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.     

How much noise reduction at airports?

Airport noise nuisance is a negative externality especially when it occurring near urban areas. Like all externalities, noise nuisance may be a reason for government intervention. When intervening, governments should set quantitative policy targets with care. In practice, this issue is generally neglected. This line of research sets the first step towards determining optimal policy targets in the case of noise nuisance near airports, more specifically in the case of Amsterdam Airport. We use hedonic pricing to establish the benefits of noise reduction. Furthermore, we develop a bottom-up cost function to analyze the costs of reducing noise for airlines. We then equate marginal costs and benefits to establish the optimal level of noise reduction, which appears to be 3 dB in the case of Amsterdam Airport. Welfare increasing measures include alternative approach procedures, regional substitution of planes within existing fleets and early depreciation of noisy planes increase welfare. Reducing the number of flights has a negative effect on net welfare.     

Estimation of the effects of aircraft noise on residential satisfaction

This study assesses the effects of aircraft noise on residential satisfaction, an important indicator of subjective well-being. A structural equation model is specified that estimates the relationships between objective variables, noise annoyance variables and residential satisfaction. Secondary data-analysis is used to estimate the model. The survey was conducted in 1996/1997 among the population living within a 25-km radius of Amsterdam Schiphol, the largest airport in the Netherlands. The effect of aircraft noise annoyance is found to be relatively small. In addition, the objective level of aircraft noise exposure is found to be a better predictor of residential satisfaction than its subjective counterpart. The most important determinants of residential satisfaction are found to be road traffic noise annoyance, age and neighbor noise annoyance.     

The economics of airport noise: How to manage markets for noise licenses

This paper discusses various issues in the implementation of a local market for aircraft noise licenses to solve the noise externalities harming the residents located near airports. The design of such markets is affected by aircraft heterogeneity, wind contingencies, peak times, runways capacity constraints, hub strategies, and airport planning is discussed.     

Costs and benefits of US aviation noise land-use policies

Aircraft noise affects human health and welfare. One method US airports use to mitigate the impact of noise on nearby residents is through sound insulation and residential land acquisition projects. Costs of residential insulation and acquisition projects are taken from federal grant summaries while the benefits of noise reduction are calculated as the combined willingness-to-pay for abatement and direct and indirect costs of illness from hypertension, myocardial infarction, and stroke. We show that the average cost of sound insulation projects is $15,600 per person affected while that of land acquisition is $48,900 per person affected. We find that for only in 15% of projects do the benefits to residents from willingness-to-pay for reduction and reduced risk of mortality and morbidity exceed the costs of sound insulation for residences exposed to 65 dB Day Night Level (DNL) of noise. Our estimates suggest that noise insulation projects are more cost-effective than fleet wide mandatory aircraft retirement.     

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.     

Multi-objective optimisation for aircraft departure trajectories minimising noise annoyance

This paper presents a strategy for designing noise abatement procedures aimed at reducing the global annoyance perceived by the population living around the airports. A non-linear multi-objective optimal control problem is implemented and numerically solved obtaining minimal annoyance trajectories. Annoyance criteria are treated as non-linear functions that can be obtained by using fuzzy logic modelling techniques. Here, a basic implementation is shown where the annoyance is expressed in function of the maximum perceived noise level, the period of the day when the trajectory takes place and the type of area over-flown. Then, lexicographic optimisation techniques are used to deal with the multi-criteria nature of the problem. Finally, an illustrative example is given concerning a hypothetical scenario with five different noise sensitive locations and where different optimal trajectories are obtained for different hours of the day.     

Environmental noise inequity in the city of Barcelona

Environmental noise is a growing concern for urban planners and public health experts. Continuous noise exposure has implications for people’s physical and mental health. Urban planning strategies are also involved in the need for regular noise assessments within urban areas. The objective of this study is to evaluate the exposure to noise of vulnerable population groups in the city of Barcelona, and to determine whether they are affected by an environmental inequity regarding this nuisance. Assessment of noise levels was performed by two methods of analysis—real measures and simulation—in order to build the noise database at block level for the 10 districts of the city. The results obtained by various statistical tests and spatial regression analysis show that children and low-income individuals are not affected by environmental inequity. On the other hand, we found a positive relationship between noise levels and the other groups considered: namely, the unemployed and people over age 65.     

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.     

Air traffic assignment to reduce population noise exposure using activity-based approach

Aircraft noise has been regarded as one of the major environmental issues related to air transport. Many airports have introduced a variety of measures to reduce its impact. Several air traffic assignment strategies have been proposed in order to allocate noise more wisely. Even though each decision regarding the assignment of aircraft to routes should consider population exposure to noise, none of the air traffic assignment strategies has addressed daily migrations of population and number of people exposed to noise. The aim of this research is to develop a mathematical model and a heuristic algorithm that could assign aircraft to departure and arrival routes so that number of people exposed to noise is as low as possible, taking into account temporal and spatial variations in population in an airport’s vicinity. The approach was demonstrated on Belgrade airport to show the benefits of the proposed model. Numerical example showed that population exposure to noise could be reduced significantly by applying the proposed air traffic assignment model. As a consequence of the proposed air traffic assignment, overall fuel consumption increased by less than 1%.     

The effects of information bias and riding frequency on noise annoyance to a new railway extension in Hong Kong

We investigate how two non-acoustic factors, information bias and riding frequency, can affect the annoyance response of an urban population to noise created by a new railway line. The study shows that information bias is asymmetrical. Respondents receiving only information on positive measures taken by the authority to reduce noise emission are more tolerant of the noise impact, but those receiving only critical views tend to be more annoyed because they feel that not all measures to reduce noise have been employed. Additionally people who use the line frequently are more tolerant to the noise impact than those who do not. Information bias seems to have a temporary masking effect over riding frequency lasting for a few weeks after railway opening. This suggest that whilst free flow of information provided by the authority can help alleviate annoyance response, encouraging the people affected to make use of the new infrastructure may be useful to reduce public resistance and noise annoyance.     

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.     

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.     

Effects of noise exposure of other people on aircraft noise tolerability using a reference point approach

Reactions to aircraft noise resulting from an airport development vary considerably among individuals. This paper examines whether the noise level tolerated by individuals is affected when they compare their own situation to the situations of other people who are more severely affected by the noise. We modeled the individual noise tolerability by adopting the reference point concept and the value function of prospect theory. A questionnaire assessed different levels of noise-affected zones at a hypothetical airport. Individual noise tolerable level was measured by a prerecorded aircraft noise presented via headphones. Decision-making associated with the reported satisfaction level regarding the changes in operational flight frequency settings at the airport. An interview survey was conducted with residents near Manila airport in the Philippines. We applied genetic algorithm to jointly estimate the parameters for noise tolerability model and the value function. Results showed that individuals tolerated more overhead flights when they considered the situations of other people worse affected by the noise than they were. The tendency of noise tolerability increased with the severity of noise exposure situations of other people, but lower reactions to noise escalation. We also observed diminishing sensitivity to changes in noise relative to the noise tolerable level. The aircraft noise tolerability and the consideration of noise exposure situations of other people appeared to be a vital aspect to be considered in airport noise management and policy.     

A time series analysis of the dynamic competition between major cargo airports

This paper models the dynamic competition between major cargo airports from the time series perspectives of long-term equilibriums and short-run dynamics. We first apply a unit root test to examine the stationarity of cargo throughput data. Airports are then analysed pairwise by region to test their equilibrium relationships through cointegration analysis. Meanwhile, we also utilise the error correction model to investigate the short-run impacts of cargo traffic between the airports. According to our findings, there are four positive long-term equilibriums, one positive short-run dynamic and three negative short-run dynamics in Asia. In addition, the airports in North America are found to have four positive long-term equilibriums, three negative long-run equilibriums, seven positive short-run impacts and three negative short-run impacts. As these dynamic relationships imply competition between cargo airports, our study can provide airport authorities with the reference to develop their long-term strategies and short-run operational plans.     

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。     

Using measured instead of perceived noise in hedonic models

This paper compares the use of perceived and measured noise in a hedonic housing model. Although in theory the use of subjective variables is recommended, most empirical applications use measured noise variables. Merging different databases, we obtain a sample of about 2800 apartments located in Geneva, Switzerland, containing both measured and perceived noise data. We make the measured and perceived noise data comparable and analyse their performance by fitting alternatively three hedonic models. We find that for moderate to high noise levels the measured noise safely approximates its perception.     

A model to forecast aircraft operations at general aviation airports

Forecasting the demand for aviation activities is an important task in economic planning. Traditionally, forecasting the demand for general aviation airports has been done using trend and ratio analyses. Both techniques ignore the changes in many external factors that influence aviation activities. This paper develops an econometric model that relates the number of aircraft operations at a general aviation airport to some socioeconomic characteristics and supply variables. The model was estimated using data for 82 airports in the state of Georgia. The results of estimating the model suggest that the demand is inelastic with respect to total employment. The results also show that presence of aviation related services such as avionics, charter flights, rental, repair and crop dusting are important factors in determining aviation activities. The demand seems to be responsive to the location of the county as a tourist/recreational destination.     

Determination and Applications of Environmental Costs at Different Sized Airports – Aircraft Noise and Engine Emissions

With the increasing trend of charging for externalities and the aim of encouraging the sustainable development of the air transport industry, there is a need to evaluate the social costs of these undesirable side effects, mainly aircraft noise and engine emissions, for different airports. The aircraft noise and engine emissions social costs are calculated in monetary terms for five different sized airports, ranging from hub airports to small regional airports. The number of residences within different levels of airport noise contours and the aircraft noise classifications are the main determinants for accessing aircraft noise social costs. The environmental impacts of aircraft engine emissions include both aircraft landing and take-off and 30-minute cruise. The social costs of aircraft emissions vary by engine type and aircraft category, depending on the damage caused by different engine pollutants on the human health, vegetation, materials, aquatic ecosystem and climate. The results indicate that the relationship appears to be curvilinear between environmental costs and the traffic volume of an airport. The results and methodology of environmental cost calculation could be applied to the proposed European wide harmonised noise charges as well as the social cost benefit analysis of airports.     

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.