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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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