Urban Residential CO2 from Spatial and Non-Spatial Perspectives: Regional Difference between Northern and Southern China

Abstract

Urban residential carbon dioxide (CO2) emissions have increased sharply along with the rapid urbanization process. Few studies have considered the different effects of influencing factors between Northern and Southern China, and the analysis of CO2 per unit area from the spatial perspective is also rarely involved. Using the spatial Durbin model (SDM), this study aimed at revealing the influencing factors (including income, inequality, population density, urban morphology, etc.) on CO2 per capita and CO2 per unit area during 2001–2018 between Northern and Southern China. The results showed that the Northern cities had higher carbon emissions and a faster growth rate, and the high-high clusters were also mainly located in the Northern cities. The Gini coefficient was correlated adversely with CO2, while income imposed a positive effect on carbon emissions. The negative coefficients of the quadratic term of the GDP per capita demonstrated that the residential carbon emissions have the potential to decrease when the income increases to a certain level. The indirect effects of income and the Gini showed that spatial spillover effects exist. Urban population density and the ratio of residential area to built-up area had an opposite effect on CO2 per capita and CO2 per unit area, and they have a bigger impact on the CO2 per unit area. This study revealed the different roles of various factors in reducing CO2 per unit area from the spatial perspective and CO2 per capita from the non-spatial perspective between the Northern and Southern regions, which could help policymakers to design targeted mitigation measures in the residential sector in China, providing references for developing countries to jointly reduce carbon emissions to promote the mitigation of global climate change.