Information integration in a smart city system—a case study on air pollution removal by green infrastructure through a vehicle smart routing system

peer reviewedOver the past few years, the "smart city" concept has emerged as a new trend to answer challenging issues related to urban development. Transformation of a city system into a smart system is meant to improve the quality of life for its people and their way of living, its environment, economy, transport, and governance. Due to benefits associated with the concept of the smart city and associated implementation challenges, traditional city systems have been undergoing transformation into smart city systems. However, observed approaches of transformation presented disconnected and fragmented city systems that usually hamper the interaction of city subsystems with the efficient and environmentally friendly urban environment. This work emphasizes the systematic view of a city system and proposes a novel method of smart city system integration. The results of our study show that in a smart city environment, where ecosystem services are valorised, air pollution emitted by vehicles can be removed by taking into consideration information related to air pollution reduction. A case study is presented to demonstrate that, with an integrated system, information outputs on travel decisions are different and more valuable. The case study explores the operability of the system, its limitations, and potential future improvements

Quantifying road traffic emissions embedded in a multi-objective traffic assignment model

In a road network, drivers typically seek to minimize their own travel time, often affecting system-wide performance. With the increasing environmental awareness, for an efficient traffic assignment (TA), besides concerns with travel times, traffic managers should not neglect the system-wide level of both global and local pollutant emissions. Measuring road traffic emissions can be costly and different models based on vehicle-specific parameters with many input variables have been suggested in the literature. This paper proposes a simple way to quantifying carbon dioxide (CO2) and nitrogen oxides (NOX) emissions with only average speed as input variable and presents a multi-objective TA approach that seeks to minimize system-wide travel time, distance travelled (associated with fuel consumption) and global and local pollutant emissions. A real-world case study on an intercity corridor with many alternative routes between two zones is presented. Experiments considering TA based on travel time, and on time, distance travelled, and pollutant emissions are reported. Results highlight that system optimal distribution based on the suggested multi-objective TA based on three components yields savings in terms of distance travelled (2.6%) and emissions (1.3% for CO2 and 1.1% for NOX), but penalizes travel time 3%, which is translated in an increase of 20sec per vehicle, when compared to the solution only focused on minimizing travel time. The developed methodology is a suitable tool for traffic analysts to predict vehicle system-wide travel time, distance travelled and pollutant emissions with few vehicle information but with a reasonable detail for a specific traffic flow on a given road network, to support analyses for sustainable transport policies and may be used, for instance, as an environmental impact component of a pricing scheme, traffic signal control strategies based on emissions reduction, or to minimize congestion by giving prior information to drivers on the specific routes to be chosen.publishe

Advanced impact integration platform for cooperative road use

In order to improve networks efficiency, a considerable number of studies has been addressing the potential of eco-friendly assignment solutions as alternative approaches to reduce emissions and/or fuel use. So far the majority of studies generally assumes that the most eco-friendly solutions are the ones that minimize the absolute amount of emissions produced along a certain trip. In this work a platform based on both empirical GPS data and microscopic simulation models of traffic, emissions, noise, and road safety was developed to examine in depth 4 routes of an origin-destination pair over a Portuguese city. In addition to the integrated externalities assessment based on state of the art techniques, a novelty of this work was the preliminary inclusion of social criteria in defining sustainable assignment solutions. This paper provides new insights about sustainable traffic management issues and addresses multiple novel route choice indicators. Specifically we found that the relative variation of the individual costs and total pollution produced among 4 routes varies to a factor of 1.4 while the variation of the potentially exposed population ranges up to a factor of 10. The main results confirm the need to take into account real-time urban activity patterns in order to effectively implement sustainable traffic management measures

Every breath you take. Every freight you make: environmental pollution index for road transportation

Goal: This study analyzes the impacts of the transportation sector on air pollution within the scope of one major Brazilian metropolitan region. Design / Methodology / Approach: A literature review was conducted on the subject's constructs, with subsequent reasoning grounded on the fleet's characteristics and data obtained from in-depth interviews from a government transportation agency. Results: The results show Brazil's contextual evidence that risk management for the haulage sector should consider air pollution's negative impacts. With air quality standards as an essential reference, it is possible to observe that the city of Uberlândia does not effectively manage air quality. Limitations of investigation: One limitation of this research is related to the representativeness of the sample. The research also recommends future studies to use government policies for the improvement of the framework. Practical implications: The local and contextual addressing of air pollution and transport correlation in one focal point for cargo transportation at a national level pontentially contributes to environmental public policies. Originality / Value: Originality value resides in considering emissions from cargo vehicles as a significant factor in this process of air pollution in a specific context of a metropolitan area of an emerging economy that has its transportation modal grounded on trucking freight

Modeling the relationship between air quality and intelligent transportation system (ITS) with artificial neural networks.

Environmental or air quality impacts of Intelligent Transportation Systems (ITS) are very difficult to measure. Some researchers have attempted to quantify the effects of individual ITS application on emissions; yet, the effects of ITS as a whole on ambient air quality have not been investigated. The objective of this research was to model the relationship between ITS and ambient air quality. The multiple Artificial Neural Networks (ANN) training with the data yielded a model for predicting the air quality. In addition, the ANN made the measurement of the effect of ITS on air quality possible. Data pertaining to sixty US cities (urbanized area) were used for this research. Input variables used were related to transportation and local characteristics, and ITS applications. Output variables were the annual average concentrations of CO, Ozone, and N02 in ambient air. The K-fold cross validation technique was used to train the ANN. The results of ANN model were compared with that of a Multiple Regression (MR) model showing the supremacy of ANN over MR. The ANN model results show that the Mean Absolute Errors (MAEs) in prediction vary from 5 to 20 %. This variance is justified since the factors related with industries, which contribute significantly to air pollution, have not been taken into consideration in this study. There were some unusual findings: in contrast to the common assumptions, N02 concentration increases with ITS intensity, and Ground Level Ozone concentration, in ambient air, seemed to be more transportation-dependent as compared with that of CO and N02• A recommendation for further research on this topic is to include more input variables, especially those which are relatcd with industries, to improve the accuracy of prediction. Scientific experimentations have also been recommended to corroborate the unusual findings

Plataforma de informação de tráfego para redução de consumos e emissões

Doutoramento em Engenharia MecânicaApesar das recentes inovações tecnológicas, o setor dos transportes continua a exercer impactes significativos sobre a economia e o ambiente. Com efeito, o sucesso na redução das emissões neste setor tem sido inferior ao desejável. Isto deve-se a diferentes fatores como a dispersão urbana e a existência de diversos obstáculos à penetração no mercado de tecnologias mais limpas. Consequentemente, a estratégia “Europa 2020” evidencia a necessidade de melhorar a eficiência no uso das atuais infraestruturas rodoviárias. Neste contexto, surge como principal objetivo deste trabalho, a melhoria da compreensão de como uma escolha de rota adequada pode contribuir para a redução de emissões sob diferentes circunstâncias espaciais e temporais. Simultaneamente, pretende-se avaliar diferentes estratégias de gestão de tráfego, nomeadamente o seu potencial ao nível do desempenho e da eficiência energética e ambiental. A integração de métodos empíricos e analíticos para avaliação do impacto de diferentes estratégias de otimização de tráfego nas emissões de CO2 e de poluentes locais constitui uma das principais contribuições deste trabalho. Esta tese divide-se em duas componentes principais. A primeira, predominantemente empírica, baseou-se na utilização de veículos equipados com um dispositivo GPS data logger para recolha de dados de dinâmica de circulação necessários ao cálculo de emissões. Foram percorridos aproximadamente 13200 km em várias rotas com escalas e características distintas: área urbana (Aveiro), área metropolitana (Hampton Roads, VA) e um corredor interurbano (Porto-Aveiro). A segunda parte, predominantemente analítica, baseou-se na aplicação de uma plataforma integrada de simulação de tráfego e emissões. Com base nesta plataforma, foram desenvolvidas funções de desempenho associadas a vários segmentos das redes estudadas, que por sua vez foram aplicadas em modelos de alocação de tráfego. Os resultados de ambas as perspetivas demonstraram que o consumo de combustível e emissões podem ser significativamente minimizados através de escolhas apropriadas de rota e sistemas avançados de gestão de tráfego. Empiricamente demonstrou-se que a seleção de uma rota adequada pode contribuir para uma redução significativa de emissões. Foram identificadas reduções potenciais de emissões de CO2 até 25% e de poluentes locais até 60%. Através da aplicação de modelos de tráfego demonstrou-se que é possível reduzir significativamente os custos ambientais relacionados com o tráfego (até 30%), através da alteração da distribuição dos fluxos ao longo de um corredor com quatro rotas alternativas. Contudo, apesar dos resultados positivos relativamente ao potencial para a redução de emissões com base em seleções de rotas adequadas, foram identificadas algumas situações de compromisso e/ou condicionantes que devem ser consideradas em futuros sistemas de eco navegação. Entre essas condicionantes importa salientar que: i) a minimização de diferentes poluentes pode implicar diferentes estratégias de navegação, ii) a minimização da emissão de poluentes, frequentemente envolve a escolha de rotas urbanas (em áreas densamente povoadas), iii) para níveis mais elevados de penetração de dispositivos de eco-navegação, os impactos ambientais em todo o sistema podem ser maiores do que se os condutores fossem orientados por dispositivos tradicionais focados na minimização do tempo de viagem. Com este trabalho demonstrou-se que as estratégias de gestão de tráfego com o intuito da minimização das emissões de CO2 são compatíveis com a minimização do tempo de viagem. Por outro lado, a minimização de poluentes locais pode levar a um aumento considerável do tempo de viagem. No entanto, dada a tendência de redução nos fatores de emissão dos poluentes locais, é expectável que estes objetivos contraditórios tendam a ser minimizados a médio prazo. Afigura-se um elevado potencial de aplicação da metodologia desenvolvida, seja através da utilização de dispositivos móveis, sistemas de comunicação entre infraestruturas e veículos e outros sistemas avançados de gestão de tráfego.Despite recent technological innovations, transportation sector is still producing significant impacts on the economy and environment. In fact, the success in reducing transportation emissions has been lower than desirable due to several factors such as the urban sprawl and several barriers to the market penetration of cleaner technologies. Therefore, the “Europe 2020” strategy has emphasised the relevance of improving the efficiency in the transportation networks through the better use of the existing infrastructures. In this context, the main objective of this thesis is increasing the understanding of how proper route choices can contribute to reduce emissions output over different spatial and temporal contexts. Simultaneously, it is intended to evaluate the potential of different traffic management strategies in terms of traffic performance and energy/environmental efficiency. The integration of empirical and analytical methods to assess the impact of different traffic optimization strategies on CO2 emissions and local pollutants constitutes one the main contributions of this work. This thesis has been divided in two main parts. The first is predominantly empirical, using field data as the main source of information. Using GPS equipped vehicles, empirical data for approximately 13200 km of road coverage have been collected to estimate energy and emissions impacts of route choice in three different scenarios: a medium-sized urban area (Aveiro), a metropolitan area (Hampton Roads, VA) and an intercity corridor (Oporto-suburban area). The second part, predominantly analytical, is essentially based on the output of traffic simulators and optimization models. The analytical component was based on the capability of microscopic traffic models to generate detailed emissions information and to generate link-based performance functions. Then, different traffic management strategies were tested to evaluate road networks in terms of traffic performance and emissions. Both outcomes of the empirical and analytical approaches have demonstrated that fuel use and emissions impacts can also be significantly reduced through appropriate route choices and advanced traffic management systems. The empirical assessment of route choice impacts has shown that both during off peak and peak periods, the selection of an appropriate route can lead to significant emissions reduction. Depending on the location, potential emissions savings of CO2 up to 25% and local pollutants up to 60% were found. The analytical approach has demonstrated that it is possible to significantly reduce system environmental costs (30%) by modifying traffic flow distribution along a corridor with 4 alternative routes. However, despite the positive results in terms of the potential for emissions reduction based on appropriate route choices, a number of important trade-offs that need to be considered in future implementations of eco-routing systems. Among these trade-offs it is worth noting that: i) different pollutants may lead to different ecorouting strategies, ii) the minimization of pollutants emissions often involves choosing urban routes (densely populated), iii) for higher penetration levels of eco-routing devices considering local pollutants, system environmental impacts can be higher than if drivers were guided under the traditional devices focused on travel time. With this research, it has been demonstrated that road traffic management strategies focused on minimizing CO2 emissions and fuel consumption can be compatible with the minimization of system travel time. On the other hand the minimization of local pollutants may lead to considerable increases in travel time. However, given the trend rate of reduction in the emissions factors of local pollutants, it is expected that such trade-offs would tend to be minimized in medium term. Thus, the developed methodology has great potential for further real life application, either through the use of nomadic devices, infrastructures to vehicle communication or different advanced traffic management systems

A dynamic link-based eco-indicator for supporting equitable traffic management strategies

This paper presents a methodology for building a link-based eco-indicator which includes different impacts of road traffic. The proposed traffic management tool can be updated in real-time through multiple information sources and translated into a cost factor to be straightforwardly applied into eco-routing algorithms and/or intelligent road pricing systems. The link-based eco-indicator has been tested in several urban and rural links of heterogeneous characteristics during peak and off-peak hours. It has been shown that both dynamic adjustment factors related to online background concentrations and/or citizen's activity may lead to different sustainable traffic management strategies. When evaluating and comparing costs of a single link-based eco-based indicator with National Average (without taking in account people exposure) and a Vulnerability Factor (VF), the total costs using VF increase 158%. In the origin-destination routing problem performed using the distance and travel time as criteria, the costs (for off-peak hours) using VF factor are 80% and 15% higher, respectively. The results achieved in this paper highlight the importance of taking into account vulnerability of people exposure when implementing eco traffic management measures.publishe

Ultrafine Particle Levels Monitored at Different Transport Modes in Lisbon

Ultrafine particles (UFP) are defined as particulate matter with a diameter smaller than 0.1 μm. Because of their reduced size and consequently very low mass, they are usually expressed in particle number concentration (PNC), in particles per cubic centimetre (pt.cm-3). There have been growing evidences that long-term exposure to UFP may induce or aggravate pulmonary and cardio-respiratory health conditions and are linked to increased hospitalization and mortality rates. More recently, they have also been linked to neurological diseases and to children cognitive development issues. Airports, road traffic and maritime transport have been identified as significant sources of ultrafine particulate matter. There is lack of information regarding PNC in the vicinity of airports. In the case of Lisbon Airport (LA), located within the city and surrounded by housing areas, offices, schools, hospitals and sport and recreational complexes, knowing their levels assumes vital relevance. In-land passenger ferries are also a source of UFP, far less addressed. A significant fraction of a person's total daily exposure to fine and ultrafine particles occurs during home-work commuting periods. Therefore, microenvironments influenced by different transport modes are particularly relevant. Thus, to associate their contribution with to UFP concentrations is important and allows the estimation of their contribution to air quality degradation within the city and the degree of population exposure. This work aims to assess the effect on UFP concentrations from road, air and river traffic modes, in Lisbon. UFP monitoring campaigns were carried out between July 2017 and December 2018, for a 36 nonconsecutive days period, complying approximately 160 hours of suitable measurements. Concerning road traffic, three sites were chosen with different traffic patterns, vehicle circulation, legal restrictions and different flow intensity of pedestrians close-by. Regarding air traffic, the monitoring network was designed to include several sampling sites in the vicinity of LA and a set of sites further away, under the landing and take-off path. Finally, to assess the in-land ferries-related UFP levels, the sampling sites were chosen in order to maximize measurements under downwind conditions and allow the association between ferry operations and PNC response. Based on the information collected, the obtained levels were analysed and several statistical analysis were performed, particularly searching for correlations between UFP concentrations and the three different traffic activity modes. Concerning road traffic, in Av. da Liberdade, results show high peak values of 1-minute PNC mean (up to 75 x 103 pt.cm-3). This avenue (downtown, in the most striker Low Emission Zone (LEZ1)) presents the higher PNC levels and dispersion (18.2 ± 13.2 x 103 pt.cm-3) followed by a highspeed road (2nd Circular, 15.0 ± 12.2 x 103 pt.cm-3). The lowest values were found at an interception close to LEZ2 boundary (Entrecampos, 10.3 ± 5.1 x 103 pt.cm-3). Moreover, the results of analysis of variance (ANOVA) show that PNC levels are statistically different among the sampled locations. Results suggest that PNC are strongly dependent on the type and age of vehicles: light-duty vehicles, taxis and buses. PNC peak values were mainly associated with vehicles prior to the Euro 3/III Standard. Finally, results show a strong positive correlation, statistically significant, between hourly mean values of PNC and PM10 (r = 0.76, p < 0.01) and a moderate positive correlation between PNC and nitrogen oxides (r coefficients of 0.55, 0.51 and 0.59, with all p-values lower than 0.01, for NO, NO2: and NOx, respectively). Regarding air traffic, results show the occurrence of high UFP concentrations in LA vicinity. Considering 10-minutes means, the particle counting increases by 18 to 26-fold at downwind locations near the airport, and by 4-fold at locations up to 1 km distance to LA. Results show that particle number increases with the number of flights and decreases with the distance to LA. Finally, concerning ferries, data show that UFP emitted contributes to PNC increase in the surrounding area. Results show an increase in PNC, ranging from 25 to 197% during the third minute before an arrival or departure of a ship, with moderate to positive correlations, statistically significant, between PNC values and the number of ferry operations (r = 0.79 to r = 0.94). Moreover, negative correlations (r = -0.85 to r = -0.93) between PNC and wind intensity were also found. This work, based on Lisbon study-case, show that people working, living or spending a considerable amount of time close to intense traffic roads, nearby the airport or close to ferries’ stations or downwind to their cruising path are exposed to high UFP concentrations with a magnitude which may lead to considerable health risks