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Energy and environmental policies are important methods for the government to restrain carbon emissions growth. Identifying the potential dynamic trends of China's carbon emissions under different scenarios has important reference significance for the government's policy implementation. This paper firstly predicted China's carbon emissions from 2017 to 2040 based on three energy transition scenarios at the industrial level. Then, Logarithmic Mean Divisia Index decomposition model was applied to evaluate the driving forces of emissions changes during 1997–2040. Finally, the Spatial–Temporal Logarithmic Mean Divisia Index model was used to explore the emissions reduction potential and the potential reduction path at provincial level. The results showed that (1) as the reduction in energy intensity cannot offset the growth of industrial scale, the carbon emissions of all industries have shown an increasing trend from 1997 to 2017; (2) In the current policies scenario, China's carbon emissions cannot reach the peak before 2040. And only in the sustainable development scenario, the carbon emissions of the three industries will all reach the peaks before 2030. And the development of non-fossil energy will reduce carbon emissions by more than 30%; (3) Hebei, Shanxi, Inner Mongolia, Ningxia, and Heilongjiang are key provinces and improving energy efficiency of the secondary industry is a potential way to promote carbon emissions reduction. The framework and main content of this paper. [ABSTRACT FROM AUTHOR]

Renewable energy (RE), the key to realizing the low-carbon transformation of energy, is significant in reducing social carbon emissions (CEs). However, the regional differences in the impact of RE on CEs and the impact mechanism are still unclear. Clarifying the regional differences and impact mechanisms will encourage the government to formulate a development plan for RE in line with the actual situation. To explore the heterogeneous impacts and conduction paths of RE on CEs, this paper uses province-level data from 2000 to 2019 in China. Based on clarifying regional CE efficiency, panel quantile regression models are introduced to assess the differential impacts of RE at different CE efficiencies. And the conduction mechanism of the effect of RE on CE efficiency is explored through the parallel multiple mediation effect model. The results show that RE development, the accumulation of social affluence, and technological innovation can improve carbon efficiency while increasing population size and energy consumption inhibit carbon efficiency. Urbanization rate, industrial structure, and opening to the outside world affect travel alienation in regions with different levels of CE efficiency. RE development improves regional CE efficiency, which is more evident in regions with low and high efficiency. In addition, RE can increase CE efficiency indirectly through effects on population size, urbanization rate, scientific and technological innovation, and intensity of fossil energy consumption. However, it decreases CE efficiency indirectly through social enrichment. These findings will provide broader insights for improving the development of regional RE and formulating differentiated policies. [ABSTRACT FROM AUTHOR]

How to utilize human, financial, and material resources reasonably in the technological innovation of new energy vehicles to obtain the maximum benefit with the least investment is an important issue that needs to be solved urgently. This paper employs the stochastic frontier model to analyze the innovation efficiency and its influencing factors of new energy vehicles in China. The investment of innovation is divided into four dimensions: human resource input, R&D input, technology acquirement input and environment support input. The results demonstrate that the mean of innovation efficiency of the new energy vehicle industry is low in general. The Yangtze River Delta and Pearl River Delta regions have the highest innovation efficiency comparable to that of other regions. There is a significant positive impact of asset turnover ratio, per capita compensation of management, and education level on innovation efficiency. The effects of asset-liability ratio and government support on innovation efficiency are not significant. But the government support has a significant positive moderation effect on innovation efficiency through financial factors. Based on the conclusions, this paper proposes insights to promote the development of the new energy vehicle industry. [ABSTRACT FROM AUTHOR]

Environmental protection tax is of great significance to the realization of an environment-friendly society. Using data from 280 Chinese cities from 2010 to 2020, this paper measures total factor energy efficiency in China by the super slack-based measure model. The impact of China's environmental protection tax reform on total factor energy efficiency is tested through differences-in-differences method, and its transmission mechanism is explored. Environmental protection tax reform policies have a significant positive impact on total factor energy efficiency. Environmental protection tax reform policies have greater impact on resource-intensive cities in central region and cities with lower initial energy efficiency. Cities with increased tax have positive spillover effects on the neighboring cities. This study provides empirical evidence for further optimization of environmental protection taxes and energy efficiency. The structure of the environmental tax system should be optimized, and the environmental tax policy should be implemented according to local conditions. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of the automotive industry has brought about several environmental and energy issues worldwide. Many countries have established fuel consumption regulations. Among them, fuel consumption regulations based on the curb weight or footprint have been put forward in China and the US. This paper mainly compares the effect of the application of footprint-based and curb weight-based regulations in China. To compare the effect of these two different benchmarks, a Chinese footprint-based fuel consumption regulation is designed based on the principles of the American footprint regulations and the actual conditions of the Chinese passenger car market, and fuel consumption data from 14 enterprises are also used. It is found that regulations help maintain market neutrality if the target value is separated into two curves according to the type of vehicle. Additionally, footprint regulations are more conducive to vehicle lightweighting than curb weight regulations. Finally, policy recommendations are drawn: to maintain market neutrality, there should be two target value curves in the fifth stage of the weight regulation: one for sedans and one for SUVs. Meanwhile, footprint regulation adaptation should be considered in the future to promote vehicle lightweighting in the Chinese market. [ABSTRACT FROM AUTHOR]

Hydropower is the most economically developed renewable energy source in China. In the twenty-first century, the era of clean and low-carbon development, hydropower can meet the continuous growth of energy consumption and help China achieve its goal of carbon neutrality by 2060. In 2019, China's installed hydropower capacity was 358.04 GW, and hydropower consumption was 1.132 × 1016 kJ, with a growth rate of 5.5%, well above the global average of 0.8%. Although China's hydropower achievements are renowned worldwide, hydropower development in China still faces challenges in relation to environmental, technological, economic and social issues. In this paper, we first review the history, achievements and current situation of China's hydropower development and summarize the specific challenges mentioned above. Then, we take the Dadu River Hydropower Base as a case study. This project ranks fifth among China's 13 largest hydropower bases, and the construction of 14 cascade hydropower stations was completed in December 2020, accounting for 61.3% of the total planned installed capacity of 28 cascades, with 3 more still under construction (accounting for another 16.3%). We comprehensively describe the background, tasks and exploitation of hydropower development in the Dadu River basin and highlight current practices, including exploration of environmental protection and ecological restoration, technical innovation, supporting facility construction, economic promotion and resettlement. Finally, based on the identified practices and lessons, we propose feasible suggestions for China's future hydropower development. [ABSTRACT FROM AUTHOR]

China's transport industry has made rapid progress, which has led to a great amount of carbon emissions. However, it is still unclear how carbon emissions from the transport sector are punctuated by shifts in underlying factors. This paper aims to examine the process of China's carbon emissions from the transport sector as well as its major driving forces at the provincial level during the period of 2000 to 2015. We first estimate the carbon emissions from the transport sector at the provincial level based on the fuel and electricity consumption using a top-down method. We find that the carbon emission per capita is steadily increasing across the country, especially in the provinces of Chongqing and Inner Mongolia. However, the carbon emission intensity is decreasing in most provinces, except in Yunnan, Qinghai, Chongqing, Zhejiang, Heilongjiang, Jilin, Inner Mongolia, Henan and Anhui. We then quantify the effect of socioeconomic factors and their regional variations on carbon emissions using a panel model. The results show that the development of secondary industry is the most significant variable for carbon intensity at both the national and regional levels, while the effects of the other variables vary across regions. Among these factors, population density is the main factor of the increasing carbon emissions per capita from the transport sector for both the whole country and the western region, whereas the consumption level per capita of residents and the development of tertiary industry are the primary drivers of per capita carbon emissions for the eastern and central regions. [ABSTRACT FROM AUTHOR]

China's energy use has been, and will be for a long time, dominated by coal. The literature has studied little on the material metabolism of coal mines, especially for China, from a systems perspective. The aim of this study is to develop a quantitative framework to investigate the internal material metabolism of coal mining enterprises in China. This framework, three-dimensional hybrid enterprise input-output (3D-HEIO) model, combines scenario analysis and the enterprise input-output model. To illustrate the application of this framework, the material metabolism of Wang Coal-mine (WCM) in Shanxi, China is analyzed. Results show that the WCM has the annual potential to recover 10,862 tonnes of coal, reduce 404,515 tonnes of water consumption, 13 million kWh of electricity consumption, 70 tonnes of coagulant agents, 90,000 pieces of paper, and 146 tonnes of sulfur dioxide and dust emissions, and reuse 100,000 tonnes of coal gangue. The potential of economic profit can be 14.24 million yuan per year. [ABSTRACT FROM AUTHOR]

As an energy-intensive industry, the energy and environmental issues of non-ferrous metals industry receive increasing attention. Dividing the production of non-ferrous metals into two sub-stages including mining and processing (M&P) and smelting and pressing (S&P), a non-cooperative game network data envelopment analysis model with double viewpoints (optimistic and pessimistic) is developed to evaluate the energy and environmental efficiency of China's non-ferrous metals industry. Moreover, we construct a novel network Malmquist productivity index to identify the dynamic evolution of energy and environmental performance. The results of 25 provinces over 2010–2017 show that energy and environmental efficiency of China's non-ferrous metals industry is very low during the study period, and the efficiency gap of two sub-stages increases significantly over time. Additionally, the energy and environmental efficiency in eastern region is more affected by the M&P sub-stage, while the efficiency of that in central and western regions is greatly influenced by the S&P sub-stage. Technical progress plays a key role in the productivity improvement of the M&P sub-stage, but the main driving force of productivity change in the S&P sub-stage is different in the three regions. Based on above findings, several targeted policy implications are suggested to prompt the sustainable development of China's non-ferrous metals industry. [ABSTRACT FROM AUTHOR]

This study investigates the impact of electric vehicle development on China's greenhouse gas emissions and fossil energy consumption from a life cycle perspective. Based on vehicle technology and China's energy development plan, the potential for energy conservation and greenhouse gas emissions reduction of electric vehicles is explored. Utilizing a logistic model, the market evolution of electric vehicles under different timing for banning the sale of the traditional fuel vehicle is simulated and analyzed, and the corresponding effect on energy conservation and greenhouse gas emissions reduction is also examined. The results show that the high proportion of coal-fired thermal power limits the energy saving and emission reduction potential of electric vehicles in China. The life cycle greenhouse gas emissions and fossil energy consumption intensities of electric vehicles in various regions are approximately − 2.63%–30.98% (− 7.63–89.81 g CO2-eq/km) and 17.71%–43.16% (0.67–1.64 MJ/km) lower than those of traditional fuel vehicles, respectively. As the proportion of renewable electricity generation continues to increase, by 2050, replacing traditional fuel vehicles with electric vehicles can reduce greenhouse gas emissions by at least 22.32% and fossil energy consumption by 29.94% in all regions of China. In addition, if China plans to ban the sale of traditional fuel vehicle between 2040 and 2060, the cumulative fossil energy savings and greenhouse gas emission reductions during the period of 2020–2050 can reach approximately 25.70–73.47 million TJ and 1511.95–4303.87 million tons of CO2-eq, respectively. [ABSTRACT FROM AUTHOR]

To facilitate a better understanding of China's regional energy consumption, this study develops a coupled framework to analyze the socioeconomic and policy drivers of the evolution of Sichuan province's energy consumption. The results show that during 2002–2016, GDP per capita was the most significant driver of energy consumption, accounting for 185.16% of the total change, followed by economic structure (4.02%). Energy intensity has been at the center of Sichuan's energy policies and the only factor exerting downward pressure on energy consumption, accounting for − 91.72% of the total change, although the reducing effect was not stable through the years. By contrast, although the government has continuously stressed economic restructuring for energy conservation, the relevant policies have been largely ineffective. Except for major social emergencies, such as the Wenchuan earthquake, the basic energy strategy has been focused on reducing coal consumption, stabilizing the petroleum supply and encouraging the development and use of natural gas. In addition, the key indicators of energy consumption control basically showed cyclical trends with respect to the provincial 4-year plan (FYP), i.e., increasing (or decreasing slowly) in the first 3–4 years of a FYP and then decreasing (or decreasing more rapidly) during the last 1–2 years. Therefore, this study suggests the building of a FYP-centered energy policy system to integrate the various policies issued by different departments and the introduction of more market-oriented approaches for energy conservation to curb deficiencies in the administration-driven economic restructuring. [ABSTRACT FROM AUTHOR]

Industrial parks play a significant role in economic development while consuming a great deal of energy and emitting a lot of greenhouse gas (GHG). Meanwhile, under the pressure of limiting the global average temperature rise to 2 degrees Celsius as proposed by the Paris agreement, industrial parks have compelling obligation to reduce GHG emissions, driving them on the path to low-carbon development. This study established the GHG emission inventory and assessed carbon emission reduction potential in an industrial park. The GHG emission inventories were accounted from 2013 to 2017, including energy-related emission, industrial processes related emission and indirect emission from electricity. Then, three scenarios were designed to assess carbon emission reduction potential, as follows: industrial waste heat recovery scenario (WHR scenario), utilization of renewable energy (RNE scenario) and energy efficiency improvement scenario (EEI scenario). The results show that the total amount of GHG emission in 2017 was 14.9 Mt CO2e, twice more than 2013, and the energy-related GHG emission was the dominant sector in the total GHG emission. Scenario analysis indicates that the total carbon emission reduction of the three approaches is 3.29 Mt CO2. Among them, the measures of low-pressure waste heat recovery and energy efficiency improvement have great potential for carbon emission reduction in industrial parks. This study could provide a comprehensive understanding of GHG emission mitigation to improve the energy and environmental performance at the industrial park. [ABSTRACT FROM AUTHOR]

China is responsible for around one-quarter of global vehicle production. The associated Greenhouse Gas (GHG) emissions have become a major concern to the industrial sustainable development. With the aim of identifying the opportunities of cutting GHG emissions from China's automotive industry, this study estimates the life cycle GHG emissions from vehicle production in China and compares the results with the case in the USA from multiple perspectives. The results reveal that the GHG emissions from the production of a standard internal combustion engine-based passenger vehicle in China are around 9.6 ton per vehicle, 54% higher than the US level of 6.2 ton per vehicle. The power-intensive nature of vehicle production and China's higher GHG emission intensity of power generation are the major reasons behind the difference. Accordingly, total GHG emissions from passenger vehicle production in China were around 173.9 million tons in 2013, accounting for nearly 3% of the GHG emissions from the manufacturing and construction sector. Based on the analysis, it is recommended that China should further optimize the grid mix and reduce the emission intensity of power generation. Besides, emission intensities of steel and aluminum productions should be further reduced through applying energy-efficient technologies and promoting material recycling. [ABSTRACT FROM AUTHOR]

This study primarily investigated the forecasting of the growth trend in renewable energy consumption in China. Only 22 samples were acquired for this study because renewable energy is an emerging technology. Because historical data regarding renewable energy were limited in sample size and the data were not normally distributed, forecasting methods used for analyzing large amounts of data were unsuitable for this study. Grey system theory is applied to system models involving incomplete information, unclear behavioral patterns, and unclear operating mechanisms. In addition, it can be used to perform comprehensive analyses, observe developments and changes in systems, and conduct long-term forecasts. The most prominent feature of this theory is that a minimum of only four data sets are required for establishing a model and that making stringent assumptions regarding the distribution of the sample population is not required. However, to address the limitations of previous studies on grey forecasting and to enhance the forecasting accuracy, this study adopted the grey model (1, 1) [GM(1, 1)] and the nonlinear grey Bernoulli model (1, 1) [(NGBM)] for theoretical derivation and verification. Subsequently, the two models were compared with a regression analysis model to determine the models' predictive accuracy and goodness of fit. According to the indexes of mean absolute error, mean square error, and mean absolute percentage error, NGBM(1, 1) exhibited the most accurate forecasts, followed by GM(1, 1) and regression analysis model. The results indicated that the modified NGBM(1, 1) grey forecasting models demonstrated superior predictive abilities among the compared models. [ABSTRACT FROM AUTHOR]