Air transport and economic growth: a review of the impact mechanism and causal relationships

ABSTRACT

The impacts of air transport on the economy arise both directly, via activity in the aviation sector; and indirectly, via increased spending and wider economic benefits associated with improved access to resources, markets, technology and economic mass. Economic activity, in turn, supports and generates demand for air transport. Despite its potential importance, the reciprocal nature of the causal relationship between air transport and economic performance has remained somewhat understudied. This paper provides a synthesis review of the channels the aviation sector interacts with regional economy. The review focuses on quantitative studies that contribute to the state-of-the-art understandings of the causality. We find that the reciprocal causal relationship is more likely to prevail in less developed economies. For more developed economies, only one direction of the causality is recognised, which runs from air transport to economic growth. Especially substantial is the effect of airline enplanement on service-related employment. The reverse direction of the relationship is, however, not as significant as believed in a causal sense within the developed world. Therefore, cautions need to be taken when applying income elasticities (such as the elasticity of air passenger demand with respect to GDP) in air travel demand forecasting, which implicitly assumes that economic growth causally leads to air traffic increment. Based on the fundamental links between air transport and economic growth, some typical imperfections and inefficiencies in aviation markets are discussed and promising avenues for future research are proposed.     

Economic factors affecting the registration of lower CO2 emitting aircraft in Europe

We examine the various forces influencing the development and uptake of environmentally beneficial technical changes, focusing on airline technology. Within this context, we consider not only the nature of competition within the final market in which aircraft, an intermediate product, are sold, but also that of the product market itself, the commercial airline industry. The reasons for the gradual reduction in CO₂ per seat per aircraft movement in aircraft design are examined in terms of the real costs of aviation fuel, changes in the nature of the supply industry, the movement towards carbon cap-trade policies, and endogenous technical progress in the technology of the industry. The latter being taken as an empirical proxy for the role market forms play in influencing the fuel efficiency of the types of aircraft used. The results support the existence of these latter forces on the demand for aircraft types, allowing for other influences that affect aircraft technology.     

Impact of transition between signal timing plans in social cost based in delay,fuel consumption and air emissions

Significant effects of traffic congestion include the cost associated with extra travel time, fuel consumption, and gas emissions. This paper develops a mathematical function to quantify the monetary impact of transition designs between signal timing plans on users and the environment. This function offers an approach to reduce problems such as excessive travel time, pollution emissions and fuel consumption. The proposed social cost function is evaluated for various transition plans to assess the impact of the number of steps required to adjust signal timing. The relationships between delay, fuel consumption and gas emissions and the number of steps needed to achieve the transition are also analysed.     

Analysis of air traffic control operational impact on aircraft vertical profiles supported by machine learning

The Air Traffic Management system is under a paradigm shift led by NextGen and SESAR. The new trajectory-based Concept of Operations is supported by performance-based trajectory predictors as major enablers. Currently, the performance of ground-based trajectory predictors is affected by diverse factors such as weather, lack of integration of operational information or aircraft performance uncertainty.Trajectory predictors could be enhanced by learning from historical data. Nowadays, data from the Air Traffic Management system may be exploited to understand to what extent Air Traffic Control actions impact on the vertical profile of flight trajectories.This paper analyses the impact of diverse operational factors on the vertical profile of flight trajectories. Firstly, Multilevel Linear Models are adopted to conduct a prior identification of these factors. Then, the information is exploited by trajectory predictors, where two types are used: point-mass trajectory predictors enhanced by learning the thrust law depending on those factors; and trajectory predictors based on Artificial Neural Networks.Air Traffic Control vertical operational procedures do not constitute a main factor impacting on the vertical profile of flight trajectories, once the top of descent is established. Additionally, airspace flows and the flight level at the trajectory top of descent are relevant features to be considered when learning from historical data, enhancing the overall performance of the trajectory predictors for the descent phase.     

基于非定常流场的离心压气机气动噪声分析

对150mm直径车用涡轮增压器离心压气机的流场进行非定常数值模拟,将流场的静压力脉动从时域转换到频域,根据声学原理,对该离心压气机近场声源区的频谱特征进行研究.结果表明,针对本算例,离心叶轮向外辐射的噪声信号在频域上体现出旋转噪声的特性,基频振幅达到了7 000 Pa数量级,而湍流噪声则十分微弱,对压气机的声辐射特性影响很小,基本可以忽略.进一步对湍流噪声的单独分析表明,湍流噪声基频为叶轮的整周通过频率,这是由下游流道的非对称几何结构蜗壳喉部决定的,并且其基频振幅达到了5 000 Pa量级.     

增压器压气机叶轮的三维弹塑性精细分析

用基于参变量变分原理的有限元参数二次规划法对增压器压气机叶轮进行了三维弹塑性精细分析的研究，并计算了叶轮在用预超速工艺制造过程中的残余应变，给出了其分布规律，计算结果与实测符合得很好．     

基于S7-200 PLC和TP170A的船舶中央空调综合控制系统的实现

本文利用S7-200PLC实现船舶中央空调的综合控制和管理，对制冷压缩机进行有级能量调节，温度和湿度实现PID和PWM控制，达到了节能和操作方便的效果。     

A methodology for identifying similar days in air traffic flow management initiative planning

This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.     

Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand

This paper proposes a novel short/medium-term prediction method for aviation emissions distribution in en route airspace. An en route traffic demand model characterizing both the dynamics and the fluctuation of the actual traffic demand is developed, based on which the variation and the uncertainty of the short/medium-term traffic growth are predicted. Building on the demand forecast the Boeing Fuel Flow Method 2 is applied to estimate the fuel consumption and the resulting aviation emissions in the en route airspace. Based on the traffic demand prediction and the en route emissions estimation, an aviation emissions prediction model is built, which can be used to forecast the generation of en route emissions with uncertainty limits. The developed method is applied to a real data set from Hefei Area Control Center for the en route emission prediction in the next 5 years, with time granularities of both months and years. To validate the uncertainty limits associated with the emission prediction, this paper also presents the prediction results based on future traffic demand derived from the regression model widely adopted by FAA and Eurocontrol. The analysis of the case study shows that the proposed method can characterize well the dynamics and the fluctuation of the en route emissions, thereby providing satisfactory prediction results with appropriate uncertainty limits. The prediction results show a gradual growth at an average annual rate of 7.74%, and the monthly prediction results reveal distinct fluctuation patterns in the growth.     

金杯客车空调系统的电路组成和工作原理

依据实物测绘出金杯（SY6480A2F-E）客车空调控制器内部的原理电路,列出其空调系统原理电路图。在讲述各元器件功能的基础上,着重分析在不同情况下空调系统的工作过程。