Cyclists’ exposure to atmospheric and noise pollution: a systematic literature review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cyclists constitute a population particularly exposed to atmospheric and noise pollution in urban environments; at the same time, they contribute to its reduction. For about ten years now, more and more studies have been completed to assess cyclists’ exposure, comparing this mode of transportation with others, quantifying its impacts in term of individual and collective health, understanding cyclists’ perceptions regarding their exposure, etc. Though some literature reviews have examined some of these specific issues, none have yet proposed a general overview of this field of study. Therefore, this mapping literature review fills this gap by jointly analysing 205 articles and identifying elements of consensus and disagreement, as well as existing gaps. Among others, our results indicate that the cities in the South and exposure to noise are under-studied and that cyclists’ ventilation is still too rarely accounted for, regardless of the type of studies. Modelling studies regarding exposure are too heterogeneous methodologically to allow a generalisation of their results. Conversely, intermodal comparison studies clearly indicate overexposure for cyclists compared to other modes. Also, health studies conclude that, either individually or collectively, the benefits of cycling surpass the costs of exposure to atmospheric pollution. The knowledge produced by this research trend remains difficult to exploit by urban planners, but the recent work done seems to offer more practical perspectives to professionals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 it