Efficiency and Driving Factors of Agricultural Carbon Emissions: A Study in Chinese State Farms

被引:35
|
作者
Han, Guanghe [1 ]
Xu, Jiahui [2 ]
Zhang, Xin [1 ]
Pan, Xin [1 ]
机构
[1] Heilongjiang Bayi Agr Univ, Coll Econ & Management, Daqing 163319, Peoples R China
[2] Hebei Finance Univ, Int Educ Coll, Baoding 071051, Peoples R China
来源
AGRICULTURE-BASEL | 2024年 / 14卷 / 09期
关键词
state farms; agricultural carbon emission; agricultural carbon emission efficiency; IPCC method; Super-SBM model; LMDI method; sustainable agriculture; LIFE-CYCLE ASSESSMENT; SLACKS-BASED MEASURE; PRODUCTIVITY;
D O I
10.3390/agriculture14091454
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Promoting low-carbon agriculture is vital for climate action and food security. State farms serve as crucial agricultural production bases in China and are essential in reducing China's carbon emissions and boosting emission efficiency. This study calculates the carbon emissions of state farms across 29 Chinese provinces using the IPCC method from 2010 to 2022. It also evaluates emission efficiency with the Super-Slack-Based Measure (Super-SBM model) and analyzes influencing factors using the Logarithmic Mean Divisia Index (LMDI) method. The findings suggest that the three largest carbon sources are rice planting, chemical fertilizers, and land tillage. Secondly, agricultural carbon emissions in state farms initially surge, stabilize with fluctuations, and ultimately decline, with higher emissions observed in northern and eastern China. Thirdly, the rise of agricultural carbon emission efficiency is driven primarily by technological progress. Lastly, economic development and industry structure promote agricultural carbon emissions, while production efficiency and labor scale reduce them. To reduce carbon emissions from state farms in China and improve agricultural carbon emission efficiency, the following measures can be taken: (1) Improve agricultural production efficiency and reduce carbon emissions in all links; (2) Optimize the agricultural industrial structure and promote the coordinated development of agriculture; (3) Reduce the agricultural labor scale and promote the specialization, professionalization, and high-quality development of agricultural labor; (4) Accelerate agricultural green technology innovation and guide the green transformation of state farms. This study enriches the theoretical foundation of low-carbon agriculture and develops a framework for assessing carbon emissions in Chinese state farms, offering guidance for future research and policy development in sustainable agriculture.
引用
收藏
页数:22
相关论文
共 50 条
  • [41] Study on the Structure, Efficiency, and Driving Factors of an Eco-Agricultural Park Based on Emergy: A Case Study of Jinchuan Eco-Agricultural Park
    Li, Ziwei
    Ma, Qiuying
    Wang, Yong
    Shi, Fengxue
    Jiang, Haibo
    He, Chunguang
    SUSTAINABILITY, 2024, 16 (07)
  • [42] Study on the efficiency evolution of carbon emissions and factors affecting them in 143 countries worldwide
    Dong, Fugui
    Wang, Peijun
    Li, Wanying
    URBAN CLIMATE, 2025, 59
  • [43] Exploratory Study on Modelling Agricultural Carbon Emissions in Ireland
    Madden, Sinead M.
    Ryan, Alan
    Walsh, Patrick
    AGRICULTURE-BASEL, 2022, 12 (01):
  • [44] Exploring the Driving Factors and Their Spatial Effects on Carbon Emissions in the Building Sector
    Wei, Jia
    Shi, Wei
    Ran, Jingrou
    Pu, Jing
    Li, Jiyang
    Wang, Kai
    ENERGIES, 2023, 16 (07)
  • [45] Accounting and driving factors analysis of energy carbon emissions in Heilongjiang Province
    Liu, Hao-Dong
    Qiu, Wei
    Chen, Shuang
    Zhongguo Huanjing Kexue/China Environmental Science, 2024, 44 (07): : 4117 - 4126
  • [46] Regional difference and driving factors of industrial carbon emissions performance in China
    Wang, Quanyi
    Zhao, Chenyuan
    ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (01) : 301 - 309
  • [47] Driving factors of carbon emissions from household energy combustion in China
    Sun, Xinlu
    Mi, Zhifu
    Zhang, Jin
    Li, Jinkai
    ENERGY POLICY, 2024, 186
  • [48] Driving factors of carbon emissions in China’s municipalities: a LMDI approach
    Yuanxin Liu
    Yajing Jiang
    Hui Liu
    Bo Li
    Jiahai Yuan
    Environmental Science and Pollution Research, 2022, 29 : 21789 - 21802
  • [49] Driving factors of carbon emissions in China's municipalities: a LMDI approach
    Liu, Yuanxin
    Jiang, Yajing
    Liu, Hui
    Li, Bo
    Yuan, Jiahai
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (15) : 21789 - 21802
  • [50] Spatiotemporal Variations of Carbon Emissions and Their Driving Factors in the Yellow River Basin
    Wang, Shiqing
    Sun, Piling
    Sun, Huiying
    Liu, Qingguo
    Liu, Shuo
    Lu, Da
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (19)