scholarly journals Does the Opening of High-Speed Railway Lines Reduce the Carbon Intensity of China’s Resource-Based Cities?

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4648
Author(s):  
Zhipeng Tang ◽  
Ziao Mei ◽  
Jialing Zou

The carbon intensity of China’s resource-based cities (RBCs) is much higher than the national average due to their relatively intensive mode of development. Low carbon transformation of RBCs is an important way to achieve the goal of reaching the carbon emissions peak in 2030. Based on the panel data from 116 RBCs in China from 2003 to 2018, this study takes the opening of high-speed railway (HSR) lines as a quasi-experiment, using a time-varying difference-in-difference (DID) model to empirically evaluate the impact of an HSR line on reducing the carbon intensity of RBCs. The results show that the opening of an HSR line can reduce the carbon intensity of RBCs, and this was still true after considering the possibility of problems with endogenous selection bias and after applying the relevant robustness tests. The opening of an HSR line is found to have a significant reducing effect on the carbon intensity of different types of RBC, and the decline in the carbon intensity of coal-based cities is found to be the greatest. Promoting migration of RBCs with HSR lines is found to be an effective intermediary way of reducing their carbon intensity.

2021 ◽  
Vol 13 (14) ◽  
pp. 7603
Author(s):  
Xiangdong Liu ◽  
Guangxi Cao

The key to transforming China’s economy from high-speed growth to high-quality development is to improve total factor productivity (TFP). Based on the panel data of China’s listed companies participating in PPP (Public–Private Partnerships) projects from 2010 to 2019, this paper constructs the time-varying DID method to test the impact of participation in PPP projects on the company’s TFP empirically, explore the mechanism of the effect of participation in PPP projects on the company’s TFP, and then conduct heterogeneous analysis from four perspectives: region, industry, ownership form, and operation mode. The empirical results show that participation in PPP projects can significantly promote the growth of the company’s TFP, which mainly comes from the promotion of the innovation level of listed companies and the alleviation of financing constraints by participating in PPP projects. In addition, participation in PPP projects has a significant impact on TFP of listed companies in the eastern region, listed companies in the secondary and tertiary industries, state-owned listed companies, and listed companies participating in PPP projects under the BOT mode.


Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2713-2735 ◽  
Author(s):  
Xiaomin Fan ◽  
Yingzhi Xu ◽  
Yongqing Nan ◽  
Baoli Li ◽  
Haiya Cai

Purpose The purpose of this paper is to analyse the impact of high-speed railway (HSR) on industrial pollution emissions using the data for 285 prefecture-level cities in China from 2004 to 2016. Design/methodology/approach The research method used in this paper is the multi-period difference-in-differences (DID) model, which is an effective policy effect assessment method. To further address the issue of endogeneity, the DID integrated with the propensity score matching (PSM-DID) approach is employed to eliminate the potential self-selection bias. Findings The results show that the HSR has significantly reduced industrial pollution emissions, which is validated by several robustness tests. Compared with peripheral cities, HSR exerts a greater impact on industrial pollution emissions in central cities. In addition, the mechanism test reveals that the optimised allocation of inter-city industries is an important channel for HSR to mitigate industrial pollution emissions, and this is closely related to the location of HSR stations. Originality/value Previous studies have paid more attention to evaluating the economic effects of HSR, however, most of these studies overlook its environmental effects. Consequently, the impact of HSR on industrial pollution emissions is led by using multi-period DID models in this paper, in which the environmental effects are measured. The results of this paper can provide a reference for the pollution reduction policies and also the coordinated development of economic growth and environmental quality.


Author(s):  
Minling Feng ◽  
Chaoxian Wu ◽  
Shaofeng Lu ◽  
Yihui Wang

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jing Wang ◽  
Yinghan Wang ◽  
Yichuan Peng ◽  
Jian John Lu

Purpose The operation safety of the high-speed railway has been widely concerned. Due to the joint influence of the environment, equipment, personnel and other factors, accidents are inevitable in the operation process. However, few studies focused on identifying contributing factors affecting the severity of high-speed railway accidents because of the difficulty in obtaining field data. This study aims to investigate the impact factors affecting the severity of the general high-speed railway. Design/methodology/approach A total of 14 potential factors were examined from 475 data. The severity level is categorized into four levels by delay time and the number of subsequent trains that are affected by the accident. The partial proportional odds model was constructed to relax the constraint of the parallel line assumption. Findings The results show that 10 factors are found to significantly affect accident severity. Moreover, the factors including automation train protection (ATP) system fault, platform screen door and train door fault, traction converter fault and railway clearance intrusion by objects have an effect on reducing the severity level. On the contrary, the accidents caused by objects hanging on the catenary, pantograph fault, passenger misconducting or sudden illness, personnel intrusion of railway clearance, driving on heavy rain or snow and train collision against objects tend to be more severe. Originality/value The research results are very useful for mitigating the consequences of high-speed rail accidents.


Innotrans ◽  
2021 ◽  
pp. 3-7
Author(s):  
Nakip Z. Sabirov ◽  
◽  
Shamil K. Valiev ◽  

The article deals with the issues of resource saving on railways. Approaches to the definition of the essence of resource saving are highlighted. The influence of high-speed railway lines on the change in the structure of labor resources is revealed. The tasks of improving the resource management system and specific resources on railway transport are defined. Special attention is paid to railway automation and telemechanics systems, which will significantly reduce the labor costs of the HSR. The specific energy costs for different types of transport and per passenger-kilometer are given.


2019 ◽  
Vol 7 (2) ◽  
pp. 99-114 ◽  
Author(s):  
Yun Zhao ◽  
Chongren Bi

Abstract The calculation for the influence of high-speed railway on knowledge spillover is based on the results of global instantaneous equilibrium in the mechanism explanation of knowledge spillover. In real production, the interaction between the high-speed railway and the regional innovation system is dynamic and local. In order to simulate the impact of high-speed railway on innovation activities in the time dimension, it is necessary to simulate scenarios under appropriate parameter assumptions. Based on the interaction of economic participants, a discrete evolutionary simulation model is established, which is helpful to predict and estimate the evolution of spatial effect of high-speed railway according to the theory of cellular automata. It is concluded that high-speed railway accelerates the formation of knowledge innovation industry cluster in the region in the process of regional knowledge innovation and evolution. Under the influence of high-speed railway, the node city will gradually evolve into a regional innovation center. By comparing the production evolution of knowledge innovation system with and without high-speed railway, the results show that high-speed railway has a more significant impact on knowledge spillover in higher knowledge privatization environment. Under the background of low labor migration rate, high-speed railway has increased the potential of regional innovation to external knowledge spillover. In the case of higher labor migration rate, the convergence rate of influence of high-speed railway on the concentration of innovation is faster.


2020 ◽  
Vol 10 (4) ◽  
pp. 473-496
Author(s):  
Hongling Guo ◽  
Keping Wu

PurposeThis study aims to investigate how opening high-speed railways affects the cost of debt financing based on China's background.Design/methodology/approachUsing panel data on Chinese listed firms from 2008 to 2017, this study constructs a quasi-natural experiment and adopts a difference-in-difference model with multiple time periods to empirically examine the relation between the high-speed railway openings and debt financing cost.FindingsOur results show that opening high-speed railways reduces the cost of debt financing, and this negative correlation is more significant in non-state firms, firms with weaker internal control, and firms that hire non-Big Four auditors. Besides, we explore the impact mechanisms and find that opening high-speed railways improves analyst attention, institutional investor participation, and information disclosure quality, which in turn lowers the cost of debt financing.Research limitations/implicationsThe results imply that the opening of high-speed railways helps to alleviate the information asymmetry and adverse selection between firms and creditors and ultimately reduces the cost of corporate debt financing.Practical implicationsThis paper can inform firms and stakeholders about the impact of opening high-speed railways on debt financing cost: it improves the information environment, reduces the geographical location restrictions of debt financing, ensures the reasonable pricing of corporate debt, and thus promotes the healthy and sound development of the debt market.Originality/valueThis paper provides theoretical support and empirical evidence for the impact of infrastructure construction on the information environment of the debt market in China, which enriches the research on the “high-speed railway economy.” In addition, as an exogenous event, the opening of high-speed railways instantly shortens the time distance between firms and external stakeholders, which gives us a natural environment to conduct empirical research, thus providing a new perspective for financial research on firms' geographical location.


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