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China, as the world's largest carbon dioxide emitter, is bound to assume the important responsibility of energy conservation and emission reduction. To this end, each city, led by representative municipalities, must enhance efforts in carbon emission reduction to jointly realize China's low-carbon transition. Taking four representative municipalities, namely, Beijing, Tianjin, Shanghai, and Chongqing as the case cities, this paper establishes a decomposition analysis for the driving factors of carbon emissions by applying the LMDI method covering data from 2007 to 2017. Kaya identity is used to decompose the effects into eight driving factors: GDP effect, industrial structure effect, energy intensity effect, overall energy structure effect, population effect, urbanization effect, per capita energy consumption effect, urban and rural energy structure effect. The results show that at the municipality level, the driving factors that contribute to carbon emissions are the GDP growth effect and the population effect, with the former still being the most important factor in the municipalities with faster economic growth; and industrial structure effect is the most important factor that inhibits carbon emissions, followed by energy structure effect. This paper considers the driving factors of both the production side and the residential consumption side from the city level. The research reveals the main driving factors that effect the carbon emissions of megacities in developing countries, and highlights the leading role of megacities in terms of carbon emission reduction in China and even the world. The paper thereby puts forward policy implications for China's economic policies. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

Exploring the relationship between economic development and carbon emissions is a hot issue of concern to academia. Taking Chinese cities as the research object, this study constructed an allometric growth model of economic scale and carbon emissions to analyze the spatial–temporal evolution of their allometric growth from 2000 to 2017. Additionally, the geographical detector model was used to reveal the driving mechanism of allometric growth. The findings were as follows. (1) The spatial–temporal patterns of economic scale and carbon emissions were dominated by hot spots. Additionally, their size distribution was in an equilibrium stage. (2) The gap between the economic growth rate of Chinese cities and the growth rate of carbon emissions grew, reflecting the remarkable achievements in carbon emission reduction in Chinese cities as a whole. The scaling exponent declined from east to the west during 2000–2008, but showed the opposite trend during 2009–2017. The proportion of cities with negative allometric growth in the sample cities increased from 76.49 to 97.86%. (3) The influence of city investment intensity, energy utilization efficiency, technological development level, social consumption level, fiscal investment level and economic development level on allometric growth gradually decreases. These factors were also the main factors affecting the spatial–temporal heterogeneity of allometric growth. (4) The impact of various factors had a synergetic enhancement effect. These factors can be classified as economic factors, environmental factors and a combination of them. Under the nonlinear coupling of multiple factors, a spatially differentiated pattern of allometric growth was formed. [ABSTRACT FROM AUTHOR]

This study aims to develop a framework linking New-Type Urbanization (NTU) and carbon emissions, considering both direct and spillover effects. Firstly, the paper constructs a multi-dimensional index to measure NTU and documents the spatial patterns of NTU levels in China, showing remarkable inequality between the eastern and western regions. Secondly, the study evaluates the effectiveness of pilot policies aimed at achieving Smart City and NTU goals. Using the Difference-in-Difference model based on panel data collected from 108 cities in the Yangtze River Economic Belt from 2006 to 2019, the study provides empirical evidence that these policies can significantly reduce carbon emissions in terms of production and consumption. Moreover, the study finds that the policies have significant spatial spillover effects on neighboring cities based on the Spatial Panel Durbin Model. The findings suggest that such policies can effectively reduce carbon emissions in areas with significant human activity and have important policy implications for achieving sustainable development in China. • The research assesses how New-Type Urbanization affects emission reduction. • Policy pilots for Smart City & New-type Urbanization reduced environmental emissions. • The impact of emission reduction is spatially heterogeneous. • New-Type Urbanization can increase environmental emissions in nearby cities. [ABSTRACT FROM AUTHOR]

Technological progress is considered an effective means to reduce carbon emissions, and an innovative city pilot scheme may contribute to this target. However, the impact of innovation city construction on carbon emissions has not been systematically studied. Based on panel data of 285 cities at prefecture level and above in China from 2003 to 2017, this study employs the difference-in-differences approach to evaluate the impact of innovative city pilots on CO2 emissions. The results show that CO2 emissions in pilot cities are 17.1% lower than that in non-pilot cities, indicating that the scheme contributes significantly to carbon emission reduction. Meanwhile, the spatiotemporal characteristics suggest that the local effect increases over time and the spillover effect is significant within 150–250 km. Additionally, a heterogeneity analysis shows that the impact of the pilot scheme on CO2 emissions is mainly reflected in the central region and prefecture-level cities. Lastly, mechanism analysis indicates that the pilot policy reduces CO2 emissions by promoting technological innovation, industrial upgrading, and environmental governance, of which technological innovation plays the most important mediating role. [ABSTRACT FROM AUTHOR]