Passenger Transport Energy Use in Ten Swedish Cities: Understanding the Differences through a Comparative Review
Bibliographic record
Abstract
Energy conservation in the passenger transport sector of cities is an important policy matter. There is a long history of transport energy conservation, dating back to the first global oil crisis in 1973–1974, the importance and significance of which is explained briefly in this paper. Detailed empirical data on private and public passenger transport energy use are provided for Sweden’s ten largest cities in 2015 (Stockholm, Göteborg, Malmö, Linköping, Helsingborg, Uppsala, Jönköping, Örebro, Västerås and Umeå), as well as Freiburg im Breisgau, Germany, which is a benchmark small city, well-known globally for its sustainability credentials, including mobility. These data on per capita energy use in private and public transport, as well as consumption rates per vehicle kilometer and passenger kilometer for every mode in each Swedish city and Freiburg, are compared with each other and with comprehensive earlier data on a large sample of US, Australian, Canadian, European and Asian cities. Swedish cities are found to have similar levels of per capita car use and energy use in private transport as those found in other European cities, but in the context of significantly lower densities. Possible reasons for the observed Swedish patterns are explored through detailed data on their land use, public and private transport infrastructure, and service and mobility characteristics. Relative to their comparatively low densities, Swedish cities are found to have healthy levels of public transport provision, relatively good public transport usage and very healthy levels of walking and cycling, all of which help to contribute to their moderate car use and energy use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".