Spatiotemporal characteristics and determinants of agricultural carbon offset rate in China based on the geographic detector

被引:13
作者
Huang, Jie [1 ]
Sun, Zimin [1 ]
Du, Minzhe [2 ]
机构
[1] Xinyang Normal Univ, Business Sch, Xinyang 464000, Henan, Peoples R China
[2] South China Normal Univ, Sch Econ & Management, Guangzhou 510006, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Agricultural carbon offset rate; Spatiotemporal characteristics; Dynamic evolution; Determinants; GREENHOUSE-GAS EMISSIONS; SEQUESTRATION; DIOXIDE;
D O I
10.1007/s11356-023-26659-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper attempts to explore the spatiotemporal variation characteristics of the agricultural carbon offset rate (ACOR) and the reasons that shape its differentiation characteristics in China. To achieve this objective, the Dagum Gini coefficient, kernel density estimation, and geographic detector model are employed in this study. The results show that there are some differences in ACOR among regions in China. Interregional differences are the main source of their overall variation. Excluding the spatial conditions, the ACOR of each province in the sample period shows low mobility characteristics. Considering the spatial conditions, there is convergence in the lower-middle neighborhoods. The three-year lag period did not significantly affect the interaction of ACOR between regions under the accession time horizon. At the aggregate level, the spatial and temporal divergence in China's ACOR is driven by urbanization rate, agricultural fiscal expenditure, and rural education level. As for the regional level, the scale of household farmland operation plays a greater role in determining the spatiotemporal variation of the eastern and central regions' ACOR. While urbanization rate is more determinant for the western region, the interaction between any two factors has significantly higher explanatory power for the spatial and temporal variation of ACOR than the single factor.
引用
收藏
页码:58142 / 58155
页数:14
相关论文
共 49 条
  • [21] Measurement and Spatial-Temporal Characteristics of Agricultural Carbon Emission in China: An Internal Structural Perspective
    Wen, Shibin
    Hu, Yuxiang
    Liu, Hongman
    AGRICULTURE-BASEL, 2022, 12 (11):
  • [22] Spatiotemporal characteristics of carbon emissions in Shaanxi, China, during 2012–2019: a machine learning method with multiple variables
    Ziyan Liu
    Ling Han
    Ming Liu
    Environmental Science and Pollution Research, 2023, 30 : 87535 - 87548
  • [23] Spatio-temporal characteristics of livestock and their effects on pollution in China based on geographic information system
    Ruimin Liu
    Fei Xu
    Yongyan Liu
    Jiawei Wang
    Wenwen Yu
    Environmental Science and Pollution Research, 2016, 23 : 14183 - 14195
  • [24] Disaster process–based spatiotemporal characteristics of apricot frost in the warm temperate zone (WTZ), China
    Jianying Yang
    Lei Zhang
    Zhiguo Huo
    Peijuan Wang
    Dingrong Wu
    Yuping Ma
    International Journal of Biometeorology, 2023, 67 : 1733 - 1744
  • [25] Spatiotemporal characteristics and influencing factors of carbon emissions from land-use change in Shaanxi Province, China
    Fang, Wei
    Luo, Pingping
    Luo, Lintao
    Zha, Xianbao
    Nover, Daniel
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (59) : 123527 - 123555
  • [26] Spatio-temporal characteristics of livestock and their effects on pollution in China based on geographic information system
    Liu, Ruimin
    Xu, Fei
    Liu, Yongyan
    Wang, Jiawei
    Yu, Wenwen
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2016, 23 (14) : 14183 - 14195
  • [27] China's CO2 Emissions: A Thorough Analysis of Spatiotemporal Characteristics and Sustainable Policy from the Agricultural Land-Use Perspective during 1995-2020
    Liu, Shuting
    Jia, Junsong
    Huang, Hanzhi
    Chen, Dilan
    Zhong, Yexi
    Zhou, Yangming
    LAND, 2023, 12 (06)
  • [28] Spatiotemporal characteristics of carbon emissions in Shaanxi, China, during 2012-2019: a machine learning method with multiple variables
    Liu, Ziyan
    Han, Ling
    Liu, Ming
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (37) : 87535 - 87548
  • [29] Disaster process-based spatiotemporal characteristics of apricot frost in the warm temperate zone (WTZ), China
    Yang, Jianying
    Zhang, Lei
    Huo, Zhiguo
    Wang, Peijuan
    Wu, Dingrong
    Ma, Yuping
    INTERNATIONAL JOURNAL OF BIOMETEOROLOGY, 2023, 67 (11) : 1733 - 1744
  • [30] Analysis of spatiotemporal characteristics of surface soil moisture across China based on multi-satellite observations
    Liu R.
    Zhang K.
    Chao L.
    Wang Q.
    Hong Y.
    Tu Y.
    Qu W.
    Zhang, Ke (kzhang@hhu.edu.cn), 1600, International Research and Training Center on Erosion and Sedimentation and China Water and Power Press (28): : 479 - 487