Analyzing the impact of urbanization quality on CO2 emissions: What can geographically weighted regression tell us?

Abstract China is facing increasingly severe challenges in its quest to achieve urbanization and mitigate CO 2 emissions. The existing studies have usually introduced a single indicator to describe urbanization and have ignored the complexity and multi-dimensionality of urbanization. This study establishes an evaluation system of urbanization quality to estimate the urbanization development level. The geographically weighted regression (GWR) model is employed to examine the impact of the urbanization quality on CO 2 emissions and reveals the spatial differences of 30 provinces in 2000, 2005, 2010, and 2015. The results show that there are significant temporal and spatial differences in the effects of the urbanization quality on CO 2 emissions between provinces. Improvements in the urbanization quality have contributed to cutting CO 2 emissions in most provinces. The impact of the urbanization quality on CO 2 emissions in the central region and western region is greater than that in the eastern region. The energy intensity has the largest positive impact on CO 2 emissions, which indicates that technical progress can effectively reduce CO 2 emissions. The industrial structure has a positive impact on CO 2 emissions in 2000 and 2015, whereas it has a negative impact on the CO 2 emissions of some provinces in 2005 and 2010. This paper provides valuable findings and conclusions of the relationship between urbanization quality and CO 2 emissions. Differentiated policy implications are proposed according to geographical differences. Graphical abstract fx1 Highlights • This study establishes an evaluation system of urbanization quality (UQ). • This study examines the spatial effect of urbanization quality on CO 2 emissions. • There are obvious differences in the effect of UQ on emissions between provinces. • Energy intensity has the largest positive impact on CO 2 emissions. • Industrial structure has a positive impact on CO 2 emissions in 2000 and 2015. [ABSTRACT FROM AUTHOR]