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The current period of rapid industrialization has not only brought about rapid economic growth but also caused serious energy shortages and environmental pollution, which have affected the sustainable development of the economy. Therefore, it is of great significance to analyse the changes in regional economic, energy, and environmental carrying capacity (3ECC); analyse the interaction among them; and propose corresponding optimization strategies for promoting regional sustainable development. In this study, a 3ECC simulation system is constructed from the pressure and support levels of load-bearing capacity. A system dynamics model is used to simulate the evolution path and action relationship of the 3ECC system, and an empirical test is completed in the Yangtze River Economic Belt region in China. A coupling coordination model and Bayesian vector autoregressive model are used to further explore the degree and action mode of the 3ECC system support and pressure indices. The results show that the model can truly reflect the characteristics of regional development and is suitable for prediction in this study. From 2015 to 2035, driven by technological progress, China's economic aggregate will grow by 223%, oil consumption by 33%, coal consumption by 23%, soil pollution by 197%, water pollution by 134%, and air pollution by 80.9%. Moreover, the coordination degree of the 3ECC supporting indicators gradually increases, while that of the pressure indicators gradually decreases, indicating that economic growth has a synergistic effect on environmental protection and energy conservation, thus further expanding the differences between environmental pollution and energy consumption. Finally, the supporting index of the economic carrying capacity and supporting index of the environmental carrying capacity have the widest influence range, and the optimization of economic and environmental development status is beneficial to the overall improvement of the 3ECC system. The influence range of the energy carrying capacity support index is small, indicating that coal and oil are being gradually replaced by other energy sources. Therefore, the research results of this paper can provide a reference for the sustainable development of other regions. [ABSTRACT FROM AUTHOR]

The rapid urbanization in China has been associated with a growing hunger for energy consumption and steadily-increasing CO2 emissions. In this paper, an integrated system dynamics model composed of four sub-models is developed to simulate the urbanization and energy consumption in China from 1998 to 2050. Three scenarios are provided: accelerated economic development, emission reduction constraint, and low-carbon oriented. The result reveals that rapid economic growth and sufficient energy supply will foster China's urbanization in all three scenarios. Under the low carbon transition scenario, China's urbanization rate is expected to reach 76.41% in 2050, both reducing carbon emissions and promoting eco-friendly development. All three scenarios witness a dramatic growth of residential energy consumption and a steady increase of industrial energy consumption. China still has a long way to achieve the low-carbon transition goal. China should promote renewable resources and energy, pursue a low-carbon lifestyle, and reduce energy intensity over the next few decades. [ABSTRACT FROM AUTHOR]

Low-carbon development has always been an important focus of China's economic transformation. In order to promote the development of low-carbon economy, this study used SBM-DEA model to evaluate China's provincial LCEE from 2005 to 2019, studied its temporal and spatial evolution law, used spatial autocorrelation to explore the correlation of China's provincial LCEE, and explored the key influencing factors of LCEE with Tobit model. The empirical results show that the LCEE of most provinces in China is declining, and there are significant differences among different regions in China. Because the eastern region of China can rely on its own human resources, capital environment, and economic foundation, the overall LCEE level is relatively high, while the central and western regions still have obvious deficiencies due to industrial conditions, geographical location, and other factors. LCEE has significant spatial correlation, and neighboring provinces have spillover effects on local LCEE. On this basis, the key factors that affect LCEE are determined. Urbanization level, traffic level, economic development level, financial development, investment in fixed assets, and energy consumption are the important factors that affect LCEE in China, but these influences vary from province to region. It is more reasonable for local governments to develop low-carbon economy according to their own conditions. [ABSTRACT FROM AUTHOR]

China becomes the largest energy consumer in 2010 but its energy productivity is well below the world average. To meet China's fast growing energy using, energy efficiency should be especially emphasized under China's energy policy. This paper focuses on the regional level of energy efficiency change in China. And we analyze total factor energy efficiency for 30 Chinese provinces over the period 1998-2009 using Malmquist index method and Tobit analysis. The Malmquist estimation results suggest there is a dropping change trend of energy productivity growth. Chinese energy efficiency still faces with huge regional disparity, but the energy technical efficiency reflects convergence in the nationwide and west region. As a result of Tobit regression, we find that industrial structure, energy consumption structure and institutional factor have different influences on energy efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we review the energy efficiency in China, and the following topics are discussed. (i) Some useful empirical analyses applied on the energy efficiency based on some expanded models, (ii) the relationship among environment, energy and economic growth, (iii) some important environmental efficiency evaluation indexes, and (iv) some latest researches on the emission system. Finally, some policy recommendations are made. [ABSTRACT FROM AUTHOR]

Since coronavirus disease 2019 (COVID-19) was first reported on December 2019 in Wuhan, it fast spread to the rest of China, which has turned into a global public health problem later and generated global stock markets to violently shake. We inspect the causal relationships between economic development (ED) and environmental quality (EQ) during the period from January 2019 to May 2020 with the structural break for China and investigate the causal linkages between ED and EQ in subgroup of before and after the outbreak of COVID-19 with a semi-parametric model. The empirical tests show that smoothing structural transforms matter for the linkages of causality between ED and EQ, especially after COVID-19 infection. While the Toda–Yamamoto causality analysis supports unidirectional causality between ED and EQ before the outbreak of COVID-19, under structural shifts by the causality supplies of bidirectional casual linkages after the outbreak of COVID-19. Our results further clarified the proof that the economic activity gives rise to the environmental pollution and energy utilization mainly via the shock of COVID-19 in China. The emphasis on nonlinear causality between economic development and environmental quality may be an opportunity for China's economic recovery under considering the factor of COVID-19 infection. [ABSTRACT FROM AUTHOR]

The impact of China's financial openness and economic growth on consumption of fossil fuels was analyzed for a panel of ten Latin American countries, throughout 34 years (from 1980 to 2014). An autoregressive distributed lag in the form of unrestricted error correction model was used as the chosen econometric methodology. The results showed that the financial openness, as well as the economic growth of China, increase the fossil fuels consumption in the long-run, while the economic growth of Latin American countries increases the energy use in the short- and the long-run. Moreover, the empirical findings of this research have significant consequences to the local government's appraisal of the relationship between financial openness, China's economic growth and consumption of fossil fuels. [ABSTRACT FROM AUTHOR]

To accurately predict the consumption of clean energy in China, a grey dynamic model is constructed by taking economic growth and environmental regulation as exogenous variables. The Nash equilibrium idea-based optimization method is proposed to solve the parameters of the model so as to obtain better modeling effects than that of the traditional model. The empirical results show that: (1) a spontaneous increasing mechanism of the clean energy consumption has not yet formed in China; (2) both GDP and effluent charge play a positive role in accelerating clean energy consumption in China, but effluent charge has a stronger effect than GDP; (3) clean energy consumption in China is expected to stably increase at an annual rate of 5.73 % averagely in 2012-2020. By 2020, clean energy consumption in China is expected to reach 454.55 million tons of standard coal. The study also provides some policy suggestions of promoting clean energy consumption based on the empirical analysis conclusions. [ABSTRACT FROM AUTHOR]