Fifteen-Year Global Time Series of Satellite-Derived Fine Particulate Matter
Bibliographic record
Abstract
Ambient fine particulate matter (PM2.5) is a leading environmental risk factor for premature mortality. We use aerosol optical depth (AOD) retrieved from two satellite instruments, MISR and SeaWiFS, to produce a unified 15-year global time series (1998-2012) of ground-level PM2.5 concentration at a resolution of 1° x 1°. The GEOS-Chem chemical transport model (CTM) is used to relate each individual AOD retrieval to ground-level PM2.5. Four broad areas showing significant, spatially coherent, annual trends are examined in detail: the Eastern U.S. (-0.39 ± 0.10 μg m(-3) yr(-1)), the Arabian Peninsula (0.81 ± 0.21 μg m(-3) yr(-1)), South Asia (0.93 ± 0.22 μg m(-3) yr(-1)) and East Asia (0.79 ± 0.27 μg m(-3) yr(-1)). Over the period of dense in situ observation (1999-2012), the linear tendency for the Eastern U.S. (-0.37 ± 0.13 μg m(-3) yr(-1)) agrees well with that from in situ measurements (-0.38 ± 0.06 μg m(-3) yr(-1)). A GEOS-Chem simulation reveals that secondary inorganic aerosols largely explain the observed PM2.5 trend over the Eastern U.S., South Asia, and East Asia, while mineral dust largely explains the observed trend over the Arabian Peninsula.
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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 | 0.000 | 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 | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".