An evaluation of spatial–temporal dynamics of city size distribution & CO₂ emission in China from nighttime light data: a Pathway to sustainable urban planning

Abstract

Understanding the relationship between urban growth and CO2 emissions is essential for sustainable urban and environmental planning in China. Even though some studies have been conducted in this regard, there is a lack of comprehensive studies that integrate socioeconomic and nighttime light (NL) data on both spatial and temporal scales. Therefore, using NL data as a proxy for urban growth, this study offers a novel approach to assess city size distribution (CD) and CO₂ emission dynamics from 2000 to 2020 at the provincial and prefecture levels. The present study was conducted in three phases: (1) assessing the association between urban growth and socioeconomic characteristics; (2) measuring CD dynamics using corrected NL data; and (3) modeling CO₂ emission dynamics through panel data analysis. While the Ordinary Least Squares (OLS) method examined the relationship between socioeconomic characteristics and urban growth, the CD dynamics were measured using Catteow’s formula. A panel unit root test, panel co-integration test, and panel regression analyses were performed to explore the relationship between urban growth and CO₂ emissions. Results revealed that maximum NL data have stronger correlations with population, GDP, and EPC at the provincial level than at the prefecture level, with an average R2 range from 0.6219 to 0.8985. The analysis of CD dynamics revealed an increase in urban disparity, particularly among larger cities, with the q value rising from 0.7920 to 0.8268. CO₂ emissions expanded by 250.76% from 2000 to 2020, with the highest growth seen in coastal megacities. Panel unit root and co-integration tests confirmed a long-term relationship between urban growth and CO₂ emissions at both scales. Panel regression analysis showed a positive and significant impact of urban growth on CO₂ emissions at the national level and across all regions and provinces. These findings highlight the importance of sustainable urban planning strategies that incorporate socioeconomic characteristics with spatial and temporal considerations to reduce CO₂ emissions in China. However, further research is necessary to explore multidimensional strategies for balancing urban expansion and CO₂ emissions.

Keywords

City size / CO₂ emission / DMSP-OLS / Nighttime light / Panel data analysis / Zipf’s law

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