基于生态效率框架的城市可持续发展的时空格局、效应和互动驱动机制:来自中国地级城市的证据

IF 5.4 Q1 ENVIRONMENTAL SCIENCES Environmental and Sustainability Indicators Pub Date : 2024-04-18 DOI:10.1016/j.indic.2024.100391
Kaisen Nong , Jiaan Lin , Dongqi Sun
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引用次数: 0

摘要

生态效率是评估和推进区域可持续发展的重要工具。本研究提出了一个值得广泛应用的城市生态效率(UEE)框架。研究采用基于超级松弛的测算模型,计算了中国 284 个地级市 2005 年至 2022 年的城市生态效率。研究采用标准偏差椭圆来说明中国 UEE 的时空格局,并使用非参数核密度估计、变异系数以及全局和局部 Moran's I 检验其影响。此外,Malmquist 指数、双向固定效应(TWFE)模型和面板向量自回归(PVAR)模型揭示了中国 UEE 的动态变化和互动驱动机制。结果表明(1) 中国的 UEE 呈现出一致的 "核心-外围 "模式,从区域、规模和行政角度看,都表现出明显的层次性影响。由于 COVID-19 的影响,UEE 时空变化的复杂性有所增加。(2) 中国城市的 UEE 显示出显著的 "俱乐部 "效应,高-高和低-低聚合的效率临界值为 0.8。(3) 只有 25% 的中国城市达到最佳 UEE 水平。值得注意的是,西部城市对全国 UEE 增长的贡献最大,而中部城市的贡献最小。城市能效水平增长的下降趋势凸显了中国城市发展模式转变的迫切性。(4) 中国的人均可支配收入得益于一种有弹性的自我强化机制,城市发展和经济增长极大地促进了人均可支配收入的增长。尽管政府干预的负面影响并不显著,但密集型产业结构对 UEE 的抑制作用转化为促进作用,尤其是在 COVID-19 之后。
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Spatiotemporal patterns, effects, and the interactive driving mechanisms of urban sustainability based on the eco-efficiency framework: Evidence from Chinese prefecture-level cities

Eco-efficiency is a vital tool for evaluating and advancing regional sustainable development. This study presents an urban eco-efficiency (UEE) framework that deserves widespread application. By using the Super Slacks-Based Measure model, the research calculates the UEE of 284 prefecture-level cities in China from 2005 to 2022. The study employs the Standard Deviational Ellipse to illustrate the spatiotemporal pattern of UEE in China and examines its effects using non-parametric kernel density estimation, the coefficient of variation, and both global and local Moran's I. The integration of UEE with urban development patterns, which is not immediately clear, is achieved through the entropy-based TOPSIS model. Additionally, the Malmquist index, the Two-way Fixed Effects (TWFE) model, and the Panel Vector Autoregression (PVAR) model reveal the dynamic changes and interactive driving mechanisms of UEE in China. The results indicate that: (1) UEE in China displays a consistent “core-periphery” pattern, exhibiting a notable hierarchical impact from regional, scale, and administrative perspectives. The complexity of UEE's spatiotemporal variations has increased due to the impact of COVID-19. (2) The UEE of Chinese cities shows a significant ‘club’ effect, with efficiency thresholds for high-high and low-low aggregations set at 0.8. (3) Only 25% of Chinese cities have achieved optimal UEE levels. Notably, cities in the west contribute most to national UEE growth, while midland cities contribute the least. The decreasing trend in UEE growth underscores the urgent need for a shift in China's urban development model. (4) UEE in China benefits from a resilient self-reinforcing mechanism, with urban development and economic growth significantly aiding UEE growth. Despite a non-significant negative impact from government intervention, the inhibitory effect of an intensive industrial structure on UEE turns into a promotional effect, especially following COVID-19.

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来源期刊
Environmental and Sustainability Indicators
Environmental and Sustainability Indicators Environmental Science-Environmental Science (miscellaneous)
CiteScore
7.80
自引率
2.30%
发文量
49
审稿时长
57 days
期刊最新文献
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