He, Q, Jiang, X, Gouldson, A orcid.org/0000-0002-1464-6465 et al. (6 more authors) (2016) Climate change mitigation in Chinese megacities: A measures-based analysis of opportunities in the residential sector. Applied Energy, 184. pp. 769-778. ISSN 0306-2619
Abstract
China’s commitment to the UNFCCC to peak its emissions by 2030, or sooner, signaled a long anticipated shift in China’s model of development with far reaching consequences. Cities in China, and particularly the residential sector in cities, will be charged with making significant reductions in emissions growth even as rates of urbanization continue to climb. Focusing on Beijing and Shanghai, this paper carries out a measures-based economic analysis of low carbon investment opportunities in the residential sector. Results find significant opportunity: between 2015 and 2030, BAU levels of CO2 emissions could be reduced by 10.2% in Beijing and 6.8% in Shanghai with the adoption of economically attractive low carbon measures. While these headline results underline the case for low carbon investment in the residential sectors of these megacities in China, a closer analysis provides insights for understanding the economics of decarbonisation in cities more generally.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). |
Keywords: | Megacities; Climate change; Energy; Carbon; Residential buildings; Measures-based analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Sep 2016 10:29 |
Last Modified: | 05 Oct 2017 16:08 |
Published Version: | http://dx.doi.org/10.1016/j.apenergy.2016.07.112 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.apenergy.2016.07.112 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104651 |