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- Publisher Website: 10.5194/acp-20-11371-2020
- Scopus: eid_2-s2.0-85093860249
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Article: Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories
Title | Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories |
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Authors | |
Issue Date | 2020 |
Citation | Atmospheric Chemistry and Physics, 2020, v. 20, n. 19, p. 11371-11385 How to Cite? |
Abstract | China s fossil-fuel CO2 (FFCO2) emissions accounted for approximately 28% of the global total FFCO2 in 2016. An accurate estimate of China s FFCO2 emissions is a prerequisite for global and regional carbon budget analyses and the monitoring of carbon emission reduction efforts. However, significant uncertainties and discrepancies exist in estimations of China s FFCO2 emissions due to a lack of detailed traceable emission factors (EFs) and multiple statistical data sources. Here, we evaluated China s FFCO2 emissions from nine published global and regional emission datasets. These datasets show that the total emissions increased from 3.4 (3.0 3.7) in 2000 to 9.8 (9.2 10.4) Gt CO2 yr-1 in 2016. The variations in these estimates were largely due to the different EF (0.491 0.746 t C per t of coal) and activity data. The large-scale patterns of gridded emissions showed a reasonable agreement, with high emissions being concentrated in major city clusters, and the standard deviation mostly ranged from 10% to 40% at the provincial level. However, patterns beyond the provincial scale varied significantly, with the top 5% of the grid level accounting for 50 % 90% of total emissions in these datasets. Our findings highlight the significance of using locally measured EF for Chinese coal. To reduce uncertainty, we recommend using physical CO2 measurements and use these values for dataset validation, key input data sharing (e.g., point sources), and finer-resolution validations at various levels. |
Persistent Identifier | http://hdl.handle.net/10722/334694 |
ISSN | 2023 Impact Factor: 5.2 2023 SCImago Journal Rankings: 2.138 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Han, Pengfei | - |
dc.contributor.author | Zeng, Ning | - |
dc.contributor.author | Oda, Tom | - |
dc.contributor.author | Lin, Xiaohui | - |
dc.contributor.author | Crippa, Monica | - |
dc.contributor.author | Guan, Dabo | - |
dc.contributor.author | Janssens-Maenhout, Greet | - |
dc.contributor.author | Ma, Xiaolin | - |
dc.contributor.author | Liu, Zhu | - |
dc.contributor.author | Shan, Yuli | - |
dc.contributor.author | Tao, Shu | - |
dc.contributor.author | Wang, Haikun | - |
dc.contributor.author | Wang, Rong | - |
dc.contributor.author | Wu, Lin | - |
dc.contributor.author | Yun, Xiao | - |
dc.contributor.author | Zhang, Qiang | - |
dc.contributor.author | Zhao, Fang | - |
dc.contributor.author | Zheng, Bo | - |
dc.date.accessioned | 2023-10-20T06:49:59Z | - |
dc.date.available | 2023-10-20T06:49:59Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Atmospheric Chemistry and Physics, 2020, v. 20, n. 19, p. 11371-11385 | - |
dc.identifier.issn | 1680-7316 | - |
dc.identifier.uri | http://hdl.handle.net/10722/334694 | - |
dc.description.abstract | China s fossil-fuel CO2 (FFCO2) emissions accounted for approximately 28% of the global total FFCO2 in 2016. An accurate estimate of China s FFCO2 emissions is a prerequisite for global and regional carbon budget analyses and the monitoring of carbon emission reduction efforts. However, significant uncertainties and discrepancies exist in estimations of China s FFCO2 emissions due to a lack of detailed traceable emission factors (EFs) and multiple statistical data sources. Here, we evaluated China s FFCO2 emissions from nine published global and regional emission datasets. These datasets show that the total emissions increased from 3.4 (3.0 3.7) in 2000 to 9.8 (9.2 10.4) Gt CO2 yr-1 in 2016. The variations in these estimates were largely due to the different EF (0.491 0.746 t C per t of coal) and activity data. The large-scale patterns of gridded emissions showed a reasonable agreement, with high emissions being concentrated in major city clusters, and the standard deviation mostly ranged from 10% to 40% at the provincial level. However, patterns beyond the provincial scale varied significantly, with the top 5% of the grid level accounting for 50 % 90% of total emissions in these datasets. Our findings highlight the significance of using locally measured EF for Chinese coal. To reduce uncertainty, we recommend using physical CO2 measurements and use these values for dataset validation, key input data sharing (e.g., point sources), and finer-resolution validations at various levels. | - |
dc.language | eng | - |
dc.relation.ispartof | Atmospheric Chemistry and Physics | - |
dc.title | Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.5194/acp-20-11371-2020 | - |
dc.identifier.scopus | eid_2-s2.0-85093860249 | - |
dc.identifier.volume | 20 | - |
dc.identifier.issue | 19 | - |
dc.identifier.spage | 11371 | - |
dc.identifier.epage | 11385 | - |
dc.identifier.eissn | 1680-7324 | - |
dc.identifier.isi | WOS:000578982100001 | - |