The need for urban form data in spatial modeling of urban carbon emissions in China: A critical review
Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively con...
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| Published in | Journal of Cleaner Production Vol. 319; p. 128792 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English Japanese |
| Published |
Elsevier Ltd
15.10.2021
Elsevier BV |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0959-6526 1879-1786 |
| DOI | 10.1016/j.jclepro.2021.128792 |
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| Abstract | Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover.
•The spatial modeling studies of urban carbon emission in China are reviewed.•The available data and methods are summarized.•The strengths and weaknesses of the methods are compared.•Urban forms can affect urban carbon emissions.•Future developments will require a finer spatial resolution and urban form data. |
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| AbstractList | Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover.
•The spatial modeling studies of urban carbon emission in China are reviewed.•The available data and methods are summarized.•The strengths and weaknesses of the methods are compared.•Urban forms can affect urban carbon emissions.•Future developments will require a finer spatial resolution and urban form data. Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover. |
| ArticleNumber | 128792 |
| Author | Yamagata, Yoshiki Ren, Chao Cai, Meng Shi, Yuan Ding, Chao Yoshida, Takahiro Zhou, Nan |
| Author_xml | – sequence: 1 givenname: Meng orcidid: 0000-0003-1489-2583 surname: Cai fullname: Cai, Meng organization: School of Architecture, The Chinese University of Hong Kong, Hong Kong – sequence: 2 givenname: Yuan orcidid: 0000-0003-4011-8735 surname: Shi fullname: Shi, Yuan organization: Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong – sequence: 3 givenname: Chao orcidid: 0000-0002-8494-2585 surname: Ren fullname: Ren, Chao email: renchao@hku.hk organization: Faculty of Architecture, The University of Hong Kong, Hong Kong – sequence: 4 givenname: Takahiro orcidid: 0000-0001-8741-5345 surname: Yoshida fullname: Yoshida, Takahiro organization: National Institute for Environmental Studies, Japan – sequence: 5 givenname: Yoshiki surname: Yamagata fullname: Yamagata, Yoshiki organization: National Institute for Environmental Studies, Japan – sequence: 6 givenname: Chao surname: Ding fullname: Ding, Chao organization: Lawrence Berkeley National Laboratory, USA – sequence: 7 givenname: Nan surname: Zhou fullname: Zhou, Nan organization: Lawrence Berkeley National Laboratory, USA |
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| Title | The need for urban form data in spatial modeling of urban carbon emissions in China: A critical review |
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