A Short-Term Measurement of PM2.5 Concentration During the COVID-19 Lockdown Period in Kathmandu Valley
Bibliographic record
Abstract
The Government of Nepal implemented a nationwide lockdown from 24 March 2020 to 21 July 2020 to control the person-to-person transmission of COVID-19. This study was conducted in a trafficintensified area of Kathmandu valley, where vehicular movement represents one of the main sources of air pollution. Hence, this study was intended to quantify the concentration of particulate matter (PM2.5) for 11 hours of daytime from 23 April to 20 May 2020. It was also to evaluate the influences of lockdown on air quality. PM2.5 was observed using HAZ-Dust, Environmental Particulate Air Monitor in the 18 different traffic sites of the Kathmandu valley. During the lockdown period, a substantially low mean concentration of PM2.5 ranging from 3.69±1.78 µg/ m3 to 7.58±3.98 µg/m3 was recorded in Kathmandu valley, which reflected improved air quality due to the cessation of vehicular activities. Therefore, the study outcome suggests that controlling the existing vehicular activities and promoting energy-efficient vehicles like electric vehicles in specific locations in the city will improve air quality and benefit public health.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".