Methodologies to measure and to manage the decarbonisation of road transport: the case of Spain

El sector del transporte por carretera es uno de los principales contribuyentes de consumo de combustible y emisiones de España. Por lo tanto, la evaluación de los impactos ambientales del tráfico rodado es esencial para los programas de mitigación del cambio climático y la eficiencia energética. Sin embargo, uno de los retos en la planificación del transporte y el diseño de políticas consiste en la aplicación de metodologías de evaluación de emisiones consistentes, el diseño de estrategias y la evaluación de su eficacia. Las metodologías existentes de evaluación de las emisiones del transporte por carretera, utilizan diferentes niveles de análisis y períodos. Sin embargo, estos análisis son puntuales y no existe una continuidad en el análisis de diferentes estrategias o políticas. Esta tesis doctoral proporciona conocimientos y herramientas para el análisis de las políticas destinadas a reducir las emisiones de tráfico, tomando España como caso de estudio. La investigación se estructura en dos partes: i) el desarrollo y aplicación de metodologías para el análisis de factores y políticas que contribuyen en la evolución de las emisiones GEI del transporte por carretera en España; desde una perspectiva nacional; y ii) el desarrollo y aplicación de un marco metodológico para estimar las emisiones del tráfico interurbano y de evaluar estrategias centradas en la operación del tráfico y en la infraestructura. En resumen, esta tesis demuestra la idoneidad de utilizar diferentes herramientas para analizar las emisiones de tráfico desde diferentes puntos de vista. Desde el diseño de políticas de mitigación y eficiencia energética a nivel nacional, a estrategias centradas en la operación del tráfico interurbano y la infraestructura. Road transport is one of the major contributors to fuel consumption and emissions in Spain. Consequently, assessing the environmental impacts of road traffic is essential for climate change mitigation and energy efficiency programs. However, one of the key challenges of policy makers and transport planners consists of implementing consistent assessment emissions methodologies, applying mitigation strategies, and knowing their effectiveness. Current state-of-the-art emissions assessment methodologies estimate emissions from different levels and periods, using different approaches. Nevertheless, these studies are timely and they usually take different methodologies for analysing different strategies or policies, regardless of the assessment as a whole. This doctoral thesis provides knowledge and methodologies for analysing policies designed to reduce road traffic emissions, using the case study of Spain. The research procedure consists of two main scopes: i) the development and application of methodologies for analysing key factors and policies driving the GHG emissions of road transport in Spain; from a national perspective; and ii) the development and application of a road traffic emissions model for assessing operational and infrastructure strategies of the interurban road network at segment level. In summary, this thesis demonstrates the appropriateness to use different tools to analyse road traffic emissions at different levels: from appropriate nationwide mitigation and energy efficiency policies, to strategies focused on the operation of interurban traffic and infrastructure.

Development and assessment of traffic-related emission abatement measures for the Madrid city (Spain) through the WRF-SMOKE-CMAQ modelling system

The achievement of the limit values established in the European legislation pose an important handicap for large urban areas with intense road traffic, such as Madrid (Spain). Despite permanent measures included in air quality plans it is important to assess additional measures that may be temporally applied under unfavourable conditions. This paper reports on the simulation of different traffic restriction strategies in Madrid for high-pollution episodes.

Understanding how to reduce road transport emissions : modelling the impact of eco-driving

Entre los problemas medioambientales más trascendentales para la sociedad, se encuentra el del cambio climático así como el de la calidad del aire en nuestras áreas metropolitanas. El transporte por carretera es uno de los principales causantes, y como tal, las administraciones públicas se enfrentan a estos problemas desde varios ángulos: Cambios a modos de transporte más limpios, nuevas tecnologías y combustibles en los vehículos, gestión de la demanda y el uso de tecnologías de la información y la comunicación (ICT) aplicadas al transporte. En esta tesis doctoral se plantea como primer objetivo el profundizar en la comprensión de cómo ciertas medidas ICT afectan al tráfico, las emisiones y la propia dinámica de los vehículos. El estudio se basa en una campaña de recogida de datos con vehículos flotantes para evaluar los impactos de cuatro medidas concretas: Control de velocidad por tramo, límites variables de velocidad, limitador de velocidad (control de crucero) y conducción eficiente (eco‐driving). Como segundo objetivo, el estudio se centra en la conducción eficiente, ya que es una de las medidas que más ahorros de combustible presenta a nivel individual. Aunque estas reducciones están suficientemente documentadas en la literatura, muy pocos estudios se centran en estudiar el efecto que los conductores eficientes pueden tener en el flujo de tráfico, y cuál sería el impacto si se fuera aumentando el porcentaje de este tipo de conductores. A través de una herramienta de microsimulación de tráfico, se han construido cuatro modelos de vías urbanas que se corresponden con una autopista urbana, una arteria, un colector y una vía local. Gracias a los datos recogidos en la campaña de vehículos flotantes, se ha calibrado el modelo, tanto el escenario base como el ajuste de parámetros de conducción para simular la conducción eficiente. En total se han simulado 72 escenarios, variando el tipo de vía, la demanda de tráfico y el porcentaje de conductores eficientes. A continuación se han calculado las emisiones de CO2 and NOx mediante un modelo de emisiones a nivel microscópico. Los resultados muestran que en escenarios con alto porcentaje de conductores eficientes y altas demandas de tráfico las emisiones aumentan. Esto se debe a que las mayores distancias de seguridad y las aceleraciones y frenadas suaves hacen que aumente la congestión, produciendo así mayores emisiones a nivel global. Climate change and the reduced air quality in our metropolitan areas are two of the main environmental problems that the society is addressing currently. Being road transportation one of the main contributors, public administrations are facing these problems from different points of view: shift to cleaner modes, new fuels and vehicle technologies, demand management and the use of information and communication technologies (ICT) applied to transportation. The first objective of this thesis is to understand how certain ICT measures affect traffic, emissions and vehicle dynamics. The study is based on a data collection campaign with floating vehicles to evaluate the impact of four specific measures: section speed control, variable speed limits, cruise control and eco‐driving. The second objective of the study focuses on eco‐driving, as it is one of the measures that present the largest fuel savings at an individual level. Although these savings are well documented in the literature, few studies focus on how ecodrivers affect the surrounding vehicles and the traffic, and what would be the impact in case of different eco‐drivers percentage. Using a traffic micro‐simulation tool, four models in urban context have been built, corresponding to urban motorway, urban arterial, urban collector and a local street. Both the base‐case and the parameters setting to simulate eco‐driving have been calibrated with the data collected through floating vehicles. In total 72 scenarios were simulated, varying the type of road, traffic demand and the percentage of eco‐drivers. Then, the CO2 and NOx emissions have been estimated through the use of an emission model at microscopic level. The results show that in scenarios with high percentage of co‐drivers and high traffic demand the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.

Measuring the global burden of disease and epidemiological transitions: 2002-2030

Any planning process for health development ought to be based on a thorough understanding of the health needs of the population. This should be sufficiently comprehensive to include the causes of premature death and of disability, as well as the major risk factors that underlie disease and injury. To be truly useful to inform health-policy debates, such an assessment is needed across a large number of diseases, injuries and risk factors, in order to guide prioritization. The results of the original Global Burden of Disease Study and, particularly, those of its 2000-2002 update provide a conceptual and methodological framework to quantify and compare the health of populations using a summary measure of both mortality and disability: the disability-adjusted life-year (DALY). Globally, it appears that about 5 6 million deaths occur each year, 10. 5 million (almost all in poor countries) in children. Of the child deaths, about one-fifth result from perinatal causes such as birth asphyxia and birth trauma, and only slightly less from lower respiratory infections. Annually, diarrhoeal diseases kill over 1.5 million children, and malaria, measles and HIV/AIDS each claim between 500,000 and 800,000 children. HIV/AIDS is the fourth leading cause of death world-wide (2.9 million deaths) and the leading cause in Africa. The top three causes of death globally are ischaemic heart disease (7.2 million deaths), stroke (5.5 million) and lower respiratory diseases (3.9 million). Chronic obstructive lung diseases (COPD) cause almost as many deaths as HIV/AIDS (2.7 million). The leading causes of DALY, on the other hand, include causes that are common at young ages [perinatal conditions (7. 1 % of global DALY), lower respiratory infections (6.7%), and diarrhoeal diseases (4.7%)] as well as depression (4.1%). Ischaemic heart disease and stroke rank sixth and seventh, retrospectively, as causes of global disease burden, followed by road traffic accidents, malaria and tuberculosis. Projections to 2030 indicate that, although these major vascular diseases will remain leading causes of global disease burden, with HIV/AIDS the leading cause, diarrhoeal diseases and lower respiratory infections will be outranked by COPD, in part reflecting the projected increases in death and disability from tobacco use.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

A Framework for Spatial Road Safety Assessment: Case Study of Northern Ireland

Road traffic injuries are a major health issue worldwide. There are many factors that can
affect the levels of road traffic collisions which in turn increase the levels of people killed or
seriously injured. When road traffic collisions occur, observed facts are recorded in relation
to the incident. These facts are recorded as variable observations, and for this study,
variables and indicators are defined almost equivalently. There can be hundreds of different
indicators for the various collisions, as different countries face different road situations. This
makes it difficult to perform a road safety assessment, which can be applied globally. The
goal of this study is to select the most appropriate indicators and create a composite
indicator as a function of these indicators, which can be used as summary values, allowing
ease of comparisons between the countries/regions that have undergone a road safety
assessment. The composite indicator will then be used to assess the current situation in
Northern Ireland and provide scores for ranking policing in terms of overall road safety on
their road networks.

Strategies for Integrated Traffic Control.

This paper begins with a short review of the current state of integrated traffic control. This is followed by a summary of the main components for the Integrated Road Transport Environment (IRTE) and the role of the DRIVE II project HERMES, which aims at providing some of these components. The paper concludes with an outline of some scenarios for integrated traffic control operation.

Guidelines on building design and operation to minimize air quality impacts from major roads in transit oriented development

Poor air quality has a huge detrimental effect, both economic and on the quality of life, in Australia. Transit oriented design (TOD), which aims to minimise urban sprawl and lower dependency on vehicles, leads to an increasing number of buildings close to transport corridors. This project aims at providing guidelines that are appropriate to include within City Plan to inform future planning along road corridors, and provide recommendations on when mitigation measures should be utilised.

Decision - Support Software Tool Handbook

The road and transport industry in Australia and overseas has come a long way to understanding the impact of road traffic noise on the urban environment. Most road authorities now have guidelines to help assess and manage the impact of road traffic noise on noise-sensitive areas and development. While several economic studies across Australia and overseas have tried to value the impact of noise on property prices, decision-makers investing in road traffic noise management strategies have relatively limited historic data and case studies to go on. The perceived success of a noise management strategy currently relies largely on community expectations at a given time, and is not necessarily based on the analysis of the costs and benefits, or the long-term viability and value to the community of the proposed treatment options. With changing trends in urban design, it is essential that the 'whole-of-life' costs and benefits of noise ameliorative treatment options and strategies be identified and made available for decisionmakers in future investment considerations. For this reason, CRC for Construction Innovation Australia funded a research project, Noise Management in Urban Environments to help decision-makers with future road traffic noise management investment decisions. RMIT University and the Queensland Department of Main Roads (QDMR) have conducted the research work, in collaboration with the Queensland Department of Public Works, ARUP Pty Ltd, and the Queensland University of Technology. The research has formed the basis for the development of a decision-support software tool, and helped collate technical and costing data for known noise amelioration treatment options. We intend that the decision support software tool (DST) should help an investment decision-maker to be better informed of suitable noise ameliorative treatment options on a project-by-project basis and identify likely costs and benefits associated with each of those options. This handbook has been prepared as a procedural guide for conducting a comparative assessment of noise ameliorative options. The handbook outlines the methodology and assumptions adopted in the decision-support framework for the investment decision-maker and user of the DST. The DST has been developed to provide an integrated user-friendly interface between road traffic noise modelling software, the relevant assessment criteria and the options analysis process. A user guide for the DST is incorporated in this handbook.

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

The Brisbane Cordon scheme : part A - preliminary investigation

It could be said that road congestion is one of the most significant problems within any modern metropolitan area. For several decades now, around the globe, congestion in metropolitan areas has been worsening for two main reasons. Firstly, road congestion has significantly increased due to a higher demand for road space because of growth in populations, economic activity and incomes (Hensher & Puckett, 2007). This factor, in conjunction with a significant lack of investment in new road and public transport infrastructure, has seen the road network capacities of cities exceeded by traffic volumes and thus, resulted in increased traffic congestion. This relentless increase in road traffic congestion has resulted in a dramatic increase in costs for both the road users and ultimately the metropolitan areas concerned (Bureau of Transport and Regional Economics, 2007). In response to this issue, several major cities around the world, including London, Stockholm and Singapore, have implemented congestion-charging schemes in order to combat the effects of road congestion. A congestion-charging scheme provides a mechanism for regulating traffic flows into the congested areas of a city, whilst simultaneously generating public revenue that can be used to improve both the public transport and road networks of the region. The aim of this paper was to assess the concept of congestion-charging, whilst reflecting on the experiences of various cities that have already implemented such systems. The findings from this paper have been used to inform the design of a congestion-charging scheme for the city of Brisbane in Australia in a supplementary study (Whitehead, Bunker, & Chung, 2011). The first section of this paper examines the background to road congestion; the theory behind different congestion-charging schemes; and the various technologies involved with the concept. The second section of this paper details the experiences, in relation to implementing a congestion-charging scheme, from the city of Stockholm in Sweden. This research has been crucial in forming a list of recommendations and lessons learnt for the design of a congestion-charging scheme in Australia. It is these recommendations that directly inform the proposed design of the Brisbane Cordon Scheme detailed in Whitehead et al. (2011).

Investigation into the transport, behaviour and deposition of combustion aerosols from transport sources

The deterioration of air quality is a significant issue in large and growing cities. This work investigates particulate emissions from transport, the largest source of air pollution in cities today. Emitters such as busy roads and diesel trains are investigated, with specific reference to the evolution of particles over time and distance. Diesel trains are investigated as an alternative to road traffic in investigating evolutionary processes. Higher emissions and solitary sources mean that the emitted plume can be observed over time in a single location. These results represent the first investigation of the evolution of fine and ultrafine aerosol particles from this type of source. Aerosols near a busy road are investigated, with the result that a dependence of total number concentration on distance from the road is shown to be related to the fragmentation of nanoparticle clusters. Local meteorological conditions are also monitored and humidity is shown to vary with distance from the road in a nonmonotonic way. Particles from a busy road were also examined using a scanning electron microscope, with the intention of understanding the make up of the emitted aerosol plume. It was determined that due to significant surface behaviour post-deposition, this method of analysis could not directly classify airborne pollutants. Some interesting results were obtained however, particularly in terms of composite particles and the analysis of deposited patterns. This thesis introduces new work in terms of the analysis of diesel train particulate emissions, as well as adding further evidence towards the fragmentation process of aerosol evolution in both background concentrations and emitted aerosol plumes.

Efficient safety message dissemination for cooperative collision warning via context modelling

A Cooperative Collision Warning System (CCWS) is an active safety techno- logy for road vehicles that can potentially reduce traffic accidents. It provides a driver with situational awareness and early warnings of any possible colli- sions through an on-board unit. CCWS is still under active research, and one of the important technical problems is safety message dissemination. Safety messages are disseminated in a high-speed mobile environment using wireless communication technology such as Dedicated Short Range Communication (DSRC). The wireless communication in CCWS has a limited bandwidth and can become unreliable when used inefficiently, particularly given the dynamic nature of road traffic conditions. Unreliable communication may significantly reduce the performance of CCWS in preventing collisions. There are two types of safety messages: Routine Safety Messages (RSMs) and Event Safety Messages (ESMs). An RSM contains the up-to-date state of a vehicle, and it must be disseminated repeatedly to its neighbouring vehicles. An ESM is a warning message that must be sent to all the endangered vehi- cles. Existing RSM and ESM dissemination schemes are inefficient, unscalable, and unable to give priority to vehicles in the most danger. Thus, this study investigates more efficient and scalable RSM and ESM dissemination schemes that can make use of the context information generated from a particular traffic scenario. Therefore, this study tackles three technical research prob- lems, vehicular traffic scenario modelling and context information generation, context-aware RSM dissemination, and context-aware ESM dissemination. The most relevant context information in CCWS is the information about possible collisions among vehicles given a current vehicular traffic situation. To generate the context information, this study investigates techniques to model interactions among multiple vehicles based on their up-to-date motion state obtained via RSM. To date, there is no existing model that can represent interactions among multiple vehicles in a speciffic region and at a particular time. The major outcome from the first problem is a new interaction graph model that can be used to easily identify the endangered vehicles and their danger severity. By identifying the endangered vehicles, RSM and ESM dis- semination can be optimised while improving safety at the same time. The new model enables the development of context-aware RSM and ESM dissemination schemes. To disseminate RSM efficiently, this study investigates a context-aware dis- semination scheme that can optimise the RSM dissemination rate to improve safety in various vehicle densities. The major outcome from the second problem is a context-aware RSM dissemination protocol. The context-aware protocol can adaptively adjust the dissemination rate based on an estimated channel load and danger severity of vehicle interactions given by the interaction graph model. Unlike existing RSM dissemination schemes, the proposed adaptive scheme can reduce channel congestion and improve safety by prioritising ve- hicles that are most likely to crash with other vehicles. The proposed RSM protocol has been implemented and evaluated by simulation. The simulation results have shown that the proposed RSM protocol outperforms existing pro- tocols in terms of efficiency, scalability and safety. To disseminate ESM efficiently, this study investigates a context-aware ESM dissemination scheme that can reduce unnecessary transmissions and deliver ESMs to endangered vehicles as fast as possible. The major outcome from the third problem is a context-aware ESM dissemination protocol that uses a multicast routing strategy. Existing ESM protocols use broadcast rout- ing, which is not efficient because ESMs may be sent to a large number of ve- hicles in the area. Using multicast routing improves efficiency because ESMs are sent only to the endangered vehicles. The endangered vehicles can be identified using the interaction graph model. The proposed ESM protocol has been implemented and evaluated by simulation. The simulation results have shown that the proposed ESM protocol can prevent potential accidents from occurring better than existing ESM protocols. The context model and the RSM and ESM dissemination protocols can be implemented in any CCWS development to improve the communication and safety performance of CCWS. In effect, the outcomes contribute to the realisation of CCWS that will ultimately improve road safety and save lives.