Emission inventories of primary particles and pollutant gases for China
Bibliographic record
Abstract
Detailed high-resolution emission inventories of primary particles (PM2.5, BC and OC) and pollutant gases (SO2, NO x , NH3, CO and VOCs) for China in 2007 were constructed on the basis of the latest fuel consumption data, mostly at the county level, and from socio-economic statistics and data on fossil and biomass fuels obtained from government agencies. New emission factors reflecting local features were also used. The calculated emissions were 13.212 Mt PM2.5, 1.4 Mt BC, 2.946 Mt OC, 31.584 Mt SO2, 23.248 Mt NO x , 16.017 Mt NH3, 164.856 Mt CO and 35.464 Mt VOCs. The national and regional emissions were gridded with 0.5° × 0.5° resolution for use in air quality models. Larger emissions were found in eastern and central China than in western China. The emissions estimated here are roughly equal to those obtained in previous studies, but with different contributions from because of seasonal changes in residential heating and biomass combustion. Finally, uncertainties in inventories were analyzed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".