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Green energy efficiency (GEE) is pivotal for sustainable economic growth, particularly in the context of China's ambitious environmental goals. This study assesses the impact of Green Financial Reform and Innovation Pilot Zones on GEE from 2005 to 2020, using the SBM-GML method and a Double Difference Model (DID). Findings indicate a significant improvement in GEE within these zones, driven by advancements in green innovation and environmental regulation. At the micro level, firms in pilot zones show enhanced Environmental, Social, and Governance (ESG) performance and experience fewer financial constraints. The effectiveness of green finance policies is more pronounced in resource-rich and financially efficient regions, suggesting that these initiatives can significantly contribute to sustainable development. Based on empirical evidence, we recommend expanding pilot zones, promoting green technological innovation, and developing tailored green finance policies to address regional ecological sensitivities. [ABSTRACT FROM AUTHOR]

This paper chooses 98 mining cities in China from 2007 to 2021 as research samples. It investigates the policy practice of green development in mining cities according to the point of view of policy combination. We establish a super-efficiency model considering undesirable output to measure the green development level of mining cities and further construct a dynamic panel model based on the Gaussian mixture model (GMM) to test the transmission mechanism and heterogeneous effect of different types of environmental regulation to promote the green development of mining cities. The findings demonstrate that environmental regulations about command control, market incentives, and public participation can all help mining cities develop more sustainably. Additionally, there is a nonlinear relationship of an inverted "U" shape between the degree of green development in mining cities and environmental regulations related to command control. Combining policies can encourage the green development of mining cities, but there are crowding-out and substitution effects when environmental regulations are combined with market forces. Environmental regulation promotes urban green development by improving the energy consumption structure of mining cities. In this process, the level of digital development positively regulates the impact of environmental regulation on urban green development. Therefore, the government should choose environmental regulation tools and combinations according to local needs to achieve a multi-pronged effect of energy structure improvement and urban green development and use digital technology to support the green development of mining cities. • Command-controlled, market-motivated, and public-participating environmental regulations can significantly promote urban green development by promoting the improvement of energy structure. • There is an inverted' U' -shaped nonlinear relationship between the intensity of command and control environmental regulation and the green level of mining cities. • The level of digitization can positively regulate the relationship between environmental regulation and urban green development. • The combination of environmental regulations have a significant positive impact on urban green development. • The combination of environmental regulations has heterogeneity in urban green development due to factors such as regional resource endowment. [ABSTRACT FROM AUTHOR]

The environment constraints have become more restrictive over time, because the transformation of energy consumption structure (ECS) is the key path to achieve the commitment of net-zero emission. However, the adjustment of ECS involves the influence of many factors, including economic factors, energy factors and social factors. Not to mention how ECS -driving factors under tougher environmental regulation may behave throughout long time period remains explored. According to the background, the periodic driving factors of industrial ECS in China based on the periodic effect of environmental regulation on ECS are discussed. In this paper, industries of China are divided into four sectors from 1998 to 2017, and a multi-layer LMDI decomposition model is constructed to decompose ECS of the four sectors in stages. Since the industrial and commercial sector provides the largest contribution rate, the LMDI model based on PDA production theory method is applied to decompose industrial and commercial ECS , aiming to deeply explore the main driving factors of ECS in subindustries, and formulate scientific energy and environmental policies. The results show that from the perspective of the whole industry, the per capita pollution control investment has the most significant negative contribution, and the economic activity effect provides a great positive contribution to the ECS. In terms of subindustries, the main negative drivers are potential energy intensity and GDP technology change. The comprehensive decomposition framework. [Display omitted] • The drivers of ECS in four sectors are identified. • An integrated decomposition measurement combined LMDI with PDA is constructed. • EP is major inhibiting factor of ECS optimizing in four sectors. • PE and GT are major inhibiting factors of ECS optimizing in subsectors. • Some policy recommendations to optimize energy consumption structure are purposed. [ABSTRACT FROM AUTHOR]

Optimizing energy consumption structure (ECS) is the key to reduce pollution emissions and develop a green economy. Understanding the effect of each influencing factor on ECS is conducive to providing theoretical reference for the formulation of energy and environmental policies, howbeit it lacks studies about the main drivers of national and regional ECS in China. With the consideration of increasingly standardized formal environmental regulation (FER), an extended LMDI model is constructed to decompose the national and regional ECS from 1998 to 2017 into ten influencing factors. The ultimate goals of this concept are to explore the dominant factors of national and regional ECS at different time stages by employing temporal decomposition model, and to investigate the primary drivers that cause the disparity between provincial ECS and national average ECS by applying spatial decomposition model. The results reveal that the effect of FER, the reciprocal of industrial pollution control investment per unit GDP and economic development are the main factors leading to the change of national and regional ECS, specifically FER has a stronger effect on resource-based regions. Also, R&D intensity and R&D efficiency are important factors for ECS change. Energy efficiency and Per capita energy production are the leading factors of ECS disparity between 30 provinces and the national average. What's more, FER and R&D factors play important roles. Policy suggestions are put forward according to the results. Image 1 • Energy efficiency acts as leading force to increase ECS. • R&D intensity and R&D efficiency are important factors for ECS. • FER has a stronger effect on resource-based regions. • Policy- and development-oriented factors should be considered in policy formulation. [ABSTRACT FROM AUTHOR]