Guidance for new policy developments on railway noise and vibration

Noise and vibration are two of the main problems associated with railways in residential areas. To ensure quality of life and well-being of inhabitants living in the vicinity of railway paths, it is important to evaluate, understand, control and regulate railway noise and vibration. Much attention has been focused on the impact of noise from railway traffic but the consideration of railway-induced vibration has often been neglected. This paper aims to provide policy guidance based on results obtained from the analyses of relationships estimated from ordinal logit models between human response, railway noise exposure and railway vibration exposure. This was achieved using data from case studies comprised of face-to-face interviews (N = 931), internal vibration measurements (N = 755), and noise calculations (N = 688) collected within the study “Human Response to Vibration in Residential Environments” by the University of Salford, UK. Firstly, the implications of neglecting vibration in railway noise policies are investigated. The findings suggest that it is important to account for railway induced vibrations in future noise and transport policies, as neglecting vibrations results in an underestimation of people highly annoyed by noise. Secondly, implications of neglecting different types of railway sources are presented. It was found that the impact of noise and vibration form maintenance operations should be better understood and should be taken into account when assessing the environmental impact of railways in residential environments. Finally, factors that were found to influence railway vibration annoyance are presented and expressed as weightings. The data shows that factors specific to a particular residential area should also be taken into account in future vibration policies as the literature shows that attitudinal, socio-demographic and situational factors have a large influence on vibration annoyance responses. This work will be of interest to researchers and environmental health practitioners involved in the assessment of vibration complaints, as well as to policy makers, planners and consultants involved in the design of buildings and railways.     

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.     

Valuing reductions in environmental pollution in a residential location context

A stated preference ranking experiment is designed to estimate the willingness-to-pay (WTP) for reducing the amount of atmospheric pollution in a group-based residential location context. Important issues are the proper definition of the context and the variable metric for the environmental attribute. Sample members were asked to rank 10 options arising from variations in the attributes travel time to work and to study, rent of the house and an environmental attribute (the number of days of Alert, in terms of concentration of PM₁₀, at a dwelling’s location). Multinomial logit models based on a consistent microeconomic framework were estimated for various stratifications of the data (income, pollution sensitivity, and type of dwelling currently inhabited). From these subjective values of time and WTP were derived for reductions in the number of days of alert and hence the amount of pollutant concentration at a given location. The WTP came out at about 1% of the family income for reducing one contingence day per year; this is approximately 60% higher than an estimate reported for the city of Edmonton, Canada, but the average PM₁₀ concentration in Santiago is about six times higher.     

The measurement of train noise: a case study in northern Italy

This paper analyses the interactions between vehicles, infrastructure and environment for rail traffic. It identifies variables having a significant influence on sound levels, defines a standard procedure for measuring noise, and develops a database for setting up and calibrating train noise models. A pilot study looks at two railway lines passing through Vercelli, a medium sized town in the north-west of Italy. Four main conclusions were drawn. First, in certain conditions, variables that normally influence noise production can be neglected (e.g. when surrounding environmental conditions are constant, different types of train do not cause a significant variation in noise level). Secondly, when diesel trains are travelling at less than 70 km/h, a speed change of 30–40 km/h significantly affects the maximum noise level (Lmax). However, for electrified lines, when speed is below 80 km/h, a change of 20–30 km/h does not cause significant variations in Lmax. Thirdly, for diesel trains transiting at low speeds––e.g. near stations––noise emissions are strongly affected by acceleration/deceleration. Lastly, an approach based on ‘sites types’ is able to produce useful results because site configuration and the presence of building significantly affect Lmax. High buildings along the line can increase noise levels and may nullify the advantages derived from technological advance in the vehicles.     

Aircraft noise social cost and charge mechanisms – a case study of Amsterdam Airport Schiphol

The increasing trend of charging for aircraft noise nuisance to encourage the sustainable development of the air transport industry has resulted in a need to evaluate the real social costs of such externalities for the formulation of effective charge mechanisms. After comparing the current charge mechanisms at world airports as well as reviewing existing externality measurements, mathematical models are developed to calculate the noise social cost in monetary terms, and noise charge mechanisms are subsequently established. The hedonic price method is applied to calculate the annual social cost of aircraft noise during the landing and take-off stages of the flight. This is done by estimating the implicit costs of aircraft noise imposed through a decline in property values in the vicinity of the airport. The empirical results, using Amsterdam Airport Schiphol as the case study, show that the current noise charge level imposed by the Dutch Government is lower than the actual noise social cost resulting from aircraft movements. Several noise charge mechanism scenarios are derived according to the modelling results, as well as the environmental objectives of the airport related authorities.     

Meta-analysis of public transport demand

The present study uses meta-regression in order to explain the wide variation in elasticity estimates obtained in previous demand studies, and provide summaries of several bus demand elasticities.One important finding as to the price elasticity is that the often cited rule of thumb of −0.3 holds good if quality of service represented by vehicle-kilometres is treated as an exogenous variable, but not when it is treated as endogenous.Based on the results it is recommended that demand models should include car ownership, price of petrol, own price, income and some measure of service among the explanatory variables and that the service variable should be treated as endogenous.In previous meta-studies in this field focus has been on own price elasticity only while this study also includes elasticities with respect to, level of service, income, price of petrol and car ownership. The short run for the US are found to be −0.59, 1.05, −0.62, 0.4 and −1.48 respectively.     

Have Emission Control Areas (ECAs) harmed port efficiency in Europe?

Ports in the European Union and North America have enforced environmental regulations on controlling SO_x and NOx emissions from ships in their coastal areas known as Emission Control Areas (ECAs). This study uses two-stage approaches to examine whether ECA regulations impact the efficiency of ports operating in such areas. First, port efficiencies are estimated using non-radial slacks-based measure (SBM) Data Envelopment Analysis (DEA) models. The efficiency scores estimated by the SBM DEA models are then regressed on explanatory variables, including the ECA factor, and macroeconomic indicators using bootstrapped truncated regression (BTR) models. Panel data is collected on countries in EU ECAs and non-ECAs regarding such input variables as capital and labor, with cargo as an output variable. The results indicate that ECA regulations can harm port efficiency, reflecting concerns of policy-makers and industrial managers: the average efficiency loss from an ECA designation amounts to 0.058–0.066 on a scale of 0–1, accounting for a 15–18% loss from ECA ports’ average efficiency scores.     

Measuring the environmental efficiency of the global aviation fleet

This research analyses the environmental footprint of the airline industry in an attempt to highlight potential paths for improvement. We develop a directional economic-environmental distance function (DEED) which accounts for the production of both desirable and undesirable output and the potential for constrained increases in input utilization. This research applies the modeling framework to analyze the potential to reduce noise and airborne pollutants emitted by aircraft–engine combinations given the current state of aeronautical technology. The global aircraft–engine market is viewed from the regulatory perspective in order to compare the single environmental and operational efficient frontier to that of the airline carriers, and environmental objectives. The results of DEED are then applied in order to substitute the fleets serving Schipol, Amsterdam and Arlanda, Stockholm airports in June 2010 with the benchmark aircraft. The results highlight the inefficiencies of the current airline fleets and that the IPCC values of externalities are a magnitude of TEN too low to encourage changes in the global fleet hence the need for government intervention.     

A methodology to control urban traffic noise under the constraint of environmental capacity: A case study of a double-decision optimization model

This paper presents a novel methodology to control urban traffic noise under the constraint of environmental capacity. Considering the upper limits of noise control zones as the major bottleneck to control the maximum traffic flow is a new idea. The urban road network traffic is the mutual or joint behavior of public self-selection and management decisions, so is a typical double decision optimization problem.The proposed methodology incorporates theoretically model specifications. Traffic noise calculation model and traffic assignment model for O–D matrix are integrated based on bi-level programming method which follows an iterated process to obtain the optimal solution. The upper level resolves the question of how to sustain the maximum traffic flow with noise capacity threshold in a feasible road network. The user equilibrium method is adopted in the lower layer to resolve the O–D traffic assignment.The methodology has been applied to study area of QingDao, China. In this illustrative case, the noise pollution level values of optimal solution could satisfy the urban environmental noise capacity constraints. Moreover, the optimal solution was intelligently adjusted rather than simply reducing the value below a certain threshold. The results indicate that the proposed methodology is feasible and effective, and it can provide a reference for a sustainable development and noise control management of the urban traffic.     

Evaluation of variable speed limits to improve traffic safety

This paper examines automated control strategies of variable speed limits that aim at reducing crash potential on instrumented freeways. A real-time crash prediction model was developed to estimate crash potential based on short-term variation of traffic flow characteristics. A microscopic traffic simulation model was used to realistically simulate changes in traffic conditions as an effect of variable speed limits and combined with the crash prediction model for the evaluation of control logics. Within this integrated evaluation framework, the study investigated the effect of strategy control factors on the crash potential reduction and total travel time. The study results indicated that variable speed limits could reduce crash potential by 5–17%, by temporarily reducing speed limits during risky traffic conditions when crash potential exceeded the pre-specified threshold.     

Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration

This paper studies the heterogeneous energy cost and charging demand impact of autonomous electric vehicle (EV) fleet under different ambient temperature. A data-driven method is introduced to formulate a two-dimensional grid stochastic energy consumption model for electric vehicles. The energy consumption model aids in analyzing EV energy cost and describing uncertainties under variable average vehicle trip speed and ambient temperature conditions. An integrated eco-routing and optimal charging decision making framework is designed to improve the capability of autonomous EV’s trip level energy management in a shared fleet. The decision making process helps to find minimum energy cost routes with consideration of charging strategies and travel time requirements. By taking advantage of derived models and technologies, comprehensive case studies are performed on a data-driven simulated transportation network in New York City. Detailed results show us the heterogeneous energy impact and charging demand under different ambient temperature. By giving the same travel demand and charging station information, under the low and high ambient temperature within each month, there exist more than 20% difference of overall energy cost and 60% difference of charging demand. All studies will help to construct sustainable infrastructure for autonomous EV fleet trip level energy management in real world applications.     

Geographical unit based analysis in the context of transportation safety planning

A wide array of spatial units has been explored in macro-level modeling. With the advancement of Geographic Information System (GIS) analysts are able to analyze crashes for various geographical units. However, a clear guideline on which geographic entity should be chosen is not present. Macro level safety analysis is at the core of transportation safety planning (TSP) which in turn is a key in many aspects of policy and decision making of safety investments. The preference of spatial unit can vary with the dependent variable of the model. Or, for a specific dependent variable, models may be invariant to multiple spatial units by producing a similar goodness-of-fits. In this study three different crash models were investigated for traffic analysis zones (TAZs), block groups (BGs) and census tracts (CTs) of two counties in Florida. The models were developed for the total crashes, severe crashes and pedestrian crashes in this region. The primary objective of the study was to explore and investigate the effect of zonal variation (scale and zoning) on these specific types of crash models. These models were developed based on various roadway characteristics and census variables (e.g., land use, socio-economic, etc.).It was found that the significance of explanatory variables is not consistent among models based on different zoning systems. Although the difference in variable significance across geographic units was found, the results also show that the sign of the coefficients are reasonable and explainable in all models.Key findings of this study are, first, signs of coefficients are consistent if these variables are significant in models with same response variables, even if geographic units are different. Second, the number of significant variables is affected by response variables and also geographic units.Admittedly, TAZs are now the only traffic related zone system, thus TAZs are being widely used by transportation planners and frequently utilized in research related to macroscopic crash analysis. Nevertheless, considering that TAZs are not delineated for traffic crash analysis but they were designed for the long range transportation plans, TAZs might not be the optimal zone system for traffic crash modeling at the macroscopic level. Therefore, it recommended that other zone systems be explored for crash analysis as well.     

Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars

Recently, policy makers’ expectations about the role of electric cars in reducing emissions have risen substantially. In parallel, academic research on purchase intentions has dramatically increased. Originally, most studies have focused on utility attributes and price. More recently, several hybrid choice models have been estimated to include the impact of attitudes on choice probabilities. In addition, a few studies have caught the attention to social influence. In contributing to this line of research, this paper reports the results of an expanded hybrid choice, which simultaneously estimated all these different effects in a single integrated model of purchase intention. Results indicate that the model performs well. Costs considerations contribute most to the utility of electric cars. Social influence is less important, but there is also evidence that people tend to take it into consideration when there are positive public opinions about electric cars and the market share becomes almost half of friends of their social network. The intention to purchase an electric car is also influenced by attitudes about environmental concerns and technology acceptance.     

Estimation of road traffic noise emissions: The influence of speed and acceleration

This paper relies on vehicle trajectory collection on a corridor, to compare different traffic representations used for the estimation of the sound power of light vehicles and the resulting sound pressure levels. Four noise emission models are tested. The error introduced when the emissions are calculated based on speeds measured at regular intervals along the road network are quantified and explained. The current noise emission models might in particular misestimate noise levels under congestion. This bias can be reduced by introducing additional traffic variables in the modeling. In addition, significant differences within the models are highlighted, especially concerning their accounting of vehicle accelerations. Models that rely on a binary representation of acceleration regimes (a vehicle or a road segment is accelerating or not) can lead to errors in practice. Models under use in Europe have a very low sensitivity to acceleration values. These results help underlying the further required improvements of dynamic road traffic noise models.     

Modelling Externalities using Dynamic Traffic Assignment Models: A Review

Recently, there has been a growing interest in externalities in our society, mainly in the context of climate and air quality, which are of importance when policy decisions are made. For the assessment of externalities in transport, often the output of static traffic assignment models is used in combination with so-called effect models. Due to the rapidly increasing possibilities of using dynamic traffic assignment (DTA) models for large-scale transportation networks and the application of traffic measures, already several models have been developed to assess the externalities using DTA models more precisely. Different research projects have shown that there is a proven relation between the traffic dynamics and externalities, such as emissions of pollutants and traffic safety. This means that the assessment of external effects can be improved by using temporal information about flow, speed and density, which is the output of DTA models. In this paper, the modelling of traffic safety, emissions and noise in conjunction with DTA models is reviewed based on an extensive literature survey. This review shows that there are still gaps in knowledge in assessing traffic safety, much research is available concerning emissions, and although little research has been conducted concerning the assessment of noise using DTA models, the methods available can be used to assess the effects. Most research so far has focused on the use of microscopic models, while mesoscopic or macroscopic models may have a high potential for improving the assessment of these effects for larger networks.     

How the environmental impact affects the design of logistics networks based on cost minimization

The degree of centralization of the logistics network is one of the important strategic decisions to take. This issue has often been studied but mainly from a cost minimization focus. This research studies the influence of incorporating the environmental impact in logistics network design models, comparing the results with those obtained considering cost minimization only. A fuzzy biobjective optimization model is used to carry out a number of experiments. By weighting the relative importance of the two objectives, the differences with respect to the base cost minimization solution can be ascertained. Our results show that in general more material is moved through warehouses when the environmental impact is considered and more decentralized facilities are opened.     

Highway traffic noise effects on land price in an urban area

The study evaluates the monetary effect of traffic noise on property values in Seoul, Korea. Hedonic price models are estimated using the zone-based data that includes traffic noise levels, official land price, land use classification, distance to roadways, type of nearby roadway facilities, and traffic characteristics. It is found that a 1% increase in traffic noise associated with a 1.3% decline in land price. Based on this, the annual cost per kilometer due to traffic noise is about $347 thousand.     

A traffic noise model for road intersections in the city of Cartagena de Indias,Colombia

Road traffic noise models are fundamental tools for designing and implementing appropriate prevention plans to minimize and control noise levels in urban areas. The objective of this study is to develop a traffic noise model to simulate the average equivalent sound pressure level at road intersections based on traffic flow and site characteristics, in the city of Cartagena de Indias (Cartagena), Colombia. Motorcycles are included as an additional vehicle category since they represent more than 30% of the total traffic flow and a distinctive source of noise that needs to be characterized. Noise measurements are collected using a sound level meter Type II. The data analysis leads to the development of noise maps and a general mathematical model for the city of Cartagena, Colombia, which correlates the sound levels as a function of vehicle flow within road intersections. The highest noise levels were 79.7 dB(A) for the road intersection María Auxiliadora during the week (business days) and 77.7 dB(A) for the road intersection India Catalina during weekends (non-business days). Although traffic and noise are naturally related, the intersections with higher vehicle flow did not have the highest noise levels. The roadway noise for these intersections in the city of Cartagena exceeds current limit standards. The roadway noise model is able to satisfactorily predict noise emissions for road intersections in the city of Cartagena, Colombia.