珠江三角洲地区碳排放空间关联网络特征及影响因素

徐茜; 林洁欣; 林子晴; 张家俊; 程丽; 杨忍

doi:10.16152/j.cnki.xdxbzr.2026-04-017

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珠江三角洲地区碳排放空间关联网络特征及影响因素

人地系统科学 | 更新时间：2026-07-27

- 珠江三角洲地区碳排放空间关联网络特征及影响因素
- The characteristics and influencing factors of spatial correlation network of carbon emissions in the Pearl River Delta Region
- 西北大学学报（自然科学版） 2026年56卷第4期页码：898-912
- 作者机构：
  
  1.广东财经大学　公共管理学院，广东　广州　510320
  2.广州康养集团有限公司，广东　广州　510630
  3.中山大学　地理科学与规划学院，广东　广州　510006
- 作者简介：
  
  徐茜，女，博士，副教授，硕士生导师，从事土地利用生态效应及土地资源管理研究，xuqian@gdufe.edu.cn。
  杨忍，男，博士，教授，博士生导师，从事土地资源管理及乡村地理研究，yangren0514@163.com。
- 基金信息：
  
  国家自然科学基金(42171193)
- DOI：10.16152/j.cnki.xdxbzr.2026-04-017
  中图分类号： X321
- 收稿：2025-09-15，
  
  修回：2025-11-09，
  
  纸质出版：2026-08-25
- 稿件说明：
移动端阅览
徐茜, 林洁欣, 林子晴, 等. 珠江三角洲地区碳排放空间关联网络特征及影响因素[J]. 西北大学学报（自然科学版）, 2026,56(4):898-912.

Xu Qian, Lin Jiexin, Lin Ziqing, et al. The characteristics and influencing factors of spatial correlation network of carbon emissions in the Pearl River Delta Region[J]. Journal of Northwest University (Natural Science Edition), 2026, 56(4): 898-912.
徐茜, 林洁欣, 林子晴, 等. 珠江三角洲地区碳排放空间关联网络特征及影响因素[J]. 西北大学学报（自然科学版）, 2026,56(4):898-912. DOI： 10.16152/j.cnki.xdxbzr.2026-04-017.

Xu Qian, Lin Jiexin, Lin Ziqing, et al. The characteristics and influencing factors of spatial correlation network of carbon emissions in the Pearl River Delta Region[J]. Journal of Northwest University (Natural Science Edition), 2026, 56(4): 898-912. DOI： 10.16152/j.cnki.xdxbzr.2026-04-017.

摘要

在“双碳”目标下，揭示珠江三角洲地区碳排放空间关联网络特征，对探索区域社会经济的绿色化和低碳化转型具有重要理论价值和现实意义。采用IPCC测评方法、修正后的引力模型及QAP回归方法等，剖析2010—2022年珠三角碳排放的时空演化过程，以及碳排放的空间关联网络演化特征和影响因素。结果表明：①珠三角碳排放量在时序上呈持续上升态势，但2020年略有下降，在空间上呈现以深圳和广州为核心的高排放区域，且珠江东岸地区明显高于西岸地区，珠三角碳排放与社会经济发展的脱钩关系整体呈弱脱钩特征，2020年以来，随着碳排放量持续下降，正加速向强脱钩迈进；②碳排放空间关联网络整体特征逐渐趋于复杂化、通达化演变，关联线更加密集且朝着多向性发展，广州和深圳位于网络的中心位置，扮演着“中心行动者”角色，其他各区域板块在空间关联网络中呈现出显著的梯度性，板块内部存在明显的空间溢出特征；③地理空间邻近性、经济发展水平、能源消费强度和产业结构等对区域碳排放的空间关联网络产生重要影响。上述研究为区域协同减排、优化碳平衡及推动可持续发展提供了科学依据与实践指引。

Abstract

Under the "dual carbon goals"

revealing the spatial correlation network characteristics of carbon emissions in the Pearl River Delta Region

holds significant theoretical value and practical significance for exploring the green and low-carbon transformation of regional socioeconomic systems. Using the IPCC assessment methodology

modified gravity model

and QAP regression method

this study conducts an analysis of the spatiotemporal evolution process of carbon emissions in the Pearl River Delta Region from 2010 to 2022

and explores the evolutionary characteristics and influencing factors of the spatial correlation network of carbon emissions. The results have 3 findings. ①Temporally

carbon emissions presented a continuous upward trend in the Pearl River Delta Region

with a slight decline in 2020; spatially

it showed a pattern where Shenzhen and Guangzhou were the core high-emission areas

and the eastern bank of the Pearl River was significantly higher than the western bank. The overall decoupling relationship between carbon emissions and socioeconomic development in the Pearl River Delta Region showed a weak decoupling characteristic

and since 2020

with the continuous decline in carbon emissions

it has been accelerating toward strong decoupling. ②The overall characteristics of the carbon emission spatial correlation network have gradually evolved toward being more complex and accessible

with connection lines becoming denser and developing toward multi-directionality. Guangzhou and Shenzhen are located at the center of the network

playing the role of "central actors"; other regional plates show significant graduality in the spatial association network

with obvious spatial spillover characteristics within the plates. ③Geographical proximity

economic development level

energy consumption intensity

and industrial structure have significant impacts on the spatial correlation network of regional carbon emissions. The research provides scientific basis and practical guidance for regional collaborative emission reduction

optimizing carbon balance

and promoting sustainable development.

关键词

Keywords

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