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The COVID-19 pandemic has tremendously affected the whole of human society worldwide. Travel patterns have greatly changed due to the increased risk perception and the governmental interventions regarding COVID-19. This study aimed to identify contributing factors to the changes in public and private transportation mode choice behavior in China after COVID-19 based on an online questionnaire survey. In the survey, travel behaviors in three periods were studied: before the outbreak (before 27 December 2019), the peak (from 20 January to 17 March 2020), and after the peak (from 18 March to the date of the survey). A series of random-parameter bivariate Probit models was developed to quantify the relationship between individual characteristics and the changes in travel mode choice. The key findings indicated that individual sociodemographic characteristics (e.g., gender, age, ownership, occupation, residence) have significant effects on the changes in mode choice behavior. Other key findings included (1) a higher propensity to use a taxi after the peak compared to urban public transportation (i.e., bus and subway); (2) a significant impact of age on the switch from public transit to private car and two-wheelers; (3) more obvious changes in private car and public transportation modes in more developed cities. The findings from this study are expected to be useful for establishing partial and resilient policies and ensuring sustainable mobility and travel equality in the post-pandemic era.

Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

How can urban policies and planning approaches help in achieving a safer mobility and carbon reduction in the transport sector? The attention of planners and policy makers towards the promotion of sustainability and reduction of environmental impacts has grown in recent years. This paper investigates the role that Urban Planning plays in the long term towards a safer and climate friendlier mobility, highlighting the need for integrated approaches gathering spatial planning and mobility management. After a review of several urban policies and planning strategies, initiatives, and approaches, mainly based on the urban scale, the paper presents an urban regeneration case study leading to an increase of pedestrian accessibility at the neighborhood level. This can be seen as a support tool to foster sustainable, safe, and climate friendly mobility in cities. The results of the performed analysis show a dependency of accessibility from two different factors: the distribution of services and the capillarity of the soft mobility network, which can contribute to creating a more walkable space.

As it is widely accepted, cycling tends to produce health benefits and reduce air pollution. Policymakers encourage people to use bikes by improving cycling facilities as well as developing bicycle-sharing systems (BSS). It is increasingly interesting to investigate how environmental factors influence the cycling behavior of users of bicycle-sharing systems, as users of bicycle-sharing systems tend to be different from regular cyclists. Although earlier studies have examined effects of safety and convenience on the cycling behavior of regular riders, they rarely explored effects of safety and convenience on the cycling behavior of BSS riders. Therefore, in this study, we aimed to investigate how road safety, convenience, and public safety affect the cycling behavior of BSS riders by controlling for other environmental factors. Specifically, in this study, we investigated the impacts of environmental characteristics, including population density, employment density, land use mix, accessibility to point-of-interests (schools, shops, parks and gyms), road infrastructure, public transit accessibility, road safety, convenience, and public safety on the usage of BSS. Additionally, for a more accurate measure of public transit accessibility, road safety, convenience, and public safety, we used spatiotemporally varying measurements instead of spatially varying measurements, which have been widely used in earlier studies. We conducted an empirical investigation in Chicago with cycling data from a BSS called Divvy. In this study, we particularly attempted to answer the following questions: (1) how traffic accidents and congestion influence the usage of BSS; (2) how violent crime influences the usage of BSS; and (3) how public transit accessibility influences the usage of BSS. Moreover, we tried to offer implications for policies aiming to increase the usage of BSS or for the site selection of new docking stations. Empirical results demonstrate that density of bicycle lanes, public transit accessibility, and public safety influence the usage of BSS, which provides answers for our research questions. Empirical results also suggest policy implications that improving bicycle facilities and reducing the rate of violent crime rates tend to increase the usage of BSS. Moreover, some environmental factors could be considered in selecting a site for a new docking station.

The European Commission (EC) has set ambitious CO2 emission reduction objectives for the transport sector by 2050. In this context, most decarbonisation scenarios for transport foresee large market penetration of electric vehicles in 2030 and 2050. The emergence of electrified car mobility is, however, uncertain due to various barriers such as battery costs, range anxiety and dependence on battery recharging networks. Those barriers need to be addressed in the 2020–2030 decade, as this is key to achieving electrification at a large scale in the longer term. The paper explores the uncertainties prevailing in the first decade and the mix of policies to overcome the barriers by quantifying a series of sensitivity analysis scenarios of the evolution of the car markets in the EU Member States and the impacts of each barrier individually. The model used is PRIMES-TREMOVE, which has been developed by E3MLab and constitutes a detailed energy-economic model for the transport sector. Based on model results, the paper assesses the market, energy, emission and cost impacts of various CO2 car standards, infrastructure development plans with different geographic coverage and a range of battery cost reductions driven by learning and mass industrial production. The assessment draws on the comparison of 29 sensitivity scenarios for the EU, which show that removing the barriers in the decade 2020–2030 is important for electrification emergence. The results show that difficult policy dilemmas exist between adopting stringent standards and infrastructure of wide coverage to push technology and market development and adverse effects on costs, in case the high cost of batteries persists. However, if the pace of battery cost reductions is fast, a weak policy for standards and infrastructure is not cost-effective and sub-optimal. These policies are shown to have impacts on the competition between pure electric and plug-in hybrid vehicles. Drivers that facilitate electrification also favour the uptake of the former technology, the latter being a reasonable choice only in case the barriers persist and obstruct electrification.

A “Well-to-Propeller” Life Cycle Assessment of maritime transport was performed with a European geographical focus. Four typical types of vessels with specific operational profiles were assessed: a container vessel and a tanker (both with 2-stroke engines), a passenger roll-on/roll-off (Ro-Pax) and a cruise vessel (both with 4-stroke engines). All main engines were dual fuel operated with Heavy Fuel Oil (HFO) or Liquefied Natural Gas (LNG). Alternative onshore and offshore fuel supply chains were considered. Primary energy use and greenhouse gas emissions were assessed. Raw material extraction was found to be the most impactful life cycle stage (~90% of total energy use). Regarding greenhouse gases, liquefaction was the key issue. When transitioning from HFO to LNG, the systems were mainly influenced by a reduction in cargo capacity due to bunkering requirements and methane slip, which depends on the fuel supply chain (onshore has 64% more slip than offshore) and the engine type (4-stroke engines have 20% more slip than 2-stroke engines). The combination of alternative fuel supply chains and specific operational profiles allowed for a complete system assessment. The results demonstrated that multiple opposing drivers affect the environmental performance of maritime transport, a useful insight towards establishing emission abatement strategies.

Introduction: During the COVID-19 lockdown significant improvements in urban air quality were detected due to the absence of motorized vehicles. It is crucial to perpetuate such improvements to maintain and improve public health simultaneously. Therefore, this exploratory study approached bicycle infrastructure in the case of Munich (Germany) to find out which specific bicycle lanes meet the demands of its users, how such infrastructure looks like, and which characteristics are potentially important. Methods: To identify patterns of bicycle infrastructure in Munich exploratory data is collected over the timespan of three consecutive weeks in August by a bicycle rider at different times of the day. We measure position, time, velocity, pulse, level of sound, temperature and humidity. In the next step, we qualitatively identified different segments and applied a cluster analysis to quantitatively describe those segments regarding the measured factors. The data allows us to identify which bicycle lanes have a particular set of measurements, indicating a favorable construction for bike riders. Results: In the exploratory dataset, five relevant segment clusters are identified: viscous, slow, inconsistent, accelerating, and best-performance. The segments that are identified as best-performance enable bicycle riders to travel efficiently and safely at amenable distances in urban areas. They are characterized by their width, little to no interaction with motorized traffic as well as pedestrians, and effective traffic light control. Discussion: We propose two levels of discussion: (1) revolves around what kind of bicycles lanes from the case study can help to increase bicycle usage in urban areas, while simultaneously improving public health and mitigating climate change challenges and (2) discussing the possibilities, limitations and necessary improvements of this kind of exploratory methodology.