The CO2 and PM2.5 levels in Downtown Vancouver at peak (5 p.m.) and off-peak (12 a.m.) hours
Bibliographic record
Abstract

 The effects of air pollution and global warming on human health have reached a dangerous level and this situation has become a critical environmental concern all over the world. The aim of the study was to explore levels of PM2.5 and CO2 emitted from the combustion engines of the road vehicles. The reason for choosing PM2.5 as one of the variables in this study is that it easily penetrates the lungs alveoli and is transmitted to other body organs by blood circulation. Exposure to PM2.5 from a few hours to a few weeks can cause serious cardiovascular diseases (CVDs), including death. The longer the exposure, the higher the risk for cardiovascular mortality. On the other hand, decrease in PM2.5 levels reduces cardiovascular mortality. Studies also show that PM2.5 is associated with diabetes, hypertension, and heart failure. The reason for choosing CO2 was its being as one of the six greenhouse gases leading to the climate change or global warming that threatens human health all over the world. Traffic emissions are the major source for both PM2.5 and CO2. That is why to understand the extent of the PM2.5 and the CO2 emissions from fossil fuel burning and thus their impact on human life is important. Studies show that while air pollution is high during peak hours, it is lower during off-peak hours. Moving from this fact, the discrepancies between peak and off-peak hours readings of the PM2.5 and CO2 levels, which were measured in Vancouver Downtown during 30 consecutive days, were observed. Air particulates PM2.5 were measured with the Dust Trak aerosol monitor and CO2 levels with Q Trak monitor. Results showed a statistically significant difference in the median concentration of PM2.5 between 5 p.m. and 12 a.m. (p=0.018). However there was no statistically significant difference in the median concentration of CO2 between 5 p.m. and 12 a.m. (p=0.84). Measures to reduce air pollution, particularly through reducing PM2.5 and CO2 levels, especially in urban settings, can help reduce the risks of global warming (CO2 effect) and have positive effect on public health issues by preventing or reducing the risks of occurrence of many diseases, and their fatal consequences in some instances, caused or triggered by exposure to air pollution. Both national governments and international agencies should support the scientific research the results of which will inform the public health policies and regulations that will promote cleaner air and thus healthier societies by both implementing some enforcement measures and educating the public on the risks of air pollution and global warming and the relevant and available remedies. This study has been carried out to contribute to the efforts made to this end.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".