Building a mine-level database of methane emission factors for China’s underground coal
Bibliographic Data
| ID | 15550978 |
|---|---|
| Authors | Ziqi Wu (0009-0006-3042-8755, Tsinghua University, corresponding author), Yanwei Wang (0000-0001-6042-3206, Tsinghua University), Fei Teng (0000-0003-0371-1142, Tsinghua University) |
| Year | 2025 |
| Volume | 21 |
| Issue | 2 |
| Pages | 024003-024003 |
| Publication date | 2025-12-29 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/ae3190 |
| OpenAlex | W7117600692 |
| Language | EN |
| References cited | 46 |
Methane (CH 4 ) from China’s underground coal mines is a significant warming source and a priority for near-term mitigation. Yet mine-level inventories remain uncertain because publicly available measurements are sparse, outdated, and inconsistent. We assemble a 2011–2023 mine-level database of methane emission factors (EFs) by integrating the national coal-mine gas assessment with provincial disclosures and other sources. We harmonize definitions and impute missing data (10%–30% for key predictors; 23% for relative gas emissions) using a random-forest multiple-imputation framework incorporating geological and operational predictors and propagating uncertainty. The database reveals pronounced spatiotemporal heterogeneity, with a 92% reduction in small mines despite broadly stable national capacity. National production-weighted EFs declined from 5.39 kg t −1 in 2011 to 4.24 kg t −1 in 2020 as de-capacity policies retired high-emission mines and operational upgrades reduced intensities, and then rebounded to 4.78 kg t −1 in 2023, mainly due to higher production in provinces with above-average EFs, with a possible contribution from deeper mining. A persistent north–south gradient remains, and provinces dominated by coking coal exhibit systematically higher emissions. Selective non-disclosure by high-gas mines may introduce non-random missingness and bias the upper tail downward. Uncertainty analysis shows larger absolute but smaller relative errors for high-gas mines, with total uncertainty dominated by model generalization. The integrated dataset enables targeted mitigation at mine and provincial levels and provides a transparent basis for prioritizing high-emission and high-uncertainty regions. It highlights the need for standardized reporting, targeted measurements, and continuous updates to strengthen China’s coal-methane governance and NDC-aligned policy design
Coal · Coal mining · Corporate governance · Greenhouse gas · Methane · Production (economics · Atmospheric and Environmental Gas Dynamics · Coal Properties and Utilization · Mining and Resource Management
| Highly cited | No |
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