How the Pilot Low-Carbon City Policy Promotes Urban Green Innovation: Based on Temporal-Spatial Dual Perspectives

Low-carbon pilot policy and development path in urban agglomerations of China: Mechanism analysis and stage identification

Urban agglomeration (UA) plays as the main carrier of economy and society in China, concentrating the human activities, energy consumptions, and subsequent carbon emissions in space. The policy-induced mechanism of carbon emissions in the units of UA is currently less explored, and diversities of low-carbon development path of UAs remain unknown. Thus, this study analyzes the carbon emissions of 19 UAs in China from 2006 to 2019, focuses on the low-carbon city pilot policy (LCPP), constructs an SDM-DID model to investigate the impacts of LCPP on carbon emissions regionally, and delineates the stages of low-carbon development in UAs based on the theory of Environmental Kuznets Curve. The results show that carbon emissions of China's UAs are spatially distributed as higher in the east but lower in the west, and increase faster in the central. The effect of LCPP on carbon emissions is significant but inhibitory in the central and northeastern UAs, while it becomes insignificant in the eastern ones. Finally, the low-carbon development paths of all UAs are divided into Type I, strong Type I, Type II, Type III, and Type IV stage. The eastern UAs are all at Type I stage because they are more sensitive and ahead in terms of low-carbon development strategies. The findings of this study can provide references for city groups to formulate carbon reduction policies and decouple the relations between economic development and carbon emissions.

Spatial-temporal pattern and spatial convergence of carbon emission intensity of rural energy consumption in China

Based on the panel data of 30 provinces (municipalities and autonomous regions) in China from 2005 to 2019, this paper uses Gini coefficient decomposition and kernel density estimation to investigate the regional differences and dynamic evolution trend of rural energy carbon emission intensity in China. Then, the convergence model is used to analyze the convergence characteristics and influencing factors of carbon emission intensity. The study found the following: (1) During the observation period, the carbon emissions of coal energy and oil energy were much higher than those of gas energy. The carbon emissions of rural energy consumption experienced three stages of development, and the carbon emission intensity showed a downward trend as a whole. The spatial distribution pattern of total carbon emissions present an "adder" distribution, and the spatial agglomeration phenomenon gradually strengthens with the passage of time. (2) The Gini coefficient of China's rural energy consumption carbon emission intensity shows a trend of "Inverted N-shaped." The Gini coefficient of carbon emission intensity in the eastern and northeastern regions shows an increasing trend, while the Gini coefficient of carbon emission intensity in the western and central regions shows a downward trend. The super variable density is the main source of carbon emission intensity difference. The peak value of the main peak of the nuclear density curve of the carbon emission intensity increased significantly, the bimodal form evolved into a single peak form, and the density center moved to the left. (3) The carbon emission intensity of rural energy consumption in the whole, central, and western regions of China has the characteristic of σ convergence, while the carbon emission intensity in the eastern and northeastern regions does not have the characteristic of σ convergence. There is a significant spatial positive correlation in the carbon emission intensity, there is also a significant β convergence characteristic, the speed of conditional β convergence is significantly higher than that of absolute β convergence, and the spatial interaction will further improve the convergence speed. Industrial structure, industrial agglomeration, and energy efficiency will increase the convergence speed. In terms of sub-regions, the conditional convergence rate of carbon emission intensity in the four regions shows a decreasing trend in the northeast, central, eastern, and western regions.

Carbon emissions trading scheme and regional total factor carbon productivity: based on temporal-spatial dual perspectives

The carbon emissions trading scheme (CETS) in China is an important market-based environmental policy mechanism for decreasing carbon emissions. This paper calculates the total factor carbon productivity (TFCP) based on data from 275 cities in China from 2007 to 2020 using the DEA method and investigates the impact of the CETS on regional TFCP using the differences-in-differences (DID) method, all against the backdrop of carbon peaking and carbon neutrality. The research findings reveal that CETS has consistently improved TFCP in pilot cities, and this conclusion has held up following a number of robustness tests. Temporal heterogeneity experiments demonstrate that as implementation time increases, the enhancing effect takes on an inverted "U-shaped" structure with a 7-year effective lifetime. Spatial heterogeneity studies reveal that as one moves away from the pilot cities, the policy effect on surrounding cities' TFCP is inhibited, followed by facilitation. CETS policies can influence regional TFCP through the effects of green innovation and industry upgrading, according to mediation mechanism testing. We present policy recommendations based on the research findings for meeting the "dual" carbon goals and strengthening the carbon trading mechanism.

Can rural e-commerce contribute to carbon reduction? A quasi-natural experiment based on China's e-commerce demonstration counties

As information and communication technologies gain prominence in rural areas, rural e-commerce has emerged as a crucial mechanism for fostering agricultural and rural development. While the economic impact of rural e-commerce is widely studied, its effects on carbon emissions remain underexplored. Utilizing a multi-period DID model and Chinese county-level panel data from 2011 to 2017, this paper examines the impact of rural e-commerce on carbon emission reduction, employing the "comprehensive demonstration of e-commerce into villages" policy introduced by the Chinese government in 2014 as a quasi-natural experiment. Our findings show that e-commerce demonstration counties experienced a 10.6% reduction in carbon emissions compared to the control group, indicating a significant emission reduction effect. Further analysis reveals that rural e-commerce drives carbon reduction through decreased fertilizer usage, altered cropping structures, and enhanced transportation efficiency. Notably, rural e-commerce's emission reduction effect is more pronounced in major grain-producing regions and areas with higher digitalization levels. This study has crucial theoretical and practical implications for achieving carbon emission reduction and sequestration in agriculture and advancing green agricultural development.

Towards sustainable development: what carbon trading pilot policy has been done for mitigating carbon emissions and air pollution?

This study examines the impact of carbon trading pilot policy (CTPP) on carbon emissions (CO2) and air pollution (Ap) using the difference in differences method (DID) utilizing panel data from 30 Chinese areas spanning from 2008 to 2020. The results indicate that CTPP implementation can effectively decrease CO2 and Ap. CTPP can reduce CO2 and Ap through positive incentive effects that promote industrial structure upgrading and drive technological progress. Moreover, CTPP exhibits significant regional variation, with CTPP significantly reducing CO2 in both the eastern and central and western regions. CTPP do not show an effective reduction in Ap in eastern region, while effectively reduce Ap in central and western regions.

The effect of the digital economy on carbon emissions: an empirical study in China

Under the new development model, the digital economy has become a new engine to promote the green development of the economy and achieve the goal of "double carbon." Based on panel data from 30 Chinese provinces and cities from 2011 to 2021, the impact of the digital economy on carbon emissions was empirically studied by constructing a panel model and a mediation model. The results show that firstly, the effect of the digital economy on carbon emissions is a non-linear inverted "U" shaped relationship, and this conclusion still holds after a series of robustness tests; secondly, the results of the benchmark regression show that economic agglomeration is an essential mechanism through which the digital economy affects carbon emissions and that the digital economy can indirectly suppress carbon emissions through economic agglomeration. Finally, the results of the heterogeneity analysis show that the impact of the digital economy on carbon emissions varies according to the level of regional development, and its effect on carbon emissions is mainly in the eastern region, while its impact on the central and western regions is weaker, indicating that the impact effect is primarily in developed regions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the development strategy of the digital economy according to local conditions to promote a more significant carbon emission reduction effect of the digital economy.