Airport traffic complexity and environment efficiency metrics for evaluation of ATM measures

For a given (current or planned) traffic demand, different air traffic management measures could result in different airport traffic complexity and efficiency. This paper presents the research on the relationship between airport traffic complexity and time and environmental efficiency for different air traffic control (ATC) tactics applied to the given or planned airport layout. Emphasis is placed on the evaluation of airport traffic complexity, aircraft fuel consumption, gas emissions and time efficiency for different ATC tactics and/or airport airfield layouts. For busy airports during peak hours, arrival queuing delays, taxi-in, taxi-out times and departure queuing delays increase, which induces additional unnecessary fuel consumption, gas emission and time inefficiency. In order to find a tool which could indicate potential delay generators, a measure of airport traffic complexity – called Dynamic Complexity is proposed. Experiments were performed for airports with different airfield layouts, for different traffic demands and ATC applied tactics using SIMMOD simulation model. Traffic situations were analyzed and delays were measured. The values of airport traffic complexity, fuel consumption and gas emissions were also determined. A comparative analysis of the results show: first, the proposed airport traffic complexity metric quite satisfactorily reflects the influence of traffic characteristics upon the environmental state of the system, and second, different ATM strategic and tactical measures (airport airfield infrastructure development and applied ATC tactics) could significantly reduce traffic complexity and increase time and environmental efficiency at the airport.     

Control-based optimization approach for aircraft scheduling in a terminal area with alternative arrival routes

This paper presents an optimization approach for dynamically scheduling aircraft operations and supporting air traffic controllers in both determining and implementing operationally feasible landing and departure times at an airport. The mixed integer linear programming model proposed incorporates air traffic control infrastructure in terms of route network, introduces the concept of alternative approach routes and is designed to generate an output that can be converted into effective advisories for executable flight commands. It shows reasonable computational times for obtaining the optimal solution and delay reductions of up to 35% with practical size instances from Sao Paulo/Guarulhos International Airport.     

Analyzing tactical control strategies for aircraft arrivals at an airport using a queuing model

This paper proposes to analyze control strategies for arrival air traffic at an airport using a classical queuing model. The parameters of our model are estimated by means of a data-driven analysis of two years of radar tracks and flight plans for arrival flights at Tokyo International Airport from 2016 to 2017. Our results show that increasing the capacity with one or two more aircraft in the airspace up to 60 NM around the airport significantly mitigates arrival delays, even when assuming future, increased arrival traffic volumes. The outcomes of this study provide insights into the effectiveness of arrival control strategies and are seen as a means to recommend scenarios to be further analyzed with human-in-the-loop simulations.     

Local emission charges – A new economic instrument at German airports

In January 2008, charges were introduced at selected German airports aimed at reducing local emissions of nitrogen oxide and hydrocarbon. The charge is aimed at setting economic incentives to accelerate the introduction and foster the use of environmentally friendly engine technology and is designed to be revenue-neutral in the sense that it does not increase the airports' overall revenues from air traffic. To achieve this, the general landing fees need to be decreased by the amount of the emission charge. The introduction of this charge will have economic impacts on airlines and may have an impact on airline competition in the German air transport market. Case studies based on empirical data are presented for selected German airports. The results indicate that airline's finances will be affected differently by the emission charge, depending on the engines employed and on the aircraft population of the airport considered.     

CO2 emissions associated with hubbing activities in air transport: an international comparison

Hubbing is an important operational practice in air transport. Many studies have been conducted to examine the benefits and impacts of hubbing from an economic perspective. However, its impact on CO₂ emissions, especially across different air spaces, is not well understood. This paper explores the impact of hubbing activities in air transport from an environmental perspective. With a detailed methodology and data from the Greek and Hong Kong/Sanya flight information regions (FIRs), three levels of CO₂ emissions are estimated: airport-based, airspace-based and flight-based. After contrasting the CO₂ emission efficiencies of Athens International Airport (AIA) and the Hong Kong International Airport (HKIA), aircraft type and flight distance are examined to explain their emission efficiency differences. It is found that HKIA is associated with poorer CO₂ emission efficiency at the airport and airspace levels because of the larger aircraft and longer flight distance. However, when CO₂ emission efficiency at the flight level is considered, HKIA, with a higher passenger load factor, performs better. Major international hub airports should implement additional environmental measures to minimize the impact of hubbing activities on CO₂ emissions at the airport and airspace levels.     

Modeling different penetration rates of eco-driving in urban areas: Impacts on traffic flow and emissions

Climate change and air quality are two main environmental challenges in metropolitan areas. As road transportation is one of the main contributors, public administrations are facing these problems with a number of complementary policy measures: shift to cleaner modes, new fuels and vehicle technologies, demand management, and the use of information and communication technologies (ICT) applied to transportation. Eco-driving is one of the measures that present large fuel savings at individual level. Although these savings are well documented in the literature, few studies focus on how eco-drivers driving patterns affect the surrounding vehicles and the traffic in general, and more particularly what would be the impact when the number of eco-drivers grows. Using a traffic microsimulation tool, four models in urban context have been built, corresponding to the different types of urban roads. Both the base-case and the parameters setting to simulate eco-driving have been calibrated with real data collected through floating vehicles performing the trips with normal and eco behaviors. In total, 72 scenarios were simulated, varying the type of road, traffic demand, and the percentage of eco-drivers. Then, the CO₂ and NO_x emissions have been estimated through a microscopic emission model. The results show that in scenarios with low or medium demand levels and increasing number of eco-drivers, the effects are positive in terms of emissions. On the other side, with high percentage of eco-drivers and high traffic demand, the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.     

Dynamic management of aircraft stand allocation

This paper aimed to present an original approach for solving the aircraft stand allocation (SA) problem dynamically when due to operational disturbances, the planned allocation cannot be accomplished. The proposed Multiple-criteria Dynamic Stand Allocation (MDSA) method uses fuzzy logic to support decision-making under uncertainty. The MDSA method provides effective solutions in a short time, necessary for traffic management in case of delays, emergency, and untypical cases. It considers partially conflicting points of view of different airport users (airport managers, air traffic controllers, airlines, handling agents, and passengers) and may significantly support managers on the SA problem. The approach proposed can also be used for creating an initial SA plan for a considerable number of aircraft.     

The impact of airport capacity constraints on future growth in the US air transportation system

This paper simulates airline strategic decision making and its impact on passenger demand, flight delays and aircraft emissions. Passenger flows, aircraft operations, flight delays and aircraft emissions are simulated for 22 airports in the US, under three airport capacity scenarios. The simulation results indicate that most system-wide implications for operations and environmental impact seem to be manageable, but local impacts at congested hub airports may be significant. The response of the air transportation system to avoid airports with high delays could significantly impact passenger demand and air traffic for these and directly dependent airports. The simulations also suggest that frequency competition effects could maintain flight frequencies at high levels, preventing a significant shift toward larger aircraft, which would otherwise reduce the impact of the capacity constraints.     

A global model for estimating the block time of commercial passenger aircraft

This paper uses a two-stage statistical model to estimate the block time of commercial passenger aircraft. The model considers many of the factors contributing to airport congestion and provides a basis for future development of multivariate statistical models of the flight operation process. The model is tested using 2 million US domestic flights by six airlines in 2004. Model analysis provided insight regarding the relative impact of weather conditions and airport utilization on block time. In particular, population, arrival time, airport utilization, ice, and the interaction of poor weather conditions and traffic were found to be significant predictors of block time.     

Analysis of the recent evolution of commercial air traffic CO2 emissions and fleet utilization in the six largest national markets of the European Union

This paper presents the results of a study performed to analyze the evolution of commercial air traffic and CO₂ emissions in the European Union, from 2010 to 2013. Data sources are the European Commission's Eurostat Air Transport Statistics (Eurostat) and EUROCONTROL flight plans database. The changes in the fuel efficiency are analyzed and the potential reasons for those changes investigated. The evolution in the airline fleet composition during the last decade is presented as one of the reasons for the improvement in fuel efficiency, measured in burnt fuel per total Revenue Tonne Kilometre (RTK), as well as the different parameters depending on the airline business model (network carriers, low cost companies, etc.) and the aircraft type.Results show a slight reduction in the traffic, both for passengers and cargo (about −0.8%), and a more important reduction in CO₂ emissions (−4.3%), thanks to an improvement in the fuel efficiency parameter (−3.5%) for the three years period. There has been a relevant change in the fleet composition in the last ten years, with the replacement of older models for more efficient ones, and a shift to larger aircraft, particularly in the regional segment. Traffic has decreased in shorter distances (internal EU traffic), but increased in more efficient long range flights (extra-EU traffic), resulting also in an improvement of the efficiency parameter as average aircraft size and stage length increases.     

A hybrid fuzzy MCDM approach for mitigating airport congestion: A case in Ninoy Aquino International Airport

In this paper, we introduce the application of an integrated fuzzy multi-criteria decision-making (MCDM) model to mitigate airport congestion which affects the on-time performance of airlines, operational reputation of airports, and air travel experience of passengers. In a classical approach, when congestion occurs at the destination airport while the aircraft is en-route, an air traffic flow management action is prompted for implementation. In selecting the most suitable action in the event of airport congestion, the decision must reflect the multiple criteria nature of the problem as well as the uncertainty and vagueness associated with the decision-making process; thus, an integrated fuzzy MCDM is adopted. The applicability of the proposed approach is demonstrated in a case study at Ninoy Aquino International Airport. It is found that stakeholders of the commercial aviation industry favored to apply rerouting, among other actions, as this satisfies aviation safety as the most prioritized criterion.     

A systematic approach to assess the effectiveness of airport noise mitigation strategies

Regional airports are often located very close to the urban area they serve and the increasing traffic rate that many of them have experienced in the last years has produced several impacts on the communities living close to the airport area, mainly aviation noise. If not properly managed, noise impacts produced by airport operations can cut down significantly the development of airport air traffic with direct effects on the economic and territorial systems. Aeronautical noise has greatly reduced in the last decade, due to aircraft design technological improvements and more severe regulations. However, the noise reduction during a single event does not make the issue of the airport location – and then the whole noise impact – less significant. This paper proposes an assessment process to evaluate the effects of actions adopted to reduce airport noise impacts on populated areas. Both airport-related factors – such as number of take-off; day-evening-night distributions of movements; aircraft type; flying paths – and land-use characteristics have been considered and combined in a density index that synthesizes the impacts of airport noise on the territory. The assessment process has been tested on a real case, the airport of Bologna in Northern Italy. The predicted results, compared with available real data for the test case, are significant and encourage the use of the proposed assessment process as decision support system for the airport management.     

An analysis of the greenhouse gas emissions profile of airlines flying the Australian international market

International commercial flights (with the exception of flights between countries in European Union including Iceland, Norway and Liechtenstein) are currently not subject to greenhouse gas emission reduction regulation. To formulate effective and efficiency policy to manage greenhouse gas emissions from air transport, policy makers need to determine the emissions profiles of all airlines currently flying into their country or region. In this paper, we use 2012 data on airlines' aircraft characteristics, passenger load and cargo load (obtained from statistics reported by Australian Government Bureau of Infrastructure, Transport and Regional Economics) to estimate the volume and carbon efficiency on each international route flying to and from Australia. This is the first study to use actual passenger and cargo load data to determine the greenhouse gas (specifically CO₂) efficiency of airlines operating in the Australian international aviation market. Airlines' CO₂ emission profile is dependent on many factors including but not limited to the aircraft used, payload, route taken, weather conditions. Our results reveal that the airlines’ CO₂ emission profile is not only dependent on the aircraft used and the number of passengers but also the amount of cargo on each flight.     

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement.Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.     

Ramsey pricing including CO2 emission cost: An application to Spanish airports

The long-term growth in the air transport is leading to the need to expand airport infrastructure but this has serious environmental implications. Thus, there is the need to establish an alternative to the traditional airport pricing structure for landing fees, which reflects the overall costs that air transport operators impose on others. Airport pricing should provide a sound guide for future investments, and at the same time reflect whether additional facilities are needed and at what price, by taking into account all costs, including environmental costs. This paper analyses one application of Ramsey Pricing on uncongested Spanish airport, by considering the CO₂ emission costs as a valuable input.     

Investigations on the distribution of air transport traffic and CO2 emissions within the European Union

This study analyses the structure of air traffic and its distribution among the different countries in the European Union, as well as traffic with an origin or destination in non-EU countries. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The segmentation of air traffic in terms of distance permits an assessment of air transport competition with surface transport modes.The results show a clear concentration of traffic in the five larger countries (France, Germany, Italy, Spain and UK), in terms of RPKs. In terms of distance the segment between 500 and 1000 km in the EU, has more flights, passengers, RTKs and CO₂ emissions than larger distances. On the environmental side, the distribution of CO₂ emissions within the EU Member States is presented, together with fuel efficiency parameters. In general, a direct relationship between RPKs and CO₂ emissions is observed for all countries and all distance bands. Consideration is given to the uptake of alternative fuels. Segmenting CO₂ emissions per distance band and aircraft type reveals which flights contribute the most the overall EU CO₂ emissions. Finally, projections for future CO₂ emissions are estimated, according to three different air traffic growth and biofuel introduction scenarios.     

Impact of landing fees on airlines’ choice of aircraft size and service frequency in duopoly markets

A one-shot simultaneous game-theoretic model is applied in a duopoly market to investigate how airport landing fees could influence airlines’ decisions on aircraft size and service frequency. It is found that higher landing fees will force airlines to use larger aircraft and less frequency, with higher load factor for the same number of passengers. It is also found that airlines will be better off if some of the extra landing fees are returned to airlines as a bonus for airlines using larger aircraft, which consequently reduces airport congestion.     

Relevance of airport accessibility and airport competition

Airport accessibility is an important criterion for airport competition. The relevance of airport accessibility and airport competition was studied in this paper based on the panel data collected from nine large airports in Jiangsu province, China from 2005 to 2014. The results showed that the cost of expense, time and fatigue for the arrival at the airport are proposed to quantify levels of fastness, economy and amenity for the passengers to arrive at airport. The airport accessibility is significantly affected by airport passenger traffic and airline frequency. The passenger traffic can be increased by 2% with 1% increase of airport accessibility based on the analysis results of the nine large airports in Jiangsu province.     

The potential for European aviation CO2 emissions reduction through the use of larger jet aircraft

There is increasing pressure to reduce global CO₂ emissions, with aviation targeted as an industry with high future expected growth and limited potential for reduced emissions. In Europe, air transport is likely to be included in the Emissions Trading Scheme from 2012, allowing open trading with other sectors. The proposed scheme may be economically efficient but will it do much towards curbing aviation emissions? A number of papers have looked at the ETS impact on air traffic growth rates, and others have forecast the rate of likely future fuel efficiency gains. This paper examines the potential for greater fuel efficiency through the use of larger aircraft and different patterns of operation. Fuel efficiency was found to be related to aircraft size with more benefit from trading up with short/medium-haul than with long-haul aircraft. This relationship only held for long-haul aircraft if those aircraft with two main decks were removed from the sample (these types showing inherently lower fuel efficiency). Combining these findings with manufacturers' and other forecasts of average aircraft size suggests that less than 1% a year of fuel efficiency gains will be available from this source over the next 20 years.     

Urban taxis and air pollution: a case study in Harbin, China

Taxis share a high proportion of urban traffic volume and contribute a large proportion to urban air pollution. This paper addressees this context by exploring urban taxi air pollution emissions and possible reduction countermeasures. Based on a survey of Harbin taxis, we have developed different urban taxi pollution emissions models and considered taxi passenger occupancy and taxi average vacant ratio. To reduce taxi air pollution emission, this paper sets a reduction goal and puts forward three kinds of transport management policies. These are taxi market regulation, introduction of electric and Liquefied Petroleum Gas powered vehicles, and the introduction of dial-a-ride services. The paper provides recommendations for managing urban taxi development using these strategies.