碳排放

黄河流域城市紧凑度对碳排放绩效的影响

  • 程兰花 ,
  • 杨显明 ,
  • 吴昕燕
展开
  • 1.青海师范大学地理科学学院,青海 西宁 810016
    2.青藏高原地表过程与生态保育教育部重点实验室,青海 西宁 810016
    3.宁夏大学工程与地理学部,宁夏 银川 750021
程兰花(1991-),女,博士研究生,主要从事能源经济与区域可持续发展等方面的研究. E-mail: chenglanhua91@163.com
杨显明(1980-),男,博士,副教授,主要从事城市地理与城市经济、区域可持续发展与空间规划等方面的研究. E-mail: 21cnyjs@163.com

收稿日期: 2024-06-11

  修回日期: 2024-08-12

  网络出版日期: 2025-05-13

基金资助

国家级第二次青藏高原综合科学考察研究子项目(SQ2019QZKK2905);青海科技厅软科学研究计划项目(2019-ZJ-605);国家自然科学基金项目(41961045)

Impact of urban compactness on carbon emission performance in the Yellow River Basin

  • CHENG Lanhua ,
  • YANG Xianming ,
  • WU Xinyan
Expand
  • 1. College of Geographical Sciences, Qinghai Normal University, Xining 810016, Qinghai, China
    2. Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation (Ministry of Education), Xining 810016, Qinghai, China
    3. Faculty of Engineering and Geography, Ningxia University, Yinchuan 750021, Ningxia, China

Received date: 2024-06-11

  Revised date: 2024-08-12

  Online published: 2025-05-13

摘要

国家“双碳”目标背景下,适度的紧凑是黄河流域城市绿色低碳高质量发展的最佳选择。以黄河流域77个地级市为例,多维度构建综合评价指标体系,基于熵权法、综合加权求和模型、核密度估计、双变量空间自相关分析、时空地理加权回归模型和地理探测器等方法,分析2005—2021年黄河流域城市紧凑度对碳排放绩效的影响。结果表明:(1) 2005—2021年黄河流域城市紧凑度与碳排放绩效均略有提升,分别呈现“上中游低、下游高”“中游低、上下游高”的空间分布格局。(2) 2005—2021年黄河流域内城市紧凑度与碳排放绩效的关联性具有明显的时空差异,多呈空间负相关性,且呈空间负相关性的城市数量增多,呈空间正相关性的城市多位于中下游地区。(3) 2005—2021年黄河流域城市土地利用紧凑度和人口紧凑度对碳排放绩效的负向影响较为明显,土地利用紧凑度负向影响减弱,人口紧凑度在中上游地区负向影响增强但在下游地区负向影响减弱;经济紧凑度和交通紧凑度对碳排放绩效主要为正向影响,但交通紧凑度在上下游地区负向影响区均增多。(4) 2005—2021年黄河流域城市紧凑度与其他社会经济因子交互后对碳排放绩效的影响均增强,各因子协同作用共同影响碳排放绩效,其中经济紧凑度和能源消耗水平协同作用影响最大。未来,该流域应通过因地制宜实施差异化的城市紧凑发展策略、优化产业结构、提升城镇化质量、强化低碳技术创新和加强城市紧凑度动态调控等方式,促进经济增长、社会福利提升与低碳减排的协同发展。

本文引用格式

程兰花 , 杨显明 , 吴昕燕 . 黄河流域城市紧凑度对碳排放绩效的影响[J]. 干旱区地理, 2025 , 48(5) : 838 -853 . DOI: 10.12118/j.issn.1000-6060.2024.363

Abstract

Under the framework of China’s “double carbon” goal, moderately compact urban development is considered the optimal approach for achieving green, low-carbon, and high-quality growth in the Yellow River Basin. Considering 77 prefecture-level cities in the Yellow River Basin as examples, this study constructed a comprehensive evaluation index system across several dimensions such as population, economy, and society. Employing the entropy weight technique, comprehensive weighted summation model, kernel density estimation, bivariate spatial autocorrelation analysis, spatiotemporal weighted regression model, and a geographical detector, this study analyzed the effects and mechanisms of urban compactness on carbon emission performance in the Yellow River Basin from 2005 to 2021. The results are as follows. (1) From 2005 to 2021, both the urban compactness and carbon emission performance in the Yellow River Basin slightly increased. Urban compactness exhibited a spatial distribution pattern of “lower in the upper and middle reaches, and higher in the lower reaches”, whereas carbon emission performance exhibited a pattern of “lower in the middle reaches, and higher in the upper and lower reaches”. (2) The correlation between urban compactness and carbon emission performance varied significantly across time and space in the Yellow River Basin from 2005 to 2021. Most cities demonstrated a negative spatial correlation, with the number of such cities increasing over time in the Yellow River Basin. Cities of the Yellow River Basin with positive spatial correlation between urban compactness and carbon emission performance were mostly located in the middle and lower reaches. (3) The negative impacts of land use compactness and population compactness on carbon emission performance were relatively obvious in the Yellow River Basin from 2005 to 2021. The negative impact of land use compactness weakened. For population compactness, the negative impact increased in the mid-upper reaches regions but weakened in the downstream regions. The economic compactness and transportation compactness mainly had positive impacts on carbon emission performance, yet the areas with negative impacts of transportation compactness increased both in the upstream and downstream regions. (4) The influence of urban compactness on the carbon emission performance was enhanced when interacting with other socioeconomic factors in the Yellow River Basin from 2005 to 2021. Synergies among various factors considerably affected the carbon emission performance. The greatest combined effect was observed between the economic compactness and energy consumption levels. Thus, to promote coordinated development in the Yellow River Basin, differentiated urban compact development strategies must be implemented based on regional conditions. Further, efforts should focus on the optimization of industrial structures, improvement of urbanization quality, fostering of low-carbon technology innovation, and dynamic adjustments of urban compactness. These measures are aimed at promoting balanced economic growth, social welfare, and low-carbon development across the entire basin.

参考文献

[1] 杨浩, 卢新海, 匡兵, 等. 城市紧凑度与碳排放强度的时空互动关系及驱动因素——以长株潭城市群为例[J]. 长江流域资源与环境, 2021, 30(11): 2618-2629.
  [Yang Hao, Lu Xinhai, Kuang Bing, et al. Spatial-temporal interaction and driving factors of urban compactness and carbon emission intensity: A case study in Changsha-Zhuzhou-Xiangtan urban agglomeration[J]. Resources and Environment in the Yangtze Basin, 2021, 30(11): 2618-2629. ]
[2] 万赟, 吴文恒, 刘金凤, 等. 近30 a黄河流域中心城市空间扩展特征及启示[J]. 干旱区地理, 2024, 47(2): 281-292.
  [Wan Yun, Wu Wenheng, Liu Jinfeng, et al. Spatial expansion characteristics and their enlightenment in central cities in the Yellow River Basin in the last 30 years[J]. Arid Land Geography, 2024, 47(2): 281-292. ]
[3] 王录仓, 屈艳琦, 武潼. 城市群空间结构对城市群空间扩张模式与形态的影响——兰西城市群和宁夏沿黄城市群比较[J]. 中国沙漠, 2024, 44(3): 63-74.
  [Wang Lucang, Qu Yanqi, Wu Tong. The influence of spatial structure of urban agglomeration on spatial expansion patterns and forms: Comparison between Lanzhou-Xining urban agglomeration and Ningxia urban agglomeration along the Yellow River[J]. Journal of Desert Research, 2024, 44(3): 63-74. ]
[4] 王少剑, 高爽, 黄永源, 等. 基于超效率SBM模型的中国城市碳排放绩效时空演变格局及预测[J]. 地理学报, 2020, 75(6): 1316-1330.
  [Wang Shaojian, Gao Shuang, Huang Yongyuan, et al. Spatio-temporal evolution and trend prediction of urban carbon emission performance in China based on super-efficiency SBM model[J]. Acta Geographica Sinica, 2020, 75(6): 1316-1330. ]
[5] Salvati L. From sprawl to compactness and back: Population dynamics (1848—2011) and the economic structure of a Mediterranean City[J]. GeoJournal,2016, 81: 319-332.
[6] Liu Y, Song Y, Song X D. An empirical study on the relationship between urban compactness and CO2 efficiency in China[J]. Habitat International, 2014, 41: 92-98.
[7] McFarlane C. Density and the compact city[J]. Dialogues in Human Geography, 2023, 13(1): 35-38.
[8] 毛广雄, 丁金宏, 曹蕾. 城市紧凑度的综合测度及驱动力分析——以江苏省为例[J]. 地理科学, 2009, 29(5): 627-633.
  [Mao Guangxiong, Ding Jinhong, Cao Lei. Comprehensive level and impetus of city compactness: A case of Jiangsu Province[J]. Scientia Geographica Sinica, 2009, 29(5): 627-633. ]
[9] Luan H, Fuller D. Urban form in Canada at a small-area level: Quantifying “compactness” and “sprawl” with Bayesian multivariate spatial factor analysis[J]. Environment and Planning B: Urban Analytics and City Science, 2022, 49(4): 1300-1313.
[10] 周新刚, 郎嵬. 面向就业活动紧凑度的紧凑城市规划策略[J]. 城市规划学刊, 2019(3): 50-57.
  [Zhou Xingang, Lang Wei. Planning for compact city from the perspective of employment activities[J]. Urban Planning Forum, 2019(3): 50-57. ]
[11] Stretesky P B, Lynch M J. A cross-national study of the association between per capita carbon dioxide emissions and exports to the United States[J]. Social Science Research, 2009, 38(1): 239-250.
[12] 程钰, 张悦, 王晶晶. 中国省域碳排放绩效时空演变与技术创新驱动研究[J]. 地理科学, 2023, 43(2): 313-323.
  [Cheng Yu, Zhang Yue, Wang Jingjing. Spatial-temporal evolution of provincial carbon emission performance and driving force of technological innovation in China[J]. Scientia Geographica Sinica, 2023, 43(2): 313-323. ]
[13] 陈飞, 沈世芳, 李永贺, 等. 城市密度对空间碳绩效的影响——以上海市为例[J]. 城市问题, 2022(2): 96-103.
  [Chen Fei, Shen Shifang, Li Yonghe, et al. The effect of urban density on spatial carbon performance: A case of Shanghai City[J]. Urban Problems, 2022(2): 96-103. ]
[14] 李珊, 温榕冰, 李建军, 等. 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.
  [Li Shan, Wen Rongbing, Li Jianjun, et al. Impact of land use landscape pattern on carbon emission performance in five major urban agglomerations in China[J]. Economic Geography, 2023, 43(12): 91-102. ]
[15] 陈飞, 谌子群, 王树建, 等. 城市空间紧凑发展对碳绩效的影响效应研究——以长三角41个城市为例[J]. 地域研究与开发, 2024, 43(2): 139-145.
  [Chen Fei, Chen Ziqun, Wang Shujian, et al. Study on effects of compact urban spatial development on carbon performance: A case study of 41 cities in the Yangtze River Delta[J]. Areal Research and Development, 2024, 43(2): 139-145. ]
[16] 郭艺, 曹贤忠, 魏文栋, 等. 长三角区域一体化对城市碳排放的影响研究[J]. 地理研究, 2022, 41(1): 181-192.
  [Guo Yi, Cao Xianzhong, Wei Wendong, et al. The impact of regional integration in the Yangtze River Delta on urban carbon emissions[J]. Geographical Research, 2022, 41(1): 181-192. ]
[17] 陈飞, 徐鹤, 李永贺. 长三角地区城市密度对碳排放绩效的影响效应与机制[J]. 生态学报, 2024, 44(10): 4092-4104.
  [Chen Fei, Xu He, Li Yonghe. Low-carbon development effects and mechanisms of urban density in the Yangtze River Delta region[J]. Acta Ecologica Sinica, 2024, 44(10): 4092-4104. ]
[18] 卢新海, 李佳, 刘超, 等. 中国城市土地绿色利用效率驱动因素及空间分异[J]. 地理科学, 2022, 42(4): 611-621.
  [Lu Xinhai, Li Jia, Liu Chao, et al. Driving factors and spatial differentiation of the urban land green use efficiency in China[J]. Scientia Geographica Sinica, 2022, 42(4): 611-621. ]
[19] 刘润佳, 把多勋. 中国省会城市紧凑度与城镇化水平关系[J]. 自然资源学报, 2020, 35(3): 586-600.
  [Liu Ruijia, Ba Duoxun. The relationship between urban compactness and urbanization level in capital cities of China[J]. Journal of Natural Resources, 2020, 35(3): 586-600. ]
[20] 邵帅, 范美婷, 杨莉莉. 经济结构调整、绿色技术进步与中国低碳转型发展——基于总体技术前沿和空间溢出效应视角的经验考察[J]. 管理世界, 2022, 38(2): 46-69, 4-10.
  [Shao Shuai, Fan Meiting, Yang Lili. Economic restructuring, green technical progress, and low-carbon transition development in China: An empirical investigation based on the overall technology frontier and spatial spillover effect[J]. Journal of Management World, 2022, 38(2): 46-69, 4-10. ]
[21] 李志英, 朱晓珊, 杨丽, 等. 成渝城市群紧凑度与碳排放强度时空演变及协调发展[J]. 环境科学, 2024, 45(6): 3402-3411.
  [Li Zhiying, Zhu Xiaoshan, Yang Li, et al. Spatio-temporal evolution and coordinated development of compactness with carbon emission intensity in the Chengdu-Chongqing urban agglomeration[J]. Environmental Science, 2024, 45(6): 3402-3411. ]
[22] 辛奕霖, 刘艳军, 柳力玮. 中国老工业城市人口增长与收缩对碳排放强度的影响效应[J]. 地理研究, 2024, 43(3): 558-576.
  [Xin Yilin, Liu Yanjun, Liu Liwei. The influence of population growth and shrinkage on carbon emission intensity in old industrial cities of China[J]. Geographical Research, 2024, 43(3): 558-576. ]
[23] Ribeiro H V, Rybski D, Kropp J P. Effects of changing population or density on urban carbon dioxide emissions[J]. Nature Communications, 2019, 10(1): 1-9.
[24] 孙浩, 郭劲光. 地方经济增长目标管理对碳排放效率的影响[J]. 自然资源学报, 2024, 39(1): 186-205.
  [Sun Hao, Guo Jinguang. The impact of local economic growth target management on carbon emissions efficiency[J]. Journal of Natural Resources, 2024, 39(1): 186-205. ]
[25] 江三良, 贾芳芳. 科技金融政策对城市碳排放绩效的影响效应研究——基于“科技与金融结合试点”的准自然实验[J]. 软科学, 2024, 38(3): 37-43.
  [Jiang Sanliang, Jia Fangfang. Impact of science and technology finance policy on urban carbon emission performance: A quasi-natural experiment[J]. Soft Science, 2024, 38(3): 37-43. ]
[26] 郑瑞婧, 程钰. 黄河流域创新要素集聚对碳排放效率的影响研究[J]. 地理研究, 2024, 43(3): 577-595.
  [Zheng Ruijing, Cheng Yu. Impacts of innovation factor agglomeration on carbon emission efficiency in the Yellow River Basin[J]. Geographical Research, 2024, 43(3): 577-595. ]
[27] 祁慧博, 沈欣懿, 龙飞, 等. 浙江省县域碳排放的时空格局与影响因素研究[J]. 长江流域资源与环境, 2023, 32(4): 821-831.
  [Qi Huibo, Shen Xinyi, Long Fei, et al. Study on spatial-temporal pattern and influencing factors of county carbon emissions in Zhejiang Province[J]. Resources and Environment in the Yangtze Basin, 2023, 32(4): 821-831. ]
[28] 吴尚, 翟彬, 程利莎. 黄河流域城市创新能力测度及空间分异研究[J]. 干旱区地理, 2024, 47(4): 720-732.
  [Wu Shang, Zhai Bin, Cheng Lisha. Measurement and spatial differentiation of innovation capacity of cities in Yellow River Basin[J]. Arid Land Geography, 2024, 47(4): 720-732. ]
[29] 师博, 何璐, 张文明. 黄河流域城市经济高质量发展的动态演进及趋势预测[J]. 经济问题, 2021(1): 1-8.
  [Shi Bo, He Lu, Zhang Wenming. Dynamic evolution and trend prediction of high-quality urban economic development in the Yellow River Basin[J]. On Economic Problems, 2021(1): 1-8. ]
[30] 金声甜, 李小花. 国家重点生态功能区设立对县域碳排放强度的影响——以长江经济带为例[J]. 经济地理, 2023, 43(9): 139-147.
  [Jin Shengtian, Li Xiaohua. Impact of the establishment of national key ecological function zones on carbon emission intensity: Taking the Yangtze River Economic Belt as the research area[J]. Economic Geography, 2023, 43(9): 139-147. ]
[31] 冯朝睿, 张楠. 云南省农产品流通业绿色发展效率测度及影响因素研究[J]. 经济问题探索, 2024(4): 124-135.
  [Feng Zhaorui, Zhang Nan. Research on the measurement and influencing factors of green development efficiency of the agricultural product circulation industry in Yunnan Province[J]. Inquiry into Economic Issues, 2024(4): 124-135. ]
[32] 吕洋, 高子茗, 李孟谕. 城市空间形态与碳排放——基于经济主体差异化行为的分析[J]. 经济问题探索, 2023(12): 124-142.
  [Lü Yang, Gao Ziming, Li Mengyu. Urban spatial form and carbon emissions: Analysis based on the differentiated behavior of economic entities[J]. Inquiry into Economic Issues, 2023(12): 124-142. ]
[33] 潘竟虎, 韩文超. 近20 a中国省会及以上城市空间形态演变[J]. 自然资源学报, 2013, 28(3): 470-480.
  [Pan Jinghu, Han Wenchao. Spatial-temporal changes of urban morphology of provincial capital cities or above in China[J]. Journal of Natural Resources, 2013, 28(3): 470-480. ]
[34] 任栋, 吴翔, 曹改改. 中国各地人类发展水平的测度与影响因素分析[J]. 中国人口科学, 2020(1): 41-52, 127.
  [Ren Dong, Wu Xiang, Cao Gaigai. Measurement of human development level in China and its influencing factors[J]. Chinese Journal of Population Science, 2020(1): 41-52, 127. ]
文章导航

/