Spatial-temporal characteristics and influencing factors of farmland carbon emissions in Guangdong Province, China

被引:0
|
作者
Chao, Zihao [1 ,2 ,3 ]
Zhu, Ziyang [1 ,2 ,3 ]
Li, Yuchen [4 ]
机构
[1] Surveying & Mapping Inst Lands & Resource Dept Gua, Guangzhou, Peoples R China
[2] Minist Nat Resources, Key Lab Nat Resources Monitoring Trop & Subtrop Ar, Guangzhou, Peoples R China
[3] Guangdong Sci & Technol Collaborat Innovat Ctr Nat, Guangzhou, Peoples R China
[4] South China Normal Univ, Sch Geog, Guangzhou, Peoples R China
关键词
farmland carbon emissions; spatial-temporal characteristics; influencing factors; decoupling model; LMDI; AGRICULTURE; FOOTPRINT;
D O I
10.3389/fenvs.2024.1515571
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Agricultural carbon emissions account for 17% of total greenhouse gas emissions in China. To effectively address the eco-environment changes in farmland, which serves as the foundation of agricultural activities, it is essential to estimate regional farmland carbon emissions. This study calculated the farmland carbon emissions in Guangdong from 2011 to 2021 using the classical IPCC carbon emission calculation methodology. The decoupling characteristics betweem farmland carbon emissions and agricultural output values were analyzed utilizing a decoupling model, and the influencing factors were examined through the Logarithmic Mean Divisia Index (LMDI). The results indicate that: 1) Farmland carbon emissions in Guangdong decreased by 13.21% from 2011 to 2021, with pesticide reductions contributing the most to emission decreases. Chemical fertilizers were the largest contributor to farmland carbon emissions, accounting for approximately 61.78% of the total. 2) The spatial distribution of farmland carbon emissions followed the pattern of "Western Guangdong > Northern Guangdong > Eastern Guangdong > Pearl River Delta". While emission intensity generally declined, regional disparities widened. 3) Most cities in Guangdong exhibited a strong decoupling relationship between farmland carbon emissions and agricultural output values, with decoupling coefficient ranging from -1.182 to -0.004. However, Heyuan and Shenzhen demonstrated a weak decoupling relationship. 4) The primary driver of increased farmland carbon emissions in Guangdong was the level of agricultural output, while improvements in agricultural production efficiency were the most significant inhibitory factor, followed by changes in the scale of agricultural labor force. This study offers policy recommendations to promote the reduction and sequestration of farmland carbon emissions in Guangdong.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Spatial-temporal characteristics and influencing factors of county-level carbon emissions in Zhejiang Province, China
    Qi, Huibo
    Shen, Xinyi
    Long, Fei
    Liu, Meijuan
    Gao, Xiaowei
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (04) : 10136 - 10148
  • [2] Spatial-temporal characteristics and influencing factors of farmland expansion in different agricultural regions of Heilongjiang Province, China
    Chen, Hang
    Meng, Fei
    Yu, Zhenning
    Tan, Yongzhong
    LAND USE POLICY, 2022, 115
  • [3] Spatial-temporal pattern and influencing factors of agricultural carbon emissions at the county level in Jiangxi Province of China
    Zheng B.
    Liang H.
    Wan W.
    Liu Z.
    Zhu J.
    Wu Z.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2022, 38 (23): : 70 - 80
  • [4] Influencing Factors and Their Spatial-Temporal Heterogeneity of Urban Transport Carbon Emissions in China
    Zhao, Peng
    Tian, Bei Si
    Yang, Qi
    Zhang, Shuai
    ENERGIES, 2024, 17 (03)
  • [5] Spatial-temporal evolution of carbon emissions and spatial-temporal heterogeneity of influencing factors in the Bohai Rim Region, China
    Zhang, Yangyang
    Hong, Wenxia
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2024, 31 (09) : 13897 - 13924
  • [6] Spatial-temporal evolution of carbon emissions and spatial-temporal heterogeneity of influencing factors in the Bohai Rim Region, China
    Yangyang Zhang
    Wenxia Hong
    Environmental Science and Pollution Research, 2024, 31 : 13897 - 13924
  • [7] Spatial-temporal patterns and influencing factors of carbon emissions in different regions of China
    Wang, Ning
    Qu, Zhongke
    Li, Jin
    Zhang, Yang
    Wang, Huanyuan
    Xi, Hui
    Gu, Zhaolin
    ENVIRONMENTAL RESEARCH, 2025, 276
  • [8] Spatial-Temporal Evolution and Influencing Factors of Animal Husbandry Carbon Emissions: A Case Study of Shandong Province, China
    Wei, Chunbo
    Sha, Yanyu
    Hou, Yongwei
    Li, Jiaqi
    Qu, Yongli
    SUSTAINABILITY, 2024, 16 (09)
  • [9] Spatial-temporal Evolution Characteristics and Decoupling Analysis of Influencing Factors of China’s Aviation Carbon Emissions
    Ruiling Han
    Lingling Li
    Xiaoyan Zhang
    Zi Lu
    Shaohua Zhu
    Chinese Geographical Science, 2022, 32 : 218 - 236
  • [10] Spatial-temporal Evolution Characteristics and Decoupling Analysis of Influencing Factors of China's Aviation Carbon Emissions
    HAN Ruiling
    LI Lingling
    ZHANG Xiaoyan
    LU Zi
    ZHU Shaohua
    Chinese Geographical Science, 2022, 32 (02) : 218 - 236