Oscar van Vliet


Last Name

van Vliet

First Name

Oscar

ORCID

0000-0002-3964-428X

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Publications1 - 7 of 7
  • Assessing risks of low-carbon transition pathways
    Item type: Other Journal Item
    Lieu, Jenny; Hanger-Kopp, Susanne; van Vliet, Oscar; et al. (2020)
    Environmental Innovation and Societal Transitions
  • Switzerland: Risks associated with implementing a national energy strategy
    Item type: Book Chapter
    van Vliet, Oscar (2019)
    Routledge Studies in Energy Transitions ~ Narratives of Low-Carbon Transitions. Understanding Risks and Uncertainties
  • Availability of private charging infrastructure influences readiness to buy electric cars
    Item type: Journal Article
    Patt, Anthony; Aplyn, David; Weyrich, Philippe; et al. (2019)
    Transportation Research Part A: Policy and Practice
  • Measuring modelling
    Item type: Journal Article
    van Vliet, Oscar; Brändle, Urs (2020)
    ETH Learning and Teaching Journal
    Modelling is an essential skill in many scientific fields, including environmental science. We designed a Modelling Competence Inventory (MCI) to measure the progress of students in acquiring competence in modelling during the bachelor curriculum. As models in environmental science borrow from many disciplines, and modelling is by nature an abstract activity that requires critical thinking, we find that designing an MCI is difficult compared to competence inventories for more physical subjects. We discuss the design process, two iterations of our MCI, and the results of testing these on a group of students before and after a modelling course. Results suggest that students understanding of the learning goals taught in the course improved somewhat, but their score on other learning goals decreased. Overall, we find that bachelor students need more supervised independent practice with modelling and building of confidence in their modelling abilities. The MCI needs further development and differentiated questions specific to the course in which the MCI is administered. The process of searching for competencies to track and developing the MCI, in cooperation with lecturers in the environmental science bachelor, by itself helped build a community of practice and led to steps to better align courses in our curriculum.
  • Public preferences for the Swiss electricity system after the nuclear phase-out: A choice experiment
    Item type: Journal Article
    Plum, Christiane; Olschewski, Roland; Jobin, Marilou; et al. (2019)
    Energy Policy
  • Risk blindness in local perspectives about the Alberta oil sands hinders Canada's decarbonization
    Item type: Journal Article
    Virla, Luis D.; van de Ven, Dirk-Jan; Sampedro, Jon; et al. (2021)
    Environmental Innovation and Societal Transitions
    Local perspectives can conflict with national and international climate targets. This study explores three stakeholder (community, provincial, and federal) perspectives on the Alberta oil sands as risks for a sustainability transition in Canada. In an ex-post analysis, we compared outputs from stakeholder consultations and energy-economy models. Our research shows that different local stakeholders groups disregarded some policy risks for the Alberta oil sands and Canadian energy transition. These stakeholders expected the sector to grow, despite increasing environmental penalties and external market pressures. The study revealed that blind-spots on risks, or “risk blindness”, increased as stakeholders became less certain about policy climate goals. We argue that “risk blindness” could be amplified by dominant institutional narratives that contradict scientific research and international climate policy. Strategies that integrate local narratives, considered as marginalized, provide perspectives beyond emission reductions and are essential for meeting climate targets while supporting a just transition.
  • City-scale car traffic and parking density maps from Uber Movement travel time data
    Item type: Journal Article
    Aryandoust, Arsam; van Vliet, Oscar; Patt, Anthony (2019)
    Scientific Data
    Car parking is of central importance to congestion on roads and the urban planning process of optimizing road networks, pricing parking lots and planning land use. The efficient placement, sizing and grid connection of charging stations for electric cars makes it even more important to know the spatio-temporal distribution of car parking densities on the scale of entire cities. Here, we generate car parking density maps using travel time measurements only. We formulate a Hidden Markov Model that contains non-linear functional relationships between the changing average travel times among the zones of a city and both the traffic activity and flow direction probabilities of cars. We then sample the traffic flow for 1,000 cars per city zone for each city from these probability distributions and normalize the resulting spatial parking distribution of cars in each time step. Our results cover the years 2015–2018 for 34 cities worldwide. We validate the model for Melbourne and reach about 90% accuracy for parking densities and over 93% for circadian rhythms of traffic activity.
Publications1 - 7 of 7