Key driving forces on the development of low carbon city (LCC) in China
Developing low carbon city (LCC) has been widely appreciated as the key strategy for achieving emission mitigation goal. Despite the impact factors on cities’ carbon emission reduction have been extensively studied in recent years, little attention has been paid to investigating the key driving forc...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-05-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X21000443 |
| _version_ | 1818743913238757376 |
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| author | Ya Wu Liyin Shen Chenyang Shuai Liudan Jiao Shiju Liao Zhenhua Guo |
| author_facet | Ya Wu Liyin Shen Chenyang Shuai Liudan Jiao Shiju Liao Zhenhua Guo |
| author_sort | Ya Wu |
| collection | DOAJ |
| description | Developing low carbon city (LCC) has been widely appreciated as the key strategy for achieving emission mitigation goal. Despite the impact factors on cities’ carbon emission reduction have been extensively studied in recent years, little attention has been paid to investigating the key driving force (KDF) on the development of LCC. This study aims to explore the KDF affecting LCC within the context of China through identifying systematically representative forces (RFs) and examining the interactive relationships between RFs. Based on topic modeling of Latent Dirichlet Allocation (LDA), RFs for LCC are identified firstly from the policies issued by the pilot LCCs in China. Then KDFs for LCC are investigated through establishing the interactive relationships between RFs by adopting the Interpretive Structure Modeling (ISM). Results show that: (1) 16 RFs on LCC are identified from the pilot LCC policies in China; (2) emission trading system, carbon emission accounting system, and low carbon planning are identified as the KDFs on the development of LCC; (3) carbon sink is positioned at the topmost level and performs as the most frontier force on the development of LCC. Results of the KDFs identification can provide policy-makers with insight for designing LCC improvement path, and consequently promote emission mitigation in China. |
| first_indexed | 2024-12-18T02:35:58Z |
| format | Article |
| id | doaj.art-d149a25b06e04346befbb819eb4d6ea9 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-12-18T02:35:58Z |
| publishDate | 2021-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-d149a25b06e04346befbb819eb4d6ea92022-12-21T21:23:46ZengElsevierEcological Indicators1470-160X2021-05-01124107379Key driving forces on the development of low carbon city (LCC) in ChinaYa Wu0Liyin Shen1Chenyang Shuai2Liudan Jiao3Shiju Liao4Zhenhua Guo5College of Resources and Environment, National Cultivation Base of Eco-Circulating Agriculture in Southwest Mountainous Area, Southwest University, Chongqing, ChinaSchool of Construction Management and Real Estate, International Research Center for Sustainable Built Environment, Chongqing University, Chongqing, China; Corresponding authors.School for Environment and Sustainability, University of Michigan, MI, United StatesSchool of Economics and Management, Chongqing Jiaotong University, Chongqing, China; Corresponding authors.School of Construction Management and Real Estate, International Research Center for Sustainable Built Environment, Chongqing University, Chongqing, ChinaSchool of Construction Management and Real Estate, International Research Center for Sustainable Built Environment, Chongqing University, Chongqing, ChinaDeveloping low carbon city (LCC) has been widely appreciated as the key strategy for achieving emission mitigation goal. Despite the impact factors on cities’ carbon emission reduction have been extensively studied in recent years, little attention has been paid to investigating the key driving force (KDF) on the development of LCC. This study aims to explore the KDF affecting LCC within the context of China through identifying systematically representative forces (RFs) and examining the interactive relationships between RFs. Based on topic modeling of Latent Dirichlet Allocation (LDA), RFs for LCC are identified firstly from the policies issued by the pilot LCCs in China. Then KDFs for LCC are investigated through establishing the interactive relationships between RFs by adopting the Interpretive Structure Modeling (ISM). Results show that: (1) 16 RFs on LCC are identified from the pilot LCC policies in China; (2) emission trading system, carbon emission accounting system, and low carbon planning are identified as the KDFs on the development of LCC; (3) carbon sink is positioned at the topmost level and performs as the most frontier force on the development of LCC. Results of the KDFs identification can provide policy-makers with insight for designing LCC improvement path, and consequently promote emission mitigation in China.http://www.sciencedirect.com/science/article/pii/S1470160X21000443Low carbon cityRepresentative forceKey driving forceLatent Dirichlet AllocationInterpretive Structural ModelingChina |
| spellingShingle | Ya Wu Liyin Shen Chenyang Shuai Liudan Jiao Shiju Liao Zhenhua Guo Key driving forces on the development of low carbon city (LCC) in China Ecological Indicators Low carbon city Representative force Key driving force Latent Dirichlet Allocation Interpretive Structural Modeling China |
| title | Key driving forces on the development of low carbon city (LCC) in China |
| title_full | Key driving forces on the development of low carbon city (LCC) in China |
| title_fullStr | Key driving forces on the development of low carbon city (LCC) in China |
| title_full_unstemmed | Key driving forces on the development of low carbon city (LCC) in China |
| title_short | Key driving forces on the development of low carbon city (LCC) in China |
| title_sort | key driving forces on the development of low carbon city lcc in china |
| topic | Low carbon city Representative force Key driving force Latent Dirichlet Allocation Interpretive Structural Modeling China |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X21000443 |
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