Investigating the Link Between Cyclist Volumes and Pollution Levels Along Bicycle Facilities in Dense Urban Core
Bibliographic record
Abstract
Cycling as a mode of travel is becoming more popular especially in dense urban areas and with this reality comes concerns for cyclist safety. These concerns have lead to different studies focusing on injury occurrence and severity analyses as well as helmet effectiveness and bicycle facility design. An issue that has yet to attract much attention is cyclist exposure to traffic-related air pollution. Cyclists generally ride alongside cars and therefore are exposed to higher ground-level concentrations of nitrogen oxides, carbon monoxide, volatile organic compounds, fine particulate matter and ground-level ozone which could lead to adverse health outcomes. In this paper the authors explore the air pollution levels along different types of bicycle facilities using a nitrogen dioxide (NO2) land-use regression model previously developed for Montreal. A comparison of over twenty cycling corridors is carried out as well as an evaluation of the potential exposure of cyclists to air pollution along five different routes. As expected, the authors observe that corridors with either a bicycle lane or cycle track generally rank higher in terms of bicycle volumes; they also have higher NO2 concentrations than corridors without bicycle facilities. This indicates that facilities that attract a large number of cyclists are also the ones that are characterized with higher pollution levels. The paper ends with a discussion on the use of these findings to inform the development of a personal exposure monitoring study for cyclists in Montreal.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".