The rapid growth in air traffic has resulted in increased emission and noise levels in terminal areas, which brings negative environmental impact to surrounding areas. This study aims to optimize terminal area operations by taking into account environmental constraints pertaining to emission and noise. A multi-objective terminal area resource allocation problem is formulated by employing the arrival fix allocation (AFA) problem, while minimizing aircraft holding time, emission, and noise. The NSGA-II algorithm is employed to find the optimal assignment of terminal fixes with given demand input and environmental considerations, by incorporating the continuous descent approach (CDA). A case study of the Shanghai terminal area yields the following results: (1) Compared with existing arrival fix locations and the first-come-first-serve (FCFS) strategy, the AFA reduces emissions by 19.6%, and the areas impacted by noise by 16.4%. AFA and CDA combined reduce the emissions by 28% and noise by 38.1%; (2) Flight delays caused by the imbalance of demand and supply can be reduced by 72% (AFA) and 81% (AFA and CDA) respectively, compared with the FCFS strategy. The study demonstrates the feasibility of the proposed optimization framework to reduce the environmental impact in terminal areas while improving the operational efficiency, as well as its potential to underpin sustainable air traffic management.
To cope with the environmental impact of aviation and pollution problems in the future, airlines need to assess environmental impacts and offer countermeasures in advance. In order to measure the influence of environment on the airlines’ operational costs, this paper establishes an aircraft green direct operating cost (GDOC) model to quantify adverse environmental effects, such as air pollution and greenhouse effects, into the direct operating cost (DOC). Furthermore, fuel consumption, flight time, and distance in the cruising stage account for about 80% of the entire flight mission, and optimizing cruise flight performance can contribute greatly to reduce GDOC. Therefore, this paper sets up an optimal control model to minimize GDOC, establishes a discrete time dynamic system for optimizing the cruise altitude and speed profiles, and searches the optimal results by using dynamic programming. Besides, as meteorological conditions affect aircraft aerodynamics, fuel flow rate, contrail formation, and so on, this paper analyzes meteorological uncertainty by using historic meteorological data. Finally, a route is selected as an example, and the rationality of the optimal results is proven by comparing GDOC with DOC. The results and discussion of the numerical test also show that environmental effects on aircraft operation can be reduced significantly by adopting GDOC as the optimization objective, especially the contrail cost, and the step-climb cruise mode can further reduce GDOC effectively.
For the current development of green civil aviation, this study aims to optimize the green four-dimensional (4D) trajectory of commercial flight by taking into account conventional cost and environmental cost. Some fundamental models, efficient processing methodologies, and conventional objectives are proposed to construct the framework of trajectory optimization. Based on the environmental cost including greenhouse gas cost and harmful gas cost, green objective functions are presented. The A * algorithm and the trapezoidal collocation method are employed to optimize the lateral path and vertical profile for 4D optimization trajectory generation. A case study for the A320 from Barcelona Airport to Frankfurt Airport yields the results that the optimal costs can be obtained under different objectives and the total cost can be more optimized by adjusting the weights of environmental cost and conventional cost. The study builds an aided tool for 4D trajectory optimization and demonstrates that environmental factors and conventional factors should be taken into comprehensive consideration when constructing the flight trajectory in the future, as well as it can underpin the green and sustainable development of the air transport industry.
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