Abstract
To mitigate climate change and safeguard energy security, it is necessary to limit car dependence, reduce car weights, and shift to alternative car powertrains. This study therefore looked into the real-world specific energy consumption and CO2 emissions of cars in the Netherlands. Next, it analyzed how sociodemographic and built environment variables influence energy-relevant car type choices with a multilevel discrete choice modeling framework. At a first stage, this framework considered the number of cars owned. Conditional on that decision, it simultaneously considered choices between different car fuel types and weight categories. The results showed that small, lower-income households with few male or older members in non-green (urban) environments were more likely to own light (efficient) vehicles. Remote households had a preference for light and diesel vehicles. In contrast, households with private parking tended to own heavy and electric vehicles. Finally, owning multiple cars was correlated with both non-urban living and heavy car preferences. The combined effect was a mild preference for energy efficient vehicles in urban areas. Previous studies that omitted vehicle energy efficiency thus slightly underestimated urban planning’s environmental impact. However, our results indicate that the built environment has a greater effect on travel energy use through the number of cars owned than through car specific energy consumption. The bias in the official vehicle energy data was also much larger than the total influence of the built environment on car specific energy consumption.
Original language | English |
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Number of pages | 28 |
Journal | Transportation |
DOIs | |
Publication status | E-pub ahead of print - 11 Jul 2024 |
Bibliographical note
Publisher Copyright:© The Author(s) 2024.
Funding
In this publication, we made use of data from the Netherlands Mobility Panel administered by KiM Netherlands Institute for Transport Policy Analysis. We would especially like to thank KiM researcher Mathijs de Haas for his continuous support. Moreover, we used recent research by the Netherlands Organization for Applied Scientific Research (TNO) and CE Delft to compute the specific energy consumption of the vehicles in the dataset. We were thereby assisted by TNO-researcher van Gijlswijk and CE Delft researcher Daan van Seters. We would like to thank Job Hoenderdos for helping us scrape the Travelcard data from Praktijkverbruik.nl. We would also like to acknowledge the help of Margot Stoete. Furthermore, we want to thank Matthieu Brinkhuis for his input and ideas. We lastly want to thank Bogdan Kapatsila, Santiago Cardona Urrea, and our anonymous reviewers for their constructive feedback.DAS:The research data is not publicly available due to privacy concerns. All data was obtained from third parties.
Funders | Funder number |
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Netherlands Organization for Applied Scientific Research (TNO) |
Keywords
- Built environment
- Car ownership
- CO emissions
- Discrete choice modeling
- Electric vehicles
- Energy efficiency