Cheng, L, Mi, Z, Sudmant, A orcid.org/0000-0001-8650-8419 et al. (1 more author) (2022) Bigger cities better climate? Results from an analysis of urban areas in China. Energy Economics, 107. 105872. ISSN 0140-9883
Abstract
Continued urban population expansion will be a defining challenge for climate change mitigation, and global sustainability more generally, over the coming decades. In this context, an important but underexplored issue concerns the relationship between the scale of urban areas and their carbon emissions. This paper employs the urban Kaya relation and Reduced Major Axis regression to look at urban emission patterns in China from 2000 to 2016. Our results reveal that larger cities tend to have lower per capita emissions. Thus, population agglomeration may be able to contribute to climate change mitigation and a wider transition to sustainability. The inverse-U shape between carbon emissions and population size is found. In addition, we observe unique scaling patterns in different regions, revealing how the relationship between emissions and population can be influenced by economic geography. City consumption weakens the role of population agglomeration in reducing carbon emissions in the East region, therefore it should be placed top priority in carbon emissions mitigation. These findings are important for China which looks to achieve carbon neutrality by 2060 against the backdrop of intertwined interplay between population agglomeration and city consumption.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Urban scaling; Carbon emissions; Sustainable cities; Urban population agglomeration; Urban Kaya relation |
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: | 09 Feb 2022 16:34 |
Last Modified: | 04 Aug 2023 00:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.eneco.2022.105872 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:183400 |
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