Estimation of airport noise impacts on public health. A case study of İzmir Adnan Menderes Airport

The air transport industry is showing rapid growth in line with the call for meeting the requirements of a rising population. Noise mapping is more useful than surveys and measurements to estimate the effects of noise on public health. In this paper, noise levels for the day, evening and night time slices around İzmir Adnan Menderes Airport were calculated by use of the SoundPLAN 7.2 software according to the European Noise Directive, and the “ECAC Doc. 29-Interim” method was applied for the computation of the aircraft noise. Air traffic data of year 2012, technical information about the airport and geographical data including the layers of elevation, residential buildings, auxiliary buildings, hospitals and schools were used as the main inputs for the model developed in the study. The model was found to perform well for the areas closer to the airport. The results of the study suggested that the area at the north side of the airport, where the city center of İzmir is located, is more affected than other areas. The threshold value of 55 dB(A) was found to be exceeded in 0.3% of the land area covered by İzmir City center during the time slice “day”. The results showed that about 2% of the resident population was exposed to noise levels of 55 dB(A) or higher during day-time in İzmir. In addition, it was understood that the number of people who are potentially exposed to high noise levels and threatened by several illness such as hypertension and sleep disturbances is significant in the surrounding area of the airport. It is thought to be important for airport operators to manage the airport capacity based on the flight schedules in order to control the noise exposure level around the airport.     

Transport and environment interactions: the italian framework

With road traffic in Europe forecast to increase, strategies are needed to keep transportation sector growth within the bounds imposed by a sustainable development. Research is contributing through a large number of projects dealing with transport–environment interactions. This paper reviews international research activities in this field, focusing on technological innovations, air and noise pollution prediction models, and existing tools for socioeconomic evaluation of traffic impacts on the environment. In particular, research projects of the Second Special Project on Transport (PFT2) of the Italian National Research Council (CNR) are outlined.     

Development of an emissions inventory model for mobile sources

Traffic represents one of the largest sources of primary air pollutants in urban areas. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentrations of a wide range of pollutants. A mutual characteristic of most of these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emissions inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for a wide range of vehicle types. The majority of inventories are compiled using ‘passive’ data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. Current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this paper, a methodology for estimating emissions from mobile sources using real-time data is described. This methodology is used to calculate emissions of sulphur dioxide (SO₂), oxides of nitrogen (NO_x), carbon monoxide (CO), volatile organic compounds (VOC), particulate matter less than 10 μm aerodynamic diameter (PM₁₀), 1,3-butadiene (C₄H₆) and benzene (C₆H₆) at a test junction in Dublin. Traffic data, which are required on a street-by-street basis, is obtained from induction loops and closed circuit televisions (CCTV) as well as statistical data. The observed traffic data are compared to simulated data from a travel demand model. As a test case, an emissions inventory is compiled for a heavily trafficked signalized junction in an urban environment using the measured data. In order that the model may be validated, the predicted emissions are employed in a dispersion model along with local meteorological conditions and site geometry. The resultant pollutant concentrations are compared to average ambient kerbside conditions measured simultaneously with on-line air quality monitoring equipment.     

Use of Bayesian inference method to model vehicular air pollution in local urban areas

Traffic Related Air Pollution (TRAP) studies are usually investigated using different categories such as air pollution exposure for health impacts, urban transportation network design to mitigate pollution, environmental impacts of pollution, etc. All of these subfields often rely on a robust air pollution model, which also necessitates an accurate prediction of future pollutants. As is widely accepted by the heath authorities, TRAP is considered to be the major health issue in urban areas, and it is difficult to keep pollution at harmless levels if the time sequenced dynamic pollution and traffic parameters are not identified and modelled efficiently. In our work here, artificial intelligence techniques, such as Bayesian Networks with an optimized configuration, are used to deliver a probabilistic traffic data analysis and predictive modelling for air pollution (SO₂, NO₂ and CO) at very local scale of an urban region with up to 85% accuracy. The main challenge for traditional data analysis is a lack of capability to reveal the hidden links between distant data attributes (e.g. pollution sources, dynamic traffic parameters, etc.), whereas some subtle effects of these parameters or events may play an important role in pollution on a long-term basis. This study focuses on the optimisation of Bayesian Networks to unveil hidden links and to increase the prediction accuracy of TRAP considering its further association with a predictive GIS system.     

Vehicle inspection and maintenance,and air pollution in Mexico City

Information from the Mandatory Inspection and Maintenance (I/M) Program carried out in October 1996 and the first semester of 1998 provides a useful emission database for Mexico City. Carbon monoxide (CO) and hydrocarbon (HC) exhaust emission levels were measured for at least a million private and public transportation vehicles. Analysis of this database leads us to conclude that this information can be used to test anti-pollutant policies, and is useful as a performance quality index for vehicle manufacturers. Some of the results of this analysis include: the finding of a typical exhaust emission distribution curve for each vehicle manufacturer, with differences for each brand and model for the same manufacturer, the fact that not all new vehicles pass the I/M test; and public transportation vehicles in Mexico City have almost useless catalytic converters.     

Sensitive analysis of emission rates in MOVES for developing site-specific emission database

With the rapid social and economic development, vehicle emissions have been identified as a major source of urban air pollutions in China. Therefore, the study on vehicle emission estimations is necessary. In light of the limitation of emission data for establishing a local comprehensive emission database, this paper analyzes the characteristics of emission rates in MOVES released by U.S. Environmental Protection Agency (EPA) to investigate the feasibility and to design a method for developing site-specific emission database. Sensitive analysis for model year, age group and speed interval is performed, and the regularity is concluded. The result shows that emission rates are almost constant with model year, but increase with age groups because of emission deterioration. With respect to speed intervals, the emission rates in 25–50 mph are higher than both those <25 mph and >50 mph in the same VSP (vehicle specific power) bins. In addition, an analysis of local emission data in Beijing is conducted to build the relationship between vehicle activities and emission rates. After that, a comparison of emission rates by VSP bins in MOVES and in local database is conducted in this study. The result shows that the absolute values are different because of regulatory emission standards, fuel quality, and other factors. However, the relative changes described by normalizing emission rates have a good consistency. Hence, the regularities of emission rates by VSP bins in MOVES can be used to develop local emission database in Beijing.     

Control of drivers' route choice: Pipe dream or panacea?

In most large cities traffic flow is controlled or manipulated in a number of ways. The methods used are mostly negative in the sense that they restrict the driver's choice of alternative routes rather than encourage him to use a particular one. This paper reviews some of the conventional measures and goes on to consider whether a more positive approach to route control might be justified, by inducing a more efficient or acceptable pattern of traffic movement in urban areas. The principal criteria for an efficient pattern are taken to be the total rate of expenditure of vehicle mileage and the frequency of route crossings, and an attempt is made to evaluate the potential benefits of route control in these terms. Social, technical and political considerations suggest that compulsory control will not be feasible for some time (at least, in the UK), but if the benefits to drivers as individuals can be shown to be worthwhile an advisory system might be practicable. Some possible systems are briefly outlined.The author is grateful to the City Engineer of Westminster City Council, Mr A.J. Cryer, for permission to publish this paper,which, however, does not necessarily represent the views . City Council. The author is greatly indebted to E. M. Holroyd for numerous suggestions and advice.     

Noise prediction for highways in Thailand

A model of highway traffic noise is formulated based on vehicle types. The data were collected from local highways in Thailand with free-flow traffic conditions. First, data on vehicle noise was collected from individual vehicles using sound level meters placed at a reference distance. Simultaneously, measurements were made of vehicles’ spot speeds. Secondly, are data for building the highway traffic noise model. This consists of traffic noise levels, traffic volumes by vehicle classification, average spot speeds by vehicle type, and the geometric dimension of highway sections. The free-flow traffic noise model is generated from this database. A reference energy mean emission level (the basic noise) level for each type of vehicles is developed based on direct measurement of Leq (10 s) from the real running condition of each type of vehicles. Modification of terms and parameters are used to make the model fit highway traffic characteristics and different types of vehicle.     

A combined assessment of air and noise pollution on the High Line,New York City

The High Line is an elevated public park in New York City, transformed from an unused freight rail line. Pedestrians walking through Manhattan’s West Side can walk either on the High Line or on a footpath below. Using Manhattan as a laboratory, this paper offers a combined assessment of noise and particulate matter pollution for its pedestrians. Noise and PM_2.5 levels were recorded simultaneously for two cases (i) pedestrians walking on a footpath alongside road traffic and (ii) pedestrians walking on the elevated High Line. Testing took places over three days in autumn 2014. Results were analysed to investigate if pedestrians using the High Line would have a lower pollution exposure to those using the footpath below. Results showed statistically significant differences between the upper and lower levels in exposure to both pollution types. In order to quantify the overall impact, results are expressed through a combined air–noise pollution index. This index indicates that the average reduction in PM_2.5 and noise pollution along the High Line compared to the footpath below is approximately 37%.     

Floating car based travel times for city logistics

City logistics routing requires time-dependent travel times for each network link. We rely on the concept of Floating Car Data (FCD) to develop and provide such travel times. Different levels of aggregation in the determination of time-dependent travel times from a database of historical FCD are presented and evaluated with regard to routing quality. Furthermore, a Data Mining approach is introduced, allowing for a substantial reduction of the volume of input data required for city logistics routing. The different approaches are investigated and evaluated by a huge amount of FCD collected for the urban area of Stuttgart, Germany. The results show that the Data Mining approach enables efficient provision of time-dependent travel times without a significant loss of routing quality for city logistics applications.     

A tool for calculating aircraft emissions and its application to Greek airspace

This paper quantifies the impact of aircraft emissions on local air quality and climate change. Aircraft emissions during the cruise cycle and the landing/take-off cycle are considered. A tool is developed that computes emission values using real-time air traffic data derived from various databases. Emissions include carbon dioxide, hydrocarbons, carbon monoxide and nitrogen oxides. The overall output is a detailed ‘emissions map’ of a given territory that enables the identification of critical emission spots including routes, airports, season, aircraft type and flight category. The method can be used for real-time monitoring of airline emissions and for policy analysis. The proposed tool and resulting outputs are illustrated in the case of the Greek airport system using domestic, international and overflights. Demand volatility driven mainly by tourism and its impact on emissions is assessed.     

Should traffic-related air pollution and noise be considered when designing urban bicycle networks?

This study was motivated by an interest in capturing the factors affecting the exposure of cyclists to ambient Ultrafine Particles (UFP), Black Carbon (BC), and noise (LA_eq) across the entire bicycle network of the City of Toronto. Measurements were conducted along 270 km of unique roads, and we developed land use regression models and exposure surfaces. Median UFP, BC and noise levels recorded were 19,848 part/cm³, 1224 ng/m³, and 72.9 dB respectively. The average UFP and BC exposures along the biking routes (18,900 part/cm³ and 1130 ng/m³) were higher than the average levels measured at a fixed station located in downtown Toronto (13,300 part/cm³ and 809 ng/m³). The highest UFP and BC levels were experienced on dedicated bicycle tracks (30,000 part/cm³ and 1600 ng/m³ as median concentrations), while the highest noise levels occurred on major roads (median of 74 dB). In contrast, median levels on trails were 13,200 part/cm³, 535 ng/m³ and 70.2 dB, for UFP, BC, and noise. The exposure surfaces developed for the air pollutants and noise were intersected with the planned extensions to the bicycle network in the City of Toronto to evaluate the distributions of exposures expected across the future cycling network. We observe that the mean and median UFP, BC, and noise levels across planned facilities are equal to or significantly higher than the levels across the current network.     

Fuel cycle emissions and life cycle costs of alternative fuel vehicle policy options for the City of Houston municipal fleet

Municipal fleet vehicle purchase decisions provide a direct opportunity for cities to reduce emissions of greenhouse gases (GHG) and air pollutants. However, cities typically lack comprehensive data on total life cycle impacts of various conventional and alternative fueled vehicles (AFV) considered for fleet purchase. The City of Houston, Texas, has been a leader in incorporating hybrid electric (HEV), plug-in hybrid electric (PHEV), and battery electric (BEV) vehicles into its fleet, but has yet to adopt any natural gas-powered light-duty vehicles. The City is considering additional AFV purchases but lacks systematic analysis of emissions and costs. Using City of Houston data, we calculate total fuel cycle GHG and air pollutant emissions of additional conventional gasoline vehicles, HEVs, PHEVs, BEVs, and compressed natural gas (CNG) vehicles to the City's fleet. Analyses are conducted with the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model. Levelized cost per kilometer is calculated for each vehicle option, incorporating initial purchase price minus residual value, plus fuel and maintenance costs. Results show that HEVs can achieve 36% lower GHG emissions with a levelized cost nearly equal to a conventional sedan. BEVs and PHEVs provide further emissions reductions, but at levelized costs 32% and 50% higher than HEVs, respectively. CNG sedans and trucks provide 11% emissions reductions, but at 25% and 63% higher levelized costs, respectively. While the results presented here are specific to conditions and vehicle options currently faced by one city, the methods deployed here are broadly applicable to informing fleet purchase decisions.     

The cumulative effect of nuisances from road transportation in residential sectors on the Island of Montreal – Identification of the most exposed groups and areas

Air pollution and road traffic noise are considered to be the two most important nuisances that could negatively affect the quality of life. A prolonged exposure to high concentrations of these pollutants could conduct to various health problems. Studies in environmental equity have often considered these nuisances individually whenever it comes from the same source. The main objective of this paper is to determine if the 15 years of age, those aged 65 and over, visible minorities and low income individuals located in a portion of the Island of Montreal are overrepresented in city blocks characterized by having among the highest levels of transportation-related air pollutants (i.e., ambient concentrations of NO₂ and road traffic noise in decibels (dB(A)). The results show that low-income individuals and, to a lesser extent, visible minorities, are significantly overrepresented in city blocks characterized by the higher levels of NO₂ and road traffic noise in dB(A). Multinomial logistic regression analysis confirms these results, and also shows that young people under 15 years are under-represented in the most polluted areas. However, contrary to the previous bivariate results, people aged 65 and over are negatively and significantly associated with the likelihood of their living in a city block located in an advantaged area after controlling for the independent effects of the other explanatory variables. Moreover, visible minorities are significantly overrepresented in advantaged areas. Considering the observed results, some solutions are identified to reduce road traffic noise and air pollution in the city blocks localized near major traffic arteries.     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

Optimization of terminal airspace operation with environmental considerations

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.     

Efficiency measurement of bus routes and exogenous operating environment effects on efficiency

This study develops an independent efficiency measurement model framework of bus routes, so as to treat preferably the heterogeneous outputs in a data envelopment analysis (DEA)-based efficiency measurement. It then introduces four new exogenous operating environment factors at the microscopic level of bus routes, and applies the three-stage DEA approach to incorporate operating environment effects and statistical noise into the efficiency measurement framework. The main purpose is to measure impartially the managerial efficiency of bus routes, purged of operating environment effects and statistical noise, and additionally to investigate the operating environment effects on efficiency. An empirical analysis, based on 39 routes operated in Jiangyin City, China, is presented. The principal finding is that the adoption of the independent efficiency measurement model framework is reasonable and has many virtues. Moreover, the proposed approach could substantially provide decision support both for regulators and for producers of bus services. In addition, the operating environment does indeed significantly affect operating efficiency and quality efficiency, especially the latter.     

The design of environmentally aware travel diaries

Any policy addressing the concerns and trends associated with the impact of travel on the environment should be based on a solid understanding of the activities giving rise to them. While the measurement of the total environment loads by air or noise measurement stations is essential, it needs to be matched by the observation of the human behaviours creating them. This is especially true in the transport sector, which has been rightly or wrongly identified as having the potential to make a substantial contribution to the reduction of air and noise pollution. While the contribution of freight transport is of growing concern and importance, this paper focuses on the measurement of passenger transport throughout.

In the past transport planners have largely relied on the travel diary as their prime instrument to measure traveller behaviour. The travel diary is a survey instrument designed to record all movements during the course of one or more days including their relevant details. It is complemented by spearate household and personal forms for recording general information. In the following paper the term travel diary implies all three elements (the diary, the person form and the household form).

The remainder of the paper discusses to what extent and how the travel diary can be used to capture data for the assessment of policies directed at reducing the impact of transport on the social and natural environment. The requirements of a travel diary and the potential uses of new technologies in realising such a travel diary are then presented. A brief outlook on the possibilities of reasling such a diary concludes the paper.     

A new methodology for vehicle trajectory reconstruction based on wavelet analysis

Vehicle trajectories with high spatial and temporal resolution are known as the most ideal source of data for developing innovative microscopic traffic models. Aside from the method applied for collecting the vehicle trajectories, such data are more or less error-infected. The ever-increasing noise amplitude during the process of deriving the data (such as speed and acceleration) required for developing models, might change or even hide the structure of data and lead to useful information being overlooked. This highlights the importance of presenting the efficient methods which are adequate to remove noise and enhance the quality of vehicle trajectory data. Accordingly, in this paper a simple two-step technique based on wavelet analysis has been recommended for filtering errors and reconstructing trajectory data. Primarily, by using wavelet transform a special treatment was employed to identify and modify the outliers. Next, the noise in trajectory data was eliminated by applying the wavelet-based filter. The results of applying the proposed method to the synthetic noise-infected trajectory and the NGSIM dataset reveal how appropriate its performance is compared with other methodologies in terms of quantitative criteria.     

Assessing the importance of transportation activity data for urban emission inventories

The aim of this research is the implementation of a GPS-based modelling approach for improving the characterization of vehicle speed spatial variation within urban areas, and a comparison of the resulting emissions with a widely used approach to emission inventory compiling. The ultimate goal of this study is to evaluate and understand the importance of activity data for improving the road transport emission inventory in urban areas. For this purpose, three numerical tools, namely, (i) the microsimulation traffic model (VISSIM); (ii) the mesoscopic emissions model (TREM); and (iii) the air quality model (URBAIR), were linked and applied to a medium-sized European city (Aveiro, Portugal). As an alternative, traffic emissions based on a widely used approach are calculated by assuming a vehicle speed value according to driving mode. The detailed GPS-based modelling approach results in lower total road traffic emissions for the urban area (7.9, 5.4, 4.6 and 3.2% of the total PM10, NO_x, CO and VOC daily emissions, respectively). Moreover, an important variation of emissions was observed for all pollutants when analysing the magnitude of the 5th and 95th percentile emission values for the entire urban area, ranging from −15 to 49% for CO, −14 to 31% for VOC, −19 to 46% for NO_x and −22 to 52% for PM10. The proposed GPS-based approach reveals the benefits of addressing the spatial and temporal variability of the vehicle speed within urban areas in comparison with vehicle speed data aggregated by a driving mode, demonstrating its usefulness in quantifying and reducing the uncertainty of road transport inventories.