Air quality at bus stop microenvironments in a Metro Vancouver urban and suburban area
Bibliographic record
Abstract

 BACKGROUND Those commuters waiting in small-scale transportation microenvironments, such as bus stops, can be exposed to levels of pollution higher than what is registered by ambient air quality monitoring stations. In addition, historically, those commuting in urban areas experience greater exposure to air pollutants than those commuting in suburban or rural areas, due to the nature of the environment. Little quantitative research has been conducted in the Metro Vancouver area regarding air quality in small scale transportation microenvironments. OBJECTIVES The aim of this study was to assess the differences in commuter exposure during AM Peak and PM Peak periods between an urban (Vancouver) and suburban (Ladner) bus stop. Furthermore, results were to be compared to the Metro Vancouver 24 hour rolling average objective as well as nearby Lower Fraser Valley (LFV) Ambient Air Quality Monitoring Network stations. METHODS The author measured particulate matter (PM) 2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter), using the DustTrakTM Aerosol Monitor 8520 between January 6, 2014 and January 21, 2014 on 12 weekdays, from 6:30am to 7:00am and 5:00pm to 5:30pm, at Stop #55165 Northbound Harvest Dr at Ladner Trunk Rd in Ladner, BC and from Stop #50043 Burrard Stn Bay1 in Vancouver, BC. In addition, meteorological conditions, traffic density, bus volume, and other observations were taken during sampling periods. RESULTS The author found that average PM2.5 exposures were highest during the morning in Ladner (μ=34.38667μg/m3) and lowest during the morning in Vancouver (μ=13.44 μg/m3). In addition, there was a statistically significant difference (p<0.05) between Vancouver AM and the other groups (Ladner AM, Ladner PM [μ=28.07778 μg/m3], and Vancouver PM [μ=30.16667 μg/m3]), but the other groups were not significantly different from each other. Furthermore, the author found that the Vancouver AM average (μ=13.44 μg/m3) was below the Metro Vancouver 24 hour rolling average (25μg/m3) while all other groups (Ladner AM, Ladner PM, and Vancouver PM) exceeded this average. Lastly, when comparing all groups to the AM and PM hourly averages of their respective LFV Air Quality Monitoring Network stations (Ladner AM and PM vs. Tsawwassen AM and PM and Vancouver AM and PM vs. Kitsalano AM and PM), the author found that all groups averages exceeded the hourly averages of their respective stations. CONCLUSION Commuters’ peak hour exposures were significantly influenced by different microenvironments and were found to be higher than the ambient PM2.5 levels registered by the respective LFV Air Quality Monitoring Network stations. In order to address this, Metro Vancouver should implement personal exposure assessments, especially near roadways, to obtain actual levels of exposure to pollutants, such as PM2.5, by their residents. In this way, acute and chronic health outcome risks to air pollution can be better understood.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".