A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories

被引:46
作者
Han, Pengfei [1 ]
Zeng, Ning [2 ,3 ]
Oda, Tomohiro [2 ,3 ,4 ,5 ]
Zhang, Wen [6 ]
Lin, Xiaohui [6 ]
Liu, Di [1 ]
Cai, Qixiang [1 ]
Ma, Xiaolin [7 ]
Meng, Wenjun [8 ]
Wang, Guocheng [6 ]
Wang, Rong [9 ]
Zheng, Bo [10 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
[2] Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA
[3] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA
[4] Univ Space Res Assoc, Goddard Earth Sci Res & Technol, Columbia, MD USA
[5] NASA, Goddard Space Flight Ctr, Global Modeling & Assimilat Off, Greenbelt, MD USA
[6] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing, Peoples R China
[7] Nanjing Univ, Sch Environm, State Key Lab Pollut Control & Resource Reuse, Nanjing, Peoples R China
[8] Peking Univ, Coll Urban & Environm Sci, Lab Earth Surface Proc, Beijing, Peoples R China
[9] Fudan Univ, Dept Environm Sci & Engn, Shanghai, Peoples R China
[10] CEA CNRS UVSQ, Lab Sci Climat & Environm, UMR8212, Gif Sur Yvette, France
基金
国家重点研发计划;
关键词
City-level fossil fuel CO2; Industry processes; Multiple inventories; Policy making; CO2; monitoring; CARBON-DIOXIDE EMISSIONS; CHINA; ENERGY; UNCERTAINTIES; QUANTIFICATION; COMBUSTION; PROVINCES; PATTERNS; DATABASE;
D O I
10.1186/s13021-020-00163-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background Quantifying CO2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO2 emissions. As the largest urbanized megalopolis region in northern China, the Beijing-Tianjin-Hebei (Jing-Jin-Ji, JJJ) region (population: 112.7 million) is under considerable pressure to reduce carbon emissions. Despite the several emission inventories covering the JJJ region, a comprehensive evaluation of the CO2 emissions at the prefectural city scale in JJJ is still limited, and this information is crucial to implementing mitigation strategies. Results Here, we collected and analyzed 8 published emission inventories to assess the emissions and uncertainty at the JJJ city level. The results showed that a large discrepancy existed in the JJJ emissions among downscaled country-level emission inventories, with total emissions ranging from 657 to 1132 Mt CO2 (or 849 +/- 214 for mean +/- standard deviation (SD)) in 2012, while emission estimates based on provincial-level data estimated emissions to be 1038 and 1056 Mt. Compared to the mean emissions of city-data-based inventories (989 Mt), provincial-data-based inventories were 6% higher, and national-data-based inventories were 14% lower. Emissions from national-data-based inventories were 53-75% lower in the high-emitting industrial cities of Tangshan and Handan, while they were 47-160% higher in Beijing and Tianjin than those from city-data-based inventories. Spatially, the emissions pattern was consistent with the distribution of urban areas, and urban emissions in Beijing contributed 50-70% of the total emissions. Higher emissions from Beijing and Tianjin resulted in lower estimates of prefectural cities in Hebei for some national inventories. Conclusions National-level data-based emission inventories produce large differences in JJJ prefectural city-level emission estimates. The city-level statistics data-based inventories produced more consistent estimates. The consistent spatial distribution patterns recognized by these inventories (such as high emissions in southern Beijing, central Tianjin and Tangshan) potentially indicate areas with robust emission estimates. This result could be useful in the efficient deployment of monitoring instruments, and if proven by such measurements, it will increase our confidence in inventories and provide support for policy makers trying to reduce emissions in key regions.
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页数:16
相关论文
共 64 条
[1]  
[Anonymous], 2014, CLIM CHANG 2014 MIT
[2]  
[Anonymous], 2016, China Energy Statistical Yearbook 2015
[3]   A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of results [J].
Asefi-Najafabady, S. ;
Rayner, P. J. ;
Gurney, K. R. ;
McRobert, A. ;
Song, Y. ;
Coltin, K. ;
Huang, J. ;
Elvidge, C. ;
Baugh, K. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2014, 119 (17) :10,213-10,231
[4]   Observation and modeling of vertical carbon dioxide distribution in a heavily polluted suburban environment [J].
BAO, Zhongxiu ;
HAN, Pengfei ;
ZENG, Ning ;
LIU, Di ;
CAI, Qixiang ;
WANG, Yinghong ;
TANG, Guiqian ;
ZHENG, Ke ;
YAO, Bo .
ATMOSPHERIC AND OCEANIC SCIENCE LETTERS, 2020, 13 (04) :371-379
[5]   China city-level greenhouse gas emissions inventory in 2015 and uncertainty analysis [J].
Cai, Bofeng ;
Cui, Can ;
Zhang, Da ;
Cao, Libin ;
Wu, Pengcheng ;
Pang, Lingyun ;
Zhang, Jihong ;
Dai, Chunyan .
APPLIED ENERGY, 2019, 253
[6]   A benchmark city-level carbon dioxide emission inventory for China in 2005 [J].
Cai, Bofeng ;
Lu, Jun ;
Wang, Jinnan ;
Dong, Huijuan ;
Liu, Xiaoman ;
Chen, Yang ;
Chen, Zhanming ;
Cong, Jianhui ;
Cui, Zhipeng ;
Dai, Chunyan ;
Fang, Kai ;
Feng, Tong ;
Guo, Jie ;
Li, Fen ;
Meng, Fanxin ;
Tang, Wei ;
Wang, Gengzhe ;
Xie, Yunsheng ;
Zhang, Jianjun .
APPLIED ENERGY, 2019, 233 :659-673
[7]   China high resolution emission database (CHRED) with point emission sources, gridded emission data, and supplementary socioeconomic data [J].
Cai, Bofeng ;
Liang, Sai ;
Zhou, Jiong ;
Wang, Jinnan ;
Cao, Libin ;
Qu, Shen ;
Xu, Ming ;
Yang, Zhifeng .
RESOURCES CONSERVATION AND RECYCLING, 2018, 129 :232-239
[8]   Source data supported high resolution carbon emissions inventory for urban areas of the Beijing-Tianjin-Hebei region: Spatial patterns, decomposition and policy implications [J].
Cai, Bofeng ;
Li, Wanxin ;
Dhakal, Shobhakar ;
Wang, Jianghao .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2018, 206 :786-799
[9]   Comparing a global high-resolution downscaled fossil fuel CO2 emission dataset to local inventory-based estimates over 14 global cities [J].
Chen, Jingwen ;
Zhao, Fang ;
Zeng, Ning ;
Oda, Tomohiro .
CARBON BALANCE AND MANAGEMENT, 2020, 15 (01)
[10]   Interprovincial transfer of embodied energy between the Jing-Jin-Ji area and other provinces in China: A quantification using interprovincial input-output model [J].
Chen, Weiming ;
Wu, Sanmang ;
Lei, Yalin ;
Li, Shantong .
SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 584 :990-1003