Experience sampling in and around airports. Momentary subjective wellbeing,airports, and aviation noise in England

We explore the wellbeing of people in and around English airports using real-time data from a large spatial positioning experience sampling dataset (Mappiness). We analyze the association between subjective wellbeing reported in the moment and aviation, in terms of airport location, aircraft noise, and activities within airports. This is the first time that a large Experience Sample Method (ESM) of momentary wellbeing measurements has been used to quantify the associations between aviation and subjective wellbeing. Being within areas of high levels of aircraft noise is associated with lower levels of happiness and relaxation. Those surveyed in proximity to airports report significantly lower levels of relaxation. These findings have important implications to policy. Exploiting the panel nature of the ESM data provides the strongest causal claims to date of the negative association between aviation activities and subjective wellbeing. The Mappiness application also allows us to assess the association between airports and wellbeing on those inside them, and divide activities within airports between those who work there and those who are passing through for travel purposes, as well as the effects of aircraft noise beyond airports. This gives us a broader insight into the range of impacts, both positive and negative, that aviation has on peoples’ momentary wellbeing, which may be used to inform aviation noise mitigation and compensation policies in the future.     

Much Ado about Nothing? - An analysis of economic impacts and ecologic effects of the EU-emission trading scheme in the aviation industry

From 2012 on, all CO₂ emissions from flights departing from or arriving at airports within the European Union have to be offset. We analyze the economic and ecological impacts that are caused by an inclusion of the aviation industry into the proposed emissions trading scheme (ETS). Building on the now fixed system design we employ a simulation model to estimate the impacts of the scheme. Our results indicate that financial impacts are highly dependant on external settings, such as allowance prices and demand growth. We show that the financial burden on the aviation industry will be rather modest in the first years after the introduction of the system and therefore induce only low competition distortions. Likewise, emission reductions within air transportation will be comparably low. While aviation will induce a decline of emissions in other sectors, significant absolute reductions within air transportation can only be reached by a more restrictive system design.     

Living with aircraft noise: Airport proximity,aviation noise and subjective wellbeing in England

Airport expansion is an issue of intense public debate due to the potential impacts on climate change and the quality of life of affected local communities. This paper is the first study to analyse the relationships between airports and multiple subjective wellbeing measures, by merging national-level population statistics with noise measurement maps for seventeen English airports. The presence of daytime aviation noise was found to consistently negatively impact on five subjective wellbeing measures. We found a marginal negative association with every additional decibel of aircraft noise. We found no significant association between wellbeing and living within night-time noise contours or living in close airport proximity. We conclude that living under air traffic flight paths has a negative effect on peoples’ overall and momentary wellbeing, equivalent to around half the effect of being a smoker for some wellbeing measures. The subjective wellbeing method findings support wider revealed preference literature showing lower market demand in areas affected by aviation noise.     

Demand for rail travel to and from airports

Rail access to airports is becoming increasingly important for both train operators and the airports themselves. This paper reports analysis of inter-urban rail demand to and from Manchester and Stansted Airports and the sensitivity of this market segment to growth in air traffic and the cost and service quality of rail services. The estimated demand parameters vary in an expected manner between outward and inward air travellers as well as between airport users and general rail travellers. These parameters can be entered into the demand forecasting framework widely used in the rail industry in Great Britain to provide an appropriate means of forecasting for this otherwise neglected market segment. The novel features of this research, at least in the British context, are that it provides the first detailed analysis of aggregate rail flows to and from airports, it has disaggregated the traditional generalised time measure of rail service quality in order to estimate separate elasticities to journey time, service headway and interchange, and it has successfully explored departures from the conventional constant elasticity position.     

Modeling taxi drivers’ decisions for improving airport ground access: John F. Kennedy airport case

Taxi service is an important component of airport ground access, which affects the economic competitiveness of an airport and its potential positive impact on the surrounding region. Airports across the globe experience both taxi shortages and excesses due to various factors such as the airport’s proximity to the city center, timing and frequency of flights, and the fare structure. Since taxi drivers are independent entities whose decisions affect the taxi supply at airports, it is important to understand taxi drivers’ decision mechanisms in order to suggest policies and to maintain taxi demand and supply equilibrium at the airports. In this paper, New York City (NYC) taxi drivers’ decisions about airport pick-ups or cruising for customers at the end of each trip is modeled using logistic regression based on a large taxi GPS dataset. The presented approach helps to quantify the potential impacts of parameters and to rank their influence for policy recommendations. The results reveal that spatial variables (mainly related to proximity) have the highest impact on taxi drivers’ airport pickup decisions, followed by temporal, environmental and driver-shift related variables. Along with supplementary information from unstructured taxi driver interviews, the model results are used to suggest policies for the improvement of John F. Kennedy (JFK) airport’s ground access and passenger satisfaction, i.e. the implementation of taxi driver frequent airport server punch cards and a time-specific ride share program.     

Sizing parking facilities at airports

Established rules-of-thumb and industry guidelines for estimating the supply of parking at airports are based on uncertain quantities such as design year enplanements and number of airport employees, and are independent of cost. In the presence of continued uncertainty and increasing competition for limited space in and around airports, it is important that facilities are sized in relation to cost of providing and using them. A probabilistic model based on the classical “newsboy” problem is proposed to determine the optimal supply of parking in relation to expected total cost while treating demand as a random quantity. Empirical data are used to demonstrate the application of the proposed model for decision making. In addition to construction and maintenance costs, and user costs, decisions are shown to be sensitive to the level of uncertainty of design year enplanements.     

Benchmarking airports with specific safety performance measures

The purpose of this paper is to develop safety performance measures and test the measures on data for air traffic management failure events. Failure events are classified by the severity of the consequence of occurrence, resulting in the rate of occurrence in severity categories. The safety measures are standard statistics calculated from this “distribution” for comparison of airport operations by stochastic ordering. For comparisons a benchmark is developed from the aggregation of failure data on a set of comparable airports. Airport performance is then compared with the benchmark using the defined safety measures. The benchmark comparison was implemented with failure data for major airports in Canada from 2005 to 2012. The results show a number of patterns and anomalies and some airports perform poorly in comparison to a class of similar operations. We conclude by suggesting benchmarking safety measures as a natural addition to the information system on aviation safety compiled by a national regulatory body to unravel anomalies such as implementation problems of a safety management system.     

Measuring the performance of airport resilience to severe weather events

The increased severe weather events in recent years as a result of global climate change has created a substantial challenge for aviation system operation. Although transportation engineers and planners have attempted to improve system resilience through the adaptation of new technologies and the implementation of various strategies to achieve effective risk management, it remains unclear how resilience performance (measured by the speed of recovery) of airports varies in different severe weather events and what factors may explain such variations. This paper addresses these fundamental questions using the aviation system in China as an example. A resilience metric, which reflects the speed of recovery (bounce back) from a shock, was developed to measure the performance of airport resilience under various severe weather conditions. In addition, an empirical econometric analysis was conducted based on a dataset that includes both detailed aviation performance and weather conditions for the period of October 2016 – September 2017. The research findings show that airport resilience to severe weather events does vary substantially based on factors, such as weather conditions, airport capacity, and the level of modal substitution. In particular, the recovery time of air services in central and south China tends to be relatively longer in thunderstorms than other weather conditions. The study also confirms that modal substitution is a very effective resilience tactic of the transportation system as the recovery speed of air service was found to be faster by 22.9% if an alternative mode, such as high-speed rail (HSR) service was also available in the city.     

基于功能定位的国际航空枢纽评价

针对我国国际枢纽机场未按照设计之初功能定位发展的现状,运用AHP法构建国际枢纽机场综合评价指标体系,将国际航空运输规模指标、国际节点网络连通度指标、枢纽功能指标、综合交通指标纳入体系当中。首先对国内外大型国际枢纽机场进行评价,其次对我国机场布局规划中的10个国际枢纽机场进行评价。结果表明我国国际枢纽机场国际业务发展、航空枢纽建设与国外对标机场有一定差距,与自身战略规划有所偏差,针对薄弱指标项基于自身优势给出发展建议。最后基于一市两场与机场群的视角,分析了如何根据自身功能定位进行协同发展问题。     

The integration of Taiwanese and Chinese air networks for direct air cargo services

The two sides of the Taiwan Strait perform mutually dependent but complementary activities in the global manufacturing supply-chain. As a result, trade between Taiwan and China grew in double digits annually in the 1990s. With growing economic ties, direct air links are inevitable. In this research, we analyzed government documents and interviewed the air cargo carriers and airlines that currently serve the Taiwan–China air cargo market. This information enabled us to tabulate the trade, estimate the airport-to-airport air cargo demand and calibrate the international and domestic freight tariffs. We used a connectivity measurement and classified Chinese airports into national, regional and local classes in a hub-and-spoke air cargo network. We developed a mathematical model and a branch-and-bound algorithm. The results showed that at least two transit airports are economically necessary for a Taiwan–China air link. Shanghai and Xiamen were always the top two transit airports. The third airport would be Changsha if the decision becomes three air-links. These links are different from the top three passenger transit airports, Fuzhou, Xiamen and Shanghai, even though the cost saving is moderate.     

Performance based clustering for benchmarking of US airports

Managing service operations is gaining significant attention in both academic and practitioner circles. In this broad area, performance evaluation and process improvement of airlines and air carriers has been the focus of several studies. Although efficient airport operations are critical for improved performance of airlines and air carriers, few studies have focused on airport performance measurement. This study evaluates the operational efficiencies of 44 major US airports across 5 years using multi-criteria non-parametric models. These efficiency scores are treated by a clustering method in identifying benchmarks for improving poorly performing airports. Efficiency measures are based on four resource input measures including airport operational costs, number of airport employees, gates and runways, and five output measures including operational revenue, passenger flow, commercial and general aviation movement, and total cargo transportation. The methodology presented here can be generalized to other industries and institutions.     

上市航空类企业现金持有水平研究

新冠肺炎疫情重新使人们认识到现金对企业的重要性。航空业运营成本巨大,持有一定量现金对维持航空企业运营具有重要意义。本文利用1998~2019年间沪深两市航空类上市公司的数据,研究了我国航空业现金持有水平。研究发现:航空业现金持有水平较低,航空公司更是呈逐年下降的趋势,低现金持有水平可能是投资挤压导致的;近几年,航空类企业持有的现金最多仅能维持5个月;企业债务融资与固定资产投资等密切相关;航空公司和机场利用商业信用的程度较弱。对此,我国民航企业应改变单一的投融资方式,加大对商业信用的利用。     

The federal republic of Germany: the federal ministry of transport

The continued liberalization of the airline market in the European Community offers the prospect of competition in terms of price, frequency of service and many other attributes. Understanding these factors that influence passenger demand and incorporating them into a demand function poses a substantial theoretical and empirical challenge. A basis for estimating demand functions is the logit model. This paper examines the value of a logit share model in explaining how the share of airlines between airports varies as a function of measured and unmeasured attributes. It shows how demand functions are necessary for understanding a competitive market and evaluates the progress to date in identifying accurate coefficients of the logit function.     

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.     

Effects of corruption on efficiency of the European airports

The effect of corruption on airport productive efficiency is analyzed using an unbalanced panel data of major European airports from 2003 to 2009. We first compute the residual (or net) variable factor productivity using the multilateral index number method and then apply robust cluster random effects model in order to evaluate the importance of corruption. We find strong evidence that corruption has negative impacts on airport operating efficiency; and the effects depend on the ownership form of the airport. The results suggest that airports under mixed public–private ownership with private majority achieve lower levels of efficiency when located in more corrupt countries. They even operate less efficiently than fully and/or majority government owned airports in high corruption environment. We control for economic regulation, competition level and other airports’ characteristics. Our empirical results survive several robustness checks including different control variables, three alternative corruption measures: International Country Risk Guide (ICRG) corruption index, Corruption Perception Index (CPI) and Control of Corruption Index (CCI). The empirical findings have important policy implications for management and ownership structuring of airports operating in countries that suffer from higher levels of corruption.     

Determinants of airports’ environmental effects

Aviation is a fast growing sector with increasing environmental concerns linked to aircraft emissions at airports and noise nuisance. This paper investigates the factors affecting the annual environmental effects produced by a national aviation system. The environmental effects are computed using certification data for each aircraft-engine combination. Moreover, we also take into account for the amount of environmental effects that is internalized at the airport, mainly through noise regulation. We study a dataset covering information on Italian airports during the period 1999–2008. We show that a 1% increase in airport’s yearly movements yields a 1.05% increase in environmental effects, a 1% in aircraft size (measured in MTOW) gives rise to a 1.8% increase and a 1% increase in aircraft age generates a 0.69% increase in environmental effects. Similar results but with smaller magnitudes are observed if airport internalization is considered. Our policy implications are that the tariff internalizing the total amount of externality is about euro 180 per flight, while the tariff limiting only pollution is about euro 60 and the one reducing noise is about euro 110. Moreover, our airport examples show that managers should prefer to address additional capacity by increasing frequency rather than aircraft size, since the former strategy is more environmental friendly.     

Deconstructing delay: A non-parametric approach to analyzing delay changes in single server queuing systems

This paper introduces an empirically driven, non-parametric method to isolate and estimate the effects that changes in demand and changes in throughput have on delay – in particular, arrival and departure flight delay at airport runways. Classic queuing concepts were used to develop a method by which an intermediate, or counterfactual, queuing scenario could be constructed, to isolate the delay effects due to shifts in demand and throughput. This method includes the development of a stochastic throughput function that is based entirely on data and has three key features. Firstly, the function relies on non-parametric, empirically-based probability distributions of throughput counts. Secondly, facility capacity needs not be explicitly defined, as it is implicitly included in the probability distributions of throughput. Thirdly, the throughput performance function preserves the effect of factors that cause capacity (and, therefore, throughput) to fluctuate over a given period. Temporal sequences of high, moderate, and low capacity are maintained between the observed and counterfactual scenarios. The method was applied to a case study of the three major New York area airports of LaGuardia (LGA), Newark Liberty (EWR), and John F. Kennedy (JFK), using operational data extracted from the Federal Aviation Administration’s (FAA’s) Aviation System Performance Metrics (ASPM) database. The focus was on the peak summer travel seasons of 2006 and 2007, as these airports experienced record levels of delay in 2007. The results indicate that decreases in both demand and throughput were experienced at LGA and EWR, although the decreases in throughput had more significant effects on operational delays as they increased overall at these airports. At JFK, the increase in departure throughput was not sufficient to offset the increase in departure demands. For arrivals, demand increased and throughput decreased. These trends caused a significant growth in delay at JFK between 2006 and 2007.     

Evaluation of general aviation management at Denver Stapleton airport

The potential benefits of general aviation management at a major airport is examined in this paper. The three general aviation management techniques investigated are volume reduction, runway segregation and time restriction.

First, a methodology for analyzing these techniques is discussed. The various effects on each user group are quantified for economic comparison between each management technique attempted. A computer simulation model was used to measure the delay effects. Then, these techniques are applied to Denver Stapleton Airport to measure their effects in present and future scenarios.

The results show that the best general aviation management technique is volume restriction. The use of peak‐hour pricing mechanism provided better results than random rejection, particularly if only a small degree of diversion is desired. The construction of a new general aviation runway provided equivalent results to the best technique tested.     

Airport congestion and near-midair collisions

This paper presents a model that systematically integrates, for the first time, the association between a region's aviation near-midair collision risk and its traffic levels, its type and amount of air traffic control, and the complexity of its airspace. The model incorporates the tight interrelatedness (and correlation) between traffic, airspace complexity, and air traffic controller staffing. An estimation of the model using cross-sectional data on 143 U.S. airports in 1985 indicates that the frequency of reported near-midair collisions (NMACs) is positively associated with regional traffic and airspace complexity, despite the fact that busier, more complex regions generally have more air traffic controllers. Also, in regions governed by “terminal radar service areas” (TRSAs), the reported near-midair collisions are positively associated with the presence of more satellite airports than would be expected on the basis of traffic alone. Finally, deviations from controller staffing levels that would be expected on the basis of traffic and airspace complexity alone are significantly associated with variations in reported NMACs in terminal control areas but not in terminal radar service areas.     

Optimization of airport bus timetable in cultivation period considering passenger dynamic airport choice under conditions of uncertainty

An airport bus service, which is newly introduced in a multi-airport region, commonly leads to a gradually increasing market share of airports until a new state of equilibrium is reached. With the goal of speeding up and enlarging the increase in market share, this paper proposes a timetable optimization model by incorporating reactions of airport-loyal passengers to bus service quality. The simulation part of the model, which uses cumulative prospect theory to formulate discrete airport choices, results in predicted passenger demand needed in the optimization part. Then a genetic algorithm for multi-objective optimization problems called NSGA-II is applied to solve the model. To illustrate the model, the “Lukou airport-Wuxi” airport bus in China is taken as an example. The results show that the optimized timetables shorten the cultivation period and impel the market share to grow rapidly.