African dust particles over the western Caribbean – Part I: Impact on air quality over the Yucatán Peninsula
Bibliographic record
Abstract
On a global scale, African dust is known to be one of the major sources of mineral dust particles, as these particles can be efficiently transported to different parts of the planet. Several studies have suggested that the Yucatán Peninsula could be influenced by such particles, especially in July, associated with the strengthening of the Caribbean low-level jet. Although these particles have the potential to significantly impact the local air quality, as shown elsewhere (especially with respect to particulate matter, PM), the arrival and impact of African dust in Mexican territory has not been quantitatively reported to date. Two short-term field campaigns were conducted to confirm the arrival of African dust on the Yucatán Peninsula in July 2017 and July 2018 at the Mérida atmospheric observatory (20.98 ∘ N, 89.64 ∘ W). Aerosol particles were monitored at ground level using different online and off-line sensors. Several PM 2.5 and PM 10 peaks were observed during both sampling periods, with a relative increase in the PM levels ranging between 200 % and 500 % with respect to the normal background conditions. Given that these peaks were found to be highly correlated with supermicron particles and chemical elements typically found in mineral dust particles, such as Al, Fe, Si, and K, they are linked with African dust. This conclusion is supported by combining back trajectories with vertical profiles from radiosondes, reanalysis, and satellite images to show that the origin of the air masses arriving at Mérida was the Saharan Air Layer (SAL). The good agreement found between the measured PM 10 concentrations and the estimated dust mixing ratio content from MERRA-2 (Version 2 of the Modern-Era Retrospective analysis for Research and Applications) corroborates the conclusion that the degradation of the local (and likely regional) air quality in Mérida is a result of the arrival of African dust.
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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 | 0.001 | 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) | 0.001 | 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".