Energy Use and CO2 Emission Inventories in the Four Municipalities of China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emission inventories are important tools for monitoring air quality and assisting the policies in urban areas. This paper estimates Beijing, Shanghai, Tianjin, and Chongqing's CO2 emissions of energy consumption and carbon intensity of the economic activities in 1990, 1995, 2000 and 2004-2007 based on the method recommended by IPCC. The results show that the coal combustion is the leading cause of total CO2 emission from energy consumption, occupied over 60% of total CO2 emission of fuels. But the share of CO2 emission from coal is descending gradually because of energy consumption restructuring. In addition, the four mega-cities’ carbon intensity of the economic activities, which is the low Carbon Economy index, is improving persistently. These results imply that China's CO 2 emission in the future may not become as high as expected but improve with time.
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.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it