A comparison of PM <sub>2.5</sub> -bound polycyclic aromatic hydrocarbons in summer Beijing (China) and Delhi (India)
Bibliographic record
Abstract
Abstract. Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air, soil and water and known to have harmful effects on human health and the environment. The diurnal and nocturnal variation of 17-PAHs in ambient particle-bound PAHs were measured in urban Beijing (China) and Delhi (India) during the summer season using GC-Q-TOF-MS. The mean concentration of particles less than 2.5 microns (PM2.5) observed in Delhi was 3.6 times higher than in Beijing during the measurement period in both the day-time and night-time. In Beijing, the mean concentration of the sum of the 17 PAHs (∑17-PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the highest contribution from Indeno[1,2,3-cd]pyrene (12 %), while at night-time the total PAHs was 7.2 ± 2.0 ng m−3, with the largest contribution from Benzo[b]fluoranthene (14 %). In Delhi, the mean ∑17-PAHs was 13.6 ± 5.9 ng m−3 in daytime, and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from Indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %). Elevated mean concentrations of total PAHs in Delhi observed at night were attributed to emissions from vehicles and biomass burning and to meteorological conditions leading to their accumulation from a stable and low atmospheric boundary layer. Local emission sources were typically identified as the major contributors to total measured PAHs, however, in Delhi 25 % of the emissions were attributed to long-range atmospheric transport. Major emission sources were characterized based on the contribution from each class of PAHs, with the 4, 5, and 6 ring PAHs accounting ~ 95 % of the total PM2.5-bound PAHs mass in both locations. The high contribution of 5 ring PAHs to total PAH concentration in summer Beijing and Delhi suggests a high contribution from petroleum combustion. In Delhi, a high contribution from 6 ring PAHs was observed at night, suggesting a potential emission source from the combustion of fuel and oil in power generators, widely used in Delhi. The lifetime excess lung cancer risk (LECR) was calculated for Beijing and Delhi, with the highest estimated risk attributed to Delhi (LECR = 155 per million people), 2.2 times higher than Beijing risk assessment value (LECR = 70 per million people). Finally, we have assessed the emission control policies in each city and identified those major sectors that could be subject to mitigation measures.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".