Measurement Report: Interpretation of Wide Range Particulate Matter Size Distributions in Delhi
Bibliographic record
Abstract
Abstract. Delhi is one of the world’s most polluted cities, with very high concentrations of airborne particulate matter. However, little is known on the factors controlling the characteristics of particle number size distributions. Here, new measurements are reported from three field campaigns conducted in winter, pre-monsoon and post-monsoon seasons on the Indian Insitute of Technology campus in the south of the city. Particle number size distributions were measured simultaneously using a Scanning Mobility Particle Sizer and a Grimm optical particle monitor, covering 15 nm to > 10 µm diameter. The merged, wide-range size distributions were categorised into five size ranges: nucleation (15–20 nm), Aitken (20–100 nm), accumulation (100 nm–1 µm), large fine (1–2.5 µm) and coarse (2.5–10 µm) particles. The ultrafine fraction (15–100 nm) accounts for about 52 % of all particles by number (PN10), but just 1 % by PM10 volume (PV10). The measured size distributions are markedly coarser than most from other parts of the world, but are consistent with earlier cascade impactor data from Delhi. Our results suggest substantial aerosol processing by coagulation, condensation and water uptake in the heavily polluted atmosphere, which takes place mostly at nighttime and in the morning hours. Total number concentrations are highest in winter, but the mode of the distribution is largest in the post-monsoon (autumn) season. The accumulation mode particles dominate the particle volume in autumn and winter, while the coarse mode dominates in summer. Polar plots show a huge variation between both size fractions in the same season and between seasons for the same size fraction. The diurnal pattern of particle numbers is strongly reflective of a road traffic influence upon concentrations, especially in autumn and winter. There is a clear influence of diesel traffic at nighttime when it is permitted to enter the city, and also indications in the size distribution data of a mode < 15 nm, probably attributable to CNG/LPG vehicles. New particle formation appears to be infrequent, and in this dataset is limited to one day in the summer campaign. Our results reveal that the very high emissions of airborne particles in Delhi, particularly from traffic, determine the variation of particle number size distributions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".