Influencing Factors of Energy-Related CO2 Emissions in China: A Decomposition Analysis
Bibliographic record
Abstract
China is the largest CO2 emitter in the world and is still reliant on energy consumption for economic growth. Research has focused on effective approaches of reducing and mitigating CO2 emissions. This paper undertakes a decomposition study of energy-related CO2 emissions from the industrial and household sectors during the period 1996–2012, with the objectives of investigating trends of the changes in energy-related CO2 emissions, the driving forces of these changes, and approaches of mitigating CO2 emission. Results show the following: (1) the expansion of economic activity is the dominant stimulatory factor of the increase of CO2 emissions in China and that a sustained increase in CO2 emissions can be expected; (2) the decline in energy intensity and the adjustment of energy mix and industrial structure effectively mitigate CO2 emissions; and (3) the government should give more attention to enhancing the energy utility efficiency and reducing CO2 emissions in rural households.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".