Quantifying the trends and affecting factors of CO2 emissions under different urban development patterns: An econometric study on the Yangtze river economic belt in China

Abstract

Environmental issues are rarely investigated within the framework of different urban development patterns, especially concerning CO2 emissions. This research works to reveal the trends and determining factors of urban CO2 emissions under different urban development patterns. Taking the cities in the Yangtze River Economic Belt (YREB) as an example, this study develops an identification system in light of the dynamics of urban population and population density to categorize urban development patterns as growth, potential shrinkage, smart shrinkage, and continuous shrinkage. Then, the Theil-sen medium analysis and spatial econometric modeling are applied to shed light on the trend and influencing factors of CO2 emissions, respectively. The findings indicate that urban growth and potential shrinkage are the main development patterns in the YREB, and the percentage of growing cities and potentially shrinking cities is more than 77 % across the different geographic areas of the YREB. CO2 emissions are remarkably heterogeneous under different urban development patterns. Over 90 % of cities show a growth trend or fluctuation in per capita CO2 emissions under the four development patterns during 2010∼2019. Only a few growing and potentially shrinking cities show a decreasing trend in per capita carbon emissions, suggesting a severe peak carbon challenge in the YREB. CO2 emissions in growing and shrinking cities are significantly influenced by their neighboring cities. Factors affecting CO2 emissions are different in shrinking and growing cities, and spatial spillover effects enhance the role of these factors. Compared with growing cities, improving population concentration, developing appropriate tertiary industries, strictly controlling land expansion, and developing green areas can pave the way for carbon emission reduction in shrinking cities. This study can support designing efficient carbon emission reduction measures for various cities.