Chemical Characterization and Source Apportionment of PM2.5 in Rabigh, Saudi Arabia
Bibliographic record
Abstract
The present study describes the measurement, chemical characterization and delineation of sources of fine particulate matter (PM2.5) in Rabigh, Saudi Arabia. The 24-h PM2.5 was collected from May 6th–June 17th, 2013. The sources of various air pollutants and their characterization was carried by computations of Enrichment Factor (EF), Positive Matrix Factorization (PMF) and Backward-in-time Trajectories. The 24-h PM2.5 showed significant temporal variability with average (37 ± 16.2 μg m–3) exceeding the WHO guideline (20 μg m–3) by 2 fold. SO42–, NO3–, NH4+ and Cl– ions dominated the ionic components. Two broad categories of aerosol Trace Elements (TEs) sources were defined as anthropogenic (Ni, V, Zn, Pb, S, Lu and Br) and soil/crustal derived (Si, Rb, Ti, Fe, Mn, Mg, K, Sr, Cr, Ca, Cu, Na and Al) elements from computations of EF. Anthropogenic elements originated primarily from fossil-fuel combustion, automobile and industrial emissions. A factor analysis model (PMF) indicated the major sources of PM2.5 as Soil (Si, Al, Ti, Fe, Mg, K and Ca); Industrial Dust (Ca, Fe, Al, and Si); Fossil-Fuel combustion (V, Ni, Pb, Lu, Cu, Zn, NH4+, SO42– and BC); Vehicular Emissions (NO3–, C2O42–, V and BC) and Sea Sprays (Cl– and Na). Backward-in-time trajectories showed a significant contribution by long distance transport of fine aerosols to the overall daily PM2.5 levels. Results are consistent with previous studies and highlight the need for more comprehensive research into particulate air pollution in Rabigh and the neighboring areas. This is essential for the formulation of sustainable guidelines on air pollutant emissions in Saudi Arabia and the whole Middle East.
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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 | 0.003 | 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 | 0.001 |
| 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".