IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i23p10291-d1528478.html
   My bibliography  Save this article

Spatial and Temporal Evolution of the Coupling of Industrial Agglomeration and Carbon Emission Efficiency—Evidence from China’s Animal Husbandry Industry

Author

Listed:
  • Qingmei Zeng

    (School of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Bin Fan

    (School of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Fuzeng Wang

    (School of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

Abstract

Drawing upon the data of China’s animal husbandry industry from 2000 to 2020 in 30 provinces, an EBM model incorporating non-desired outputs was employed to gauge the carbon emission efficiency of the animal husbandry industry. Coupling degree models, spatial autocorrelation models, and Markov chain models were utilized to assess the coupling degree between the industrial agglomeration of the animal husbandry sector and its carbon emission efficiency, and to analyze its spatio-temporal distribution and evolution. The outcomes showed that (1) the coupling degree of China’s animal husbandry industry agglomeration and carbon emission efficiency exhibited an overall downward inclination. Notably, the diminishing tendency of the coupling degree was more pronounced in the eastern, central, and western parts of the country; (2) the coupling degree of the 30 provinces showed a spatial distribution of “western > central > northeast > eastern”; (3) the coupling degree showed obvious agglomeration distribution characteristics, wherein a substantial quantity of provinces was located in high–high clustering zones and low–low clustering zones; (4) the coupling degree of various provinces remained fairly stable, but after considering the spatial and geographical correlation, the coupling degree of each province would be influenced by the coupling degree of its adjacent provinces. Evidently, there remained a substantial scope for the enhancement of the coupling coordination degree between the industrial agglomeration of China’s animal husbandry and the carbon emission efficiency. This research is capable of furnishing a theoretical allusion for promoting regional cooperation, leveraging agglomeration advantages, and implementing carbon emission abatement regimes and directives to enhance the low-carbon development level of animal husbandry industry agglomeration in China.

Suggested Citation

  • Qingmei Zeng & Bin Fan & Fuzeng Wang, 2024. "Spatial and Temporal Evolution of the Coupling of Industrial Agglomeration and Carbon Emission Efficiency—Evidence from China’s Animal Husbandry Industry," Sustainability, MDPI, vol. 16(23), pages 1-26, November.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:23:p:10291-:d:1528478
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/23/10291/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/23/10291/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jianxing Chen & Xuesong Gao & Yanyan Zhang & Petri Penttinen & Qi Wang & Jing Ling & Ting Lan & Dinghua Ou & Yang Li, 2023. "Analysis on Coupling Coordination Degree for Cropland and Livestock from 2000 to 2020 in China," Agriculture, MDPI, vol. 13(7), pages 1-20, June.
    2. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    3. Vander Donckt, Marie & Chan, Philip & Silvestrini, Andrea, 2021. "A new global database on agriculture investment and capital stock," Food Policy, Elsevier, vol. 100(C).
    4. Wenli Yang & Langang Feng & Zuogong Wang & Xiangbo Fan, 2023. "Carbon Emissions and National Sustainable Development Goals Coupling Coordination Degree Study from a Global Perspective: Characteristics, Heterogeneity, and Spatial Effects," Sustainability, MDPI, vol. 15(11), pages 1-23, June.
    5. Yixuan Huang & Mingfei Liu, 2023. "Coupling Coordination and Spatiotemporal Evolution of Low-Carbon Logistics, Industrial Agglomeration, and Regional Economy in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    6. Dequan Hao & Rui Wang & Chaojie Gao & Xinyan Song & Wenxin Liu & Guangyin Hu, 2022. "Spatial-Temporal Characteristics and Influence Factors of Carbon Emission from Livestock Industry in China," IJERPH, MDPI, vol. 19(22), pages 1-23, November.
    7. Chuanhui Wang & Asong Han & Weifeng Gong & Mengzhen Zhao & Wenwen Li, 2023. "Threshold Effect of Manufacturing Agglomeration on Eco-Efficiency in the Yellow River Basin of China," Sustainability, MDPI, vol. 15(19), pages 1-18, September.
    8. Yun Tian & Rui Wang & Minhao Yin & Huijie Zhang, 2023. "Study on the Measurement and Influencing Factors of Rural Energy Carbon Emission Efficiency in China: Evidence Using the Provincial Panel Data," Agriculture, MDPI, vol. 13(2), pages 1-16, February.
    9. Sensen Zhang & Zhenggang Huo, 2023. "Analysis of Spatial Correlation and Influencing Factors of Building a Carbon Emission Reduction Potential Network Based on the Coordination of Equity and Efficiency," Sustainability, MDPI, vol. 15(15), pages 1-21, July.
    10. Cheng Peng & Xiaona Wang & Xin Xiong & Yaxing Wang, 2024. "Assessing Carbon Emissions from Animal Husbandry in China: Trends, Regional Variations and Mitigation Strategies," Sustainability, MDPI, vol. 16(6), pages 1-15, March.
    11. Moomaw, William R. & Unruh, Gregory C., 1997. "Are environmental Kuznets curves misleading us? The case of CO2 emissions," Environment and Development Economics, Cambridge University Press, vol. 2(4), pages 451-463, November.
    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. Shoulin Li & Jianing Liu & Weiya Guo, 2025. "Empowered or Negative? Research on the Impact of Industrial Agglomeration on the Development of Agricultural New Quality Productive Forces: Evidence from Shandong Province, China," Sustainability, MDPI, vol. 17(8), pages 1-23, April.

    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. Muhammad Uzair Ali & Zhimin Gong & Muhammad Ubaid Ali & Fahad Asmi & Rizwanullah Muhammad, 2022. "CO2 emission, economic development, fossil fuel consumption and population density in India, Pakistan and Bangladesh: A panel investigation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 18-31, January.
    2. B. Venkatraja, 2021. "Does China exhibit any evidence of an Environmental Kuznets Curve? An ARDL bounds testing approach," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 88-110,111-.
    3. Ren, Siyu & Hao, Yu & Wu, Haitao, 2022. "The role of outward foreign direct investment (OFDI) on green total factor energy efficiency: Does institutional quality matters? Evidence from China," Resources Policy, Elsevier, vol. 76(C).
    4. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    5. Haixiang Xu & Rui Zhang, 2024. "Dynamic Analysis of Urban Land Use Efficiency in the Western Taiwan Strait Economic Zone," Land, MDPI, vol. 13(8), pages 1-26, August.
    6. Ting Wang & Wanyi Li & Tianyu Jin & Jing Wu & Jianghua Liu, 2025. "Research on Regional Differences and Influencing Factors of Energy Efficiency in China’s Agricultural Production Sector," Agriculture, MDPI, vol. 15(11), pages 1-30, May.
    7. Xiangqian Wang & Shudong Wang & Yongqiu Xia, 2022. "Evaluation and Dynamic Evolution of the Total Factor Environmental Efficiency in China’s Mining Industry," Energies, MDPI, vol. 15(3), pages 1-19, February.
    8. Chen, Yang & Mu, Huaizhong, 2023. "Natural resources, carbon trading policies and total factor carbon efficiency: A new direction for China’s economy," Resources Policy, Elsevier, vol. 86(PA).
    9. Xuejuan Wang & Qi Deng & Riccardo Natoli & Li Wang & Wei Zhang & Catherine Xiaocui Lou, 2025. "Analyzing Regional Disparities in China’s Green Manufacturing Transition," Sustainability, MDPI, vol. 17(15), pages 1-19, August.
    10. Wu, Yaling & Wu, Bi & Liu, Xiaohong & Zhang, Shiwei, 2025. "Digital finance and agricultural total factor productivity–From the perspective of capital deepening and factor structure," Finance Research Letters, Elsevier, vol. 74(C).
    11. Matias Piaggio & Emilio Padilla & Carolina Roman, 2015. "The long-run relationshiop between C02 emissions and economic activity in a small open economy: Uruguay 1882-2010," Working Papers wpdea1506, Department of Applied Economics at Universitat Autonoma of Barcelona.
    12. Wang, Weilong & Wang, Jianlong & Wu, Haitao, 2024. "The impact of energy-consuming rights trading on green total factor productivity in the context of digital economy: Evidence from listed firms in China," Energy Economics, Elsevier, vol. 131(C).
    13. Zhicheng Lai & Lei Li & Zhuomin Tao & Tao Li & Xiaoting Shi & Jialing Li & Xin Li, 2023. "Spatio-Temporal Evolution and Influencing Factors of Ecological Well-Being Performance from the Perspective of Strong Sustainability: A Case Study of the Three Gorges Reservoir Area, China," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    14. He, Jie & Richard, Patrick, 2010. "Environmental Kuznets curve for CO2 in Canada," Ecological Economics, Elsevier, vol. 69(5), pages 1083-1093, March.
    15. Wang, Ke-Liang & Sun, Ting-Ting & Xu, Ru-Yu & Miao, Zhuang & Cheng, Yun-He, 2022. "How does internet development promote urban green innovation efficiency? Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    16. Verbeke, Tom & De Clercq, Marc, 2006. "The income-environment relationship: Evidence from a binary response model," Ecological Economics, Elsevier, vol. 59(4), pages 419-428, October.
    17. Shahbaz, Muhammad & Haouas, Ilham & Hoang, Thi Hong Van, 2019. "Economic growth and environmental degradation in Vietnam: Is the environmental Kuznets curve a complete picture?," Emerging Markets Review, Elsevier, vol. 38(C), pages 197-218.
    18. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    19. Pascalau, Razvan & Qirjo, Dhimitri, 2017. "TTIP and the Environmental Kuznets Curve," MPRA Paper 80192, University Library of Munich, Germany.
    20. Tan, Xiujie & Xiao, Ziwei & Liu, Yishuang & Taghizadeh-Hesary, Farhad & Wang, Banban & Dong, Hanmin, 2022. "The effect of green credit policy on energy efficiency: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:16:y:2024:i:23:p:10291-:d:1528478. 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.