Decarbonizing the Skies: Evolution of EU Air Transport Efficiency and Carbon Emissions

Abstract

The European air traffic sector underwent significant disruption due to the COVID-19 pandemic, followed by a complex recovery phase. Throughout this period, the decarbonization of aviation remained a strategic priority for EU institutions and regulators. This study presents a comparative analysis of air traffic activity and associated CO₂ emissions across EU member states between 2019 and 2024, using publicly available operational data and a standardized emissions estimation method. It explores changes in traffic volume, structural shifts in fleet composition, and the evolving market dynamics among European carriers. While the overall sectoral characteristics remained relatively stable, notable intra-EU variations influenced both operational efficiency and emissions outcomes. These findings underscore the importance of tailoring decarbonization measures to reflect national and regional differences, ensuring equitable and effective implementation across the EU.

1. Introduction

Global aviation contributes to human-induced climate change through a complex set of mechanisms that result in net surface warming. Key contributors include emissions of carbon dioxide (CO₂), nitrogen oxides (NO_x), water vapor, soot, and sulfate aerosols, as well as increased cloud formation due to contrails [1]. CO₂ is believed to be responsible for one-third of the sector’s net climate impact [2] and is the most widely monitored and reported parameter across all sectors. The air transport industry, while responsible for only 2.8% of global CO₂ emissions and 12% of transport-related emissions in 2019 [3,4], presents severe challenges in its decarbonization due to its reliance on high energy-density fuels, long development cycles for new technologies, and the global nature of its operations [5,6,7,8,9,10]. Its steady pre-pandemic growth, averaging 2.3% annually between 1990 and 2019 [11], raised concerns about the sector’s long-term environmental impact. The European market was impacted by regulatory responses both at global level, through ICAO, and regional level, through the European Union (EU) [12,13,14]. Notably, ICAO set aspirational fuel efficiency and net-zero targets [15], and introduced the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) [16], while the EU incorporated aviation into its Emissions Trading System (EU ETS) [17] and proposed further climate-related measures under the “Fit for 55” package [18,19,20]. These initiatives emphasize sustainable aviation fuel (SAF), taxation reforms, and technological innovation as core pathways to reduce emissions [21].

The COVID-19 pandemic, however, brought an abrupt disruption to air traffic from 2020 to 2023 [22,23]. Lockdowns, travel bans, and behavioral changes led to a collapse in demand and forced a reconfiguration of airline networks, fleet strategies, and operational models. Although vaccine rollouts and improved health protocols enabled gradual recovery, the pace and pattern of that recovery varied significantly across regions. In some cases, the pandemic even fostered the emergence of new airlines, while simultaneously exposing structural vulnerabilities within traditional carriers. The reduction in air mobility not only had economic consequences but also raised questions about the sustainability of the aviation industry’s pre-pandemic growth model. To understand the impact that COVID-19 had in the industry, this study applies a model developed at the School of Aerospace Engineering (ETSIAE) of the Universidad Politécnica de Madrid, which has been tested and applied in several other publications [24,25,26]. The unique proposition of the model used is that it is based on the public available information from EUROCONTROL [27], which feeds the also open emissions calculator of the European Environment Agency (EEA) and the European Monitoring and Evaluation Program (EMEP) [28]. It provides details of fuel consumption as a function of the distance flown by aircraft type and flight phase. Then, the efficiency of each flight is calculated based on the load factors obtained from the database of the European Commission’s Eurostat Air Transport Statistics (Eurostat) [29].

The analysis in this work focuses on two reference years: 2019, the last full year before the pandemic, and 2024, to capture the status of post-pandemic recovery. This article applies the model to the data of 2019 and 2024 to investigate the changes that the COVID-19 period caused in the EU’s traffic structure and how it impacted the volume of CO₂ emissions and fuel distribution. Its findings can be used to review and improve the application of the existing environmental regulations. It also explores the fuel efficiency improvements achieved and how they have impacted aviation’s environmental footprint. These insights can support the refinement of climate policy and enhance the design of data-driven regulatory frameworks.

2. Methodology

This study follows an established methodological approach first introduced in the 2014 reference study [24], which combines data from EUROCONTROL’s Demand Data Repository (DDR) and the European Commission’s Eurostat Air Transport Statistics (Eurostat) to estimate air traffic volumes, load factors, fuel consumption, and CO₂ emissions across the European Union air transport network, focusing on civil, scheduled, and charter commercial passenger flights only.

EUROCONTROL’s database contains all the flights that took place in its forty-two country members plus Iceland and Azerbaijan on a day-by-day basis. It includes the origin and destination airports, the date and the departure time of flights, the company operating each flight, and the aircraft model used, among other data. Due to the high volume of daily flights in the area under consideration, a simplified methodology aligned with standard industry practices was adopted [30]. To estimate annual averages, data from two representative weeks (the central week of June and the central week of September) were analyzed to capture seasonal variations. Furthermore, only departure flights from the countries in scope were included to prevent double counting and to ensure consistency with methodologies used in current regulatory initiatives [31].

The Eurostat database includes information provided by thirty-six countries: the twenty-seven members of the EU, Norway, Switzerland, Iceland, Turkey, Bosnia and Herzegovina, Serbia, Montenegro, North Macedonia, and the United Kingdom until 2020. The two data sets used in this study were the number of seats available (ST_PAS) and passengers on board (PAS_BRD) per airport pair, and depending on the reporting country, the information was provided by months, quarters, or years. These values were used to estimate the load factor (LF) for each route, dividing the number of passengers over the available seats in each route. As a result, this operation gives the seat factor (SF) but since the network effects are not considered because the analysis only contemplates point-to-point routes where the distance remains constant, it is possible to assimilate the SF as the LF. The distance between airport pairs was calculated using the great-circle formula based on airport geographic coordinates. The downside of this method is that all airlines share the same LF in the same routes, but detailed information per airline per route is, in general, not available [32,33].

At flight level, the main metrics calculated were revenue passenger kilometers (RPKs) and the CO₂ emissions. The calculation of the RPKs was carried out using available seat kilometers (ASKs), resulting from multiplying the number of available seats in the flight by the distance flown in kilometers, calculated using the great-circle formula based on the geographical coordinates of the airport pair. In this case, it was possible to account for the differences between operators through the seat plan of each aircraft model, which is usually provided in the corporative websites of the respective airlines. In general, low-cost airlines (LCCs) operate planes with higher seat densities, which means that they obtain higher ASK values than legacy airlines for the same route and the same plane aircraft model. Once again, since this study considers only point-to-point flights, it was possible to estimate the RPKs by multiplying the ASKs by the LF.

The fuel consumption and the CO₂ emissions were determined using the EEA’s emission calculator [28,34], which provides the fuel consumption as a function of the distance flown and the aircraft type per flight phase. Since specific flight conditions such as take-off weight, speed, or altitude were not considered, the values obtained must be considered as minimum consumption. While lacking precision, these values are very helpful when analyzing large volumes of flights, as in the case of this study. The CO₂ emissions were calculated by multiplying the fuel consumption by 3.15, following the EU’s directives and assuming that traditional aviation kerosene was used (Jet A/Jet A1).

Finally, the flights in scope were segmented, depending on their origin and destination airports, into three categories, as follows:

• NAT: the origin and destination airports are in the same country;
• EUR: the origin and destination airports are in different countries, but both belong to the EU;
• INT: the origin airport is in the EU, but the destination is not.

Methodological Limitations

While the methodology applied in this study aims to provide a representative and consistent analysis following standard industry practices, several limitations must be acknowledged. The first one is the already introduced simplification for the selection of flights to calculate the annual average values. This approach, while practical, inevitably sacrifices accuracy compared to analyzing data from all flights throughout the year. Second, the indicators sourced from EUROSTAT are based on standardized collection and validation procedures [35,36]. It is considered impossible to compute any meaningful numerical measure of error margins [37], although the precision of specific indicators is considered to increase with the level of aggregation [24]. In that sense, the ability to assess the precision of the results is limited. Third, the calculation of load factors, as discussed in previous paragraphs, assumes uniformity across airlines operating the same route, which may not reflect actual variations in airline performance. Fourth, fuel consumption estimates are based solely on the fuel required for each specific flight, excluding considerations such as tankering, reserve fuel, or additional fuel used due to operational factors, thus providing minimum values only. Fifth, the analysis does not account for variations in take-off weight, flight phases, atmospheric conditions, or operational modifications, all of which can influence fuel consumption and emissions. Finally, while the United Kingdom represents a significant share of European air traffic, it was intentionally excluded from this analysis. This decision was made to maintain a consistent analytical scope focused on EU member states. These limitations highlight areas for future refinement and underscore the importance of interpreting the results within the context of these methodological constraints.

3. Results

The methodology explained in Section 2 was applied to the data compiled from EUROCONTROL and Eurostat for 2019 and 2024. Comprehensive data can be found in the tables located in Appendix A.

3.1. At Country Level

3.1.1. Traffic Structure

Figure 1 captures the evolution of the number of departures between 2019 and 2024; the number of departures increased by 7.40%, suggesting a full recovery from the disruption caused by the COVID-19 pandemic in 2020. The countries that saw the highest increases were Slovenia (+64%) and Malta (+43.42%). Spain, Greece, Croatia, Ireland, Italy, Portugal, and Slovakia saw increases of over 20% in the numbers of departures, which could indicate a shift towards leisure travel. On the other hand, the countries with the largest declines in the number of flights were Bulgaria (−18.31%), Latvia (−17.79%), and Sweden (−17.03%). While the decrease in the number of flights for first two countries was strongly linked to the sanctions imposed by the EU in the aftermath of Russia’s invasion of Ukraine [38], Sweden’s situation was related to a decrease in the internal flights linked to the “flygskam” movement, as analyzed later in this document.

Figure 1 also represents the relative relevance of each country in terms of departure volumes. In 2019, the countries with the highest number of departures were Germany (16.55%), Spain (16.26%), and France (12.08%). In 2024, the situation changed, with Spain leading (18.32%), followed by Germany (13.54%) and Italy (13.28%). The top three countries accounted for 44.89% of the total flights in 2019, increasing slightly to 45.14% in 2024, which shows a high level of concentration of the European network and centralization trend. It is interesting to note that Germany was the only one of these key countries that decreased the number of flights, as will be discussed later.

Figure 2 includes the values of the average distance by country. The average distance of a flight in the area in scope increased 3.02% between 2019 and 2024, moving from 1418 km to 1464 km. In both years, the country with the highest average distance was Cyprus, with 2183 km in 2019 and 2093 km in 2024. The longer average flights are explained by the lack of internal flights and the high relevance of INT flights, especially in 2019 when they accounted for 35.63% of the total. At the opposite end were Luxembourg and Estonia. Whereas in 2019 both countries had very close values (799 km for Luxembourg and 800 km for Estonia), in 2024 the values diverged. Luxembourg reached an average of 964 km, a 20.68% increase, the highest among all states, due to the rise of the number of INT flights. Estonia averaged 893 km, which meant a still significant 11.69% growth, but was affected by the slight reduction of the INT flights versus the surge of the EUR and NAT ones. Malta was the country where the average distance decreased the most, 12.81%, linked to a decrease in INT flights and increase in EUR ones. As shown in

Table A1. Traffic structure in each EU country in 2019 and 2024.

Country		Number of Departures			% of Flights
Name	Code	2019	2024	Var. (%)	2019	2024	Var. (%)
Austria	AT	147,264	147,108	−0.11	2.57	2.38	−7.32
Belgium	BE	119,028	124,904	4.94	2.07	2.02	−2.64
Bulgaria	BG	57,928	47,320	−18.31	1.01	0.77	−24.21
Cyprus	CY	42,328	47,892	13.14	0.74	0.77	4.97
Czechia	CZ	77,220	77,896	0.88	1.35	1.26	−6.41
Germany	DE	949,936	837,252	−11.86	16.55	13.54	−18.23
Denmark	DK	174,408	173,680	−0.42	3.04	2.81	−7.61
Estonia	EE	22,984	21,320	−7.24	0.40	0.34	−13.94
Spain	ES	933,244	1,133,184	21.42	16.26	18.32	12.65
Finland	FI	111,852	94,952	−15.11	1.95	1.54	−21.24
France	FR	692,952	734,916	6.06	12.08	11.88	−1.61
Greece	GR	343,200	424,736	23.76	5.98	6.87	14.82
Croatia	HR	68,640	82,836	20.68	1.20	1.34	11.96
Hungary	HU	53,040	55,952	5.49	0.92	0.90	−2.13
Ireland	IE	126,152	152,412	20.82	2.20	2.46	12.09
Italy	IT	670,332	821,288	22.52	11.68	13.28	13.67
Lithuania	LT	24,232	28,028	15.67	0.42	0.45	7.31
Luxembourg	LU	27,664	28,548	3.20	0.48	0.46	−4.26
Latvia	LV	39,468	32,448	−17.79	0.69	0.52	−23.73
Malta	MT	22,516	32,292	43.42	0.39	0.52	33.06
Netherlands	NL	271,388	272,532	0.42	4.73	4.41	−6.83
Poland	PL	210,548	238,628	13.34	3.67	3.86	5.15
Portugal	PT	220,220	270,244	22.72	3.84	4.37	13.85
Romania	RO	94,848	98,592	3.95	1.65	1.59	−3.56
Sweden	SE	219,856	182,416	−17.03	3.83	2.95	−23.02
Slovenia	SI	5200	8528	64.00	0.09	0.14	52.15
Slovakia	SK	11,856	15,184	28.07	0.21	0.25	18.82
Total		5,738,304	6,185,088	7.40

, the general distribution among types of flights remained quite stable during the period, with a small increase of EUR flights that offset decreases in INT and NAT ones. In 2019, the country with the highest proportion of EUR flights was Luxembourg, with 80% of the total. Cyprus had the highest share of INT flights (65.48%), while Sweden had the highest proportion of NAT flights (44.09%). In 2024, the country with the highest proportion of EUR flights was still Luxembourg, which maintained 2019 values. Cyprus remained the country with the highest proportion of INT flights, though this figure fell to 52.66%. Spain slightly surpassed Sweden in the share of NAT flights, with 37.86% compared to Sweden’s 37.34%. One possible explanation for the change in the Swedish market could be the strong impact that the flygskam or “flight shame” movement [39,40] has had and the availability of alternative means of transport. In the case of Spain, there are reduced connectivity alternatives for the insular territories, which leaves flying as the main option (see Table A1 for further details).

3.1.2. Fuel Uptake and CO₂ Emissions

Assuming, as explained in Section 2 that aircraft are refueled before departure with only the necessary amount for the flight, excluding any amount related to the reserves, and presuming no “tankering” occurs (i.e., the practice of carrying more fuel than is needed for the flight to avoid refueling at the destination airport [41]), Figure 3 shares the minimum fuel uptake in the countries within scope.

Overall, the amount of fuel provided by the airports increased by 5.86% during the period 2019–2024, from 38.49 to 40.74 million tonnes. The countries in which the highest quantities of fuel were uplifted were Germany and France in 2019, and Germany and Spain in 2024. Spain experienced a 19.10% surge in the amount of fuel provided, linked to the 21.42% rise in the number of flights during the period, as seen in Section 3.1.1. In comparison, Germany’s supply decreased by 7.77%, losing 2.55 percentage points in the global uptake. These states accounted for 46.11% and 45.92% of the total fuel uplifted in the region in 2019 and 2024 respectively, showing a slight decrease. Together, the top five countries accounted for 65.91% and 66.05% of total fuel uptake in 2019 and 2024, respectively, which was twice the share of the remaining twenty-two countries combined.

The countries that saw a higher increase in the amount of fuel provided were those with the lowest relevance in the global count: Slovenia (+51.81%), Luxembourg (+32.90%), and Lithuania (+30.19%). The rise in Slovenia was linked to the surge in the number of departures whereas in Luxembourg, it was linked to the extension of the average distance. Lithuania’s situation was a combination of both factors. Greece followed closely with a 30.02% increase linked to the 23.76% growth in the number of flights during the period. At the other end of the list, the countries for which the supply of fuel decreased were Bulgaria (−24.35%), Sweden (−22.87%), and Finland (−11.67%) due to the reduction in the number of flights, especially INT ones. The case of Germany, which also included a reduction in the amount of fuel supplied (−7.77%), is relevant due to the number of factors that it includes. For instance, the number of departures from the country decreased by 11.86%. This decline was caused mainly by the severe reduction of NAT flights, which hence increased the relevance of both EUR and INT flights and in consequence caused a rise in the average distance flown of 11.77%. The decrease in the demand for internal flights has been blamed both on the switch to alternative transportation methods [42] and on the taxes and fees that the country applies to aviation [43].

The analysis of the fuel uptake per type of flight is aligned with the results presented in

Table A2. Average distance for flights departing EU countries in 2019 and 2024.

Country Code	Average Distance (km)			Type of Flight
				2019			2024
	2019	2024	Variation (%)	EUR	INT	NAT	EUR	INT	NAT
AT	1302	1292	−0.75	63.38	31.43	5.19	68.22	28.63	3.15
BE	1605	1602	−0.19	68.28	31.50	0.22	71.61	28.31	0.08
BG	1427	1386	−2.87	58.80	34.20	7.00	67.03	28.13	4.84
CY	2183	2093	−4.12	34.52	65.48	0.00	46.91	52.66	0.43
CZ	1441	1454	0.95	60.81	37.91	1.28	61.68	37.18	1.13
DE	1441	1611	11.77	46.74	29.75	23.51	52.88	31.53	15.58
DK	1023	1211	18.41	48.30	27.28	24.42	53.98	28.29	17.72
EE	800	893	11.69	72.40	14.93	12.67	74.39	13.90	11.71
ES	1452	1474	1.49	34.99	26.47	38.54	37.36	24.78	37.86
FI	1430	1464	2.36	45.75	21.34	32.91	58.54	16.27	25.19
FR	1543	1550	0.41	39.42	30.20	30.38	41.00	32.35	26.65
GR	1373	1457	6.16	39.30	24.27	36.42	43.25	24.00	32.75
HR	1106	1052	−4.86	55.53	30.76	13.71	62.90	24.98	12.12
HU	1345	1329	−1.19	60.88	38.73	0.39	66.26	33.55	0.19
IE	1600	1640	2.47	45.63	51.85	2.51	50.05	48.14	1.81
IT	1293	1262	−2.40	41.37	23.85	34.78	44.49	21.25	34.26
LT	1101	1266	15.02	64.81	35.19	0.00	74.03	25.97	0.00
LU	799	964	20.68	80.08	19.92	0.00	79.05	20.95	0.00
LV	1050	1227	16.78	62.06	36.63	1.32	76.44	23.56	0.00
MT	1695	1478	−12.81	63.05	36.95	0.00	73.27	26.73	0.00
NL	1865	1858	−0.38	56.66	43.09	0.25	60.01	39.53	0.46
PL	1241	1353	9.02	52.36	33.19	14.45	56.29	32.34	11.38
PT	1651	1691	2.39	45.17	28.45	26.38	45.06	28.59	26.34
RO	1281	1295	1.10	55.04	27.74	17.21	57.91	28.53	13.55
SE	1032	1085	5.11	39.59	16.32	44.09	46.86	15.79	37.34
SI	1029	998	−3.01	44.00	56.00	0.00	55.49	44.51	0.00
SK	1408	1369	−2.77	46.93	52.19	0.88	51.71	47.60	0.68
Total	1418	1464	3.02	45.19	29.32	25.49	48.60	28.20	23.20

. The amount of fuel for INT and NAT flights decreased in parallel with the number of flights, whereas the opposite occurred for EUR flights. The bulk of the fuel was used for INT flights due to their longer average length and accounted for way over half of the total fuel used. The NAT flights represented just between 7 and 8% of the fuel, implying that the limitations to internal flights introduced by certain countries have had a reduced impact on the efforts towards the reduction of the national emissions.

When comparing the results from Table A2 and

Table A3. Fuel uptake by country and type of flight in 2019 and 2024.

Country Code	Fuel Uptake (Million Tonnes)			% of Total Uptake			Fuel Uptake per Type of Flight
							2019			2024
	2019	2024	Var (%)	2019	2024	Var.	EUR	INT	NAT	EUR	INT	NAT
AT	0.88	0.86	−2.25	2.28	2.11	−0.17	34.73	64.42	0.85	41.89	57.54	0.57
BE	0.82	0.85	3.30	2.14	2.09	−0.05	40.84	59.12	0.04	45.07	54.92	0.01
BG	0.31	0.23	−24.35	0.80	0.57	−0.23	55.27	42.23	2.49	62.78	35.45	1.76
CY	0.35	0.34	−3.50	0.92	0.84	−0.08	28.81	71.19	0.00	43.14	56.78	0.08
CZ	0.47	0.42	−11.67	1.23	1.03	−0.20	37.71	61.95	0.34	47.35	52.33	0.32
DE	7.62	7.03	−7.77	19.80	17.25	−2.55	23.08	70.70	6.22	26.38	69.71	3.90
DK	0.79	0.88	10.37	2.06	2.15	0.09	39.59	53.86	6.54	41.94	53.25	4.81
EE	0.06	0.06	13.69	0.15	0.16	0.01	64.40	34.66	0.94	69.46	29.16	1.38
ES	5.89	7.01	19.10	15.29	17.21	1.92	30.05	55.99	13.97	31.70	53.63	14.67
FI	0.71	0.61	−13.11	1.83	1.50	−0.33	33.56	59.36	7.08	41.96	52.43	5.61
FR	6.00	6.06	1.01	15.59	14.87	−0.72	17.94	72.92	9.14	19.31	72.97	7.71
GR	1.78	2.31	30.02	4.62	5.68	1.06	48.02	44.03	7.95	47.52	45.28	7.20
HR	0.28	0.31	9.86	0.74	0.77	0.03	47.71	48.84	3.45	61.39	34.87	3.74
HU	0.29	0.29	−0.47	0.76	0.71	−0.05	43.08	56.80	0.11	50.95	49.00	0.05
IE	0.97	1.10	12.93	2.53	2.70	0.17	32.60	67.20	0.20	38.03	61.66	0.32
IT	4.13	4.83	16.97	10.72	11.85	1.13	26.51	58.13	15.36	30.09	53.98	15.92
LT	0.09	0.12	30.19	0.24	0.30	0.06	53.56	46.44	0.00	65.07	34.93	0.00
LU	0.07	0.09	32.90	0.17	0.22	0.05	81.88	18.12	0.00	76.50	23.50	0.00
LV	0.11	0.14	25.16	0.28	0.33	0.05	51.54	48.22	0.24	67.79	32.21	0.00
MT	0.13	0.17	22.42	0.35	0.41	0.06	58.03	41.97	0.00	67.57	32.43	0.00
NL	2.76	2.70	−2.18	7.18	6.63	−0.55	23.02	76.96	0.03	24.57	75.36	0.07
PL	1.01	1.20	19.76	2.61	2.95	0.34	42.52	54.70	2.77	46.54	50.34	3.12
PT	1.51	1.84	21.64	3.93	4.52	0.59	35.67	55.47	8.86	35.04	55.92	9.04
RO	0.44	0.46	5.71	1.13	1.13	0,00	57.69	37.68	4.63	60.68	35.68	3.64
SE	0.94	0.72	−22.87	2.43	1.77	−0.66	41.66	42.03	16.32	53.17	33.38	13.44
SI	0.02	0.03	51.81	0.05	0.07	0.02	36.52	63.48	0.00	49.53	50.47	0.00
SK	0.06	0.07	19.29	0.16	0.18	0.02	38.78	60.85	0.36	43.62	56.11	0.27
Total	38.49	40.74	5.86				29.42	62.56	8.02	32.87	59.45	7.68

on the percentage of flights and fuel loaded in each country, the values are generally similar, with a few exceptions such as the Netherlands and Germany, where the percentage of fuel loaded exceeds the percentage of flights by three percentage points, indicating the importance of longer-distance flights.

The amount of CO₂ emissions is calculated by multiplying the amount of fuel burned by 3.15. The estimated quantity of emissions from the departures in the area in scope was 121.56 million tonnes in 2019 and 128.21 in 2024. The split between types of flights, shown in Table A3, means that in 2024, 7.68% of the CO₂ emissions were generated by NAT flights, 59.45% by INT flights, and 32.87% by the EUR ones. This situation highlights the relative importance of the different types of flights in the volumes of emissions, with INT flights being responsible for most of the emissions whereas the contribution of the NAT ones is way smaller in comparison. This means that the regulatory measures taken to limit domestic flights, such as those in France [44], might have a very limited impact in the EU’s objective of reducing CO₂ emissions.

Figure 4 shows the CO₂ efficiency parameter values of the flights departing from each EU member country. The average efficiency parameter changed from 0.111 to 0.098 kg/RPK, representing an improvement of 11.71%. Luxembourg experienced the largest improvement in the efficiency parameter, 27.61%, followed by Denmark, 21.53%. The only countries where the factor worsen were Latvia (10.64%) and Croatia (4.90%). The country with the worst values across the period was Estonia, 0.160 kg/RPK, that only improved 0.63%. The country with the best values was Malta, starting the period with 0.081 kg/RPK and ending with 0.0.75 kg/RPK, a 7.41% change.

As shown in

Table A4. CO₂ efficiency by country and type of flight in 2019 and 2024.

ISO Code	2019				2024
	Average CO2 (kg)/RPK	Average CO2 (kg)/RPK			Average CO2 (kg)/RPK	Average CO2 (kg)/RPK
		EUR	INT	NAT		EUR	INT	NAT
AT	0.111	0.113	0.095	0.176	0.098	0.097	0.086	0.214
BE	0.103	0.103	0.103	0.429	0.093	0.093	0.090	0.643
BG	0.093	0.082	0.086	0.209	0.084	0.079	0.085	0.158
CY	0.086	0.081	0.089		0.077	0.070	0.083	0.270
CZ	0.091	0.094	0.082	0.239	0.087	0.091	0.075	0.227
DE	0.120	0.107	0.101	0.172	0.101	0.093	0.088	0.152
DK	0.144	0.113	0.107	0.246	0.113	0.095	0.093	0.201
EE	0.160	0.151	0.113	0.266	0.159	0.164	0.078	0.219
ES	0.104	0.079	0.076	0.147	0.092	0.071	0.071	0.126
FI	0.130	0.114	0.103	0.170	0.115	0.112	0.088	0.138
FR	0.106	0.098	0.093	0.130	0.101	0.091	0.092	0.130
GR	0.116	0.076	0.078	0.184	0.104	0.071	0.071	0.170
HR	0.102	0.096	0.088	0.156	0.107	0.092	0.091	0.212
HU	0.092	0.095	0.084	0.208	0.081	0.084	0.075	0.139
IE	0.095	0.076	0.108	0.173	0.088	0.069	0.104	0.202
IT	0.107	0.096	0.090	0.131	0.091	0.085	0.085	0.104
LT	0.116	0.123	0.103		0.099	0.110	0.070
LU	0.134	0.137	0.120		0.097	0.098	0.096
LV	0.094	0.094	0.093	0.155	0.104	0.112	0.078
MT	0.081	0.086	0.073		0.075	0.079	0.063
NL	0.108	0.104	0.110	0.400	0.102	0.097	0.106	0.435
PL	0.098	0.096	0.082	0.141	0.096	0.087	0.072	0.213
PT	0.117	0.082	0.080	0.217	0.106	0.075	0.075	0.192
RO	0.101	0.085	0.088	0.172	0.088	0.076	0.084	0.143
SE	0.129	0.101	0.098	0.166	0.111	0.093	0.093	0.140
SI	0.122	0.141	0.106		0.106	0.112	0.099
SK	0.089	0.103	0.076	0.189	0.083	0.096	0.068	0.137
Total	0.111	0.097	0.092	0.157	0.098	0.086	0.084	0.138

, by type of flight, the best efficiency values were achieved from INT flights, closely followed by EUR flights. However, EUR flights showed a greater improvement, with their efficiency parameter decreasing by 11.34%, compared to an 8.70% decrease for INT flights. NAT flights had the worse values, emitting 70% more kg of CO₂ per RPK than INT flights in 2019. In 2024, the difference dropped to 64% due to a 12.10% reduction of the efficiency parameter. The best efficiency values were recorded forINT flights departing from Malta in 2024 and the worst were for the very limited NAT flights within Belgium in 2024. These results underscore the efforts made towards the improvement of the efficiency of longer flights due to their bigger impact on overall emissions.

3.1.3. Airport Network Structure

The structure of the airport network in each EU member country plays a significant role in how fuel is distributed. Based on the data shown in

Table 1. Fuel uptake in the main airport of each country in 2019 and 2024.

Country Code	Main Airport (IATA Code)	% of Country’s Fuel Uptake			% of Total Fuel Uptake
		2019	2024	Var. (%)	2019	2024	Var. (%)
AT	VIE	93.93	93.71	−0.23	2.14%	1.97%	−0.14
BE	BRU	87.73	79.91	−8.91	1.88%	1.67%	−0.17
BG	BOJ	41.48	59.61	43.7	0.33%	0.34%	0
CY	LCA	75.85	67.9	−10.48	0.70%	0.57%	−0.1
CZ	PRG	92.66	84.32	−8.99	1.14%	0.87%	−0.22
DE	FRA	48.31	47.92	−0.8	9.56%	8.27%	−1.05
DK	CPH	84.91	84.45	−0.54	1.75%	1.82%	0.04
EE	TLL	99.22	98.7	−0.52	0.15%	0.16%	0.01
ES	MAD	35.93	35.24	−1.93	5.50%	6.06%	0.39
FI	HEL	94.67	94.06	−0.65	1.74%	1.42%	−0.25
FR	CDG	65.43	61.44	−6.1	10.20%	9.14%	−0.88
GR	ATH	34.58	37.44	8.28	1.60%	2.13%	0.39
HR	ZAG	31.55	25.17	−20.21	0.19%	0.22%	−0.01
HU	BUD	95.89	97.9	2.1	0.73%	0.70%	−0.03
IE	DUB	89.43	87.34	−2.34	2.26%	2.36%	0.05
IT	FCO	37.64	36.69	−2.52	4.04%	4.35%	0.2
LT	VNO	78.49	73.86	−5.9	0.19%	0.22%	0.02
LU	LUX	100	100	0	0.17%	0.22%	0.03
LV	RIX	99.88	100	0.12	0.28%	0.33%	0.04
MT	MLA	100	100	0	0.35%	0.41%	0.04
NL	AMS	93.98	93.59	−0.41	6.74%	6.21%	−0.46
PL	WAW	49.89	43.82	−12.18	1.30%	1.29%	−0.02
PT	LIS	63.17	59.93	−5.11	2.48%	2.71%	0.15
RO	OTP	64.37	63.46	−1.4	0.73%	0.72%	−0.01
SE	ARN	67.75	71.68	5.81	1.65%	1.27%	−0.3
SI	LJU	99.59	100	0.41	0.05%	0.07%	0.02
SK	BTS	75.99	68.54	−9.8	0.12%	0.12%	0
Total					57.97	55.59	−1.89

, countries can be grouped into two main categories: those where most of the traffic and consequently, the fuel supply is concentrated at a single main airport, such as Luxembourg, Malta, Latvia, Slovenia, and Estonia; and those with a more decentralized distribution, like Italy, Spain, Greece, and Croatia, where the main airport accounts for about one-third of the total fuel volume. The trend in the period indicates a decline in the dominance of main airports, with 19 out of 27 EU countries seeing a reduced share of total national fuel distribution concentrated at their primary airport. Overall, the proportion of fuel handled by these airports dropped from 57.97% in 2019 to 55.59% in 2024.

Only seven of these main airports belonged to the top ten airports in terms of supply, as observed in Figure 5. Over the period, the combined supply of these airports went from 50.35% to 47.82% of the region’s total, pointing towards a reduction in the traffic concentration. In 2019, Paris Charles de Gaulle accounted for 10.2% of the total fuel loaded in the EU, followed closely by Frankfurt am Main with 9.5%. Then, the third airport in the classification was Amsterdam Schiphol, with 6.7%. In total, they supplied 26.5% of the total amount of fuel, which highlights the level of centralization in the region. In 2024, Paris Charles de Gaulle remained as the top airport but saw its share drop to 9.1%. It was followed again by Frankfurt am Main with 8.3% and Amsterdam Schiphol with 6.2%, bringing their combined share down to 23.6%. Only Madrid, Lisbon, and Dublin airports increased their relative relevance in terms of fuel supply during these years.

3.2. Results at Airline Level

This analysis considers only EU-based airlines, classified into two categories, i.e., traditional carriers (TRAD) and low-cost carriers (LCCs), based on the following general criteria:

• TRAD: full-service carriers with a hub-and-spoke network, typically operating long-haul operations.
• LCCs: point-to-point carriers, with very limited use of interlining and often operating secondary airports.

3.2.1. Traffic Structure

Table 2. Traffic structure in 2019 of the top twenty EU airlines based by number of departures.

Airline	Type	Departure Airports	Departure Flights (%)	Departure Flights per Type (%)			Average Distance (km)	Average Distance (km)
				EUR	INT	NAT		EUR	INT	NAT
Lufthansa	TRAD	113	8.16	58.69	14.89	26.42	1207	883	3931	389
Ryanair	LCC	171	7.54	56.79	28.10	15.11	1305	1405	1389	773
Air France	TRAD	72	4.32	38.74	20.30	40.96	1554	950	4655	587
Eurowings	LCC	100	4.17	62.86	7.69	29.44	953	1137	1356	455
Vueling	LCC	89	3.94	48.75	6.55	44.70	937	1097	1193	725
EasyJet Europe	LCC	100	3.92	57.17	10.33	32.50	945	1077	1193	635
KLM	TRAD	65	3.55	72.48	27.52	0.00	1390	843	2830	0
SAS	TRAD	90	3.26	55.04	18.68	26.28	939	1024	1425	416
Alitalia	TRAD	58	3.18	22.95	11.07	65.98	972	942	3598	541
Wizz Air	LCC	94	2.74	67.32	32.52	0.17	1392	1324	1540	176
Austrian	TRAD	77	2.15	77.09	16.72	6.19	1021	767	2465	281
Finnair	TRAD	77	2.09	55.07	15.05	29.88	1374	1288	3639	392
LOT Airlines	TRAD	61	1.96	56.02	17.41	26.57	994	829	2591	296
TAP Portugal	TRAD	48	1.89	60.99	17.90	21.11	1651	1486	3344	694
Air Europa	TRAD	48	1.62	25.36	8.23	66.41	1079	1209	5536	476
Air Nostrum	TRAD	58	1.42	25.77	1.72	72.51	511	970	782	342
Olympic Air	TRAD	32	1.32	7.12	0.00	92.88	318	956	0	269
Iberia	TRAD	36	1.30	44.25	21.81	33.94	1995	1316	5752	465
Volotea	LCC	85	1.23	40.59	0.37	59.04	883	1133	1319	709
Brussels Airlines	TRAD	74	1.20	84.71	15.21	0.08	1259	1118	2048	309
Total/Average		309	60.96	53.30	16.41	30.29	1163	1085	2610	516

summarizes the traffic structure of the top twenty airlines in terms of number of departures in 2019. Lufthansa topped the list with 8.16% of the total departure flights in the EU, almost same as the thirteen smallest countries in terms of volume from Table A1. It was followed by Ryanair, with 7.54% of the departures. Ryanair led in terms of network reach, operating from 171 distinct airports in the EU out of the total 309 that these airlines covered.

Grouping by flight type, Brussels Airlines had the biggest proportion of EUR flights (84.71%), followed by Austrian (77.09%). The airline with the highest proportion of NAT flights was Olympic (92.88%), followed by Air Nostrum (72.51%). The airlines with the highest volumes of INT flights were Wizz Air (32.52%) and Ryanair (28.10%), since some of their key destinations, namely, the United Kingdom and the Middle East, are outside of the EU but close enough as to be serviced by their fleet. The difference with the TRAD airlines was observed in analysis of the average distance; Iberia’s INT flights had an average distance of 5752 km due to its strong connectivity with Latin America, whereas Wizz Air and Ryanair recorded average distances of 1540 and 1389 km, respectively, due to their operational focus on the European region and its immediate surroundings.

Table 3. Traffic structure in 2024 of the top twenty EU airlines based by number of departures.

Airline	Type	Departure Airports	Departure Flights (%)	Departure Flights per Type (%)			Average Distance (km)	Average Distance (km)
				EUR	INT	NAT		EUR	INT	NAT
Ryanair	LCC	189	16.57	61.95	19.10	18.95	1200	1308	1329	720
Lufthansa	TRAD	101	6.28	59.53	15.24	25.23	1258	947	3902	397
Air France	TRAD	78	3.92	43.05	21.02	35.92	1595	938	4695	569
EasyJet Europe	LCC	83	3.72	59.47	16.24	24.29	1036	1110	1292	684
Vueling	LCC	74	3.51	46.90	7.94	45.15	991	1108	1221	830
KLM	TRAD	70	3.34	73.43	26.39	0.18	1400	879	2860	131
Eurowings	LCC	102	2.77	87.35	9.31	3.34	1278	1341	995	418
SAS	TRAD	81	2.61	55.28	20.26	24.46	1062	1061	1808	446
ITA	TRAD	36	2.09	24.23	9.15	66.61	964	855	4172	562
Austrian	TRAD	85	2.00	82.33	13.93	3.73	1003	818	2301	242
Aegean	TRAD	99	1.89	41.86	10.30	47.85	979	1638	1460	299
Finnair	TRAD	71	1.71	67.62	12.14	20.25	1436	1294	3802	493
Wizz Air Malta	LCC	83	1.70	67.23	29.21	3.56	1429	1441	1472	848
TAP Portugal	TRAD	45	1.66	59.34	20.66	20.00	1838	1462	3982	739
Volotea	LCC	100	1.64	45.31	2.25	52.43	914	1184	1012	677
LOT Airlines	TRAD	76	1.62	58.64	16.66	24.70	1109	942	2919	285
Wizz Air	LCC	77	1.48	69.05	30.32	0.62	1447	1423	1525	213
Iberia	TRAD	47	1.44	51.73	24.05	24.22	2225	1362	5879	440
Transavia France	LCC	77	1.33	62.17	22.89	14.94	1457	1481	1910	660
Air Nostrum	TRAD	51	1.33	26.19	2.53	71.28	514	973	845	334
Total/Average		381	62.63

shows the same set of data for 2024. Sixteen of the airlines remain in the list, plus Alitalia now converted in ITA. The new joiners were Aegean, which replaced its subsidiary Olympic Air, Wizz Air Malta, and Transavia France, increasing the number of LCCs from six to eight. This indicates that the low-cost carrier (LCC) model not only endured the challenges of the pandemic but may have even benefited from them, highlighting the relative resilience of leisure travel compared to the business travel sector. The airlines that dropped from the list were the already mentioned Olympic Air, Air Europa, and Brussels Airlines. The airlines included in the analysis accounted for 62.62% of total departures. Within this group, LCCs made up 32.72% in 2024, an increase from 23.54% in 2019, surpassing TRAD airlines, whose share declined from 37.42% in 2019 to 29.89% in 2024. For instance, Ryanair overtook Lufthansa as the airline with the highest number of departures, accounting for 16.57% of the total, 2.6 times more than Lufthansa, whose share declined from 8.16% to 6.28%, mainly due to the reduction in NAT flights. The network coverage of Ryanair was also higher, departing from 189 airports, compared with the 102 of Eurowings and 101 of Lufthansa. Per type of flight, Eurowings had the highest proportion of EUR flights, 87.35%. The airline with the lowest percentage was ITA, with 24.23%. Wizz Air had the highest proportion of INT flights (30.32%) followed by its subsidiary Wizz Air Malta (29.21%). Air Nostrum had the highest share of NAT flights at 71.28%, as it operates under a franchise agreement with Iberia, managing part of its regional services. Consequently, Iberia had the longest average flight distance, 2225 km and the highest average for INT flights, 5879 km. Air Nostrum operated the shortest flights, with 514 km on average.

3.2.2. Fuel Uptake and Efficiency

Table 4. Fuel uptake and efficiency in 2019 of the top twenty EU airlines by number of departures.

Airline	Fuel Loaded (MTn) *	% of Total EU Fuel	Fuel Burnt per Type of Flight (%)			Average CO2 (kg)/RPK	Average CO2 (kg)/RPK
			EUR	INT	NAT		EUR	INT	NAT
Lufthansa	3.57	9.27	26.93	65.67	7.40	0.133	0.117	0.106	0.183
Ryanair	2.15	5.58	60.23	29.11	10.67	0.081	0.076	0.079	0.101
Air France	2.48	6.45	14.05	75.12	10.84	0.113	0.107	0.098	0.125
Eurowings	0.88	2.30	69.19	13.64	17.17	0.109	0.090	0.112	0.149
Vueling	0.86	2.23	54.92	7.65	37.43	0.095	0.082	0.092	0.111
EasyJet Europe	0.83	2.16	62.53	12.15	25.32	0.094	0.086	0.084	0.111
KLM	1.54	3.99	30.58	69.42	0.00	0.122	0.124	0.117	0.000
SAS	0.67	1.74	53.18	33.07	13.76	0.134	0.119	0.112	0.183
Alitalia	0.88	2.28	16.60	49.58	33.82	0.131	0.109	0.106	0.143
Wizz Air	0.84	2.19	65.37	34.58	0.05	0.075	0.076	0.071	0.209
Austrian	0.55	1.42	50.73	47.91	1.36	0.116	0.115	0.095	0.176
Finnair	0.72	1.86	43.86	49.58	6.57	0.131	0.118	0.101	0.171
LOT Airlines	0.42	1.09	35.77	57.99	6.23	0.124	0.123	0.101	0.141
TAP Portugal	0.72	1.87	44.51	46.35	9.13	0.102	0.088	0.090	0.152
Air Europa	0.47	1.22	23.70	50.51	25.78	0.131	0.085	0.072	0.156
Air Nostrum	0.12	0.31	43.14	2.45	54.41	0.162	0.106	0.124	0.182
Olympic Air	0.12	0.31	20.24	0.00	79.76	0.163	0.089	0.000	0.169
Iberia	0.89	2.32	18.42	73.80	7.78	0.099	0.085	0.084	0.127
Volotea	0.23	0.60	48.10	0.49	51.42	0.107	0.098	0.088	0.114
Brussels Airlines	0.34	0.87	68.59	31.38	0.03	0.102	0.102	0.106	0.150
Total/Average	19.27	50.06	38.84	48.46	12.71	0.113	0.100	0.095	0.145

* MTn = million tonnes.

shows the fuel consumption of the top twenty EU-based airlines in number of departures during 2019. Their consumption combined represented half of the fuel consumed in the region during that year. Their fuel efficiency was slightly better than the general average, suggesting that larger airline size and higher flight volumes may contribute to improved productivity and, consequently, greater operational efficiency. Lufthansa, the airline with the highest consumption, loaded 3.57 million tonnes of fuel in the EU. The following airline was Air France, with 2.48 million tonnes. Both combined added up to almost all the fuel provided by Spain during the year.

When comparing the efficiency values, the best results were obtained by Wizz Air, with 0.076 CO₂ kg per RPK. Olympic Air had the worse efficiency value, 0.169 kg of CO₂/RPK.

The data for 2024 is shown in

Table 5. Fuel uptake and efficiency in 2024 of the top twenty EU airlines by number of departures.

Airline	Fuel Loaded (MTn) *	% of Total EU Fuel	Fuel Burnt per Type of Flight (%)			Average CO2 (kg)/RPK	Average CO2 (kg)/RPK
			EUR	INT	NAT		EUR	INT	NAT
Ryanair	4.48	11.00	66.01	20.47	13.51	0.076	0.072	0.075	0.091
Lufthansa	2.97	7.30	28.69	64.37	6.94	0.114	0.102	0.097	0.151
Air France	2.37	5.81	15.01	76.03	8.96	0.114	0.104	0.097	0.135
EasyJet Europe	0.88	2.15	62.56	18.94	18.50	0.083	0.079	0.079	0.094
Vueling	0.84	2.06	51.55	9.24	39.21	0.085	0.076	0.076	0.096
KLM	1.53	3.75	30.93	69.02	0.05	0.114	0.113	0.117	0.319
Eurowings	0.78	1.91	90.80	7.59	1.61	0.084	0.080	0.099	0.166
SAS	0.62	1.52	47.24	41.69	11.07	0.111	0.103	0.096	0.142
ITA	0.61	1.50	16.52	48.59	34.89	0.111	0.100	0.091	0.118
Austrian	0.55	1.34	60.31	38.78	0.90	0.109	0.107	0.090	0.215
Aegean	0.43	1.05	63.64	14.04	22.32	0.112	0.072	0.079	0.154
Finnair	0.67	1.64	50.25	44.83	4.92	0.120	0.121	0.093	0.131
Wizz Air Malta	0.56	1.38	67.36	30.36	2.28	0.067	0.064	0.073	0.076
TAP Portugal	0.75	1.84	39.01	52.84	8.15	0.097	0.089	0.088	0.128
Volotea	0.35	0.86	54.48	2.42	43.10	0.095	0.083	0.099	0.104
LOT Airlines	0.43	1.05	40.69	51.68	7.63	0.133	0.111	0.083	0.219
Wizz Air	0.49	1.21	68.84	30.96	0.20	0.067	0.067	0.066	0.178
Iberia	1.08	2.66	20.66	74.73	4.61	0.085	0.074	0.073	0.121
Transavia France	0.43	1.07	62.91	28.44	8.65	0.080	0.073	0.075	0.121
Air Nostrum	0.12	0.29	44.20	3.77	52.03	0.147	0.097	0.115	0.166
Total/Average	20.94	51.39	45.78	42.99	11.23	0.095	0.087	0.085	0.123

* MTn = million tonnes.

. Except for Air France and LOT, all airlines included in both years lists improved their efficiency during the period either due to the increase in the average distance, the increase in the LF, fleet renewal, or a combination of these. Eurowings achieved the greatest reduction, lowering its efficiency parameter from 0.109 to 0.084 CO₂ kg/RPK, which was 23% less. The airline flew less (−28%), used less fuel (−11%), and flew longer flights (+34%). The same applied for SAS, which reduced the efficiency factor by 17%. It reduced the number of flights (−15%) and the fuel uptake (−7%), and increased the average distance flown (+13%). EasyJet Europe, however, improved its efficiency parameter (−11.7%) while increasing the number of departures (+2.13%), the average distance (+9.6%), and the fuel consumption (+6%). Ryanair, which widely increased its operations (+137%), improved its efficiency parameter (−6%) while decreasing the average distance (−8%) of its flights. Overall, the amount of fuel loaded by the airline increased by 108% in the period. Lufthansa experienced a sharper decrease in the efficiency parameter (−14%), the number of departures (−17%), and the amount of fuel loaded (−17%) while increasing the average flight distance (+4%). Overall, the best efficiency parameter was achieved by Wizz Air Malta in its INT flights during 2024, 0.064 CO₂ kg/RPK.

3.2.3. Fleet Structure

In general terms, the fleet operating within the EU increased from 6656 unique plates in 2019 to 6805 in 2024, a 2% increase. The average age decreased from 16.11 years to 12.08, a significant 25% change. Figure 6 captures the volume of flights operated by some of the most popular models in the period, both in 2019 and 2024.

The most used aircraft in the period were A320s and B738s, which covered 44% of the flights in both years, even when the relative relevance of each changed, with the Boeings surpassing the Airbus in 2024. In terms of plates, the B738 led with 1145 and 1160 respectively (17.20% and 17.05% of the total) and the A320 followed with 1128 units in 2019 and 1042 in 2024. These numbers are consequence of the LLC airlines’ business model, which focuses on maintaining a standardized fleet to achieve operational savings and hence limiting their networks to the range of their aircraft, in opposition to major TRAD airlines, which focus on covering a wider array of destinations. For instance, the main operator of the B738 was Ryanair with 292 units in 2019 (all its fleet except 1 aircraft) and 395 units in 2024 that represented 70% of the fleet and which covered 70% of the flights. The rest were operated with the B38M, the newest version of the aircraft. EasyJet Europe was the main operator of A320s, although ownership of this model is not as concentrated as in the case of the B738.

The newest versions of these models, the A20N and the B38M, were introduced around the same time and managed to capture 6.41 and 6.32% of the market, respectively, by 2024. The third and fourth models in terms of relevance during 2019, the A319 and A321, lost market presence, moving from 10.51 and 7.26% of the total flights to 6.52 and 5.04% respectively. The A321 maintained traction thanks to its newer version, the A21N, which covered 4% of flights in 2024. The A319s were replaced either by the biggest versions of the family (A20N, A21N) or by the BCS3 (Airbus A220-300), specifically designed for short-medium routes, depending on the needs of the operator. In both cases, the newer options present better fuel efficiency values. The shorter-haul regional fleet saw in general a decrease in volumes, except for the AT76, which captured part of the market served by its predecessor, the AT75, and the E190, which maintained its value. Older models such the DH8D and the CRJ9 lost relevance. Finally, newer long-range aircraft such as the A359 and B789 increased the significance of this fleet segment in terms of percentage of flights operated. However, due to their characteristics, their overall share remained relatively small. By comparison, the models shown in the graph accounted for 87.32% and 91.93% of total departures in 2019 and 2024, respectively.

At operator level, the number of plates controlled by the top twenty airlines by flight volume increased by 10% over the period, from 2395 in 2019 to 2642 in 2024, representing 36% and 39%, respectively, of the total plates included in the analysis. Among these, LCC’s accounted for 12% of the total fleet and TRAD for 23% in 2019. In 2024, these values were the 18% and 21%. Most of the jump is related to the fleet expansion carried out by Ryanair, which went from 293 unique plates in 2019 to 562 in 2024. Volotea was the next in terms of growth, adding 13 plates in the period, a 45% increase in its fleet. In absolute terms, Iberia added the most plates to its service, 19. Following its bankruptcy and following transformation into ITA, the former Alitalia lost 29 planes, 26% of its fleet. Lufthansa retired 43 plates, 12.6% of its fleet, and Wizz Air transferred 23 to its new subsidiary, Wizz Air Malta.

These changes in the fleet led to an improvement in the average age of the fleet, which for this group of airlines went from 15.51 years to 11.69 (−24%), close to the general value (−25%). Figure 7 depicts the evolution between 2019 and 2024 for the seventeen airlines that were both in the top twenty list of 2019 and 2024. The airline that achieved the highest reduction in its fleet age (−44%) was Alitalia/ITA thanks to the already mentioned decommission of older aircraft, which let them achieve one of the best values in 2024. Wizz Air, which had the youngest fleet in 2019, was surpassed only by its subsidiary, Wizz Air Malta, in 2024. In contrast, the oldest aircraft were operated by Volotea, Brussels Airlines, Austrian, and Air France. Among the airlines still included in the 2024 list, Volotea and Austrian continued to have the highest average aircraft age, although both achieved some reduction in this parameter over the period.

4. Discussion

4.1. Changes in the Period 2019–2024

Following the uncertainty caused by COVID-19 in the aviation sector, the results show that the EU not only recovered by 2024, but it experienced a 7.40% increase in the number of departures compared with 2019. This increase caused a rise of 5.86% in the volume of fuel consumed, and consequently, CO₂ emissions. The gap between the two values was a consequence of the improvement of the efficiency factor, which went from 0.111 to 0.098 CO₂ kg/RPK, 11.71%. As discussed, NAT flights experienced the biggest efficiency increase in relative terms (12.10%), followed by EUR flights, (11.34%) and INT flights (8.70%) which already started with the best values in absolute terms. This improvement in efficiency parameter was achieved through a combination of increases in occupation, average distance flown, and capacity offered and a decrease in fuel consumption, with the last two directly dependent on the fleet in use.

The LF, which was calculated based on the data available in Eurostat and was used to calculate the RPKs, changed from 0.81 in 2019 to 0.84 in 2024, a 5% increase. In alignment with the recovery trend, the NAT flights saw the highest increase, 8% (from 0.76 to 0.82) followed by EUR flights (4%, from 0.82 to 0.86) and INT flights (2%, from 0.83 to 0.85). Overall, NAT flights retained the lowest LF values and EUR flights surpassed INT flights. This means that the demand for air transport in the period not only reflected in the number of flights offered but also in how full they were, surpassing pre-COVID-19 values and pointing to further increases in the upcoming years, in alignment with the demand evolution forecasted by most relevant entities [5,45,46]. The average distance flown rose from 1418 km in 2019 to 1464 km in 2024, 3.02%, as captured in Table A2. Going into further detail, the increase was led by NAT flights, whose average distance flown increased 7% pointing towards a general increase in the internal connectivity of the countries, except for some exceptions already reviewed. The EUR flights also saw an increase in the average distance, which rose 5%. Finally, the distance of INT flights increased 1%. This situation is inherited from the recovery from COVID-19 restrictions, which progressed from national to regional and finally to international frameworks, delaying the reintroduction of long-range destinations by airlines due a slower recovery in demand.

The last two parameters, the number of seats and the fuel consumption, changed because of the revamp of the fleet. Airlines took the opportunity to retire older aircraft and progressively introduce the new replacements to accommodate the rebound in demand. In general, newer models such as the A20N or the B38M achieve a 20% reduction in the fuel consumption, which helps airlines not only to comply with environmental requirements, especially in the studied area [17,47] but also to reduce their operational costs, especially after the mandatory introduction of SAF in the EU [31,48,49,50,51]. For example, in the case of longer-range aircraft airlines such as Lufthansa, Air France, and Iberia opted to replace their long-range, four-engine models such as the A340 or A380 with the A359.

The renovation of the fleet increased the capacity offered by airlines; the average number of seats per segment moved from 163 in 2019 to 172 in 2024. Per type, NAT flights experienced the highest increase, from 133 to 143 (7%), followed by EUR, which went from 161 to 171 (6%), and INT, which moved from 193 to 200 (4%). Indeed, when analyzing the aircraft used during the period, it was observed that operators shifted towards using larger aircraft. In 2019, 24.57% of the flights within scope were operated by the A320 model, 19.45% by the B738, and 10.51% by the A319. The A20N and the A21N were still in the minority, operating 2.69% and 0.52% of the flights respectively. In 2024, these models were still the most relevant, but their operations had decreased. B738 covered 22.45% of the flights, the A320 the 21.56%, and the A319 just 6.52%. The market for the newer versions took off, with the A20N and A21N capturing 6.41% and 4.03% of the market. The B38M, with a very limited presence in 2019, operated 6.32% of the flights in 2024. Although there are variations between airlines and not all of them decide to utilize the densest configuration, the A320 can accommodate a maximum of 186 passengers, whereas the A20N can reach 194, 4% extra. Similarly, the A321 can accommodate a maximum of 220 passengers and the A21N, 244, almost 11% more. The change is more remarkable against the A319, which can hold a maximum of 156 passengers.

The fleet replacement helped increase the efficiency of the air transport sector, but it faces some challenges worth discussing. Firstly, there is the slower rate of delivery of new aircraft, linked to the effect of COVID-19 on the manufacturer’s supply chain [52] and certification problems faced by the Boeing 737 MAX following the grounding of the model [53]. The aircraft deliveries in 2024 were 30% below 2018 peak levels and 8% below 2023’s and, while the values are expected to increase in 2025, deliveries for the European market are estimated as 400 units [54]. Given that most flights in the region are operated with A320 and B738 aircraft, of which 15% and 12%, respectively, were over 20 years old at the end of 2024, modernizing this segment of the fleet is essential for airlines to meet their emission reduction targets, since the newer models can achieve up to 20% of emissions reduction in comparison [55,56]. Secondly, the impact that the decommissioned fleet will have both at the economic and environmental levels. While part of the older fleet can potentially be sold to other operators, cargo only airlines for example, this will trigger the final retirement of even older planes. While airlines are not forced to recycle their old aircraft and can opt for solutions such as permanently park them, it could be possible that future regulation would enforce their recycling. Some publications estimate that the recycling cost could vary between USD 109,000 for a twin-engine regional jet and USD 268,000 for a four-engine widebody aircraft, which, although limited in impact, would add to the already high transition costs [57]. Moreover, the use of complex new materials to improve the efficiency of aircraft results in an increase in the complexity of the recycling process [58,59].

The improvement of the efficiency parameter had a positive impact in the sustainability of the air transport industry. However, it is not enough to compensate the increase in emissions caused by growing demand. As analysed in this paper, the 11.71% improvement of the efficiency parameter achieved during the 2019–2024 period, while aligned with ICAO’s objectives [60], was not sufficient to reduce the net emissions, which grew 5.86% during the period. Several authors have proposed the implementation of market-based instruments to curb demand [12,13,61]. It is possible that the implementation of measures such as CORSIA, EU ETS, and RefuelEU could impact the demand through the rise of ticket prices because of the increase in operational costs for airlines [62,63,64]. Once the new policies are fully in place, it will be necessary to re-evaluate their impact in the market.

4.2. Policy Implications

4.2.1. CORSIA and EU ETS

CORSIA [65] and EU ETS [17] are the two principal regulatory mechanisms currently applied within the EU to mitigate the environmental impact of aviation. CORSIA, a global initiative led by ICAO, applies to all international flights of the participating countries, including all the UE members, whereas EU ETS only applies to flights in the European Economic Area (EEA) (EU countries plus Iceland, Liechtenstein, and Norway), the United Kingdom, and Switzerland. Based on the flight segmentation proposed in the Methodology section, the application of these measures is as follows:

• NAT: EU ETS;
• EUR: both CORSIA and EU ETS;
• INT: CORSIA and part of EU ETS.

In the case of CORSIA, airlines will have to offset all the emissions that surpass a certain threshold through the purchase of eligible carbon credits [65,66]. Under the EU ETS, operators are allocated a certain number of emission allowances. If their emissions exceed this allocation, they can purchase additional allowances from other sectors or operators with surplus credits, enabling compliance through market-based mechanisms.

Based on the methodology used throughout this paper, an analysis of the exposure of each airline to the discussed mechanisms was compiled.

Table 6. Percentage of emissions affected by each regulatory mechanism in 2024 of the top twenty EU airlines by number of departures.

Airline	Emissions Covered by Each Mechanism (%)
	EU ETS	CORSIA	EU ETS + CORSIA
Ryanair	13.51	3.80	82.68
Lufthansa	6.94	61.70	31.36
Air France	8.96	74.73	16.32
EasyJet Europe	18.50	4.94	76.56
Vueling	39.21	2.11	58.67
KLM	0.05	63.60	36.35
Eurowings	1.61	3.06	95.33
SAS	11.07	26.54	62.39
ITA	34.89	46.79	18.32
Austrian	0.90	35.13	63.97
Aegean	22.32	8.14	69.54
Finnair	4.92	38.89	56.18
Wizz Air Malta	2.28	21.36	76.36
TAP Portugal	8.15	47.85	44.00
Volotea	43.10	2.13	54.78
LOT Airlines	7.63	48.78	43.59
Wizz Air	0.20	17.19	82.61
Iberia	4.61	71.69	23.70
Transavia France	8.65	27.68	63.67
Air Nostrum	52.03	2.22	45.76

shows the percentage of emissions affected by each mechanism of the airlines analyzed in Section 3.2.1.

Among the airlines analyzed, Eurowings exhibited the highest proportion of emissions subject to both CORSIA and EU ETS, with 95.3% of its operations falling under these regulatory frameworks. The next four airlines in this ranking were all LCCs, with Aegean Airlines being the first TRAD carrier to appear. This distribution reflects the operational focus of LCCs, which typically concentrate on short- to medium-haul routes within Europe due to the range limitations of their preferred aircraft types. As a result, these carriers are disproportionately affected by the simultaneous application of both regulatory mechanisms. Despite often demonstrating strong emission efficiency and not necessarily being the largest contributors to overall emissions, LCCs may face higher offsetting costs unless targeted mitigation measures are introduced. Meanwhile, the airlines with lowest levels of emissions exposed to both regulations at the same time were Air France and ITA. Airlines with higher volume of domestic flights will be primarily subject to EU ETS, and those focused on long-haul international operations will have to dedicate more resources to CORSIA. It is important to notice that until 2026, only flights between states that voluntarily participate in CORSIA can be considered, which means that flights to countries such as India, Brazil, or China are excluded until 2027, when all international flights will fall in scope [66].

This context underscores the importance of adopting a transparent and standardized emissions accounting method, such as the one employed in this study using publicly available data, to ensure consistency across reporting entities. Such an approach helps validate reported emission figures, prevents double-counting, and strengthens the integrity of compliance with regulatory frameworks.

4.2.2. RefuelEU

One of the key findings of this study is the resilience of market consolidation at both the network and operator levels. Despite minor shifts, such as changes in the relative importance of certain airports or the strengthening of the LCC model, the overall concentration of departures remained largely stable throughout the period. This stability also extended to fuel distribution patterns, indicating that the core structure of EU air traffic has endured the disruptions caused by the pandemic with limited structural fragmentation. This structural consistency is particularly relevant in the context of the ReFuelEU Aviation initiative, which mandates a progressive increase in the share of sustainable aviation fuels (SAF) supplied at EU airports as part of the “Fit for 55” package, which aims to reduce the European Union’s (EU) emissions by at least 55% by 2030 relative to 1990 levels [21,31]. The application of the RefuelEU initiative relays in the distribution of a mix of SAF and traditional fuels across most of EU’s airports, increasing the percentage of SAF of the fuel progressively until 2025 [67,68]. The key purpose of this approach is to ensure that the impact of the measure affects equally to all players, since the main effect of the use of SAF is an increase in fuel prices [50,69]. However, based in the analysis undertaken in this paper, it could be possible to speed up the results of the initiative by focusing on a smaller set of airports. For example, the distribution of SAF to the airports supplied by the Central Europe Pipeline System (CEPS) [26], which was discussed in the working document of the plan [70], would ensure that SAF is delivered to Brussels (BRU), Frankfurt am Main (FRA), Luxembourg (LUX), and Amsterdam Schiphol (AMS), with minimal logistic costs. Assuming that the relevance of the airports in their percentage of fuel distribution would remain the same as in the data provided in Table 5, these four airports would account for the 16.37% of the fuel distributed in the EU. In order to achieve the first SAF ramp-up objectives of 2% in 2025 and 5% in 2030, it would be enough to supply a 12.2% SAF mix in 2025 and 30.5% by 2030 through the pipeline in order to cover the requirements of ReFuelEU for the whole EU. This would allow suppliers to include SAF from almost all available pathways, since the maximum blending ratio acceptable at this point, 50%, would not be achieved. In achieving the maximum 50% ratio, 8.2% of the total amount of SAF for the whole EU would be provided, almost half of the 2035 objective just focusing on four airports. However, The EU would need to implement financial instruments to compensate for the economic burden that the higher price of the SAF mix would have in airlines highly dependent on those airports (i.e., Lufthansa, KLM, Luxair, or Bussels Airlines).

A less centralized alternative would be the distribution of SAF to the main airports of each country, highlighted in

Table 7. Percentage of SAF necessary in the main airport of each EU member country to fulfil the ramp-up.

Country	Airport	% Fuel 2024	2025 (2%)	2030 (5%)	2035 (20%)	2040 (32%)	2045 (38%)	2050 (63%)
AT	VIE	93.71	2.13	5.34	21.34	34.15	40.55	67.23
BE	BRU	79.91	2.50	6.26	25.03	40.05	47.55	78.84
BG	BOJ	59.61	3.36	8.39	33.55	53.68	63.75	105.69
CY	LCA	67.9	2.95	7.36	29.46	47.13	55.96	92.78
CZ	PRG	84.32	2.37	5.93	23.72	37.95	45.07	74.72
DE	FRA	47.92	4.17	10.43	41.74	66.78	79.30	131.47
DK	CPH	84.45	2.37	5.92	23.68	37.89	45.00	74.60
EE	TLL	98.7	2.03	5.07	20.26	32.42	38.50	63.83
ES	MAD	35.24	5.68	14.19	56.75	90.81	107.83	178.77
FI	HEL	94.06	2.13	5.32	21.26	34.02	40.40	66.98
FR	CDG	61.44	3.26	8.14	32.55	52.08	61.85	102.54
GR	ATH	37.44	5.34	13.35	53.42	85.47	101.50	168.27
HR	ZAG	25.17	7.95	19.86	79.46	127.14	150.97	250.30
HU	BUD	97.9	2.04	5.11	20.43	32.69	38.82	64.35
IE	DUB	87.34	2.29	5.72	22.90	36.64	43.51	72.13
IT	FCO	36.69	5.45	13.63	54.51	87.22	103.57	171.71
LT	VNO	73.86	2.71	6.77	27.08	43.33	51.45	85.30
LU	LUX	100	2.00	5.00	20.00	32.00	38.00	63.00
LV	RIX	100	2.00	5.00	20.00	32.00	38.00	63.00
MT	MLA	100	2.00	5.00	20.00	32.00	38.00	63.00
NL	AMS	93.59	2.14	5.34	21.37	34.19	40.60	67.31
PL	WAW	43.82	4.56	11.41	45.64	73.03	86.72	143.77
PT	LIS	59.93	3.34	8.34	33.37	53.40	63.41	105.12
RO	OTP	63.46	3.15	7.88	31.52	50.43	59.88	99.28
SE	ARN	71.68	2.79	6.98	27.90	44.64	53.01	87.89
SI	LJU	100	2.00	5.00	20.00	32.00	38.00	63.00
SK	BTS	68.54	2.92	7.30	29.18	46.69	55.44	91.92

. Following the ramp-up approach, Table 7 shows the percentage of SAF, from the total fuel, that should be delivered in each of those airports to fulfil the requirements assuming that their relevance during 2024 in terms of fuel handled remains.

Taking into consideration the current allowable SAF mix ratio of 50%, airports could contribute, at maximum, half of the total provision. Once that threshold is reached (the amount has been written in italics), a second airport in the country should start providing SAF. For the period 2025–2030, the ramp-up requirements would be covered just by supplying SAF to the main airports of each member state. By 2035, only Spain, Greece, Croatia, and Italy, which have a more decentralized airport infrastructure, would have to distribute SAF to at least another airport in their network. Continuing with the exercise, in 2040, Bulgaria, Germany, France, Poland, Portugal and Romania would also need to receive SAF in at least a second airport unless the mix ratios had expanded. In this case, TRAD airlines would be more exposed to higher fuel prices, which would affect the level playing field unless other compensation measures were taken, such as subsidies for affected airlines or a taxation mechanism to help distributed the burden equally across all operators.

Both approaches would give time to the SAF market to mature while minimizing emissions associated with transporting SAF from production facilities to a dispersed network of EU airports. By concentrating initial deployment at high-traffic hubs or well-connected airports, consistent with the stable fuel distribution patterns identified in this study, ReFuelEU Aviation targets could be met more efficiently, reducing logistical burdens and supporting a smoother integration of SAF into existing operations.

5. Conclusions

This analysis focuses on two reference years: 2019, the last full year before the COVID-19 pandemic, and 2024, representing the post-pandemic recovery phase. By applying a standardized model to publicly available data, the study examines how the pandemic influenced the volume and structure of EU air traffic, including shifts in fleet composition and fuel usage. It further explores the operational changes that occurred during this period and their implications for fuel efficiency and CO₂ emissions. These findings offer a nuanced understanding of the evolving dynamics within the European aviation sector and provide evidence to support the refinement of environmental regulations and the development of more targeted, data-driven policy frameworks. The number of departures increased 7.40% while the general traffic structure remained. The four more relevant countries (Germany, Spain, France and Italy) accounted for more than half of the departures, showing the great level of concentration in the market. The split between types of flights had small variations, moving towards an increase in EUR flights at the expense of NAT ones, which led to an increase in average distance flown of 3.02%. The LF increased 5% and the average age of the fleet dropped from 16.11 years to 12.08, representing a 25% reduction. The combination of these factors contributed to the improvement of the average CO₂ efficiency parameter, which changed from 0.111 to 0.098 kg/RPK on average, a 11.71% variation. Consequently, the net amount of fuel consumed and hence, CO₂ emissions increased (5.86%) but remained below the rate of the number of departures.

The period saw the consolidation of the LCC model, with the top eight airlines reaching a third of the total departures in the region, reflecting the resilience of the leisure segment. LCCs also led in terms of efficiency, showing overall better values than TRAD airlines. The changes in the fleet, both in number of plates and type of aircraft used have been analyzed from both market and environmental perspective, investigating their impact in the decarbonization effort of the sector and discussing how the upcoming regulations could affect the demand in the EU and what extra measures should be taken to ensure a balanced impact across the sector. Despite the major disruption caused by the pandemic, environmental objectives remained firmly in place, driving improvements in efficiency and operational performance. The challenges associated with the implementation of CORSIA, the European Union Emissions Trading System, and RefuelEU Aviation must be addressed to ensure that the aviation sector can meet its climate targets while maintaining competitiveness and fairness across all market segments. At the same time, these efforts are essential for building a more sustainable and resilient aviation industry that is better equipped to face future challenges and aligned with long-term climate objectives.