Global Chemical Composition of Ambient Fine Particulate Matter for Exposure Assessment
Bibliographic record
Abstract
Epidemiologic and health impact studies are inhibited by the paucity of global, long-term measurements of the chemical composition of fine particulate matter. We inferred PM2.5 chemical composition at 0.1° × 0.1° spatial resolution for 2004-2008 by combining aerosol optical depth retrieved from the MODIS and MISR satellite instruments, with coincident profile and composition information from the GEOS-Chem global chemical transport model. Evaluation of the satellite-model PM2.5 composition data set with North American in situ measurements indicated significant spatial agreement for secondary inorganic aerosol, particulate organic mass, black carbon, mineral dust, and sea salt. We found that global population-weighted PM2.5 concentrations were dominated by particulate organic mass (11.9 ± 7.3 μg/m(3)), secondary inorganic aerosol (11.1 ± 5.0 μg/m(3)), and mineral dust (11.1 ± 7.9 μg/m(3)). Secondary inorganic PM2.5 concentrations exceeded 30 μg/m(3) over East China. Sensitivity simulations suggested that population-weighted ambient PM2.5 from biofuel burning (11 μg/m(3)) could be almost as large as from fossil fuel combustion sources (17 μg/m(3)). These estimates offer information about global population exposure to the chemical components and sources of PM2.5.
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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 | 0.001 | 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) | 0.001 | 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 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".