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Article: Decarbonizing China’s Urban Agglomerations

TitleDecarbonizing China’s Urban Agglomerations
Authors
Keywordsaglomeraciones urbanas
imágenes de luminosidad nocturna
intensidad de la emisión de CO 2
modelado espaciotemporal
Issue Date2019
Citation
Annals of the American Association of Geographers, 2019, v. 109, n. 1, p. 266-285 How to Cite?
AbstractChina’s urban agglomerations contribute 64 percent to China’s energy-related CO 2 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 CO 2 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 CO 2 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 CO 2 intensities in western China, a convergence of CO 2 intensities across the country has occurred over the last few decades. Using panel regression modeling, we analyze differences in the decline of CO 2 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 CO 2 intensities are the ongoing industrialization that demands the increase in the production of heavy industry, in infrastructure investment, and in housing stock.
Persistent Identifierhttp://hdl.handle.net/10722/369309
ISSN
2023 Impact Factor: 3.2
2023 SCImago Journal Rankings: 1.510

 

DC FieldValueLanguage
dc.contributor.authorWang, Shaojian-
dc.contributor.authorFang, Chuanglin-
dc.contributor.authorSun, Laixiang-
dc.contributor.authorSu, Yongxian-
dc.contributor.authorChen, Xiuzhi-
dc.contributor.authorZhou, Chunshan-
dc.contributor.authorFeng, Kuishuang-
dc.contributor.authorHubacek, Klaus-
dc.date.accessioned2026-01-22T06:16:28Z-
dc.date.available2026-01-22T06:16:28Z-
dc.date.issued2019-
dc.identifier.citationAnnals of the American Association of Geographers, 2019, v. 109, n. 1, p. 266-285-
dc.identifier.issn2469-4452-
dc.identifier.urihttp://hdl.handle.net/10722/369309-
dc.description.abstractChina’s urban agglomerations contribute 64 percent to China’s energy-related CO <inf>2</inf> 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 CO <inf>2</inf> 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 CO <inf>2</inf> 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 CO <inf>2</inf> intensities in western China, a convergence of CO <inf>2</inf> intensities across the country has occurred over the last few decades. Using panel regression modeling, we analyze differences in the decline of CO <inf>2</inf> 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 CO <inf>2</inf> intensities are the ongoing industrialization that demands the increase in the production of heavy industry, in infrastructure investment, and in housing stock.-
dc.languageeng-
dc.relation.ispartofAnnals of the American Association of Geographers-
dc.subjectaglomeraciones urbanas-
dc.subjectimágenes de luminosidad nocturna-
dc.subjectintensidad de la emisión de CO 2-
dc.subjectmodelado espaciotemporal-
dc.titleDecarbonizing China’s Urban Agglomerations-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/24694452.2018.1484683-
dc.identifier.scopuseid_2-s2.0-85055718392-
dc.identifier.volume109-
dc.identifier.issue1-
dc.identifier.spage266-
dc.identifier.epage285-
dc.identifier.eissn2469-4460-

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