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 \(\hbox {CO}_{{2}}\) 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.

为了减缓气候变化和保障能源安全，有必要限制汽车依赖、减轻汽车重量并转向替代汽车动力系统。因此，本研究调查了荷兰汽车的实际能耗和 \(\hbox {CO}_{{2}}\) 排放量。接下来，它通过多级离散选择建模框架分析了社会人口统计和建筑环境变量如何影响与能源相关的汽车类型选择。在第一阶段，该框架考虑了拥有的汽车数量。在此决定的基础上，它同时考虑了不同汽车燃料类型和重量类别之间的选择。结果表明，在非绿色（城市）环境中男性或老年成员较少的小型低收入家庭更有可能拥有轻型（高效）车辆。偏远家庭更喜欢轻型和柴油车。相比之下，拥有私人停车位的家庭往往拥有重型汽车和电动汽车。最后，拥有多辆汽车与非城市生活和重型汽车偏好相关。综合效应是城市地区对节能汽车的温和偏好。之前的研究忽略了车辆能源效率，因此略微低估了城市规划对环境的影响。然而，我们的结果表明，建筑环境通过拥有的汽车数量对出行能源使用的影响比通过汽车特定能源消耗的影响更大。官方车辆能源数据的偏差也远大于建筑环境对汽车能耗的总影响。