Modeling study on distributions and variations of global dust aerosol sources and sinks
Bibliographic record
Abstract
Based on a 10-year(1995~2004) simulation of dust emissions and dry and wet depositions with the global air quality model system GEM-AQ/EC,the global spatial and temporal variations of the dust aerosol sources and sinks were characterized.Global dust emissions are centered over the major desert regions where the North African deserts are estimated with the largest emission contribution to the global dust aerosol up to 66.6%;the high dust aerosol depositions are concentrated over the desert sources and their immediately downwind areas.Thereby,the net dust aerosol sinks are largely distributed around the desert regions forming a receptor zone with the net sinks of greater than 10t/(km2·a)between 0°N and 60°N from North Africa,Eurasia,west Pacific Ocean,the north Indian Ocean, North America to the Atlantic ocean.In five major deserts of North Africa,Arabian Peninsula,Central Asia,East Asia and Australia,the dust emissions and depositions present the significant seasonal variations,The regional depositions expecting Central Asia experience almost the same seasonal cycle with the emissions;both dust aerosol emissions and depositions oscillate seasonally with the largest amplitudes in East Asia and with the lowest amplitudes in the North Africa.The seasonal dust emissions and depositions peak in summer over Central Asia and the Arabian Peninsula as well as during spring in the other three regions.Over the 10 years,the global annual emission is averaged with(150094)Mt in a slightly rising trend.The inter-annual variability rate of dust emissions in North Africa is lowest(6.3%),up to 28.3% in East Asia and highest in Australia(45.0%).The dust aerosol depositions over global land decrease at a rate of around 9.9Mt/a,while they increase year to year over the oceans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".