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@article{1460956, author = {Wang, Shaojian and Fang, Chuanglin and Sun, Laixiang and Su, Yongxian and Chen, Xiuzhi and Zhou, Chunshan and Feng, Kuishuang and Hubacek, Klaus}, article_location = {Abingdon}, article_number = {1}, doi = {http://dx.doi.org/10.1080/24694452.2018.1484683}, keywords = {urban aglomerations; night light resolution; CO2 emissions intensity; spatiotemporal modelling}, language = {eng}, issn = {2469-4452}, journal = {Annals of the American Association of Geographers}, title = {Decarbonizing China’s Urban Agglomerations}, url = {https://www.tandfonline.com/doi/full/10.1080/24694452.2018.1484683}, volume = {109}, year = {2019} }
TY - JOUR ID - 1460956 AU - Wang, Shaojian - Fang, Chuanglin - Sun, Laixiang - Su, Yongxian - Chen, Xiuzhi - Zhou, Chunshan - Feng, Kuishuang - Hubacek, Klaus PY - 2019 TI - Decarbonizing China’s Urban Agglomerations JF - Annals of the American Association of Geographers VL - 109 IS - 1 SP - 266-285 EP - 266-285 PB - Routledge, Taylor & Francis SN - 24694452 KW - urban aglomerations KW - night light resolution KW - CO2 emissions intensity KW - spatiotemporal modelling UR - https://www.tandfonline.com/doi/full/10.1080/24694452.2018.1484683 L2 - https://www.tandfonline.com/doi/full/10.1080/24694452.2018.1484683 N2 - China’s urban agglomerations contribute 64 percent to China’s energy-related CO2 emissions and thus play a vital role in determining the future of climate change. There is little information available about city-level energy consumption and CO2 emissions; thus, we employ spatiotemporal modeling using Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) nighttime light imagery. Our findings show that such agglomerations have in fact experienced a remarkable decline in CO2 emission intensity—from 0.43 t/thousand yuan to 0.20 t/thousand yuan between 1995 and 2013, which constitutes an average annual decline of 4.34 percent. Despite still very high CO2 intensities in western China, a convergence of CO2 intensities across the country has occurred over the last few decades. Using panel regression modeling, we analyze differences in the decline of CO2 emission intensities due to regional differences in socioeconomic variables such as economic growth, population, economic structure, population density, and characteristics of urbanization. Factors that have hampered the decline of CO2 intensities are the ongoing industrialization that demands the increase in the production of heavy industry, in infrastructure investment, and in housing stock. Key Words: CO2 emission intensity, nighttime light imagery, spatiotemporal modeling, urban agglomerations. ER -
WANG, Shaojian, Chuanglin FANG, Laixiang SUN, Yongxian SU, Xiuzhi CHEN, Chunshan ZHOU, Kuishuang FENG and Klaus HUBACEK. Decarbonizing China’s Urban Agglomerations. \textit{Annals of the American Association of Geographers}. Abingdon: Routledge, Taylor \&{} Francis, 2019, vol.~109, No~1, p.~266-285. ISSN~2469-4452. Available from: https://dx.doi.org/10.1080/24694452.2018.1484683.
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