IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i23p15554-d981128.html
   My bibliography  Save this article

Carbon Emission Measurement and Influencing Factors of China’s Beef Cattle Industry from a Whole Industry Chain Perspective

Author

Listed:
  • Yumeng Sun

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Chun Yang

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Mingli Wang

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Xuezhen Xiong

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Xuefen Long

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

Abstract

The beef cattle industry is pivotal in China’s livestock industry and is important for meeting people’s needs for a better life in the new era. It is strategically important for prospering the frontier, enriching people, and revitalizing the countryside. Because of the national “double carbon” target, there will be an impact on the development of the meat cattle industry, which has a relatively high carbon emission level. The scientific measurement of carbon emission levels in the beef cattle industry, clarifying its main impact factors, are particularly critical. This study measured the carbon emissions from China’s beef cattle industry from 2008 to 2020, using provincial data and the life cycle method, and investigated its influencing factors using a spatial econometric model. The study is of great practical significance for accurately understanding the carbon emissions of the beef cattle industry and for promoting low carbon emission reductions and the transformational development of the beef cattle industry.

Suggested Citation

  • Yumeng Sun & Chun Yang & Mingli Wang & Xuezhen Xiong & Xuefen Long, 2022. "Carbon Emission Measurement and Influencing Factors of China’s Beef Cattle Industry from a Whole Industry Chain Perspective," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15554-:d:981128
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/23/15554/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/23/15554/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alemu, Aklilu W. & Janzen, Henry & Little, Shannan & Hao, Xiying & Thompson, Donald J. & Baron, Vern & Iwaasa, Alan & Beauchemin, Karen A. & Kröbel, Roland, 2017. "Assessment of grazing management on farm greenhouse gas intensity of beef production systems in the Canadian Prairies using life cycle assessment," Agricultural Systems, Elsevier, vol. 158(C), pages 1-13.
    2. Heena Panchasara & Nahidul Hoque Samrat & Nahina Islam, 2021. "Greenhouse Gas Emissions Trends and Mitigation Measures in Australian Agriculture Sector—A Review," Agriculture, MDPI, vol. 11(2), pages 1-16, January.
    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. Shanshan Zhao & Mingsen Qin & Xia Yang & Wenke Bai & Yunfeng Yao & Junqiang Wang, 2023. "Freeze–Thaw Cycles Have More of an Effect on Greenhouse Gas Fluxes than Soil Water Content on the Eastern Edge of the Qinghai–Tibet Plateau," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    2. Pogue, Sarah J. & Kröbel, Roland & Janzen, H. Henry & Alemu, Aklilu W. & Beauchemin, Karen A. & Little, Shannan & Iravani, Majid & de Souza, Danielle Maia & McAllister, Tim A., 2020. "A social-ecological systems approach for the assessment of ecosystem services from beef production in the Canadian prairie," Ecosystem Services, Elsevier, vol. 45(C).
    3. Zbigniew Gołaś, 2022. "Changes in Energy-Related Carbon Dioxide Emissions of the Agricultural Sector in Poland from 2000 to 2019," Energies, MDPI, vol. 15(12), pages 1-18, June.
    4. Maksymilian Mądziel, 2023. "Liquified Petroleum Gas-Fuelled Vehicle CO 2 Emission Modelling Based on Portable Emission Measurement System, On-Board Diagnostics Data, and Gradient-Boosting Machine Learning," Energies, MDPI, vol. 16(6), pages 1-15, March.
    5. Putri Aliah Mohd Hidzir & Shafinar Ismail & Sharifah Heryati Syed Nor & Aqilah Nadiah Md Sahiq, 2023. "Financial Well-Being of Micro-Entrepreneurs: A Proposed Conceptual Framework," Information Management and Business Review, AMH International, vol. 15(3), pages 418-428.
    6. Huae Dang & Yuanjie Deng & Yifeng Hai & Hang Chen & Wenjing Wang & Miao Zhang & Xingyang Liu & Can Yang & Minghong Peng & Dingdi Jize & Mei Zhang & Long He, 2025. "Integrating Geodetector and GTWR to Unveil Spatiotemporal Heterogeneity in China’s Agricultural Carbon Emissions Under the Dual Carbon Goals," Agriculture, MDPI, vol. 15(12), pages 1-33, June.
    7. Huang, Zhenyu & Yan, Ziyan & Tan, Minghong & Xu, Xiaofan & Yang, Xue, 2024. "Impact of cropland spatial shift on carbon footprint of agricultural inputs for grain production in China, 1990–2018," Energy Policy, Elsevier, vol. 195(C).
    8. Dalia Štreimikienė & Ahmad Bathaei & Justas Streimikis, 2025. "Enhancing Sustainable Global Supply Chain Performance: A Multi-Criteria Decision-Making-Based Approach to Industry 4.0 and AI Integration," Sustainability, MDPI, vol. 17(10), pages 1-19, May.
    9. Ahlgren, Serina & Wirsenius, Stefan & Toräng, Per & Carlsson, Annelie & Seeman, Anett & Behaderovic, Danira & Kvarnbäck, Olle & Parvin, Nargish & Hessle, Anna, 2024. "Climate and biodiversity impact of beef and lamb production – A case study in Sweden," Agricultural Systems, Elsevier, vol. 219(C).
    10. Nahina Islam & Md Mamunur Rashid & Faezeh Pasandideh & Biplob Ray & Steven Moore & Rajan Kadel, 2021. "A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    11. Modongo, Oteng & Kulshreshtha, Suren N., 2018. "Economics of mitigating greenhouse gas emissions from beef production in western Canada," Agricultural Systems, Elsevier, vol. 162(C), pages 229-238.
    12. Daiva Makutėnienė & Dalia Perkumienė & Valdemaras Makutėnas, 2022. "Logarithmic Mean Divisia Index Decomposition Based on Kaya Identity of GHG Emissions from Agricultural Sector in Baltic States," Energies, MDPI, vol. 15(3), pages 1-26, February.
    13. Xiaowen Dai & Xin Wu & Yi Chen & Yanqiu He & Fang Wang & Yuying Liu, 2022. "Real Drivers and Spatial Characteristics of CO 2 Emissions from Animal Husbandry: A Regional Empirical Study of China," Agriculture, MDPI, vol. 12(4), pages 1-18, April.
    14. Rui Zhang & Lingling Zhang & Meijuan He & Zongzhi Wang, 2023. "Spatial Association Network and Driving Factors of Agricultural Eco-Efficiency in the Hanjiang River Basin, China," Agriculture, MDPI, vol. 13(6), pages 1-16, May.
    15. Camel, Afaf & Belhadi, Amine & Kamble, Sachin & Wetzels, Martin & Touriki, Fatima Ezahra, 2025. "Servitizing for sustainability: Leveraging technology-enabled platforms and service innovation for carbon reduction in Africa’s Agri-Food Sector: A dynamic capabilities perspective," Journal of Business Research, Elsevier, vol. 189(C).
    16. Ravjit Khangura & David Ferris & Cameron Wagg & Jamie Bowyer, 2023. "Regenerative Agriculture—A Literature Review on the Practices and Mechanisms Used to Improve Soil Health," Sustainability, MDPI, vol. 15(3), pages 1-41, January.
    17. Kyuhyeon Joo & Jinsoo Hwang, 2023. "Do Consumers Intend to Use Indoor Smart Farm Restaurants for a Sustainable Future? The Influence of Cognitive Drivers on Behavioral Intentions," Sustainability, MDPI, vol. 15(8), pages 1-13, April.
    18. Martynas Rusteika & Lina Skinulienė, 2023. "Expectations of the Participants of the Crop Insurance System and Their Implementation," Agriculture, MDPI, vol. 13(3), pages 1-30, March.
    19. Suproń, Błażej, 2024. "The impact of agriculture in Visegrad countries on CO2 emissions using the FMOLS and DOLS methods in an empirical panel data study," MPRA Paper 125421, University Library of Munich, Germany.
    20. Shixiong Song & Siyuan Zhao & Ye Zhang & Yongxi Ma, 2023. "Carbon Emissions from Agricultural Inputs in China over the Past Three Decades," Agriculture, MDPI, vol. 13(5), pages 1-12, April.

    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:14:y:2022:i:23:p:15554-:d:981128. 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.