A social media Data-Driven analysis for transport policy response to the COVID-19 pandemic outbreak in Wuhan, China.

Non-pharmacological interventions (NPI) such as social distancing and lockdown are essential in preventing and controlling emerging pandemic outbreaks. Many countries worldwide implemented lockdowns during the COVID-19 outbreaks. However, due to the lack of prior experience and knowledge about the pandemic, it is challenging to deal with short-term polices decision-making due to the highly stochastic and dynamic nature of the COVID-19. Thus, there is a need for the exploration of policy decision analysis to help agencies to adjust their current policies and adopt quickly. In this study, an analytical methodology is developed to analysis urban transport policy response for pandemic control based on social media data. Compared to traditional surveys or interviews, social media can provide timely data based on the feedback from public in terms of public demands, opinions, and acceptance of policy implementations. In particular, a sentiment-aware pre-trained language model is fine-tuned for sentiment analysis of policy. The Latent Dirichlet Allocation (LDA) model is used to classify documents, e.g., posts collected from social media, into specific topics in an unsupervised manner. Then, entropy weights method (EWM) is used to extract public policy demands based on the classified topics. Meanwhile, a Jaccard distance-based approach is proposed to conduct the response analysis of policy adjustments. A retrospective analysis of transport policies during the COVID-19 pandemic in Wuhan, China is presented using the developed methodology. The results show that the developed policymaking support methodology can be an effective tool to evaluate the acceptance of anti-pandemic policies from the public's perspective, to assess the balance between policies and people's demands, and to further perform the response analysis of a series of policy adjustments based on online feedback.

Exploring the potential role of bikeshare to complement public transit: The case of San Francisco amid the coronavirus crisis.

The recent worldwide SARS-CoV-2 (COVID-19) pandemic has reshaped the way people live, how they access goods and services, and how they perform various activities. For public transit, there have been health concerns over the potential spread to transit users and transit service staff, which prompted transportation agencies to make decisions about the service, e.g., whether to reduce or temporarily shut down services. These decisions had substantial negative consequences, especially for transit-dependent travelers, and prompted transit users to explore alternative transportation modes, e.g., bikeshare. However, local governments and the public in general have limited information about whether and to what extent bikeshare provides adequate accessibility and mobility to those transit-dependent residents. To fill this gap, this study implemented spatial and visual analytics to identify how micro-mobility in the form of bikesharing has addressed travel needs and improved the resilience of transportation systems. The study analyzed the case of San Francisco in California, USA, focusing on three phases of the pandemic, i.e., initial confirmed cases, shelter-in-place, and initial changes in transit service. First, the authors implemented unsupervised machine learning clustering methods to identify different bikesharing trip types. Moreover, through spatiotemporally matching bikeshare ridership data with transit service information (i.e., General Transit Feed Specification, GTFS) using the tool called OpenTripPlanner (OTP), the authors studied the travel behavior changes (e.g., the proportion of bikeshare trips that could be finished by transit) for different bikeshare trip types over the three specified phases. This study revealed that during the pandemic, more casual users joined bikeshare programs; the proportion of recreation-related bikeshare trips increased; and routine trips became more prevalent considering that docking-station-based bikeshare trips increased. More importantly, the analyses also provided insights about mode substitution, because the analyses identified an increase in dockless bikeshare trips in areas with no or limited transit coverage.

Capability Index: Applying a Fuzzy-Based Decision-Making Method to Evaluate Social Inclusion in Urban Areas Using the Capability Approach.

There is rising interest in re-evaluating transport policy, moving away from analysing concrete economic indicators and towards examining the number of persons participating in activities as 'social justice.' So, using the Capacity Approach, this study presents an aggregated model to calculate the level of capability in two neighbourhoods in Tehran, Iran, involving variables from the 'Individuals' and 'Environment' dimensions. The computed factors were then weighted by the Fuzzy AHP technique based on the opinion of Iranian and international experts and combined to produce the final Capability Index (CI). CI results show that residents of the central business district, with an average of 0.628, had a 20% higher CI than residents of the city's outskirts, with 0.483. Furthermore, CI values corroborate prior research results that individuals with higher income, education level, and work position, in addition to higher individual capacity, benefit from a better neighbourhood environment. Also, calculations show that the neighbourhoods are not environmentally accessible for people with disabilities, and this group is suffering from low external capability. Additionally, the model estimates different levels of CI to evaluate the current status and prioritize future urban projects, so the model can be helpful for policy-makers to investigate the capability dimensions separately and decide about future plans.

[The urban transport as social economic health determinant].

The article considers role of transport as one of social economic health determinants. The aspects having positive and negative impact on health of population are presented. The necessity to design and plan transport systems considering population needs is postulated. It is emphasized that main priority in improving health is transition from using cars to ecological types of transport, for example, bicycles. The 8 concrete measures of improving health of urban residents are described, including increase of accessibility of points of destination, management of cars demand by reducing their accessibility and increasing parking costs, design of transport networks convenient for pedestrians and cyclists, achieve optimal population density, reduce distance to public transport and increase attractiveness of active modes of movement, etc. The strategies encouraging use of public transport are outlined.

A systematic review of the impacts of the coronavirus crisis on urban transport: Key lessons learned and prospects for future cities.

The COVID-19 pandemic continues to have a significant impact on the transport sector worldwide. Lockdown and physical distancing requirements continue to be enforced in many cities leading to severe travel restrictions and travel demand reduction to limit the spread of the disease. This article provides bibliometric evidence-based insights into how the pandemic has exposed the vulnerability of established public transport systems and shared mobility solutions. It shows how some transport interventions can accelerate the shift to sustainable urban mobility practices such as micro-mobility and active transport. To accomplish this, the article examines recent studies (244 publications) from the Scopus database using a rigorous systematic literature review approach covering the period from January 2020 to February 2021. Importantly, the mapping of bibliographic coupling and co-citation analysis showed four heterogeneous clusters representing research efforts into "environment", "travel behavior and mode choice", "public transport", and "interventions". Inductive reasoning is used to analyze the disruptions that cities have encountered worldwide, the rapid interventions that were put in place, the aftershocks and the short and long-term impacts. Finally, the paper summarizes the lessons learned and opportunities ahead, and the challenges that must be overcome. The article also outlines pathways to build on the momentum of sustainable practices as part of a holistic approach for enabling resilient transport solutions for the new urban world.

Active mobility versus motorized transport? User choices and benefits for the society.

Measures promoting active mobility - walking or cycling - are often seen as an effective strategy to meet multiple urban objectives. The advantages of such behavioural changes cover multiple dimensions at public and individual level, including positive impacts on health, safety, climate, economy, environment and air quality. However, there is still a considerable potential for increasing the uptake of active mobility in urban areas. This paper explores the determinants of active mobility choice and compares the demographic, socio-economic and cultural factors that influence it. The methodology combines extensive survey data, an EU-wide transport model and detailed indicators of external costs of transport with a Gradient Boosting Machine Learning approach. The model based scenarios quantify the benefit in terms of external costs savings from increasing active mobility shares. Such savings - at EU level, can reach the amount of 15 billion euro per year for a shift of 10% of trips to active mobility modes.

Assessing emission reduction effects from shifts of urban passenger transport modes by implementing targeted emission tax considering the whole fuel cycle.

Controlling the emission of urban passenger transport modes has become one of the most important tasks of governing urban air pollution. Most strategies only focused on carbon emission, whereas neglecting the influences of other pollutants (CO, HC, NOx, PM2.5), especially for upstream emissions from electricity generation caused by the electricity consumed during the operation of electrified transport modes. Based on the multinomial logit model (MNL), this study firstly calculated and evaluated the emission reduction effects brought about by the implementation of targeted emission taxes on different transport modes from the perspective of whole fuel cycle. Taking Jiangning District as an example, our research found that the policy implementing targeted emission tax for different transport modes can not only bring reduce 13.104 tons of CO, 0.327 tons of HC, 0.568 tons of NOx, and 0.140 tons of PM2.5, but also 26,726.82 (euro) of eco-environmental benefits for the treatment of air pollution. Our study can provide useful insights for shifting the structure of urban passenger transport modes, especially promoting the transfer of private cars to the urban green transport systems, to alleviate urban air pollution by formulating effective emission reduction strategies.

Data for a city-level health impact assessment of urban transport in Mauritius.

Participatory quantitative Health Impact Assessments (HIAs) in developing countries are rare partly due to data scarcity. This paper reports on primary data collected in the city of Port Louis to complete a HIA of urban transport planning in Mauritius. We conducted a full-chain participatory HIA to assess health impacts on the basis of a transport mode shift in Port Louis, Mauritius [1]. By applying mixed-methods, we estimated averted deaths per year and economic outcomes by assessing the health determinants of air pollution, traffic deaths and physical activity. The participatory quantitative HIA included [1] baseline data collection [2] co-validation of transport policy scenarios with stakeholders and [3] quantitative modelling of health impacts. We used the risk assessment method for HIA appraisal. The data can be reused for epidemiological analysis and different types of impact assessments.

Pandemic waves and the time after Covid-19 - Consequences for the transport sector.

This paper discusses the dual role of the transport sector in the Covid-19 pandemic: spreading the virus around the world and being most negatively impacted by the pandemic. This paper describes and analyzes the following: (a) actions taken by the governments and international community in order to control the spreading and to alleviate negative economic impacts including massive fiscal and monetary stimulus funding; (b) detailed discussions on the impacts of the pandemic on air transport, rail and bus transport, and urban transit, and major countries' responses to reduce the negative effects; (c) discussions on the positive effects of the pandemic on the environment and climate change by suggesting policy measures in order to make it sustainable over the long term. Finally, the paper addresses social acceptance issue of the behavioral changes necessary in the post-pandemic world, in particular reflecting historical experience of the Spanish flu case. We end the paper with some observations and discussion of the normative issues for a sustainable development of the transport sector.

E-scooter sharing schemes operational zones in Poland: Dataset on voivodeship capital cities.

In this paper, we present the vector dataset of the operational zones of e-scooter shared mobility services in the voivodeship capital cities in Poland. The data were acquired manually from the applications of a single provider of e-scooters for each city. The dataset contains not only the size and the position of the geographic service areas, or geofences of e-scooter sharing schemes, but also the size and position of no-parking zones, parking zones and low-speed zones, if applicable. The data can be used for various researches which cover the topic of micro-mobility, accessibility and broader issues connected with urban development and spatial management. The dataset captures the state of the e-scooter sharing scheme in the voivodeship capital cities in Poland at the beginning of August 2020. Additionally, the data are accompanied by the table of cities with identified providers of e-scooter sharing systems.

Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.

Electric scooters (e-scooters) are an increasingly popular form of transportation in urban areas. While research on this topic has focused primarily on injuries, there are multiple mechanisms by which e-scooter share programs may impact health. The aim of this study is to explore the health-related behaviors of e-scooter users and to discuss their implications for public health. Data were collected using an online survey emailed to registered e-scooter users. A total of 1070 users completed the survey. Descriptive variable statistics and chi-squared analysis were performed to determine variable dependent relationships and equality of proportions. The most common destinations reported were "just riding around for fun", home, and dining/shopping. The two most common modes of transportation that would have been used if e-scooters were not available were walking (43.5%) and using a personal vehicle (28.5%). Riding behavior was equally mixed between on the street, on the sidewalk, and equal amounts of both. e-Scooters in Provo are likely having both positive (e.g., air pollution) and negative impacts on health (e.g., injuries, physical inactivity). Future research should further explore patterns of e-scooter use and explicitly examine the linkages between e-scooters and areas of health beyond just injuries.

Conceptualizing environmental effects of carsharing services: A system thinking approach.

Emerging carsharing services and their interconnections with other modes of urban transport, regulations, car manufacturing and population have affected the dynamics of energy consumption, environmental pollution and greenhouse gas emission within a complex system. However, although some aspects of environmental impacts of transport sector have been investigated in the literature, well-deserved studies on the environmental effects of carsharing services following a system thinking approach is missing. This research aims at providing a comprehensive conceptual framework to systematize the interconnections between carsharing services and their environmental effects. To do this, system dynamics (SD) modeling, as a tool to simulate complex and dynamic systems, is applied and the proposed framework model is illustrated by using a causal-loop diagram (CLD). Along with analyzing the main identified causal loops within the presented CLD, relevant strategies are proposed to reduce the negative environmental effects associated with the carsharing services, considering the whole lifecycle of a shared vehicle. The proposed framework can help environment policy makers and shared mobility practitioners in long-term strategic decision-making. Moreover, it can be applied by the researchers as a basis for future research, not only for SD modeling but also other simulation and analysis structures.

Participatory quantitative health impact assessment of urban transport planning: A case study from Eastern Africa.

BACKGROUND: High rates of motorization in urban areas of Africa have adverse effects on public health. Transport-related mortality will increase as a result of inadequate transport infrastructure, air pollution and sedentary lifestyles. Health Impact Assessments (HIAs) have proven to be a successful tool to predict and mitigate negative health impact of urban transport planning policies, programmes or projects. Yet, there is a gap of evidence on transport and health in African countries. The aim of this study is assessing the health impacts of transport scenarios in Port Louis (city of 119,018 inhabitants in Mauritius) using a full chain participatory HIA model. METHODS: We estimated health and economic impacts associated to transport scenarios with qualitative data and quantitative comparative risk assessment methods. The health impact modeling was based on differences between the baseline and three transport scenarios (worse, good, ideal), estimating the averted deaths per year and economic outcomes by assessing health determinants of air pollution (AP), traffic deaths and physical activity (PA). Data on air pollution and traffic fatalities were obtained from public data sources. Data used to construct scenarios, establish baseline travel mode shares and physical activity were collected through (a) open-ended individual interviews (IDIs) with 14 stakeholders (b) closed-ended survey questions to 600 citizens and (c) 2 focus group discussions (FGDs) with the same 14 stakeholders from (a). RESULTS: In Port Louis, the worse-case transport scenario (doubling in car trips and a reduction in walking, motorcycle, and public transport), resulted in a total increment of 3.28 premature deaths per year. The good-case scenario (reducing car trips by half and increasing walking, motorcycle, and public transport trips) resulted in a total increment of 0.79 premature deaths per year. The ideal-case scenario (reduction in car and motorcycle trips and an increase in walking and public transport trips) resulted in a total reduction of 13.72 premature deaths per year. We estimated USD 23 millions of economic benefits related to mortality if the ideal-case was achieved. CONCLUSION: Participatory HIA shows that implementing transport policies aiming for less than an ideal situation may not be adequate or sufficient to avoid negative transport-related mortality in Mauritius. Urban transport planning is an opportunity to encourage physical activity in rapidly urbanizing settings of Africa. Transport policies should aim to restrict all forms of private motorized vehicles and promote active and public transport to support public health. We highly recommend the use of participatory approaches in quantitative HIA to ensure context specificity and policy relevance.

Research on Human Travel Correlation for Urban Transport Planning Based on Multisource Data.

With the rapid development of positioning techniques, a large amount of human travel trajectory data is collected. These datasets have become an effective data resource for obtaining urban traffic patterns. However, many traffic analyses are only based on a single dataset. It is difficult to determine whether a single-dataset-based result can meet the requirement of urban transport planning. In response to this problem, we attempted to obtain traffic patterns and population distributions from the perspective of multisource traffic data using license plate recognition (LPR) data and cellular signaling (CS) data. Based on the two kinds of datasets, identification methods of residents' travel stay point are proposed. For LPR data, it was identified based on different vehicle speed thresholds at different times. For CS data, a spatiotemporal clustering algorithm based on time allocation was proposed to recognize it. We then used the correlation coefficient r and the significance test p-values to analyze the correlations between the CS and LPR data in terms of the population distribution and traffic patterns. We studied two real-world datasets from five working days of human mobility data and found that they were significantly correlated for the stay and move population distributions. Then, the analysis scale was refined to hour level. We also found that they still maintain a significant correlation. Finally, the origin-destination (OD) matrices between traffic analysis zones (TAZs) were obtained. Except for a few TAZs with poor correlations due to the fewer LPR records, the correlations of the other TAZs remained high. It showed that the population distribution and traffic patterns computed by the two datasets were fairly similar. Our research provides a method to improve the analysis of complex travel patterns and behaviors and provides opportunities for travel demand modeling and urban transport planning. The findings can also help decision-makers understand urban human mobility and can serve as a guide for urban management and transport planning.

Perceived factors associated with boda-boda (motorcycle) accidents in Kampala, Uganda.

Objective: According to the United Nations, nearly 1.25 million people are killed and up to 50 million people are injured on the world's roads every year. Uganda loses about 10 people daily to road accidents, costing about US$1.2 billion annually, which represents about 5% of the gross domestic product (GDP). The objective of this study was to identify causal factors that can be associated with boda-boda accidents in Uganda.Method: A cross sectional study assessed 200 boda-boda riders in the urban areas of Kampala, Uganda. Interviews using semistructured questionnaires were administered to all participants. Data were entered in Excel and imported to STATA for analysis. Multivariate and bivariate analyses were conducted to determine factors that influenced accident risk perception. All variables that were significant at a bivariate level and thought to be theoretically important in influencing the outcome variable were included in a logistic regression model. All tests were performed at a significance of P < .05.Results: Competition for passengers with other public transport operators (83%), negligence of road safety rules (78%), and inadequate helmet usage (62%) were the main factors perceived to be associated with boda-boda accidents. Other factors identified by the respondents include age of the boda-boda rider (58%) and drug use (56%; P < .05). At multivariate analysis, competition for passengers (adjusted odds ratio [AOR] = 17; 95% confidence interval CI, 1.34-26.5) and being in between 18 and 25 years old (AOR = 19; 95% CI, 1.42-27.1) remained statistically significant.Conclusions: This study revealed behavioral factors by all public transport users as the main factors associated with boda-boda accidents in urban Kampala. This demonstrates the need for holistic interventions to address such boda-boda accidents in Uganda. Such interventions can be through digitization of transport system for clients to engage remotely with the transport operators, routine refresher trainings of all transport operators, and construction of lanes for boda-boda riders.

A (não) atuação frente ao assédio moral no trabalho: estudo sobre um sindicato / The (lack of) action against workplace bullying: study on a union

O assédio moral no trabalho é entendido como um conjunto de atos hostis que ocorrem de forma processual e podem estar relacionados às prescrições da organização do trabalho. Os sindicatos e associações que defendem os interesses e direitos de categorias profissionais devem estar atentos a essa violência psicológica. Com o objetivo de identificar a percepção e a atuação de dirigentes sindicais frente a situações de assédio moral no trabalho, realizou-se uma pesquisa qualitativa com representantes sindicais dos trabalhadores de transporte coletivo urbano de uma capital do sul do país. O sindicato ao qual pertencem esses dirigentes é reconhecido por sua luta e enfrentamento, assim como pela obtenção de conquistas e melhorias nas condições de trabalho de seus representados. Com relação e esse tipo de assédio, os resultados obtidos neste estudo evidenciaram uma visão simplificada sobre o fenômeno - sem um entendimento processual e ampliado. Tal compreensão indicou a associação entre práticas de assédio moral e pessoas específicas (os agressores), o que tende a reforçar uma atuação sindical tímida acerca dessa violência presente nas relações de trabalho. Os sindicatos, com função política e social, são entidades de suporte e amparo aos trabalhadores e, quando possuem um arcabouço de informações que subsidie o entendimento, a orientação e a construção de ações de luta e busca de melhores condições trabalhistas, tornam-se instrumentos de combate a condutas não aceitáveis no ambiente de trabalho.

The workplace bullying can be understood as a set of hostile actions that occur as a process and may be instructed by work organizations. Unions, which are associations that defend the interests and rights of professional categories, must be attentive to this form of psychological violence. In order to identify the perception and action of union leaders against situations of workplace bullying, a qualitative research was conducted with union representatives of the urban collective transport workers from a capital in the South of Brazil. The union to which these leaders belong is known for its struggle and confrontation tradition, as well as for the gains and improvements accomplished in the work conditions of its members. Regarding this kind of bullying, the results obtained in this study have showed a narrow view of the phenomenon, instead of understanding it more globally and as a process. This current view associates workplace bullying practices with specific people - the aggressors -, which tends to reinforce a timid union action against this kind of violence within working relationships. Unions, which play a social and political role, are organizations to support and protect workers, and when they have an information framework to support their view, orientation, and the implementation of actions of struggle and search for better working conditions, they can become instruments to fight against unacceptable behaviors in the workplace.

Carbon dioxide emission and bio-capacity indexing for transportation activities: A methodological development in determining the sustainability of vehicular transportation systems.

CO2 emissions from urban traffic are a major concern in an era of increasing ecological disequilibrium. Adding to the problem net CO2 emissions in urban settings are worsened due to the decline of bio-productive areas in many cities. This decline exacerbates the lack of capacity to sequestrate CO2 at the micro and meso-scales resulting in increased temperatures and decreased air quality within city boundaries. Various transportation and environmental strategies have been implemented to address traffic related CO2 emissions, however current literature identifies difficulties in pinpointing these critical areas of maximal net emissions in urban transport networks. This study attempts to close this gap in the literature by creating a new lay-person friendly index that combines CO2 emissions from vehicles and the bio-capacity of specific traffic zones to identify these areas at the meso-scale within four ranges of values with the lowest index values representing the highest net CO2 levels. The study used traffic volume, fuel types, and vehicular travel distance to estimate CO2 emissions at major links in Dhaka, Bangladesh's capital city's transportation network. Additionally, using remote-sensing tools, adjacent bio-productive areas were identified and their bio-capacity for CO2 sequestration estimated. The bio-productive areas were correlated with each traffic zone under study resulting in an Emission Bio-Capacity index (EBI) value estimate for each traffic node. Among the ten studied nodes in Dhaka City, nine had very low EBI values, correlating to very high CO2 emissions and low bio-capacity. As a result, the study considered these areas unsustainable as traffic nodes going forward. Key reasons for unsustainability included increasing use of motorized traffic, absence of optimized signal systems, inadequate public transit options, disincentives for fuel free transport (FFT), and a decline in bio-productive areas.

Assessment of GHG mitigation and CDM technology in urban transport sector of Chandigarh, India.

The increase in number of vehicles in metropolitan cities has resulted in increase of greenhouse gas (GHG) emissions in urban environment. In this study, emission load of GHGs (CO, N2O, CO2) from Chandigarh road transport sector has been estimated using Vehicular Air Pollution Inventory (VAPI) model, which uses emission factors prevalent in Indian cities. Contribution of 2-wheelers (2-w), 3-wheelers (3-w), cars, buses, and heavy commercial vehicles (HCVs) to CO, N2O, CO2, and total GHG emissions was calculated. Potential for GHG mitigation through clean development mechanism (CDM) in transport sector of Chandigarh under two scenarios, i.e., business as usual (BAU) and best estimate scenario (BES) using VAPI model, has been explored. A major contribution of GHG load (~ 50%) in Chandigarh was from four-wheelers until 2011; however, it shows a declining trend after 2011 until 2020. The estimated GHG emission from motor vehicles in Chandigarh has increased more than two times from 1065 Gg in 2005 to 2486 Gg by 2011 and is expected to increase to 4014 Gg by 2020 under BAU scenario. Under BES scenario, 30% of private transport has been transformed to public transport; GHG load was possibly reduced by 520 Gg. An increase of 173 Gg in GHGs load is projected from additional scenario (ADS) in Chandigarh city if all the diesel buses are transformed to CNG buses by 2020. Current study also offers potential for other cities to plan better GHG reduction strategies in transport sector to reduce their climate change impacts.

Integrating Norm Activation Model and Theory of Planned Behavior to Understand Sustainable Transport Behavior: Evidence from China.

With increasing urbanization in China, many cities are facing serious environmental problems due to continuous and substantial increase in automobile transportation. It is becoming imperative to examine effective ways to reduce individual automobile use to facilitate sustainable transportation behavior. Empirical, theory-based research on sustainable transportation in China is limited. In this research, we propose an integrated model based on the norm activation model and the theory of planned behavior by combining normative and rational factors to predict individuals' intention to reduce car use. Data from a survey of 600 car drivers in China's three metropolitan areas was used to test the proposed model and hypotheses. Results showed that three variables, perceived norm of car-transport reduction, attitude towards reduction, and perceived behavior control over car-transport reduction, significantly affected the intention to reduce car-transport. Personal norms mediated the relationship between awareness of consequences of car-transport, ascription of responsibility of car-transport, perceived subjective norm for car-transport reduction, and intention to reduce car-transport. The results of this research not only contribute to theory development in the area of sustainable transportation behavior, but also provide a theoretical frame of reference for relevant policy-makers in urban transport management.

Benefits on public health from transport-related greenhouse gas mitigation policies in Southeastern European cities.

Climate change is a major environmental threat of our time. Cities have a significant impact on greenhouse gas emissions as most of the traffic, industry, commerce and more than 50% of world population is situated in urban areas. Southern Europe is a region that faces financial turmoil, enhanced migratory fluxes and climate change pressure. The case study of Thessaloniki is presented, one of the only two cities in Greece with established climate change action plans. The effects of feasible traffic policies in year 2020 are assessed and their potential health impact is compared to a business as usual scenario. Two types of measures are investigated: operation of underground rail in the city centre and changes in fleet composition. Potential co-benefits from reduced greenhouse gas emissions on public health by the year 2020 are computed utilizing state-of-the-art concentration response functions for PMx, NO2 and C6H6. Results show significant environmental health and monetary co-benefits when the city metro is coupled with appropriate changes in the traffic composition. Monetary savings due to avoided mortality or leukaemia incidence corresponding to the reduction in PM10, PM2.5, NO2 and C6H6 exposure will be 56.6, 45, 37.7 and 1.0 million Euros respectively. Promotion of 'green' transportation in the city (i.e. the wide use of electric vehicles), will provide monetary savings from the reduction in PM10, PM2.5, NO2 and C6H6 exposure up to 60.4, 49.1, 41.2 and 1.08 million Euros. Overall, it was shown that the respective GHG emission reduction policies resulted in clear co-benefits in terms of air quality improvement, public health protection and monetary loss mitigation.