| 多维城镇化与碳排放的非线性关系及其驱动机制 |
| 摘要点击 671 全文点击 81 投稿时间：2023-11-07 修订日期：2024-12-23 |
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| 中文关键词 多维城镇化 碳排放 非线性关系 驱动机制 环渤海地区 |
| 英文关键词 multidimensional urbanization carbon emissions nonlinear relationship driving mechanism Bohai Rim |
| DOI 10.13227/j.hjkx.20250619 |
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| 中文摘要 |
| 厘清多维城镇化与碳排放的内在关系及驱动机制是推动新型城镇化和“碳中和”协同发展的科学基础.基于2000~2021年环渤海地区面板统计数据和遥感影像，采用空间自相关模型探查CO2排放量的时空演变规律，并运用系统动态面板回归模型研判多维城镇化与CO2排放量之间的非线性关系与驱动机制. 结果表明： ①2000~2021年，环渤海地区CO2排放量总体呈上升趋势，空间集聚性不强，但2016年后，CO2排放量增速放缓，空间关联特征呈现增强趋势. ②环渤海地区城镇化子系统在不同发展阶段对CO2排放量的影响差异显著.经济城镇化和CO2排放量呈显著的倒“N”型曲线关系，符合环境库兹涅茨曲线（EKC）关系；人口城镇化与CO2排放量的关系仅表现为倒“U”曲线的左侧部分，与碳排放的拐点尚有一定距离；土地城镇化对CO2排放量的影响与经济城镇化相似，呈明显的倒“N”型关系. ③人口规模、产业结构、外商投资、环境保护和居民消费水平对碳排放具有促进或抑制作用.④环渤海地区碳排放的时空异质性特征是城镇化各子系统与经济、社会和政策等相关要素发生相互作用、反馈、整合、重组等复杂多维动态过程的结果. |
| 英文摘要 |
| Understanding the relationships and associated mechanisms between multidimensional urbanization and carbon emissions is essential for the coordinated development of strategies for high-quality urbanization and carbon reduction. Using panel statistical data and remote sensing imagery from cities in the Bohai Rim from 2000 to 2021， in this study， we employed spatial autocorrelation models to investigate the spatiotemporal evolution of CO2 emissions and applied a system dynamic panel regression model to assess the nonlinear relationship and driving mechanisms between multidimensional urbanization and CO2 emissions. From 2000 to 2021， CO2 emissions in the Bohai Rim exhibited an upward trend， with a deceleration in growth after 2016. The CO2 emission intensity generally declined， with fluctuations post 2019 and a transition from lower to higher emission levels among cities. Spatial agglomeration was not prominent during the study period. However， after 2016， there was a noticeable trend toward stronger correlational characteristics. Significant differences were observed in the nonlinear relationships between the various stages of urbanization subsystems in the Bohai Rim and CO2 emissions. Economic urbanization showed an inverted "N" curve relationship with CO2 emissions， indicative of an environmental kuznets curve （EKC） effect. When per capita GDP exceeded 89 278.41 Yuan， economic urbanization exhibited an inhibitory effect on CO2 emissions， suggesting the importance of enhancing the comprehensive urban quality and shifting development strategies for managing emissions. The relationship between population urbanization and CO2 emissions was confined to the left side of the inverted “U” curve， indicating that the carbon emissions inflection point had not been reached. The impact of land urbanization on CO2 emissions mirrored that of economic urbanization， displaying a distinct inverted “N” pattern. Population size， industrial structure， foreign investment， and consumer spending levels promoted or inhibited carbon emissions. The nonlinear relationships between urbanization subsystems and carbon emissions corresponded to the theoretical predictions of EKC. The spatiotemporal heterogeneity of carbon emissions in the Bohai Rim was influenced by multidimensional and iterative interactions， feedback， integration， and reorganization among urbanization subsystems and the associated economic， social， political， ecological， and cultural factors. The Bohai Rim should focus on the coordinated advancement of high-quality urbanization and carbon reduction targets， adjust the interactions and configurations between subsystems according to local conditions， and promote precise policy implementation to harmoniously integrate economic and social development with ecological and environmental protection. |
