Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions

China’s Eco-Efficiency: Regional Differences and Influencing Factors Based on a Spatial Panel Data Approach

From the Kyoto Protocol to the Copenhagen Conference and the Paris Agreement, eco-environmental problems have gradually become a matter of common concern worldwide. Eco-efficiency (EE) is an essential indicator for measuring levels of sustainable development. This study uses an epsilon-based measure (EBM) model with undesirable outputs to evaluate the EEs of 30 Chinese provinces during the research period 2008 to 2017, and a spatial Durbin model (SDM) to search for the impact factors of EE. The results indicate that most provinces in China have a low EE level. The EE value of the eastern area is higher than are those for the central, western, or northeastern areas. The EE in China as a whole demonstrates an inverted V-shaped trend with a high point in 2011. The SDM shows that economic development level, foreign trade dependence, and technological progress exert significant positive effects on EE, while population density exerts significant negative influences on EE. This paper provides scientific bases for the formulation of policies resulting in sustainable development

Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions

How Strategic Interaction of Innovation Policies between China’s Regional Governments Affects Wind Energy Innovation

Prior research has shown the importance of innovation policies that promote innovation in renewable energy, such as wind power. We study the impact of the strategic interaction of innovation policies between regional governments in terms of wind energy innovation in China. Based on panel data from 2007 to 2018 on a provincial level in China, we construct an innovation strength index of each province in the wind power industry and investigate the inductive effect of the technology-push policy and the demand-pull policy, as well as their spatial spillover effect on wind energy innovation. The results show that the technology-push policy of local governments has an obvious inductive effect on wind energy innovation in the region, while also having a negative spillover effect through R&D factor competitions between regions with geography proximity or with proximity in the ranking of R&D funds input. In terms of the demand-pull policy, only changes at the national level can produce positive spillover effects by promoting expectations of market growth. Yet, competition between regions with proximity in the ranking of wind energy resource reserves produce negative spillover effects. The findings should have a far-reaching impact on the sustainable development of global wind power

Enhanced filament ablation of metals based on plasma grating in air

We demonstrate efficient ablation of metals with filamentary plasma grating generated by two intense blue femtosecond filaments and a third focused infrared pulse. This scheme leads to significant promotion of ablation efficiency on metal targets in air in comparison with single infrared or blue filament with equal pulse energy. The reason is that the blue plasma grating firstly provides stronger intensity and a higher density of background electrons, then the delayed infrared pulse accelerates local electrons inside the plasma grating. These two processes finally results in robustly increased electron density and highly ionized metallic atoms

What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China

The contributions of this research are making the theoretical analysis of the impact mechanism of urbanisation on carbon emissions efficiency (CEE), and then empirically analysing the effects of urbanisation on CEE in Western China from 2010 to 2019 by applying the super-efficiency epsilon-based measure model with undesirable outputs and the Tobit model. Major findings are: (1) The mean CEE of the 11 western provinces show a trend of declining and then increasing over those 10 years, demonstrating U-shaped change characteristics. (2) The CEE of Guangxi has the most significant decrease, while the CEE of Chongqing showed only a small fluctuation; the CEE of Guizhou has the characteristic that first it rises, then descends, then rises again; the CEEs of Inner Mongolia and Yunnan have been in the production frontier surface from 2010 to 2015, and presents the trend of declining, then increasing after 2015. The CEEs of the other six western provinces present a trend of declining, then increasing. (3) Chongqing, Sichuan, Inner Mongolia, and Yunnan have a high level of CEE, followed by Shaanxi, Xinjiang, Guangxi, and Guizhou, with an intermediate level of CEE, and Gansu, Ningxia, and Qinghai, with the lowest level of CEE. (4) The effects of urbanisation on CEE in Western China present a U-shaped relationship, meaning that the process of influence was first inhibition, then stimulation. At present, the process of urbanisation shows negative impacts on the CEE, while the tipping point has not yet arrived. The western provinces of China should follow the path of high-quality urbanisation to quickly shift the impact of urbanisation on CEE to the right side of the U-shaped curve

Spatiotemporal Characteristics and Influencing Factors of Water Resources’ Green Utilization Efficiency in China: Based on the EBM Model with Undesirable Outputs and SDM Model

A shortage of water resources is a global issue of common concern. The contribution of the article mainly includes the following two parts. First is the study of water resources’ green utilization efficiency (WRGUE) in 30 provincial administrative units of China from 2009 to 2019 by adopting the epsilon-based measure (EBM) model with undesirable outputs, which can yield a more accurate and reasonable assessment result. In addition, the spatial Durbin model was applied to analyze the driving factors of the WRGUE, which considers the spatial effects. The results are as follows: (1) The discrepancy of the WRGUE in different regions of China is conspicuous, with the highest in East China, followed by the central and the western region, while the Northeast is the lowest. A general decrease trend from China’s southeast coastal area to the northwest inland is presented. (2) Global spatial autocorrelation analysis shows a significant positive spatial autocorrelation in the WRGUE of the 30 sample provinces. However, the local spatial autocorrelation analysis shows that the WRGUE in China presents stronger spatial homogeneity than heterogeneity. (3) The levels of technology advancement, economic development, and the Opening-up policy implementation serve as positive factors influencing the WRGUE in China. On the contrary, the urbanization level has a significant negative impact on the WRGUE. The results of this paper may have great value for sustainable water resource utilization

The Carbon Emission Intensity of Industrial Land in China: Spatiotemporal Characteristics and Driving Factors

CO2 emission reduction has become a consensus all around the world. This paper investigates the spatiotemporal characteristics of industrial land carbon emission intensity (ILCEI) in China by spatial autocorrelation analysis, and applies the spatial Durbin model to reveal the influence of driving factors on ILCEI. The results indicate the following: (1) national ILCEI first shows a downward and then an upward trend during the period and presents a low pattern in both Eastern and Northeastern regions and a high pattern in the Northwestern region. (2) From a global perspective, ILCEI shows significant spatial agglomeration characteristics; from a local perspective, ILCEI is dominated by H-H and L-L agglomeration types, showing that spatial heterogeneity and spatial dependence are apparent in ILCEI. (3) ILCEI is significantly negatively affected by both R & D personnel and foreign-trade dependence, while urban population density notably has positive impacts on ILCEI. This paper is a beneficial policy practice for harmonizing the contradiction between industrial land expansion and carbon discharge

China’s Transport Land: Spatiotemporal Expansion Characteristics and Driving Mechanism

The literature about changes in land use includes many studies of global sustainable development goals, while studies of transport land expansion have been relatively scarce. In this paper, we present an analysis of the spatiotemporal characteristics of transport land expansion in China’s 31 provinces from 2009 to 2017, applying the spatial Dubin model to identify the factors that influenced changes in per capita transport land area (PCTLA). The eastern and western regions have continued to lead the nation in terms of the total area dedicated to transport land. The expansion speed of transport land in the central and western regions, however, has been faster than in the eastern and northeast regions. As for PCTLA, the western region had the greatest amount and the central region the least. Further, PCTLA showed significant spatial autocorrelation. Economic development, government regulations, industrial structure, and the extent of opening up and urbanization had significant positive impacts on PCTLA, while the development of railway freight had a negative impact. This paper concludes with some policy suggestions for optimizing transport investment, accelerating the adjustment of industrial structure and transport structure, and implementing high-quality urbanization. The results should be of interest to those involved in the sustainable development of transport systems

China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model

The threat of global climate change has caused the international community to pay close attention to atmospheric levels of greenhouse gases such as carbon dioxide. Transportation sector carbon dioxide emissions efficiency (TSCDEE) is a key indicator used to prioritize sustainable development in the transportation sector. In this paper, the epsilon-based measure data envelopment analysis model with undesirable outputs is applied to estimate TSCDEE for 30 provinces in China from 2010 to 2016. We also analyze influencing factors using the spatial Durbin model. Research shows that the overall TSCDEE of the Chinese provinces studied was 0.618, indicating that most regions are still in need of improvements. The provinces with the highest TSCDEE are located in developed coastal regions of China. This study shows that factors such as transportation structure, traffic infrastructure level, and technological progress have prominent positive effects on TSCDEE, while both urbanization level and urban population density exert significantly negative effects on TSCDEE. The findings should have a far-reaching impact on the sustainable development of global transportation.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Housing Quality and Process Innovatio