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Clean energy development has played a pivotal role in economic transformation. Based on the panel data of 30 provinces in China from 2006 to 2021, the spatial Dubin model was used to empirically investigate the impact of clean energy development on green economic growth. Furthermore, this research selected industrial structure optimization as the mediating variable to analyze the mediating effect between clean energy development and green economic growth. The results are as follows. Firstly, there is a positive spatial correlation for green economic development, in which the level of green economic development in a region can be influenced by neighboring regions. Secondly, there is a significant positive relationship between clean energy development and green economic growth, in which the clean energy development has a positive impact on green economic growth. Thirdly, the mediating effect analysis demonstrates that the clean energy development can influence green economic growth through industrial structure optimization. Based on the findings in this paper, several suggestions are proposed. China should formulate a unified national strategy for green economy by coordinating and balancing regional differences, develop the clean energy industry to promote green economic growth, and pay attention to the intermediary effect of industrial structure to promote green economic growth. [ABSTRACT FROM AUTHOR]

Intelligence relieving energy consumption and economic growth nexus is important for green development. To explore the potential power for sustainability, this paper uses entropy weight method to measure the intelligent level, adopts decoupling indicator between energy consumption and economic growth for green growth performance, and builds a spatial model to diagnose the mechanism of decoupling system. The results show that the achievements of intelligent development in the three regions are remarkable, and the intelligent level in the eastern region is the most prominent of all. Regardless of regional differences, intelligence is the main and stable driver deepening decoupling indicator; Notable pushing-out or pushing-in spilling power on regional decoupling through many channels can be identified, namely urbanization, income and FDI. Clean energy can help promote the driving effects of intelligence on decoupling and is not confined by regions. The fierce green competition race in the form of "anti-typicality" mode exists in various regions, especially in the Western region; only in the Middle region, the intelligent spatial spillover effect can form the driving force for decoupling. Accelerating the intelligent development and the application of clean energy is an effective measure to achieve the green environmental targets. [ABSTRACT FROM AUTHOR]

After reform and opening-up, rapid industrialization and urbanization led to environmental degradation in China, including excessive energy consumption, soil contamination, and water pollution. Toward sustainable development, the Chinese government has promoted the introduction of clean energy sources such as geothermal and hydroelectric power generation, which have reduced the environmental burden. However, the impact of this energy shift on environmental improvement and economic growth is unclear. This study empirically analyzes the impact of green energy deployment and economic growth on CO2 emissions in China. The analysis of time series data from 1980 to 2020 shows that in the long run, a 1% increase in renewable energy significantly reduces CO2 emissions by 0.87%, and a 1% increase in GDP significantly increases CO2 emissions by 0.26%. In contrast, in the short run, the negative effect of renewable energy on CO2 emissions and the positive effect of GDP on it are not significant. This result was confirmed after the robustness checks. Based on the results obtained, several policy recommendations are made. [ABSTRACT FROM AUTHOR]

China's adoption of an "ecological civilization" strategy since 2012 demonstrates its vision to move toward more sustainable development models while promoting green energy and strengthening environmental protection. However, China's continuing heavy reliance on fossil fuels, especially coal, masks the complex positive trends in energy use, more sustainable economic development, and environmental management. Through examining the evolving energy-GDP relationships in China over the past few decades, we elucidated the underlying complex nonlinear processes using environmental Kuznets curve analysis and showed that the energy–GDP relationship has fluctuated between positive and negative decoupling. Furthermore, fluctuating trajectories manifested as sharp regional divergences when early-transitioning coastal areas restructured toward services and exhibited robust decoupling, whereas the industrial interior remained fossil fuel reliant. We identified various forces related to these provincial disparities, where rapid urbanization, industrial realignment, and income growth were all important. By promoting service transitions and enabling low-carbon technologies in coastal hubs, these drivers also exposed infrastructure deficits and entrenched fossil fuel usage in the interior. These problems led to China's latest strategic plans emphasizing "higher quality" growth underpinned by clean energy transitions and coordinated regional policies. Ongoing declines in coal and the rise in renewable energy usage highlight promising momentum, but stable decoupling remains contingent on sustained policy coordination. The intricate balance between growth and environmental pressures in China provides essential lessons to help emerging economies achieve sustainability by catalyzing green transitions and attaining developmental milestones. [ABSTRACT FROM AUTHOR]

The 2030 agenda of the United Nations provides a framework of 17 Sustainable Development Goals (SDGs) and 232 indicators for its members to fulfill. The overall achievement critically depends on how nations understand the interactions between these SDGs and set priorities for development pathways. This study provides a comprehensive network analysis of global SDG complementarities, measured by the co-occurrences of SDG pairs' comparative advantages in the same region by adopting the 'product space' concept from economics. We construct the 'SDG space' at goal and indicator levels with the most recently available data and then validate its robustness by comparing it to the commonly used correlation network and confirm its predictive power using historical data. Network analysis reveals a strongly connected socioeconomic-related core and an environmental-related periphery, with 'bridge' indicators connecting different clusters. The goal-level space identifies the 'bridge' goals as SDG 17 (Partnerships for the Goals), SDG 8 (Decent Work and Economic Growth), and SDG 15 (Life on Hand) in the environmental-related cluster, while identifying SDG 7 (Affordable and Clean Energy), SDG 6 (Clean water and Sanitation), and SDG 16 (Justice and Strong Institutions) in the socioeconomic cluster. The indicator-level space provides details to explain how they act as 'bridges' in the network. In particular, 16–9: Free Press Index is the 'bridge' indicator with the highest betweenness centrality value and acts as the bottleneck indicator in China for its overall sustainable development. Improving it can enhance connected indicators' performance, leading to positive cascading effects on different aspects of sustainability. • A comprehensive network analysis of global SDG complementarities, measured by the co-occurrences of comparative advantages in the same region. • Network analysis reveals a strongly connected socioeconomic-related core and an environmental-related periphery, with 'bridge' indicators connecting different clusters. • The goal-level space identifies the 'bridge' goals as SDG 17 (Partnerships for the Goals), SDG 8 (Decent Work and Economic Growth), SDG 15 (Life on Hand) in the environmental-related cluster, while identifying SDG 7 (Affordable and Clean Energy), SDG 6 (Clean water and Sanitation), and SDG 16 (Justice and Strong Institutions) in the socioeconomic cluster. • The indicator-level space provides details to explain how they act as 'bridges' in the network.16–9: Free Press Index is the 'bridge' indicator with the highest betweenness centrality value and acts as the bottleneck indicator in China for its overall sustainable development. • 16–9: Free Press Index is the 'bridge' indicator with the highest betweenness centrality value and acts as the bottleneck indicator in China for its overall sustainable development [ABSTRACT FROM AUTHOR]

Recently, there has been an urgent need to fully implement renewable energy sources to realise green energy transitions and combat environmental pollution. This study uses a benchmark estimation model to analyse the links between green economic growth, green financing, and green energy from 2010 to 2020 and green energy advancement in China. Within the context of renewable energy, scholars have investigated various, unequal, and mediating influence connections. According to the extant literature, green economic expansion and green finance are significantly linked with renewable energy, but with diverse influences in various types of renewable technology and in various regions. The effect of green growth in the economy on green energy is non-linear, while green finance is coherent. Green technological advancement is efficiently facilitates green productivity expansion and green energy, and the investment impact is partially mediated. This study contributes significantly to the formulation of several practical initiatives to strengthen the green energy sector and facilitate sustainable growth. The results indicate that it is essential to maximise the potential of green economic activity to advance the green energy sector through the full utilisation of green accomplishments in their transformed forms. • Urgent need for renewable energy: Implementing renewables for green transitions. • Linking green growth, financing, and energy: Analyzing connections in China. • Diverse influences on renewables: Varied impacts by region and technology. [ABSTRACT FROM AUTHOR]

• An expanded food-energy-water (FEW) nexus in China is built from the lens of Sustainable Development Goals (SDGs). • China has more trade-offs than synergies in the framework of expanded FEW nexus. • Economic growth has a stronger impact on the FEW nexus than consumption and production patterns. • Changing the priorities of actions could contribute to transforming trade-offs into synergies. • Addressing the mutual inhibiting between different sectors is crucial for applying the nexus approach The nexus approach offers an important heuristic tool for the sustainable management of resources by considering the links among different sectors. The food-energy-water (FEW) nexus corresponds to links among the three of seventeen United Nations Sustainable Development Goals (SDGs), namely SDG2 (No Hungry), SDG6 (Clean Water and Sanitation), and SDG7 (Affordable and Clean Energy), and their interlinkages have a direct or indirect impact on other SDGs. However, there is still a lack of a systematic and quantitative analysis of how the nexus approach could promote achieving SDGs. Here, taking China as a case, we built an expanded FEW nexus framework from the lens of SDGs, which consists of six sectors, including food (SDG2), water (SDG6), energy (SDG7), economic (SDG8), consumption and production (SDG12), and forest (SDG15). We quantified the two-way interactions between the six sectors by the panel vector autoregressive (PVAR) model. Results indicate that sectors exhibit different response characteristics (positive or negative) in their interactions, and these responses could change over time. These results imply that changing the priorities of actions may be an effective measure to transform trade-offs into synergies. Moreover, the contribution of different sectors to each other varies considerably, with economic growth (SDG8) generally having a higher impact on changes in the FEW nexus than consumption and production patterns (SDG12). Our research suggests that strengthening the quantitative assessment of two-way interactions among the FEW nexus has crucial implications for leveraging nexus approaches effectively to achieve sustainable development for all. [Display omitted] [ABSTRACT FROM AUTHOR]