Although the concept of sustainable development has made certain achievements in many fields, airport sustainability (AS) has not yet formed a unified and comprehensive theory and evaluation method. According to the connotation of sustainable development, this paper proposes the definition of airport sustainability by considering China’s national conditions and airport characteristics. Secondly, this paper identifies four AS dimensions of economy, environment, society, and operation and selects and screens evaluation indicators for each dimension. Thirdly, a synthetic evaluation index model of AS is constructed based on the benefit of the doubt (BoD) model, and the process of evaluation method is planned according to a synthetic evaluation method. Finally, Guangzhou Baiyun International Airport (CAN) is selected as a case study to evaluate the AS from 2008 to 2017, and the influencing factors of AS are discussed to predict AS in 2018. The evaluation and prediction results are consistent with the actual operational characteristics of CAN.

Under the background of economic globalization, the air transport industry developed rapidly. It turns out that the city-to-city network has not been able to adapt well to the development of the society, and the hub-and-spoke network came into being. The hub-and-spoke network demonstrates the advantages of reducing the operating costs of airlines to keep a competitive advantage, and by maintaining the interests of airlines in the rapidly developing context. However, during the operation of aircrafts, they consume fuel and spew a great deal of harmful pollutants into the air, which has an adverse impact on the living environment. This paper explores the impact and external costs associated with hub-and-spoke network in air transport from an environmental perspective. With some mathematical models, we construct a hub-and-spoke network and take a quantitative study on the environmental impact of air transport. For calculating pollutant emissions, meteorological conditions were considered to revise the pollutant emission factors of the Engine Emissions Data Base (EEDB) published by International Civil Aviation Organization (ICAO). The environmental external costs measurement model is employed to calculate the externality of toxic gas and greenhouse gas (GHG). In order to make the study more convincing, two alternative networks are computed: hub-and-spoke network and city-to-city network. It is found that the hub-and-spoke network is associated with poorer environmental impact and environmental external costs because of the different network characteristics and the scale of the fleets. Therefore, under the general trend of green aviation, the environmental impact and environmental external costs associated with hub-and-spoke network in air transport provides a certain reference for airlines’ strategic decision-making.

Requirements of digitization, intellectualization, and integration for the programming and management of air transportation have been recommended as information technology booms. A variety of single ground movement optimization problems have been discussed with few taking the impact of other segments into account. In this research, bilevel programming is applied to simultaneously consider three problems including the gate assignment, taxi path scheduling, and pushback time delay. For evaluating the strategy of gate assignment and measuring its connection with taxiing comprehensively, an auxiliary variable and the matching degree of gate and aircraft are introduced. In addition, an algorithm incorporating the genetic algorithm and routing algorithm is designed to obtain a solution with satisfactory performance in both taxi time and conflict risk. The scheme obtained also assigns aircraft to gates more appropriately and maintains the characteristics of environmental protection as well as high efficiency, showing considerable reliability in practice.

The increasing demand for environmentally friendly and passenger-favored flight operation requires a systematic scheme of sustainable trajectory optimization for the aircraft cruise. This paper achieves it by proposing an innovative performance framework based on the comprehensive benefit to the society considering both economic and noneconomic ones, following which the sustainable trajectory optimization problem is modeled by discretization. A method combining forward recurrence and memoization operation, called memoization dynamic programming, is developed to solve the model with computational efficiency. Working with real-world operational data of a typical flight route, we demonstrate the effectiveness of the proposed scheme at different levels and explore the difference in its performance due to meteorological conditions, aircraft type, and time horizon. The scheme is proved to perform robustly in comprehensive performance with a stable benefit rate of about 8% through sensitivity analysis, by which we find that it is relatively better for the flights cruising on business route with a load factor of 85%. Tradeoff results suggest that the systematic consideration of both the economic and noneconomic performance contributes to improved integrated sustainability. In particular, the optimal comprehensive performance at a monthly level can be obtained when accepting an additional $26,500 economic cost.

With the air transport industry developing dramatically, the problem of flight congestion in the terminal area (TMA) has been aggravated. Particularly for arrival aircraft, the extraholding and delay not only increase the workload of air traffic controllers and aircrew but also reduce the operational efficiency. To struggle with this issue, it is crucial to study how to improve the operational efficiency of arrival aircraft. Under the background of the rapid promotion of Point Merge (PM) procedure program in the busy TMAs in the world, this paper firstly combines the optimization of PM procedure and arrival aircraft sequencing, aiming to maximize the operational benefits of arrival aircraft in TMA. Firstly, the framework of the PM procedure is set up to replace the traditional approach route known as Standard Instrument Arrival (STAR). After that, the PM procedure optimization model is established to provide a better approach route for each arrival aircraft. Then for a flow of arrival traffic, an aircraft sequencing model is established to readjust the landing sequence of arrival aircraft, thus further improving the operational benefits of arrival aircraft. Finally, taking the TMA of Shanghai Hongqiao International Airport as the case, we compare the impact of different flight procedures and different landing sequences on the operational benefits of arrival aircraft. The experimental results show that the application of the PM procedure optimization model and sequencing model can effectively improve the operational benefits on the premise of ensuring safety, thus realizing the safe and orderly approach in TMA.

As explainable artificial intelligence (XAI) has grown in popularity, it has become possible to more clearly explain the functional correspondence between airspace and traffic flow, which can alleviate the contradiction between the continuously increasing traffic demand in the terminal area and the limited airspace capacity; this paper studies the three-dimensional sectorization in the terminal area based on the airspace function. First, trajectory clustering is adopted to classify the functions of air traffic flows. Then, a functional sectorization framework is proposed to enable different airspace sectors with varied functions, where specifically the functional consistency objective between the airspace sector and the traversed air traffic flows is proposed. Third, a corresponding efficient algorithm is designed to generate functional sectors with an accurate scope that can well separate different traffic flows. Finally, the proposed method is evaluated by the actual operation datasets in the Shanghai terminal area. The results show that the method proposed in this paper can not only generate three-dimensional sectors with specific functions according to the prevailing traffic flow in the complex terminal area, which is conducive to the construction of controllers’ situational awareness, but also can reduce potential conflicts and traffic density variance, increasing average sector flight time a lot.