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Article: Reprint of: The impact of urbanization on carbon emissions in developing countries: a Chinese study based on the U-Kaya method

TitleReprint of: The impact of urbanization on carbon emissions in developing countries: a Chinese study based on the U-Kaya method
Authors
KeywordsCarbon emissions
Forecasting
U-Kaya identity
Urbanization
Issue Date2017
Citation
Journal of Cleaner Production, 2017, v. 163, p. S284-S298 How to Cite?
AbstractUrbanization results in a considerable economic disparity between urban and rural areas in developing countries, which has had a consequent significant impact on CO2 emissions. To accommodate this directly, this paper presents a modified version of the Kaya Identity formula, U-Kaya, that includes a direct urbanization factor to determine the relationship between energy consumption intensity, population growth, urbanization rates, urban and rural GDP per capita and the volume of carbon emissions, for application in the dynamic forecasting of carbon emissions by Monte Carlo simulation. The method is demonstrated in forecasting China's likely carbon emissions in 2020 by three different modes of urbanization policy: the government-dominant mode, market-dominant mode and a hybrid government market-dominant mode. The results indicate that a higher urbanization rate, energy carbon emission coefficient and energy intensity will lead to increased carbon emissions. Finally, three policy implications are identified, comprising the narrowing of the economic gap between urban and rural areas, adjustments to the energy structure and technical innovation, which will provide a valuable reference for developing countries in their efforts to reduce carbon emissions.
Persistent Identifierhttp://hdl.handle.net/10722/333329
ISSN
2023 Impact Factor: 9.7
2023 SCImago Journal Rankings: 2.058
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWu, Yuzhe-
dc.contributor.authorShen, Jiahui-
dc.contributor.authorZhang, Xiaoling-
dc.contributor.authorSkitmore, Martin-
dc.contributor.authorLu, Wisheng-
dc.date.accessioned2023-10-06T05:18:31Z-
dc.date.available2023-10-06T05:18:31Z-
dc.date.issued2017-
dc.identifier.citationJournal of Cleaner Production, 2017, v. 163, p. S284-S298-
dc.identifier.issn0959-6526-
dc.identifier.urihttp://hdl.handle.net/10722/333329-
dc.description.abstractUrbanization results in a considerable economic disparity between urban and rural areas in developing countries, which has had a consequent significant impact on CO2 emissions. To accommodate this directly, this paper presents a modified version of the Kaya Identity formula, U-Kaya, that includes a direct urbanization factor to determine the relationship between energy consumption intensity, population growth, urbanization rates, urban and rural GDP per capita and the volume of carbon emissions, for application in the dynamic forecasting of carbon emissions by Monte Carlo simulation. The method is demonstrated in forecasting China's likely carbon emissions in 2020 by three different modes of urbanization policy: the government-dominant mode, market-dominant mode and a hybrid government market-dominant mode. The results indicate that a higher urbanization rate, energy carbon emission coefficient and energy intensity will lead to increased carbon emissions. Finally, three policy implications are identified, comprising the narrowing of the economic gap between urban and rural areas, adjustments to the energy structure and technical innovation, which will provide a valuable reference for developing countries in their efforts to reduce carbon emissions.-
dc.languageeng-
dc.relation.ispartofJournal of Cleaner Production-
dc.subjectCarbon emissions-
dc.subjectForecasting-
dc.subjectU-Kaya identity-
dc.subjectUrbanization-
dc.titleReprint of: The impact of urbanization on carbon emissions in developing countries: a Chinese study based on the U-Kaya method-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jclepro.2017.05.144-
dc.identifier.scopuseid_2-s2.0-85047640304-
dc.identifier.volume163-
dc.identifier.spageS284-
dc.identifier.epageS298-
dc.identifier.isiWOS:000416300200027-

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