ABSTRACT
The air transport system is currently in a rapid development stage, accurate forecasting emissions is critical for identifying and mitigating its environmental impact. Accurate forecasting depends not only on temporal features from historical air traffic data but also on the influence of spatial factors. This paper proposes a deep learning-based forecasting framework for en route airspace emissions. It combines three-channel networks: a graph convolutional network, a gated recurrent unit, and the attention mechanism, in order to extract the spatial, temporal, and global temporal dynamics trends, respectively. The model is evaluated with real-world datasets, and the experimental results outperform existing state-of-the-art benchmarks on different evaluation metrics and forecasting horizons in complex airspace networks. Our method provides an alternative for forecasting air traffic emissions using publicly available traffic flow data. Furthermore, we propose an extension index that can be taken as an early warning indicator for stakeholders to monitor air traffic emissions.
ABSTRACT
The development of CAAC began in the early days of 1949. From a comparatively less popular means of transport to the world's second largest by volume, this means of transport has undergone major and minor changes in the last 70 years. It is not known whether there are significant laws in the process of development. For this reason, we analyze the statistical indicators of the development of civil aviation transport and select representative indicators, namely, the total turnover of transport, the number of routes, the number of aircraft, the number of transport aircraft, and the number of domestic city connections. At the same time, the life cycle theory is introduced, and the typical growth curve model is used to fit the data. It is found that the evolution life cycle of civil aviation in China can be divided into three stages: the first life cycle stage from 1950 to 1981, the second from 1982 to 2003, and the third from 2004 to 2017. Each life cycle follows the growth characteristics of occurrence, growth and maturity, and each life cycle has a time range of approximately 30 years. At present, China's civil aviation industry is in the period of rapid growth in the third life cycle. This industry is expected to reach maturity in approximately 2026 and then to begin to grow slowly. Relevant departments can adopt corresponding development strategies to guide the smooth development of civil aviation in accordance with the growth law of the development and evolution life cycle of civil aviation in China.
