Urban development sustainability, industrial structure adjustment, and land use efficiency in China

Wang, Zhaoya; Fu, Haiyue; Liu, Hongguang; Liao, Chuan

doi:10.1016/j.scs.2022.104338

Cited by 59 publications

(17 citation statements)

References 44 publications

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“…It is known that a series of factors can influence CEI. Referring to the existing research and combining the urban development characteristics of China [57][58][59][60], this paper selected six indicators-economic scale, industrial structure, population urbanization, residents' income, technological progress, and opening degree-as the detection factors of carbon emissions of the UAs.…”

Section: Influencing Factors Of Cei In China's Uasmentioning

confidence: 99%

Spatial Differences and Influencing Factors of Carbon Emission Intensity in China’s Urban Agglomerations toward the Carbon Neutrality Target

Wang,

Hui,

Liu

2024

Atmosphere

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It is of great scientific value to study the spatial differences and influencing factors of carbon emission intensity (CEI) in urban agglomerations (UAs), and it also has reference significance for China in formulating energy-saving and emission-reduction policies to achieve the target of carbon neutrality. Taking 165 prefecture-level cities in 19 UAs in China from 2007 to 2019 as the research object, this study investigated the spatial differences of CEI in UAs using exploratory spatial data analysis and explored the influencing factors of CEI via Geodetector. The results showed the following: (1) The CEI of the UAs showed a downward trend. (2) The CEI of the UAs has typical spatial agglomeration characteristics, where the North comprises mainly high-high and low-high types, whereas the South is primarily high-low and low-low types. (3) The influencing factors of CEI have undergone a transformation from industrial structure to population urbanization.

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Section: Influencing Factors Of Cei In China's Uasmentioning

confidence: 99%

Spatial Differences and Influencing Factors of Carbon Emission Intensity in China’s Urban Agglomerations toward the Carbon Neutrality Target

Wang,

Hui,

Liu

2024

Atmosphere

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“…The development of ecological efficiency promotes the optimization of the material space and time process of urbanization, thus promoting the benign development of new urbanization [ 35 ], and the result of urbanization also beneficially promotes the improvement of ecological efficiency, so there is a coupling between the two. New urbanization corresponds to the urban space [ 36 ]. In contrast, ecological efficiency corresponds to the county space, and these two aspects show a correlation of "point and surface, source and flow" in urban and county areas.…”

Section: Theoretical Analysismentioning

confidence: 99%

Can new urbanization and ecological environment achieve synergistic development? Empirical evidence from 63 counties in Zhejiang, China

Ma,

Xu,

Hong

et al. 2023

PLoS ONE

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As China’s urbanization accelerates, ecological environmental issues have become increasingly prominent, and how to achieve the synergistic development of urbanization and ecological environment is worth exploring. The paper uses the Super-SBM model and the improved entropy method to calculate the ecological efficiency and the new urbanization in 63 counties in Zhejiang Province from 2000 to 2019. Furthermore, the coupling coordination degree between new urbanization and ecological efficiency is discussed with the coupling degree model, Markov chain, and spatial correlation methods, and its influencing factors are explored by the geographic detector. The results show that: (1) The development trends of new urbanization and ecological efficiency in Zhejiang Province counties both present a "U" shape. Their inflection points appeared in 2005 and 2006, respectively. The gap between counties is gradually narrowing. (2) The coupling coordination degree between new urbanization and ecological efficiency in Zhejiang Province counties also develops in a "U" shape with the minimum value appearing in 2006. Its temporal evolution is dominated by advancement towards a higher level and maintenance of the original type, with most countries advancing from General Disorder to Preliminary Coordination. There is a good positive correlation in the spatial distribution, showing significant High-High and Low-Low agglomeration. (3) In detecting the driving factors, the explanatory power of economic development, natural conditions and social conditions diminishes sequentially. The interaction groups mostly are nonlinear enhancements, and the rest are all two-factor enhancements. Social factors are the main interaction objects. (4) The empirical analysis verified the efficacy of the "Two Mountains" theory and the importance of government investment in the regional coordinated development.

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“…This relationship, however, isn't merely linear but intricately layered [ [6] , [7] , [8] ]. Various determinants, such as economic trajectories, population flux, and industrial shifts, influence urban growth [ [9] , [10] , [11] , [12] ]. Interestingly, these determinants also play a pivotal role in shaping urban carbon footprints [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Dynamics of urban expansion and form changes impacting carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area counties

Ming,

Wang,

Chen

et al. 2024

Heliyon

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Urban development sustainability, industrial structure adjustment, and land use efficiency in China

Cited by 59 publications

References 44 publications

Spatial Differences and Influencing Factors of Carbon Emission Intensity in China’s Urban Agglomerations toward the Carbon Neutrality Target

Spatial Differences and Influencing Factors of Carbon Emission Intensity in China’s Urban Agglomerations toward the Carbon Neutrality Target

Can new urbanization and ecological environment achieve synergistic development? Empirical evidence from 63 counties in Zhejiang, China

Dynamics of urban expansion and form changes impacting carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area counties

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