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In light of the carbon neutrality goals set post-Paris Climate Conference (COP21), this study delves into the relationship between green technology innovations, energy consumption, and CO2 emissions in China, spanning the period of 1990 to 2021. The objective of this paper is to creatively present the idea of a low-carbon digital economy from the viewpoint of digital technology. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, we scrutinize this relationship, employing unit-root testing to verify the integrative attributes of the variables, inclusive of structural break data. Further analysis using the bootstrap Autoregressive Distributed Lag (ARDL) bound testing method corroborates the relationship between these key variables. The study reveals unidirectional co-integration over time among green technology innovations, renewable and non-renewable energy, per capita income, population, and CO2 emissions as per the Granger causality test. Interestingly, our findings suggest that while green technology innovation, per capita income, and renewable energy contribute to the reduction of CO2 emissions, non-renewable energy consumption and population growth exacerbate them. These insights offer valuable guidance for policymakers in formulating comprehensive strategies to enhance environmental quality through the promotion of renewable energy and green technology innovations, with a specific emphasis on the Chinese context. [ABSTRACT FROM AUTHOR]

China building energy consumption (BEC) has been gradually derived and also sparked attention. However, something worth discussing is estimating the BEC based on the definition of life cycle or building operation. In addition, there exists discrepancy in the previous studies and the real status of BEC has not been known well. In order to settle the disputes over the calculation of BEC, this paper establishes an appropriate accounting method of building energy to present the BEC situation in China and lays the foundation for policymakers to develop appropriate energy saving policies. Meanwhile, this study attempts to clarify the BEC to help policymakers assess the effect of environmental policies. Using the method in this document, we find that the energy consumption of buildings just accounts for 15%–16% of the final total energy consumption in China; by contrast, the previous studies usually have double accounting through a top-down approach if central heat supply of buildings was taken into additional consideration. [ABSTRACT FROM AUTHOR]

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces' URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China's policymakers. [ABSTRACT FROM AUTHOR]

The trade-off between economic growth and ecological improvement has always become an important and difficult issue for many countries, especially for developing countries. Due to a long-term extensive economic growth pattern, the regional resource allocation deviates from the optimal, especially the existence of energy misallocation, which hinders the maximization of economic output. Therefore, considering the characteristics and heterogeneity of resource endowments in different regions and increasing renewable energy consumption, that is, promoting energy transition, is it capable of sustainable development under China's actual conditions? The exploration of the issue is a core step in the research of the impact of renewable energy on industrial green transformation. Based on the panel data of 30 regions in China from 2009 to 2016, this paper constructs a threshold model from the perspective of regional energy misallocation and empirically tests the nonlinear mechanism of renewable energy consumption to promote industrial green transformation. The results show that China's energy allocation efficiency is low, there is a certain misallocation phenomenon, and the improvement effect in recent years is not satisfactory. Further, the relationship between renewable energy consumption and industrial green transformation is not a simple linear relationship, but a double threshold effect due to regional energy misallocation. In areas with severe energy misallocation, renewable energy consumption does not have a significant boost to industrial green transformation. Finally, this paper proposes the policy enlightenment of promoting industrial green transformation from the aspects of performance evaluation, market reform, and factor flow. [ABSTRACT FROM AUTHOR]

Developing energy from renewable sources and modernizing the energy system are critical components of China's efforts to combat climate change. Policymakers and authorities have made significant attempts to bring them. However, one of the major impediments to China's energy revolution is financial limitations, which are inextricably linked to the country's economic growth. The present research paper intends to investigate the relationship between economic growth and sustainable financial development on the use of energy from renewable sources in both the short and long run in the context of China. To achieve this, the researchers have utilized the panel data consisting of 10 years from 2011 to 2020. When compared to cross-sectional and time-series data samples, the panel data model offers many benefits. For starters, the panel data includes information on the passage of time and the cross-sectional area. Another benefit of using panel-data models with a larger degree of freedom is that they provide more stable and reliable estimates across short periods across cross-sections. In the case of the short run, there is a positive relationship between economic and financial development and the use of energy from renewable sources in the context of all of China. While in the case of long-term effects, the results indicate the adverse impact of financial development on the use of energy from renewable sources in the western regions of China. These results were deduced using the causality test Granger proposed to determine the path of the causal relationship and the direction of the relationship between the variables. These results indicated that the relationship between economic and financial development in east China was unidirectional, and the nature of the underlying relationship was causal. Meanwhile, in east and west China, economic development in China as a whole has been unidirectionally increasing energy from renewable sources. Our empirical findings suggest many strategies for promoting the growth of energy from renewable sources. [ABSTRACT FROM AUTHOR]

This paper compares the greenhouse gas (GHG) emissions of natural gas (NG)- based fuels to the GHG emissions of electric vehicles (EVs) powered with NG-to-electricity in China. A life-cycle model is used to account for full fuel cycle and use-phase emissions, as well as vehicle cycle and battery manufacturing. The reduction of life-cycle GHG emissions of EVs charged by electricity generated from NG, without utilizing carbon dioxide capture and storage (CCS) technology can be 36%-47% when compared to gasoline vehicles. The large range change in emissions reduction potential is driven by the different generation technologies that could in the future be used to generate electricity in China. When CCS is employed in power plants, the GHG emission reductions increase to about 71%-73% compared to gasoline vehicles. It is found that compressed NG (CNG) and liquefied NG (LNG) fuels can save about 10% of carbon as compared to gasoline vehicles. However, gas-to-liquid (GTL) fuel made through the Fischer-Tropsch method will likely lead to a life-cycle GHG emissions increase, potentially 3%-15% higher than gasoline, but roughly equal to petroleum-based diesel. When CCS is utilized, the GTL fueled vehicles emit roughly equal GHG emissions to petroleum-based diesel fuel high-efficient hybrid electric vehicle from the life-cycle perspective. [ABSTRACT FROM AUTHOR]

With support of GIS tools and Theil index, the spatial variance of urban energy consumption in China was discussed in this paper through the parallel comparison and quantitative analysis of the 30 provincial capital cities of mainland China in 2005, in terms of scale, efficiency and structure. The indicators associated with urban energy consumption show large spatial variance across regions, possibly due to diversities of geographic features, economic development levels and local energy source availability in China. In absolute terms, cities with the highest total energy consumption are mostly distributed in economic-developed regions as Beijing-Tianjin-Tangshan Area, Yangtze River Delta and Pearl River Delta of China, however, the per capita urban energy use is significantly higher in the Mid-and-Western regions. With regard to the energy mix, coal still plays the dominant role and cities in Mid-and-Western regions rely more on coal. In contrast, high quality energy carrier as electricity and oils are more used in southeast coastal zone and northern developed areas. The energy intensive cities are mainly located in the northwest, while the cities with higher efficiency are in southeast areas. The large spatial variance of urban energy consumption was also verified by the Theil indices. Considering the Chinese economy-zones of East, Middle and West, the within-group inequalities are the main factor contributing to overall difference, e.g., the Theil index for per capita energy consumption of within-group is 0.18, much higher than that of between group (0.07), and the same applies to other indicators. In light of the spatial variance of urban energy consumptions in China, therefore, regionalized and type-based management of urban energy systems is badly needed to effectively address the ongoing energy strategies and targets. [ABSTRACT FROM AUTHOR]

China has experienced rapid social and economic development in the past 40 years. However, excessive consumption of fossil fuel energy has caused an energy shortage and led to severe environmental pollution. To achieve sustainable development, China is striving to transform its growth mode. Adopting renewable energy (RE) including solar photovoltaic (PV) power is an effective measure. How to promote the further development of solar PV power under the scenario of China's aspirational target of carbon peak by 2030 and 20% RE ratio in the energy mix remains a theme that need to be addressed. This paper analyzes the potential opportunities and challenges confronting solar PV power in China. The analysis covers the dimensions of political, economic, social, and technological (PEST). The results revealed a significant prospect for the further deployment of solar PV power in the coming decades. The aggressive estimated installed capacity of solar PV power is expected to reach 80+ GW annually. To successfully achieve the goal of 80+ GW, barriers that hinder the further development of solar PV power have to be eliminated. Suggestions for policymakers include maintaining enforceability and continuity of policies, favorable financial supports, mandatory RE quotas for all parties, and supporting fundamental R&D. Suggestions for the solar PV industry include full utilization of integrated applications, set up an after-sales service network, collaborative innovation among the industry chain, and engaging in storage and hydrogen technology. The findings are greatly beneficial for policymakers and the solar PV industry. [ABSTRACT FROM AUTHOR]

Agricultural direct energy use is responsible for about 1–2% of global emissions and is the major emitting sector for methane (2.9 GtCO2eq y−1) and nitrous oxide (2.3 GtCO2eq y−1). In the last century, farm mechanisation has brought higher productivity levels and lower land demands at the expense of an increase in fossil energy and agrochemicals use. The expected increase in certain food and bioenergy crops and the uncertain mitigation options available for non-CO2 emissions make of vital importance the assessment of the use of energy and the related emissions attributable to this sector. The aim of this paper is to present a simulation framework able to forecast energy demand, technological diffusion, required investment and land use change of specific agricultural crops. MUSE-Ag & LU, a novel energy systems-oriented agricultural and land use model, has been used for this purpose. As case study, four main crops (maize, soybean, wheat and rice) have been modelled in mainland China. Besides conventional direct energy use, the model considers inputs such as fertiliser and labour demand. Outputs suggest that the modernisation of agricultural processes in China could have the capacity to reduce by 2050 on-farm emissions intensity from 0.024 to 0.016 GtCO2eq PJcrop−1 (−35.6%), requiring a necessary total investment of approximately 319.4 billion 2017$US. [ABSTRACT FROM AUTHOR]

This paper conducts panel analysis to evaluate the effects of a structural economic shift from the industrial to the tertiary sector, a reduction in industrial overcapacity, and improvements in energy efficiency on energy consumption using data for 30 Chinese provinces from 1995 to 2015. We find that, at the national level, the structural shift to the tertiary sector, the reduction in cement and steel production, and the increase in energy efficiency in the industrial sector all have statistically significantly negative effects. We also divide the sample into three geographic and economic regions to evaluate regional differences. We find that the gross domestic product (GDP) share of the tertiary sector shows its greatest impact on reducing energy consumption in the eastern region, a decline in heavy industry production would reduce energy demand more in the central region, and improvement in industrial electricity efficiency would also help reduce energy consumption the most in eastern China. We also forecast energy consumption in China will reach 4.8–4.9 billion tonnes of coal equivalent (tce) in 2020 and further grow to 5.0–5.4 billion tce in 2030. [ABSTRACT FROM AUTHOR]