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Carbon lock-in has become a major obstacle to green development in all countries, and carbon unlocking (CUL) is of great significance in accelerating the process of carbon neutrality worldwide. Based on the panel data of 292 prefecture-level cities in China from 2006 to 2020, this paper constructs a PSM-DID model based on machine learning to empirically test the impact of LCCP policy on urban CUL. The regression result shows that the low carbon city pilot (LCCP) policy significantly increases the level of CUL by 1.25 % in the pilot cities, which is still valid after range of robustness tests, and the mechanism analysis shows that green innovation and green habits are important ways for the policy to affect CUL. Based on the generalized random forest (GRF) algorithm, we further find that the policy can increase the CUL level by 0.6 %, and the average treatment effect (ATE) of the sample is concentrated between 0.004 and 0.006, which exhibits obvious heterogeneity. This paper chooses population quality, openness level and industrial structure as heterogeneous factors, which are finally found to have a U-shaped or inverted U-shaped relationship with ATE. This study provides useful insights for China and other countries to break the carbon lock-in and realize green development. • Low-carbon city pilot policy can effectively promote urban carbon unlocking. • Causal forest model is used for causal inference based on generalized random forests algorithm. • The propensity score is calculated by machine learning. • Generalized random forest is used for heterogeneity analysis. • Low-carbon city pilot policy transmits policy effects through green innovation and green habits. [ABSTRACT FROM AUTHOR]

[Display omitted] • Incentive initiatives on energy-efficient renovation of existing buildings in China were analyzed. • The dynamic evolution of incentive initiatives was analyzed from different perspectives. • A critical analysis of representative initiatives in two batches of pilot cities was conducted. • Implementation barriers and limitations on energy-efficient renovation of existing buildings were summarized. • Recommendations and pathways of promoting related incentive initiatives were proposed. Under China's national strategy of carbon neutrality by 2060, it is urgently necessary and challenging for the governments to proactively explore policy tools to facilitate energy-efficient renovation of existing buildings. Currently, a considerable number of studies have been conducted on building energy-efficient renovation and its derivative topics, however, a comprehensive overview on incentive initiatives related to existing renovation practices in China is still scarce, such as a lack of critical correlation analysis between national and local initiatives, a lack of the synthesis and critique towards the latest policies and related achievements, and inadequate generalization of the diverse and multi-layered barriers and challenges in building energy-efficient renovation practices. To address these issues, this paper adopts a diversified policy segmentation approach to deeply analyze the dynamic evolution of the incentive initiatives from both national and local level perspectives, as well as to establish the related network of policy linkages between national to local, and between different localities. In addition, this paper presents a critical analysis on representative initiatives in two batches of pilot cities, and proposes good practices and valuable experiences for building energy-efficient renovation. Finally, this paper further summarizes and discusses the barriers to building energy-efficient renovation from four perspectives: governments, householders, enterprises and research institutions, and proposes a series of targeted and feasible pathways and strategies. This study can provide theoretical guidance and targeted recommendations for the formulation of policies, standards and regulations for building energy-efficient renovation in China. [ABSTRACT FROM AUTHOR]

The comprehensive cohesion of the digital economy, structural deviation adjustment, and green development is a crucial step towards promoting high-quality economic growth and realizing carbon peak and carbon neutrality. This paper probes the impact of intra- and inter-regional digital economy on carbon emissions, considering the mediating effect of structural deviation, utilizing panel data from 267 prefecture-level cities in China spanning the years 2011–2019. The findings reveal the following key insights. First, the connection between the digital economy and carbon emissions within cities follows an inverted "U" shape. In the early stages, the digital economy leads to an average increase in carbon emissions of 0.069%. However, in the later stages, the digitized economy markedly decrease emissions. Second, both the digital economy and carbon emissions exhibit spatial spillover effects. Within the region, DE has a significant nonlinear spillover effect on CO 2 emissions in the neighboring regions, with the spatial decay boundary of this effect extending up to 380 km. Third, analysis of the impact mechanism reveals that the digital economy mitigates local and neighboring carbon dioxide emissions by adjusting structural deviation. Heterogeneity analysis indicates that the digital economy is more likely to have a carbon emission reduction effect in cities that are not involved in the industrial transfer and those that do not belong to the old industrial base. These findings provide a rationale and policy reference for China to harness the opportunities presented by digital economy development and to achieve the "dual-carbon" goal. [ABSTRACT FROM AUTHOR]