doesn't directly impact engine performance (Sidib\u0026eacute; et. al. 2010). Moreover, the flash point is often utilized as a regulatory criterion for categorizing fuels during transport and storage, and these standards vary across different regions. Harmonizing these standards would likely necessitate corresponding alignment in regulations.\u003c/p\u003e\u003cp\u003eThe density of microalgal oil and different vegetable oils is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Density represents the mass per unit volume of the oil. Nanno microalgae oil has the highest density, which might impact its behavior in various applications, while Tetra microalgae oil has the lowest density among the three. The results exhibited that the nanno microalgae oil has the highest density (915 kg/m\u0026sup3;), which may impact its behavior in various applications. Tetra, Iso, and Nanno microalgae oils showcase varying densities compared to the array of vegetable oils, indicating unique characteristics within this spectrum of properties. Overall, Tetra, Iso, and Nanno microalgae oils exhibit diverse physical properties in comparison to the range of vegetable oils listed, showcasing variations in viscosity, low-temperature performance, ignition resistance, density, and pour points.\u003c/p\u003e\u003cp\u003eThe pour point of microalgal oil and different vegetable oils is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This is the temperature at which the oil begins to solidify or lose its flow characteristics. Lower pour points like those of Tetra (-10\u0026deg;C) and Nanno (-17\u0026deg;C) microalgae oils signify better performance in colder environments. The pour point signifies the lowest temperature at which the oil remains fluid. Tetra and Nanno microalgae oils have lower pour points compared to Iso microalgae oil, indicating better performance in colder conditions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eChemical Properties of microalgal oil\u003c/h2\u003e\u003cp\u003eThe chemical properties of fatty acids found in microalgal oil, compared with various vegetable oils, are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The outcomes highlight specific compositions of fatty acid methyl esters (FAME). In Tetra microalgae oil, the dominant fatty acid is Linoleic acid (C18:2) at 50.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 wt. %, followed by Oleic acid (C18:1) at 38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 wt. %, Stearic acid (C18:0) at 34.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 wt. %, Palmitoleic acid (C16:1) at 2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 wt. %, Palmitic acid (C16:0) at 0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 wt. %, and Linolenic acid (C18:3) at 0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 wt. %. In ISO sp microalgae oil, Oleic acid (C18:1) dominates at 60.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 wt. %, while Palmitoleic acid (C16:1) registers the lowest percentage at 0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 wt. %. Meanwhile, in NANNO sp, the highest value is found in Oleic acid (C18:1) at 54.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 wt. %, whereas Linoleic acid (C18:2) is recorded at 0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 wt. %.\u003c/p\u003e\u003cp\u003eThese findings differ significantly from the composition observed in biodiesel derived from Palm oil, where Palmitic acid (C16:0) holds the highest percentage (45.60% and 38.50%), followed by Linoleic acid (C18:2) at 10.50%, Stearic acid (C18:0) at 3.80%, and Linolenic acid (C18:3) at 0.10%.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents a comparative analysis of fatty acid distribution in microalgae oil and three types of vegetable oil: soybean, palm, and sunflower. In microalgae oil, the dominant fatty acids are palmitic (C16:0), stearic (C18:0), and oleic (C18:1), with percentages of approximately 3.12%, 45.82%, and 16.52% respectively. It also contains smaller amounts of palmitoleic (C16:1), linoleic (C18:2), and linolenic (C18:3) acids at 1.22%, 7.54%, and negligible amounts, respectively. Soybean oil, on the other hand, is characterized by higher proportions of linoleic acid (C18:2) at 55.40%, followed by oleic acid (C18:1) at 25.20%. Palmitic acid (C16:0) and stearic acid (C18:0) constitute 11.2% and 2.90% of the fatty acid composition, respectively. Palm oil shows a significantly higher percentage of palmitic acid (C16:0) at 45.60%, with oleic acid (C18:1) and stearic acid (C18:0) constituting 38.50% and 3.80%, respectively. Sunflower oil displays a high content of linoleic acid (C18:2) at 51.30%, followed by oleic acid (C18:1) at 38.70%. Palmitic acid (C16:0) and stearic acid (C18:0) are present in smaller amounts at 6.70% and 2.90%, respectively. It can be concluded that microalgae oil exhibits a unique fatty acid profile compared to traditional vegetable oils, with potential implications for nutritional and industrial applications.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFatty acid distribution in microalgae oil and three types of vegetable oil (Batista et. al. 2018).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMicroalgae oil\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePalmitic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePalmitoleic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStearic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOleic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003elinoleic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003elinolenic\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC 16:0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eC 16:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC 18:0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC 18:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eC 18:2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eC 18:3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTetra\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e50.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIso\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNannochloris\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emicroalgae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esoybean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e55.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePalm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esunflower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e51.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003ePhysical Properties of biodiesel production\u003c/h2\u003e\u003cp\u003eThe physical of microalgae biodiesel are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The viscosity at 40\u0026deg;C, which indicates the fluidity of the biodiesel, was measured for three microalgae species. Nanno microalgae biodiesel exhibited a viscosity of 6.2 cSt, Tetra microalgae biodiesel had a viscosity of 7.976 cSt, and Iso microalgae biodiesel had a viscosity of 7.6 cSt. These values provide insights into the flow characteristics of the biodiesel derived from different microalgae species. Viscosity refers to the resistance of a fluid to flow. Lower viscosity biodiesel flows more easily and efficiently through fuel systems, enhancing engine performance. In the case of microalgae-derived biodiesel, varying viscosities are observed across different strains (Nanno, Tetra, Iso). Lower viscosity, as seen in Nanno biodiesel (6.2 cSt), can contribute to improved fuel atomization and combustion efficiency, potentially leading to reduced emissions, including CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\u003cp\u003eThe flash point, which denotes the lowest temperature at which the biodiesel can ignite, was determined for each microalgae biodiesel. Nanno microalgae biodiesel exhibited a flash point of 100.5\u0026deg;C, Tetra microalgae biodiesel had a flash point of 99.9\u0026deg;C, and Iso microalgae biodiesel had a flash point of 99.1\u0026deg;C. These values indicate the safety aspects of handling and storing microalgae biodiesel. The flash point is the temperature at which vapors produced by a fuel can ignite when exposed to an ignition source. Higher flash point values indicate greater safety and reduced fire hazards during handling and storage. The microalgae-derived biodiesels (Nanno, Tetra, Iso) exhibit high flash points (above 99\u0026deg;C), ensuring safer operation. This characteristic is crucial for mitigating risks during transportation and storage, thereby minimizing potential environmental impacts such as spills or accidents that could result in CO\u003csub\u003e2\u003c/sub\u003e emissions.\u003c/p\u003e\u003cp\u003eThe cloud point, which represents the temperature at which the biodiesel begins to solidify and form a cloudy appearance, was measured for the microalgae biodiesel samples. Nanno microalgae biodiesel displayed a cloud point of -39\u0026deg;C, Tetra microalgae biodiesel had a cloud point of -40.8\u0026deg;C, and Iso microalgae biodiesel had a cloud point of -45\u0026deg;C. Lower cloud point values indicate better low-temperature performance and reduced chances of fuel gelling or clogging fuel filters in cold environments. Cloud point refers to the temperature at which solid crystals begin to form in a fuel, causing it to become cloudy and potentially impacting its flow properties. Lower cloud points are desirable, especially in cold climates, as they ensure the fuel remains fluid and operable at lower temperatures. Microalgae-derived biodiesels demonstrate relatively low cloud points (e.g., Nanno: -39\u0026deg;C), indicating good cold flow properties. Enhanced cold flow characteristics can lead to improved fuel efficiency and reduced CO\u003csub\u003e2\u003c/sub\u003e emissions by facilitating engine start-up and operation in colder environments.\u003c/p\u003e\u003cp\u003epH is a measure of the acidity or alkalinity of a substance. While biodiesel is generally considered to have a neutral pH, slight variations may occur depending on the feedstock and production process. Microalgae-derived biodiesels (Nanno, Tetra, Iso) exhibit pH values within a relatively neutral range (6.8 to 7.71). Maintaining a neutral pH is important for ensuring compatibility with engine materials and minimizing corrosion or degradation, which can affect engine performance and emissions. By producing biodiesel with stable pH levels, the potential for CO\u003csub\u003e2\u003c/sub\u003e emissions related to engine maintenance or replacement due to corrosion can be minimized, contributing to overall CO\u003csub\u003e2\u003c/sub\u003e reduction efforts.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysical properties of biodiesel from microalgae.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProperties\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNanno\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTetra\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIso\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViscosity at 40\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecSt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.976\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlash Point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCloud point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-40.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e provides a comprehensive comparison of fuel properties between algae biodiesel sourced from different microalgae strains (Nanno, Tetra, and Iso) and conventional diesel, alongside ASTM biodiesel standards as benchmarks. Viscosity at 40\u0026deg;C shows notable variations across the biodiesel types, with Nanno microalgae biodiesel exhibiting the lowest viscosity at 6.2, followed by Tetra microalgae biodiesel at 7.976 and Iso microalgae biodiesel at 7.6. In contrast, conventional diesel falls within the ASTM standard range of 1.9\u0026ndash;4.1, suggesting a generally lower viscosity compared to the algae biodiesel variants. Flash points for the algae biodiesel samples are considerably higher than those of conventional diesel, with Nanno, Tetra, and Iso microalgae biodiesel recording values of 100.5, 99.9, and 99.1 respectively, surpassing the ASTM standard minimum of 100. Conventional diesel, however, falls short of this standard with a flash point of 60. Cloud points, indicative of low-temperature operability, depict a challenge for algae biodiesel, as all three variants exhibit considerably lower values compared to conventional diesel. Nanno, Tetra, and Iso microalgae biodiesel display cloud points of -38.9, -40.8, and \u0026minus;\u0026thinsp;45 respectively, contrasting with the range of -15 to 5 for conventional diesel, as per ASTM standards. This comparative analysis underscores the distinct fuel property profiles of algae biodiesel compared to conventional diesel and highlights areas for further optimization, particularly in addressing cloud point challenges to ensure broader operational suitability and regulatory compliance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of algae biodiesel with convectional biodiesel and ASTM biodiesel Standards ().\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFuel property\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNanno microalgae\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTetra microalgae\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIso microalgae\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConventional diesel (Akubude et. al. 2019)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eASTM\u003c/p\u003e\u003cp\u003estandard\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViscosity at 40\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.976\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.9\u0026ndash;4.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.5\u0026ndash;5.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlash Point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e99.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMin 100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCloud point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-38.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-40.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-15 to 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003ePetro-diesel and microalgae biodiesel cost comparison\u003c/h2\u003e\u003cp\u003eThe production costs of Petro-diesel and microalgae biodiesel differ significantly. Petro-diesel production is largely influenced by crude oil prices and refining costs, while microalgae biodiesel production entails factors such as cultivation, extraction, and processing of microalgae biomass. Additionally, microalgae biodiesel production may involve expenses related to research and development, infrastructure, and technology optimization. Overall, microalgae biodiesel production costs can be higher initially but may offer long-term environmental and economic benefits due to its potential for sustainable production and reduced greenhouse gas emissions, especially CO\u003csub\u003e2\u003c/sub\u003e emissions.\u003c/p\u003e\u003cp\u003eProduction costs for both petrodiesel and biodiesel are influenced by two key factors related to scaling production. The first factor, scaling cost, refers to the expenses incurred when increasing production capacity. Utilizing economies of scale can help reduce biodiesel manufacturing costs, as seen in various industrial processes. This implies that significant outputs necessitate large-scale production facilities, as supported by our laboratory findings indicating minimal dry mass yield from microalgae despite sizable production volumes. Another critical aspect of cost scaling is learning effects, which denote advancements in technological processes, such as optimizing growth mediums and cultivation methods. These improvements compound, with each enhancement in output influencing subsequent outcomes. For instance, situating algae production facilities near power plants can lower costs due to constant CO\u003csub\u003e2\u003c/sub\u003e availability and reduced distribution expenses leveraging existing infrastructure. The costs of biodiesel production from microalgae can be categorized into depreciation, labor expenses, and equipment size and type. While raceway ponds are cheaper to construct and maintain, photobioreactors offer higher biomass production and easier management. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates the scaling costs of photobioreactors across various capacities, offering insights into the correlation between capacity, dimensions, resource needs, and related expenses.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eScaling cost of photobioreactor (Jorquera et. al. 2010).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCapacity (Tons of dry weight biomass per day)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLength (meters)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCarbon Dioxide (Kgs per day)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eArea (Acres)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eElectricity (Kilowatts)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCost\u003c/p\u003e\u003cp\u003e(Euros)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemonstration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e69000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2881\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e580000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10692\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.5 million\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e53466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 million\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e106932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e288053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10 million\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe results revealed that the spans a range of capacities from demonstration-scale to 100 tons of dry weight biomass per day, illustrating various stages of production scalability. With increasing capacity, both the length and area of photobioreactors proportionally expand, necessitating larger physical infrastructure to accommodate higher biomass production. Daily carbon dioxide requirements also increase with capacity, indicating the direct relationship between biomass production and carbon dioxide consumption, emphasizing photobioreactors' role in carbon sequestration and mitigation. Larger photobioreactors exhibit significantly higher electricity consumption, implying increased energy input for greater biomass output. This highlights the importance of considering energy efficiency and sustainable power sources in large-scale algae cultivation.\u003c/p\u003e\u003cp\u003eThe cost of scaling up photobioreactors rises substantially with capacity. From demonstration-scale to 100-ton capacity, there is a significant escalation in investment, ranging from thousands to millions of euros, covering expenses related to infrastructure, equipment, energy, and maintenance.Biodiesel derived from palm oil typically costs approximately \u003cspan\u003e$\u003c/span\u003e0.66 per liter, representing a 35% increase compared to petrodiesel. This suggests that the conversion process from palm oil to biodiesel adds roughly \u003cspan\u003e$\u003c/span\u003e0.14 per liter to the oil's price (Acevedo et. al. 2015). To compete with petrodiesel, the price of palm oil-based biodiesel should ideally not exceed \u003cspan\u003e$\u003c/span\u003e0.48 per liter, assuming no biodiesel tax. Similarly, for microalgal oil to be cost-competitive with petrodiesel, a target price of \u003cspan\u003e$\u003c/span\u003e0.48 per liter is reasonable. Achieving independence from petroleum diesel and ensuring environmental sustainability require reducing the production cost of algal oil from around \u003cspan\u003e$\u003c/span\u003e2.80 to \u003cspan\u003e$\u003c/span\u003e0.48 per liter\u0026mdash;a strategic imperative (Abdo et. al. 2015). This cost reduction target decreases to \u003cspan\u003e$\u003c/span\u003e0.72 per liter if the algal biomass, with 70% oil content by weight, is cultivated in photobioreactors. While these cost reductions are substantial, they are feasible with strategic efforts.\u003c/p\u003e\u003cp\u003eThe integration of photo-bioreactors and astaxanthin co-production can slash biodiesel production costs from \u003cspan\u003e$\u003c/span\u003e3.90 to \u003cspan\u003e$\u003c/span\u003e0.54 per liter, highlighting the potential for cost-effective strategies in biorefinery operations. Despite facing technical hurdles, economic analysis demonstrates the viability and profitability of such approaches. Cultivating microalgae in wastewater or co-producing with valuable products (VAPs) can drive down biodiesel production costs to \u003cspan\u003e$\u003c/span\u003e0.73 per kilogram of dry weight or \u003cspan\u003e$\u003c/span\u003e0.54 per liter (Aci\u0026eacute;n-Fern\u0026aacute;ndez et. al. 2019; Nazifa et. al. 2021). Encouraging access to markets for VAPs, projected to reach \u003cspan\u003e$\u003c/span\u003e53.43\u0026nbsp;billion by 2026, is crucial. Thus, incentivizing research, development, and consumption of microalgae-based biodiesel is essential for bridging the cost gap with petroleum diesel.\u003c/p\u003e\u003cp\u003eMicroalgal oils have the potential to entirely supplant petroleum as the primary source of hydrocarbon feedstock for the petrochemical sector. To achieve this, microalgal oil must be obtainable at a price comparable to that of crude oil, as follows Yusuf (2007):\u003c/p\u003e\u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csub\u003ealgal\u003c/sub\u003e oil\u0026thinsp;=\u0026thinsp;6:9 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e \u003cem\u003eC\u003c/em\u003e\u003csub\u003epetroleum\u003c/sub\u003e (2)\u003c/p\u003e\u003cp\u003eIn the equation, where \u003cem\u003eC\u003c/em\u003e\u003csub\u003ealgal\u003c/sub\u003e oil (\u003cspan\u003e$\u003c/span\u003e per liter) represents the price of microalgal oil and \u003cem\u003eC\u003c/em\u003e\u003csub\u003epetroleum\u003c/sub\u003e denotes the price of crude oil in dollars per barrel, microalgal oil should ideally not exceed approximately \u003cspan\u003e$\u003c/span\u003e0.41 per liter to be a viable substitute for crude oil when the latter is priced at \u003cspan\u003e$\u003c/span\u003e60 per barrel. If the price of crude oil increases to \u003cspan\u003e$\u003c/span\u003e80 per barrel, as is sometimes predicted, microalgal oil priced at \u003cspan\u003e$\u003c/span\u003e0.55 per liter is likely to become economically competitive with crude petroleum. This equation assumes that algal oil contains roughly 80% of the energy content of crude petroleum. Overall, the results underscore the complexities and challenges associated with scaling up photobioreactors for algae cultivation. While larger capacities offer greater potential for biomass production and CO\u003csub\u003e2\u003c/sub\u003e mitigation, they also entail higher resource requirements and investment costs. Balancing these factors is crucial for achieving economic viability and environmental sustainability in large-scale algae cultivation projects. Additionally, further research and technological advancements may be necessary to optimize efficiency and reduce costs in photobioreactor systems, facilitating their widespread adoption as a green solution for biomass production and carbon capture.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e\u003c/b\u003eNannochloropsis showcased the greatest promise as a microalgal feedstock for biodiesel production, achieving an impressive oil yield of 45.01 mL per 80 grams of biomass alongside a remarkable biodiesel conversion efficiency of 96.06% when utilizing calcium methoxide catalyst. In comparison, Isochrysis and Tetraselmis produced 30.04 mL and 20.00 mL of oil respectively, with biodiesel conversion efficiencies of 90.07% and 93.06%. The superior performance of Nannochloropsis can be attributed to its higher lipid content and favorable fatty acid profile. Furthermore, calcium methoxide demonstrated exceptional catalytic efficiency as a heterogeneous catalyst, delivering high conversion rates while minimizing soap formation and providing significant environmental benefits over conventional homogeneous catalysts.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eOil extraction of microalgae revealed distinct differences among species. Nannochloropsis led with the highest oil yield of 45 mL, followed by Isochrysis at 30 mL, and Tetraselmis at 20 mL, reflecting variations in lipid content and extraction efficiency. Tetraselmis oil exhibited the lowest viscosity at 13.3 cSt (40\u0026deg;C), while Nannochloropsis showed the highest viscosity of 39.1 cSt, with Isochrysis falling in between at 25.2 cSt. Both Tetraselmis and Nannochloropsis oils performed well in cold conditions, with cloud points of \u0026minus;\u0026thinsp;3.3\u0026deg;C and \u0026minus;\u0026thinsp;4\u0026deg;C respectively, whereas Isochrysis had a slightly higher cloud point of \u0026minus;\u0026thinsp;1.2\u0026deg;C. Nannochloropsis oil\u0026rsquo;s notably high flash point of 274\u0026deg;C suggests superior safety during handling, complemented by its relatively high density of 915 kg/m\u0026sup3;, which may influence its suitability for various applications. Additionally, Tetraselmis and Nannochloropsis oils displayed low pour points of \u0026minus;\u0026thinsp;10\u0026deg;C and \u0026minus;\u0026thinsp;17\u0026deg;C, respectively, outperforming Isochrysis in cold flow properties. Fatty acid analysis showed Tetraselmis oil rich in linoleic acid (50.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2%) and oleic acid (38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7%), whereas Isochrysis oil was predominantly oleic acid (60.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5%), and Nannochloropsis oil had the highest oleic acid content (54.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9%) with minimal linoleic acid (0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6%).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMicroalgae-derived biodiesels demonstrate a compelling combination of physical properties that enhance fuel performance, safety, and environmental compatibility. Nannochloropsis biodiesel exhibited the lowest viscosity (6.2 cSt), promoting efficient fuel injection and combustion, while all three biodiesels\u0026mdash;Nanno, Tetra, and Iso\u0026mdash;maintained high flash points (above 99\u0026deg;C), ensuring safer handling and reduced fire risks. Their exceptionally low cloud points (from \u0026minus;\u0026thinsp;39\u0026deg;C to -45\u0026deg;C) highlight their superior cold flow characteristics, making them well-suited for colder climates without fuel gelling or filter blockages. Moreover, their near-neutral pH values (6.8\u0026ndash;7.71) support engine material compatibility and long-term operational stability. Collectively, these traits not only confirm microalgae as a viable feedstock for high-quality biodiesel but also reinforce their potential to reduce carbon emissions and contribute to sustainable energy solutions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDespite its current higher production costs compared to petro-diesel, microalgae biodiesel stands out as a promising long-term solution due to its sustainability, carbon dioxide mitigation potential, and ability to integrate with high-value co-products like astaxanthin. Through strategic scaling, technological innovation, and the use of photobioreactors\u0026mdash;particularly when paired with wastewater treatment\u0026mdash;costs can be significantly reduced. With ongoing research, infrastructure investment, and supportive market policies, achieving a competitive price of \u003cspan\u003e$\u003c/span\u003e0.48\u0026ndash;\u003cspan\u003e$\u003c/span\u003e0.55 per liter is within reach. This positions microalgae biodiesel as a viable, eco-friendly alternative for both the energy and petrochemical industries, offering a pathway toward a greener and more sustainable future.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthical Approval\u003c/h2\u003e\u003cp\u003eThis study does not involves humans and/or animals subjects.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003cp\u003eThe authors confirm that the study does not involves humans and/or animals materials.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003cp\u003eAll authors have provided their consent for this publication.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003e\u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003enot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthors\u0026rsquo; Contributions\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study's conception and design. Material collection, sample preparation, and drafting of the initial manuscript were performed by Hala Ghazi and Ali Al Sawalmih. Mohammad Al-Hwaiti contributed to the conceptualization, materials analysis, and interpretation of results, in addition to reviewing and editing the manuscript. He was also actively involved in data collection, writing, supervision, and final revisions. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors express their sincere gratitude to all contributors who made this research possible. We are especially indebted to the Faculty of Plant Science at Tanta University, Egypt, for generously providing the marine microalgae samples that were essential to this study. Special thanks are extended to Eng. Oday Al Shamaseen and Eng. Njoud Alhabahbeh from the Bioenergy Laboratory at the Faculty of Engineering, Al-Hussein Bin Talal University, for their invaluable support in performing the physical and chemical analyses. We also deeply appreciate the efforts of Ms. Mashalla Al-Ryati and Ms. Maysoon Qteifan for their dedicated work in cultivating microalgae at the Marine Science Station, University of Jordan in Aqaba. Their contributions were fundamental to the success of this research.\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdo SM, Abo El-Enin SA, El-Khatib KM, El-Galad MI, Wahba SZ, El Diwani G (2016) Preliminary Economic Assessment of Biofuel Production from Microalgae. 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In Biofuels for a More Sustainable Future, 11\u0026ndash;19.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Marine microalgae, Biodiesel production, Transesterification, Sustainable biofuels, Greenhouse gas reduction","lastPublishedDoi":"10.21203/rs.3.rs-6819238/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6819238/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBiodiesel derived from lipid-rich oils extracted from microalgae holds promise for fulfilling future energy consumption. Three microalgae varieties, namely Nannochloropsis, Tetraselmis, and Isochrysis, were assessed. A novel aspect of this study is the use of calcium methoxide (C\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e6\u003c/sub\u003eCaO\u003csub\u003e2\u003c/sub\u003e) as a catalyst for transesterification in the production of biodiesel from marine microalgae. Oil yields from 80g of microalgae were determined as follows: 45 ml for Nannochloropsis, 30 ml for Isochrysis,\u0026nbsp; and 20 ml for TetraselmisTop of Form. Furthermore, the calcium methoxide catalyst enhanced biodiesel yield for Nannochloropsis, Tetraselmis, and Isochrysis microalgae by 96%, 93%, and 90%, respectively. Tetra microalgae oil showcases exceptional characteristics with notably low viscosity (13.3 cSt at 40°C), contrasting sharply with Nanno's higher viscosity (39.1 cSt), while Iso falls in between at 25.2 cSt. In colder conditions, Tetra (-3.3°C) and Nanno (-4°C) oils perform well without solidifying, although Iso's slightly superior cloud point (-1.2°C) outperforms Tetra's in lower temperatures. Nanno's high flash point (274°C) ensures greater safety, while its density of 915 kg/m³ stands out among the three, potentially impacting its performance across various applications. Both Tetra (-10°C) and Nanno (-17°C) demonstrate lower pour points, making them more effective in colder environments compared to Iso. The composition of fatty acids differs across these oils: Tetra microalgae oil contains primarily Linoleic acid (50.60±1.2%) and Oleic acid (38.2±0.7%), while ISO sp microalgae oil is predominantly Oleic acid (60.5±1.5%), and NANNO sp contains the highest percentage of Oleic acid (54.7±0.9%) with minimal Linoleic acid (0.4±0.6%). In terms of microalgae biodiesel, Nanno exhibited a viscosity of 6.2 cSt, Tetra had 7.976 cSt, and Iso showed 7.6 cSt, reflecting their individual flow characteristics. Their flash points Nanno at 100.5°C, Tetra at 99.9°C, and Iso at 99.1°C highlight safety during handling. Additionally, Nanno (-39°C), Tetra (-40.8°C), and Iso (-45°C) biodiesels' cloud points imply superior performance in colder temperatures, minimizing the risks of fuel solidification and filter issues. These parameters indicated that marine microalgae biodiesel has the potential to not only meet stringent green fuel standards but also significantly reduce CO\u003csub\u003e2\u003c/sub\u003e emissions across its entire lifecycle, spanning from production to combustion.\u003c/p\u003e","manuscriptTitle":"Environmentally Friendly Biodiesel Synthesis from Marine Microalgae Using Calcium Methoxide as a Novel Catalyst","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-21 10:02:42","doi":"10.21203/rs.3.rs-6819238/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"07ab6523-1616-4b18-9f0b-ac438ffc6f99","owner":[],"postedDate":"July 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-02T09:41:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-21 10:02:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6819238","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6819238","identity":"rs-6819238","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}