Comparative Life Cycle Assessment of Sustainable Aviation Fuel Production from Different Biomasses

Abstract

The aviation sector makes up 11% of all transportation emissions and is considered a “hard to abate” sector since, due to the long distances to be traveled, opportunities for electrification are rather limited. Therefore, since there are no alternatives to fuels, Sustainable Aviation Fuels (SAFs), or fuels produced from biomass, have recently been developed to reduce climate-changing emissions in the aviation sector. Using Life Cycle Assessment, this research evaluated the environmental compatibility of different SAF production routes from seven biomasses: four food feedstocks (Soybean, Palm, Rapeseed, and Camelina), one non-food feedstock (Jatropha curcas L.), and two wastes (Waste Cooking Oil, or WCO, and Tallow). The evaluation was carried out using SimaPro 9.5 software. The results showed that the two potentially most favorable options could be Camelina and Palma, as they show minimal environmental impacts in 4 and 7 out of 18 impact categories, respectively. Soybean, on the other hand, appears to be the least sustainable precursor. Considering GWP, SAF production could reduce the values compared to fossil fuel by 2.8–3.6 times (WCO), 1.27–1.66 times (Tallow), 4.6–5.8 times (Palm), 3.4–4.3 times (Jatropha), 1.05–1.32 times (Rapeseed), and 4.36–5.5 times (Camelina), demonstrating the good environmental impact of these pathways. Finally, the sensitivity analysis showed that SAF production from waste could be an environmentally friendly option, with rather low environmental impacts, in the range of 5.13 g CO₂ eq/MJ for Tallow and 3.12 g CO₂ eq/MJ for WCO. However, some of the energy would have to come from sustainable energy carriers such as biomethane and renewable sources such as photovoltaic energy.

1. Introduction

1.1. Background

In 2022, the aviation sector produced nearly 1 billion tons of CO₂ [1], or about 2% of the 42 billion tons of CO₂ produced annually by human activity [2]. However, the aviation sector also contributes 11% of the emissions associated with transportation [3] (Figure 1), making it, the second largest source of GHG emissions after road transport [4]. If it were a country, it would be in the top 10 for emissions and a Lisbon–New York round-trip flight would generate about the same level of emissions as an average European citizen heating his or her home for an entire year. Airplanes, in addition to emitting CO₂ from fuel combustion, also affect the concentration of other air gases and pollutants. For example, they generate increased concentrations of ozone and emissions of water vapor, soot, methane, and sulfur [5], which alter the radiative properties of the atmosphere [6,7]. Overall, the warming effect is far stronger, to the point that Klöwer et al. (2021) [8] estimated that 4% of the global temperature increase since the pre-industrial era is due to aviation. Moreover, some observations by Copernicus, the European Union’s Earth monitoring program, have shown that aviation has a greater effect than other sectors because of the altitude at which emissions are released, namely within the troposphere [9].

While, for CO₂, the most impactful greenhouse gas, the difference in altitude has no particular significance, other gases, such as nitrogen oxide and water vapor, may have a higher effect at higher altitudes. Furthermore, in 2022, aircraft fleets and air passenger traffic increased by +30% and +97%, respectively, from the previous year’s levels [10]. Considering the growth in revenue and reliability of air travel, the Global Fleet and Maintenance, Repair and Overhaul (MRO) Market Forecast 2023–2033 [11] estimates how commercial aircraft fleets will grow by +33% to more than 36,000 aircraft by 2033, just as Airport Council International (ACI) World has estimated average annual growth of +5.8% in passenger traffic over the period 2022–2040 when 19 billion passengers will transit in the world’s airports annually. All this will most likely generate further growth in CO₂ emissions, which are projected by the International Energy Agency [1] to exceed the 2019 level by around 2025. Adding to all this is another issue, which is not insignificant, namely, that aviation is one of the most difficult sectors to decarbonize, which is why it is called “hard to abate”. While emissions from electricity generation can be reduced through the expansion of renewable energy, and road transport can be electrified, the aviation sector faces greater difficulties. This is because, in air transport (as well as in maritime transport), there are no alternatives to fuels, and, due to long distances, weight, and size constraints, electrification opportunities are limited. Therefore, in line with the Net Zero Emission (NZE) scenario [12], to reduce the level of climate-changing emissions in the aviation sector, the need has arisen to search for new fuels that are sustainable and have zero net carbon emissions. To this end, the European Commission recently announced the ReFuelEU initiative [13], the goal of which is to support the production of fuels derived from biomass. Such fuels are also known as bio-jet fuels or Sustainable Aviation Fuels (SAFs), which are chemically and physically the same as their fossil counterparts [14]. Indeed, they have low sulfur content, high thermal stability, meet cold flow properties, and are compatible with aircraft engines without the need to change their trim [15]. SAFs can be produced either by biochemical processes (using microorganisms used to convert biomass to fuel) [16] or by thermochemical processes (where biomass is converted to fuel by pyrolysis or gasification) [17]. Biomass, therefore, due to its abundance, can be considered the optimal energy option to effectively replace fossil fuels in the aviation sector.

1.2. Originality and Literature Gap

To date, there is a lack of work providing accurate information on the environmental impacts of SAF production pathways from biomass, especially regarding cellulosic residues. For example, Akter et al. (2024) [18], considered SAF produced from logging residues generated during harvesting and thinning operations in Georgia, with the results showing values of 750–976 g CO₂ eq/L. Likewise, Deuber et al. (2023) [19] studied the production of SAF from lignocellulosic residues via hydrothermal liquefaction (HTL), showing 73–82% less climate mitigation potential than fossil fuel. Therasme and Kumar (2023) [20], estimated that the average GHG emissions to produce SAFs from woody crops are 29–90 gCO₂ eq/MJ. Marangon et al. (2024) [21] evaluated the environmental impacts of SAF production from microalgae, considering HTL and gasification followed by Fischer–Tropsch synthesis (G + FT). The results showed that, for SAFs from HTL, the emissions were −51.6 g CO₂ eq/MJ, while in G + FT they were 250 g CO₂ eq/MJ. In any case, it is interesting to note that the relevant literature on the study of environmental compatibility of SAFs is rather recent and mostly concentrated in recent years. Entering the keywords “Life Cycle Assessment” AND “Sustainable Aviation Fuels” into Scopus, the search starts from 2011 and returns about 123 papers (June 2024), of which 74% are from 2021 (Figure 2).

1.3. Aim of the Study

Considering the above then, this research attempted to provide a study of the environmental sustainability of different SAF production pathways from different biomasses through the use of the Life Cycle Assessment (LCA). In more detail, seven biomasses were chosen and grouped into (i) food feedstocks (Soybean, Palm, Rapeseed, and Camelina), (ii) non-food feedstocks (Jatropha curcas L.), and (iii) waste (used cooking oil, and Tallow). The evaluation was carried out using Simapro 9.5 software [22].

It was decided to analyze the Hydrotreated Esters and Fatty Acids production process, starting from lipid raw materials. This is because, after a literature review, HEFA appears to have a more mature Technology Readiness Level (TRL), relative to certification routes, which is why most of the commercial aviation biogas oil comes from this technology. Overall, therefore, technological readiness and maturity, combined with data availability, contributed to the selection of this production pathway as a case study.

The results of the evaluation could therefore offer interesting information on the production process of SAFs in the context of the decarbonization of aviation and in line with the energy transition.

2. Sustainable Aviation Fuels and Certified Production Routes

The integration of SAFs into commercial aviation requires a rigorous approval process, which corresponds to an equally rigorous certification criterion. Indeed, SAFs must demonstrate that their physical and chemical properties are nearly indistinguishable from their fossil counterparts, making them compatible with blending [23]. This approach allows SAFs to be incorporated to fuel existing fleets, avoiding changes to both aircraft trim and refueling infrastructure. However, for SAF to be effective, it must be blended with conventional jet fuel, ensuring a proper balance of paraffin, olefins, and aromatics [24]. The blending ratio varies according to SAF production technology, with a current maximum of 50% blending with conventional jet fuel. This restriction is in place primarily to ensure compatibility with existing aircraft engines and infrastructures. The 50% blending requirement for SAF with conventional fuel addresses the need for material compatibility and fuel properties [25]. This is because aromatics contribute to energy density and overall fuel properties (such as viscosity, oxidative stability, and combustion properties), which is why, currently, the overall blend must necessarily still contain aromatics from the conventional fossil fuel portion [26]. As aircraft are refueled in different nations, international standards have been introduced for aviation fuels. The American Society for Testing Materials (ASTM) D1655 is a widely accepted international standard for defining requirements for kerosene-based fuels used in commercial aviation, such as Jet A and Jet A-1 [27]. These specifications establish criteria such as composition, volatility, fluidity, combustion, corrosion, thermal stability, contaminants, and additives to ensure compatible fuel blending. The certification of new fuels for commercial use, according to ASTM D4054, is a rigorous three-step, four-level process that requires different volumes of fuel and can take 3 to 5 years, with significant costs [28]. To speed up the research, ASTM introduced a “Rapid Procedure Annex” in 2020, but with the blending being limited and set at 10%. Once all testing steps have been passed, the new fuel can be included in ASTM D7566, establishing quality specifications for SAF fuels. The SAF produced can then be blended with existing fuel within allowable limits [29]. Once this blending is completed, the resulting fuel is certified according to ASTM D1655 and is usable as Jet A or conventional Jet A1 [27]. In summary, each batch of aircraft fuel must go through a certification step before use. While conventional jet fuels are certified following D1655, SAFs obtain certification by following the stringent requirements specified in Annex D7566 regarding the production pathway. The resulting blended fuel obtains certification by the D7566 blend criteria and, thus, automatically obtains a D1655 certification. This procedure transforms the SAF into a “drop-in fuel” that is fully compatible with Jet A/Conform A-1, ready to be used without modification in current jet fueling infrastructure and equipment. To date, ASTM has approved nine different technology platforms, each representing a specific conversion process for SAF production. These pathways are defined through additional annexes to the standards mentioned earlier, particularly D7566. Each of these platforms is related to different types of feedstocks and has corresponding maximum mixing limits (

Table 1. Production routes of certified SAFs [30].

Process Name	Biomass/Precursor	Certification Type and Blending Limit	Technology Readiness Level
Biomass gasification and Fischer Tropsch	Cereals, lignocellulosic materials, and waste	FT-SPK (+50%)	7–8
Hydroprocessed Esters and Fatty Acids (HEFA) or Hydrotreated Vegetable Oil (HVO)	Animal and vegetable fat	HEFA-SPK (+50%)	8–9
Direct sugars to hydrocarbons (DSHC)	Lignocellulosic sugars	HFS-SIP (+10%)	7–8
Biomass gasification and FT with aromatics	Cereals, lignocellulosic materials, and waste	FT-SPK/A (+50%)	6–7
Alcol to Jet (ATJ)	Starchy cereals, lignocellulosic sugars	ATJ-SPK (+50%)	7–8
Catalytic Hydrothermolysis Jet (CTJ)	Animal and vegetable fat	CHJ, CH-SK (+50%)	6
HEFA from algae	Microalgae	HC-HEFA-SPK (+10%)	5
Fog co-processing	fats and oils	FOG (+5%)	-
Fischer Tropsch co-processing	Fischer Tropsch biocrude	FT (+5%)	-

) [30].

The technological maturity of each production pathway can be assessed through the concept of the Technology Readiness Level, which scales from level 1 (basic ideas) to level 9 (a fully proven system in an operational environment) [31]. In more detail: TRL 1—basic principles observed; TRL 2—technology concept formulated; TRL 3—experimental proof of concept; TRL 4—technology validated in the laboratory; TRL 5—technology validated in relevant environment (industrially relevant environment in the case of key enabling technologies); TRL 6—technology demonstrated in relevant environment (industrially relevant environment in the case of key enabling technologies); TRL 7—system prototype demonstration in the operational environment; TRL 8—system complete and qualified; TRL 9—actual system is proven in operational environment (competitive manufacturing in the case of key enabling technologies) [32]. Most of the aviation biofuel currently produced is derived from fats and oils through the HEFA process [33]. This process was certified in 2011 with a maximum mixing ratio of 50%. HEFA converts lipids to hydrocarbons through the following five steps: purification, deoxygenation, cracking, isomerization, and distillation. Feedstocks include animal fats, used cooking oils, and vegetable oils such as Camelina or Jatropha [34].

SAF obtained from HEFA demonstrates good efficiency at low temperatures, high thermal stability, and low tailpipe emissions. This process is cost-effective and can be easily integrated into petroleum refineries, which is why it has been used in more than 95% of SAF flights to date [35]. In addition, SAFs, being hydrotreated, have an additional advantage, namely having shallow levels of aromatic compounds (around 8% of the weight) [26], since hydrotreatment removes them to improve the overall quality of the fuel. This minimizes wear and tear on the seals over time, preventing any fuel leakage [36] while managing to balance the proportion of aromatics necessarily still present in the remaining fossil part of the overall mixture. From this perspective, the research aims to find an appropriate balance in which the environmental benefits of SAF can be realized without compromising the safety, reliability, and performance of aviation fuels. Also, being energy-dense, it can be used in aircraft engines directly.

Despite this, the range of GHG emissions (16.5–47 g CO₂ eq/MJ) is slightly higher than other production routes due to the higher environmental impact during raw material procurement and processing [24]. The predominant challenge to be addressed, however, relates to the significant costs of oleochemical feedstocks, coupled with the need to ensure sustainability in the use of cultivated vegetable oils and to manage feedstock supply. A tangible example of this challenge is waste cooking oil, which serves as a source of raw material. However, its availability is limited, and the increased demand for SAF has raised prices from EUR 500 to EUR 1120 /ton during 2022 [37]. This has led oil to be 60% more expensive than conventional jet fuel. As a result, there may be global competition for oleochemical feedstocks, as several biofuel technologies can be made from lipids. However, the projected availability for jet fuel production has a large uncertainty due to dependence on crop yields, climatic conditions, and competition for feedstocks. Converted refineries and those adopting co-processing will compete for the same oleochemical/lipid feedstocks. In addition, feedstock conversion rates to SAF from biomass are relatively low, varying from 0.1 to 0.2 kg of fuel per jet produced from each kg of biomass, depending on the type of feedstock. As a result, the costs of producing fuels through the HEFA process are between three and six times higher than the costs of producing conventional jet fuels [38]. However, despite these costs, HEFA routes remain more cost-effective than other alternatives. Several studies show that HEFA is the most economical SAF production technology due to its low investment costs (CAPEX), operating expenses (OPEX), and minimum jet fuel selling price (MJSP) [24]. Therefore, in both economic and environmental terms, this production pathway is currently considered the best option, as it is also the most commercially developed SAF technology. Currently, biomass-based pathways are the most developed and certified ones.

However, reducing aviation’s impact on the environment will require a multifaceted approach. Indeed, as the industry moves toward alternatives to fossil fuels, it is also important to examine how SAF can work both symbiotically and in tandem with carbon removal for further climate mitigation. Indeed, when converting biomass to SAF, there are other opportunities to capture additional CO₂ emissions that occur during the conversion process. In more detail, the FT conversion pathway allows for the integration of two carbon capture technologies, Carbon Capture And Usage (CCU) and Carbon Capture And Storage (CCS), which provide additional carbon offsetting capabilities [39]. The basic assumption of CCU is to capture carbon dioxide produced during the production process of SAFs and use it together with renewable electricity to generate renewable hydrogen and convert these molecules into hydrocarbons [40]. CCS, on the other hand, involves capturing CO₂ generated in processes that are stored permanently within deep geological formations (such as oil fields or deep aquifers) [41]. The ultimate goal is to effectively reduce net CO₂ emissions. Future biomass production of SAFs could then be further integrated with carbon capture and storage to support greater emission reductions and potentially negative net emissions. However, at present, challenges remain related to the economic feasibility of this process. In any case, considering both fossil and biogenic carbon fluxes and if the engines were adapted to run on 100% SAFs, there could most likely be the possibility of negative net emission flights.

3. Materials and Methods

Life Cycle Assessment

In this study, sustainability assessment was carried out through Life Cycle Assessment, a standardized method used to quantify the environmental impacts of a process or product throughout its life cycle.

It refers to two standards, ISO 14040:2006 [42] and ISO 14044:2006 [43] and consists of the following four steps: (1) Goal and Scope Definition; (2) Life Cycle Inventory (LCI); (3) Life Cycle Impact Assessment (LCIA); and (4) Interpretation.

(1)

Goal and Scope Definition

The goal of this research was to assess the environmental impact of SAF production using different biomasses through the Hydrotreated Esters and Fatty Acids (HEFA) process to understand which could be the most sustainable precursor and pathway. Consistent with other literature studies on SAFs, including Deuber et al. (2023) [19], Therasme and Kumar (2024) [20], and Marangon et al. (2024) [21] the Functional Unit (FU) used is the production of 1 megajoule (MJ) of SAF-HEFA. Seven different oil biomasses were considered and divided into three different groups:

• Feedstocks: Soybean, Palm, Rapeseed, and Camelina, considering a cradle-to-gate process, starting from the biomass cultivation stage to SAF-HEFA conversion.
• Non-food feedstock: This group includes Jatropha curcas L., a tropical plant that is not used for food purposes because of its toxicity. It grows wild on marginal land without the need for inputs during the cultivation stage. Therefore, given the absence of inputs for the cultivation phase, the production process of SAF HEFA from Jatropha is from gate to gate, starting from the oil extraction stage and continuing until its conversion.
• Waste: This group includes Waste Cooking Oil (WCO) and Tallow. Since they are considered waste, their system boundary starts from the oil processing stage resulting from the production processes and continues until the conversion stage to SAF HEFA. Again, the process is considered from gate to gate, given the absence of initial production stages.

(2)

Life Cycle Inventory (LCI)

Secondary data obtained from the International Civil Aviation Organization (ICAO) (2022) [44], Stratton et al. (2010) [45], and Seber et al. (2014) [46] were used to compose the inventory (whose data are shown in

Table 2. Life Cycle Inventory data.

Input/output	Unit	Feedstock							Source
		Jatropha	Camelina	Palm	Soybean	Rapeseed	WCO	Tallow
Cultivation
INPUT
Nitrogen	kg	-	0.04	0.01	0.05	0.05	-	-	Ecoinvent v3.9
Phosphoric acid		-	0.02	0.01	0.19	0.01	-	-	Agrybalize 4
Potassium oxide		-	0.02	0.01	0.30	0.02	-	-	Ecoinvent v3.9
Calcium carbonate		-	-	-	-	0.01	-	-
Herbicide		-	0.01	0.01	0.02	0.0003	-	-	WFLDB
Insecticide		-			0.0004	0.0001	-	-
Diesel		-	0.03	0.004	0.31	0.02	-	-	Ecoinvent v3.9
Gasoline		-	-	-	0.07	-	-	-	Agrybalize 4
Methane		-	-	-	0.02	-	-	-	Ecoinvent v3.9
LPG		-	-	-	0.02	-	-	-
Electricity	MJ	-	-	-	0.94	-	-	-
OUTPUT
Flour	kg	2.76	1.02	1.46	2.09	1.05	-	-
Extraction
INPUT
N-Hexane	kg	0.004	0.001	-	0.001	0.01	-	-	Ecoinvent v3.9
Methane		0.03	0.01	-	0.04	0.02	0.03	0.16
Fuel		-	0.01	-	0.001	-	-	-
Carbon		-	-	-	0.03	-	-	-
Gas		-	-	-	0.01	-	-	-
Diesel		-	-	0.0003	-	-	-	-
Electricity	MJ	0.70	0.10	0.002	0.33	0.22	0.15	0.63
OUTPUT	-
Flour	kg	-	0.63	-	1.65	0.57	-	-
Methane		-	-	0.0008	-	-	-	-
Heat		-	-	0.0004	-	-	-	-
Crude oil		-	-	0.03	-	-	-	-
Conversion
INPUT
Hydrogen	kg	0.001	0.01	-	0.01	0.003	-	-	Ecoinvent 3.9
Methane		0.002	0.05	0.002	0.03	0.07	0.09	0.09
Phosphoric acid		-	-	0.00001	-	-	-	-
Sodium hydroxide		-	-	0.000002	-	-	-	-
Nitrogen		-	-	0.000004	-	-	-	-
Electricity	MJ	0.005	0.11	0.01	0.09	0.15	0.22	0.22
OUTPUT
Propane mixture	kg	0.002	0.03	-	0.03	-	-	-
Nafta		0.001	0.01	-	0.01	0.01	-	-
BTL Fuel		-	-	0.03	-	-	-	-
Steam	MJ	-	-	0.06	-	-	-	-

). These data were then modeled on SimaPro 9.5 software databases. Specifically, nitrogen, potassium oxide, diesel, methane, liquefied petroleum gas, electricity, n-hexane, calcium carbonate, fuel oil, coal, landfill gas, hydrogen, phosphoric acid, and sodium hydroxide from Ecoinvent 3.8 [47] were used. Phosphoric acid and gasoline from Agribalyse 3 [48] and herbicide and insecticide from the World Food LCA Database (WFLDB) [49] were also utilized. The Ecoinvent 3.8 database contains LCI data for energy production, transportation, and chemical production. Agribalyse 3 and WFLDB are comprehensive LCI databases that contain data for agricultural and agri-food production. Where possible, process data were adapted to typical conditions and productions based on the average process data from the international databases mentioned above (since these are the only ones available in the LCA software package 9.5.0 used in this study) and adjusted to be as consistent as possible with the objective and scope of the study. Inputs for the cultivation stage were similar for most of the food commodities studied. Nitrogen, phosphoric acid, potassium oxide, insecticides, herbicides, and the use of diesel for farm equipment are the main inputs for the cultivation stage.

However, it should be noted that Soybean cultivation also requires the consumption of methane, gasoline, LPG, and electricity. Next, the oil extraction process for food and non-food biomass can be accomplished by mechanical seed pressing followed by extraction with a non-polar solvent, such as n-hexane, to maximize oil yield. This solvent extraction method is commonly used in large-scale production facilities and can provide up to 99% oil extraction efficiency [50]. In all the crops considered, the use of methane and electricity is a common practice, except in Palm cultivation. In the case of Soybean, the extraction phase has more inputs, including the use of coal and landfill gas. It is important to point out that, in the literature review conducted for the palm oil extraction phase, methane emissions were evaluated for both closed and open ponds. However, since only a small percentage of global palm oil production capacity currently involves methane capture, it was decided to rely on data for open ponds, averaging the information from the Argonne National Laboratory (ANL) and Joint Research Centre (JRC). Otherwise, the extraction of oil from WCO and Sego is performed through a chemical and thermal process called “rendering”, the main utilized inputs of which are methane and electricity. Finally, in the conversion stage for all biomass involved in the study, hydrogen and/or methane and electricity are used. It is important to note that, albeit with small and low values, palm oil, at this stage, has more inputs, including phosphoric acid, sodium hydroxide, and nitrogen. To create the inventory, it was necessary to standardize the units of measurement for the various inputs used in the three phases analyzed. Initially, the data were expressed in different units, such as grams (g), Megajoules (MJ), and British Thermal Units (BTUs). For this reason, it was chosen to convert all units to kilograms (Kg) to adopt a uniform unit of measurement compatible with the software used. The exception to this rule was electricity, which was kept in Megajoules (MJ). In detail, for data expressed in Btus (such as diesel, gasoline, methane, etc.), the conversion to Megajoules (MJ) was first carried out, and then the heating value of the material was sought in MJ/Kg. In the analysis of HEFA biofuels and related feedstocks, it is crucial to consider the origin of biomass, as its production and related emissions can vary significantly depending on the geographic region where it is grown or produced. The assumptions considered regarding the origin of the biomass involved are described below:

• Soybeans are mainly grown in the United States and Latin America. For this analysis, a large-scale crop from the United States was considered as a reference point. Agricultural practices, soil conditions, and climate can vary greatly among these regions, thus affecting the overall emissions associated with Soybean production.
• Rapeseed is commonly grown in cold climates and is an important crop in Europe. Therefore, data on its European cultivation were used. Different climatic conditions and European farming practices may result in differences in emissions compared to other regions of the world.
• Camelina is a plant grown in several regions of the world, including Europe, the United States, and Canada. This widespread geographic distribution of cultivation led to the use of an average of data regarding camelina production in these regions to obtain the inventory data.
• For palm oil, a precise place of origin was not specified, but the reference data came from ANL and CCR, and an average was calculated. It can be assumed that Palm is mainly grown in Malaysia, where it is a significant crop. Palm oil cultivation is often associated with environmental concerns, such as deforestation and greenhouse gas emissions, depending on practices in the region.
• For Jatropha, the data refer to its cultivation in India, where semi-arid conditions favor high yields. However, it is cultivated in different parts of the world, and emissions may vary depending on the region of cultivation and the agricultural practices adopted.
• For WCO and Tallow, data came from the United States, where they were collected from commercial kitchens and restaurants. However, the generation of these wastes can occur worldwide, and specific emissions may depend on the waste collection and treatment practices in each region.

(3)

Life Cycle Impact Assessment

To guarantee the robustness of the study, the ReCiPe 2016 MidPoint (I) [51] was used. This offers a systematic and transparent approach to selecting impact categories. Among the three available perspectives (individualist, hierarchical, egalitarian), the individualist one was chosen, which considers impacts in the short term, i.e., over a 20-year time horizon. This choice reflects an optimistic view in which technology could help reduce many of the future problems. Several factors were weighed in the selection of impact categories, including scientific relevance, stakeholder concerns, and environmental context. ReCiPe includes a total of 18 impact categories, which were divided into four macro areas:

• Atmospherical Effects: Global Warming Potential (GWP); Stratospheric Ozone Depletion (SOD); Ionizing Radiation (IR); Ozone Formation, Human Health (OFHH); Fine Particulate Matter Formation (FPMP); Ozone Formation, Terrestrial Ecosystems (OFTE); Terrestrial Acidification Potential (TAP);
• Eutrophication: Freshwater Eutrophication Potential (FEP) and Marine Eutrophication Potential (MEP);
• Toxicity: Terrestrial Ecotoxicity (TEC); Freshwater Ecotoxicity (FEC); Marine Ecotoxicity (MEC); Human Carcinogenic Toxicity (HCT); Human Non-Carcinogenic Toxicity (HNCT);
• Abiotic Resources: Land Use (LU); Mineral Resources Scarcity (MRS); Fossil Resources Scarcity (FRS), Water Consumption (WC).

The choice of the ReCiPe 2016 MidPoint (I) method for environmental impact assessment was motivated by its remarkable capability to provide detailed and comprehensive results compared to other alternative calculation methods. This method is distinguished by its inclusion of more impact categories than other common approaches, such as ILCD 2011 [52], CML 2001 [53], or TRACI [54], which is why it was considered to be more comprehensive. Calculations and analyses were performed using SimaPro 9.5 software, a widely recognized and used platform for life cycle assessments.

(4)

Interpretation: Sensitivity Analysis

Life cycle assessments require many input parameters, and many of these parameters are uncertain. Therefore, to assess the sensitivity of results to changes in input, ISO suggests conducting a sensitivity analysis (SA). More precisely, according to Yao et al. (2011) [55], SA is the study of how a change in the model’s output can be statistically or qualitatively attributed to various sources of variation in the model or its inputs. This method allows uncertainty variables to be systematically investigated to quantify their impact on the output of the system.

Therefore, in this study, once the environmental impacts were quantified, an SA was performed. Two scenarios were considered in addition to the baseline scenario. In detail:

• Scenario 1 (S1): This is where 20% of the electricity used in biomass extraction processes is replaced with renewable electricity, in particular, electricity from solar panels. This scenario therefore assumes that extraction plants are partially powered by renewable energy, thus reducing dependence on fossil fuels.
• Scenario 2 (S2): In this scenario, not only is 20% of the electricity replaced with solar energy but the methane used in production processes is also replaced with biomethane. Biomethane is a sustainable alternative to fossil-derived methane and is produced from organic waste materials through anaerobic digestion [56]. This part of the analysis aimed to explore the combined effect of integrating renewable electricity and a sustainable fuel source.

4. Results and Discussions

4.1. Life Cycle Impact Assessment

LCIA results are expressed in

Table 3. LCIA results.

Impact Categories	Unit	WCO	Soybean	Tallow	Palm	Jatropha	Rapeseed	Camelina
Atmospherical effects
GWP	g CO2 eq	2.94 × 101	3.91 × 102	6.35 × 101	1.81 × 101	2.40 × 101	7.93 × 101	1.91 × 101
SOD	g CFC11 eq	1.36 × 10−5	3.77 × 10−4	2.92 × 10−5	2.18 × 10−5	1.04 × 10−5	8.36 × 10−5	1.22 × 10−5
IR	kBq Co-60 eq	2.26 × 10−4	4.20 × 10−3	5.18 × 10−4	1.20 × 10−4	4.37 × 10−4	4.41 × 10−4	2.35 × 10−4
OFHH	g NOx eq	3.59 × 10−2	7.63 × 10−1	7.83 × 10−2	2.87 × 10−2	3.91 × 10−2	8.69 × 10−2	3.29 × 10−2
FPMP	g PM2.5 eq	6.54 × 10−3	1.16 × 10−1	1.44 × 10−2	4.50 × 10−3	8.00 × 10−3	1.19 × 10−2	5.01 × 10−3
OFTE	g NOx eq	3.62 × 10−2	7.68 × 10−1	7.90 × 10−2	2.90 × 10−2	3.98 × 10−2	8.84 × 10−2	3.32 × 10−2
TAP	g SO2 eq	7.00 × 10−2	2.23 × 100	1.53 × 10−1	6.43 × 10−2	7.76 × 10−2	2.10 × 10−1	7.19 × 10−2
Eutrophication
FEP	g P eq	1.16 × 10−3	5.59 × 10−2	2.62 × 10−3	1.66 × 10−3	2.12 × 10−3	3.23 × 10−3	1.72 × 10−3
MEP	g N eq	1.63 × 10−4	3.88 × 10−2	3.56 × 10−4	5.24 × 10−4	1.56 × 10−4	5.34 × 10−4	8.85 × 10−5
Toxicity
TEC	g 1.4-DCB	5.70 × 10−1	7.90 × 101	1.29 × 100	2.21 × 100	1.29 × 100	4.05 × 100	3.64 × 100
FEC		5.27 × 10−4	1.42 × 10−1	1.16 × 10−3	7.67 × 10−3	6.32 × 10−4	3.28 × 10−3	6.65 × 10−4
MEC		6.42 × 10−4	5.11 × 10−2	1.43 × 10−3	1.51 × 10−3	1.02 × 10−3	2.92 × 10−3	2.34 × 10−3
HCT		1.98 × 10−3	9.33 × 10−2	4.23 × 10−3	4.80 × 10−3	1.26 × 10−3	7.11 × 10−3	1.63 × 10−3
HNCT		1.39 × 10−2	2.29 × 10 0	3.15 × 10−2	1.03 × 10−1	3.14 × 10−2	1.23 × 10−1	1.70 × 10−2
Abiotic resources
LU	m2a crop eq	1.83 × 10−3	7.57 × 10−2	4.14 × 10−3	1.61 × 10−3	3.15 × 10−3	4.76 × 10−3	1.42 × 10−3
MRS	g Cu eq	4.04 × 10−2	1.18 × 100	8.71 × 10−2	5.58 × 10−2	2.75 × 10−2	8.08 × 10−2	1.64 × 10−2
FRS	g oil eq	2.43 × 101	2.13 × 102	5.15 × 101	7.02 × 100	1.21 × 101	4.08 × 101	2.01 × 101
WC	m3	1.73 × 10−4	7.80 × 10−3	3.94 × 10−4	1.96 × 10−4	3.20 × 10−4	7.34 × 10−4	1.09 × 10−4

. The results of the assessment showed that, among the seven biomasses, Palm is the most sustainable, presenting the lowest values in 7 out of 18 impact categories. Palm also shows minimal effects on atmospheric categories (GWP with 1.81 × 10¹ g CO₂ eq, IR with 1.20 × 10⁻⁴ kBq Co-60 eq, OFHH with 2.87 × 10⁻² g NOx eq, FPMP with 4.50 × 10⁻³ g PM_2.5 eq, OFTE with 2.90 × 10⁻² g NOx eq and TAP with 6.43 × 10⁻² g SO₂ eq) and one abiotic resource category (FRS with 7.02 × 10⁰ g oil eq). The low environmental impact of the fuel obtained from palm oil can be attributed to several factors, including the limited amount of chemicals used along the process, the absence of methane and n-hexane in the extraction phase (which are common in other biomasses), and the lower overall number of inputs, especially in comparison to the cultivation phase related to other raw food materials. Then, there is WCO, which shows the lowest effects in five out of eighteen categories, one related to eutrophication (FEP with 1.16 × 10⁻³ g P eq) and four related to toxicity (TEC with 5.70 × 10⁻¹ g 1.4-DCB, FEC with 5.27 × 10⁻⁴ g 1.4-DCB, MEC with 6.42 × 10⁻⁴ g 1.4-DCB, and HNCT with 1.39 × 10⁻² g 1.4-DCB). Finally, Camelina shows the lowest impacts on MEP (8.85 × 10⁻⁵ g N eq) and the three remaining impact categories for the abiotic resources category, namely LU (1.42 × 10⁻³ m²a crop eq), MRS (1.64 × 10⁻² g Cu eq) and WC (1.09 × 10⁻⁴ m³). Conversely, the least sustainable biomass is Soybean, which shows higher values than the others in all the impact categories considered. This is mainly due to the more complex route required for its processing and extraction, processes that include many inputs, including pesticides, fertilizers, diesel, electricity, etc.

Considering GWP, the results range from a minimum of 18.12 g CO₂ eq/MJ (Palm) to a maximum of 390 g CO₂ eq/MJ (Soybean). Comparing the results of this study with other literature studies could be misleading, given the great variability in the methodological framework of individual authors in LCA studies (e.g., different system boundaries and production processes), as well as the type of biomass. For example, in the case of Camelina (19.14 g CO₂ eq/MJ) and WCO (29.40 g CO₂ eq/MJ), the data from this research show lower values than Kourkoumpas et al. (2024) [14], who estimated ethanol production from lignocellulosic biomass from an innovative Alcohol-to-Jet (ATJ) pathway, showing emissions of 44.15 g CO₂ eq/MJ, lower (except for Soya) than the 250 g CO₂ eq/MJ estimated by Marangon et al. (2024) [21] for biofuel production from microalgae grown in wastewater. In contrast, Kurzawska-Pietrowicz (2023) [57], SAF-HEFA produced from Jatropha oil shows values of 10.4 gCO₂ e/MJ, twice as high as the results of this study (24.02 g CO₂ eq), although, as also pointed out by the author, different results for the same feedstock and pathway could depend on cultivation, transport and other phases of the feedstock life cycle. Budsberg et al. (2016) [58] then studied the environmental impact of biofuel produced from poplar biomass, finding a GWP of 32–66 g CO₂ eq/MJ, higher than SAFs produced from WCO, Palm, Jatropha, and Camelina. Finally, Zhu et al. (2022) [59] estimated values of 43.6 g CO₂ eq/MJ for a HEFA conversion pathway of Soybean, eight times higher than the 390 g CO₂ eq of this study. In the literature, there is no real baseline value for the GWP of fossil fuel, which is why an average baseline emission value set by the EU Renewable Energy Directive was chosen, which is 83.8–105.7 g CO₂ eq/MJ [60]. Therefore, it emerges that, except for Soybean, the GWP of all biomasses considered is lower than the fossil fuel baseline values. SAF production pathways from biomass could reduce the GWP compared to fossil fuel by 2.8–3.6 times (WCO), 1.27–1.66 times (Tallow), 4.6–5.8 times (Palm), 3.4–4.3 times (Jatropha), 1.05–1.32 times (Rapeseed), and 4.36–5.5 times (Camelina), demonstrating the good environmental impact of biofuel. As for OFHH, TAP, MRS, and FRS, Soya shows particularly high values of 0.76 g NOx eq, 2.23 g SO₂ eq, 1.18 g cu eq, and 212 g oil eq, respectively. This is mainly due to the use of agricultural machinery and diesel used during field operations [61].

Soya also shows particularly high values for TEC (79.05 g 1–4 DCB), mainly due to the pesticides used during its cultivation [62]. After an initial assessment of the environmental impacts, the yield of the various biomasses was calculated by dividing 1 MJ by the weight of the biomass in kg. The yields (MJ/kg) obtained are expressed in

Table 4. Biofuel yields (MJ/kg and %), biomass quantity, and invested energy.

Feedstock	Starting Biomass (kg)	Invested Energy (MJ)	Energy Density (MJ/kg)	Yields (%)
Camelina	1.02	0.21	0.98	98%
Rapeseed	1.05	0.37	0.95	95%
WCO	1.36	0.37	0.74	74%
Palm	1.46	0.02	0.68	68%
Soybean	2.09	1.36	0.47	47%
Jatropha	2.76	0.70	0.36	36%
Tallow	3.45	0.85	0.29	29%

.

As an example, this means that if 1 MJ of energy is produced from 2.09 kg of soya, then it will have an energy density of 0.47 MJ × 1 kg (1 MJ/2.09) and a yield of 47%. Therefore, from 1 kg of Soy, we can expect to obtain this energy (47% of the biomass is converted into energy). Similarly, concerning Camelina, if 1 MJ of energy is produced from 1.02 kg, the energy density is 1 MJ/1.02 kg, or about 0.98 MJ/kg, with a yield of 98%.

This means, for example, that Rapeseed-based biofuel, having a higher energy density than Soya-based biofuel, produces more energy. Considering the same calculations (energy density = 1 MJ/quantity of biomass), if 1 MJ of energy is produced from 1.05 kg of Rapeseed, its energy density is 1 MJ/1.05 kg or about 0.952 MJ/kg for a yield of 95%. Comparing the biofuels, Rapeseed biofuel is more energy-dense than Soybean biofuel but less energy-dense than Camelina biofuel. When comparing Camelina and Soya, on the other hand, the Camelina-based biofuel is more energy-efficient than Soya, because, for the same mass (1 kg for both), it produces almost twice as much energy as the Soya-based biofuel. For a biofuel company, a more energy-dense fuel is generally better because it means that more energy can be obtained from the same mass of fuel. So, in essence, a biofuel that requires less raw material to produce a given amount of energy is more efficient. Therefore, the two most efficient biomasses in terms of yield are Camelina (98% or 0.98 MJ/kg) and Rapeseed (95% or 95 MJ/kg). They are followed by WCO (74% or 0.74 MJ/kg), Palm (68% or 0.68 MJ/kg), Soya (48% or 0.48 MJ/kg), Jatropha (36% or 0.36 MJ/kg) and Tallow (29% or 0.29 MJ/kg). Thus, considering both all 18 impact categories and energy yield, Camelina appears to be the biomass that could give particularly favorable results because, on the one hand, it has the highest yield and, on the other hand, it has the lowest impacts on four impact categories. Palm, on the other hand, shows the lowest impacts in seven out of eighteen categories but has a lower yield than Camelina.

This study assumed that the raw materials had a precise origin, e.g., Soybean being from the USA, Rapeseed from Europe, Palm from Malaysia, and Jatropha from India. The WCO and Tallow were obtained from restaurant kitchens in the USA, while, for Camelina, the average data between Europe, the USA, and Canada were considered. Therefore, it seems reasonable that the results also depend on the local cultivation techniques provided within each state, soil and climate conditions, growing season, energy mix, land use, water consumption, and raw material transport. For example, concerning Soybeans, the literature study shows that different environmental and geographic characteristics of a production site, such as rainfall [63], temperature [64], photoperiod [65], or altitude or latitude [63] have significant effects on the need for more or fewer inputs, which is ultimately reflected in the sustainability of its production. In particular, temperature plays a crucial role in regulating plant growth and development, and, for example, in the case of Soybean, 1 °C more could reduce its yield by −17% [66]. But results could also vary depending on, for example, the energy mix used. Within this study, Soybean is produced in the United States, just as the extraction and conversion of all raw materials are carried out in the U.S. Here, 60% of the electricity mix comes from fossil fuels, 19% from nuclear power, and about 21% from renewable energy sources [67]. This could push the results upward, especially in terms of global warming and ionizing radiation (which depend on whether nuclear power is used or not). Then, there is the factor related to the cost of energy, which is central to SAF conversion processes and which can vary widely among regions. Regions with access to low-cost renewable energy sources (e.g., solar, wind, hydro) may have an advantage in producing SAFs more cheaply. Palm has a remarkable capacity to produce large amounts of vegetable oil in a small, cultivated area, which is why it has become the top choice as an agricultural crop in Malaysia. This could be especially useful because Malaysia has limited agricultural land and, at the same time, needs to preserve its tropical forests. However, being a labor-intensive type of cultivation, there remain social issues, as also shown by Haryati et al. (2022) [68], which will be further explored in a future study. Finally, the availability and quality of infrastructure, such as transportation networks, processing facilities, and storage capacity, could affect the overall efficiency and profitability of SAF production. Therefore, in light of the above, it is reasonable to assume how the results of this study could still vary based on regional differences in biomass availability, feedstock composition, energy costs, infrastructure, and local environmental and economic conditions.

4.2. Sensitivity Analysis

Data from the SA are shown in Supplementary Materials, in Table S1, while the reduction in environmental impacts is shown in Figure 3, Figure 4 and Figure 5. For food raw materials, as shown in Figure 3, the S2 scenario could be the one that generates a substantial environmental benefit. For example, in the case of Camelina, there could be a reduction in impacts in 13 out of 18 impact categories, except the categories related to macro-area toxicity and land use. This is true for all remaining biomasses. This could be due to either the mining of mineral raw materials or, as also shown by Stolz et al., (2017) [69], the disposal of waste associated with the production of PV panels and their transport, all of which affect carcinogenic and non-carcinogenic toxicity. Considering the GWP, the impacts of Camelina production could be reduced by −43% (S1) and −61% (S2) compared to the baseline scenario, from 19.14 g CO₂ eq to 13.35 g CO₂ eq (S1), down to 11.88 g CO₂ eq (S2). Overall, environmental impacts could be reduced from a minimum of −2% (FEP) to a maximum of −150% (FRS) in the case of S1 and from a minimum of −9% (SOD) to a maximum of −233% (FRS). However, as can be seen from Figure 3A–D, there could be a general reduction in impacts for all food biomasses, except for the categories associated with toxicity. On the other hand, for non-food raw materials (Camelina), on average, except for the values in the toxicity category, there could be environmental benefits in all impact categories, with reductions ranging from a minimum of −30% (Marine Eutrophication) to a maximum of −93% (Ionizing Radiation) (Figure 4). GWP could be lowered by −75% in S2, going from 24.02 g CO₂ eq to 5.97 g CO₂ eq. Therefore, considering a renewable energy carrier and a source of solar electricity, Jatropha could be an excellent biomass in terms of produce SAFs. In fact, unlike biomass for food use, Jatropha curcas could pose some interesting advantages. First, it is a rustic, highly drought-resistant crop that can adequately grow in marginal lands [70], thus in regions characterized by unfavorable soil and climate conditions (poor soil quality, low rainfall). This could lead to the recovery and valorization of inland areas, where it is almost impossible to carry out agricultural activities that can be competitive in commodity markets, and thus to the improvement of farmers’ income by supporting bioenergy production. Furthermore, Jatropha has a rather fast production cycle and a long production period (up to 50 years) in addition to the fact that its seeds are toxic to humans and animals, which is why it is used for medical purposes but not for food [71].

Therefore, Jatropha curcas could have the advantage of not competing, both in terms of land and production, with the agri-food sector and could therefore be an attractive option for producing SAF. However, its actual commercialization as an aviation fuel still faces some critical issues, e.g., that it has a higher viscosity than diesel due to its high molecular weight [34]. On the other hand, concerning the waste raw materials WCO and Tallow, the results of the sensitivity analysis (Figure 5) show that environmental benefits could be achieved for both biomasses. With tallow (Figure 5A), by way of example, there are reductions of −91% for GWP, with values ranging from 63.50 g CO₂ eq/MJ to 46.75 g CO₂ eq/MJ (S1) to 5.13 g CO₂ eq/MJ (S2). Likewise, there are reductions of −95% for IR (with values as low as 0.0005 g CO₂ eq/MJ for S2). Finally, there are reductions of −97% for FRS (from 51.52 g Cu eq/MJ to 47.08/MJ in S1, then down to 1.08 Cu eq/MJ in S2). Regarding these two waste biomasses, in the case of Tallow, there could be environmental benefits overall in 12 out of 18 impact categories.

In contrast, in the case of WCO (Figure 5B), the reduction could be in 15 out of 18 impact categories, with reductions in impacts of up to −97% for FRS (from 24.34 g Cu eq/MJ, down to 22.40 g Cu eq/MJ for S1 and 0.63 g Cu eq/MJ for S2). The GWP, one of the values that could be of most interest to the aviation industry, could go from 29.40 g CO₂ eq/MJ to 22.11 g CO₂ eq/MJ (S1) and 3.12 g CO₂ eq/MJ. In this case, therefore, the results of the sensitivity analysis partly reverse the results of the LCA, as they show that producing SAFs from waste biomass could be an environmentally compatible option if part of the energy comes from sustainable energy carriers such as biomethane and renewable sources such as photovoltaic energy. However, as in the case of Jatropha, there persist problems with the rather low yields of these precursors. Finally, two further issues continue. Indeed, although there are environmental benefits in most of the impact categories for all the biomasses considered, it is interesting to note that, in some cases (e.g., Jatropha, Rapeseed, and Camelina), the use of renewable energies poses problems related to toxicity, depletion of mineral resources, and land use. Most likely, the database and the software used in the calculation of the results also consider the hard commodities used for PV generation. Indeed, the impacts of the three impact categories are linked. The extraction of the minerals that provide the raw materials to sustain our economies (including silicon and copper) are among the main sources of toxic waste because their extraction process involves the excavation of large quantities of rocks, which are discarded and stored in tailings with associated acid drainage.

This occurs when run-off water encounters rocks containing pyrite, resulting in sulphuric acid and iron-rich water, generating groundwater and surface water contamination [72]. In addition, the extraction of mining raw materials causes a large land use (LU) due to the mine itself (expanding increasingly to biodiversity-rich ecosystems) and waste dumps [73]. However, while some critical issues related to waste management remain, it is important to emphasize that, even in the long run, the use of electricity from renewable sources is fundamentally more efficient than the use of fossil fuels and the environmental benefits still outweigh the impacts, with improvements being seen in several impact categories. In this respect, however, mining technologies and the management of PV waste should improve.

5. Conclusions and Future Perspectives

The key findings of this research can be summarized as follows:

• Considering a trade-off between energy yield and environmental impacts, the two potentially most favorable biomasses for SAF production could be Camelina and Palm, as they show minimal environmental impacts in 4 and 7 out of 18 impact categories, respectively, with yields of 98% and 68%.
• Soybean appears to be the least sustainable precursor due to the large number of inputs for its production.
• SAF production from biomass could reduce GWP compared to fossil fuel by 2.8–3.6 times (WCO), 1.27–1.66 times (tallow), 4.6–5.8 times (Palm), 3.4–4.3 times (Jatropha), 1.05–1.32 times (Rapeseed), and 4.36–5.5 times (Camelina), demonstrating the good environmental impact of these pathways.
• By using a share of solar energy and a renewable vector such as biomethane, environmental impacts are reduced for all biomasses considered in 12–13 impact categories, except toxicity categories. However, while issues related to the extraction of raw materials to produce photovoltaic panels remain, the benefits still outweigh the environmental impacts.
• Producing SAF from waste biomass could be an environmentally compatible option, as they would produce rather low environmental impacts, in the order of 5.13 g CO₂ eq/MJ for Tallow and 3.12 g CO₂ eq/MJ for WCO. Moreover, being waste biomass, they would not compete with the agri-food sector, as would be the case if SAFs were produced from Rapeseed, Camelina, Palm, etc. However, part of the energy would have to come from sustainable energy vectors, although, as in the case of Jatropha, there are still problems with the rather low yields of these precursors.

Therefore, the most obvious advantage of SAF lies in the significant reduction in carbon emissions in their life cycle compared to traditional fuels. Furthermore, the amount of CO₂ emitted during the combustion of the new fuels in aircraft engines roughly balances out with the CO₂ absorbed by plants during the growth of the biomass used. This could lead to a decrease in overall CO₂ emissions from the aviation sector. In addition, commercial airlines could exploit SAFs as a valuable promotional tool to attract passengers. Finally, a further strength of SAFs relates to energy security and future independence. A diverse range of energy sources, including combinations of conventional fossil and renewable fuels, could mitigate potential disruptions in trade and national security due to future uncertainties. However, SAF production could translate into new employment opportunities, especially in rural regions abundant in raw materials needed for their production. On the other hand, several challenges hinder their growth and expansion, e.g., from a biomasses availability perspective, the fact that some biomass may compete with the agri-food sector, effectively taking away the availability of inputs and allocating food toward non-food production, in effect exacerbating food insecurity. There are also challenges related to the loss of forests and pastures, increased food prices, increased water consumption and increased shadow prices, and increased nitrogen consumption. On the other hand, for waste biomass, there remain issues associated with large-scale biomass supply as well as its energy density. From a process perspective, however, the lack of maturity of fuel routes is a significant obstacle. In addition, limited support from local governments and international organizations to facilitate the transition from fossil fuels to renewable fuels is another barrier. We must also consider the high production costs of SAFs, which, due to low production levels, are still not economically competitive. This conjunction of problems contributes to undermining the economic viability of SAFs. Without addressing these challenges, and without a clear economic pathway, there is a risk that decarbonization efforts will slow down and that the sector will fail to meet its targets for the coming decades. The high cost of SAFs presents a further disadvantage, as airlines would be forced to pass on part of these expenses to passengers through higher fares. In this context, it is crucial to raise public awareness of new technologies, as social acceptance of such innovations is closely related to their adoption. Lack of awareness may undermine the willingness to pay, jeopardizing the success of the entire innovation process. Public perception of the benefits (such as reduced emissions and independence from fossil fuels) and concerns (such as competition with food supply and impacts on ecosystems) will play a crucial role. The greater the trust in the institutions and promotional efforts of SAFs, the greater the willingness to pay. Apart from the challenges listed above, which open up future research directions related mainly to production process efficiency, yield, and biomass availability, the relative ease of implementation of SAFs could enable a relatively smooth transition from conventional fuels, making it a reasonably viable solution even now. The challenge is that the SAF market remains trapped in a dead-end spiral where demand is suppressed by high prices and investment could stagnate. Without investment, SAF production will not increase to reach the levels needed to achieve economies of scale, which is why prices will most likely remain high. From this perspective, the quickest way is for central governments to intervene and implement policies to increase SAF production. However, nothing is simple, and governments must be cautious when intervening in markets. For now, however, SAFs remain a promising environmentally friendly option.