The energy-environment efficiency of road and railway sectors in China: Evidence from the provincial level

Zhao, Liang; Qin, Chang-Xiong; Zhang, Yue‐Jun

doi:10.1016/j.ecolind.2016.05.016

Cited by 72 publications

(32 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is an uncertain relationship between population density and CEE. Liu et al (2016b) suggested that higher population density may urge the government and population to pay more attention to the environment, and it may improve CEE. However, Cropper and Griffiths (1994) thought that higher population density may lead to higher pressure on the environment, which can in turn lead to a decrease in CEE.…”

Section: Variable and Software Selectionmentioning

confidence: 99%

“…Many studies investigated energy efficiency or CEE at the country level (Beltr an-Esteve and Picazo-Tadeo, 2017; Girod et al, 2017;Sakamoto and Managi, 2017;Zhou et al, 2017) or province level (Liu et al, 2016a(Liu et al, , 2016bZhang et al, 2016b;Zhou and Liu, 2016). Due to the spatial variations in economic development and the source of carbon emissions inside the country or province, there is obvious spatial difference in CEE across its prefecture-level cities inside the country or province.…”

Section: Introductionmentioning

confidence: 99%

“…While there are some studies on CEE, there are three limitations in previous research. First, the study scale was mainly the country (Beltr an-Esteve and Picazo-Tadeo, 2017; Girod et al, 2017;Sakamoto and Managi, 2017;Zhou et al, 2017) or the province (Liu et al, 2016a(Liu et al, , 2016bZhang et al, 2016b;Zhou and Liu, 2016), and few studies have examined the CEE of prefecture-level cities (Yuan et al, 2013). Second, previous studies on the factors that influence CEE mainly focus on market-oriented reforms (Lin and Du, 2015), environmental regulations (Zhao et al, 2015), technology and management factor (Cui and Li, 2015;Qin et al, 2017), while few of them focus on urbanization.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China

Huang

Kwan

et al. 2018

Journal of Cleaner Production

142

View full text Add to dashboard Cite

a b s t r a c tCities have been one of the most important areas of CO 2 emissions. It is increasingly important to research the effect of urbanization on CO 2 emissions, especially in large emerging and developing economies, due to the indispensable need for understanding the effect of urbanization on CO 2 emissions, evaluating carbon reduction tasks and providing the scientific basis for low-carbon urbanization. Utilizing a balanced panel dataset in the Yangtze River Delta (YRD), China, during the period of 2000e2010, this paper employed data envelopment analysis (DEA) window analysis and a spatial lag panel Tobit model to investigate the effect of urbanization on CO 2 emissions efficiency (the ratio of the target CO 2 emissions to the actual CO 2 emissions). The results show that the average CO 2 emissions efficiency was 0.959 in 2010, and CO 2 emissions efficiency ranged from 0.816 to 1 and exhibited spatial clustering in the region. The larger potential of CO 2 emissions reduction appeared in Zhenjiang and Yangzhou, indicating that more CO 2 emissions reduction tasks should be allocated to these two cities. Urbanization has negative effects on improving CO 2 emissions efficiency, and there is a U-curve relation between CO 2 emissions efficiency and urbanization, indicating that CO 2 emissions efficiency decreases at the early stage of urbanization, then increases when urbanization reach a high level. There is spatial spillover effect among the prefecture-level cities, suggesting that different prefecture-level governments should coordinate with each other to improve CO 2 emissions efficiency in the whole area. Gross domestic product (GDP) per capita also plays a markedly positive role in improving CO 2 emissions efficiency. This research highlights the effect of urbanization on CO 2 emissions efficiency and the importance of improving CO 2 emissions efficiency in developing countries.

show abstract

Section: Variable and Software Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China

Huang

Kwan

et al. 2018

Journal of Cleaner Production

142

View full text Add to dashboard Cite

show abstract

“…The first is to expand the scope of efficiency research. The analysis of urban scales is more granular than provincial ones [80] and more systematic than industrial parks [81], businesses [41], and industries [82]. A city is an important carrier of human activities in production and life.…”

Section: Implications For Policy-makingmentioning

confidence: 99%

A Road to Sustainable Development of Chinese Cities: A Perception of Improving Urban Management Efficiency Based on Two-Level Production Factors

Zhang

Chu

et al. 2017

Sustainability

View full text Add to dashboard Cite

Abstract:It is an inevitable requirement of regional governance and sustainable development to improve urban management efficiency (UME). Different from the previous studies, this paper gives it a new meaning based on the production factors theories. Then the paper analyzes the response of UME to the primary production factors (PPFs) characterized by the traditional production factors theory (land, labor, and capital), and the expanded production factors (EPFs) reflected by the modern production factors theory (energy and ecology). By analyzing UME in China's 334 cities on global and local scales, this paper found four characteristics of UME: (1) the striking spatial differences; (2) the strong correlation between management models; (3) the evident development emphasis; and (4) the weak matching linkage. Finally, we put forward the countermeasures of spatial governance, including strengthening the agglomeration effect, promoting diversified development models on different scales, and accelerating resource coordination and sharing.

show abstract

“…Then, the radial stochastic model was extended to a non-radial model for measuring pure energy use and CO 2 emissions efficiencies. The proposed approach has been applied to evaluate regional efficiencies of energy use and CO 2 emissions in China [4]. Meanwhile, the level of energy efficiency was sketched out and explained from an economic perspective via the theoretical framework [5].…”

Section: Literature Reviewmentioning

confidence: 99%

Promotion Potentiality and Optimal Strategies Analysis of Provincial Energy Efficiency in China

et al. 2016

View full text Add to dashboard Cite

Abstract:In order to meet the dual requirements of economic development and energy consumption, the Chinese government has adopted a series of measures and policies to improve energy efficiency. However, the developing characteristics are not the same in different regions. Thus, it is necessary to analyze the actual energy efficiency levels in a more targeted manner. In this paper, 30 provinces in China will be adopted to study energy efficiency based on the statistical data from National Energy Administration and National Bureau of Statistics. With the trends of Chinese energy consumption and economy development, the Lorenz curve between Chinese energy consumption and GDP is fitted firstly. The Lorenz coefficient (0.1562) shows that the energy allocation in China is neither reasonable nor balanced. Then, by cluster analysis, the regions of different provinces are newly divided into five divisions from the dimensions of economy and energy, i.e., (high development level and high consumption level, HH), (moderate development level and moderate consumption level, MM), (moderate development level and low consumption level, ML), (low development level and low consumption level, LL), and (low development level and moderate consumption level, LM). Based on the division results, the provincial promotion potentialities are estimated quantitatively according to the absolute convergence feature of energy efficiency promotion. The provinces that have more promotion potentialities of energy efficiency are located, such as Hebei (56.29%) in division (HH), Liaoning (38.15%) in division (MM), Anhui (44.17%) in division (ML), Ningxia (71.63%) in division (LL), and Xinjiang (35.26%) in division (LM), According to the different provincial potentialities, energy efficiency in China needs to improve more, but the improvement approaches should be specific and differential. Driven by technology, policy and mechanism, and industrial restructuring, the Chinese economy and energy resources should be integrated afresh to promote the energy efficiency level. Some optimal strategies on energy efficiency promotion are discussed, finally, aiming to provide effective references for the Chinese government to make relative policies. The study proposes a new perspective for provincial energy efficiency research which can also provide a reference for other countries.

show abstract

The energy-environment efficiency of road and railway sectors in China: Evidence from the provincial level

Cited by 72 publications

References 54 publications

The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China

The effect of urbanization on carbon dioxide emissions efficiency in the Yangtze River Delta, China

A Road to Sustainable Development of Chinese Cities: A Perception of Improving Urban Management Efficiency Based on Two-Level Production Factors

Promotion Potentiality and Optimal Strategies Analysis of Provincial Energy Efficiency in China

Contact Info

Product

Resources

About