Climate-neutral aviation: will it fly?

doi:10.21203/rs.3.rs-2185970/v1

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Climate-neutral aviation: will it fly?

https://doi.org/10.21203/rs.3.rs-2185970/v1

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published 06 Jul, 2023

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The aviation sector must substantially reduce its climate impacts to reach net-zero goals. Such a reduction, however, must not be limited to flight CO₂ emissions, since such a narrow focus leaves up to 80% of climate impacts unaccounted for – especially with further growth of air traffic. This study – based on rigorous life-cycle assessment combined with a time-dependent quantification of non-CO₂ climate impacts – shows that both electricity-based synthetic jet fuels and compensating climate impacts via direct air carbon capture and storage (DACCS) can enable climate-neutral aviation. However, with a continuous increase in air traffic, synthetic jet fuels produced with electricity from renewables would exert excessive pressure on economic and natural resources, while compensation via DACCS would require massive CO₂ storage volumes and prolong dependence on fossil fuels. Hence, the idea of a climate-neutral aviation will fly only if air traffic decreases to reduce the scale of climate impacts to mitigate.

Earth and environmental sciences/Environmental sciences/Environmental impact

Physical sciences/Energy science and technology/Carbon capture and storage

Physical sciences/Energy science and technology/Energy modelling

Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation

Today, aviation causes 2.5% of the world’s CO₂ emissions¹. Although the last two decades saw a 2% annual improvement in aircraft fuel efficiency², CO₂ emissions kept growing due to a 4% increase in annual demand, doubling aviation’s contribution to global anthropogenic CO₂ emissions (barring temporary reductions caused by Covid-19 pandemic)³. Besides flight CO₂ emissions, aviation contributes to climate change through “non-CO₂ effects” in the atmosphere⁴ via release of short-lived climate forcers (SLCF). Although associated with large uncertainties, the understanding of non-CO₂ effects has improved over the years, allowing characterization of the relationship between atmospheric SLCF emissions and increase in radiative forcing (RF) with acceptable accuracy (see Lee et al.⁴ and Allen and co-workers^5–8 for the relevant state-of-the-art).

The European Commission acknowledges the need for policies targeting aviation’s full climate impacts⁹; a recent analysis it commissioned¹⁰ suggested ways to regulate non-CO₂ effects. Yet they are rarely considered in policy and roadmap documents, misestimating the effort needed to reduce the aviation contribution to climate change. Mitigation relies on improving air traffic management, producing larger, more fuel-efficient aircrafts, introducing sustainable aviation fuels, and compensating for any leftover effect. In the roadmap “Destination 2050”, EU-based aircraft manufacturers, airports and airlines aim at cutting CO₂ emissions by 92% by 2050, while compensating the rest through, e.g. carbon removal projects². Other national¹¹ and international^12–16 organizations, and some airlines^17,18, follow a similar approach. However, these neither include non-CO₂ effects nor underline the need for low-carbon electricity for synthetic jet fuels to become climate-neutral^19,20. Furthermore, a recent report reveals that none of the efficiency or alternative fuel-related targets expressed by the industry in the last two decades has ever been met²¹. Furthermore, the effectiveness of some of the carbon offset schemes may be questioned²² as in practice non-reversibility and avoidance of double-accounting of carbon credits are often not ensured^23,24.

As the European Union actively develops initiatives to decarbonize aviation, e.g. ReFuelEU²⁵, first, we assess the climate impact of a fossil-based European aviation fleet over the 2018–2100 period under different socio-economic pathways and demand evolution scenarios. Second, we explore the potential of two technology options to limit aviation’s climate impact and to meet different mitigation scopes: CO₂ removal (CDR) and use of synthetic fuels. Finally, for each technology option, we quantify the associated life-cycle costs, energy, and natural resources needs. We find that failing to consider the climate impact caused by the production of synthetic fuels from a life cycle perspective, as in two recent papers^26,27, would neglect about half of the total impact caused by a growing European fleet. Furthermore, unless demand is reduced, fully and truly offsetting aviation’s climate impact in the future will require an important use of resources, whether synthetic jet fuel is used or not.

Main

Beside the reference scenario where European aviation relies exclusively on fossil jet-fuel, we consider two technology options, i.e., mitigation approaches, that can be deployed to reduce climate impact: (a) CO₂ removal performed by Direct Air Capture (DAC) and permanent geological storage of CO₂ (aka DACCS) to offset aviation’s climate impact for a fossil-based fleet (Fig. 1a); (b) syn-jet fuel (short for synthetic jet fuel), produced from CO₂ captured from air (i.e., DAC with CO₂ utilization, i.e. DACCU) and hydrogen synthesized through water electrolysis, with the remaining impacts offset by DACCS (Fig. 1b). Like the EC-proposed ReFuelEU initiative, we assume that syn-jet fuel is initially blended with conventional jet fuel, with a volume percentage of 5% in 2030, 63% in 2050, and finally 100% in 2063 (i.e., + 2.6% per year). As we focus on DAC-based approaches, other sustainable aviation fuels (e.g., bio-²⁷ and solar-jet fuels²⁸), though worth further investigation, are beyond the scope of this work.

To highlight the relevance of non-CO₂ effects in designing measures to reduce the climate impact of the European aviation fleet, we consider three scopes of mitigation over the second half of the century: (i) flight-CO₂ neutrality, where flight-CO₂ emissions only and greenhouse gas (GHG) emissions due to the mitigation approach itself are eliminated (1 and 5 in Fig. 1a); (ii) warming neutrality, achieved by mitigating any increase in climate impacts with respect to 2050 levels (1 to 5 in Fig. 1a, and 2 to 5 in Fig. 1b); and (iii) climate neutrality, achieved by mitigating all climate impacts caused by the fleet from 2018 onwards (1 to 5 in Fig. 1a; 2 to 5 in Fig. 1b). While climate neutrality implies that the total radiative forcing (RF) caused by the fleet is brought to net-zero after 2050 onwards (with respect to 2018), warming neutrality only requires that the forcing is stabilized at the 2050 level.

Furthermore, we consider three different air-traffic demand trajectories, assuming the European aircraft fleet reaches and exceeds its pre-Covid-19 level by 2024. There is consensus within the industry about this²⁸, but also the chance that the Covid-19 pandemic may have profound, irrevocable behavior-changing effects on air travel’s future demand²⁹. The European air-traffic demand trajectories considered from 2025 after the post-Covid recovery onwards are: (i) growing demand, whereby the European air traffic, in terms of kilometers flown, converges towards a 2% annual growth rate; (ii) stationary demand, whereby European air traffic stabilizes shortly after 2024; and (iii) declining demand, whereby global air traffic reduces at the annual rate needed to achieve warming neutrality without using carbon dioxide removal (CDR). Furthermore, we consider two future socio-economic pathways (“climate scenarios”) to project future LCA-based GHG emissions embodied in electricity, materials and services: a scenario in line with the Paris Agreement objectives (i.e., SSP 2-RCP 2.6), aiming at a global temperature increase below 2°C by 2100 compared to pre-industrial levels, i.e. the 2°C scenario; and a baseline scenario (i.e., SSP 2-RCP 6), corresponding to a global temperature increase of approximately 3.5°C by 2100 compared to pre-industrial levels, i.e. the 3.5°C scenario. These scenarios offer a wide range of projected cumulative GHG emissions by 2100, which are plausible and consistent with the emissions growth rates of the past two decades³⁰. Both climate scenarios consider, to a different extent, the expected improvements in aircraft light-weighting, engine efficiency, seating capacity and occupancy, but also the progress in other sectors like electricity and syn-jet fuel production, until 2050. No further advancements are considered thereafter due to limitations and uncertainty in projected performances, except for the electricity mix which is projected until 2100 (see Methods for details and values). We exclude other potentially impactful innovations (e.g., improved air traffic management, notably to avoid ice supersaturated regions^31,32), revolutionary aircraft designs, biomass-based alternative fuels³³, hydrogen-powered aircrafts^34,35, and battery electric aircrafts³⁵. We report the results for the 3.5° C scenario in the following, and those for the 2° C scenario in Extended Data Figures.

For each scope of mitigation, air-traffic demand trajectory, and climate scenario, the performance of the two technology options is assessed in terms of emission of climate forcers, total RF, and CDR requirement for the European fleet. Furthermore, their impacts on resources (costs, electricity, geological CO₂ storage capacity, and land and freshwater use) are quantified using a life-cycle environmental and cost assessment model, based on previous studies^29,30.

In the following, we distinguish flight emissions (emissions 1 and 2 in Fig. 1) from surface emissions (emissions 3, 4 and 5 in Fig. 1), with the latter caused by the supply of infrastructure, aircrafts, fuel (fossil or synthetic), and by DACCS operation. Surface emissions include CO₂ but also SLCF such as methane, hydrogen, and various refrigerants (CFCs, HCFCs, HFCs). Flight emissions include CO₂ and SLCF such as Sulphur oxides, black carbon, and water vapor released in the troposphere (i.e., below 9,000 m), nitrogen oxides released in the stratosphere (i.e., above 9,000 m), and the formation of cirrus clouds. Atmospheric lifetimes and radiative efficiencies of surface forcers are sourced from Chap. 7 of the IPCC AR6 WG1 report³⁶, while those for flight forcers from Lee et al.⁴. The RF of both types of emissions is calculated via the linear impulse-response model, except for cirrus clouds, whereby we apply an empirical relationship to correlate the kilometers flown to the cirrus-induced RF, following the literature^4,26. However, unlike these studies which use the so-called GWP* metric introduced by Allen and colleagues^5,6,37,38, the warming contribution of flight and surface emissions is expressed as timeseries of CO₂ emissions that would cause identical warming through the Linear-Warming-Equivalent (LWE) method, introduced by Allen et al.⁷, which is both exact and metric independent. The amount of CO₂-LWE to sequester to compensate for the warming caused by SLCF emissions is calculated by inverting the linear impulse-response model routinely used for metrics calculation. We present this approach in detail in Radiative forcing and warming contribution of emissions. Another significant difference with the approach used in Brazzola et al.²⁶ is that we consider the life-cycle emissions of CO₂ and SLCF related to the manufacture of the aircrafts, infrastructure (e.g., airport), fuel (including electricity), as well as to DACCS operation. Applying the method of LWE to a timeseries of emissions calculated by prospective life-cycle assessment is in itself a novel approach.

Conventional jet fuel vs. Synthetic jet fuel

We analyze two scenarios, in which the European aviation fleet relies either on fossil-based jet fuel (Fig. 2), or on syn-jet fuel with a blend volume percentage increasing from 5% in 2030 to reach 63% in 2050 and 100% by 2063 (Fig. 3). In both cases, DACCS is deployed to mitigate the remaining contributions to climate change. The syn-jet fuel is produced through Fischer-Tropsch synthesis, fed by hydrogen (H₂) from water electrolysis and carbon monoxide (CO) from the reverse water-gas shift reaction using CO₂ from DAC – further information on the relevant processes is given in Methods.

Growing air-traffic demand. Despite higher fuel efficiency and larger seating capacity and occupancy than today, a fossil-based fleet growing at its average historical rate unmitigated will directly emit 24 GtCO₂ during the 2018–2100 period (Fig. 2.a), while SLCF would cause over two thirds of the RF (Fig. 2.d). By 2100, unmitigated emissions of CO₂ will increase three-fold relative to 2018 (Fig. 2.d). Using low-aromatic, hydrogen-rich syn-jet fuel appears attractive as it avoids flight-CO₂ emissions of fossil origin (Fig. 3.a), while reducing soot and ice particle formation at high altitude in ice supersaturated regions (based on data extrapolation from Ref. ³⁹). This reduces the cloudiness and lifetime of cirrus clouds, and their associated effective RF by 65%⁴⁰. Overall, the use of 100% syn-jet fuel reduces the fleet-induced climate warming by one third in 2100, as opposed to using jet fuel (Fig. 3.d). In addition to stabilizing the contribution of flight-CO₂ to the total RF after 2063, the increase of syn-jet fuel share in the blend decreases flight SLCF emissions (Fig. 3.a). Unfortunately, this positive effect is cancelled out by the increase in fleet activity, resulting in a growing share of RF due to SLCF emissions (Fig. 3.d). Furthermore, the forcing caused by surface CO₂ emissions increases linearly until 2100 (Fig. 3.d), as the annual production of syn-jet fuel increases from 110 billion liters in 2063 to 205 billion liters, mainly due to electricity consumption for DAC and H₂ production, despite the reduction in the carbon intensity of the energy mix (i.e., from 130g CO₂/kWh in 2050 down to 30g CO₂/kWh in 2100). Furthermore, H₂ leaks, represented by a 1% mass loss related to venting, storage and boil-off along the supply chain⁴¹, also contribute to the overall forcing induced by a syn-jet fuel-based aviation by extending the atmospheric lifetime of methane⁴² (Fig. 3.d, Surface-others).

Should mitigation measures be deployed, the amount of CO₂ to sequester via DACCS would vary largely depend on the mitigation scope and would be lower for the fleet relying on syn-jet fuel (Figs. 2.g and 3.g). Regardless of the fuel, achieving climate neutrality from 2050 onwards implies an important removal the first year (2050) to offset the cumulated RF caused by aviation between 2018 and 2049. This is difficult in practice, and the use of CDR could start before 2050 to avoid such peak. It is followed by an increasing removal effort due to the raising RF induced by the fleet. Pursuing warming neutrality would reduce the CDR effort needed over the 2050–2100 period by 50% (jet fuel) to 60% (syn-jet fuel), stabilizing the Global Mean Surface Temperature (GMST) increase caused by the fleet to ca. +0.015° C (Figs. 2.d and 3.d). Most importantly, failing to consider the additional RF caused by the production of syn-jet fuel from a life cycle perspective, as in Brazzola et al.²⁶, would neglect about half of the impact caused by a growing European fleet activity (Figs. 3.d). This holds true, although to a lower extent, in a more climate-ambitious scenario, where the electricity is already decarbonized by 2030–2040 – see Figure E.2, Extended Data Figures. Mitigating solely flight-CO₂ emissions would require a significantly smaller CDR effort but would leave most of the climate change impacts unmitigated. Additionally, in the case of syn-jet fuel, as its share in the blend increases, the decrease in the RF caused by cirrus clouds (based on Refs. ^39,40) more than compensates for the warming caused by other forcers, resulting in a net negative amount of CDR (Fig. 3.g).

The GHG emissions associated with electricity supply for DACCS operation increase the overall CDR requirement by 36% in 2050, but this decreases to 5% by 2100 as the electricity decarbonizes (see difference between dashed and solid lines in Figs. 2.g and 3.g).

The uncertainty around the RF caused by non-CO₂ effects is significant, as discussed by Lee at al⁴ and represented in Figs. 2 and 3 by the large error bars, which are obtained from the 5th and 95th percentile values of the effective RF indices for each non-CO₂ effect, also from Ref ⁴. Most of the spread stems from the uncertain time- and location-dependent effect of cirrus clouds formation. In this respect, the more recent work of Digby et al.⁴³ indicates a lower central estimate for the RF of cirrus clouds formation, while maintaining equally important uncertainty ranges. Consequently, climate- and warming-neutrality exhibit wider uncertainties than flight CO₂-neutrality: the CDR requirement scales with the uncertainty associated with non-CO₂ effects, which are left unmitigated in the case of flight CO₂-neutrality, as shown by the shaded areas in Fig. 2.g and 3.g.

Stationary air-traffic demand. Stabilizing the fleet activity at the 2024 level results, in the second half of the century, in a constant forcing caused by SLCF (mostly cirrus and NO_x) and an increasing forcing from CO₂ (either flight- or surface-CO₂), because CO₂ cumulates (Figs. 2.e and 3.e). The climate impacts of the fossil- and syn-jet fuel-powered European aviation fleets decrease in 2100 by 60% and 50%, respectively, with respect to the growth scenario

As the net contribution of aviation to climate change reduces, the need for compensation via DACCS to achieve climate neutrality decreases as well, for both fuel options (Figs. 2.h and 3.h). Under the scenario of a fossil-based fleet, flight-CO₂ and warming-neutrality mitigation targets tend to converge as the forcing caused by SLCF is kept at the 2024 level, and thus require a similar amount of CDR (Fig. 2.h). By using syn-jet fuel, warming neutrality is achieved as soon as 2050 without the need for DACCS, thanks to the stabilization of the fleet activity (Fig. 3.e). Indeed, the RF caused by the European fleet decreases with respect to 2050, resulting in a negative CDR requirement if warming neutrality is pursued. However, as the fleet relies exclusively on syn-jet fuel from 2063 onwards, the cooling effect of the decreasing RF from SLCF is counterbalanced by the increase in surface CO₂ emissions due to fuel production (especially hydrogen synthesis). Similarly, flight-CO₂ neutrality is achieved after 2050 solely using syn-jet fuel without the need for DACCS, owing to the constant fleet activity after this onset year (Fig. 3.e).

Declining air-traffic demand. A limited decline in aviation activity (i.e., kilometers flown) of up to 0.8% per year if the fleet is powered by jet fuel would eliminate the need for CDR to reach both flight-CO₂ and warming-neutrality (Figs. 2.i and 3.i). Such decline could be limited to 0.4% per year if the fleet uses syn-jet fuel instead. The decline in SLCF emissions would counteract the additional RF caused by the accumulation of CO_2, with respect to 2050 (Figs. 2.f and 3.f). The cooling effect (with respect to the onset year) caused by the fall in SLCF emissions would effectively act as an offset mechanism for CO₂ emissions. For warming- and flight-CO₂ neutrality, DACCS need is virtually eliminated thanks to the continued decrease of SLCF emissions (mostly reduced formation of cirrus clouds). On the other hand, climate neutrality cannot be achieved through demand reduction measures alone and requires a large amount of CDR the first year (2050) to compensate for the RF cumulated between 2018 and 2049, followed by a decreasing CDR rate to compensate for newly emitted forcers, to an extent similar to the Stationary scenario (Figs. 2.i and 3.i).

Climate-neutral European aviation and resources

Although syn-jet fuel and DACCS could offer feasible climate impact mitigation pathways for the aviation sector, Fig. 4 puts these options in the context of resources needed.

If growth in air-traffic demand is sustained, using syn-jet fuel combined with DACCS would require substantial amounts of resources, among which deeply decarbonized electricity (i.e., with a carbon intensity of 30 gCO₂/kWh in 2100). To achieve climate neutrality, almost 80 times the electricity production of the European Union in 2020⁴⁴ (i.e., 2,600 TWh) would be needed cumulatively between 2018 and 2100 (~ 200,000 TWh) – but mostly during the second half of this century, and predominantly for hydrogen production. In other words, 1.6 times the current annual production of electricity in the EU-28 would be needed each year between 2050 and 2100. The cumulative abstraction of freshwater and use of land between 2018 and 2100 would also reach unreasonable levels: over between 200 and 250 million hectares-year of land would be required, while the freshwater needed would correspond to one time the annual consumption of the EU-28. Most of the use of land and freshwater stems from renewable electricity production (i.e., solar, wind, biomass and hydropower plants), despite considering efficiency improvements in the LCA database – e.g., the area occupied by PV panels per kW installed decreases by 50% between 2020 and 2050 to reflect the expected increase in the conversion efficiency; such footprints could be partially reduced by using an alternative low-carbon electricity mix, but at the risk of impacting other resources. Such massive demand for decarbonized electricity, land and freshwater suggests that the entire large-scale syn-jet fuel supply for Europe cannot be produced domestically. On the other hand, using (fossil) jet fuel and offsetting the climate impacts via DACCS would decrease the use of electricity, land, and freshwater by 50 to 60%, relative to using syn-jet fuel complemented with DACCS. However, this would prolong our dependance on fossil energy and require a CO₂ storage capacity larger than the proven storage capabilities of the Norwegian North Sea. This CO₂ storage capacity may turn out to be a limited resource, due to both limitations in scale-up and competition for CO₂ storage space with other hard-to-decarbonize sectors⁴⁵. Under the 2° C scenario, land occupation increases (i.e., higher share of supply from renewable energy plants and use of biomass-based power), whilst the abstraction of freshwater decreases (i.e., among other reasons, less cooling water is used, as the share of combustion-based power plants decreases). Moreover, the CO₂ storage requirements are lower: a low-carbon electricity helps decrease the amount of CO₂ to mitigate from the production of fuel and the operation of DACCS. Finally, using (fossil) jet fuel rather than syn jet-fuel and offsetting the climate change contribution with DACCS is less costly across mitigation scopes (despite accounting for cost reductions due to learning-by-doing). However, as the mitigation scope becomes more stringent (i.e., warming-neutrality), the differences in costs between the two fuel options disappear. In fact, the climate scenario seems to be a stronger determinant for costs than the fuel option. Reducing the demand for air-traffic should be a priority as it significantly decreases the amount of resources needed, regardless of the climate scenario or technology option considered.

This study quantifies the efforts needed to mitigate the contribution of the European aviation fleet to global warming. Over the 2018–2100 period, our results agree on two points with the recent findings of Grewe et al.46 and Klöwer et al.8. First, given their significance non-CO2 effects – particularly those triggered by NOx emissions and cirrus clouds formation – should be considered when laying out plans to reduce aviation’s contribution to climate change. It is, however, important to acknowledge the significant uncertainty surrounding their RF potential. For example, the recent work of Digby et al.43 suggests that the warming effect of cirrus clouds may be lower than the estimate used in this study. Second, the non-CO2-to-CO2 warming effect ratio increases as the aviation sector grows. Furthermore, our results also agree with the findings of Brazzola et al.26: there is some ambiguity around the notion of “net zero” put forward by the different roadmaps and agendas. This ambiguity may be misleading: “net zero” in terms of flight CO2 emissions only superficially tackles the GMST increase caused by the fleet, while “net zero” in terms of climate impacts implies the deployment of resources to an extent not fully understood until now.

Generally, the extent to which CDR and resources are needed depends on three factors.

First and foremost, the mitigation scope: simply offsetting flight-CO2 emissions requires limited or no CDR and may be achieved by adopting syn-jet fuel produced from CO2 captured from air only. Yet, unless this fuel is produced with fully decarbonized electricity, such a mitigation scope appears ill-defined as it would simply move CO2 emissions upstream, to the stage of fuel production. And most importantly, this would only avoid ~ 20% of the GMST increase by 2100. Achieving warming- or climate-neutrality, that is offsetting any additional contribution to global warming with respect to an offset year (i.e., 2050 in our analysis) or offsetting any past and future contribution to global warming with respect to the offset year, respectively, would require a major use of CDR as well as of natural, energy and economic resources. On the other hand, this would indeed limit the increase in GMST by 2100 to ~ 50–60% and to 5%, respectively, of its value if unmitigated.

Second, the technology option deployed matters: using syn-jet fuel can result in a lower requirement for CO2 storage, but only if produced with low-carbon electricity. Hence, using synthetic jet-fuel depends on adding low-carbon power generation capacities.

Third, the CDR and resource requirement depends on the air-traffic demand trend and on the contribution of non-CO2 effects: mitigating the climate impact of the European aviation fleet with DACCS will be extremely resource intensive unless demand-reduction measures are adopted. Such measures would lead to a decrease in non-CO2 effects (i.e., a cooling effect relative to the current warming induced by aviation) that compensates for the continued accumulation of aviation CO2 emissions, to an extent where CDR may not even be required to achieve flight-CO2 or warming neutrality. However, this only holds true if demand decreases. Once a new, albeit reduced, stationary demand level is attained, the “cooling” effect caused by the downward emission trend of short-lived climate forcers (i.e., non-CO2 effects) wears off and CDR is required again to compensate for the warming caused by CO2 emissions.

In summary, if aviation growth is sustained, fully mitigating the climate impacts caused by the European aviation sector this coming century will simultaneously require CDR and major amounts of energy, natural and financial resources – despite (i) avoiding flight-CO2 emissions of fossil origin by using synthetic jet fuel, (ii) technical and economic improvements in aircrafts and fuel production, (iii) de-carbonized energy supply and (iv) considering lower bound levels for non-CO2 effects. Thus concluding, reducing air-traffic demand is a good short- to mid-term solution, as it drastically reduces the scale of the environmental and economic effort needed to limit the impact of aviation on the climate and gives society time to develop longer-term sustainable solutions.

General workflow

The European air-traffic demand trajectories are modelled between 2018 and 2100, based and extrapolated from the Destination 2050 report projections for demand² in the case of the growing trajectory, to derive the flown distance and amount of passengers to transport over the period. Considering this, an iterative spreadsheet-based model that combines both life-cycle energy and material inventories and costs (available as part of the Supplementary Information material) is used to dimension the aircrafts of the European fleet, calculate the emissions during take-off, climb, cruise, descent, and landing, as well as the requirements in terms of fuel supply, infrastructure and aircraft production and associated emissions and resource impacts. The RF contribution of surface and flight emissions are calculated for the three different demand trajectories, two fuel options and two socio-economic pathways for future development of the economy (“climate scenarios”). The requirement in terms of CDR (i.e., DACCS in this case) is calculated iteratively to attain the mitigation scope and mitigate the emissions of its own operation.

Life-cycle environmental and cost modelling

At the center of the framework used to produce results is the life-cycle model present in the spreadsheet that supports this study. The model calculates the required material, energy flows and related emissions directly and indirectly needed to support the different life cycle stages of a flight. The life-cycle stages considered include the aircraft manufacture and maintenance, the construction of the airport, the production and distribution of the fuel (i.e., conventional jet fuel and syn-jet fuel), the operation of the mitigation chain (DAC and CCS) as well as the aircraft operation itself (i.e., take-off, climb, cruise, descent, and landing). Note that the End-of-Life processing of the aircraft is not considered. The model derives material, energy, resource, emissions, and costs indicators based on a set of parameters: the flight distance, the fuel blend, the aircraft type, the year of manufacture (and operation), the occupancy as well as the climate scenario considered. The results are further normalized by the flight distance and the passenger occupancy, to derive indicators on a passenger-kilometer basis, then multiplied by the overall demand expressed in passenger-kilometers. Such approach follows the principles of the ISO 14040 standard series⁴⁷ and ensures a standard accounting of material and energy use and related emissions that support the realization of a functional unit (i.e., the transport of a passenger over one kilometer).

The life-cycle model sizes the aircrafts based on the flight distance and year of construction (which conditions improvement factors to apply). Details are given in Aircrafts. The approach used to calculate in-flight emissions are described in Surface and flight emissions. The approach used to calculate the RF attributed to each surface and flight emission is presented in Radiative forcing and warming contribution of emissions. The emission rate of these emissions in the atmosphere depends on the fleet demand trajectory considered, which modeling is explained in European fleet scenarios. The approach used to calculate direct operating costs is explained in Costs. The remaining processes that fall outside of immediate scope of the aircraft life-cycle are modelled using a life-cycle inventory database. This database is adapted to the year of the aircraft production and operation, but also to the climate scenario considered. The approach used to adapt the life-cycle inventory database to a specific socio-economic-climate and temporal context is explained in Prospective life-cycle inventory database.

Life-cycle GHG emissions, costs and resource indicators are calculated for representative flights by broad destination departing from Europe (i.e., North America, South America, Africa, Middle East, Asia and intra-European flights). The destination type presets the altitude profile of the flight, notably the share of the fuel emissions released in the different strata of the atmosphere – see Air emissions. Longer flights tend to spend a higher share of the flight distance at high altitude than shorter flights: on an average Europe-Asia journey, 97% of the distance is flown above 9,000 m of altitude, against 85% for an average intra-European flight. This is important as the different non-CO₂ effects considered in this study occur in different altitude ranges, while CO₂ emissions have a constant and similar warming effect regardless of the emission altitude. The results on a per passenger-kilometer basis are multiplied by the demand for transport per destination in each air-traffic demand case, to obtain overall indicators for the European fleet.

European fleet scenarios and demand projection

European air-traffic scenarios are calculated for each demand trajectory, starting from 2018. European air-traffic is comprised of flights departing from the EU-27 as well as EFTA member states. The total transport demand in passenger-km by the year 2050 is estimated for the growing demand trajectory based on projections from the roadmap report “Destination 2050”². The report indicates an expected annual growth in terms of passengers of 2% until 2050: 1.4% annual increase in flights, combined with an increase in seating capacity and load factor of 0.3% both. We further assume a similar development over the 2050–2100 period. The roadmap report “Destination 2050” also gives a distribution of that demand per region of destination. Assuming an average distance for each of these destinations with Paris (FR) as a departure point and shown in Table 2, we derive the overall transport demand, in passenger-kilometers, based on the split of the traffic by destination. For the average distance of intra-EU flights, we refer to Ref⁴⁸.

An annual growth rate of zero is used for the stationary demand trajectory. Finally, the “negative” growth rate for the declining demand trajectory is defined as the minimum decline that allows avoiding the use of DACCS to reach warming-neutrality. This depends on the climate scenario and fuel technology considered. Note that we preserve the split of traffic by destination in the stationary and declining demand trajectories. Details on how the air-traffic demand is split by destination is provided under the “European fleet” tab in the spreadsheet model and plotted in Fig. E.3.

Table 1

Representative distances considered for each flight destination performed by the European fleet
Origin	Destination	Distance [km]
	Intra-EU	1,000
France (Paris)	North America (Chicago, Illinois, USA)	6,654
	South America (Manaus, Brazil)	8,306
	Africa (Bangui, Central Africa)	5,012
	Middle East (Iran)	4,538
	Asia (Beijing, China)	8,216

Aircrafts

Flights departing from Europe to each destination are modelled using generic average-performing aircrafts and flight altitude profiles, as described in Table 3. The aircraft model largely builds on and extends the work conducted by Cox et al.⁴⁹. Improvements in weight and aerodynamics are taken from Cox et al.⁴⁹, themselves sourcing from various projections^50–52 and are described in detail under the “Aircraft specs” tab of the spreadsheet model. The fuel consumption of the different aircrafts is calculated separately for take-off, climb, cruise and descent and appears to be quasi-linearly related to the mass, based on Ref.^49,53. Expected annual improvements in terms of fuel efficiency, seating capacity and load factor between today and 2050 are aligned with those from the Destination 2050 roadmap report ²: 0.6%, 0.3% and 0.3%, respectively, to reach a cumulative improvement between 2020 and 2050 of 20%, 9% and 9%. Further specifications on aircrafts used for modelling the European fleet activity are available under the “Scenarios” tab in the spreadsheet model. We do not consider further improvements regarding light-weighting, occupancy rate, and fuel consumption after 2050. Also, we do not consider the End-of-Life treatment of the aircrafts, as this life-cycle phase is known to have negligible impacts⁴⁹. Finally, it is relevant to mention that we do not consider the weighted age of the fleet but instead assume that the fleet is composed of new aircrafts: for example, the 2050 fleet is only composed of aircrafts manufactured in 2050, with the performances an aircraft in 2050 is expected to have. This is a simplification which leads to slight underestimation of the fuel consumption of the fleet. Indeed, the age of the European passenger fleet has been in the past ranging from 9 to 10.5 years old, according to Eurocontrol⁵⁴. At an annual 0.6% improvement in fuel economy, the fleet as modelled in this study is probably underestimating the fuel consumption (and related emissions) by roughly 5%.

Table 2

General European fleet aircraft specifications and altitude profiles per destination type.
Flight to	Aircraft type	Lifetime	Flight length	Operating weight			Seating capacity			Passenger-eq. occupancy*			Fuel consumption			Share of fuel burned above 9,000 m⁵⁵
		Million km	km	kg			unit			unit			Liter kerosene per occupied seat per 100 km			%
				2020	2030	2050	2020	2030	2050	2020	2030	2050	2020	2030	2050
Intra-Europe	Large, narrow body	50	1,000	48,200	47,800	49,000	115	118	126	94	100	113	3.8	3.4	2.8	72%
North America	Small, wide body	90	6,654	121,000	117,000	112,000	211	218	231	179	190	214	3.2	2.9	2.2	96%
South America	Long, wide body	115	8,306	187,800	180,500	170,700	305	314	333	251	266	300	3.4	2.9	2.2	97%
Africa	Small, wide body	90	5,012	93,600	90,900	87,200	178	183	194	146	155	175	3.1	2.8	2.2	95%
Middle East	Small, wide body	90	4,538	65,300	63,600	61,400	130	134	142	107	114	128	3.3	3.0	2.3	95%
Asia	Long, wide body	115	8,216	270,000	259,000	245,000	425	438	466	350	372	419	3.2	2.9	2.2	97%
*Includes freight, where 100 kg of freight = 1 passenger equivalent.

Surface and flight emissions

Surface emissions are based on the life-cycle inventories for the manufacture of aircrafts (i.e., including the production of steel and light-weighting materials, such as carbon fiber, aluminum, etc.), airports, the supply of conventional jet fuel and syn-jet fuel (i.e., including the generation of electricity) as well as the operation of the DAC and subsequent CO₂ storage. These inventories (and related emissions) are modified over time and across climate scenarios to reflect future policies towards renewables, technological improvements and learning rates for emerging technologies such as DAC. The source and assumptions behind the fuel supply and DAC operation are detailed in Fuel supply and DAC and CO2 storage. The following surface emissions emitted by the above-mentioned systems are considered: fossil CO_2, methane, hydrogen, HFC-152a, HCFC-140, HCFC-22, HFC-134a, R-10, HFC-125, CFC-11, HFC-143a and CFC-113.

Flight emissions are calculated following the approach of Cox et al.²⁹, during take-off, climb, cruise, descent, and landing. They are quantified based on emission factors provided by EMEP/EEA’s air pollutant emissions inventory guidebook⁵³. Although we model the emissions of 22 different substances, only the following substances are believed to have a potential direct or indirect forcing effect when emitted in the atmosphere⁴: nitrogen oxides, black carbon, sulfur oxides, water vapor, the formation of cirrus clouds as well as fossil CO₂. Improvements in emissions for certain substances are from the trends found in ICAO engine emission database⁵⁶. As such, we consider an annual reduction in the emissions of NO_x and SO_x of 0.6%, and 0.3% of black carbon per unit mass of fuel used (which itself also improves by an annual 0.6%). Emissions of water vapor are directly determined by the fuel consumption (i.e., ~ 1.2 kg water vapor per kg jet fuel). Emissions relating to take-off, climb, descent and landing are all assumed to occur below 9,000 m. Cruise emissions are further distinguished between the amount released below and above 9,000 m, where 9,000 m is used as a threshold value between the end of the troposphere and the beginning of the stratosphere. The amount of fuel consumed below and above 9,000 m is function of the flight distance and is derived from anonymized air traffic data⁵⁵ – see “Share of fuel burnt above 9,000 m” under the “Aircraft specs” tab of the spreadsheet model. Such relation is used to define the share of the emissions during the Cruise phase emitted in the troposphere and stratosphere respectively. Generally, the longer the flight, the higher the share of fuel burnt above 9,000 m.

In the upper-troposphere and lower-stratosphere (i.e., up to 9,000 m of altitude), “non-CO₂” effects triggered by the emissions of NO_x are considered. Above 9,000 m, “non-CO₂” effects from the emissions of water vapor, sulfur oxides and soot are considered. Emissions of CO₂ are considered regardless of the altitude. Finally, the warming induced by the formation of persistent contrails and cirrus clouds is calculated based on the distance flown, as indicated in Lee et al.⁴.

The hydrogen-to-carbon (H/C) ratio for jet fuel is 1.89, while it is 2.15 for syn-jet fuel⁵⁷. Using the relation described in Eq. (3) results in a hydrogen content of 13.7% and 15.3% for jet fuel and synthetic jet fuel, respectively.

$$\%H\left(mass\right)=\frac{100H/C}{11.916+H/C}$$

(3)

According to Snijders et al.⁵⁷ and Altaher et al.⁵⁸, the use of syn-jet fuel leads to a different emission profile compared to regular jet fuel. We consider this by applying correction factors on the emission of certain substances, as described in Emission correction factors, under the “Fuel specs” tab of the spreadsheet model. For example, emissions of sulfur oxides and most hydrocarbons, such as organic volatile compounds, are null, while some others, such as particulate matter (of which soot, or black carbon), are greatly reduced. These emission reductions are explained by a higher-than-average hydrogen content in Fischer-Tropsch fuels with a low aromatics content. The relation between hydrogen content, aromatics content (notably naphthalene) and the reduction of soot particles is described in the work of Voigt et al.³⁹. Lower emissions of soot particles reduce the extent of ice nucleation and leads to ice crystals larger in size, which affects altogether the cloudiness and persistence of contrails and cirrus clouds. With a known reduction in ice particle emissions, a corresponding reduction in contrail cirrus clouds is estimated, based on Ref.⁴⁰. Details on this estimate can be consulted under the tab “Aircraft specs” of the spreadsheet model.

Additionally, the hydrogen content of the jet fuel and syn-jet fuel (i.e., 13.7% and 15.3%, respectively) is used to determine the water vapor emission factor based on the stoichiometric condition that 1 mol of H₂ produces 1 mol of H₂O upon combustion. This yields 1.23 kg and 1.39 kg water vapor per kg jet fuel and syn-jet fuel, respectively.

Radiative forcing and warming contribution of emissions

Carbon dioxide and SLCF act on different time scales: almost half of the CO₂ emitted in the atmosphere accumulates to warm it over several centuries while the remainder is quickly taken up by oceans (25%^1,59) and land (29%¹). SLCF and related effects caused by aviation on the other hand act on a smaller time scale with atmospheric lifetimes of hours (e.g., condensation trails and aviation-induced cirrus clouds), days (e.g., sulfate particles and black carbon) or weeks to months (e.g., water vapor)⁶⁰. Therefore, a unified framework considering the different atmospheric lifetimes of species is needed.

The RF of each substance emitted at surface level is calculated based on several properties. That includes the RF indices, provided by the Supplementary Information document on the Chap. 7 of the IPCC’s AR6 WG1 report³⁶, with the exception of hydrogen, which (indirect) RF index is given by Paulot et al.⁴². These values are reported in Table below.

Table 3

Properties for surface emissions
Species	Lifetime [years]	Molecular mass [g/mol]	Radiative eff. [W/m²/ppb]	Radiative eff. [W/m²/kg]	Source
Hydrogen	2.5	1.01	1.3E-04	7.28E-13	⁴²
HFC-152a	1.6	66.05	0.102	8.71E-12	³⁶
HCFC-140	5	133.4	0.065	2.75E-12
HFC-32	5.4	52.02	0.111	1.20E-11
HCFC-141b	9.4	116.95	0.161	7.77E-12
HCFC-22	11.9	86.47	0.214	1.40E-11
Methane	11.8	16.04	3.88E-04	1.36E-13
HFC-134a	14	102.03	0.167	9.23E-12
HCFC-142b	18	100.49	0.193	1.08E-11
R-10	32	153.823	0.166	6.09E-12
HFC-125	30	120.02	0.234	1.10E-11
CFC-11	52	137.37	0.259	1.06E-11
HFC-143a	51	84.04	0.168	1.13E-11
CFC-113	93	187.375	0.301	9.06E-12
Carbon dioxide		44.01	1.33E-05	1.70E-15

The (effective) RF indices of flight emissions and associated uncertainty are sourced from Lee et al.⁴, and their atmospheric residence time values are from Ref.⁶⁰. Both are presented in Table. Note that the RF of cirrus clouds formation is expressed in reference to the distance flown.

Table 4

Properties of flight emissions
Species	Lifetime [years]	Molecular mass [g/mol]	Radiative eff. [W/m²/kg, or W/m²/km for cirrus]	5th / 95th percentile for radiative eff. [W/m²/kg, or W/m²/km for cirrus]	Source
NO_x (as NO₂)	11.8	46.01	1.67E-12	-2.4E-12 / 3.83E-12	^4,60
BC	0.02	12.01	5.54E-10	7.95E-12 / 4.29E-10
SO_x	0.011	64.07	-1.10E-10	-4.98E-11 / -6.87E-12
H₂O	0.8	18.02	2.86E-14	2.1E-15 / 8.3E-15
Cirrus	0.00057		9.36E-13	6.3E-13 / 1.39E-12

The RF contribution of CO₂ and SLCF for each global air-traffic demand trajectory is obtained by multiplying the forcing response matrix of the gas by the mass emitted over time, as per the approach described in Allen et al.⁷:

$${f}_{A}={F}_{A}{e}_{A}$$

The forcing response matrix F of the gas A denoted F_A corresponds to a triangular Toeplitz matrix with elements consisting of the first derivative of the absolute global forcing potential (AGFP) – the time-integrated RF of a pulse emission of gas A⁶¹. The determination of the AGFP requires the lifetime and RF index of the gas listed in the tables above. The sum of F_A along columns represents the forcing response of gas A over time because of a pulse emission at year 0, considering its atmospheric residence time. The vector f_A returns the overall RF caused by emissions of gas A for each year of the period considered.

Multiplying f_A by the inverse of the CO₂ forcing response matrix gives the amount of CO₂ that would cause an equivalent amount of RF, i.e.,

$${e}_{{CO}_{2}}={{F}_{{CO}_{2}}}^{-1}{f}_{A}$$

Allen et al. named ${e}_{{CO}_{2}}$ the Linear Warming-equivalent CO₂ emissions (CO₂-LWE). Evidently, this last step is only needed for emissions of SLCF, not CO₂.

Multiplying the cumulative sum of emissions of CO₂ and CO₂-LWE for each SLCF by the transient climate response to cumulative carbon emissions (TCRE) gives the increase in the global mean surface temperature (GMST) over the period considered:

$$\varDelta T=\chi \left({CO}_{2}+{CO}_{2}LWE\right)$$

where:

$\varDelta T$ is the change in global temperature (in Kelvin or degree Celsius) over period t
χ is the transient climate response to cumulative carbon emissions: this is the ratio of the global average surface temperature change per unit of CO₂ emitted and is given a value of 0.45 ° C per trillion tons of CO₂.

Summing the emissions of CO₂ and CO₂-LWE for each SLCF gives the total amount of CO₂ to capture and sequester by DACCS to mitigate their contribution to global warming.

This approach implies that to stabilize the impact of aviation on the climate with respect to today or to a given time (i.e., to achieve warming neutrality), CO₂ emissions should be reduced to net-zero (e.g., through emissions avoidance and offsetting), while emissions of SLCF should be kept constant at the level of the reference time; reducing the latter would have a net-cooling effect with respect to such reference time⁶. On the contrary, to neutralize the impact of aviation on the climate over the whole period (i.e., to achieve climate neutrality), both emissions of CO₂ and SLCF should be reduced to net-zero (e.g., through emissions avoidance and offsetting).

Costs analysis

The costs estimate is based on the methodology and assumptions from Becattini et al.⁶². A simplified system analysis of the different technology options is performed, and the various options are compared based on the costs of the jet fuel supply (conventional or synthetic) and of the mitigation technologies (i.e., for DACCS) where applicable. The fuels and DACCS costs considered include the investment and operation costs, which are approximated and reduced to electricity costs. Future costs of low-maturity technologies (i.e., DAC and water electrolysis) are projected using learning curves, with the learning rate depending on the climate and socio-economic scenario considered. Unless otherwise specified, all input values are taken from Becattini et al.⁶².

The cost of electricity is an input common to all the technology options considered and is taken from the SSP2 scenarios of the REMIND Integrated Assessment Model v.2.1⁶³. In 2030, it is assumed to be 0.064 and 0.074 €/kWh in the 3.5° and 2° C scenario, respectively. In 2050, it is assumed to decrease to 0.056 and 0.050 €/kWh in the 3.5° and 2° C scenario, respectively. Afterwards, it is assumed to remain constant.

Fuel supply

Life-cycle inventories for conventional jet fuel are from the life-cycle inventory database ecoinvent v.3.7.1, “cut off by classification” system model⁶⁴. The entire fuel supply chain is included, from raw oil extraction, refining, to kerosene transport to the airport. The cost of conventional jet fuel is assumed to be 0.50 €/kg, which corresponds to the average production cost in 2019⁶². Most recent data are not considered since they were strongly impacted by Covid-19 and the Russia-Ukraine war and do not reflect standard market conditions. For both conventional and synthetic jet fuel, we consider a cost of 0.0086 €/kg for the transport, distribution, and dispensing of the final fuel amount⁶⁵.

Life-cycle inventories for the syn-jet fuel supply are based on van der Giesen et al.⁶⁶. They include the synthesis of syngas into different co-products, including jet fuel. The production of syngas relies on the supply of hydrogen and carbon monoxide. The carbon monoxide is supplied via a reverse water-gas shift reaction, using CO₂ captured from the atmosphere (see “Direct air capture and CO₂ storage”) as input. The hydrogen is supplied by water electrolysis, using proton-exchange membrane (PEM) electrolyzers. The allocation of the Fischer-Tropsch synthesis process burden is based on the respective energy content of the co-products. A post-allocation carbon correction of 40g CO₂/kg of syn-jet fuel is considered, to ensure that the embodied CO₂ per kilogram of syn-jet fuel matches its combustion emission factor of 3.14 kg CO₂ per kg fuel. Details about the allocation of the burden associated with the synthetic gas between the different fuel products can be consulted under the tab “Fuels specs” of the spreadsheet model.

Inventories for the hydrogen production by water electrolysis are from Zhang et al.⁶⁷. We consider a 1% mass loss along the hydrogen supply chain, as per the central estimate found in Ref.⁶⁸. An improvement factor in terms of energy efficiency is considered, bringing the electricity use per kg of hydrogen from 55 kWh in 2020 down to 44 kWh in 2050⁶⁹, besides a fixed amount of electricity (i.e., 3.2 kWh/kg H₂) to compress the hydrogen from 25 to 700 bar before storage⁷⁰. The cost of synthetic jet fuel is determined by the cost of DAC, water electrolysis, reverse water gas shift, Fischer-Tropsch synthesis and upgrading, and fuel distribution. For the costs of DAC, see Direct air capture and CO₂ storage. Current levelized investment costs for water electrolysis are assumed to be 0.91 € per kg of hydrogen. In addition to electricity costs (based on the electricity use mentioned above stemming from both the electrolyser operations and hydrogen compression), we account for the cost of water purification, which is however marginal (ca. 0.0084 €/kgH₂⁷¹). Projected investment costs for water electrolysis are estimated for 2030 and 2050 assuming a learning rate of 5% and 20% for the 3.5° C and 2° C climate scenario, respectively, and a time-dependent cumulative capacity as in Becattini et al.⁶². The resulting levelized costs (LC) for H₂ production and compression estimated for 2030 and 2050 are summarized in Table 5.

Table 5

Levelized costs for H₂ production and compression estimated for 2030 and 2050 for the 2 ° and 3.5 ° C climate scenarios.
Climate scenario	LC H₂ (€/kgH₂) 2030	LC H₂ (€/kgH₂) 2050
2 ° C	4.3	2.7
3.5 ° C	4.7	3.4

The total levelized investment cost for the reverse water gas shift, the Fischer-Tropsch synthesis and further upgrading is assumed to be 0.56 €/kg of synthetic jet fuel⁶⁵. The electricity costs for these steps are also accounted for using the electricity prices indicated in “Costs analysis”. Table 6 summarizes the levelized cost of synthetic jet fuel supply estimated for 2030 and 2050.

Table 6

Levelized costs for synthetic jet fuel production estimated for 2030 and 2050 for the 2 ° and 3.5 ° C climate scenarios.
Climate scenario	LC syn-jet fuel (€/kgJF) 2030	LC syn-jet fuel (€/kgJF) 2050
2 ° C	3.1	2.1
3.5 ° C	3.8	3.2

Direct air capture and CO₂ storage

Life-cycle inventories for the supply of CO₂ via direct air capture (DAC) are from Terlouw et al.⁷² using the configuration connected to the electricity grid. The operation of DAC is assisted by a heat pump with a coefficient of performance of 2.9. Expected improvements and learning rates regarding energy use of the DAC system are from Hanna et al.⁷³. A learning rate of 2% is considered for heat and electricity use, applied on the deployment capacities projected in Ref.⁷⁴, where 5 Gt CO₂ are annually captured by 2050. It is to note that there is a risk of inconsistency as the deployed capacities do not change with the climate scenario considered. In other words, the operational efficiency assumed for DAC might be overestimated in the 3.5° C scenario. There is also a fixed amount of electricity (i.e., 0.2 kWh/kg CO₂ captured) considered to compress the gas from 1 to 100 bar before injection in the reverse water-gas shift reactor (if reused) or the pipeline for subsequent geological storage. For cases where the CO₂ is subsequently reused to produce syn-Jet fuel, we consider a rather tightly integrated system where the DAC unit is located less than a kilometer away from the fuel producer, thereby minimizing the transport (and loss) of CO₂.

In cases where the CO₂ is instead stored underground, it is first transported over 400 km by pipeline and injected 3,000 m underground. The inventories for CO₂ storage are from Volkart et al.⁷⁵. They include the site preparation and borehole drilling, the pipeline transport of the CO₂ to the injection site, minor leakage during transport, as well as the necessary compressors and the electricity for CO₂ compression.

The current levelized investment cost of DAC is estimated to be 0.54 €/kgCO₂⁷⁴. The electricity expenditures associated with DAC operations and CO₂ compression are computed based on the electricity prices mentioned above. Projected investment costs for DAC are estimated for 2030 and 2050 assuming a learning rate of 5% and 20% for the 3.5° and 2° climate scenario, respectively, and a time-dependent cumulative capacity as in Becattini et al.⁶². The resulting levelized costs for CO₂ from DAC (including CO₂ compression) estimated for 2030 and 2050 are summarized in Table 7.

Table 7

Levelized costs for DAC estimated for 2030 and 2050 for the 2 ° and 3.5 ° C climate scenarios.
Climate scenario	LC DAC (€/kgCO₂) 2030	LC DAC (€/kgCO₂) 2050
2° C	0.15	0.10
3.5° C	0.40	0.37

A levelized cost of 0.02 €/kg CO₂ is assumed for the transport of CO₂ by pipeline over 400 km, where applicable. The levelized investment cost for CO₂ underground storage is assumed to be 0.01 €/kg CO₂, while electricity expenditures associated to CO₂ injection are computed based on a consumption of 0.0334 kWh/kg CO₂.

Table 8 summarizes the levelized cost of DACCS estimated for 2030 and 2050 under the 2° and 3.5° C climate scenarios.

Table 8

Levelized costs for DACCS estimated for 2030 and 2050 for the 2 ° and 3.5 ° C climate scenarios.
Climate scenario	LC DACCS (€/kgCO₂) 2030	LC DACCS (€/kgCO₂) 2050
2° C	0.16	0.12
3.5° C	0.41	0.38

Prospective life-cycle inventory database

The life-cycle inventory database ecoinvent v.3.7.1⁷⁶ is used as a “background” database to quantify the emissions of CO₂ and SLCF related to the provision of commodities and services necessary to the different life-cycle phases of the flight (e.g., electricity, heat, metals, road) that are not explicitly modeled in the spreadsheet. While this database is apt to represent the current supply chain performance of commodities, it is transformed to perform the prospective analyses (i.e., future flight performances in 2030 and 2050). To do so, the Python library premise⁷⁶ is used, together with scenario projections of the Integrated Assessment Model REMIND v.2.1^63,77. premise adjusts several aspects of the ecoinvent database to align with the scenario projections of REMIND, across different Representative Concentration Pathways (RCP), given the Shared Socioeconomic Pathway SSP 2 (also called “Middle of the road”). The SSP 2 can roughly be described as an extrapolation into the future of the historical economic and societal development observed until now. In the cases presented, the scenarios equivalent to SSP 2 with RCP 2.6 and SSP 2 with RCP 6.5 are used to represent the 2° C and 3.5° C climate scenarios respectively. We refer the reader to Ref.⁷⁸ for a detailed explanation on how SSPs relate to RCPs. On this basis, the electricity, steel, cement, and transport sectors of the ecoinvent v.3.7 database have been modified to reflect investments and efficiencies as described in the above-mentioned REMIND scenarios.

Resource impact modeling for European fleet scenarios

The cumulative use of electricity, land, and freshwater of the European fleet over the period 2018–2100 is compared to the current consumption levels in the European Union. The amount of electricity currently produced and consumed in the European Union in 2020 (i.e., EU-28) was approximately 2,600 TWh as reported by eurostat⁴⁴. The total surface area of the European Union is approximately 4.2 million km², according to Ref.⁷⁹. The area in the EU-28 used for farming purposes was 173 million hectares in 2016, according to Eurostat⁸⁰. The annual amount of freshwater abstracted in the EU-28 annually, all sectors considered, is around 350 km³ according to Ref.⁸¹, and it is estimated than an average European citizen uses about 100 liters of freshwater per day (or around 36 m³ per year)⁸². Finally, the Gross Domestic Product of the European Union in 2019 was 17 trillion USD⁸³, considering 1 € = 1 USD.

Data availability

The supporting data and calculations presented in this study are available in the spreadsheet model, which is part of the Supplementary Information material.

Acknowledgement

We thank Theo Rindlisbacher and Boris Stolz from the Swiss Federal Office of Civil Aviation (FOCA) for enlightening discussions regarding climate policies and mitigation efforts in the aviation sector as well as on non-CO₂ effects and climate change.

Authors information

Romain Sacchi is a postdoctoral researcher at the Paul Scherrer Institute, with a focus on prospective environmental assessment of mobility.

Viola Becattini is a senior scientist at ETH Zurich, within the Separation Processes laboratory, with a focus on CO₂ capture, transport, and storage technologies.

Paolo Gabrielli is a senior scientist at ETH Zurich, within the Reliability and Risk Engineering laboratory, with a focus on the modeling, optimization, and assessment of low-carbon energy systems.

Christian Bauer is a senior researcher at the Paul Scherrer Institute, with a focus on life-cycle assessment and decarbonization strategies.

Brian Cox is a senior project manager at INFRAS in the area of transport and the environment, with a focus on the topics of emissions modelling, drive and fuel strategies and sustainable mobility.

Alois Dirnaichner is postdoctoral researcher at the Potsdam Institute for Climate Impact Research (PIK), with a focus on the life-cycle footprint of future products in the light of climate mitigation.

Marco Mazzotti is professor of process engineering at ETH Zurich since 1997.

Author contributions

Conceptualization: RS, VB, CB, MM; Formal analysis: RS, VB, PG; Funding acquisition: CB, MM; Investigation: RS, VB, PG, BC; Methodology: RS, VB, PG, AD; Software: RS, VB, AD; Supervision: CB, MM; Visualization: RS, VB, MM; Writing – original draft: RS, VB; Writing – review and editing: all.

Ethics declaration

The authors declare not to have any stake in any of the outcomes of the study.

Funding sources

This work has received financial support from the SynFuel initiative of the ETH Council, PSI’s Energy System Integration platform and the Kopernikus-Projekt Ariadne (FKZ 03SFK5A), funded by the German Federal Ministry of Education and Research.

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Climate-neutral aviation: will it fly?

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