Spatial pattern evolution and driving forces of China's carbon transfer
Received date: 2024-08-19
Revised date: 2025-04-16
Online published: 2025-05-23
Supported by
National Natural Science Foundation of China(42171186)
Henan Philosophy and Social Sciences Project(2023CJJ128)
Analyzing the evolution of spatial patterns and driving forces of carbon transfer is essential for the equitable allocation of carbon emission responsibilities, accurate identification of regional carbon emission sources, and improvement in carbon reduction efficiency. Existing research on carbon transfer in China has primarily focused on inter-country and inter-provincial connections at single points in time, lacking an analysis of the long-term dynamic evolution and driving factors behind both domestic and international carbon transfers at the provincial scale. This study addresses this research gap. Using a multi-scale input-output model, this study quantified the carbon transfers associated with domestic and international trade for 31 Chinese provinces (excluding Hong Kong, Macau, and Taiwan) from 1997 to 2017. It further analyzed the evolution characteristics of spatial patterns and their driving forces. The findings indicate: (1) Carbon transfers in both domestic and international trade increased significantly across all provinces. Spatial differentiation intensified along a north-south axis for domestic trade and an east-central-west axis for international trade. (2) Growth in net carbon transfers in domestic trade was primarily driven by carbon-intensive industries, whereas growth in international trade transfers was primarily driven by manufacturing industries. (3) The intensification of spatial differentiation in domestic carbon transfers was mainly driven by the expansion of inter-regional trade in carbon-intensive industries. Similarly, intensified spatial differentiation in international carbon transfers was mainly driven by increased exports of manufactured products. Conversely, reductions in carbon emission intensity and adjustments in input-output structures had mitigating effects on these trends. This study provides scientific support for optimizing provincial carbon reduction strategies and developing coordinated inter-provincial carbon reduction policies in China.
ZHAO Danyang , TONG Lianjun , MIAO Changhong . Spatial pattern evolution and driving forces of China's carbon transfer[J]. Acta Geographica Sinica, 2025 , 80(5) : 1244 -1260 . DOI: 10.11821/dlxb202505006
[1] |
[张琦峰, 方恺, 徐明, 等. 基于投入产出分析的碳足迹研究进展. 自然资源学报, 2018, 33(4): 696-708.]
|
[2] |
|
[3] |
[毛熙彦, 贺灿飞. “全球—国家—地方”尺度下的国际贸易环境效应研究进展. 地理科学进展, 2016, 35(8): 1027-1038.]
|
[4] |
|
[5] |
|
[6] |
|
[7] |
|
[8] |
[李富佳. 区际贸易隐含碳排放转移研究进展与展望. 地理科学进展, 2018, 37(10): 1303-1313.]
|
[9] |
[韩梦瑶, 姚秋蕙, 劳浚铭, 等. 中国省域碳排放的国内外转移研究: 基于嵌套网络视角. 中国科学: 地球科学, 2020, 50(6): 748-764.]
|
[10] |
|
[11] |
|
[12] |
[刘红光, 范晓梅. 中国区域间隐含碳排放转移. 生态学报, 2014, 34(11): 3016-3024.]
|
[13] |
[陈晖, 温婧, 庞军, 等. 基于31省MRIO模型的中国省际碳转移及碳公平研究. 中国环境科学, 2020, 40(12): 5540-5550.]
|
[14] |
[钟章奇, 张旭, 何凌云, 等. 区域间碳排放转移、贸易隐含碳结构与合作减排: 来自中国30个省区的实证分析. 国际贸易问题, 2018(6): 94-104.]
|
[15] |
|
[16] |
[杨子涵, 彭宝玉, 孙君. 京津冀地区产业链空间网络及其隐含碳排放研究. 地理科学进展, 2024, 43(2): 215-230.]
|
[17] |
[黄明辉, 李巍, 陆中桂, 等. 黄河流域城市群碳足迹及隐含碳转移研究. 中国环境科学, 2024, 44(6): 3544-3552.]
|
[18] |
|
[19] |
[王育宝, 何宇鹏. 中国省域净碳转移测算研究. 管理学刊, 2020, 33(2): 1-10.]
|
[20] |
[姜鸿, 高洁, 张艺影. 基于碳排放权价值的中国省域绿色贸易利益测度. 中国人口·资源与环境, 2022, 32(5): 34-45.]
|
[21] |
|
[22] |
|
[23] |
|
[24] |
|
[25] |
|
[26] |
|
[27] |
[洪思扬, 王红瑞, 程涛, 等. 国际及省际贸易视角下的中国虚拟水和隐含能源流通规律分析. 地理科学, 2022, 42(10): 1735-1746.]
|
[28] |
[朱文博, 李双成, 朱连奇. 中国省域生态系统服务足迹流动及其影响因素. 地理研究, 2019, 38(2): 337-347.]
|
[29] |
[孙思奥, 王晶, 戚伟. 青藏高原地区城乡虚拟水贸易格局与影响因素. 地理学报, 2020, 75(7): 1346-1358.]
|
[30] |
[孙才志, 阎晓东. 基于MRIO的中国省区和产业灰水足迹测算及转移分析. 地理科学进展, 2020, 39(2): 207-218.]
|
[31] |
[王少剑, 王婕妤. 区域贸易视角下中国省域隐含土地流动研究. 地理学报, 2022, 77(5): 1072-1085.]
|
[32] |
|
[33] |
[吴乐英, 钟章奇, 刘昌新, 等. 中国省区间贸易隐含PM2.5的测算及其空间转移特征. 地理学报, 2017, 72(2): 292-302.]
|
[34] |
|
[35] |
|
[36] |
|
[37] |
|
[38] |
|
[39] |
|
/
〈 |
|
〉 |