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经济地理 >

2023 , Vol. 43 >Issue 12: 91 - 102

DOI: https://doi.org/10.15957/j.cnki.jjdl.2023.12.009

城市地理与新型城镇化

中国五大城市群用地景观格局对碳排放绩效的影响

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  • 1.广州大学 建筑与城市规划学院,中国广东 广州 510006;
    2.四川大学 商学院,中国四川 成都 610065;
    3.中山大学 地理科学与规划学院/中国区域协调发展与乡村建设研究院,中国广东 广州 510275;
    4.广州大学 经济与统计学院,中国广东 广州 510006
李珊（1987—）,女,博士,讲师,研究方向为产业升级与区域发展。E-mail：lishan@gzhu.edu.cn
※朱宁（1986—）,男,博士,副教授,研究方向为效率和生产率分析。E-mail：znzy1986@163.com

收稿日期: 2022-09-13

  修回日期: 2023-02-10

  网络出版日期: 2024-03-29

基金资助

国家自然科学基金项目（42301182）; 广东省基础与应用基础研究基金项目（2022A1515110331）; 广东省哲学社会科学规划项目（GD23XGL076）; 广州大学“2+5”学科与科研创新平台科研项目（PT252022023）

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Impact of Land Use Landscape Pattern on Carbon Emission Performance in Five Major Urban Agglomerations in China

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  • 1. College of Architecture and Urban Planning,Guangzhou University,Guangzhou 510006,Guangdong,China;
    2. Business School,Sichuan University,Chengdu 610065,Sichuan,China;
    3. School of Geography and Planning& China Regional Coordinated Development and Rural Construction Institute,Sun Yat-sen University,Guangzhou 510275,Guangdong,China; ;
    4. School of Economics and Statistics,Guangzhou University,Guangzhou 510006,Guangdong,China

Received date: 2022-09-13

  Revised date: 2023-02-10

  Online published: 2024-03-29

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摘要

文章以中国五大城市群为案例,基于精细化的碳排放与用地景观栅格数据,利用非期望产出超效率SBM模型测算2005—2018年城市碳排放绩效,利用景观指数量化城市用地景观格局,再结合核密度估计和泰尔指数揭示城市群碳排放绩效与用地景观格局的演化规律,最后结合线性拟回归与Pearson相关性对城市群用地景观格局与碳排放绩效的关系进行分析。结果表明：①五大城市群碳排放绩效呈上升趋势但整体水平不高,在空间上呈现“东高西低”格局,城市群内碳排放绩效比城市群间差异更大。②研究期间五大城市群间及内部景观指数的差距逐渐缩小,其中城市扩张指标“景观总面积”呈上升趋势,表现为东部城市群高于中西部;形状复杂性指标“景观形状指数”与紧凑型指标“分离度指数”呈下降趋势,两者均表现为京津冀最高、珠三角最低。③城市群用地景观格局与碳排放绩效紧密相关且具有区域异质性。城市建设用地扩张在京津冀、长江中游、珠三角促进碳排放绩效提升;除了长江中游城市群,城市用地形状复杂度指数与紧凑度指数均抑制碳排放绩效。

关键词： 碳排放绩效; 城市用地景观格局; 五大城市群; 建设用地; 长三角与珠三角; 京津冀; 绿色发展

本文引用格式

李珊, 温榕冰, 李建军, 杨豪, 陈婷婷, 朱宁 . 中国五大城市群用地景观格局对碳排放绩效的影响[J]. 经济地理, 2023 , 43(12) : 91 -102 . DOI: 10.15957/j.cnki.jjdl.2023.12.009

Abstract

Taking the five major urban agglomerations in China as a case study and based on the refined carbon emission and land use landscape raster data,this paper uses the super-efficiency SBM with undesirable output model to measure the urban CEP from 2005 to 2018,and uses the landscape index to quantify the urban land use landscape pattern,and then combines with the kernel density estimation and the Theil index to reveal the evolution of the urban agglomerations' CEP and the land use landscape pattern. It analyzes the relationship between urban land use landscape pattern and CEP by the means of the linear fitting regression and Pearson's correlation. The results show that: 1) The CEP of the five major urban agglomerations shows an upward trend,but its overall level is not high,it presents the spatial distribution pattern of "high in the east of China and low in the west of China", the CEP shows the bigger difference in the urban agglomerations than that among five urban agglomerations. 2) During the study period, the differences of landscape indices gradually narrow among and within the five major urban agglomerations. The total landscape area shows an upward trend,which is higher in the urban agglomerations of the eastern region than that in the central and western regions. The landscape shape index and the separation index both show an downward trend,which is the highest in Beijing-Tianjin-Hebei urban agglomeration and the lowest in the Pearl River Delta urban agglomeration. 3) The land use landscape pattern of urban agglomerations is closely related to the CEP and has regional heterogeneity. The expansion of urban construction land promotes the improvement of CEP in Beijing-Tianjin-Hebei urban agglomeration,the middle reaches of the Yangtze River urban agglomeration,and the Pearl River Delta (PRD) urban agglomeration. The complexity index and compactness index of the urban land use shape both inhibit the CEP except for the middle reaches of the Yangtze River urban agglomeration.

Key words： carbon emission efficiency; urban land use landscape pattern; five urban agglomerations; construction land; Yangtze River Delta and Pearl River Delta; Beijing-Tianjin-Hebei; green development

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