IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i10p1748-d1491947.html
   My bibliography  Save this article

The Spatiotemporal Differentiation Characteristics and Driving Forces of Carbon Emissions from Major Livestock Farming in the Shaanxi–Gansu–Ningxia Region

Author

Listed:
  • Hao Wu

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    Center for Resource Economics and Environment Management, Northwest A&F University, Yangling 712100, China)

  • Tongtong Shan

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    Center for Resource Economics and Environment Management, Northwest A&F University, Yangling 712100, China)

  • Hassan Saif Khan

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    Center for Resource Economics and Environment Management, Northwest A&F University, Yangling 712100, China)

  • Lin Dong

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    Center for Resource Economics and Environment Management, Northwest A&F University, Yangling 712100, China)

  • Hua Li

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    Center for Resource Economics and Environment Management, Northwest A&F University, Yangling 712100, China)

Abstract

Given the background of ecological fragility in western China, the northward migration of the livestock industry, and the “carbon peak” in China, it is practically significant to discuss the evolution of carbon dioxide equivalent emission intensity (CEI) in major livestock (pigs, cattle and sheep) rearing in the Shaanxi–Gansu–Ningxia (SGN) region. This discussion aims to protect the ecology of western China, achieve sustainable and healthy development of the livestock industry, and realize the national goal of “double carbon”. In this study, we utilized statistical data from 2010 to 2021 for pigs, cattle, and sheep at the municipal level in the SGN region. We applied the methodology provided by the IPCC to comprehensively measure the carbon dioxide equivalent emissions (CEs), explore spatial and temporal trends, and analyze the driving forces behind spatial variations in the intensity with the assistance of GeoDetector. The following conclusions were drawn: Firstly, the total CEs generally exhibit fluctuating and increasing patterns. Moreover, the total CEs in different cities (states) within the region show obvious variations, with a tendency to shift toward the north. Secondly, the CEI demonstrates a clear downward trend. However, the CEI in different cities (states) exhibits increasing spatial heterogeneity. Furthermore, the western part of the region is evolving toward high-value areas, while the eastern part is evolving toward low-value areas. Lastly, the results of the GeoDetector indicate that the core driving factors are the pig, cattle, and sheep rearing structure; the urban population proportion; and the per capita gross national product. In summary, the total amount of CEs demonstrates a fluctuating increase, while the intensity shows a clear downward trend. Therefore, it is recommended to reduce CEs from livestock rearing in this region by optimizing the rearing structure of pigs, cattle, and sheep, promoting low-carbon consumption, and moderately importing livestock products.

Suggested Citation

  • Hao Wu & Tongtong Shan & Hassan Saif Khan & Lin Dong & Hua Li, 2024. "The Spatiotemporal Differentiation Characteristics and Driving Forces of Carbon Emissions from Major Livestock Farming in the Shaanxi–Gansu–Ningxia Region," Agriculture, MDPI, vol. 14(10), pages 1-16, October.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:10:p:1748-:d:1491947
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/10/1748/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/10/1748/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaocang Xu & Xiuquan Huang & Jun Huang & Xin Gao & Linhong Chen, 2019. "Spatial-Temporal Characteristics of Agriculture Green Total Factor Productivity in China, 1998–2016: Based on More Sophisticated Calculations of Carbon Emissions," IJERPH, MDPI, vol. 16(20), pages 1-16, October.
    2. Zhang, Na & Jing, Yong-Cai & Liu, Cheng-Yu & Li, Yao & Shen, Jing, 2016. "A cellular automaton model for grasshopper population dynamics in Inner Mongolia steppe habitats," Ecological Modelling, Elsevier, vol. 329(C), pages 5-17.
    3. Klarin Tomislav, 2018. "The Concept of Sustainable Development: From its Beginning to the Contemporary Issues," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 21(1), pages 67-94, May.
    4. Zhou, Wenhao & Zeng, Bo & Wang, Jianzhou & Luo, Xiaoshuang & Liu, Xianzhou, 2021. "Forecasting Chinese carbon emissions using a novel grey rolling prediction model," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    5. 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.
    Full references (including those not matched with items on IDEAS)

    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. Yakun Wang & Jingli Jiang & Dongqing Wang & Xinshang You, 2022. "Can Mechanization Promote Green Agricultural Production? An Empirical Analysis of Maize Production in China," Sustainability, MDPI, vol. 15(1), pages 1-24, December.
    2. Xu He & Qin-Lei Jing, 2022. "The Impact of Environmental Tax Reform on Total Factor Productivity of Heavy-Polluting Firms Based on a Dual Perspective of Technological Innovation and Capital Allocation," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    3. Zhenfen Wu & Zhe Wang & Qiliang Yang & Changyun Li, 2024. "Prediction Model of Electric Power Carbon Emissions Based on Extended System Dynamics," Energies, MDPI, vol. 17(2), pages 1-22, January.
    4. Shuying Wang & Yifei Gao & Hongchang Zhou, 2022. "Research on Green Total Factor Productivity Enhancement Path from the Configurational Perspective—Based on the TOE Theoretical Framework," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    5. Xuelan Li & Rui Guan, 2023. "How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?," IJERPH, MDPI, vol. 20(2), pages 1-23, January.
    6. Zhicong Zhang & Hao Xie & Jubing Zhang & Xinye Wang & Jiayu Wei & Xibin Quan, 2022. "Prediction and Trend Analysis of Regional Industrial Carbon Emission in China: A Study of Nanjing City," IJERPH, MDPI, vol. 19(12), pages 1-23, June.
    7. Yang Liu & Yanlin Yang & Huihui Li & Kaiyang Zhong, 2022. "Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China’s Cities," IJERPH, MDPI, vol. 19(4), pages 1-23, February.
    8. Ruixin Su & Bojan Obrenovic & Jianguo Du & Danijela Godinic & Akmal Khudaykulov, 2022. "COVID-19 Pandemic Implications for Corporate Sustainability and Society: A Literature Review," IJERPH, MDPI, vol. 19(3), pages 1-23, January.
    9. Ginevra Malta & Fulvio Plescia & Stefania Zerbo & Maria Gabriella Verso & Serena Matera & Alenka Skerjanc & Emanuele Cannizzaro, 2024. "Work and Environmental Factors on Job Burnout: A Cross-Sectional Study for Sustainable Work," Sustainability, MDPI, vol. 16(8), pages 1-12, April.
    10. Lingyan Xu & Dandan Wang & Jianguo Du, 2022. "Spatial-Temporal Evolution and Influencing Factors of Urban Green and Smart Development Level in China: Evidence from 232 Prefecture-Level Cities," IJERPH, MDPI, vol. 19(7), pages 1-19, March.
    11. Sidong Zhao & Weiwei Li & Kaixu Zhao & Ping Zhang, 2021. "Change Characteristics and Multilevel Influencing Factors of Real Estate Inventory—Case Studies from 35 Key Cities in China," Land, MDPI, vol. 10(9), pages 1-29, September.
    12. Rui Li & Xin Chen, 2022. "Reverse Logistics Network Design under Disruption Risk for Third-Party Logistics Providers," Sustainability, MDPI, vol. 14(22), pages 1-24, November.
    13. Ke Liu & Xinyue Xie & Mingxue Zhao & Qian Zhou, 2022. "Carbon Emissions in the Yellow River Basin: Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors Based on a Logarithmic Mean Divisia Index (LMDI) Decomposition Method," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    14. Khodran Alzahrani & Mubashar Ali & Muhammad Imran Azeem & Bader Alhafi Alotaibi, 2023. "Efficacy of Public Extension and Advisory Services for Sustainable Rice Production," Agriculture, MDPI, vol. 13(5), pages 1-17, May.
    15. Chukwunazaoku E. Chukwuma, 2023. "The Economic Prospects of Sustainable Labour Migration and the Need for a Legal Framework in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(9), pages 1636-1647, September.
    16. Hu, Yusha & Man, Yi, 2023. "Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    17. Cheng Zhang & Xiong Zou & Chuan Lin, 2023. "Carbon Footprint Prediction of Thermal Power Industry under the Dual-Carbon Target: A Case Study of Zhejiang Province, China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    18. David Mhlanga, 2022. "Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    19. Shuvo Dip Datta & Bassam A. Tayeh & Ibrahim Y. Hakeem & Yazan I. Abu Aisheh, 2023. "Benefits and Barriers of Implementing Building Information Modeling Techniques for Sustainable Practices in the Construction Industry—A Comprehensive Review," Sustainability, MDPI, vol. 15(16), pages 1-28, August.
    20. Yizhen Jia & Xiaodong Yan, 2024. "Multi-Objective Optimization of the Planting Industry in Jiangsu Province and Analysis of Its “Water-Energy-Carbon” Characteristics," Sustainability, MDPI, vol. 16(7), pages 1-24, March.

    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:jagris:v:14:y:2024:i:10:p:1748-:d:1491947. 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.