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Worldwide, one of the most important causes of mortality is air pollution. To solve this problem, governments have implemented policies to reduce on-road and industrial emissions. In this regard, the Barcelona city council and Transports Metropolitans de Barcelona (TMB) started implementing the Nova Xarxa de Bus (NXB) to redefine the bus network following the criteria of connectivity, efficiency, and rationality. This policy was implemented in seven phases from 2012 to 2018. In this context, this paper analyses the impact of this policy on Barcelona's air quality using a dataset from 2008 to 2016. Using a difference-in-difference approach, we show that implementing these new routes increased air quality in Barcelona. Additionally, we show that pollution decreased in each phase analysed, especially in the air quality stations near the main roads. From our results, we can infer that an optimal bus route design can improve air quality in urban areas. [ABSTRACT FROM AUTHOR]

The growing concern over air pollution and community health, demands a comprehensive understanding of the political nature of transport-related emissions. This paper approaches how structures of power influence travel behaviour and, consequently, how they shape emissions from mobility in Barcelona. To comprehend how the intersection of gender, age, and migration background influences air pollution, we use a travel survey to build a set of models that are known to theoretically engage with intersectionality studies. Results show that identities tied to structures of power promote a greater contribution to air pollution than other mechanisms. That is, middle-aged European-born men have the most NO x -intensive mobility practices. In contrast, people that embody intersectional experiences of oppression such as misogyny, racism, or ageism, have lower emission levels. Considering these results, we argue that policies which acknowledge the unequal distribution of responsibilities present an opportunity to reduce emissions from transportation, while guaranteeing fairness and advancing environmental justice. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) are expected to revolutionise transport worldwide and transform urban life. However, there are many unknowns concerning the impacts of these technologies in terms of sustainability, justice, and safety. It has been suggested that CAVs may exacerbate inequities and safety disparities concerning the interaction of vulnerable road users (VRUs) with motorised transport. This paper investigates the justice issues that CAVs policy needs to address concerning VRUs. Our approach to studying CAVs' capabilities and their potential perverse outcomes uses transport justice as an evaluative framework. The justice-related outcomes discussed include: traffic injuries, impact on sharing road responsibilities, loss of on-street space, access to technology, inclusion for disabled and older adults, CAV technological development, and impact of congestion and air pollution. The paper proposes a future research agenda emphasising areas where CAVs may positively impact VRUs. [ABSTRACT FROM AUTHOR]

• Short-sea shipping visibly contributes to particles concentrations in coastal areas. • The bottom-up model predicts consistent particle number concentration, PN, values. • Differently, contribution of ships on PM2.5 cannot be inferred by bottom-up model. • Existing regional fuel quality restrictions mostly reduce PM2.5 emissions. • Cleaner fuels and available after-treatment systems highly reduce PN/PM2.5 levels. Several studies indicate that short-sea shipping is an important source of air pollution for coastal areas and port cities. This paper reports results of a non-reactive particles dispersion model and a new set of experiments implemented for the Channel of Procida (Italy), an area with a high signal-to-noise ratio, due to intense marine traffic and low background pollution. The model successfully predicts particle number concentrations but underestimates PM 2.5 data. Model and experiments show that thanks to the EU policies on marine fuels, the Channel of Procida already has good air quality levels. Besides, the paper demonstrates that fostering the use of LNG or methanol or the application of an exhaust-gas-cleaning-system may allow reducing particles emissions well above 90%. The reliability of control strategies and the benefits for the population suggest that the introduction of regulations on particles emissions for ships can be a realistic option for the future environmental policy agenda. [ABSTRACT FROM AUTHOR]

The paper simulates the spatial variations in the sources of, and exposure to, traffic-related PM10 emissions for the city of Vienna, Austria. Using an extended and calibrated MATSim micro-simulation model, we reproduce agent-level mobility patterns for a representative day. Street-level PM10 emissions, mostly from cars, are extrapolated for the entire city to estimate concentration and exposure levels at hourly intervals. We show that exposure levels exceed the recommended 50 μ g/m 3 threshold between peak travel hours at home, education, and work locations. Among different socioeconomic status (SES) groups, urban, single, 15 years and younger, and those living near the city center face high exposure levels, while car users, that cause a majority of the emissions, are relatively less exposed. Finally, we show that Shared Autonomous Electric Vehicles (SAEVs) reduce PM10 emissions, but the benefits are not homogeneously distributed across the different SES groups. [ABSTRACT FROM AUTHOR]

Currently, over 96% of the urban population is exposed to exceeding air pollution concentrations. Freight transport daily engenders €61,604 of air pollution health costs in the Brussels-Capital Region (BCR), of which 60% is incurred by vulnerable population segments. The construction sector is responsible for 26.40% of truck traffic in the BCR. This paper examines the exposure effects when off-site construction logistics flows are redirected around air pollution hotspots. Consequently, alternative routing scenarios are computed, and its emission dispersed assuming a Gaussian relation. Concentrations are then associated to spatiotemporal receptor densities. The health impact is monetized using hospital exposure-response functions. While overall emissions increase across all scenarios, health costs are mitigated up to 25.53% by rerouting existing flows. This study suggests to decouple policies from absolute transport emissions and focus on its health impact, considering spatiotemporal dynamics of both emissions and receptors. [ABSTRACT FROM AUTHOR]

The paper contributes to the literature on the Environmental Kuznets Curve providing an empirical analysis of the relationship between air pollutant emissions from motor vehicles and social and economic factors in 56 major Russian cities using a panel data set for 2013–2018. The fixed effect regression models were used to analyze the impact of gross municipal product per capita on various types of automobile emissions. We found the evidence of an N-shaped Environmental Kuznets Curve relationship: emissions rise with economic growth due to the rapid automobilization, thereafter growth slows down, giving way to a decline. The reason may be that the households and commercial organizations in wealthier cities can buy newer cars, which correspondingly meet modern ecological standards and require cleaner fuel. Then, beyond a certain point of the gross municipal product per capita, the growth of automobile emissions resumes. We argue that the further decline is due to the structural economic dynamics and technological shifts, and the second ascending part is because the scale effect outperforms all the others. Other substantial results are as follows: (i) population densification leads to increased automobile pollution in large cities, whereas in relatively small municipalities, the effect is opposite; (iii) roads density is a significant factor of emission reduction in large cities; (iv) increase in the cost of gasoline leads to less vehicular emission. Our results emphasize that Russian cities need massive investments in transport infrastructure to form a new settlement framework outside the established centers. This will not only significantly affect the problem of atmospheric air pollution, but also improve the overall quality of life. Finally, it is necessary to increase the transparency of state environmental statistics, including by expanding the network of monitoring of atmospheric pollution in cities. [ABSTRACT FROM AUTHOR]

Emissions from aviation contribute increasingly to both air pollution and climate change. Understanding how these emissions are distributed across regions, seasons, and different altitudes is important to fully ascertain the climate impacts caused by our current aviation sector and set a clear benchmark for our mitigation efforts. The Aviation Transport Emission Assessment Model (AviTEAM) is developed for this purpose. The model estimates various emission species from aviation activities based on flight trajectories, airplane, engine types, and atmospheric conditions. In this paper, we present the AviTEAM framework and apply it to study the emissions from commercial aviation in Norway. We find emissions associated with Norwegian air transport for 2019 of 4.5 Mt CO 2 , 26.2 ktNO x , 3.26 ktHC, and 1.8 ktCO. Furthermore, we exemplify how Automatic Dependent Surveillance-Broadcast data in combination with flight dynamic and emission models can be used to generate high-resolution geospatial emission datasets for research and national reporting purposes. • Provides an updated aviation emission inventory for Norway. • Uses Automatic Dependent Surveillance-Broadcast data for activity modeling. • Assesses each flight with aircraft type and engine-specific modeling. • Shows the distribution of fuel consumption and various emission species. • Concludes that the approach informs the scientific and other audiences. [ABSTRACT FROM AUTHOR]

Road traffic has changed as an essential source of influential urban air pollution in China. This study developed the Spatial Durbin Model to analyze the spatial spillover effects on air pollution caused by urban transportation infrastructure. The results show that high-emission areas congregate in the eastern region of China, which reflects noticeable spatial spillover effects and agglomeration characteristics as high-emission "clubs." When the traffic construction 1 1 Traffic construction area refer to the acreage of street area within the city in this paper. area increases by 1%, the air pollution level will increase 3.2% as accompanied. The improvement of the transportation infrastructure will bring out economic development. The speed of air pollution generated by the resources consumed by economic development is higher than that of technological improvement in the economic transition period to reduce air pollution. In contrast, economic growth and air pollution exacerbation represent a U-shaped curve connection. Most provinces remain in a stage where air pollution worsened with economic growth. [ABSTRACT FROM AUTHOR]

Traffic restrictions have received increasing attention in academia and are becoming a major measure to control urban air pollution. Many studies have evaluated the effects of such restrictions but have yielded mixed results. In this paper, 32 key cities in China are selected for comparative experiments. Cities that implemented traffic restriction policies are used as the experimental group, and other cities that did not implement traffic restrictions are regarded as the control group. First, based on a multi-period difference-in-difference model, we find that the implementation of traffic restriction policies improves urban air pollution. Second, we analyze the effect of only license-plate restrictions on air quality and discover that urban air pollution is still improved. Finally, we reveal that traffic restriction policies achieve different results in northern and southern Chinese cities. [ABSTRACT FROM AUTHOR]

• A strategy for navigating heavy-duty trucks through communities is developed. • The strategy reduces community-wide exposure to truck's tailpipe emissions. • For one example community, low exposure route could be found in 23% of the trips. • On average, it would reduce PM2.5 and NOx inhalation by 50% and 50%, respectively. This paper describes a strategy for navigating a heavy-duty diesel truck through communities in a way that lowers the total exposure of community members to tailpipe emissions from the truck without significantly increasing travel time. This low exposure route was evaluated against the baseline route that truck drivers would normally take for a number of truck trips in two selected communities in Southern California. The evaluation results show that, for up to a quarter of the truck trips, it is possible to find a low exposure route that would reduce community-wide exposure to the truck's tailpipe emissions by up to 50% on average, with an average travel time increase of no more than 5%. These results demonstrate the potential of the exposure-based vehicle routing strategy to mitigate the air pollution impacts of diesel trucks in disadvantaged communities that are overburdened by truck traffic. [ABSTRACT FROM AUTHOR]

• We analyse vehicle emissions in a multi-modal urban area using the pNEUMA dataset. • EPA's microscopic emission model, project level MOVES is implemented. • We investigate aggregated relations between emissions and congestion patterns. • The macroscopic fundamental diagram (MFD) is extended to the emissions-MFD (e-MFD). • The spatiotemporal distribution of vehicle emissions is revealed in high detail. Vehicle emissions are a major contributor of air pollution in urban areas, with severe consequences for public health and the environment. This paper focuses on analyzing vehicle emissions in a multimodal urban context to better understand its determinants and investigate relations between emissions and congestion patterns. Thousands of naturalistic trajectories collected with a swarm of drones during the pNEUMA experiment are analyzed and EPA's microscopic emission model, project level MOVES, is implemented to estimate vehicular emissions. The method is developed and illustrated with a CO 2 analysis. The results empirically show the aggregated relationships between congestion and vehicular emissions, while accounting for the individual characteristics of each trajectory. These systematic relationships on a network scale with the use of empirical data, allow us to extend the macroscopic fundamental diagram (MFD) to the emissions-MFD (e-MFD). The spatiotemporal distribution of emissions is also studied, highlighting areas with high concentration over the urban area. [ABSTRACT FROM AUTHOR]

• This paper reports the first attempt to study the general impact of air pollution on a large population's travel behavior via "big field data": 4.6 billion mobile positioning records of 813,360 people during 61 winter days. • Comparing to the mixed findings in the literature, we find that air pollution does have a significantly negative impact on travel behavior. • People reduce their travel distance slightly but reduce their travel area greatly on air polluted days. In detail, people reduce the average RG by 0.76%, but reduce the average NP by 6.57% as AQI increases 100 points. • People in different demographic groups react to air pollution differently. Younger people (50 and under) reduce more NP, while older people (above 50) reduce more RG on heavily air polluted days. Exposure to ambient air pollution causes 4.2 million deaths worldwide every year; thus, people may avoid traveling on polluted days. However, the extant studies have mixed findings of the travel behavior on polluted days, caused by the shortcomings of survey data and specific activity data. In order to fulfill this research gap, this study evaluates the relationship between air pollution and travel behavior based on approximately 4.6 billion mobile positioning records in Xi'an, China. Moreover, this study also investigates how different demographic groups travel differently on polluted days. The results indicate that air pollution has a significantly negative correlation with travel behavior. Specifically, (1) people reduce travel distance slightly but reduce travel area greatly; and (2) younger people (50 and under) reduce more travel area while older people (over 50) reduce more travel distance on polluted days. [ABSTRACT FROM AUTHOR]

• Metro and RENFE strikes increase air pollution. • Air pollution is slightly affected by bus strikes. • Effects on pollution are larger for public transports with no direct substitutes. • Metro and RENFE commuters switch to private cars when there is a strike. • FGC users switch to non-pollutant transports during strikes. Many Spanish cities' air contains excessive levels of pollutants caused by traffic. These pollutants are associated with high concentrations of vehicles in urban and surrounding areas, such as Madrid and Barcelona. According to the World Health Organization (WHO), 96.8% of Spain's population breathe polluted air. This paper provides empirical evidence on the effect of public transport strikes on Barcelona's air quality through an econometric analysis. The period analyzed included 147 days of some kind of public transport strike: bus (57), metro (21), trains (71), and tram (4); and also four general strikes. The estimates show that public transport strikes increases the concentration level of SO2, CO, PM 10 , and NOX throughout the city, especially in the case of metro and RENFE trains. These results also allow us to understand how commuters substitute transport modes and to propose specific policies to increase public transport use. [ABSTRACT FROM AUTHOR]