Greenhouse Gas Emissions in the Process of Landfill Disposal in China
Bibliographic record
Abstract
Quantitative accounting of greenhouse gas (GHG) emissions has become an important global focus. GHG emissions from the waste sector have high potential in GHG emissions reduction. We analyzed the GHG emissions inventory in the waste sector of the European Union, Germany, the United Kingdom, the United States of America, and Canada from 1990 to 2019. Landfill disposal was the main category of GHGs from the waste sector, with a contribution rate between 69% and 95%. Landfill disposal also played a prominent role in emission reduction, with a contribution rate higher than 86%. GHG emissions from landfill sites in China were calculated using the inventory analysis method recommended by the IPCC and combined with actual situations. The results showed that the highest GHG emissions from landfill disposal in China occurred in 2020, with an estimated 165 million tons of carbon dioxide (CO2) equivalent. In 2019, the per capita GHG emissions from landfill sites in China was 117 kg CO2 equivalent/person, which was higher than Germany (87 kg CO2 equivalent/person) but lower than the European Union (189 kg CO2 equivalent/person).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".