China Green Input-output Accounting: Coal, Efficiency of Power Generation and Green House Gas Emissions (1992–2020)
Bibliographic record
Abstract
While energy is a required factor in any kind of economic activity, most environmental problems, such as acid rain precipitation, greenhouse-gas emissions, and exhaustion of nonrenewable resources, seem to be related to overuse of primary energy. It is therefore important to consider energy within the framework of an integrated analysis of natural resources, economy, and the environment. In recent years, many scholars have studied this issue (see, for example, Balistreri & Rutherford, 2000; Jiang, 2002; Lin & Polenske, 1995; Xu et al.,2002; Zhang & Folmer, 1997) in the light of different but traditional input-output models. One kind of theoretical green input-output table, focused on energy, is designed on the basis of our Green Input-output Accounting Framework of Natural Resources-Economy- Environment. Scenario forecasting and analysis for China in 2020 are made. Coal used, without further transformation, mainly for power generation, is the major source of SO2 and CO2 emissions in China, and it will remain so without changes to the final and intermediate demand structures. Key words: Green input-output accounting, energy, structure and efficiency, scenario analysis Resume: Quand l’energie devient un facteur necessaire pout toute sorte d’activite economique, la plupart des problemes environnementaux, tels que la pluie acide, l’emission des gaz a effet de serre, l’epuisement des ressources nonrenouvelables semblent se rapporter avec l’abus de l’energie primaire. Donc il est important de considerer le probleme d’energie dans le cadre de l’analyse integree des ressources naturelles, l’economie et l’environnement. Dans les dernieres annees, beaucoup savants ont etudie ce probleme (voir, par exemple : Balistreri & Rutherford, 2000; Jiang, 2002; Lin & Polenske, 1995; Xu et al.,2002; Zhang & Folmer, 1997) a la lumiere de differents mais rationnels modeles des entrees et sorties. Une sorte de tableau des entrees et sorties vert, concentre sur l’energie, est concu sur la base de notre Cadre de la Comptabilite des Entrees et sorties Verte des Ressources Naturelles-Economie-Environnement. On a deja prevu et analyse le scenario de la Chine en 2020. Le charbon utilise, sans autre transformation, principalement pour la generation energitique , constitue la source majeure de l’emission de SO2 et CO2 en Chine, et cette situation va subsister sans aucun changement dans les structures de demande finale et intermediaire. Mots-Cles: comptabililte des entres et sortie verte, structure et efficacite, analyse du scenario
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".