1. Introduction
Tourism refers to mobility for leisure, as well as several other purposes such as business, healthcare, and visiting friends and relatives. By definition, all visitors must stay at least one night at their destination. Such trips are related to the tourism sector and have associated emissions generated by this mobility. There is international evidence, despite the rate of improvement in aircraft fuel efficiency, that the carbon dioxide emissions from air transport will increase steadily after the COVID-19 pandemic period. The emissions from air transport, in the medium term, will continue to grow rapidly [
1]. In the absence of any environmental policies oriented to decoupling the growth of the air transport volume related to tourism, both sectors will face the potential risk of being considered the main contributor to climate change. In addition, the slow development in air technology means it is urgent to address the efforts required for regulation to ensure that the air travel demand does not exceed the sustainable rate of growth. The aviation and tourism industries must show interest in improving their environmental performance in order to cultivate a positive image and avoid drastic policy actions in the future [
2].
The IPCC recommends reducing worldwide emissions by approximately 50–80% if the target objective is to be reached by 2050. However, as pointed out above, air technology improvements will not be enough to achieve this emission-reduction margin. Hence, solutions must be focused on the demand side. In this sense, the pricing structure and other incentives become relevant [
3].
Air transport for peripheral areas such as the Canary Islands has been recognized as a fundamental factor in their development. The Trans-Insular Axis (the subsidiary of the Trans-European Network) in the Canary Islands is a factor of territorial cohesion in the sense that it provides greater accessibility for air passengers from peripheral islands [
4]. As pointed out in [
5], “social exclusion is not due to a lack of social opportunities but a lack of access to those opportunities”. The Canary Islands have seven islands, and almost all of them are connected by air and sea. The two central islands, Gran Canaria and Tenerife, are the most important in economic terms and therefore have a better connection between each other, as well as with peripheral islands. Except for a few connections with shorter distances of 50–60 miles (Tenerife–Gran Canaria, Tenerife–La Gomera, and Lanzarote–Fuerteventura), where high-speed sea transport is competitive with respect to air transport, in terms of travel time, the rest of the interisland connections, which exceed distances of 80–100 miles, require air transport for inhabitant mobility [
4].
The importance of regional (interisland) air transport at Canary airports is remarkable, even at airports with international traffic. In fact, in 2019, 71% of air traffic at Canary airports was of the interisland variety. Obviously, the fragmented territory of the Canary Islands is the determining factor in the importance of regional (interisland) air traffic. Insularity increases the access costs to social and economic opportunities for Canary Island inhabitants. In that sense, the Spanish government has always given priority to the disadvantaged to facilitate the movement of inhabitants, both in connection to the mainland and in terms of interisland mobility. For this reason, air and sea traffic from the islands to the mainland and between the islands has been subsidized since 1982. The purpose is to compensate for the extra costs incurred by freight and passenger traffic as a result of the Canary Islands’ remoteness from the Spanish mainland and Europe. Recently, this allowance has increased from 50% to 75% of the travel price [
6].
One of the main objectives of subsidizing regional air transport is improving the population’s air mobility between peripheral regions. Easier access to better job opportunities, health services, and leisure travel is a reasonable argument for subsidizing aviation. This may encourage regional air market development in peripheral areas [
7]. However, these kinds of policies can also have perverse effects on airport services management, the environment, and the regional aviation market [
8].
In the Canary Island context, in the absence of any climate regulation scenarios, this means that domestic tourism or mobility for any purpose will increase substantially in the coming years, mainly due to the lack of aviation emissions regulations and the incentivization to travel via the resident subsidy. Thus, the consequences in terms of environmental issues for airports must be considered. One of the main operational issues in airports, namely aircraft taxiing operations for landing and taking off, can become more difficult if the airport is congested. At an airport, bottleneck areas where congestion occurs include departure gates, the apron area, taxiways, and the runway. Congestion during taxiing is very common and depends on several factors, such as weather variability, turbulence, runway capacity, aircrafts landing and taking off at the airport, the skills of air control services, and so on [
9]. It is crucial to reduce the time required for taxiing at airports in order to provide air services in optimal conditions and avoid congestion. The author in [
10] used a simulation approach based on a car congestion model (NS model) to optimize taxiing time. The author estimated an economic benefit in terms of kerosene use of approximately 2.3 million US dollars and a reduction in CO
2 emissions of approximately 7000 tons for Tokyo international airport after one year. On the one hand, the approach proposed in [
11] makes taxiing for ATRs aircrafts family flows autonomous from any other aircraft processed at the LPA airport. The airport-within-airport approach involves two separate subsystems for landing and take-off that avoid disturbance between aircrafts types in surface operations. The authors pointed out that this mechanism produces an annual reduction in CO
2 emissions at the LPA airport by around 1397 tons and a fuel cost saving of EUR 303,911 for regional carriers (Binter Canarias). On the other hand, the extra demand generated by the subsidy increase from 50% to 75% in June 2018 made the traffic flow in LPA airport busier and caused congestion in surface operations. It was estimated that the congestion for the peak month (December 2018) in LPA airport caused an annual fuel cost increase of about EUR 2.47 million and an increase of about 5002 tons of CO
2 emissions [
6]. Therefore, estimating the magnitude of delays caused by congestion in airports is paramount because they cause economic losses for airlines and environmental impacts, specifically in terms of increasing greenhouse gas emissions.
Delays occur when demand for runway use is greater than those available. Delays occur in the taxi-out phase mainly due to departure air space congestion. The cost of these delays is one of the greatest losses for airlines. In terms of environmental sustainability, it has to be taken into account that, according to the European Green Deal and Flightpath 2050, Europe has to become the first “climate-neutral” continent. The aviation industry is responsible of several environmental impacts. It is considered one of the main contributors to the climate change. For instance, the aviation industry contributes between 1% and 2% of human-made CO
2 emissions and other forms of emissions such as NOx. Some efforts have to be made if the goal is to achieve a more sustainable aviation sector [
2]. In this aim, it is paramount to establish emissions targets for the aviation industry. In this sense, the subsidy could be a counterproductive policy that acts against those objectives. In the case of the Canary Islands, a balanced analysis has to be implemented to evaluate mobility economic benefits against environmental global objectives. Regional aviation, in the case of archipelagos, is essential in enabling the desired level of residential mobility to incentivise economic activities such as tourism, and to provide health and education services for residents in peripheral islands. The subsidy was justified by the regional government in this way 30 years ago. However, any perverse effect of the resident subsidy has to be taken into account if environmental sustainability principles are to be considered. This might be considered as an externality caused by state aid.
In addition, several studies [
12,
13,
14] found that subsidizing routes reduces competition in the air market and produces higher costs for regional air carriers. The price discounts for residents serve as a direct revenue for regional air carriers and simultaneously mean that non-resident passengers can drop out of the regional air market. In other words, price discount is directly transferred to the airlines, increasing their monopoly power in the air market [
12,
14]. Nowadays, Binter Canarias is the air carrier that operates all interisland routes in the Canary Islands under public service obligations (PSOs). In 2021, they moved more than 2 million interisland passengers and exerted a monopoly in the regional air market [
15]. Binter showed good resilience during the COVID-19 pandemic because of its low dependence on tourism. There are two regional hub airports in the Canary Islands, Gran Canaria and Tenerife Norte. In 2019, these two airports handled around 60% of the total ATM verified by the Canary Island airport network [
15]. The price discount for Canary Island residents given by the Spanish government (75%) created an incentive within the Canary Island air market to offer new routes and increase the frequency of flights. Hence, the PSOs regime generates extra demand for flights despite the alternatives such as sea routes between the islands. Finally, one of the main consequences of the implementation of the PSO routes in the Canary Islands is that the airport capacities of the two Canary Island hub airports are being used more intensively than before [
13].
In general terms, this study examines the impact of aviation subsidies on the available capacities of the two main regional airport hubs of the Canary Island airport network and the associated environmental and economic impacts. More specifically, we analyse the impact of aviation subsidies on taxiing operations for both Gran Canaria (LPA) and Tenerife North (TFN) airports. Those two airports comprise the main regional aviation infrastructure in the archipelago and the use of their available capacity acts as a bottleneck for the regional air traffic network. The structure of this paper is as follows.
Section 2 describes the importance of the airport network in the Canary Islands and describes the methodology of the current study. Here, as we have seen above, two airports are featured from the Canary Islands regional airport network: Las Palmas and Tenerife North.
Section 3 estimates, analyses, and discusses the impact of such subsidies on these two airports by calculating the taxiing delay caused by congestion in its ground operations. The airport delay has several implications in terms of economic and environmental issues. Thus, this section calculates the economic and environmental impact of delays in ground operations on the regional air network. Finally,
Section 4 highlights the main findings of the study.
3. Estimations and Results
The subsidy applied to travel between the islands, and from the Canary Islands to mainland Spain, now represents about 75% of market price. The subsidy increased from 50% to 75% in June 2018. From
Table 1, in 2018, traffic flow increased by about 34% for both the regional hub airports compared with 2016. This increase was not only due to the subsidy. However, after this increase in subsidy, Binter airlines start developing an aggressive expansion strategy. As is apparent from
Table 2, news routes and frequency structures were established, generating new demand. All these routes have an operation base in the two regional hub airports (LAP and TFN). As a consequence, congestion may appear, as a perverse effect, at those two airports. Delays at airports depend on several factors, the main factors include the weather conditions and the traffic congestion in terminal areas. Aircraft taxiing time is associated with aircraft ground operations in the terminal area before take-off and after landing. This time depends on several factors, one of them is the available airport capacity, specifically the number of runways; this, in turn, depends on the aircraft mix using the airport, among other factors. Congestion of aircraft during taxiing is a common occurrence in airports. Hence, when airport congestion occurs, the taxiing phase becomes a key issue. Most research about the taxiing phase is based on the simulations model and queuing theory [
6,
9,
10,
16,
17,
20]. The main objective of such research involves simulating a taxiing model in order to improve taxiing time operations and to avoid delays at airports. In [
8], authors estimated the annual economic benefit of simulating reduction in taxiing time.
Therefore, it must be pointed out that the emissions and fuel costs estimated for those two airports in this study, during the taxiing phase, cannot be considered as additional emissions and fuel costs due to the subsidy increase. The aim was to show the worst congestion situation at the two busiest airports in a peak month of the year. However, to make a comparison between two situations before and after the subsidy increase, a sensitivity analysis was performed. The model was estimated with the parameters for the year 2017. This made it possible to verify changes in the estimated parameters before and after the increase in the allowance. Moreover, the objective was not to compare emissions and fuel costs before and after the subsidy increase; the main objective was to simulate a peak situation for the busiest airports in the Canaria airport network after the subsidy increase, using real data. Therefore, the ground delay model was implemented for a peak month, which was established by inspecting the flow data for the last three years at LPA and TFN airports. December was the peak month for those three years. Thus, the model was implemented in December for 2018, just six months after the subsidy increase, and for 2017. The results were estimated in a context of no conflicts between aircraft categories. The annual results for the two airports and for the two years of the study are presented in
Table 3 and
Table 4.
3.1. Waiting Time before Take-off
Different aircraft categories interact at the airport during landing and take-off operations and compete for airport capacity use. Thus, the mix of aircraft is crucial in optimizing capacity and allowing air services to be adequately controlled [
6,
17]. The disturbance between aircraft was evaluated by employing the model of landing intervals (see above) considering two aircraft categories (i.e., ATRs and B737/A320 aircraft families) for LPA and TFN airports. The LPA matrix of minimum intervals was estimated using an average mix of aircraft by 36.8% for ATRs and 63.2% for B737/A320 families. TFN airport manages mainly interisland traffic and the matrix used has an average aircraft mix of 69.2% for ATRs and 30.8% for B737/A320 families. The length of the common approach path considered was about 6 nautical miles, with a minimum separation of 3 nautical miles. The approach speed for ATRs was 130 knots, and for B737/A320 families this was about 160 knots [
6]. The complete matrices, M, and the ultimate capacity, C, computed for LPA and TFN airports, respectively, were as follows:
The average peak hour operations for LPA and TFN airports in December 2018 were about 53 and 38 operations per hour, respectively, including landing and taking off [
21]. The model estimated around 26 arrivals/h for LPA and 21 arrivals/h for TFN airport. Those values are just half the hourly saturation capacity for both airports. In other words, if we consider landing and taking off conjointly, then we approach the maximum saturation level in December 2018. Those values are very near the hourly saturation capacity of both airports. This means that the available capacity of those airports was reduced; therefore, taxiing delays could occur. Formula (5) gives us the weighted mean service time for the airport. LPA verifies a weighted mean of the landing time of 138 s, for TFN this value is 168 s. As long as an aircraft landing runway remains occupied, aircraft cannot take off. Thus, those times can be approximated as the waiting time on the head of the runway before take-off.
3.2. Taxiing Time in Route
With respect to the taxiing time of a route, certain aspects must be clarified. ATR aircraft very often have “power-back unassisted” technology, in contrast to the B737/A320 aircraft families. It will be assumed that ATRs take 31.89 s on each power-back, and on 30% of occasions, ATR aircraft perform power-backs before taxiing, while B737/A320 aircraft families take 205.83 s and perform push-back on about 50% [
11]. With respect to other ground operations for taxiing, both ATRs and B737/A320 aircraft are restricted to a maximum speed of 20 m/s [
11]. The estimation of taxiing time was performed by taking the distances as a reference, with respect to the farthest parking stand from the runway, for the two categories of aircraft and both airports. In LPA airport, the ATRs’ farthest stand is about 1200 m from the runway. For the B737/A320 family of aircrafts, the farthest stand is around 2375 m from the runway. At TFN airport, those distances for each kind of aircraft are 425 m for ATRs and 755 m for B737/A320 aircrafts [
21].
The configuration of the taxiing route at both airports implies the existence of a common route where disturbance between aircraft might appear. However, if a natural segregate subsystem to separate the taxiing of ATRs from the B737/A320 aircraft is applied, then potential interference between taxiing aircraft is removed [
11]. Hence, to estimate taxiing time of a route for both aircraft families, the “no disturbances” scenario was considered for both airports. In this case, the taxiing time of a route only depends on the distance from the spot and aircraft speed taxiing. The overestimation that could result from considering the farthest parking stand could compensate the hypothesis of the “no disturbances” scenario. In other words, the farthest parking stand was selected considering the worst-case scenario for compensating an aircraft’s common route without conflict effects. Therefore, the taxi time of a route with the previously viewed dates above, for each kind of aircraft, and for LPA and TFN airports, respectively, would be:
According to data published in [
19], the fuel consumption for taxiing an ATR 72-600 aircraft is about 6 kg/min. For B737/A320 aircraft, the fuel consumption for taxiing is approximately 13.6 Kg/min [
22]. The stoichiometries relationship of 3.15 kg of CO
2 per kg of fuel burnt allowed us to estimate the volume of CO
2 emissions [
23]. Additionally, the fuel price published in [
24], for December 2018, was 1.81 EUR/kg (using a conversion factor of 1 US dollars = EUR 0.84 and a kerosene density of 817 kg/m
3). Using those values, it is possible to estimate the values for the waiting time before take-off, taxiing time, fuel cost, and CO
2 emissions for both airports and for the periods of this study. These results are shown in
Table 4 and
Table 5.
These values have been estimated per air traffic movement (ATM) through considering those values as an average and multiplying them per annual ATM for each airport; thus, the annual fuel cost and CO
2 emissions for each of the aircraft categories may be obtained.
Table 4 shows those estimations. As is apparent from
Table 4, there is a potential economic and environmental impact associated with the implementation of the subsidy increase for resident interisland travel and for travel from the Canary Islands to the mainland. There is also a negative effect on the runway for both airports due to the capacity constraints. In addition, the subsidy given by the government must be quantified and its opportunity cost must be estimated. In terms of PSO routes, with the dates from
Table 2 and
Table 3, the main PSO route between LPA and TFN airports verified an annual emissions volume of about 1200 tons: 30.8% and 36.3% of the total annual emissions for LPA and TFN airports, respectively. In order to perform a sensitivity analysis,
Table 4 was reproduced for 2017. Considering all the parameters for that year,
Table 5 shows the results. The LPA matrix of minimum intervals was estimated using an average mix of aircraft by 31.3% for ATRs and 68.7% for B737/A320 families. The TFN airport manages mainly interisland traffic and the matrix used has an average aircraft mix of 62% for ATRs and 38% for B737/A320 families. As can be seen, in 2018, the percentage of flights between islands with ATR technology increased with respect to the short-run aircraft for both airports. In contrast, the proportion of B737/A320 aircraft families also decreased for the two airports.
As can be seen in
Table 5, for 2017, the estimated amounts are lower than those in 2018. This means that, when there is an increase in the subsidy for residents of the Canary Islands, airports experience a substantial change in fuel cost and annual emissions for the two categories of aircraft considered in the study. It should be noted that, in 2018, demand for interisland flights increased substantially. For example, the increase in ATMs for the ATR category at both airports increased by 26.6% for LPA and by 23.05% for TFN. The airlines also increased their offer, encouraged by the increase in the subsidy. There are therefore effects on both sides of the market.
3.3. Discussion
Congestion is viewed as the most immediate problem facing aviation in Europe. It has been estimated that delays in the air and on the ground have huge financial costs for the aviation industry. In addition, the growing concern over global warming and greenhouse gas emissions means that the pollution from aircraft is under increased scrutiny. As was pointed out in [
7], when one considers the consequences of subsidies in combination with the growing capacity of aviation systems and climate-change-related impacts, the subsidy mechanism does not seem to be an adequate measure for the aviation sector. For instance, one historical tendency in the aviation sector is to take the view that the economic benefits of the sector outweigh its costs in terms of contamination and congestion. However, significant empirical evidence shows that this is not true [
2,
3,
8]. Therefore, internalizing such costs is the first step towards a change in the current scenario.
On the one hand, in economic terms and in the absence of technological change, pollution and congestion can be internalized through several mechanisms (for instance, kerosene tax, emissions trading systems). Those mechanisms also could generate an incentive for technological change. On the other hand, such mitigation policies could make air transport more expensive and, in the near future, less available. The consequences for the tourism industry are clear. The increased share of air transport in international and domestic trips could compromise the growth of a labour-intensive sector such as the tourism industry.
Therefore, policymakers have to estimate tourists’ willingness to pay (WTP) for mitigating climate change before actuating on the demand side. The authors of [
25] found that the WTP for airline passengers depends on their personal income and the number of flights. The WPT for the carbon offset was around 39 US dollars. This means there is room to implement carbon-offset policies. This demand-side policy is related to supply-side policies. If ticket prices are increased, with airlines passing the carbon cost to their passengers, then demand could be affected and cause the supply to decrease. This could incentivise airlines to invest in technological development, for instance, through fleet renewal with investments in more fuel-efficient jet engines. One further suggestion, when they become commercially available, is the use of hybrid–electric aircraft or hydrogen aircraft. In [
26], the authors point out that there are a lot of challenges to be overcome before this kind of technology becomes commercially available. However, they believe that such technology could deliver substantial benefits to small-scale regional aircraft.
One way to optimize airport capacity could be to change taxiing operations. The conflict between aircraft categories was noted as a relevant factor for the management of airport capacity and for improvements to taxi operations. The authors of [
11] found that using the airport-within-airport procedure in LPA airport could produce economic and environmental benefits in terms of saving fuel costs and reducing emissions. This approach can reduce the interference between aircraft categories, and taxiing time was shown to decrease by about 76% in the case of the ATR category.
4. Conclusions
On the one hand, this study has shown that the implementation of a subsidy increase for Canary Island residents has produced substantial economic and environmental impacts. If we compare the data obtained in this study for the year 2017, just before the increase in the mobility subsidy for residents of the Canary Islands, and the data for the year 2018, we can conclude that there has been a significant increase in the activities of the two airports studied. From the airline’s point of view, this subsidy causes an increase in fuel costs and carbon dioxide. The cost of fuel and CO
2 emissions grew by approximately EUR 2.8 million and 3.097 tons, respectively. These results are consistent with those found in empirical evidence [
9,
10,
11]. In addition, it must be pointed out that this subsidy produces an increase in ground operation time and, therefore, an increase in runway occupancy. On the other hand, we have to keep in mind that those impacts are underestimated because the disturbance in taxiing route operations between aircraft was not considered; consequently, the waiting time before taking off would probably be higher.
Subsidizing air transport and PSOs implementation has generated extra demand for flight in the Canary Island’ interisland air traffic market. Furthermore, it has to be taken into account that the most of those subsidies go to those Canary Island inhabitants who have a higher-than-average income and fly frequently. Therefore, the policy results in regressive income redistribution. In that sense, a possible solution could establish a discount system for the airfare related to the income level of the passenger [
27]. This also could be a way to charge according to the willingness to pay for the emissions impact of current aircraft technologies. This new discount system could evaluate the inclusion of the non-resident tourists.
On the other hand, subsidies can attract new operators to the air market; however, existent air companies often implement an aggressive pricing strategy to make it difficult for new operators to start up, thus driving them out from the market. The final outcomes include increased market concentration and monopoly power, which have been shown through empirical evidence [
12,
13,
14]. Binter Canaria S.L., an air operator in the Canary Islands, began to develop through an aggressive expansion strategy after the subsidy increased to 75%. The main strategies have been to develop new routes and to increase flight frequency to attain the subsidies.
This study shows the importance of evaluating the impacts of new economic regulations and their potential to distort the market mechanism. The aviation sector has been excluded from carbon policies, which leads to, at least, a kind of cross subsidy (negative tax). The surface transport sector perhaps pays for their environmental impact more than they should. The argument has always been that mitigation measures might be more expensive compared with other sectors [
27]; subsidizing pricing to incentivise resident mobility could produce perverse effects in terms of increased emissions and airport congestion. However, no one of the aviation industry blames public administration for the inefficiency of their economic regulations—the eternal double measuring stick. In this sense, these environmental impacts caused by resident subsidies must be balanced with the social and economic benefits that each regional inhabitant derives from the subsidy in terms of the improvement in their mobility. This is a necessary extension of this research.
In a complementary way, as it was established in [
26], a natural extension of this work would be to implement a cost/benefit analysis for the introduction of hybrid–electric aircraft for regional mobility in the Canary Islands. Analysing whether this kind of technology could decrease the perverse effects of the subsidy, which is valuable in incentivising increased air mobility among Canary Island inhabitants. However, this advanced technology is slow to become commercially available and, in the meantime, any regulation to compensate for the perverse effects of the subsidies is needed to limit the environmental impacts. Additionally, further work needs to determine and quantify the need for additional runway capacity in the airports. This would allow us to determine how the increase in the subsidy affects congestion and thus the quality of airport services. Finally, a more technical analysis might explore the implementation of similar procedures considering interferences between aircraft categories in taxiing route operations.