Spatial-temporal evolution of carbon emissions and spatial-temporal heterogeneity of influencing factors in the Bohai Rim Region, China

被引:1
|
作者
Zhang, Yangyang [1 ]
Hong, Wenxia [1 ]
机构
[1] Qingdao Univ Technol, Sch Management Engn, Qingdao 266520, Peoples R China
关键词
Carbon emissions; KDE; Standard deviation ellipses; Geodetector; Spatial-temporal heterogeneity; BRR; DRIVING FACTORS; CO2; EMISSIONS; ENERGY-CONSUMPTION; DECOMPOSITION ANALYSIS; ECONOMIC-GROWTH; DIOXIDE EMISSIONS; IMPACT FACTORS; CLIMATE-CHANGE; INTENSITY; URBANIZATION;
D O I
10.1007/s11356-024-32057-y
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The total change in carbon emissions in the Bohai Rim Region (BRR) plays a guiding role in the policy formulation of carbon emission reduction in northern China. Taking the 43 cities in the BRR as an example, the spatial-temporal evolution of carbon emissions in the BRR was analyzed using kernel density estimation (KDE), map visualization, and standard deviation ellipses, and the spatial autocorrelation model was used to explore the spatial clustering of carbon emissions. On this basis, the spatial-temporal heterogeneity of the factors influencing carbon emissions is explained using a Geodetector. The results are as follows: (i) During the study period, the carbon emissions in the BRR were on the rise, the share of carbon emissions in the Beijing-Tianjin-Hebei region (BTHR) and Liaoning Province was decreasing, and the contribution of Shandong Province was gradually enhanced. The spatial distribution of carbon emissions shows a geographical pattern of "middle-high and low-outside." (ii) Carbon emissions from different regions show the characteristics of BTHR > Shandong Province > Liaoning Province. The high-value carbon emission area continues to move from the northwest of Beijing-Tianjin-Hebei to the southeast. (iii) Municipal carbon emissions showed a significant positive spatial correlation in the later part of the study. The high-high aggregation area is in Tianjin, and the low-low aggregation area is in Liaoning Province. (iv) The level of transport development contributes to carbon emissions with the highest growth rate, followed by industrial structure. There are also regional differences in the dominant influences on municipal carbon emission differences. Population size, urbanization, and economic development level are the core influencing factors of carbon emissions in the BTHR, Shandong Province, and Liaoning Province, respectively. In addition, the explanatory power of the interaction between the level of economic development and other factors on carbon emissions is at a high level.
引用
收藏
页码:13897 / 13924
页数:28
相关论文
共 50 条
  • [41] Spatial-temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China
    Zheng, Ziyan
    Zhu, Yingming
    Pei, Yu
    Wang, Litao
    [J]. ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2023, 25 (11) : 12735 - 12759
  • [42] The analysis of spatial-temporal effects of relevant factors on carbon intensity in China
    Zheng, Yu
    Long, Yonghong
    Fan, Honggang
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2022, 36 (11) : 3785 - 3802
  • [43] Spatial-temporal evolution characteristics and influencing factors of county rural hollowing in Henan
    Yang, Menghao
    Yao, Zhihong
    Cao, Lianhai
    Zhang, Haipeng
    Huang, Jie
    [J]. CIENCIA RURAL, 2019, 49 (04):
  • [44] Spatial-temporal Characteristics of Rural Settlements Evolution in China
    Zhang, Liqiang
    Geng, Hao
    Liu, Yansui
    Li, Xingang
    Xin, Qi
    Peng, Shuwen
    [J]. Tongji Daxue Xuebao/Journal of Tongji University, 2022, 50 (07): : 967 - 974
  • [45] Analysis of spatial-temporal association and factors influencing environmental pollution incidents in China
    Du, Linwei
    Wang, Huizhi
    Xu, He
    [J]. ENVIRONMENTAL IMPACT ASSESSMENT REVIEW, 2020, 82
  • [46] Research on Spatial-Temporal Characteristics and Driving Factor of Agricultural Carbon Emissions in China
    Tian Yun
    Zhang Jun-biao
    He Ya-ya
    [J]. JOURNAL OF INTEGRATIVE AGRICULTURE, 2014, 13 (06) : 1393 - 1403
  • [47] An empirical study on spatial-temporal dynamics and influencing factors of apple production in China
    Zhang, Qiangqiang
    Shi, Fanji
    Abdullahi, Nazir Muhammad
    Shao, Liqun
    Huo, Xuexi
    [J]. PLOS ONE, 2020, 15 (10):
  • [48] Spatial-Temporal Distribution and the Influencing Factors of Water Conservation Function in Yunnan, China
    Qin, Zhuo
    Yang, Jiameng
    Qiu, Mengyuan
    Liu, Zhiyong
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (21):
  • [49] The spatial-temporal pattern of Japanese encephalitis and its influencing factors in Guangxi, China
    Li, Feifei
    Li, Hairong
    Yang, Linsheng
    Wang, Li
    Gu, Lijuan
    Zhong, Gemei
    Zhang, Lan
    [J]. INFECTION GENETICS AND EVOLUTION, 2023, 111
  • [50] Spatial-temporal distribution and the influencing factors of mountain flood disaster in southwest China
    Xiong J.
    Li J.
    Cheng W.
    Zhou C.
    Guo L.
    Zhang X.
    Wang N.
    Li W.
    [J]. Dili Xuebao/Acta Geographica Sinica, 2019, 74 (07): : 1374 - 1391