Characterization of Wintertime Air Pollution Concentrations and Variability in Ulaanbaatar, Mongolia
Bibliographic record
Abstract
S-30C1-2 Background/Aims: Ulaanbaatar, Mongolia's capital city, has recently undergone dramatic population growth, which has led to substantial increases in air pollution emissions. Major sources include 3 coal-fired power plants, residential wood and coal burning, and vehicles, some of which still use leaded gasoline. Temperature inversions and the surrounding topography lead to high wintertime concentrations. Methods: We measured air pollution in late February and March, 2010 using 3 measurement platforms to characterize wintertime concentration patterns of relevant pollutants. Daily filter-based particulate matter (PM)2.5 and PM10 and continuous light scattering were measured at a fixed monitoring station to assess temporal variability, and data on PM10, PM2.5, NO2, and SO2 were obtained, where available, from government monitoring sites. To characterize spatial gradients in PM2.5, mobile monitoring was conducted on 3 consecutive evenings (approximately 20:00–23:00) by driving preselected routes in a vehicle equipped with a GPS and a portable nephelometer. Spatial patterns in NO2 and SO2 were assessed with passive Ogawa samplers at 39 locations across the city. Results: Daily concentrations measured at a centrally located government monitoring site were high for PM10 (138 ± 39 μg/m3), PM2.5 (93 ± 33 μg/m3), NO2 (61 ± 10 μg/m3), and SO2 (69 ± 21 μg/m3). Mobile monitoring indicated strong PM2.5 spatial gradients and the spatial patterns were consistent across evenings, with highest concentrations in poorer neighborhoods where residential coal and wood burning is common. The highest PM2.5 concentrations measured by continuous fixed monitors generally occurred at around 08:00–09:00 and 22:00–0:00, consistent with periods of home heating. Land use regression models will be used to interpolate between the 39 Ogawa NO2/SO2 monitoring sites. PM2.5 filter samples will be analyzed by inductively coupled plasma mass spectrometry to quantify elemental constituents and infer source contributions. Conclusion: This work demonstrates the use of current exposure assessment techniques in a developing city and will aid future epidemiologic studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".