Remarkable Spatial Disparity of Life Cycle Inventory for Coal Production in China
Bibliographic record
Abstract
Coal is the primary energy source in China, and its life cycle inventory (LCI) is widely used as background data for life cycle assessment studies. Previous research indicates that the inventory of coal production varies regionally. However, the development of complete regionalized LCIs for coal production is quite limited. Here, we establish the first provincial-level LCIs of local coal production and market for coal in China, based on a database of 6,122 coal mines and developed models. In the inventory results of local coal production, the coefficients of variation (CVs) of nine indicators exceed 0.5, especially SO 2 and particulate matter emission factors (CVs > 1). Compared with that, the interprovincial coal trade homogenizes the provincial production inventory of market for coal relatively, despite four indicators with CVs exceeding 0.5. Therefore, the regionalized inventory with remarkable spatial differentiation can provide more accurate fundamental data for future research such as electricity production. Furthermore, CH 4 emissions from coal production account for 24% of China’s total methane emissions, highlighting its significance in mitigating global warming. Moreover, through the increasing coal trade, the significant and implicit plunder of water resources from the three coal net-exporting provinces, located in water-scarce areas, should be noted.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".