Temporal Analysis and Source Apportionment of PM2.5/PM10 Pollution at an Urban Traffic Hotspot: A Comparative Study in Tirana, Albania
Bibliographic record
Abstract
Nowadays the human health and everyday quality of life are closely related to air quality as one of the major environmental issues.Suspended particles can cause many problems in human health by penetrating deep into the lungs and causing respiratory issues, asthma, allergies, and even severe damage to the cardiovascular system.In this paper, we use statistical analysis to estimate the urban air pollution from PM2.5 and PM10 in Vasil Shanto cross-road in Tirana in the month of April 2024.Sampling filters have been collected every 24 hours during weekdays and 48 hours on the weekends.Concentrations of PM10 range from 25.62 g/m to 69.03 g/m , with an average value of 42.96 g/m , while the values for PM2.5 range from 13.10 g/m to 63.79 g/m , with an average of 30.34 g/m .Such concentrations are significantly above the standard limits, indicating a high level of pollution in the Vasil Shanto cross-road area, and the ratio between PM2.5/PM10 indicates that the primary source of pollution in this area is the fuel burning from transport vehicles.The value of Fisher's test, F=0.39343 and a p-value of 0.03179, indicates that the variances for PM10 concentrations in April 2024 and April 2013 are significantly different at the 0.05 significance level.The results of Welch's t-test with a t-value of -0.7502 and a p-value of 0.4582 indicate a non-statistically significant difference in the mean PM10 concentrations between 2024 and 2013.Human exposure to high levels of air PM could pose significant health risks, necessitating a combination of measures at various levels, from individual actions to governmental policies, to improve air quality in the city.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".