Spatiotemporal variations of CO2 emissions and their impact factors in China: A comparative analysis between the provincial and prefectural levels
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DOI: 10.1016/j.apenergy.2018.10.050
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- Shaojian Wang & Chuanglin Fang & Guangdong Li, 2015. "Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-23, September.
- Pao, Hsiao-Tien & Tsai, Chung-Ming, 2010. "CO2 emissions, energy consumption and economic growth in BRIC countries," Energy Policy, Elsevier, vol. 38(12), pages 7850-7860, December.
- Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
- Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Yang, Chengshu & Li, Linyi & Huang, Chang & Chen, Zuoqi & Liu, Rui & Wu, Jianping, 2016. "Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data," Applied Energy, Elsevier, vol. 184(C), pages 450-463.
- Al-mulali, Usama, 2012. "Factors affecting CO2 emission in the Middle East: A panel data analysis," Energy, Elsevier, vol. 44(1), pages 564-569.
- Grunewald, Nicole & Jakob, Michael & Mouratiadou, Ioanna, 2014.
"Decomposing inequality in CO2 emissions: The role of primary energy carriers and economic sectors,"
Ecological Economics, Elsevier, vol. 100(C), pages 183-194.
- Grunewald, Nicole & Jakob, Michael & Mouratiadou, Ioanna, 2013. "Decomposing Inequality in CO2 Emissions: the Role of Primary Energy Carriers and Economic Sectors," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79779, Verein für Socialpolitik / German Economic Association.
- Wang, Shaojian & Liu, Xiaoping, 2017. "China’s city-level energy-related CO2 emissions: Spatiotemporal patterns and driving forces," Applied Energy, Elsevier, vol. 200(C), pages 204-214.
- Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.
- Al-mulali, Usama & Lee, Janice YM & Hakim Mohammed, Abdul & Sheau-Ting, Low, 2013. "Examining the link between energy consumption, carbon dioxide emission, and economic growth in Latin America and the Caribbean," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 42-48.
- Sweety Pandey & Mrutyunjaya Mishra, 2015. "CO2 Emissions and Economic Growth of SAARC Countries: Evidence from a Panel VAR Analysis," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 1(2), pages 23-33, December.
- Burnett, J. Wesley & Bergstrom, John C. & Dorfman, Jeffrey H., 2013. "A spatial panel data approach to estimating U.S. state-level energy emissions," Energy Economics, Elsevier, vol. 40(C), pages 396-404.
- Ang, B.W & Zhang, F.Q & Choi, Ki-Hong, 1998. "Factorizing changes in energy and environmental indicators through decomposition," Energy, Elsevier, vol. 23(6), pages 489-495.
- Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
- Su, Yongxian & Chen, Xiuzhi & Li, Yong & Liao, Jishan & Ye, Yuyao & Zhang, Hongou & Huang, Ningsheng & Kuang, Yaoqiu, 2014. "China׳s 19-year city-level carbon emissions of energy consumptions, driving forces and regionalized mitigation guidelines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 231-243.
- Li, Huanan & Mu, Hailin & Zhang, Ming & Li, Nan, 2011. "Analysis on influence factors of China's CO2 emissions based on Path–STIRPAT model," Energy Policy, Elsevier, vol. 39(11), pages 6906-6911.
- Fang, Chuanglin & Wang, Shaojian & Li, Guangdong, 2015. "Changing urban forms and carbon dioxide emissions in China: A case study of 30 provincial capital cities," Applied Energy, Elsevier, vol. 158(C), pages 519-531.
- Meng, Lina & Graus, Wina & Worrell, Ernst & Huang, Bo, 2014. "Estimating CO2 (carbon dioxide) emissions at urban scales by DMSP/OLS (Defense Meteorological Satellite Program's Operational Linescan System) nighttime light imagery: Methodological challenges and a ," Energy, Elsevier, vol. 71(C), pages 468-478.
- Yunjing Wang & Yoshitsugu Hayashi & Jin Chen & Qiang Li, 2014. "Changing Urban Form and Transport CO 2 Emissions: An Empirical Analysis of Beijing, China," Sustainability, MDPI, vol. 6(7), pages 1-22, July.
- Shi, Kaifang & Chen, Yun & Li, Linyi & Huang, Chang, 2018. "Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective," Applied Energy, Elsevier, vol. 211(C), pages 218-229.
- Malte Meinshausen & Nicolai Meinshausen & William Hare & Sarah C. B. Raper & Katja Frieler & Reto Knutti & David J. Frame & Myles R. Allen, 2009. "Greenhouse-gas emission targets for limiting global warming to 2 °C," Nature, Nature, vol. 458(7242), pages 1158-1162, April.
- Wang, Shaojian & Fang, Chuanglin & Guan, Xingliang & Pang, Bo & Ma, Haitao, 2014. "Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces," Applied Energy, Elsevier, vol. 136(C), pages 738-749.
- Andreoni, Valeria & Galmarini, Stefano, 2016. "Drivers in CO2 emissions variation: A decomposition analysis for 33 world countries," Energy, Elsevier, vol. 103(C), pages 27-37.
- Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
- Ana Petrović & Maarten van Ham & David Manley, 2018. "Multiscale Measures of Population: Within- and between-City Variation in Exposure to the Sociospatial Context," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 108(4), pages 1057-1074, July.
- Zhou, Yuyu & Clarke, Leon & Eom, Jiyong & Kyle, Page & Patel, Pralit & Kim, Son H. & Dirks, James & Jensen, Erik & Liu, Ying & Rice, Jennie & Schmidt, Laurel & Seiple, Timothy, 2014. "Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework," Applied Energy, Elsevier, vol. 113(C), pages 1077-1088.
- Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
- Jayanthakumaran, Kankesu & Verma, Reetu & Liu, Ying, 2012. "CO2 emissions, energy consumption, trade and income: A comparative analysis of China and India," Energy Policy, Elsevier, vol. 42(C), pages 450-460.
- Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Chen, Zuoqi & Liu, Rui & Li, Linyi & Wu, Jianping, 2016. "Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis," Applied Energy, Elsevier, vol. 168(C), pages 523-533.
- Long, Ruyin & Shao, Tianxiang & Chen, Hong, 2016. "Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors," Applied Energy, Elsevier, vol. 166(C), pages 210-219.
- Wang, Shaojian & Li, Guangdong & Fang, Chuanglin, 2018. "Urbanization, economic growth, energy consumption, and CO2 emissions: Empirical evidence from countries with different income levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2144-2159.
- Mussini, Mauro & Grossi, Luigi, 2015. "Decomposing changes in CO2 emission inequality over time: The roles of re-ranking and changes in per capita CO2 emission disparities," Energy Economics, Elsevier, vol. 49(C), pages 274-281.
- Zhang, Yanxia & Wang, Haikun & Liang, Sai & Xu, Ming & Liu, Weidong & Li, Shalang & Zhang, Rongrong & Nielsen, Chris P. & Bi, Jun, 2014. "Temporal and spatial variations in consumption-based carbon dioxide emissions in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 60-68.
- Clarke-Sather, Afton & Qu, Jiansheng & Wang, Qin & Zeng, Jingjing & Li, Yan, 2011. "Carbon inequality at the sub-national scale: A case study of provincial-level inequality in CO2 emissions in China 1997-2007," Energy Policy, Elsevier, vol. 39(9), pages 5420-5428, September.
- Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
- Pappas, Dimitrios & Chalvatzis, Konstantinos J. & Guan, Dabo & Ioannidis, Alexis, 2018. "Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia," Applied Energy, Elsevier, vol. 225(C), pages 183-194.
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Keywords
CO2 emissions; Nighttime light; Spatial autocorrelation; Spatial econometric model;All these keywords.
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