IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i8p1230-d879653.html
   My bibliography  Save this article

Spatiotemporal Patterns and Drivers of the Carbon Budget in the Yangtze River Delta Region, China

Author

Listed:
  • Qi Fu

    (School of Politics and Public Administration, Soochow University, Suzhou 215123, China
    The Institute of Regional Governance, Soochow University, Suzhou 215123, China
    Research Institute of Metropolitan Development of China, Soochow University, Suzhou 215123, China
    These authors contributed equally to this work.)

  • Mengfan Gao

    (School of Politics and Public Administration, Soochow University, Suzhou 215123, China
    These authors contributed equally to this work.)

  • Yue Wang

    (School of Politics and Public Administration, Soochow University, Suzhou 215123, China)

  • Tinghui Wang

    (School of Politics and Public Administration, Soochow University, Suzhou 215123, China)

  • Xu Bi

    (College of Resources and Environment, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Jinhua Chen

    (School of Politics and Public Administration, Soochow University, Suzhou 215123, China
    The Institute of Regional Governance, Soochow University, Suzhou 215123, China
    Research Institute of Metropolitan Development of China, Soochow University, Suzhou 215123, China)

Abstract

Improving our understanding of the patterns and drivers of regional carbon budgets is critical to mitigating climate change regionally and globally. Different from previous research, our study attempts to reveal the comprehensive impact of climate change and human activities factors on the carbon budget. Based on the Carnegie–Ames–Stanford approach (CASA) model, the IPCC inventory method, the ordinary least squares (OLS) regression model, the Geodetector model, and the geographically weighted regression (GWR) method, we investigated the spatiotemporal patterns of the carbon budget in the Yangtze River Delta (YRD) region from 2000 to 2015 and analyzed the effects of climate change and human activities on the carbon budget. The results showed that the carbon budget in the YRD region changed from 271.33 million tons in 2000 to −1193.76 million tons in 2015. During this period, the changes in the carbon budget per unit area in the four provinces all showed a decreasing trend, among which Shanghai decreased the most, followed by Jiangsu, Zhejiang and Anhui. In terms of spatial pattern, the carbon budget of the YRD region has a “core-edge” structural feature. The closer it is to Shanghai, the core area, the more severe the carbon budget deficit; the farther from it, the greater the carbon budget surplus. Overall, we found that human activities have a greater impact on the carbon budget than climate change. The top three drivers were, in order, changes in population density, GDP per capita, and unused land, with q values of 0.3317, 0.1202, and 0.0998, respectively. Locally, the impact of the drivers on the carbon budget shows obvious spatial heterogeneity. In particular, the population density was negatively correlated with carbon budget changes in the entire study area, and the coefficients of GDP per capita and unused land were negative in most counties. Based on the results, we put forward suggestions for restricting population flow among the core area and the peripheral area, promoting industrial innovation in the core area and ecological protection in the peripheral area, as well as implementing three-dimensional space development in the core area and controlling the expansion of construction land in the peripheral area. Our study can provide a scientific basis for low-carbon development in the YRD region. The methodology and findings of this study can provide references for similar studies in other urbanized regions around the world.

Suggested Citation

  • Qi Fu & Mengfan Gao & Yue Wang & Tinghui Wang & Xu Bi & Jinhua Chen, 2022. "Spatiotemporal Patterns and Drivers of the Carbon Budget in the Yangtze River Delta Region, China," Land, MDPI, vol. 11(8), pages 1-18, August.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1230-:d:879653
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/8/1230/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/11/8/1230/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yunfei Li & Sebastian Schubert & Jürgen P. Kropp & Diego Rybski, 2020. "On the influence of density and morphology on the Urban Heat Island intensity," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    2. Wenbo Cai & Wanting Peng, 2021. "Exploring Spatiotemporal Variation of Carbon Storage Driven by Land Use Policy in the Yangtze River Delta Region," Land, MDPI, vol. 10(11), pages 1-12, October.
    3. Chen, Jiandong & Fan, Wei & Li, Ding & Liu, Xin & Song, Malin, 2020. "Driving factors of global carbon footprint pressure: Based on vegetation carbon sequestration," Applied Energy, Elsevier, vol. 267(C).
    4. Joeri Rogelj & Piers M. Forster & Elmar Kriegler & Christopher J. Smith & Roland Séférian, 2019. "Estimating and tracking the remaining carbon budget for stringent climate targets," Nature, Nature, vol. 571(7765), pages 335-342, July.
    5. Shilong Piao & Jingyun Fang & Philippe Ciais & Philippe Peylin & Yao Huang & Stephen Sitch & Tao Wang, 2009. "The carbon balance of terrestrial ecosystems in China," Nature, Nature, vol. 458(7241), pages 1009-1013, April.
    6. Fengsong Pei & Rui Zhong & Li-An Liu & Yingjuan Qiao, 2021. "Decoupling the Relationships between Carbon Footprint and Economic Growth within an Urban Agglomeration—A Case Study of the Yangtze River Delta in China," Land, MDPI, vol. 10(9), pages 1-15, September.
    7. Zhou, Ya & Shan, Yuli & Liu, Guosheng & Guan, Dabo, 2018. "Emissions and low-carbon development in Guangdong-Hong Kong-Macao Greater Bay Area cities and their surroundings," Applied Energy, Elsevier, vol. 228(C), pages 1683-1692.
    8. Li, Huanan & Wei, Yi-Ming, 2015. "Is it possible for China to reduce its total CO2 emissions?," Energy, Elsevier, vol. 83(C), pages 438-446.
    9. Hao, Yu & Zhang, Zong-Yong & Yang, Chuxiao & Wu, Haitao, 2021. "Does structural labor change affect CO2 emissions? Theoretical and empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    10. Tao, Yu & Tao, Qin & Sun, Xiao & Qiu, Jiangxiao & Pueppke, Steven G. & Ou, Weixin & Guo, Jie & Qi, Jiaguo, 2022. "Mapping ecosystem service supply and demand dynamics under rapid urban expansion: A case study in the Yangtze River Delta of China," Ecosystem Services, Elsevier, vol. 56(C).
    11. Xin Li & Bin Fang & Mengru Yin & Tao Jin & Xin Xu, 2022. "Multi-Dimensional Urbanization Coordinated Evolution Process and Ecological Risk Response in the Yangtze River Delta," Land, MDPI, vol. 11(5), pages 1-25, May.
    12. Clarke-Sather, Afton & Qu, Jiansheng & Wang, Qin & Zeng, Jingjing & Li, Yan, 2011. "Carbon inequality at the sub-national scale: A case study of provincial-level inequality in CO2 emissions in China 1997-2007," Energy Policy, Elsevier, vol. 39(9), pages 5420-5428, September.
    13. Chenxu Liu & Ruien Tang & Yaqi Guo & Yuhan Sun & Xinyi Liu, 2022. "Research on the Structure of Carbon Emission Efficiency and Influencing Factors in the Yangtze River Delta Urban Agglomeration," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiuyu Zou & Jianwei Sun & Jing Luo & Jiaxing Cui & Xuesong Kong, 2023. "Spatial Patterns of Key Villages and Towns of Rural Tourism in China and Their Influencing Factors," Sustainability, MDPI, vol. 15(18), pages 1-16, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ding, Dan & Liu, Xiaoping & Xu, Xiaocong, 2024. "Projecting the future fine-resolution carbon dioxide emissions under the shared socioeconomic pathways for carbon peak evaluation," Applied Energy, Elsevier, vol. 365(C).
    2. Fan, Wei & Li, Li & Wang, Feiran & Li, Ding, 2020. "Driving factors of CO2 emission inequality in China: The role of government expenditure," China Economic Review, Elsevier, vol. 64(C).
    3. Wenjing Wang & Tong Wu & Yuanzheng Li & Shilin Xie & Baolong Han & Hua Zheng & Zhiyun Ouyang, 2020. "Urbanization Impacts on Natural Habitat and Ecosystem Services in the Guangdong-Hong Kong-Macao “Megacity”," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    4. Xie, Rui & Wang, Fangfang & Chevallier, Julien & Zhu, Bangzhu & Zhao, Guomei, 2018. "Supply-side structural effects of air pollutant emissions in China: A comparative analysis," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 89-95.
    5. López, Luis-Antonio & Arce, Guadalupe & Cadarso, María-Ángeles & Ortiz, Mateo & Zafrilla, Jorge, 2023. "The global dissemination to multinationals of the carbon emissions ruling on Shell," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 406-416.
    6. Jieming Chou & Yidan Hao & Yuan Xu & Weixing Zhao & Yuanmeng Li & Haofeng Jin, 2023. "Forest Carbon Sequestration Potential in China under Different SSP-RCP Scenarios," Sustainability, MDPI, vol. 15(9), pages 1-12, April.
    7. Yu, Shiwei & Wei, Yi-Ming & Fan, Jingli & Zhang, Xian & Wang, Ke, 2012. "Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization," Applied Energy, Elsevier, vol. 92(C), pages 552-562.
    8. Jinzhao Song & Qing Feng & Xiaoping Wang & Hanliang Fu & Wei Jiang & Baiyu Chen, 2018. "Spatial Association and Effect Evaluation of CO 2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    9. Xu, Chong & Wang, Bingjie & Chen, Jiandong & Shen, Zhiyang & Song, Malin & An, Jiafu, 2022. "Carbon inequality in China: Novel drivers and policy driven scenario analysis," Energy Policy, Elsevier, vol. 170(C).
    10. Li, Li & Shan, Yuli & Lei, Yalin & Wu, Sanmang & Yu, Xiang & Lin, Xiyan & Chen, Yupei, 2019. "Decoupling of economic growth and emissions in China’s cities: A case study of the Central Plains urban agglomeration," Applied Energy, Elsevier, vol. 244(C), pages 36-45.
    11. Junbo Wang & Liu Chen & Lu Chen & Xiaohui Zhao & Minxi Wang & Yiyi Ju & Li Xin, 2019. "City-Level Features of Energy Footprints and Carbon Dioxide Emissions in Sichuan Province of China," Energies, MDPI, vol. 12(10), pages 1-14, May.
    12. Chunli Zhou & Yuze Tang & Deyan Zhu & Zhiwei Cui, 2024. "Tracking the Carbon Emissions Using Electricity Big Data: A Case Study of the Metal Smelting Industry," Energies, MDPI, vol. 17(3), pages 1-19, January.
    13. Wanbei Jiang & Weidong Liu, 2020. "Provincial-Level CO 2 Emissions Intensity Inequality in China: Regional Source and Explanatory Factors of Interregional and Intraregional Inequalities," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    14. Zhen, Wei & Qin, Quande & Miao, Lu, 2023. "The greenhouse gas rebound effect from increased energy efficiency across China's staple crops," Energy Policy, Elsevier, vol. 173(C).
    15. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    16. Zhang, Shengling & Wang, Yao & Hao, Yu & Liu, Zhiwei, 2021. "Shooting two hawks with one arrow: Could China's emission trading scheme promote green development efficiency and regional carbon equality?," Energy Economics, Elsevier, vol. 101(C).
    17. Liu, Yajie & Dong, Feng & Wang, Yulong & Li, Jingyun & Qin, Chang, 2023. "Assessment of the energy-saving and environment effects of China's gasoline vehicle withdrawal under the impact of geopolitical risks," Resources Policy, Elsevier, vol. 86(PB).
    18. Yuhanis Ladewi & Meiryani Meiryani & Ahmad Syamil & Agustini Agustini & Agustinus Winoto, 2024. "The Relation between Climate Change and Carbon Emission Trading: A Bibliometric Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 686-697, January.
    19. Ilaria Perissi & Aled Jones, 2024. "An Emissions Offset Strategy to Accomplish 2 °C Long-Term Mitigation Goals in the European Union," Sustainability, MDPI, vol. 16(11), pages 1-13, June.
    20. Hongtao Jiang & Jian Yin & Yuanhong Qiu & Bin Zhang & Yi Ding & Ruici Xia, 2022. "Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces," Land, MDPI, vol. 11(8), pages 1-22, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1230-:d:879653. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.