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Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

Green credit is an important financial tool to promote the transformation of the low-carbon economy. On the basis of clarifying the theoretical mechanism of the impact of green credit on carbon emission reduction, this paper used the fixed effect stochastic frontier model containing unexpected output to measure the total factor carbon productivity of 156 cities in China from 2000 to 2019 and empirically tested the carbon emission reduction effect of green credit and its mechanism from the three dimensions of productivity, intensity, and total amount. The research found that: ① Green credit development significantly improved total factor carbon productivity and reduced carbon emission intensity, but the average impact on total carbon emissions was not significant. The above conclusions were still valid after a series of robustness tests and treatments of endogeneity problems. ② The carbon emission reduction effect of green credit was heterogeneous due to differences in regional location, resource endowment, and financial efficiency. In the central region, non-resource-based cities, and cities with higher financial efficiency, green credit had significant carbon reduction effects in both carbon productivity and carbon intensity dimensions, while green credit in the eastern region, resource-based cities, and cities with lower financial efficiency only reduced carbon intensity. ③ The stimulation of green innovation and the reduction of energy intensity were the most effective channels for green credit to reduce carbon emissions, whereas the mediating effect of the structural transformation channel was not yet significant. Green credit was more effective in promoting green innovation and generating positive spillovers in the green innovation channel. However, green credits were more effective in improving carbon emission efficiency in the energy intensity channel, but the role of supporting low-carbon technologies must be enhanced. ④ Environmental regulations had two moderating mechanisms, 'positive compensation' and 'negative offset,' for the carbon reduction effect of green credit. When the demand and supply of financial resources were low, strengthening environmental regulations would weaken the incentive effect of green credit on low-carbon economic transformation. The above conclusion not only provides a new research perspective and supplementary empirical evidence for understanding the environmental effects of green credit, but also provides a useful reference for further improving green credit policies and promoting the development of a low-carbon economy. [ABSTRACT FROM AUTHOR]

After setting the goal of peaking carbon emissions before 2030 and achieving carbon neutrality before 2060, it has become an irresistible trend for China to decouple carbon emissions from its economic growth. Since cities play a central role in reducing carbon emissions, the issues such as whether and when their carbon dioxide emissions can be decoupled from economic growth have become the focus of attention. Based on the carbon dioxide emissions of 264 prefecture-level cities in China from 2000 to 2017, this paper uses the Tapio decoupling index to measure the decoupling relationship between carbon emissions and economic growth of cities, analyzes the space–time evolution characteristics of carbon emissions and decoupling indexes by stages, and explores the relationship between carbon emissions and socio-economic development characteristics such as per capita GDP and industrial structure. The main conclusions drawn therefrom are as follows: (i) From 2000 to 2017, the city-wide carbon emissions rose from 2.484 billion tons in 2000 to 7.462 billion tons in 2017, registering a total increase of 200.40%. But the growth rate of carbon emissions within cities has been significantly reduced. (ii) As years passed by, the number of cities that achieved strong decoupling saw a significant increase, from zero in the 10th–11th Five-Year Plan period to 14 in the 12th Five-Year Plan period and the first two years of the 13th Five-Year Plan period, accounting for 5.3% of the total number of cities. (iii) There is an inverted U-shaped curve relationship between per capita carbon emissions and per capita GDP, which is consistent with the EKC curve hypothesis, but Chinese cities are still in the growth stage of the quadratic curve currently. The correlation between per capita CO2 emission and the proportion of the secondary industry was positive. The results of this study are expected to provide experience for the low-carbon development of cities in China and other developing countries, and provide references for the formulation and evaluation of policies and measures related to low-carbon economic development based on the decoupling model. [ABSTRACT FROM AUTHOR]

The paper integrates low-carbon development into the context of economic resilience, thus proposing "Low-carbon Economic Resilience" (LER). We establish an analysis framework to analyze LER based on regional interactions. The framework indicates that regions achieve LER by transferring the development burden to others, which will result in inter-regional trade inequality. An empirical analysis focused on inter-regional trade in cities of China is carried out to illustrate this framework. We calculate the degree of economic resilience and low-carbon development in cities of China. Then we trace the environmental-economic benefits embodied in virtual built-up land flow in regions. The characteristics of virtual built-up land flow exert an impact on the spatial distribution of regional economic resilience to a certain extent. The results show that, in China, many cities achieved only economic resilience or low-carbon development, while a few cities were able to achieve LER. The latter imported built-up land with high carbon emissions or low economic benefits from others, while developing "high-quality" built-up land themselves, which was reflected in the benefits per hectare of built-up land. The differences in environmental-economic benefits from inter-regional trade cause trade inequality, and major cities are the main beneficiaries, which contributes to their achievement of LER. • Low-carbon economic resilience is proposed. • Quantifying the environmental-economic benefits of inter-regional trade of cities in China. • Dividing built-up land into 4 categories to match MRIO model. • Analyzing low-carbon economic resilience based on regional interactions. [ABSTRACT FROM AUTHOR]