The liveability of cities worldwide is under threat by the predicted increase in intensity and frequency of heatwaves and the absence of a clear spatial overview of where action to address this. Heat stress impairs vital urban functions (Böcker and Thorsson 2014), hits the local economy (Evers et al. 2020), and brings risks for citizens’ health (Ebi et al. 2021). The ongoing densification of cities may escalate the negative consequences of heat, while rising climate adaptation ambitions require new pathways to (re)design public places for a warmer climate. Currently, policy makers and urban planners rely on remote sensing and modelling to identify potential heat stress locations, but thermal comfort models alone fail to consider socio-environmental vulnerabilities and are often not applicable in different countries (Elnabawi and Hamza 2020).In the Cool Towns Interreg project, researchers collaborated with municipalities and regions to model urban heat stress in nine North-Western European cities, to find vulnerabilities and to measure on the ground (see Spanjar et al. 2020 for methodology) the thermal comfort of residents and the effectiveness of implemented nature-based solutions. Using the Physiological Equivalent Temperature (PET) index, several meteorological scenarios were developed to show the urban areas under threat. The PET maps are complemented by heat vulnerability maps showing key social and environmental indicators. Coupled with local urban planning agendas, the maps allowed partner cities to prioritize neighbourhoods for further investigation. To this end, community amenities and slow traffic routes were mapped on top of the PET maps to identify potential focus areas.A comparative analysis of the collated maps indicates certain spatial typologies, where vital urban activities are often influenced by heat stress, such as shopping areas, mobility hubs, principal bicycle and pedestrian routes. This project has resulted in the development of a multi-level Thermal Comfort Assessment (TCA), highlighting locations where vulnerable user groups are exposed to high temperatures. Standardized for European cities, it is a powerful tool for policy makers and urban planners to strategically identify heat stress risks and prioritize locations for adapting to a changing climate using the appropriate nature-based solutions.
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Car use in the sprawled urban region of Noord‐Brabant is above the Dutch average. Does this reflect car dependency due to the lack of competitive alternative modes? Or are there other factors at play, such as differences in preferences? This article aims to determine the nature of car use in the region and explore to what extent this reflects car dependency. The data, comprising 3,244 respondents was derived from two online questionnaires among employees from the High‐Tech Campus (2018) and the TU/e‐campus (2019) in Eindhoven. Travel times to work by car, public transport, cycling, and walking were calculated based on the respondents’ residential location. Indicators for car dependency were developed using thresholds for maximum commuting times by bicycle and maximum travel time ratios between public transport and car. Based on these thresholds, approximately 40% of the respondents were categorised as car‐dependent. Of the non‐car‐dependent respondents, 31% use the car for commuting. A binomial logit model revealed that higher residential densities and closer proximity to a railway station reduce the odds of car commuting. Travel time ratios also have a significant influence on the expected directions. Mode choice preferences (e.g., comfort, flexibility, etc.) also have a significant, and strong, impact. These results highlight the importance of combining hard (e.g., improvements in infrastructure or public transport provi-sion) and soft (information and persuasion) measures to reduce car use and car dependency in commuting trips.
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Closing the loop of products and materials in Product Service Systems (PSS) can be approached by designers in several ways. One promising strategy is to invoke a greater sense of ownership of the products and materials that are used within a PSS. To develop and evaluate a design tool in the context of PSS, our case study focused on a bicycle sharing service. The central question was whether and how designers can be supported with a design tool, based on psychological ownership, to involve users in closing the loop activities. We developed a PSS design tool based on psychological ownership literature and implemented it in a range of design iterations. This resulted in ten design proposals and two implemented design interventions. To evaluate the design tool, 42 project members were interviewed about their design process. The design interventions were evaluated through site visits, an interview with the bicycle repairer responsible, and nine users of the bicycle service. We conclude that a psychological ownership-based design tool shows potential to contribute to closing the resource loop by allowing end users and service provider of PSS to collaborate on repair and maintenance activities. Our evaluation resulted in suggestions for revising the psychological ownership design tool, including adding ‘Giving Feedback’ to the list of affordances, prioritizing ‘Enabling’ and ‘Simplification’ over others and recognize a reciprocal relationship between service provider and service user when closing the loop activities.
The livability of the cities and attractiveness of our environment can be improved by smarter choices for mobility products and travel modes. A change from current car-dependent lifestyles towards the use of healthier and less polluted transport modes, such as cycling, is needed. With awareness campaigns, cycling facilities and cycle infrastructure, the use of the bicycle will be stimulated. But which campaigns are effective? Can we stimulate cycling by adding cycling facilities along the cycle path? How can we design the best cycle infrastructure for a region? And what impact does good cycle infrastructure have on the increase of cycling?To find answers for these questions and come up with a future approach to stimulate bicycle use, BUas is participating in the InterReg V NWE-project CHIPS; Cycle Highways Innovation for smarter People transport and Spatial planning. Together with the city of Tilburg and other partners from The Netherlands, Belgium, Germany and United Kingdom we explore and demonstrate infrastructural improvements and tackle crucial elements related to engaging users and successful promotion of cycle highways. BUas is responsible for the monitoring and evaluation of the project. To measure the impact and effectiveness of cycle highway innovations we use Cyclespex and Cycleprint.With Cyclespex a virtual living lab is created which we will use to test several readability and wayfinding measures for cycle infrastructure. Cyclespex gives us the opportunity to test different scenario’s in virtual reality that will help us to make decisions about the final solution that will be realized on the cycle highway. Cycleprint will be used to develop a monitoring dashboard where municipalities of cities can easily monitor and evaluate the local bicycle use.
Despite increasing efforts regarding knowledge valorisation, a significant gap between knowledge development and policy practice remains. Urban Intelligence bridges this gap by bringing cutting edge knowledge to the table, developing new policy concepts and by promoting smart data use.The professorship of Urban Intelligence takes a multimodal and integrated approach by connecting knowledge of transport engineering, urban planning and urban design. Research output encompasses data-driven projects, such as ‘Multimodal Brabant’ and ‘Measurement Weeks Breda‘, which translate big data into knowledge for policy development.Furthermore, data analysis tool and data dashboards for cycling, such as ‘CyclePRINT’ have been developed. To enhance the integration of built environment and transportation, we developed the Bicycle-Oriented Development (BOD) concept. This is currently being integrated into an overarching development philosophy, ‘Multimodal Urban Development’, which integrates the optimisation of multimodal networks, location choices for new urban developments and the provision of shared mobility via mobility hubs.
