Social and Economic Impacts of the Air Transport Industry: a MRIO Approach

SOCIAL AND ECONOMIC IMPACTS OF THE AIR TRANSPORT INDUSTRY: A MRIO APPROACH PhD TESIS Andoni Txapartegi Etxebeste Supervised by Dra. Pilar González Casimiro. University of the Basque Country Dr. Ignacio Cazcarro Castellano. University of Zaragoza Doctoral Programme in Economics: Tools of Economic Analysis 2025 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 (cc) 2025 Andoni Txapartegi Etxebeste (cc by 4.0) 2 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 3 Acknowledgements This thesis marks the end of a long and demanding journey, one that I could not have undertaken alone. I would like to express my deepest gratitude to all those who have supported and accompanied me throughout this process. First and foremost, I am sincerely thankful to my supervisor, Ignacio Cazcarro Castellano, for his unwavering guidance, dedication, and support. From the very beginning, his patience, insightful feedback, and constant encouragement have been essential to the development of this thesis. I also had the pleasure of carrying out a research stay at the University of Zaragoza, where Nacho works, which further enriched our collaboration and gave me the opportunity to interact with a vibrant academic environment. Working with him has been an incredibly valuable academic and personal experience. I would also like to thank María Pilar González Casimiro for her role as codirector and her institutional support throughout these years. I am grateful to María Ángeles Cardoso and André Carrascal, who kindly acted as external reviewers and provided thoughtful and constructive evaluations of this thesis. This thesis would not have begun without the opportunity and support provided at Metroeconomica, where the foundations of this research were laid. I am especially grateful to Ibon Galarraga, who gave me the chance to start this path and encouraged me at a crucial moment. I also want to thank the entire team at Metroeconomica, whose professional and human qualities created a truly motivating working environment during the initial stages of this journey. I am also thankful to the doctoral programme coordinators, the Department of Economic Analysis and the Institute of Public Economics for facilitating the academic framework in which this work has developed. Finally, I am especially grateful to my family and friends, who have been a constant source of support, understanding, and patience throughout these years. Their presence has helped me overcome the most difficult moments and has made the good ones even more memorable. Thank you all for being part of this chapter in my life. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 4 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 5 Index Introduction ................................................................................................................................ 18 Background and motivation .................................................................................................... 19 Research Questions and Methodological Approach ............................................................... 20 Outline of the Thesis ............................................................................................................... 27 References ............................................................................................................................... 30 1. The air transport sector of the Central Europe Functional Airspace Block: an analysis of the socioeconomic relevance ...................................................................................................... 35 1.1 Introduction ................................................................................................................ 36 1.2 Methodology ............................................................................................................... 39 1.2.1 Input-Output analysis .......................................................................................... 39 1.2.2 Multiregional Input Output ................................................................................. 41 1.2.4 Aviation as supporter of tourism and trade ............................................................... 43 1.2.5 Data ............................................................................................................................ 45 1.3 Assessing the Economic Importance of the Air Transport Sector ............................... 47 1.4 Impacts on Aviation-Dependent Sectors .................................................................... 54 1.4.1 Tourism ....................................................................................................................... 54 1.4.2 Trade .......................................................................................................................... 57 1.5 Aggregated Impact ...................................................................................................... 60 1.6 Conclusions ................................................................................................................. 62 1.7 References ................................................................................................................... 66 2. European Aviation Measures to Reduce Emissions ............................................................ 69 2.1 Introduction ................................................................................................................ 70 2.2 Overview of the European Aviation Industry .............................................................. 72 2.3 Greenhouse Gas Emissions from Aviation .................................................................. 73 2.4 Regulatory framework ................................................................................................ 79 2.4.1 International agreements........................................................................................ 79 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 6 2.4.2 European regulation ................................................................................................ 81 2.5 Technological Innovations in Aviation ........................................................................ 84 2.6 Operational Measures to Reduce Emissions ............................................................... 86 2.7 Economic Instruments for Emission Reduction .......................................................... 88 2.8 Future Trends, Challenges, and Barriers to Emissions Reductions in the European Aviation Sector ........................................................................................................................ 91 2.8.1 Barriers to Emissions Reductions ............................................................................... 91 2.8.2 Challenges and Opportunities to Emissions Reductions ............................................ 92 2.8.3 Future Trends ............................................................................................................. 93 2.8.4 Potential Areas for Further Research ......................................................................... 94 2.9 References ................................................................................................................... 95 3. Short-haul flights ban in France: relevant potential but yet modest effects of GHG emissions reduction .................................................................................................................. 100 3.1 Introduction .............................................................................................................. 101 3.2 Methodology ............................................................................................................. 103 3.2.1 Data availability ........................................................................................................ 106 3.3 Results ....................................................................................................................... 107 3.3.1 IO limitations and uncertainty discussion ................................................................ 113 3.3.2 Recent evidence on actual routes and flights .......................................................... 114 3.4 Conclusions ............................................................................................................... 115 3.5 References ................................................................................................................. 118 4. The Economic and Environmental Impact of Limiting Air Routes Where There is a Rail Alternative: A Case Study of Spain ............................................................................................ 124 4.1 Introduction..................................................................................................................... 125 4.2 Methodology ................................................................................................................... 129 4.2.1 Data availability ........................................................................................................ 130 4.3 Definition of Scenarios .................................................................................................... 131 4.3.1. Main scenarios ........................................................................................................ 131 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 7 4.3.2 Current status of short-haul flights in Spain ............................................................ 132 4.3.3 Current state of high-speed trains prices in Spain ................................................... 134 4.3.3 Affected routes and summary of scenarios implemented accordingly ................... 136 4.4 Results ............................................................................................................................. 139 4.4.1 Socioeconomic effects ............................................................................................. 139 4.4.2 Greenhouse gas emissions ....................................................................................... 142 4.5 Conclusions...................................................................................................................... 145 4.6 References ....................................................................................................................... 149 5 General conclusions and future research ......................................................................... 158 Annex I - Classifications ............................................................................................................. 166 Annex II – Supplementary material chapter 1 .......................................................................... 174 Annex III – Supplementary material chapter 3 ......................................................................... 187 Annex IV – Supplementary material chapter 4 ......................................................................... 192 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 8 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 9 List of tables Table 1.1:The spatial distribution of impacts associated with the hypothetical removal of the air transport sector ..................................................................................................................... 49 Table 1.2: Origin of products and services that satisfy the final demand of air transport sector in FABEC countries. ..................................................................................................................... 51 Table 1.3: The value-added and emissions generated to satisfy the final demand of air transport services in FABEC area relative to the total of the FABEC area. ................................. 52 Table 1.4: Geographical destination of the investments of the air transport sector of each FABEC country. ............................................................................................................................ 53 Table 1.5: Most affected sectors by the cessation of air tourism in the FABEC countries (billion €) ................................................................................................................................................. 56 Table 1.6: Weight of the air transport sector versus the weight of its extraction ...................... 62 Table 2.1: Evolution of aviation emissions in European countries ............................................. 76 Table 3.1: Prices used for cost estimation (average prices) ...................................................... 107 Table 3.2: Economic effects of both scenarios isolating air transport and including substitution by train (millions of € and number of employees) .................................................................... 109 Table 3.3: Most affected sectors in terms of output besides air transportation (NACE classification) ............................................................................................................................. 110 Table 3.4: Most affected countries and regions in terms of output ......................................... 111 Table 3.5: CO2 emissions change relative to their totals in France ........................................... 112 Table 4.1: Affected routes and their corresponding train alternative time .............................. 132 Table 4.2: Number of passengers and flights of the selected air-routes in 2019 and 2023 ..... 134 Table 4.3: Summary of Scenarios and variants (baseline and sensitivity tests) ........................ 139 Table 4.4: Most affected sectors in Spain (NACE classification) besides air transport (output loss) ........................................................................................................................................... 142 Table 4.5: Multiplier change ..................................................................................................... 144 Table 4.6: % change in GHG emissions/% change in Output for high-speed train and flight comparison ................................................................................................................................ 144 Table I.1: List of countries ......................................................................................................... 167 Table I.2: List of NACE sectors ................................................................................................... 167 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 16 MBM: Market-Based Measure MRIO: Multiregional Input-Output PBN: Performance-Based Navigation SAF: Sustainable Aviation Fuel SC-GHG: Social Cost of Airliner Emissions SES: Single European Sky SNCF: Société Nationale des Chemins de fer Français UN SDG: United Nations Sustainable Development Goals REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 17 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 18 Introduction REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 19 Background and motivation Air transport plays an essential role in the global economy and the functioning of modern societies. As a key enabler of economic integration, technological exchange, and human mobility, aviation connects markets, facilitates trade in high-value and time-sensitive goods, and supports global tourism and business travel. According to the Air Transport Action Group (ATAG), aviation supports over 88 million jobs worldwide and contributes approximately 3.5 trillion $ to global GDP when accounting for its direct, indirect and induced effects (ATAG 2020). In 2019, before the COVID-19 pandemic disrupted global mobility, more than 4.5 billion passengers and 57 million tonnes of cargo were transported by air (ICAO 2021), underlining the strategic significance of this sector for economic resilience and globalization. Thus, notwithstanding the severe impact of the COVID-19 crisis on the sector in recent years, data from 2024 indicate that air traffic demand has reached a historic peak, surpassing pre-pandemic levels recorded in 2019 (IATA 2025). Within the European Union (EU), the aviation sector plays a particularly central role in enabling regional integration, labour mobility, and cohesion among member states. The EU hosts one of the densest and most liberalized air transport markets in the world, with over 100 carriers operating under the EU’s common aviation area. This regulatory environment has allowed for the rapid expansion of both network and low-cost carriers, facilitating connectivity across metropolitan areas and peripheral regions alike (European Commission 2019). Aviation in EU supported around 12.2 million jobs and contributed over 700 billion € in GDP in 2019, making it a core sector for economic growth and territorial cohesion (European Commission 2019; Abate and Christidis 2020). However, while commercial aviation has come close to reaching prepandemic levels, it still falls slightly short of a full recovery (Eurostat, 2025). While aviation brings clear economic and social benefits, it also contributes significantly to environmental degradation, particularly through greenhouse gas emissions (GHG). It accounts for approximately 2.5% of global CO₂ emissions, and its impact is magnified by additional highaltitude effects such as contrails and NOₓ emissions, potentially tripling its net radiative forcing (European Commission 2021; Lee et al. 2021). The urgency of mitigating climate change has changed the political landscape in EU and beyond. The European Green Deal, adopted in 2019, commits the EU to achieving net zero emissions by 2050. Complementary initiatives, such as the 'Fit for 55' package, aim to reduce emissions by 55% by 2030 compared to 1990 levels (European Commission, 2023). These commitments will require profound changes in all sectors, REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 20 particularly transport, which is responsible for around 25% of the EU's greenhouse gas emissions (EEA 2025). The transition to a low-carbon aviation sector poses complex challenges and continues to represent a major and unresolved policy and research topic. While other sectors have seen emissions decline, aviation emissions in the EU increased by more than 120% between 1990 and 2019 (EEA 2024). The sector’s reliance on fossil-based kerosene, long aircraft lifespans, and the limited availability of viable technological alternatives complicate decarbonization. Electric and hydrogen-powered aircraft remain in early development stages, while sustainable aviation fuels (SAFs), despite their promise, are costly and face production scalability issues (Gössling and Humpe 2020; ICCT 2022). In this framework, the EU has introduced regulatory instruments such as the EU Emissions Trading System (EU ETS), the Refuel EU Aviation regulation, and carbon offsetting schemes. However, while demand-side interventions such as taxes, modal shift to rail and short-haul flight bans have attracted attention, they remain controversial due to their potential socio-economic impacts and modest isolated environmental benefits (Larsson et al. 2019; Gössling and Humpe 2020). As a result, much of the debate continues to focus on supplyside solutions (European Commission, 2021). In this context, the academic literature reveals several gaps. First, most studies have focused on specific technological solutions or on the aggregate climate impacts of aviation, with relatively less emphasis on the systemic, economy-wide implications of regulatory interventions (Hasan et al., 2021; Lai et al., 2022; Mayer and Ding, 2023). Second, there is a scarcity of multiregional or spatially explicit analyses capable of capturing interregional trade-offs, indirect effects, and sectoral spill-overs. Third, policies such as short-haul flight bans, though increasingly discussed, have only recently begun to be evaluated rigorously in terms of both environmental and economic consequences. Research Questions and Methodological Approach To conduct this analysis, the thesis adopts input-output (IO) modelling as its principal analytical framework. IO models, first formalised by Nobel laureate Wassily Leontief in 1936, are quantitative economic models that represent the interdependencies between different sectors of a national economy or different regional economies. The core of IO analysis is the inputoutput tables (supply and demand tables), which show the dependence of each sector on the others, both as a customer of products from other sectors and as a supplier of inputs. These inter-sectoral relationships are expressed in matrix form, where the entries in the column REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 21 represent the inputs of an industrial sector, while the entries in the row represent the outputs of a given sector. In this way, I-O models are able to capture interdependencies between sectors and regions by tracking the flow of goods and services within and between economies (Leontief, 1936; Miller and Blair, 2022). Input-output analysis is widely utilized in empirical economics and policy development because of its ability to simulate and track economic chain effects. It provides the analytical basis for examining how economic shocks, policy changes, or external shocks affect sectoral output, employment, income, and trade, allowing researchers to answer hypothetical questions: what happens to total output if demand for a specific product increases? How will supply chain linkages amplify or attenuate the impact? This transparency and granularity make IO models highly adaptable to a variety of contexts, such as macroeconomic planning, environmental accounting, and transport infrastructure analysis. For example, IO models have been used to estimate employment and value-added multipliers of public investment (Dwyer et al. 2004); assess the impact of natural disaster on regional economies, such as after hurricanes or earthquakes (Rose and Liao 2005; Okuyama and Santos 2014); support environmental footprinting, especially for carbon, energy, water, and land use (Wiedmann 2009; Lenzen et al. 2013; Ivanova et al. 2016); and assess trade dependencies and global value chain risks (Meng et al. 2014). Governments and international organizations such as the European Commission, OECD, and UN have institutionalized IO tables in their toolkits for national accounting and sustainability monitoring. Moreover, IO tables are the basis of many economic models, in particular computable general equilibrium (CGE) models, which have further extended the analytical scope of this approach (Rose, 1995). Within the IO framework, there are both demand-based models and price models (Miller and Blair 2022). The demand-driven model, introduced by Leontief (1936), assumes that production is determined by final demand (consumption, exports, government spending). It answers the question: how much output must each industry produce to meet a specific level of final demand. In contrast, price models, also called Ghosh models, analyse how changes in primary input costs (e.g., wages, raw material prices) affect output prices across sectors (Ghosh, 1958; Leontief, 1946; Miller and Blair, 2022; Pyatt, 1985). These models are often used to understand the propagation of cost shocks or taxation through an economy. While less prevalent in empirical literature, price models are valuable for tax incidence analysis and inflation dynamics. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 22 In IO analysis, multipliers provide a measure of the total economic impact resulting from a oneunit change in final demand. These multipliers are used to see how these changes affect the economy. Thus, the value-added multiplier indicates the increase in gross value added (GVA), while the employment multiplier estimates total job creation, both within the initiating sector and along the supply chain (Rose and Casler 1996; Dietzenbacher 2005; Eurostat 2008; Bess and Ambarg 2011; Miller and Blair 2022). These indicators are widely used for policy impact evaluations, regional planning, and investment appraisal. Employment multipliers can differ significantly across sectors, reflecting labour intensity, productivity, and input structures. IO models represent the interdependent relationships between different sectors of an economy. In single-region IO models, trade with the rest of the world is introduced via import and export vectors. Imports are treated as leakages, subtracting value from domestic demand, while exports are considered as injections, representing foreign demand for domestic products (Pyatt 1985; United Nations 1999; Miller and Blair 2022). This structure is well-suited for analysing the domestic impact of export shocks or import substitution policies. However, it cannot capture inter-country feedback loops (i.e., how changes in one country affect others and vice versa), which limits its effectiveness in globalized economic analyses. Multiregional Input-Output (MRIO) models represent an evolution of the traditional IO framework by integrating multiple interconnected regions into a single coherent system (Isard 1951; Chenery 1953; Moses 1955; Miller and Blair 2022). These models allow for the simultaneous analysis of economic activities across several countries or sub-national regions, capturing both intra-regional production-consumption cycles and inter-regional trade flows. By explicitly modelling interdependencies between regions, the MRIO framework enable analysts to trace the origin and destination of goods and services along global and regional supply chains (United Nations 1999; Wiedmann 2009; Lenzen et al. 2013; Tukker and Dietzenbacher 2013; Miller and Blair 2022). MRIO models are particularly powerful in contexts where globalisation, trade liberalisation, and transboundary environmental challenges require integrated analysis. Given the inherently international nature of the aviation sector, such models prove particularly valuable for capturing cross-border economic interactions, as demonstrated in this study. The application of such input-output methodologies to the aviation sector remains relatively novel in the academic literature, thereby constituting a meaningful contribution. Moreover, they are used extensively to study the spatial distribution of environmental footprints, carbon leakage from developed to developing countries, and the embedded environmental and socio-economic effects of trade. In REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 23 sustainability research, MRIO models are essential for assessing shared responsibility between producers and consumers across borders, allowing for more informed policymaking under frameworks such as the United Nations Sustainable Development Goals (UN SDGs) and the European Green Deal. Given the substantial challenges the aviation sector poses to climate change mitigation, the use of such modelling frameworks is of considerable interest. The complexity of the construction of MRIO lies in the harmonisation and reconciliation of economic statistics, trade data, and sectoral classifications across regions. Harmonisation is necessary to ensure that outputs from one region correctly align with inputs in another. Such models require large-scale data compilation, reconciliation of international trade asymmetries, and the incorporation of satellite accounts (e.g., emissions, energy use, land use). MRIO analysis typically relies on advanced mathematical tools and matrix algebra, extending the basic Leontief model to include interregional trade matrices that capture the movement of goods and services across geographical boundaries. The increasing availability of global trade and environmentlinked datasets has facilitated the growth of MRIO research in areas such as climate change, sustainable resource use, and green industrial policy. Despite their sophistication, MRIO models face methodological challenges, including data uncertainty, aggregation errors, and issues of double counting. Nevertheless, they remain among the most robust tools for integrated global economic-environmental analysis. One of the principal advantages of IO analysis, particularly in its multiregional (MRIO) form, is its capacity to integrate environmental data alongside economic transactions in a consistent, system-wide framework. These environmental extensions enhance the analytical power of IO models, enabling comprehensive sustainability assessments by quantifying how production and consumption activities contribute to a range of environmental pressures, including greenhouse gas emissions, energy use, water consumption, and material extraction. Consequently, environmental multipliers serve as a foundational mechanism for the development of environmental extensions and satellite accounts within input-output (IO) models (Kitzes, 2013; European Union, 2011; Giljum et al., 2015). In operational terms, environmental extensions are constructed by associating sectoral economic output with corresponding physical environmental data, such as CO₂ emissions, electricity usage, or water withdrawals. These data are typically incorporated into the model through satellite accounts, which allow the analyst to trace environmental impacts throughout complex global supply chains. This enables a systems-based perspective that captures not only REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 24 the direct environmental burdens of specific sectors but also the indirect impacts transmitted through inter-industry linkages. Such a framework is essential for the calculation of consumption-based environmental footprints, which reassign environmental pressures from the point of production to the point of final consumption. In contrast to conventional territorial accounting, which attributes emissions and resource use solely to the country in which they occur, environmentally extended IO models reveal the global distribution of environmental burdens associated with consumption in a given economy. For example, the emissions generated during the production of imported electronics or garments are allocated to the country where these products are consumed, thereby supporting a more equitable and transparent approach to environmental responsibility (Wiedmann 2009; Peters et al. 2011). The scope of applications for environmentally extended IO analysis is broad and policy relevant. Among its most prominent uses are carbon footprinting, which quantifies total greenhouse gas emissions linked to consumption activities (Minx et al. 2009; Wiedmann 2009; Lenzen et al. 2013), energy and resource efficiency evaluations, especially in sectors characterized by high embodied energy (Lenzen 1998), water footprint analysis, particularly relevant in water-scarce or water-intensive economic contexts (Cazcarro et al. 2014) and material flow and circular economy assessments, which are instrumental in monitoring resource sustainability and waste reduction (Ivanova et al. 2016) These analytical tools have become indispensable for informing national and international climate policy, corporate environmental performance assessments, and the design of sustainability frameworks such as the UN SDGs and the European Green Deal. Moreover, they underpin emerging regulatory mechanisms such as carbon border adjustment measures, which require robust methodologies for tracking the environmental content embedded in international trade. Although IO analysis has become a widely adopted framework in economic and environmental research, its methodological limitations have been well documented in the literature (Jensen 1980; Bickel 1987; Miller and Blair 2022; Oosterhaven 2024). At its core, IO analysis operates on aggregated representations of the economy, where sectors are treated as homogenous units with fixed inter-industry relationships. While this aggregation enables comprehensive modelling of economic interdependencies, but it often comes at the expense of detail at the sub-sectoral or firm level. In addition, one of the most commonly cited REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 25 limitations of IO models is the assumption of fixed technical coefficients, that is, production in each sector requires fixed proportions of inputs, regardless of price or technological change. Therefore, the model does not allow for input or factor substitution, nor does it incorporate price elasticity or behavioural responses to market dynamics. Furthermore, the IO framework assumes constant returns to scale, linearity, and static production techniques, all of which may oversimplify the complexity of the real-world economy (Miller and Blair 2022). Another key limitation is the absence of endogenous price mechanisms. Traditional IO models are quantity-driven and do not account for changes in prices due to supply shocks or demand surges. This makes the model less suitable for long-term forecasting or for analysing economic systems undergoing structural transformation (Oosterhaven 2024). Additionally, the static nature of IO models implies that time is not explicitly modelled, making it difficult to simulate dynamic economic adjustments beyond the short to medium term. The use of environmental extensions in IO models also introduces additional methodological challenges. These extensions typically rely on industry-average environmental coefficients, which may obscure important heterogeneity across firms, technologies, or production processes. In particular, environmental performance can vary widely even within the same economic sector. Moreover, the integration of environmental and economic data requires harmonization of classification systems, which is not always straightforward, especially in countries with limited statistical capacity or inconsistent data reporting. In MRIO models, these issues are compounded by the need to reconcile data across national boundaries, resolve trade asymmetries, and manage propagation of uncertainty through the global system (Wiedmann 2009; Tukker and Dietzenbacher 2013). However, for analyses focusing on the recent past, the present, or short-run projections, many of these limitations are considered acceptable, especially when the input data (e.g., emissions intensities, sectoral expenditures) are relatively up to date and empirically robust. Thus, IO analysis remains a well-established and methodologically mature approach, particularly in the field of environmental economics. The ability of IO models to capture the full network of interindustry linkages and to trace the indirect effects of final demand shocks throughout the economy provides unique insights that are often unattainable with other models and remain highly valuable valuable (Bickel 1987; Dietzenbacher et al. 2013; Miller and Blair 2022). 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Ecological Economics 224:108289. https://doi.org/10.1016/J.ECOLECON.2024.108289 Union PO of the E (2011) Environmentally extended input-output tables and models for Europe. United Nations (1999) Handbook on Supply and Use Tables and Input Output-Tables with Extensions and Applications Wiedmann T (2009) A review of recent multi-region input–output models used for consumptionbased emission and resource accounting. Ecological Economics 69:211–222. https://doi.org/10.1016/J.ECOLECON.2009.08.026 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 34 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 35 1. The air transport sector of the Central Europe Functional Airspace Block: an analysis of the socioeconomic relevance REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 36 1.1 Introduction The air transport sector is one of the most dynamic sectors of our economy and has grown markedly since the 1950s and especially in the 21st century in terms of Gross Domestic Product (GDP) and employment (World Bank, 2020). Thus, world passenger air traffic (expressed in Revenue Passenger-Kilometers) grew twice as fast as GDP since the 1950s to nowadays (IATA, 2022). Globally, 38.3 million passenger flights were made, and 4.5 billion passengers used this mode of transport in 2019 (ICAO, 2021). In addition, 57.6 million freight tones were transported in the same year (ICAO, 2021). Despite the significant downturn experienced by the aviation sector during the COVID-19 pandemic, recent data from 2024 reveal that global air traffic demand has not only recovered but surpassed the levels observed in 2019, marking a new historical peak (IATA, 2025). Air transport constitutes a fundamental pillar of modern economies, generating income not only within the sector itself but also across a wide range of related industries, particularly tourism and supply chain services (ATAG, 2020; ICAO, 2019). Its contribution extends beyond direct economic output, serving as a key enabler of regional and international connectivity, and as a catalyst for competitiveness and productivity gains (Perovic, 2013). Empirical studies demonstrate a strong correlation between air connectivity indices and economic performance indicators such as GDP per capita, trade volume, and investment flows (World Bank, 2020). A World Bank–IATA (2022) study found that a 1% increase in air cargo connectivity is associated with a 6.3% increase in international trade volume, illustrating the non-linear benefits of improved access. In the European context, aviation plays an especially pivotal role. Europe has developed the world’s most integrated regional air market, comprising over 100 scheduled airlines, nearly 400 commercial airports, and dozens of air navigation service providers operating under a harmonized regulatory framework (European Commission, 2016). The growing complexity of air traffic in Europe has prompted the development of new governance frameworks, most notably the Single European Sky (SES), which aims to improve the safety, efficiency, and environmental performance of air traffic management. A key element of SES is the creation of Functional Airspace Blocks (FABs), designed to organize airspace based on operational needs rather than national borders. Among these, the Central Europe one is called FABEC, which includes Belgium, France, Germany, Luxembourg, the Netherlands, and Switzerland, stands out as the most trafficked FAB in Europe, handling over 55% of total European air traffic. FABEC countries benefit from some of the highest levels of air connectivity globally, enabled by a dense network of intraREGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 37 European and intercontinental routes. Germany, France and Netherlands operate world-class hubs such as Frankfurt, Munich, Paris-CDG and Amsterdam, which not only serve their domestic markets but also act as gateways to Europe for global carriers FABEC is especially relevant due to its combination of small, highly open economies and larger states with major airlines and hub airports, making it a unique space for regional cooperation, economic interdependence, and integrated airspace management (Eurocontrol, 2022;FABEC, 2019; World Bank, 2021). This connectivity and the high air traffic density allows the economic relevance of aviation in the FABEC region to extend far beyond the sector’s direct contribution to GDP, with significant repercussions for key sectors such as international tourism and global trade. Tourism represents a critical pillar of economic activity that is highly dependent on aviation infrastructure. Globally, approximately 58% of international tourists travel by air, a figure that rises significantly for longhaul and high-spending segments, particularly in Europe (ITF, 2024). In this regard, the case of France is particularly relevant, as it the most popular destination for international visitors in the world (UN, 2024). Moreover, the citizens of FABEC countries, characterized by high per capita income levels and a strong propensity to travel, are themselves significant drivers of outbound tourism demand, generating substantial economic impacts in the destinations they visit. Thus, Germany and France rank third and fifth globally, respectively, in terms of outbound tourism expenditure (UN, 2024). Their frequent international mobility contributes to tourism-related revenues abroad, reinforcing the transnational economic relevance of aviation beyond national borders. Moreover, this area encompasses several of the world’s most export-oriented and globally integrated economies; notably, Germany, France, and the Netherlands rank third, fifth, and sixth globally in exports of goods and services, respectively (World Bank, 2023). The air transport serves as a strategic enabler of high-value, knowledge-intensive sectors such as advanced manufacturing, pharmaceuticals, precision instruments, and digital services. These industries depend heavily on reliable, high-speed international connectivity, both for accessing global markets and for maintaining the competitiveness of their complex, time-sensitive supply chains. The objective of this study is to quantify the socio-economic significance of the air transport sector within the FABEC countries and to analyse the interconnections that exist between them through aviation-related activities. By examining the economic linkages between the air transport sector and other industries and analysing the impacts of the directly dependent activities, this research aims to provide insights that are valuable for policy-makers, regulators, REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 38 and sectoral stakeholders, enabling them to design more effective and coordinated strategies for the governance, planning, and operation of the aviation system in Central Europe. More broadly, this study aims to develop a comprehensive methodological framework for assessing the socio-economic significance of the air transport sector. While various approaches exist in the literature, this work integrates multiple techniques to offer a more holistic perspective, one that captures the unique characteristics of aviation. Specifically, the sector is not only a demander of inputs but also serves as a provider of transport services essential for other industries, and as a facilitator of passenger mobility, which in turn stimulates additional economic activities at destination. To assess the significance of the aviation sector in FABEC countries, this study applies extraction methods (see Miller and Lahr (2001) and Dietzenbacher et al. (1997)) which evaluates the ripple effects of removing a sector by quantifying the disruption to its direct and indirect suppliers. Additionally, a variant known as the Global Extraction Method (GEM) (Dietzenbacher et al. 2019) is employed to simulate international substitution effects, offering a broader, though more assumption-sensitive, perspective on cross-border economic dependencies (The corresponding results are presented in the Supplementary Material). Complementarily, the analysis traces the sector’s final demand and investment to understand the input requirements necessary to meet aviation-related services. This includes stylized scenarios simulating reductions in demand, such as those arising from climate policies or investment downturns. Finally, the study evaluates aviation’s enabling role for downstream sectors, particularly international trade and tourism. By modelling the effects of disrupted air deliveries or reduced tourist arrivals, the analysis captures both domestic and international spill overs, recognizing the bidirectional nature of aviation’s economic footprint on (Arto et al. 2015). In order to do so, we make use of the framework of the Input-Output (IO) databases and models, which are commonly used to measure economic impacts across a broad spectrum of subjects at international, national or regional level (Leontief, 1967; Leurent et al., 2015, Ali et al., 2021; Miller and Blair, 2022). This approach is often used in (multi)sectoral analyses in order to determine, for example, how a change in a certain sector may affect the rest of the sectoral structure, or e.g. the way in which an external shock (pandemic, change in regulation, etc.) impacts on a specific sector, or e.g. how the economy would look without it and its links to other sectors. Moreover, to assess such geographically distributed impacts, Multiregional InputOutput (MRIO) tables offer a particularly powerful tool, as they enable the tracing of crossREGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 39 border interdependencies and spill-overs, providing a comprehensive view of aviation’s global economic impacts and footprints. To the best of our knowledge, there are no applications of these methods for the aviation sector. Given the hinted importance of aviation, but also of the cited effects (also emphasized around the COVID pandemic), this research contributes to enhance the understanding of economic impacts (which could be complemented in the future with others, e.g. environmental impacts). It quantifies them, and contributes to the academic literature on such measurements. The research is structured as follows: section 2 deals with the methodology and database used, section 3 shows the results obtained assessing the economic importance of the air transport sector, section 4 shows the results of aviation as supporter of tourism and trade and section 5 shows the aggregated impact. The last section is devoted to the conclusions. 1.2 Methodology The methodological section outlines the input-output models employed to conduct the analysis presented in this study. 1.2.1 Input-Output analysis The IO models are macroeconomic models that represent the interdependencies between different sectors in a quantitative way. The practical applications of IO analysis derive from Leontief's model (Kuznets, 1941; Leontief, 1937, 1936). Input-Output Tables (IOT) allow to empirically represent the complete economic structure of a region or country, as well as the multiple relationships between the sectors that compose it (Simpson and Tsukui, 1965). In fact, together with national accounts, they constitute the central pillar of the economic accounts in any country or region. Essentially, the IOTs record the total production of each sector and the destination of this production. Equation 1 below shows that the output of a sector is equal to intermediate consumption plus final demand for all sectors in the Leontief model: xi = zi1+ zi2+⋯+ zij+⋯+ zin+ fi=∑zij+ fi nj=1 (1.1) Where xi is the output of the i-th sector, zij are the flows from sector i to sector j and fi is the total final demand of the i-th sector (private consumption, government expenditure, investment, and exports). In matrix terms: REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 40 �x1 x2 ⋮ xn�=�z11 z12 ⋯z1n z21 z22 ⋯z2n ⋮ ⋮ ⋱ ⋮ zn1 zn2 ⋯znn� �1 1 ⋮1�+�f1 f2 ⋮fn� (1.2) x = Z1 + f (1.3) Where Z is the inter-industry transactions matrix, i is a vector of 1´s and x and f are the output and final demand vectors. If we define the technical coefficients as: 𝑎𝑎𝑖𝑖𝑖𝑖= 𝑧𝑧𝑖𝑖𝑖𝑖 𝑥𝑥𝑖𝑖; The model can be formulated as follows: �x1 x2 ⋮ xn�=�a11 a12 ⋯a1n a21 a22 ⋯a2n ⋮ ⋮ ⋱ ⋮ an1 an2 ⋯ann� �x1 x2 ⋮ xn�+�f1 f2 ⋮fn� (1.4) x = Ax + f (1.5) Where A is the matrix of technical coefficients. Each coefficient [a_ij] denotes the number of units produced by industry i necessary to produce one unit by industry j and fi is the number of externally demanded units of industry i. If we clear x in the equation, we obtain the basic Leontief model: x = [I −A]−1f = Lf (1.6) Where L is the so-called Leontief inverse matrix, technology matrix or production multiplier matrix. The coefficients of this matrix [𝑙𝑙𝑖𝑖𝑖𝑖] indicate the increase in the output of sector i that is necessary to satisfy an increase of one additional unit in the final demand of sector j. Each element of the main diagonal is always greater than 1 (lij >1) since it includes the direct effect of the increase in demand on the production of its own sector plus the indirect effects on other sectors. This Leontief inverse matrix (L) also serves as the foundation for calculating output multipliers, which quantify the total production generated throughout the economy in response to a oneunit increase in the final demand of a given sector. Specifically, the output multiplier for sector i is defined as the sum of the entries in column i of the L matrix, indicating the aggregated production (output) required across all sectors to meet a one-unit increase in the final demand (Rasmussen 1956). REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 41 Furthermore, by extending this approach, the L matrix can be employed to derive multiplier effects for a variety of socio-economic and environmental indicators. When the L matrix is postmultiplied by a vector of sector-specific coefficients for a given indicator, such as value added, employment, or emissions, the result yields the total direct and indirect impact of an exogenous demand shock on that particular indicator. This methodology is widely recognized and has been developed by numerous scholars (Cella 1984; Oosterhaven 1988; Dietzenbacher and Van Der Linden 1997; Miller and Lahr 2001; Dietzenbacher 2002, 2005; Miller and Blair 2022), reinforcing its robustness and applicability in both economic and environmental impact assessments. 1.2.2 Multiregional Input Output On the basis of the IO framework, MRIO models were subsequently developed to incorporate the economic sectors of multiple countries and the interrelations between them (Miller and Blair 2022). This extension enables the analysis of economic impacts in a broader, internationally interconnected context. The model retains the same structure as in equation (1.1), but within a multiregional framework, it encompasses N countries and n industries per country. As a result, the intermediate transaction matrix Z expands to dimensions Nn × Nn, and the final demand matrix F becomes Nn × N. Thus, the 𝑧𝑧𝑖𝑖𝑖𝑖 𝑅𝑅𝑅𝑅 element of the 𝑍𝑍𝑅𝑅𝑅𝑅 matrix represents intermediate deliveries from industry i in country R to industry j in country S. In the same way, the 𝑓𝑓𝑖𝑖𝑅𝑅𝑅𝑅 element of the 𝐹𝐹𝑅𝑅𝑅𝑅 vector represents the deliveries from industry 𝑖𝑖 in country R for final demands in country S, and the 𝑥𝑥𝑖𝑖𝑅𝑅 in country R for final demands in country S, and the 𝑥𝑥𝑖𝑖𝑅𝑅 element of the 𝑋𝑋𝑅𝑅 vector represents the output of industry i in country R. In matrixial terms: ⎝ ⎜ ⎛ X1 ⋮ XR ⋮ XN⎠ ⎟ ⎞ =⎝ ⎜ ⎛ Z11 ⋯Z1R ⋯ ⋮ ⋱ ⋮ ⋰ ZR1 ⋯ZRR ⋯ ⋮ ⋰ ⋮ ⋱ Z1N ⋮ ZRN ⋮ ZN1 ⋯ZNR ⋯ZNN⎠ ⎟ ⎞ ⎝ ⎜ ⎛ 1 ⋮1 ⋮1⎠ ⎟ ⎞ + ⎝ ⎜ ⎛ F11 ⋯F1R ⋯ ⋮ ⋱ ⋮ ⋰ FR1 ⋯FRR ⋯ ⋮ ⋰ ⋮ ⋱ F1N ⋮ FRN ⋮ FN1 ⋯FNR ⋯FNN⎠ ⎟ ⎞ ⎝ ⎜ ⎛ 1 ⋮1 ⋮1⎠ ⎟ ⎞ (1.7) Thus, as in the previous case, by using the matrix of technical coefficients and isolating the output vector, the fundamental Leontief model equation is derived and solved following the same procedure. 1.2.3 Disentangling the Role of Air Transport: Hypothetical Extraction Method The Hypothetical Extraction Method (HEM) has been used to determine the importance and the linkages of an industry (Miller & Lahr, 2001). This method allows assessing the economic the economic importance of a specific sector (e.g. air transport) by simulating its removal from the REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 48 of gross value added, with 24.5 billion € (1.04% of national GDP) occurring domestically. In the Netherlands, the effects would result in 14.9 billion € in total gross value added losses, of which 9.7 billion € (1.59% of national GDP) would be generated within the Dutch economy. Similarly, in Switzerland, total losses would amount to 11.2 billion €, with 9.2 billion € (1.86% of national GDP) being domestic. Belgium would experience 5.3 billion € in total gross value added losses, with 3.1 billion € (0.90% of national GDP) occurring internally. Finally, Luxembourg would face a 2.8 billion € reduction in total gross value added, of which 1.5 billion €, equivalent to 1.61% of national GDP, would occur domestically. We may conclude that the largest economies in FABEC (Germany and France) are the most affected countries in absolute terms, while in relative terms, Switzerland stands out as the most affected country, underscoring its structural dependence on the sector. Note that Switzerland is also the country where the highest percentage of value added loss occurs internally while in Luxemburg the national impact is the lowest in FABEC, at 56% (see Table 1.1). Figure 1.1: Impacts in output of the extraction of air transport services of FABEC countries divided by national internal and external effects and international impact (billion euros) When considering the joint effects of air transport services across all six FABEC countries, the total estimated loss in global gross value added reaches 121.8 billion €. Of this, 104.8 billion €, representing 86% of the total impact, would be concentrated within the FABEC region, demonstrating the territorial concentration of aviation-related economic activity and the strategic importance of this sector for the region’s internal economy (Table 1.1). These results reinforce the key role played by the air transport sector in sustaining national and regional REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 49 output levels within FABEC, not only through direct value added but also through its extensive interlinkages across multiple industries and geographies. Table 1.1:The spatial distribution of impacts associated with the hypothetical removal of the air transport sector DEU FRA NLD CHE BEL LUX FABEC National 78% 81% 65% 82% 58% 56% 86% FABEC 5% 4% 8% 8% 16% 24% Rest 17% 14% 27% 10% 27% 21% 14% The decreases of gross value added can be divided into internal and external effects (Dietzenbacher et al., 2019). The internal effects measure the change in GDP in the extracted sector itself (air transport sector) and the external effects consider the total change in the GDP in the rest of industries (Figure 1.1). The decomposition of gross value added losses into internal and external effects reveals notable differences among the FABEC countries in terms of how the economic repercussions of the hypothetical extraction of the air transport sector are distributed across the economy. This distinction not only reflects the degree of vertical integration of the air transport sector in each country, but also the extent of its intersectoral and international linkages. In Switzerland, external effects account for approximately 80% of the total domestic impact, indicating a high level of dependence on upstream and downstream sectors that interact with air transport services. Similarly, Germany exhibits a substantial external effect, amounting to 78% of its national gross value added loss, alongside France with 81%. These results suggest that in these economies, a significant portion of the air transport sector’s value is generated through interconnected industries, reinforcing the systemic role of aviation within the national production structure. By contrast, the Netherlands, Belgium and Luxemburg register comparatively lower external shares, with 65%, 58% and 56%, respectively. This points to a relatively more self-contained aviation sector, or at least a structure where a larger proportion of economic activity is retained within the sector itself. From a sectoral perspective, beyond the air transport sector itself, the industries most affected by its extraction include the supporting and auxiliary transport activities (including travel agencies), which account for 18% of total output losses; the refined petroleum products sector (5%), likely due to its role in supplying jet fuel and other energy inputs specific to aviation; and REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 50 the wholesale trade and commission trade (4%), reflecting its intermediary role in supply chains linked to both aviation logistics and the distribution of goods transported by air. These results underscore the broad economic reach of the air transport sector, whose disruption affects a diverse range of industries, particularly those embedded in logistics, energy, and distribution networks. Understanding this distribution of internal and external effects is crucial for designing targeted mitigation strategies in the face of sectoral shocks and for evaluating the resilience of national economies to disruptions in critical infrastructure sectors such as aviation. In the Supplementary Material (SM), we provide several complementary results to this exercise. First, as a sensitivity test to the Database choice, we also perform the results with the WIOD database and compare them with the obtained results. We find some differences in terms of sectoral and national impacts. For instance, in the table (Table SM1) exploring the most beneficiated countries with each database when the air transport services are extracted in FABEC countries, China ranks higher in WIOD, while Russia, Turkey, and Japan appear in the top10 only in EXIOBASE. Sectoral impacts also vary, with air transport services (H51) and supporting activities (H52-H53) accounting for over 70% of effects in EXIOBASE but less than 60% in WIOD. Administrative and support services (N) are more affected in WIOD, highlighting differences in how the databases measure sector linkages. The first section of the SM also provides results of the Global Extraction Method (GEM) and comparison with the HEM. The GEM method, which allows for substitution by international counterparts (which we perform in a simple way, analogously to Dietzenbacher et al., 2019), shows smaller GDP decreases compared to HEM, which assumes no substitution. This difference stems from GEM accounting for inputs from other countries, particularly in upstream industries. Germany, as the largest air transport leader in FABEC, experiences the most significant reduction in gross value added, followed by France. Smaller countries like Belgium and Luxembourg show minimal impacts. Still, and in order to avoid entering into too many scenarios and assumptions, we keep in the main text the full computation of effects from the air transport sector of the FABEC countries. Accordingly, we focus on the presented results from the HEM representing the key figure for the sector´s contribution to the economy, together with those full effects we present in the next section regarding the sectors that aviation supports, that is, the full absence of transport of goods and services (trade) and of people (essentially tourism) that the aviation sector provides REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 51 Isolating the impact of the final demand, the research also examines how the final demand for air transport services is met in each FABEC country. This analysis is essential for identifying the products and services most closely integrated within the air transport value chain, offering insights into the sector’s upstream dependencies and the extent of domestic versus international contributions to meeting this demand. As can be seen in Table 1.2, around 80% of the products and services required to satisfy the final demand of air transport services of the analysed countries are produced inside their borders. The exceptions are Luxemburg and Belgium, where less than 60% of the demanded products and services are domestically produced. In addition, the rest of the FABEC countries are important in meeting these demands, as shown in the Rest FABEC row. Thus, 83% of all goods and services required to satisfy the final demand for air transport services in the FABEC region are produced in the region itself. Table 1.2: Origin of products and services that satisfy the final demand of air transport sector in FABEC countries. BEL FRA DEU LUX NLD CHE FABEC National 58% 81% 78% 56% 65% 82% 83% Rest FABEC 16% 4% 5% 24% 8% 8% Rest World 27% 14% 17% 20% 27% 10% 17% The sectoral distribution of the products and services demanded by this final demand for air services can be seen in Figure 1.2. In addition to the air services themselves, the services most in demand are, in order of importance, “Warehousing and support activities for transportation”, “Other professional, scientific and technical activities”, “Wholesale trade, except of motor vehicles and motorcycles”, “Land transport and transport via pipelines”, “Extraction of crude petroleum and natural gas” and “Accommodation”. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 52 Figure 1.2: Sectorial distribution of products and services that satisfy the final demand of air transport sector in FABEC countries. As can be seen in Table 1.3, satisfying the final demand of the air transport in FABEC countries means around 1% in terms of value added of the whole FABEC countries. However, the atmospheric emissions generated to meet this final demand are much higher in relative terms. Table 3 includes Greenhouse Gas (CO2, CH4, N2O, SF6, HFC and PFC), Sulfuric Oxides (SOx), Nitric Oxides (NOx), Ammonia (NH3) and Carbon Monoxide (CO) emissions generated by this activity with respect to total emissions in the FABEC region. All of them are greater than the value added generated in relative terms, except from the hydrofluorocarbons (HFC). On average, the atmospheric emissions generated from the gases analysed are 6 times greater than the added value generated, meaning that this is a highly polluting sector. Table 1.3: The value-added and emissions generated to satisfy the final demand of air transport services in FABEC area relative to the total of the FABEC area. Added Value Greenhouse Gas Emissions Sulfuric Oxides Nitric Oxides Ammonia Carbon Monoxide VA CO2 CH4 N2O SF6 HFC PFC SOx NOx NH3 CO 1.06% 7.48% 1.55% 12.54% 1.05% 0.74% 3.40% 2.13% 9.25% 44.41% 9.09% Ultimately, the effects of these scenarios can be seen, as introduced above, as examples of final demand disappearance in the FABEC countries. Apart from the extreme real-world example of the COVID-19 pandemic, with the confinements, passengers’ flights demand interruption, etc., we are observing political measures which may affect some of these countries’ final demand, being partial effects of what is simulated here. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 53 To complement the final demand analysis conducted, this study also examines the geographical and sectoral allocation of investments made by the aviation sectors of FABEC countries. Germans invests the most, also in relative terms, followed closely by French and Dutch. The Swiss place in the middle ground, while the Belgians and Luxembourgian are not investing heavily. Nevertheless, they are similar in the destination of these investments, since, as shown in Table 4, from all FABEC countries except Belgium and Luxemburg investments occur mainly inside their borders. Even so, Belgium still invests more than half of its share in FABEC region. Thus, more than 70% of the FABEC countries' air services investment is spent within FABEC. Table 1.4: Geographical destination of the investments of the air transport sector of each FABEC country. BEL FRA DEU LUX NLD CHE FABEC National 41.42% 61.85% 70.79% 23.63% 66.68% 61.10% 72.37% Rest FABEC 11.90% 12.51% 5.38% 5.14% 9.57% 10.58% Rest World 46.68% 25.64% 23.83% 71.23% 23.75% 28.32% 27.63% Regarding the sectors in which the FABEC countries invest, particularly for air transport services (as given from the capital use vector of the sector), the ten most important sectors are shown in Figure 1.3. Sectors like “Construction”, “Manufacture of motor vehicles, trailers and semitrailers”, “Other professional, scientific and technical activities” and “Manufacture of machinery and equipment n.e.c.” dominate in this aspect. The investment in the construction sector is particularly relevant, accounting for more than 40% of the total investment of the air transport sector in FABEC area, and it is also the most invested sector in all countries. Figure 1.3: Sectorial distribution of investment of air transport sector of FABEC countries REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 54 1.4 Impacts on Aviation-Dependent Sectors 1.4.1 Tourism This section presents the estimated economic impact of aviation on the tourism sector within the countries of the FABEC area. As outlined in the methodological section, a dual approach has been adopted, accounting for both inbound tourism (foreign travellers arriving by air in the FABEC countries) and outbound tourism (residents of FABEC countries who travel abroad by air). This distinction is particularly relevant for the group of countries analysed, as they exhibit markedly different tourism dynamics. For example, Germany, Belgium, and the Netherlands have a structurally negative tourism balance, with residents spending more abroad than the amount received from inbound travellers. In contrast, France, Switzerland, and Luxembourg are net recipients of international tourism spending. According to the analysis, citizens of the FABEC countries travelling abroad by air spend a total of approximately 81.7 billion € on tourism. Germany accounts for nearly half of this amount (49%), followed by France with 24%. The principal destinations for this outbound air travel are the United States, Spain, and Italy (as main destinations within the EU), along with regions such as Southeast Asia and Africa (see Figure 1.4). Figure 1.4: Expenditure in tourism made by plane by FABEC citizens by region (%) On the inbound side, the FABEC countries receive approximately 49.5 billion € in tourism expenditures from foreign visitors arriving by air (see Figure 1.5). France leads as the primary destination in this group, capturing 42% of the inbound tourism expenditure, followed by Germany with 23%. This creates a clear contrast between the two largest economies in the region: while Germany spends 40.9 billion € abroad and receives 10.7 billion €, France spends 19.6 billion € and receives 22.8 billion €. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 55 Figure 1.5: Distribution of expenditure of tourism made by plane in FABEC countries (billion €) The total negative tourism balance is largely attributable to income levels and purchasing power, higher-income populations are generally more able to travel internationally and spend more while abroad. In terms of modal significance, air travel represents 26% of total trips, but it accounts for 36% of overall tourism expenditure. This reflects the nature of air-based tourism, which typically involves longer-distance travel and higher per-trip spending, often for business or long-duration leisure purposes. Thus, this tourism spending generates impacts throughout the value chain, both in the FABEC countries and beyond. In this way, the aggregate impact of aviation-related tourism activity, combining both outbound and inbound flows, amounts to 131 billion € in terms of gross value added. From a geographical perspective, only 37% of the total economic impact would be concentrated within the FABEC countries themselves (see Figure 1.6). This underscores the global nature of aviation’s role in tourism: any disruption to air travel would have far-reaching consequences across multiple regions, particularly in countries that depend on European tourists. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 56 Figure 1.6: Distribution of the economic impacts of the cessation of air tourism in the FABEC countries From a sectoral perspective, the industry experiencing the greatest impact is hotels and restaurants, which account for 38% of the total impact, followed by air transport services provided by non-FABEC countries (7%), and supporting activities for transport, including travel agencies and tour operators (4%) (Table 1.5). These findings highlight the critical role of air transport in enabling high-value tourism, which generates significant added value for receiving countries. While some substitution to alternative modes of transport might be conceivable in the event of aviation disruption, such alternatives are largely unviable for long-distance travel, especially intercontinental routes. Consequently, without aviation, large segments of the international tourism market, particularly those involving high expenditure and long-haul destinations, would effectively disappear. Table 1.5: Most affected sectors by the cessation of air tourism in the FABEC countries (billion €) Sectors ∆GDP % Hotels and restaurants -50 38.3% Air transport (other countries) -9.7 7.5% Other business activities -5.5 4.2% Supporting and auxiliary transport activities; activities of travel agencies -5.2 4% Other land transport -4.2 3.2% Wholesale trade and commission trade -3.4 2.6% REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 57 1.4.2 Trade This section presents the estimated importance of the air transport industry for trade in the countries under analysis. As detailed in the methodological framework, and following a similar bilateral approach to the tourism analysis, this section has a bilateral focus, studying the impacts produced both in the countries under study and those produced abroad through their imports and exports. or the FABEC countries, the overall trade balance for goods transported by air is positive, indicating that exports exceed imports. This outcome aligns with expectations, given that the region comprises some of the most export-oriented economies, as noted in the introduction. In terms of exports, the German air exports represent the highest economic value, 182 billion € (35% of the total), followed by Switzerland and France with 28 and 16% of FABEC's total respectively (Figure 1.7). Collectively, the cessation of air exports from FABEC countries accounts for 526 billion € in economic value of goods transported. Of particular note is the case of Switzerland, whose air exports are disproportionately significant in relative terms. This can be attributed largely to its landlocked geographic position, which limits access to maritime routes and reinforces reliance on air transport for high-value goods. Conversely, France, the only country among those analysed with coastlines on both the Mediterranean Sea and the Atlantic Ocean, benefits from access to major ports such as Marseille and Le Havre, thereby reducing its dependence on air freight relative to its peers. Ceasing airborne imports is similarly substantial, as the economic value of goods imported by air amounts to 397 billion euros. Germany again leads in terms of magnitude, accounting for 29% of the total, followed by Switzerland (25%) and the Netherlands (20%) (Figure 1.7). France ranks fourth, reaffirming its comparatively lower reliance on air freight for international trade in relative terms. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 64 All those impacts analysed on aviation-dependent sectors highlight the interconnectedness of the air transport sector within FABEC and globally, emphasizing its economic significance and environmental effects. The choice of database and extraction method influences results, with GEM providing a more nuanced view of international substitution effects. Policy measures, such as sanctions, can also disrupt supply chains and redistribute economic impacts. But all in all, those analysis, the usual and popular ones with IO modelling, probably do not yet represent the importance of the sector globally. In this regard, and inspired by the idea of (Arto et al. 2015), we realize of the importance of the aviation sector as a provider of transport, both of goods and services, which are needed as inputs in other sectors, and of people (mainly tourism), who further spend on destination countries. We compute both aspects, finding a great importance of those effects. In particular, the impacts on aviation-dependent sectors account for the vast majority of its economic impact, representing approximately 81% of total added value losses. In the case of air travel-related tourism, the FABEC countries collectively generate more tourism expenditure abroad than they receive, with 63% of tourism-related impacts occurring outside the region. However, France stands out as an exception, benefiting from substantial inbound tourism and associated international spending. In terms of airborne trade, which constitutes the largest share of the total impact in this analysis, the FABEC region functions as a net exporter, with air cargo playing a strategic role in supporting international competitiveness. Although air freight represents just 0.4% of the total trade volume by weight, it accounts for 16% of the total trade value, highlighting its disproportionately high economic significance. Furthermore, only 25% of FABEC’s air trade occurs within Europe, underscoring its intercontinental orientation. In relative terms, Switzerland is particularly dependent on-air freight due to its landlocked geography, which limits alternatives such as maritime transport. Air cargo plays a critical role in enabling high-value, time-sensitive trade. A hypothetical cessation of air trade operations would, therefore, not only disrupt domestic supply chains but also hinder a country’s participation in global trade networks. The used approach allows for a more comprehensive assessment of the structural vulnerabilities and spill over effects that arise from the disruption of aviation-enabled trade. It accounts for both direct losses in final consumption and indirect impacts on production networks caused by the breakdown of interindustry exchanges. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 65 Taken together, these findings underscore that, while the air transport sector may appear “small” in direct economic terms, it exhibits strong intersectoral linkages and is indispensable for enabling key economic activities such as international tourism and trade. As a result, its overall economic footprint far exceeds its nominal size, reinforcing its role as a critical infrastructure sector in the FABEC region and beyond. The findings also call for understanding and balancing economic benefits with environmental mitigation efforts, given the evident high presence of the aviation sector as GHG emitter. Both key aspects, environmental and economic, were already seen around the sector in a period such as the COVID-19 pandemic, when the aviation sector experienced a significant downturn. For this reason, the conducted analysis, not only provide insights on the total dimension of the sector within supply chains, but also serve as a comprehensive evaluation of such a moment that was lived a few years ago. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 66 1.7 References Ali, Y., Bilal, M., Sabir, M., 2021. Impacts of transport strike on Pakistan economy: An inoperability Input-Output model (IIOM) approach. 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URL https://data.worldbank.org/indicator/NE.TRD.GNFS.ZS?most_recent_value_desc=true (accessed 3.29.23). World Bank Group, 2020. Air Transport Annual Report 2020: Transport Global Practice. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 68 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 69 2. European Aviation Measures to Reduce Emissions REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 70 2.1 Introduction Aviation is a critical component of Europe's economic infrastructure, facilitating both business and leisure travel, while supporting regional development and global connectivity. Airports often serve as hubs of economic activity, attracting investment and enabling the movement of goods and people across borders. However, the environmental impact of aviation, particularly emissions and noise pollution, has become a growing concern. In many European districts, especially those hosting low-cost airports, residents face the trade-off between economic benefits and the downsides of proximity to air traffic. These regions experience noise pollution and other environmental stresses, but without aviation, they risk losing the influx of capital and residents who rely on connectivity for work and travel. Thus, while aviation is indispensable to the modern economy, it also places a burden on the environment and communities, creating growing awareness around climate change (European Commission, 2018). Despite accounting for a relatively small share of global CO₂ emissions, about 2% of worldwide emissions and approximately 12% of GHG emissions when considering non-CO₂ effects, such as contrails and nitrogen oxides (NOx) (European Commission, 2020), aviation has become a focal point for environmental criticism. Public sentiment often associates aviation with high energy consumption and a substantial carbon footprint. However, there are misconceptions surrounding the sector's environmental impact, particularly the belief that aviation emissions are constantly on the rise while national emissions in other sectors are being reduced. Data from the EU-27 reveals a more nuanced picture: aviation emissions rose from 24.6 Mt in 1990 to 40.2 Mt in 2011, levelling off at 39.8 Mt in 2012 (European Environment Agency, 2024a+). These fluctuations are influenced by factors such as market competition, the rise of low-cost carriers, and the varying demand for air travel across different periods. Importantly, these emissions statistics only cover flights within Europe, excluding the impact of international aviation, which further complicates the narrative. The growth of the aviation sector, both in Europe and globally, exacerbates these environmental concerns. Over the past 50 years, international air travel has expanded rapidly, and this trend is expected to continue, with forecasts suggesting that the global fleet could grow fourfold by 2050 compared to 2006 levels (IATA, 2019; ICAO, 2019; Airbus, 2024). While aviation is essential for international trade, tourism, and cultural exchange, its contribution to GHG emissions is becoming more difficult to ignore. The industry’s reliance on fossil fuels, particularly kerosene, coupled with the technological limitations of current alternative fuels, presents a significant obstacle to achieving the emissions reductions required to meet international climate targets. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 71 In response to these challenges, the European Union has taken a proactive approach to reducing aviation's environmental impact through a combination of policy measures and technological innovation. One of the most significant is the inclusion of aviation in the European Union Emissions Trading Scheme (EU ETS). The EU ETS aims to cap and reduce emissions from the sector by making airlines accountable for their carbon output, encouraging them to adopt more fuel-efficient technologies and invest in cleaner alternatives. However, the scheme has generated controversy, especially in global forums, with industry stakeholders such as the International Air Transport Association (IATA) and aircraft manufacturers like Airbus questioning its effectiveness and fairness (EUROCONTROL, 2022). The ongoing debate centres around whether the EU ETS aligns with international climate goals, as outlined by the United Nations Framework Convention on Climate Change, and how it interacts with other global initiatives, such as the Carbon Offsetting and Reduction Scheme for International Aviation (ICAO, 2020). Beyond the EU ETS, Europe has adopted a broader climate strategy aimed at reducing emissions across all sectors. The "Fit for 55" package, part of the European Green Deal, outlines ambitious targets to cut EU-wide emissions by at least 55% by 2030 compared to 1990 levels (European Commission, 2021). Aviation is a key part of this strategy, with measures such as the ReFuelEU Aviation Initiative, which seeks to increase the use of Sustainable Aviation Fuels in European airlines. SAFs, produced from renewable resources, have the potential to reduce aviation’s lifecycle emissions by up to 80%, though challenges remain in scaling up production and addressing the higher costs compared to conventional jet fuel (WORLD BANK GROUP, 2022). Additionally, the Single European Sky Initiative aims to reform air traffic management systems, enabling more efficient flight routes and reducing unnecessary fuel burn, thereby lowering emissions (SESAR, 2020). At the same time, the development of electric and hybrid aircraft is advancing, although these technologies are still far from being widely deployed for commercial use, particularly for long-haul flights. As EU works to achieve climate neutrality by 2050, the aviation sector remains a critical focus for emissions reductions. As a result, European policymakers are under increasing pressure to balance the economic benefits of aviation with the need to reduce its environmental footprint. The EU’s multi-faceted approach, combining emissions trading, fuel innovation, and air traffic management reforms, reflects a commitment to addressing aviation’s environmental impact. However, challenges remain in ensuring that these measures are both effective and equitable, particularly given the global nature of the aviation industry and the varying economic capabilities of airlines and countries. As technological advancements and policy frameworks REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 72 continue to evolve, Europe’s aviation sector will play a central role in the global fight against climate change. 2.2 Overview of the European Aviation Industry The European aviation industry is a major player in global air transportation, driving economic growth, international trade, and mobility across the continent. The fleet in Europe consists of a diverse range of aircraft types, from modern jets to turboprops, used across a variety of shorthaul and long-haul routes. These aircraft are owned and operated by airlines, leasing companies, and private owners, reflecting a complex industry structure. The overall composition and modernization of the fleet are shaped by market competition, regulatory pressures, and the need for increased fuel efficiency (IATA, 2003; Eurostat, 2019). One of the defining features of the European aviation fleet is its relatively young age compared to global averages. Many of the aircraft in operation are less than five years old, which reflects the industry's focus on upgrading to more fuel-efficient models (Eurostat, 2019). This is particularly true for turboprop planes, which are increasingly used on short-haul routes due to their efficiency and environmental advantages (IATA, 2019). The modernization of the fleet is key to meeting both markets demands and Europe’s stringent environmental targets (European Commission, 2021). The European aviation market is highly competitive, with a strong presence of both full-service carriers and low-cost carriers (LCCs). LCCs, such as Ryanair and Wizz Air, have transformed the landscape by offering affordable travel options, particularly on short-haul routes, driving an increase in passenger numbers (IATA, 2019). This fierce competition has forced full-service carriers to also invest in newer, more efficient aircraft to maintain profitability and comply with evolving environmental standards (IATA, 2019). Aircraft leasing plays also an important role in the European aviation sector, allowing airlines to quickly adjust their fleets in response to changes in demand and regulation (SESAR, 2020). Leasing companies have been instrumental in enabling airlines to modernize their fleets with more environmentally friendly aircraft, facilitating compliance with EU emissions targets. The presence of leasing companies, particularly in aviation hubs like Ireland, provides flexibility and access to cutting-edge aircraft technology for both low-cost and full-service airlines (SESAR, 2020). Technological improvements have had a notable impact on the environmental performance of European aviation. A significant portion of the fleet is equipped with state-of-the-art engines designed to reduce fuel consumption and emissions (WORLD BANK GROUP, 2022). This is REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 73 especially evident in smaller aircraft like regional jets and turboprops, where new technologies have a larger effect on overall fuel efficiency. The adoption of advanced engine technologies is expected to increase as airlines continue to upgrade their fleets in line with environmental regulations (European Commission, 2021). Airspace management reforms under the Single European Sky initiative have also contributed to the industry’s efficiency helping airlines reduce fuel consumption an emissions by reducing fragmentation in European airspace an optimizing flight routes (SESAR 2020). The initiative is a critical part of the EU's broader strategy to address climate change and achieve a greener aviation sector while simultaneously enhancing the competitiveness of European airlines (European Commission, 2021). In conclusion, the European aviation industry is undergoing significant transformation driven by environmental and economic pressures. Technology, operational improvements, infrastructure, and behaviour policies are expected to deliver only moderate reductions in future European aviation emissions. The focus on fleet modernization, advanced engine technology, and efficient airspace management is positioning Europe as a leader in sustainable aviation. As airlines continue to update their fleets and adopt greener technologies, the industry will play a pivotal role in helping Europe meet its ambitious climate goals (European Commission, 2021; Eurostat, 2019; IATA, 2019). 2.3 Greenhouse Gas Emissions from Aviation GHG emissions from aviation contribute significantly to climate change, particularly CO2, which is the most dominant emission produced by aircraft. Global aviation is responsible for approximately 2-3% of all human-made CO2 emissions, a share expected to grow substantially as air traffic continues to increase (European Commission, 2020). Aviation emissions result not only from the fuel burned by aircraft engines but also from other by products such as nitrogen oxides (NOx) and water vapor, which lead to secondary effects like contrail formation, further increasing the sector's climate impact. Thus, in addition to CO2, other emissions should not be neglected, as a report by the European Aviation Safety Agency (EASA) confirms that non-CO2 effects of aviation activities accounted for more than half (66%) of the sector's net climate forcing in 2018. The European aviation sector has seen a sharp rise in emissions, driven by the increase in the number of flights and growing passenger traffic. Between 1990 and 2014, emissions from international aviation in Europe grew by 91%, reflecting both the expanding air traffic and REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 80 industry, its workforce, and its customers. Despite its comprehensive scope, few international agreements under ICAO explicitly address the reduction and control of aviation emissions. This reflects the historical dominance of operational and safety concerns in aviation policy. The first indication of the need to legislate on aviation emissions was in 1971 when the Environmental Council called for research on this subject (ICAO, 2020). At the ICAO Conference on Air Transport and Environment, held in Paris in April 2003, it was agreed that the ICAO should consider a range of policies to achieve environmental protection and sustainable development, including economic instruments, regulations, operational improvements and technological innovations, as recommended by the EU in 2004. In the 2006 Communication, An integrated EU aviation policy, the Commission noted that aviation fuels remain untaxed, and that fairer aviation taxation is a crucial issue that is also being discussed in the European context. The communication also referred to the fact that the Community regulatory framework must keep pace with the changes in practice and that a comprehensive set of measures to protect the environment by setting appropriate regulatory measures for noise, local air quality, and climate change should be considered essential. Furthermore, complaints led to investigations by the European Court of Auditors in relation to ICAO and the Commission, with the former concluding that progress in ICAO had been slow and that it needed to clarify the approach to addressing aviation and climate change. Nevertheless, in 2016, the ICAO adopted the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA), marking a turning point in climate policy (ICAO, 2016). This decision represents the first case where a single industry sector accepts a global market-based measure aimed at addressing climate change and represents a landmark effort to address CO2 emissions from international aviation. This global market-based measure stabilizes net CO2 emissions at 85% of 2019 levels, with offsetting requirements beginning in 2021 (ICAO, 2024). CORSIA applies exclusively to international flights, as domestic emissions fall under the Paris Agreement. The scheme is implemented in phases: two voluntary phases (2021–2023 and 2024– 2026), followed by a mandatory phase from 2027. Initially, only flights between states participating voluntarily were covered, but the mandatory phase will include all international flights (ICAO, 2024). COVID-19 significantly affected the baseline emission levels for CORSIA. In response, ICAO set 2019 emissions as the baseline for the 2021–2023 period and adjusted the long-term baseline to 85% of 2019 emissions, beginning in 2024. The revised target reflects an ambitious commitment to CO2 reduction, supported by ICAO member states and the aviation industry. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 81 Offsetting under CORSIA requires operators to purchase carbon credits for emissions exceeding the baseline, promoting mitigation outside the aviation sector. Compliance is monitored through three-year reporting cycles, ensuring operators meet their obligations by cancelling emissions units. Between 2024 and 2035, CORSIA aims to stabilize annual international aviation emissions at 550–600 million tonnes of CO2, achieving reductions of 1.3–1.7 billion tonnes during this period—representing 15–21% of air transport’s projected emissions. Currently, 60% of international aviation emissions are covered by CORSIA, with coverage expected to expand to 85% by 2027 as major economies like China, Brazil, and India join. Without CORSIA, IATA estimates international aviation emissions could rise from 600 million tonnes in 2019 to 800 million tonnes by 2035. The scheme, supported by ICAO and the aviation sector, demonstrates a collective commitment to mitigating aviation’s environmental impact while balancing global growth in air travel. However, even with the introduction of mechanisms like the CORSIA, the sector’s emissions are likely to continue increasing unless more aggressive measures are adopted (Dray et al, 2010; European Commission, 2018, 2020; Terrenoire et al., 2019; Hasan et al., 2021). 2.4.2 European regulation The EU has been a leader in addressing climate change by implementing policies to reduce greenhouse gas emissions across various sectors. The EU focuses on internalising environmental costs in decision-making processes through initiatives to meet its Kyoto commitments. The EU strives to reduce the environmental impacts of aviation by promoting technical innovations, market-based environmental solutions, and encouraging behavioural changes in air travel. These efforts are part of a broader strategy to adopt stricter emission reduction targets and foster sustainable economic practices (European Commission, 2018). The European Union aimed to reduce transportation sector emissions significantly, targeting stabilization at 2005 levels by 2020 and 1990 levels by 2030 (European Commission, 2021). Given the aviation sector's growth, the EU has implemented the EU ETS, established in Directive 2003/87/EC (European Commission, 2021). This market-based approach encourages efficient emissions reductions and cost-effective abatement measures across the EU, contributing to overall greenhouse gas reduction efforts. The EU ETS, launched in 2005, aims to reduce greenhouse gas emissions in European Union member states. Initially, the EU ETS covered CO2 emissions from power plants, refineries and energy-intensive factories. Various mechanisms for including the aviation sector in the EU ETS REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 82 were discussed, but the European Emissions Trading Alliance (EATS) suggested that the most effective way would be to implement it fully with auctions in early 2011. Under the EU ETS, all airlines operating in the European Economic Area are required to monitor, report, and verify their emissions annually (European Commission, 2021). Airlines must surrender emissions allowances equivalent to their emissions for each year. This system operates under a "cap and trade" approach, where aviation has contributed to the reduction of emissions in other sectors by approximately 160 million tonnes during the third trading phase (2013-2020), as reported in the 2022 European Aviation Environmental Report (EUROCONTROL, 2022). The compliance rate within the aviation sector is very high, typically exceeding 99.5% of emissions covered by the surrender of allowances (Anger and Köhler, 2010; Nava et al., 2018; Fageda and Teixidó, 2022). The EU ETS originally applied to all flights from, to, and within the European Economic Area, including member states and countries like Iceland, Liechtenstein, and Norway. However, the European Court of Justice confirmed that this approach was incompatible with international law. To accommodate the development of a global emissions reduction strategy, the EU temporarily limited the ETS's scope to intra-EEA flights. This was done to support the establishment of CORSIA, developed under the ICAO. With the introduction of CORSIA, the scope of the EU ETS has been revised several times, with the latest extension valid until 2027. By mid-2026, the European Commission will evaluate whether additional measures are necessary for flights to and from Europe. The assessment will determine whether the EU should extend the EU ETS to include departing flights or maintain its focus on intra-European flights. This decision will also depend on CORSIA’s global implementation and the level of participation by other countries. In addition to the EU's internal measures, the EU has also signed linking agreements with some other European countries. One of them is Switzerland, where the principles governing emissions trading for aviation align with those of the EU ETS. Under this agreement, emissions from flights arriving from Switzerland are exempt from the EU ETS, and the corresponding allocation of carbon credits is adjusted. This ‘one-stop shop’ approach ensures that operators only interact with a single authority for both the EU and Swiss systems. Emissions from flights between the EU and the UK are covered under the EU ETS as per the Trade and Cooperation Agreement. Flights arriving from the UK are similarly exempt from the EU ETS and are instead subject to the UK Emissions Trading System (UK ETS). The free allocation of emissions allowances for UK operators is also adjusted accordingly to reflect this arrangement. These mechanisms aim to REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 83 streamline carbon emissions reporting and compliance across European and global aviation, contributing to international efforts to reduce the sector’s carbon footprint. Another European key legislative initiative is ReFuelEU Aviation, adopted in October 2023 (European Commission, 2023). This regulation aims to reduce the environmental impact of the aviation sector by promoting the use of sustainable aviation fuels (SAFs) as part of the EU’s Fit for 55 packages (European Commission, 2021). SAFs are considered environmentally friendlier than traditional fossil fuels, reducing CO2 emissions. This initiative is significant as the EU is the first region to establish a regulatory framework for SAFs, fostering production, supply, and market growth, ultimately lowering prices through increased volume (European Commission, 2023). This regulation includes several key provisions: • Obligations for fuel suppliers: From 2025, aviation fuel suppliers at EU airports must ensure a minimum percentage of sustainable fuel in aviation fuel. The quotas increase progressively, reaching 2% in 2025, 6% in 2030, and 70% by 2050, with 1.2% synthetic fuel required from 2030, growing to 35% by 2050. • Air operator obligations: Air operators must ensure that the annual fuel supply to each EU airport is at least 90% of the annual fuel requirement, preventing refuelling that results in additional emissions due to excessive fuel weight. • Scope of eligible fuels: Sustainable aviation fuels eligible for the quotas include certified biofuels, renewable fuels of non-biological origin (such as renewable hydrogen), and recycled carbon aviation fuels that meet the Renewable Energy Directive’s sustainability and emissions savings criteria, up to a maximum of 70%. Low carbon aviation fuels, such as low-carbon hydrogen, may also contribute to meeting the quotas. • Regulatory framework: Member States are required to designate competent authorities for enforcement of this regulation, with penalties for non-compliance. • Union labelling scheme: A new labelling scheme will be introduced to help consumers identify airlines that use environmentally friendly fuels, encouraging greener flight choices. • Data collection and reporting: Fuel suppliers and airlines are required to collect and report data on the implementation of these provisions, particularly monitoring impacts on the competitiveness of EU operators. Thus, this regulatory context in the European Union seeks to make progress in the mitigation of emissions from the aviation sector in order to meet the established climate objectives. To REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 84 achieve this mitigation, different innovations are being developed, which will be discussed further below. 2.5 Technological Innovations in Aviation Mitigating emissions in the European aviation sector is a critical challenge that has garnered significant attention from policymakers, industry stakeholders, and researchers. The European Commission, along with various international organizations such as ICAO and IATA, has been actively exploring measures to address CO2 emissions from passenger aircraft (de Jong et al., 2018; Gao, 2023; Schaefer, 2015; Shehab et al., 2023). One key strategy is the use of sustainable fuels, as a means to decarbonize the aviation sector and meet sustainability targets (Shehab et al., 2023). The sector has been working proactively with industry to explore the economic and technical potential of alternative fuels to play an increasingly important role in helping the aviation industry meet its climate neutrality goals. Sustainable aviation fuels (SAFs) are currently one of the only viable ways to significantly reduce aviation GHG emissions in the medium term and reduce the industry's dependency on fossil fuels. The European Commission has proposed a progressive mandate for the blending of sustainable aviation fuels at EU airports, starting at 2% in 2025 and rising to 63% by 2050, with a sub-mandate for Power-to-Liquid fuels (European Commission 2023). To meet these targets, the projected demand for SAF would be approximately 2.3 million tonnes by 2030, increasing to 14.8 million tonnes by 2040 and 28.6 million tonnes by 2050. However, it is clear that at present, demand for sustainable fuels significantly exceeds the available supply (Schaefer, 2015; Schäfer, et al. 2015; de Jong et al., 2018). Achieving meaningful penetration of alternative fuels will require robust and favourable regulatory frameworks and mechanisms to support scaling up the alternative fuel development and production technology. Policymakers should ensure regulatory frameworks promoting alternative fuels are designed consistently at both the European Union and national levels. This will help create the most costeffective and supportive environment for the industry, while ensuring that both EU-produced and imported sustainable fuels can contribute to the decarbonization of EU aviation in an economically and environmentally sustainable manner. In addition to SAFs, alternative jet fuels have also been identified as a viable option for reducing CO2 emissions in the aviation industry. Staples et al. (2018) highlight that advancements in airframe and engine technologies can directly contribute to lowering CO2 emissions from REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 85 aircraft, thereby helping the sector comply with climate policies such as CORSIA. These technological improvements play a crucial role in enhancing the fuel efficiency of aircraft and reducing their environmental impact. Furthermore, de Jong et al. (2018) project that renewable jet fuels (RJF) could offset a significant portion of the sector's emission growth in the EU by 2030. By transitioning to RJF and other sustainable fuel options, the aviation industry can make substantial strides towards achieving emissions mitigation targets. Thus, in addition to the above-mentioned targets, RefuelEU also aims for the share of synthetic aviation fuels at all EU airports to be 1.2% from 2030 and to increase to 35% from 2050 (European Commission, 2023). With the existing regulatory context, airlines face increasing pressure to reduce emissions while managing operational costs. Innovations in both air and ground operations are also critical to achieving lower carbon intensity in aviation. The demands to reduce emissions have catalysed innovation in aircraft design and software development. Technological breakthroughs in areas such as aerodynamic design and the application of natural laminar flow are being actively explored (Morrell, 2009). For instance, designing wings to facilitate laminar flow can significantly enhance fuel efficiency. By employing supercritical wing designs and lightweight composite materials, drag can be reduced, lowering fuel consumption and associated CO2 emissions. Additionally, the gradual renewal of the global aircraft fleet provides a long-term opportunity to improve efficiency. Aircraft constructed in the mid-2020s will remain operational into 2050, meaning that introducing more fuel-efficient models will have lasting environmental benefits. Newer aircraft not only utilize advanced materials and designs but also integrate improvements in propulsion systems and operational efficiency, ensuring reductions in emissions and better overall performance. Aircraft efficiency has shown consistent improvement over the past five decades, with modern commercial jets achieving over 40% greater fuel efficiency compared to those from the 1960s, representing an annual efficiency gain of approximately 1.3% (Zheng et al., 2020). Current estimates suggest the latest aircraft generation outperforms its predecessors by up to 20% in fuel efficiency. Emerging aircraft designs, such as blended-wing-body (BWB) models, offer ground-breaking potential for efficiency, marking a significant departure from decades of incremental progress. Innovators such as Natilus (Warwick, 2018) and JetZero (2024) project fuel efficiency improvements of up to 50% compared to conventional aircraft. The BWB design integrates the fuselage and wings, allowing the entire structure to generate lift, thereby reducing aerodynamic drag and improving fuel efficiency. This innovative design supports both REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 86 traditional jet fuel and low-emission propulsion technologies, such as battery-electric and hydrogen systems. For electric aircraft, BWB structures enhance range and payload capacity, addressing key limitations of current electric propulsion technologies. Similarly, the BWB’s increased payload capability accommodates the heavy storage requirements of hydrogen propulsion systems, making zero-emission aviation more feasible. These designs are also compatible with SAFs, offering versatility in meeting diverse decarbonization goals. BWB aircraft are being developed for a variety of applications, from unmanned vehicles and defence to cargo and passenger transportation. Companies like JetZero are exploring defence and cargo markets, while Natilus focuses on both cargo and passenger sectors, further expanding the potential applications of this transformative technology. Ground operations also stand to benefit from technological upgrades, such as electrification of airport vehicles, improvements in air traffic management, and the use of sustainable fuels. Together, these advancements contribute to an integrated approach to decarbonizing air transport, demonstrating the potential for ambitious environmental progress through innovation and fleet modernization. The aviation sector offers multiple pathways for technological innovation aimed at reducing its environmental impact. In the short term, key measures include reducing aircraft weight, enhancing engine efficiency, integrating air and ground operations, improving operational practices, and updating fleet compositions. Over the medium to long term, strategies focus on advancing scientific understanding of aviation-related climate impacts. This involves improving predictive models, refining mitigation techniques, and enhancing knowledge about emissions and their effects to guide the development of effective and sustainable solutions. 2.6 Operational Measures to Reduce Emissions Airlines are continuously adopting measures to enhance operational efficiency and reduce their environmental impact. These efforts include optimizing seat occupancy rates, deploying modern fuel-efficient aircraft, and implementing stringent environmental policies targeting reductions in carbon emissions, noise, and other externalities. Reducing empty flying time is a central goal for airlines and aircraft operators, delivering substantial economic and environmental benefits by minimizing fuel consumption and CO2 emissions. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 87 In collaboration with airlines and airport operators, air navigation service providers (ANSPs) have developed strategies to optimize flight plans and rationalize air routes. These strategies aim to alleviate airspace capacity shortages, shorten flight distances, and enhance overall route efficiency. Such measures significantly reduce fuel burn and CO2 emissions while addressing airspace fragmentation. The Single European Sky (SES) initiative plays a pivotal role in these efforts, fostering collaboration among industry stakeholders and implementing measures like performance-based navigation (PBN), continuous descent arrivals (CDAs), continuous climb departures (CCDs), and streamlined ground procedures. Introduced in 2004, it seeks to unify and modernize Europe's fragmented airspace to address challenges such as increased air traffic, delays, environmental concerns, and integration of new entrants like drones (European Commission, 2009). It focuses on enhancing safety, scalability, cost-efficiency, and sustainability in air traffic management (ATM). The SESAR project drives technological advancements for improved performance, while Eurocontrol, as the Network Manager, implements short-term congestion solutions. Reforms under the new Single European Sky Regulation (SES2+) emphasize structural adaptability, flexible navigation services, and environmental improvements to ensure the aviation sector's long-term efficiency and resilience. Within the SES initiative, 9 Functional Airspace Blocks (FABs) were created in Europe (SKYbrary, 2012). A FAB is an airspace segment organized based on operational needs rather than state boundaries, where air navigation services are optimized for performance. It aims to enhance cooperation among service providers or, when necessary, integrate services under one provider. FABs align with strategic objectives to enhance safety, capacity, cost-effectiveness, and flight efficiency in air traffic management. They aim to manage growing civilian air traffic, optimize routes, and improve air traffic control (ATC) services. FABs also emphasize reducing environmental impacts through efficient flight paths and distances flown. Additionally, they support military mission effectiveness by improving training capabilities and readiness. These goals ensure a balanced approach to managing civilian and military airspace needs within the FAB framework. Air traffic management innovations have the potential to significantly improve efficiency, reduce delays, and lower emissions. Key advancements include optimizing descent profiles and employing free routing concepts, enabling the calculation of efficient trajectories for terminal areas and reducing fuel consumption. Studies by Aghdam et al. (2021) emphasize the benefits of these approaches, which can reduce emissions while maintaining safety standards. Thus, REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 88 statistical and fuzzy techniques and data mining algorithms have been used to solve the issues of air traffic management, alongside more sophisticated machine learning and big data models (Demouge et al., 2024; Aditya et al., 2024). While optimization techniques have advanced air traffic flow efficiency, the future of Air Traffic Flow Management (ATFM) lies in real-time, adaptive solutions capable of addressing unpredictable disruptions such as severe weather or technical failures. These systems will rely on dynamic algorithms and real-time data integration to provide quick, reliable responses to emerging challenges, enhancing resilience and operational efficiency. Such advancements will enable more sustainable and flexible air traffic systems, ensuring minimal delays and improved overall performance in increasingly complex and congested airspace environments. In addition, efficient flight planning is a cornerstone of emissions reduction. The process consists of two phases: strategic (pre-tactical) planning and tactical adjustments. In the pre-tactical phase, routes are designed using predictive models for weather conditions such as wind and temperature. The tactical phase, conducted closer to departure or during flight, adapts these plans to real-time constraints, ensuring optimal altitude, speed, and trajectory. Another advantage of this method is the significant savings in fuel and emissions (Rosenow et al., 2021; Tang et al., 2021; Simorgh et al., 2024). Advanced algorithms enhance the accuracy of system forecasts, enabling better speed and altitude adjustments. Such measures reduce unnecessary holding patterns, improve precision in landing and take-off, and optimize navigation. Case studies demonstrate the approach’s effectiveness in mitigating climate impacts, even with significant regional discrepancies between input models, providing reliable solutions for climate-aware aviation planning (Simorgh et al., 2024). Thus, operational practices, innovations in air traffic management, and efficient flight planning are integral to reducing aviation emissions. By leveraging technological advancements, fostering collaboration among stakeholders, and adhering to robust regulatory frameworks, the aviation sector can significantly enhance its environmental performance. These measures align with broader efforts to create a sustainable future for air transport while maintaining economic viability. 2.7 Economic Instruments for Emission Reduction The transition towards a common European Sky is expected to contribute to lowering environmental impacts by enhancing efficiency, improving performance, and promoting costeffectiveness. However, beyond these operational changes, the role of economic instruments, REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 89 governance structures, and the distribution of burdens among member states remain crucial considerations in emission reduction efforts. Despite the prominence of technical solutions in emission reduction strategies, the economic dimension must not be overlooked. In aviation, companies and individuals often make decisions influenced by price signals, which guide producers and authorities alike. These price signals inform producers about consumer willingness to pay and enable authorities to redistribute revenues through the social and financial system. An efficient economic framework is essential for steering the aviation sector toward achieving agreed environmental and social goals. This leads to the question: How can economic instruments effectively contribute to reducing emissions in aviation? One possible economic instrument is an aviation-specific tax (White et al., 2019; Chuang, 2021; Bernardo et al., 2024). A tax levied on aviation services can be designed for simplicity, transparency, and incremental implementation. For instance, a levy could be imposed at the point of departure, at the gate, or during the ticket purchase process. This tax could apply to both domestic and intra-community flights, potentially with a modest tax on aviation fuel (kerosene), which currently benefits from an exemption under ICAO regulations. This levy structure could be introduced gradually to avoid immediate disruptions. However, the introduction of such economic measures is complicated by the principle of non-discrimination embedded in bilateral agreements between EU member states and third countries. This principle restricts unilateral actions such as introducing taxes that might disadvantage certain countries, especially those located at the periphery of Europe, where global tax systems are not uniformly applied. To address these concerns, a two-tier pricing system could be proposed, allowing internal European flights to be taxed without violating non-discrimination principles. Such a system would reduce the effectiveness of aviation-specific taxes but may still offer a viable approach for emission reduction. Another key economic instrument for emission reduction is carbon offsetting and carbon pricing. The EU ETS, introduced as part of the SES initiative, is one of the most prominent tools for curbing aviation emissions. While European carriers have participated in the EU ETS since its inception, its full implementation remains challenging due to difficulties in accurately estimating emissions and aligning the system with ICAO provisions. 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J Big Data 8:1–26. https://doi.org/10.1186/S40537021-00438-6/TABLES/8 Yue X, Byrne J (2021) Linking the Determinants of Air Passenger Flows and Aviation Related Carbon Emissions: A European Study. Sustainability 2021, Vol 13, Page 7574 13:7574. https://doi.org/10.3390/SU13147574 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 99 REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 100 3. Short-haul flights ban in France: relevant potential but yet modest effects of GHG emissions reduction8 8 This chapter has been published as: Andoni Txapartegi, Ignacio Cazcarro, Ibon Galarraga. Short-haul flights ban in France: Relevant potential but yet modest effects of GHG emissions reduction, Ecological Economics, Volume 224, 2024, 108289, ISSN 0921-8009, https://doi.org/10.1016/j.ecolecon.2024.108289. (https://www.sciencedirect.com/science/article/pii/S0921800924001861) REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 101 3.1 Introduction Transport has a very large mitigation potential (Creutzig et al., 2022) and in particular, the air transport is one of the major pollutants sectors worldwide (Fan et al., 2018), as it would rank in the top 10 emitters globally if considered as a separate country (ICAO, 2019). Thus, the GHG (especially carbon dioxide (CO2)) produced by this activity have been extensively studied in the literature (Graver et al., 2018; Loo et al., 2014; Zheng, 2020). These emissions are measured and tracked in detail by different organizations (Mendes and Santos, 2008; OECD, 2022). Contributing more than 2% of global emissions, aviation is seen as a possible target for mitigation (Delbecq et al., 2022; Dubois and Ceron, 2006; Owen et al., 2010; Planès et al., 2021; Terrenoire et al., 2019), but according to Sky views (2023), the sector is lagging behind in decarbonisation efforts. International aviation and shipping emissions may be regulated by several policies, e.g. domestic emissions trading schemes, or trading schemes established by the relevant international organizations (Haites, 2011), although there might be partial avoidance practices (Cames, 2007). In the European context, aviation accounted for 3.8% of total CO2 emissions in the EU in 2017 and is the second-largest source of transport-related GHG emissions after road transport, contributing 13.9% of transport emissions (EUROCONTROL, 2022). Moreover, the European Commission (2020) report or (Lee et al., 2021) show that the combined non-CO2 climate impacts from aviation activities are at least as important as those of CO2 alone. Therefore, the European Union (EU) is acting to address aviation emissions (European Commission, 2021). These initiatives include the adoption of a series of legislative proposals to achieve climate neutrality by 2050, with a target of at least a 55% net reduction in GHG emissions by 2030 (European Commission, 2018). One of these proposals, the review of EU climate legislation, including the European Union Emissions Trading System (EU ETS), has been in place since 2012, requiring all airlines operating in Europe to monitor, report, and verify their emissions and surrender allowances to cover their emissions. This measure has reduced the carbon footprint of the aviation sector by over 17 million tonnes per year (9% of the total emissions) (European Union, 2017). Other actions to reduce CO2 emissions in the aviation sector include fuel efficiency improvement (ICAO, 2019) or operational measures, such as modernizing air traffic management technologies and procedures (EUROCONTROL, 2022). In addition, the EU's "Fit for 55" package to reduce GHG emissions includes the ReFuel EU Aviation Regulation (European Commission, 2023). This regulation establishes rules to promote sustainable aviation fuels across the EU, such as the obligation to gradually increase the percentage of sustainable REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 102 aviation fuels or the need to report the fuel used by both airlines and suppliers (European Union, 2023). In this context, France has recently gone further in the context of other transition measures9 and adopted a measure limiting the exercise of traffic rights due to serious environmental problems (European Union, 2022). This policy bans the short-distance flight routes when there is the alternative of making the journey by train in less than 2:30 hours (details can be found in (European Union, 2022)). Even if this seems to be a step forward in the objective of reducing the emissions generated by the aviation sector, it has been widely criticised by different environmental groups (Greenpeace, 2022), as it is considered insufficient. Authors like (Dobruszkes et al., 2022) also state that such policies have little effect on emission reductions. It can be argued that this measure is among the pioneering ones (especially on banning) worldwide, and measures of similar nature are being considered in other countries, especially European ones. The final measure turned out to be less ambitious than initially proposed by the Citizens' Climate Convention (CCC, 2020) though, where the time limit was set at 4 hours. In this way, setting the limit in 2:30 hours have narrowly left out important domestic air routes. This ban only affects three domestic routes (the connections between the Orly airport in Paris with the cities of Lyon, Bordeaux and Nantes) since the 2:30 hours are calculated considering the time to travel from airport to airport. It has been criticised that it does not really have that much impact on these routes since according to the historical data (Eurostat, 2023), the routes between Paris and these three cities have had more flights and passengers from Charles de Gaulle airport than from Orly. In addition, these routes from Orly airport had already been drastically reduced due to the pandemic (Eurostat, 2023). Moreover, there may be a substitution effect between Paris airports and these routes from Charles de Gaulle may increase, reducing the effect of the measure, that will be analysed. Furthermore, only commercial flight routes are included, as private aviation (non-commercial flights) is out of the focus. With the aim to contributing to the expected impact of this policy, this research estimates the climate and socio-economic impacts of the policy along supply chains and countries using InputOutput (IO) analysis. The IO models display the interconnections between all the economic activity sectors within an economy (or within several economies). They are particularly useful to 9 E.g., launching the Ecological Transition Plan (ETP), see also (Hachaichi and Talandier, 2023) on the estimates of the Ecological Footprint, in conjunction with a spatially-nested approach, as a monitoring framework. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 103 calculate the whole overall socio-economic impact, as they consider the whole value chain to produce the service (in this case air transport). For this purpose, we analyse two alternative scenarios: The first one focused only on the air routes that have been actually banned. This first scenario (scenario 1) will serve to evaluate the policy in this initial phase, as it was done with the EU ETS (European Union, 2004) and also to increase public acceptability of the policy, as in (Maestre-Andrés et al., 2021). A second more ambitious one (scenario 2), also includes some more air routes considering that instead of airport-to-airport trips, city-to-city routes are included. The main reason for this new scenario is to analyse the more plausible situations in which travellers want to arrive at the destination city and not at the destination airport. The IO models also include the substitution effect of transport modes, in this case the increase in activity of rail transport (as is the objective of the measure). Thus, for each of the scenarios, on the one hand the isolated impact of the reduction in air transport will be measured (scenarios 1a and 2a), and on the other hand, the overall impact, including the increase in rail transport (scenarios 1b and 2b). 3.2 Methodology Several studies have explained and highlighted the strengths and weaknesses associated with top-down IO approaches (and bottom-up life cycle assessment approaches) to consumptionbased accounting, as in (Hertwich and Peters, 2009; Kokoni and Skea, 2014; Peters, 2010; Sun et al., 2019; Wiedmann, 2010). The IO models are macroeconomic models that represent the interdependencies between different sectors in a quantitative way. The practical applications of IO analysis derive from Leontief's model (Kuznets, 1941; Leontief, 1937, 1936). IO Tables (IOT) allow to empirically represent the complete economic structure of a region or country, as well as the multiple relationships between the sectors that compose it (Simpson and Tsukui, 1965). In fact, together with national accounts, they constitute the central pillar of the economic accounts in any country or region. Essentially, the IOTs record the total production of each sector and the destination of this production. Equation 3.1 below shows that the output of a sector is equal to intermediate consumption plus final demand for all sectors in the Leontief model: xi = zi1+ zi2+⋯+ zij+⋯+ zin+ fi=∑zij+ fi nj=1 (3.1) Where xi is the output of the i-th sector, zij are the flows from sector i to sector j and fi is the total final demand of the i-th sector (private consumption, government expenditure, investment, and exports). In matrix terms: REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 104 �x1 x2 ⋮ xn�=�z11 z12 ⋯z1n z21 z22 ⋯z2n ⋮ ⋮ ⋱ ⋮ zn1 zn2 ⋯znn� �1 1 ⋮1�+�f1 f2 ⋮fn� (3.2) x = Z1 + f (3.3) Where Z is the inter-industry transactions matrix and x and f are the output and final demand vectors. If we define the technical coefficients as: 𝑎𝑎𝑖𝑖𝑖𝑖= 𝑧𝑧𝑖𝑖𝑖𝑖 𝑥𝑥𝑖𝑖; The model can be formulated as follows: �x1 x2 ⋮ xn�=�a11 a12 ⋯a1n a21 a22 ⋯a2n ⋮ ⋮ ⋱ ⋮ an1 an2 ⋯ann� �x1 x2 ⋮ xn�+�f1 f2 ⋮fn� (3.4) x = Ax + f (3.5) Where A is the matrix of technical coefficients. Each coefficient [𝑎𝑎𝑖𝑖𝑖𝑖] in the matrix measures the output of sector i from sector j. If we clear 𝑥𝑥 in the equation, we obtain the basic Leontief model: x = [I −A]−1f = Lf (3.6) Where L is the so-called Leontief inverse matrix, technology matrix or production multiplier matrix. The coefficients of this matrix [𝑙𝑙𝑖𝑖𝑖𝑖] indicate the increase in the output of sector i that is necessary to satisfy an increase of one additional unit in the final demand of sector j. Each element of the main diagonal is always greater than 1 (lij >1) since it includes the direct effect of the increase in demand on the production of its own sector plus the indirect effects on other sectors. To measure the impacts on the change in final demand for a sector, it is enough to change the values in the final demand vector (f) and multiply it by the inverse Leontief matrix (L). In particular, the substitution is exact in economic terms of the final demand (hence the magnitudes of change are properly captured), but it takes the closest economic structures possible in such setup. In particular, the substitution occurs in the final demand of the French households, in the final demand of the French air transport sector. The difference between the new output vector (x�) and the original output vector (x) will be the total impacts of the change in final demand. x�= [I −A]−1f= Lf (3.7) REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 105 ∆OUTPUT = x−x� (3.8) In this case, the final demand vector consists of values for each of the sectors in each of the countries (sectors and countries can be seen in Annex I). As was discussed, the economic activities that will be directly affected by this policy are the French air and rail transport sectors. Thus, the rest of the sectors remain the same and the final demand of French aviation sector will be decreased in each case depending on the number of passengers affected, resulting in a new final demand value (fFRA,TAIR). This decrease in terms of output will be obtained from the sum of the price of the flight ticket of all travellers affected by the new measure (the acquisition of this data is explained in the section below). In the same way, the final demand of French rail sector will increase in 1b and 2b cases, resulting also in a new final demand value (fFRA,TAIR). ⎝ ⎜ ⎜ ⎜ ⎛ fAUT,PARI ⋮ fFRA,TRAI ⋮ fFRA,TAIR ⋮ fWWM,EXTO⎠ ⎟ ⎟ ⎟ ⎞ (3.9) This L matrix can also be used to calculate the output multipliers, which is defined for sector i as the total value of production in all sectors in the economy that is required to satisfy a unit increase in the final demand of sector i. The output multiplier of sector i is calculated as the sum of column i in the matrix L. Moreover, the matrix L multiplied by the coefficients associated with any indicator will allow the multiplier effect of that indicator to be calculated (Rasmussen, 1956). Thus, the multiplier effects of indicators such as value added, employment or emissions could be calculated by simply multiplying the L matrix by the vector of coefficients of the indicator (Cella, 1984; Dietzenbacher, 2005, 2002; Dietzenbacher and Van Der Linden, 1997; Miller and Blair, 2022; Miller and Lahr, 2001; Oosterhaven, 1988). In this way, the Greenhouse Gas (GHG) emissions are calculated like: GHG = e[I −A]−1f = eLf (3.10) Where e is the vector of coefficients of GHG emissions. The emissions with alternative scenarios are calculated like: GHG � � � � � � = e[I −A]−1f=eLf (3.11) REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 112 Table 3.5: CO2 emissions change relative to their totals in France Scenario 1 Scenario 2 a) Only flight b) Substitution by trains a) Only flight b) Substitution by trains CO2 France aviation -0.5% -1.6% CO2 France -0.07% -0.05% -0.22% -0.18% Output France -0.005% -0.003% -0.016% -0.010% ∆Multiplier (∆CO2/∆Output) (X)13.6 (X)17.8 (X)13.6 (X)17.4 Source: own elaboration Nevertheless, the reduc�on of emissions is a global concern. Table 3.5 focuses only on the emissions reduced in France (90% of the total reduc�on, i.e., an addi�onal 10% of CO2 emissions reduc�on is found globally, reaching 176, 138, 567 and 453 thousand metric tons of CO2 emission reduc�on respec�vely in the scenarios 1a, 1b, 2a, 2b). In addi�on, as men�oned in the introduc�on, the combined non-CO2 climate impacts of avia�on ac�vi�es are at least as important as CO2 alone. Thus, Figure 3.2 shows the total emissions reduced of GHG (CO2, Methane (CH4), Nitrous Oxide (N2O), Sulphur Hexafluoride (SF6), Hydrofluorocarbons (HFC) and Perfluorocarbons (PFC)) as well as some air pollutants such as Sulphuric Oxides (SOx), Nitric Oxides (NOx), Ammonia (NH3) and Carbon Monoxide (CO) rela�ve to the output in a global level. Being above the output line means that the rela�ve reduc�on of that type of emission is bigger than the reduc�on in output. Note that in this case the mul�pliers are smaller, as in Table 3.5 in the 2a scenario the mul�plier was 13.6 and globally the mul�plier is “only” 3.4. The reason is that globally, due to the direct and indirect purchases of the French avia�on sector, s�ll global emissions fall (slightly in percentage terms, in rela�on to global ones) and output as well (even more slightly) but in a smaller propor�on than emissions. In other words, emissions fall 340% more than output. As can be seen in Figure 3.2, the reduc�ons of emissions in CO2, N2O, NOx and CO are worth men�oning, more so if only the French context is considered. In these four cases more than 90% of the reduc�ons would be from France since these substances are very present in the final air transport service. In contrast, for the emissions of the other gases studied the impacts would be much more globally distributed, as these emissions are generated much earlier in the air services value chain. The difference between the two scenarios included in the figure is very relevant, as in all gas emissions the mul�plier is higher in the 2b scenario. This means that rail transport is less pollu�ng rela�ve to output for all gases. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 113 Figure 3.2: GHG emissions change to output when only air transport is included and when substitution by train is included. 3.3.1 IO limitations and uncertainty discussion The limitations of the IO analysis and its potential uses have been largely discussed in the literature (Bickel, 1987; Jensen, 1980; Líšková, 2015; Miller and Blair, 2022; Oosterhaven, 2023; Richardson, 1972; Ten-Raa, 2005; West and Jackson, 2004; Wiedmann et al., 2010). When being compared to other methods, or to highlight we usually find those related to the Leontief’s basic assumption of constancy of input coefficient of production (even with dynamically modelling, on the drivers of change), constant returns of scale and technique of production, linearity, lack of factor substitution, or of price adjustments mechanisms. Understanding such limitations, but also the contexts and types of studies for which these are more acceptable, together with the strengths of IO, when the analysis is of high use and explanation power, etc., the discussions of limitations then tend to move more into the questions within data and modelling choices, their uncertainties, etc. The evaluation of uncertainties in input-output and related studies has been addressed, among others, by Bessembinder (1995), Bullard (1976), Chen et al. (2018), Jensen (1980), Lenzen (2001), Lenzen et al. (2010), Roy (2004), Temurshoev (2015), Weber (2008), Wiedmann et al. (2008), Wilting (2012), Yamakawa and Peters (2009). Along such literature, it is REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 114 often showed that they may arise from various sources, namely data reliability, allocation, potential aggregation biases, imports assumption, technological changes, etc. As briefly hinted when explaining the data and modelling choices, even when always uncertainty and potential errors are likely to remain (being difficult to quantify, see e.g. Peters et al., 2007), we aimed for minimizing as much as possible several potential errors, or biases, etc. Especially with the use of multiregional input-output data (to reduce those usually associated with trade assumptions, boundaries/geographical coverage, etc. with respect to e.g. national IO choices), furthermore with a widely chosen and accepted database (especially regarding environmental satellite accounts such as carbon emissions and to avoid aggregation biases due to the very high sectoral disaggregation). Also, by combining this type of top-down information that we considered more reliable with more sectoral specific, bottom-up one, updated, etc., as well as testing sensitivity to choices. The major uncertainty that we consider the work may have is related to the most recent structural changes due to lack of updated data. Finally, Annex III includes additional estimates and discussions on the robustness and sensitivity of results. As anticipated in note 12, as a robustness test to the emission coefficients, the direct emissions were also estimated using a tool designed by the European Environmental Agency (EEA), which is a bottom-up approach used in the literature on the aviation sector emissions estimates, e.g. in Avogadro et al. (2021). Furthermore, we have also extended the sensitivity analysis to further understand the sensitivity to the year of analysis choice, as in general to further understand and discuss the robustness of the analysis. 3.3.2 Recent evidence on actual routes and flights The scenarios we are talking about would be fulfilled if these flights are reduced on the one hand and if they are replaced by the train on the other hand. Since these routes were cancelled on 23 May 2023, the first trends in the adaptation of French transport to this measure can be observed today. On the one hand, French rail transport broke all-time passenger records this summer (Le Monde, 2023a), increasing by 20% compared to the previous year. In addition, the routes from Paris to Lyon, Bordeaux and Nantes are ranked 1st, 3rd and 4th in the most frequented rail lines respectively. On the other hand, the air routes between the Charles de Gaulle and Lyon Saint-Exupery and Bordeaux-Merignac airports were in all-time highs for this summer, with an increase of 16 % and 23% relative to July 2019 respectively (Eurostat, 2023). These figures are even more significant REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 115 if it is considered that total French air traffic in 2023 is still 9% lower than in 2019 and 10% lower in summer months (EUROCONTROL, 2023). The only route that counterpoise this general trend is that between Charles de Gaulle and Nantes Atlantique airports, where the number of flights in 2023 is 8% lower than in July 2019. Moreover, according to Le Monde (2023b), the three affected routes have been already taken out by Air France at the government´s request in 2020, the main airline in France (exceeding 80% of flights for all three air routes). However, this request by the French government was probably made to give Air France time to adapt to this measure, and then although Air France no longer used these routes, other airlines did, and this ban puts an end to these routes. With these data, it can be seen that although some passengers have indeed changed their mode of transport to rail, it cannot be concluded that scenario 1b is the most realistic. The real current scenario is probably a sort of 1c scenario with less CO2 reductions and losses for the air transport sector than 1b, in which the real behavioural change is less stylized given the current law and incentives. The reduction of the three affected routes is substituted by both rail transportation and flights from/to Charles de Gaulle. In this way, on the air routes between Charles de Gaulle and Lyon Saint-Exupery and Bordeaux-Merignac, there are currently 29% and 34% more flights respectively than there would have been if the Orly passenger’s substitution had been entirely made by train. This means that the different estimations made in emissions reduction are overestimated, since part of the flights are replaced and not cancelled, and that the policy is probably even more ineffective in reducing emissions than predicted. Thus, the reduction in CO2 emissions would be 29% less than estimated in the 1b scenario, keeping them at 98 thousand metric tons. 3.4 Conclusions The measure of limiting the exercise of traffic rights due to serious ecological problems has been presented especially by French ministers and President Emmanuel Macron as a policy to cut carbon emissions, claiming to be at the forefront of ambitious climate change policy. The measure is relatively pioneer (other cases exist, truly often more partial and not driven by a whole country, for shortest distances, or introducing taxes instead of bans as in Austria, (WELT, 2020)). There is also a broad scientific consensus worldwide that emission reductions should be a priority objective (e.g. IPCC, 2023) and this measure goes in that direction addressing measures for a sector as transport that presents relevant potential for emission reduction. This research REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 116 aims to contribute to the analysis of the policy impacts in environmental and socioeconomic terms. However, the results are showing that the implementation is still having a quite limited quantitative effect. As discussed, the ambition and arbitrariness of setting the limit at 2:30 hours are also criticised by several groups (Greenpeace, 2022), as this means that the mentioned routes from Charles de Gaulle (with the consequent substitution effect) or the route to Marseille are narrowly left out. Furthermore, estimates such as (Le Monde, 2023b) do not consider the airport substitution effect that is taking place. In addition, the same article estimated that the number of flights affected if the CCC proposal (4 hours limit) was adopted would be 7 times higher than at present (scenario 1). A stringent ban in this line should take into account other considerations (business-work-family reconciliation, potential limited direct daily service (OECD, 2022), connections, and similar arguments or excuses discussed both by the European Commission17 and France) but certainly similarly to what is shown here, the GHG emissions reductions would clearly exceed in relative change other economic effects. This research therefore aims to quantify the approved scenario together with the scenario in which 2:30 hours is maintained as the time limit but is measured on a city-by-city basis. In addition, this scenario would avoid the current substitution effect of Parisian airports and effectively reduce the number of flights. The results show that with only this change in the measure, reduced emissions of CO2 can be multiplied by more than 3 times. Apart from CO2, the reductions of emissions in N2O, NOx and CO are very relevant. This ban obviously has negative economic effects on the airline industry, which has to be restructured, and on its entire value chain. Even so, by including rail as a travel alternative, a large part of the negative effects in the value chain are mitigated and that emission reductions are maintained. For the negative economic effects, potential compensations, subsidies, or other type of support could be studied. Moreover, for all gas emissions studied, substitution by train has positive effects, as the rail transport is a good alternative when the objective is reducing emissions. This substitution by rail is also very feasible in a country with such an extensive and high-capacity rail network as France, thanks in large part to the high-speed train. Even more, as 17 As summarized in (European Union, 2004), the EU executive said France was justified to introduce the measure provided it is "non-discriminatory, does not distort competition between air carriers, is not more restrictive than necessary to relieve the problem." (…) “Three more routes could be added — between Paris Charles de Gaulle and Lyon and Rennes, and between Lyon and Marseille — if rail services improve.” “Those routes currently don’t meet the threshold because travellers trying to get to airports in Paris and Lyon don't have a rail connection that would get them in early enough in the morning or late enough in the evening”. “Two other proposed routes — from Paris Charles de Gaulle to Bordeaux and Nantes — were excluded from the measure because the rail journey time falls above the two-and-a-half-hour limit”. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 117 highlighted in (OECD, 2022), improvements to rail services should see further routes banned. High-speed rail alongside improved rail networks can make ground travel more attractive and competitive with air travel (as well as remove road traffic to further reduce emissions, see (Avogadro et al., 2021). As future research, studying the impact of the setting the time limit as proposed by the CCC can be very useful to analyse de trade-off between travel comfort and environmental commitment. Quantifying the impact of the ban in private aviation would be also interesting to search for future improvement. Moreover, studying the impacts of similar measures in other European level, both individually and as European Union, can be useful to legislators in the expansion of such measures. It could be relevant to study the effects of a similar measure for other European countries using this methodology. Not only at the individual country level (e.g. in the surrounding area it could make sense for relatively large countries in the European context: Germany18, Spain...) but also for the European Union as a whole, or at least for groups of countries, as e.g. is being proposed by the Netherlands (150 km, with Belgium, etc.). Other contexts, such as the ones of the United States or China, are quite different in terms of flight distances and land transport alternatives. In any case, e.g. the fact that the US ranks first for emissions from domestic flights (OECD, 2022; Owen et al., 2010) or the hinted advances in China in high-speed rail (Lawrence et al., 2019) indicate that relevant domestic flight reduction potential exists also for such large countries and economies. All in all, the literature is quite consistent (Delbecq et al., 2022; Dubois and Ceron, 2006; European Commission, 2021; Owen et al., 2010; Planès et al., 2021; Terrenoire et al., 2019) in signalling the need of emission mitigation for the aviation sector, emissions reductions, etc. for sustainable climate trajectories. 18 See e.g. (Reiter et al., 2022) aimed to quantify the potential impact on CO2 emissions of substituting short-haul flights with rail frequencies in German air travel corridors., discussing as well the assessment in relation to travel time losses. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 118 3.5 References Avogadro, N., Cattaneo, M., Paleari, S., Redondi, R., 2021. Replacing short-medium haul intra-European flights with high-speed rail: Impact on CO2 emissions and regional accessibility. 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Using Economic Instruments to Address Emissions from Air Transport in the European Union. http://dx.doi.org/10.1068/a39255md 40, 189–209. https://doi.org/10.1068/A39255MD Miller, R.E., Blair, P.D., 2022. Input-Output Analysis: Foundations and Extensions. https://doi.org/10.1017/9781108676212 Miller, R.E., Lahr, M.L., 2001. A taxonomy of extractions. Regional science perspectives in economic analysis : a festschrift in memory of Benjamin H. Stevens. Moses, L.N., 1955. The Stability of Interregional Trading Patterns and Input-Output Analysis. Am Econ Rev 45, 803–826. OECD, 2022. Air Transport CO2 Emissions [WWW Document]. URL https://stats.oecd.org/Index.aspx?DataSetCode=AIRTRANS_CO2 (accessed 6.8.23). REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 128 operating conditions (fewer stops, i.e. less energy used for acceleration) make the high-speed rail even more efficient. This measure is very much in line with the current investment in the national high-speed train line, both in increasing the number of routes and in improving the efficiency of the trains (RENFE, 2024). The development of the high-speed train has been one of the government's main axes and will continue to be so as stated in the Mobility Plan 2030, in line with the EU Commission's Trans-European Transport Network (TEN-T) project (European Commission, 2019; ADIF, 2021; MTMS, 2021). Moreover, the current Spanish high-speed network has proven to be particularly efficient (MTMS, 2023; ADIF, 2024a). This research seeks to enhance our understanding of the anticipated effects of the proposed policy by estimating its climate and socio-economic impacts across supply chains and countries, employing Input-Output (IO) analysis. IO models serve as comprehensive frameworks illustrating the interdependencies among all economic activity sectors within a single economy or across multiple economies. Their utility lies in their ability to assess the holistic socio-economic impact, as they account for the entire value chain involved in producing a service, such as air transport in this context. IO models have been used to measure economic and environmental impacts of different transport related research (Oosterhaven and Stelder, 2002; Yu et al., 2021; Keček et al., 2022; Abbood and Meszaros, 2023). Through IO analysis, this study aims to provide a nuanced evaluation of the policy's ramifications, shedding light on its implications for both the climate and various socio-economic factors. Given the lack of specific details within the government agreement, this study will explore various future scenarios regarding the implementation of the proposed measure. These scenarios will be developed to facilitate comparative analysis, allowing for an examination of potential outcomes under different conditions. By delineating multiple scenarios, this study aims to offer a comprehensive exploration of the implications associated with the policy, thereby aiding in informed decision-making and policy formulation. The first scenario will exclusively analyse the prohibition of flights on routes with a rail alternative of less than 2:30 hours, as the original text of the proposed ban states. It is worth mentioning that this time will be measured from city to city and not in travel time at the airport, as in the French case. Considering travel time from airports has created a paradox where flights to the same city, such as Lyon, may or may not fall under the policy depending on the Parisian airport of departure (Charles de Gaulle or Orly), even though the train alternative from Paris’ REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 129 Gare du Nord station remains the same. Although the connection to Barajas airport is under construction and is expected to be available by 2026 (RENFE, 2024), there are currently no highspeed rail connections to airports. However, several important routes are left out of this measure by a few minutes (Madrid-Valencia, Madrid-Sevilla or Barcelona-Valencia). Thus, a second scenario is calculated where a limit of 4 hours is set. The reason for setting this limit at 4 hours is that this was the original proposal in the French case (the only country that has implemented it as a full national policy), although it was eventually reduced (Convention Citoyenne pour le Climat, 2020). The aim of this second scenario is to quantify a more ambitious alternative of the measure in order to compare it with the first scenario. Finally, the third scenario will project a future scenario wherein the high-speed rail lines, presently under construction, become operational. This scenario is designed to assess the aggregated impact of the proposed policy in conjunction with the realization of high-speed rail infrastructure objectives in Spain. The IO models encompass the substitution effect of transport modes, particularly relevant in this context given the intended increase in rail transport activity as a result of the policy measure. Therefore, each scenario will be analysed to gauge both the isolated impact of the reduction in air transport and the overall impact, accounting for the concurrent increase in rail transport. This dual assessment approach allows for a comprehensive understanding of the policy's implications, considering not only the direct effects on air transport but also the broader dynamics within the transportation sector resulting from mode substitution. Section 4.2 details the methodology and data used. Section 4.3 describes the different scenarios and ranges considered for complementary analyses, being quantified in the section 4.4 of results. Finally, section 4.5 focuses on the conclusions of the research and policy implications. 4.2 Methodology This study employs input–output (IO) models to analyse the economic and environmental impacts of the discussed measure (more methodological details can be found in appendix 1). IO models, grounded in the work of Leontief, provide a framework for understanding interdependencies between economic sectors. The analysis uses input–output tables (IOTs) to quantify sectoral outputs and their distribution, serving as a basis for assessing the broader economic effects of policy changes. The central tool is the Leontief inverse matrix, which captures the ripple effects of changes in final demand across the economy. Policy impacts are simulated by adjusting the final demand REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 130 vector for the Spanish aviation and rail sectors based on the affected passenger volumes and ticket prices. The model also calculates multiplier efects (see Cella, 1984; Oosterhaven, 1988; Dietzenbacher and Van Der Linden, 1997; Miller and Lahr, 2001; Dietzenbacher, 2002, 2005; Miller and Blair, 2022; Oosterhaven, 2024) for indicators such as greenhouse gas emissions, value added and employment, enabling a comprehensive understanding of economic and environmental consequences. 4.2.1 Data availability For the analysis, we have combined data from various sources. The commercial air routes, with their respective numbers of fights and passengers in 2023, have been obtained from AENA (2023), the Spanish public company which manages the airports. Train journey times were consulted in ADIF (2024b), the public company under the Ministry of Transport and Sustainable Mobility that manages the operation of Spain's railway lines. The average air fares for the selected routes in 2023 have been calculated by obtaining monthly averages from different company websites (e.g. Iberia, Vueling, Air Europa) and web comparators (mainly Omio, Booking and Kayaks). These comparators provide estimates of the average price of a route, which was obtained along 2023 for each month. These monthly averages have been cross-checked with AENA's monthly passenger data to obtain the annual average. Additionally, as air transport is a service with high seasonality, the monthly evolution of the national air transport Consumer Price Index (CPI) of the Spanish National Statistical Institute (NSI 2024a, b) has been cross-checked, being used this last one to create a confidence interval, as well as with the main statistics provided by Andrés Martínez et al. (2017); details of the process can be found in Annex IV. Rail ticket prices by quarter in 2023 for the same routes have been consulted in CNMC (2023-2024). In this case, these data have been crossed with the number of rail passengers per quarter to obtain the average annual price. Conversions between purchaser and basic prices were performed following Cazcarro et al. (2022). The annual averages can be consulted in the Annex IV (Table IV.1). The methodology described in the previous section is applied to Spain based on the EXIOBASE 3 (3.8.2 version) multiregional Input-Output (MRIO) tables at basic prices by product (Standler et al., 2021). EXIOBASE 3 provides a time series of environmentally extended MRIO tables for 44 countries (28 EU member plus 16 major economies) and five regions of rest of the world. The industrial classification goes up to 163 industries, which is very useful for accurately determining cross-sectoral connections. Moreover, EXIOBASE 3 offers Investment Matrixes describing the REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 131 total use of capital goods by industries. The environmental extension including different pollutants can be used for consumption-based accounting of greenhouse gas (GHG) emissions (Kokoni and Skea, 2014). Recall that these models measure the entire value chain and in this way the impacts of the intermediate products imported to produce Spanish air services can be measured. The reference year used is 2019, to avoid the impacts related to the COVID-19. In addition, to enhance the robustness of the analysis, direct emissions were also estimated using a tool developed by the European Environment Agency (EEA) (Annex IV). However, as shown in the section on the current state of short flights in Spain, the sector has undergone a substantial improvement in environmental efficiency, both in terms of the aircraft used and the increase in the number of passengers per flight (it has been found that carbon emissions of individual flights differ tremendously, see Baumeister, 2017). In order to reflect this new reality of the sector, the emissions coefficients of the original EXIOBASE matrix have been modified20. Specifically, the CO2, CH4, N2O, SOx, NOx, NH3 and CO emissions coefficients for the aviation sector have been modified using the 2023 data obtained from AENA (2023) and NSI (2024c). The rest of sectors have been updated using data from OTEA (2024), which provides updated annual emissions estimates up to 2023 for the major sectors of the Spanish economy. 4.3 Definition of Scenarios 4.3.1. Main scenarios As can be observed, the first scenario only includes three air routes, highlighting the Madrid - Barcelona route, the connection between the two main Spanish cities. The second scenario adds a further 11 air routes that would be abolished if the measure were to set the rail alternative limit at 4 hours. The third scenario extends the suppressible air routes by a further 8 routes. The case of Madrid-Jerez de la Frontera deserves a special mention, as it is a journey that can actually be made by train in less than 4 hours but not directly (a stopover in Seville is necessary). For this reason, it has been decided to include it in the third scenario (see Table 4.1). 20 The process and the impact of this modification is shown in Annex IV REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 132 Table 4.1: Affected routes and their corresponding train alternative time Routes Train times First scenario: 2:30 hours limit 1 Madrid – Valencia / Valencia - Madrid 1:49 2 Alicante-Madrid / Madrid-Alicante 2:17 3 Barcelona-Madrid / Madrid-Barcelona 2:29 Second Scenario: 4:00 hours limit 4 Barcelona-Valencia/ Valencia-Barcelona 2:52 5 Madrid-Málaga / Málaga-Madrid 2:47 6 Madrid-Pamplona / Pamplona – Madrid 2:59 7 Madrid – Santiago de Compostela / Santiago de Compostela – Madrid 3:16 8 Madrid – Sevilla / Sevilla – Madrid 2:42 9 La Coruña – Madrid / Madrid – La Coruña 3:48 10 Granada – Madrid / Madrid Granada 3:31 11 Logroño – Madrid / Madrid – Logroño 3:16 12 Madrid-Asturias 3:11 13 Madrid-Castellón 2:59 14 Madrid-Murcia 2:45 Third Scenario: 4:00 hours limit (including feasible routes in the future) 15 Madrid-Jerez de la Frontera / Jerez de la Frontera - Madrid* 3:47* 16 Madrid-Badajoz / Badajoz-Madrid - 17 Madrid-Bilbao / Bilbao-Madrid - 18 Madrid-San Sebastián / San Sebastián-Madrid - 19 Madrid-Santander / Santander-Madrid - 20 Barcelona-Alicante / Alicante-Barcelona - 21 Barcelona-Bilbao / Bilbao-Barcelona - 22 Barcelona-San Sebastián / San Sebastián-Barcelona - The subsequent two sections will undertake an analysis of the present status of air and rail traffic along routes presently accessible via rail within a four-hour timeframe (scenarios 1 and 2). This analysis aims to acquire an in-depth comprehension of the prevailing trends observable on these specific routes. 4.3.2 Current status of short-haul flights in Spain COVID-19 had a devastating effect on aviation worldwide and Spain was no exception. However, 2023 has already surpassed the 2019 data (last pre-pandemic year), with an 8.31% increase in the number of passengers on international flights and a 2.09% increase in the number of REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 133 domestic flights (AENA, 2023). However, several significant changes have been observed in this transitional period, changing the outlook for the Spanish airline industry. On the one hand, there have been significant changes in the aircraft models used for domestic flights. The most widely used aircraft type, the Aerospatiale ATR-72, has gone from operating 18.37% of flights in 2019 to 27.20% in 2023 (AENA, 2023). Considering that this aircraft model emits, on average, less than half the CO2 emissions per flight of the next two most used models (BOEING 737-800 and AIRBUS A320), this change is very significant in terms of reducing emissions (ATR, 2023). On the other hand, particularly the air routes identified by this directive as being eligible for cancellation have also undergone significant changes. As can be seen in the AENA data (Table 4.2), both the number of passengers and the number of commercial flights have decreased significantly. For example, the Madrid-Barcelona airlift was in 2019 the one with the highest passenger traffic and in 2023 it has been replaced by Madrid - Gran Canaria. In addition, the number of passengers per flight has increased overall due to higher load factors, improving environmental efficiency. Thus, it is important to take 2023 data in order to be able to measure the impact of these policies adjusted to reality, as the sector has undergone significant changes in recent years. REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 134 Table 4.2: Number of passengers and flights of the selected air-routes in 2019 and 2023 Routes Commercial passengers Commercial flights Passengers per flight (Δ% 20192023) 2019 2023 Δ% 2019 2023 Δ% Madrid – Valencia / Valencia - Madrid 338,823 356,348 5.17% 5,681 4,306 -24.20% 38.76% Alicante-Madrid / MadridAlicante 299,522 324,716 8.41% 4,180 3,737 -10.60% 21.26% Barcelona-Madrid / Madrid-Barcelona 2,572,702 1,933,220 -24.86% 17,077 13,062 -23.51% -1.76% Barcelona-Valencia/ Valencia-Barcelona 85,154 36,168 -57.53% 1,666 1,835 10.14% -61.44% Madrid-Málaga / MálagaMadrid 357,762 727,842 103.44% 4,757 5,936 24.78% 63.04% Madrid-Pamplona / Pamplona – Madrid 177,290 145,703 -17.82% 2,571 2,006 -21.98% 5.33% Madrid – Santiago de Compostela / Santiago de Compostela – Madrid 715,350 448,783 -37.26% 4,789 3,325 -30.57% -9.64% Madrid – Sevilla / Sevilla – Madrid 486,775 455,399 -6.45% 5,371 3,167 -41.04% 58.66% La Coruña – Madrid / Madrid – La Coruña 681,508 755,282 10.83% 5,779 5,809 0.52% 10.25% Granada – Madrid / Madrid Granada 199,170 157,241 -21.05% 2,646 1,952 -26.23% 7.02% Logroño – Madrid / Madrid – Logroño 12,752 12,006 -5.85% 460 466 1.30% -7.06% Madrid-Asturias / AsturiasMadrid 548,114 394,703 -27.99% 5,490 3,027 -44.86% 30.60% Madrid-Castellón / Castellón-Madrid 502 12,539 2398% 47 548 1066% 114.23% Madrid-Murcia / MurciaMadrid 445 2,970 567% 142 169 19.01% 460% TOTAL 6,475,869 5,762,920 -11.01% 60,514 49,176 -18.65% 9.39% 4.3.3 Current state of high-speed trains prices in Spain The Spanish high-speed rail sector has also undergone major changes since the pre-pandemic era. Through the Fourth Railway Package (European Council, 2016), which determined the European Union's railway framework, Spanish legislation set December 2020 as the date for the start of liberalisation of the passenger rail market in high-speed services (BOE, 2018). Since then, other railway companies such as OUIGO or Iryo have been operating on the Spanish high-speed network, breaking RENFE's previous monopoly. This situation has led to an increase REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 135 in the supply of high-speed trains and a reduction in prices for passengers (ADIF, 2023; Renfe, 2023). So much so that RENFE decided to compete on price through its low-cost brand AVLO (Renfe, 2023). The Spanish high-speed rail system achieved a landmark accomplishment in 2023 by surpassing its previous record for passenger volume (ADIF, 2023). This achievement was accompanied by a notable escalation in traffic, measured in trains per kilometer, with growth rates exceeding 30% in 2022 and surpassing 40% in 2023 (partly due to Covid-19 recovery). Such robust expansion not only underscores the system's resilience but also solidifies its position with traffic levels now surpassing those observed prior to the onset of the pandemic. In this manner, a forthcoming second phase of railway market liberalization is envisaged, encompassing the liberalization of additional railway lines, including those in regions such as Murcia and Galicia (ADIF, 2023). Nevertheless, the most notable transformation has been observed in pricing dynamics. As reported by CNMC (2023-2024) ticket prices on routes serviced by two or more railway companies have experienced a substantial reduction, averaging a 23% decrease in comparison to figures recorded in 2022. This reduction gains heightened significance when juxtaposed with data from 2019 or the pre-pandemic era, wherein the average price decline amounted to 65%. The augmentation in supply aligns seamlessly with the ongoing enhancements in infrastructure within the sector. ADIF (2024a), the Railway Infrastructure Manager (a public business entity attached to the Ministry of Transport and Sustainable Mobility) is carrying out tests prior to the commissioning of “key lines this year” (a steadfast commitment aimed at ensuring that nine out of ten citizens reside within a proximity of fewer than 30 kilometres from a high-speed station). Thus, the principal ongoing projects (which may have the years 2025-2027 at least as more realistic finalization periods) considered encompass: • Establishing the connection between the central region and Extremadura. • Facilitating high-speed rail access to Murcia. • Extending high-speed rail services to Santander. • Developing the Basque Y network and its integration with central and eastern regions of the country. • Enhancing connectivity with Madrid-Barajas-Adolfo Suárez airport. Currently, there are listed additional works and projects under development, but with a more uncertain period of finalization, and this have not been included. According to the Ministry of REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 136 Transport and Sustainable Mobility (MTMS 2023, INECO 2023), the cost of building a Spanish high-speed line is 17.7 million euros on average per kilometre, compared to 45.5 million euros on average in other countries with high-speed lines (see also for additional estimates, OTLE, 2024). Also, the environmental damages and effects of the construction period tend to be important, larger than during the operation phases, as several Life Cycle Assessment studies have shown for Spain (Bueno et al., 2017; Damián and Zamorano, 2023; Kortazar et al., 2021). Hence economic and environmental implications (not only of GHG emissions but also of materials, minerals, etc.) should be taken into account for any new construction and dismantling of infrastructure affecting similar measures to this. We want to stress then that our study takes the consideration, on the one hand, on the connection with cities having nearby airports, and on the other, of railway infrastructure that is already finalized, or close to be finalized, or with clear-cut advances implemented that show a firm construction path. 4.3.3 Affected routes and summary of scenarios implemented accordingly Figure 4.1: Affected routes The green routes correspond to the first scenario, the blue ones to the second scenario and the orange ones to the third scenario. As it was mentioned, after defining the three scenarios, the isolated impact of air transportation cessation is initially assessed (scenarios A), subsequently augmented by the integration of REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 137 potential passenger substitution onto rail modalities (scenarios B). In examining the substitution of rail travel, it is essential to consider the diverse dynamics underlying changes in passenger behaviour (see Figure 4.1). On one side, there may be a decline in total passengers, as not all travellers will opt for rail. As mentioned in Rodrigue (2020), restrictions or increased costs associated with a specific transport mode can significantly diminish overall passenger movement, as these changes may lead to decreased convenience and accessibility, compelling travellers to reconsider their travel options and potentially resulting in fewer trips taken. The French case is very significant in this respect, as it is the only country where such measures have been implemented and where changes in passenger behaviour in response to such a measure have been observed in a real case. Thus, one of the main findings of Txapartegi et al. (2024) was that during the first months of the adoption of this measure, some of the eliminated flights were replaced by other flights from other airports. It is important to note that such substitution would not be feasible in the Spanish case, as there are no alternative air routes available for the potentially affected connections. In addition, the report by the French Ministry of Ecological Transition (Ministère de la Transition Écologique, 2023) shows data on what modes of transport passengers who actually stop using air transport use, stating that approximately 63% of passengers would choose to travel by train, 30% would use a car, and 7% might simply choose not to travel at all. Conversely, the banning of these air routes would presumably be accompanied by an increase in high-speed train service to accommodate these passengers. This increase in service can produce a significant increase in passenger numbers and even generate induced effects, which is well documented in the literature (Givoni et al., 2013; Pagliara et al. 2013; Zhang et al. 2019; Avogadro et al. 2023), as seen with the evidence of improved high-speed train service in the section on Current state of high-speed trains prices in Spain. In particular, according to Givoni et al. (2013), this improvement in service can generate an induced effect of up to an additional 1020%. In addition, this improvement may also reduce the number of people who choose to travel by another means (car) or who choose not to travel at all. Contributing to the uncertainty of the future associated to the measures, additional dynamic effects may exist, e.g. on the evolution of demands and then on prices with modified demands (apart from the cited literature on the evidence or expected effects of modal substitution, in terms of passengers in each mode, but also on transport prices is e.g., particularly for Spain we find e.g. OECC-INECO 2021; Cantos-Sánchez et al. 2023; Ecologistas en acción 2023; CantosSanchez et al. 2024). REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 144 When considering total emission reductions in Spain, including the substitution by train (Scenarios B) does not shown such a maximum of reduction of emissions (as Scenario A), as this economic activity also produces emissions. However, apart from being more realistic the scenario B (with is variants/sensitivity analysis) considering that the objective is to reduce emissions as much as possible while affecting the economy as little as possible, the results including the rail alternative are significant. One way to see this is for example to look at the change in the CO2 emissions to output multiplier (CO2/Output) with respect to the baseline in Table 4.5. Table 4.5: Multiplier change 1A 1B 2A 2B 3A 3B % change in the CO 2 /Output multiplier -49% -135% -49% -178% -49% -146% Interestingly, it seems that in terms of the multiplier, the scenario that achieves a higher environmental benefit per output loss is scenario 2B. Another way to see is calculating the % change in GHG emissions to % change in Output ratio, where being above 1 means that the percentage reductions of that pollutant is greater than the economic loss, being larger the larger the value (the all cases in total the % changes both in emissions and output are negative, showing a positive ratio). As can be observed in Table 4.6, in that positive direction of larger environmental reduction than output loss, very relevantly are found the results for CO2, N2O, NOx, NH3 and CO, as the mitigation of negative economic effects is much more relevant than the emissions produced by this activity (while in some other cases such as SOx and the fluorinated gases this is not the case). Table 4.6: % change in GHG emissions/% change in Output for high-speed train and flight comparison Pollutant CO2 CH4 N2O SOx NOx NH3 CO SF6 HFC PFC Scenario 1A 7.07 0.95 15.57 0.86 9.91 20.62 10.78 0.29 0.27 0.23 1B 19.26 1.51 44.86 0.64 25.46 61.31 30.29 0.54 0.45 0.47 2A 7.07 0.95 15.57 0.86 9.91 20.62 10.78 0.29 0.27 0.23 2B 25.50 1.80 59.86 0.53 33.43 82.15 40.28 0.67 0.54 0.60 3A 7.07 0.95 15.57 0.86 9.91 20.62 10.78 0.29 0.27 0.23 3B 20.94 1.59 48.91 0.61 27.61 66.93 32.98 0.58 0.48 0.50 As mentioned before, the planned, and simulated here, policies and measures may lead to changes in the behaviour of passengers who do not necessarily switch to the train. The before REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 145 mentioned report by the French Ministry of Ecological Transition (Ministère de la Transition Écologique, 2023) shows data on what modes of transport passengers who actually stop using air transport use (63% train, 30% car, 7% choose not to travel). It is possible to think that the aforementioned central assumption, which considers a 30% substitution of flights by car, underscores the efficacy of trains as a commendable mode of travel (Cantos-Sánchez et al. 2023; Cantos-Sanchez et al. 2024 even question the net benefits in terms of welfare and environmental damages if as a result of the bans car traffic notably increases – together with increases in international flights and train ticket prices). The Spanish Ministry for Ecological Transition (IDAE, 2024) though provides a comparative analysis of CO₂ emissions by mode of motorized transport per passenger-kilometer, revealing emissions of 192 grams for aviation, 121 grams for cars, and 23 grams for the AVE (high-speed train). The data of the Spanish Ministry underscores a stark contrast between aviation and high-speed rail emissions, while the difference between aviation and cars is less pronounced. While based on that it may be argued that substituting cars for air travel could also contribute to reducing emissions, the data clearly indicates that the most substantial environmental impact lies in shifting passengers from planes to trains. Even more, the range of results provided here, including the common approach so far taken in this type of analyses for Spain (Ecologistas en acción, 2023; OECC-INECO, 2021) of assuming a 100% substitution by train, and even the 115% scenario, reveals more notably such potential of the train, particularly in contexts where the primary policy aim is the mitigation of emissions through this means of transport (as it is the case when basing it on a “reasonable” train alternative time). 4.5 Conclusions Transport, and especially aviation, remains a sector with ample room for improvement in the area of environmental impact mitigation (see also the aviation and climate change adaptation literature review of Ryley et al., 2020). Measures such as the one proposed by the Spanish government (and its French counterpart, already implemented) seek to reduce emissions in the sector where the rail alternative is feasible. Thus, this study aimed to quantify different alternatives for implementing the measure in order to be able to analyse its socio-economic and climatic impacts. Pre and post COVID-19 data for domestic air transport already show significant changes in aircraft models in pursuit of energy efficiency. In addition, having exceeded the preCovid number of total domestic air passengers, the routes which could fall under the ban REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 146 indicate a downward trend in both the number of flights and passengers, hence this decrease in short-haul flights is already taking place without the ban. Along these lines, we explored different levels of implementation depending on the corresponding train alternative time (scenarios 1 to 3), with the “pure” effects of aviation reduction (scenarios A) and the consideration of such effect and that of the modal substation (mainly with train, given the nature of the policy, represented in scenarios B), including around this scenario B additional sensitivity analyses to price variability and modal substitution (given the uncertainty around potential behavioural changes). With the “pure” reduction effect of scenarios A, apart from very noticeable environmental benefits, the input-output analysis shows significant negative socio-economic impacts, both for the aviation sector and its value chain. But by including rail substitution, however, between 60% and 87% of the negative impacts on the value chain would be mitigated. In particular, in terms of CO2 emissions, in 2023, the first scenario would reduce, depending on the mode of substitution of these passengers, between 99 and 184 thousand tonnes in Spain. In the second scenario, between 238 and 435, while in the third, between 351-639 thousand tonnes. Socioeconomic impacts are also explored, finding that the first scenario would reduce output between 134-201 million euros in the Spanish economy. In the second scenario there would be 250-474 million euros reduction considering all sectors; and in the third scenario, 377706 million euros. The % change in GHG emissions to % change in Output ratio is also explored, finding noticeable large ratios above one in the results of CO2, N2O, NOx, NH3 and CO, as the mitigation of negative economic effects is much more relevant than the emissions produced by this activity (while in some other cases such as SOx and the fluorinated gases this is not the case). Going more into the policy context and implications, we may highlight that the high-speed rail sector has reached unprecedented levels of patronage, evidenced by surges in both passenger volumes and available seating capacities, primarily attributed to the phenomenon of market liberalization and the influx of new competitors. Subsequently, the advent of these new market players has precipitated some decline in fare rates, thereby rendering this mode of transportation increasingly appealing to consumers. Such measures align closely with the transport objectives outlined by the Spanish government, given the concurrent expansion of supply within the high-speed rail domain, as previously delineated. Moreover, substantial investments are being directed towards the augmentation of high-speed rail infrastructure, further substantiating the government's commitment to fostering the development and utilization of this mode of transportation. These investments are key and can play a fundamental REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 147 role in changing passenger behaviour in order to redirect them to high-speed rail, as is the objective of the measure. To accommodate the anticipated influx of new passengers, it is essential to consider increasing the frequency of rail services. Such measures would not only support the greater volume of travellers but also mitigate the risk of individuals substituting air travel with other less sustainable forms of transportation, such as personal vehicles. Banning can be compared to carbon taxes in several dimensions: behavioural flexibility (taxes offer more to individuals), speed of impact (taxes rely on more of gradual behaviour shifts and technological improvements), social and economic equity (e.g. on groups, regions or industries affected), etc. But it seems clear that both approaches are more feasible where high-speed rail or other efficient, low-carbon options are available. Also, both can encounter significant challenges, particularly in gaining public support and mitigating economic impacts (Jagers et al., 2019). To address these challenges, compensatory measures have been proposed as complementary to bans or carbon tax policies. These measures are designed to offset the costs associated with these policies, enhance public acceptance, and ensure the overall effectiveness of carbon pricing mechanisms (Geroe, 2019). If applied, compensatory measures may involve carbon tax revenues redistribution to support the transition to more sustainable practices (Becattini et al., 2021). Revenue generated from carbon taxes could be invested in research and development of sustainable aviation fuels or carbon capture technologies, thereby enabling the industry to reduce its carbon footprint while maintaining economic viability. Then the airline sector may undergo another (after recovery from the COVID-19 crisis) restructuring. The choice of adoption of one or the other scenario proves to be very relevant, as the second scenario (the one that based on the change in the emissions to output multiplier, achieves a higher environmental benefit per output loss is scenario 2B) increases the reduced emissions of the first scenario by a factor of 2.4. Moreover, the train proves to be an excellent alternative for the emissions reduction objective, as it produces very low emissions in relative terms. Thus, the train emerges as the most viable alternative for achieving significant emission reductions, unlike the car, where these environmental benefits are considerably diminished. This highlights the critical role of rail transport in advancing sustainable mobility and underscores its superiority in meeting emission-saving objectives compared to other motorized transport options. Hence, it is evident that these measures are in nascent stages, suggesting a requisite period of adjustment. Beyond the airline sector, the rail industry will likewise need to undergo adaptations to effectively accommodate the surge in demand and sustain its appeal to passengers. Enhancements in infrastructure and technological capabilities within are imperative for such REGISTRO TELEMÁTICO Sarreren Erregistro Orokorra / Registro General de Entradas 29/09/2025 13:12 EHU2025E046366 148 policy. This involves obviously the companies offering the railway services and the public sector. We have seen that ADIF (2024a,b), the public company that manages the operation of Spain's railway lines, shows quite clear plans on current and new infrastructure construction. Our exploration has focused though on railway infrastructure that is already finalized, or close to be finalized, or with clear-cut advances already in the implementation (considering also the connection with cities having nearby airports, etc.) because the environmental damages (not only of GHG emissions but also of materials, minerals, etc.) and effects of the construction period tend to be high (see Bueno et al., 2017; Kortazar et al., 2021; Damián and Zamorano, 2023). Future research could examine the environmental and economic impacts of implementing these measures across diverse national and international contexts. Such studies would offer valuable insights into the broader applicability and effectiveness of these strategies, providing a foundation for scaling them up in a manner that is both sustainable and economically viable. This analysis would contribute to a more comprehensive understanding of the potential benefits and challenges associated with widespread adoption of the short-haul flight banning. For the particular case of Spain, we envisage that the studies may go in four directions: first, further exploring the economic and environmental costs and implications of new high speed train construction (for potential additional extensions of the measure); secondly, further exploring the demand diversion and induced effects through an integrated transport mode choice model (see, e.g., DT, 2014; Meixell and Norbis, 2008); thirdly, comparing the effects of the banning with alternative (tax, stick/carrot policies), fourthly, ex-post evaluating the effects of the measure if finally implemented. 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