Transportation Industry In China Research Articles

The impact of CO2 emission synergy on PM2.5 emissions and a dynamic analysis of health and economic benefits: A case study of China's transportation industry

PM2.5 is the primary pollutant that worsens air quality and has many adverse effects on human health and the social economy. Measures to reduce CO2 can synergistically reduce PM2.5. This paper focuses on the transportation industry in China, which has high carbon and high pollution emissions. It initially evaluates the synergistic effect of CO2 emissions and the impact of other socio-economic drivers on PM2.5 emissions. Subsequently, it provides a comparative analysis of the projected trajectories of PM2.5 emissions, along with the associated health and economic repercussions, across three scenarios from 2021 to 2030. The results show that: (1) The synergy effect of CO2 reduction emerges as the primary driver for mitigating PM2.5 emissions, whereas economic growth stands as the primary contributor to their escalation. (2) Both the green development (GD) scenario and the technological breakthrough (TB) scenario forecast a continuous decline in PM2.5 in 2021–2030. By 2030, the GD and TB scenarios forecast a reduction of 32,000 and 39,500 tonnes of PM2.5, respectively, compared to the business-as-usual (BAU) scenario. (3) By 2030, in contrast to the BAU scenario, premature deaths will be reduced by 39.55%, and economic losses will be reduced by 234.738 billion CNY in the GD scenario; premature deaths will be reduced by 50.04%, and economic losses will be reduced by 263.107 billion CNY in the TB scenario.

Efficiency evaluation of China's transportation system considering carbon emissions: Evidence from big data analytics methods

China's transportation sector is a vital link between production and consumption, but it also has issues with low efficiency, high carbon emissions, and technological bottlenecks. To improve efficiency and provide actionable recommendations and strategies, this study first constructs a comprehensive evaluation index system to gauge the transportation sector's inputs using panel data from different Chinese provinces from 2007 to 2021. Within the assessment system, the principal component analysis (PCA) method is used to reduce the dimension of the indexes, thereby yielding a set of adjusted inputs. Subsequently, the transportation system efficiency (TSE) is evaluated using the super-efficiency SBM-DEA model, which includes unexpected outputs such as carbon emissions, and three-stage DEA modifies the efficiency. Then, we calculate the Malmquist-Luenberger index (TML) and its components: technological change (TTC) and technological efficiency change (TEC). Lastly, the influential factors impacting TSE are analyzed via a truncated regression Tobit model. The following are the conclusions: (1) The transportation industry in China exhibits inefficiency, and the average TSE in Stage I and III is 0.91 and 0.93, respectively. TSE is underestimated due to the influence of external environmental factors and inefficiencies in management in Stage I. (2) TSE in the eastern area also produces significant carbon emissions that surpass the national average. At the same time, other regions face efficiency limitations due to geographical constraints and management obstacles. (3) Insufficient technical capacity is a major cause of inefficiency in the transport sector and is prevalent in the northeast, west, and central regions. (4) Population growth and income per capita advancements foster transportation industry development, while increased GDP, fiscal revenues, and traffic accidents contribute to declining efficiency. The study above findings serve as a foundation for regional and national management initiatives and policies to enhance transportation effectiveness.

Comparative Analysis and Construction of Evaluation Indexes of Civil Aviation Service Quality

Scientific and effective evaluation of civil aviation service quality is of great significance to improve customer satisfaction and the main competitiveness of civil aviation enterprises. In combination with the core ideas of the service quality model, this paper compares and analyzes the service quality evaluation process of airports and airlines from the two dimensions of service contents and evaluation indexes on the basis of literature arrangement and summary. Based on the SERVQUAL model and the "China Civil Airport Service Quality Evaluation Index System", the related contents of the system is appropriately revised combined with the characteristics of airport and airline services. To this end, the service quality evaluation indexes of airports and airlines are respectively built. The research shows that there are indeed some differences in five dimensions of evaluation indexes between airports focusing on ground services and airlines responsible for in-flight services. Only when scientific and reasonable evaluation index system for the quality of civil aviation transportation services is established for evaluation in line with the characteristics of civil aviation transportation services in the two scenarios, can the overall service level of passenger transportation in civil aviation industry be upgraded to achieve the high-quality development of civil aviation transportation industry in China.

Transfer of embodied carbon emissions from provincial transportation industry in China

This study employs a multi-regional input-output (MRIO) model to measure these emissions and examines the growth and transfer patterns of embodied carbon in the transportation sector across different regions of China. Then we utilize Structure Decomposition Analysis (SDA) to identify the driving factors behind the observed emissions patterns. The findings of the study indicate that the transfer of inter-provincial transportation embodied carbon emissions follows a general trend of shifting from economically developed areas to underdeveloped areas along the industrial chain. The study also highlights that the per capita demand structure plays a crucial role in driving the increase in transportation embodied carbon emissions. On the other hand, the study identifies the direct carbon emission coefficient as a key factor that inhibits the rise in transportation embodied carbon emissions.

Provincial energy and environmental efficiency analysis of Chinese transportation industry with the fixed-sum carbon emission constraint

Measuring energy and environmental performance has become a significant public concern, owing to increasingly severe environmental pressures. The transportation industry plays an essential role in modern economic and social development and has caused many environmental problems due to its huge energy consumption and carbon emissions. This study examined the provincial energy and environmental efficiency (EEE) of the transportation industry in China, considering a newly announced dual-carbon policy target with a total fixed-sum (FS) constraint on carbon emissions. The transportation industry is modeled as a parallel production system with passenger transportation and freight transportation. Because both subsystems would inevitably generate carbon dioxides, a parallel transportation system is innovatively considered with a FS constraint of shared carbon emissions under the dual-carbon policy target. This study contributes to the literature by measuring the EEE of the Chinese transportation industry under the FS constraint of shared carbon emissions in a parallel system. To address this problem, we propose a novel parallel data envelopment analysis (DEA) approach that considers FS shared undesirable outputs (FSSUO) based on the generalized equilibrium efficient frontier (GEEF) concept. The GEEF was obtained by minimizing the total adjustment of carbon emissions and used to calculate the overall parallel transportation efficiency. Furthermore, we developed a decomposition framework to estimate the individual passenger transportation performance and freight transportation performance. To the best of our knowledge, this is the first attempt to study the fixed-sum outputs (FSO) in a parallel production system, whereas previous studies addressed FSO in either black-box or two-stage series production systems. Finally, we apply the proposed approach to empirically analyze the EEE of the Chinese transportation industry at the provincial level from 2015 to 2019 and provide valuable empirical findings and policy suggestions.

Carbon peak forecast and low carbon policy choice of transportation industry in China: scenario prediction based on STIRPAT model.

As the second largest CO2 emission department, transportation industry's carbon peak and carbon reduction are very important for China to smoothly achieve carbon peak by 2030 and carbon neutrality by 2060. This paper analyzes the influencing factors from the perspectives of population, economy, technology and transportation equipment structure, subdivides 20 scenarios to predict the carbon emissions of the transportation industry of the whole China and various regions based on scenario analysis method, explores the carbon peak path, and puts forward corresponding policy recommendations. The study found that (1) from the overall trend of carbon emissions, the total carbon emissions of China's transportation industry showed an overall upward trend from 2010 to 2019 while the growth rate of carbon emissions showed a downward trend. (2) From the perspective of influencing factors, population size, urbanization rate, economic scale, traffic development, traffic carbon intensity, and highway mileage have positive effect on the growth rate of China's transportation CO2 emissions. The increase in the proportion of energy structure and railway cargo turnover has the negative effect on carbon emissions in the transportation industry. (3) From the prediction results at the national level, technological breakthroughs have a limited effect on carbon emission reduction in China's transportation industry, while structural equipment optimization has the most significant effect on its emission reduction. When technological breakthroughs and equipment structure optimization are carried out simultaneously, the carbon emission reduction effect is the best. The carbon peak of China's transportation industry would achieve as early as 2030, with a peak range of 70,355.54-84,136.17 million tons. (4) From the perspective of prediction results at the regional level, the provinces with rapid population growth and per capita GDP growth, the provinces with rapid population growth and per capita GDP growth, and the provinces with low population growth and per capita GDP growth should control their average annual growth rate of carbon emissions of the transportation industry to 1.13%, 0.72% and 0.58% respectively in 2019-2030, in order to ensure the achievements of the carbon peak target.

A Combined Evaluation Method of Corporate Social Responsibility Based on the Difference and Similarity: A Case Study of Transportation Industry in China

Currently, it is becoming more essential for a company to operate in an economically, socially and environmentally sustainable manner. This study aims to evaluate corporate social responsibility (CSR) in China’s transportation industry by applying indicator weighting approaches. This study evaluated 68 transportation companies with 82 associated CSR indicators. Firstly, this paper established an indicator system, including seven criteria layers that conform to the characteristics of the Chinese transportation industry. Secondly, by integrating the G1 method, standard deviation method and CRITIC (criteria importance though intercriteria correlation) approach, a combined weighting method, CWMDS (combined weighting method based on the combination of difference and similarity), was constructed, which embodies the two goals of “horizontal similarity and vertical difference”. The experimental results show that CWMDS achieves better results in many aspects. The empirical results show that the air transportation subindustry was the best in CSR performance while the high-speed transportation subindustry was the worst. Finally, this paper put forward some policy suggestions to promote China’s transportation enterprises to fulfill their social responsibility.

Energy dissipation characteristics of an in-chamber longitudinal culvert system with three-layer side ports designed for a large-scale lock with 60m water head

With the rapid development of the water transportation industry in China, the scale of ships navigating in the inland waterway is increasing. However, the water head formed by dams is very high, especially for the hydroelectric projects constructed in the upper mountain river. Therefore, it is critically urgent to build several high-head and large-scale locks. Moreover, when the water head is increased to 60 m, huge water energy could be generated and then introduced into the corresponding lock chamber if the valve operating time is limited. This paper presented the in-chamber longitudinal culvert system with three-layer side ports to efficiently dissipate the water energy to ensure safe mooring conditions for ships during a lock operation. A three-dimensional CFD model for 1/4 local region of the corresponding chamber was developed to predict its hydraulic behavior. The numerical simulations were conducted to examine the effect of the vertical spacing between side ports on the energy dissipation result. Results showed that good energy dissipation performance was gained when the relative vertical spacing was set B/D=0.25 (B is the vertical spacing between side ports, D is the inner height of the culvert). Furthermore, the energy dissipation mechanism of this arrangement was presented based on the results of a three-dimensional hydraulic characteristic. In addition, the corresponding dissipation result of the present arrangement was compared with those of the single-layer and two-layer side ports. The dissipation performance of the present design was found to be the best if all the side ports’ cross-section area of each arrangement keeps the same.

A novel simultaneous grey model parameter optimization method and its application to predicting private car ownership and transportation economy

<p style='text-indent:20px;'>Common models used for grey system predictions include the GM (1, 1), GM (1, N), and GM (N, 1). Their whitening equations are ordinary differential equations. However, the objects and factors are generally characterized by mutual restrictions and variable interactions. Thus, the relationship cannot be adequately described using a single differential equation. Therefore, this paper proposes a novel simultaneous grey model. A parameter optimization method is developed, and the time response equation of a simultaneous grey model with 2 interactive variables is derived. The model has high simulation and prediction precision because the parameter optimization's objective function minimizes the average relative errors of the simulation and prediction. The proposed model with two mutually influencing variables is used to predict the private car ownership and the added value of the transportation industry in China. The results indicate that the simultaneous grey model has significantly higher precision than the conventional single grey model. The novel model and method improve the grey modeling system and are significant for in-depth studies, popularization, and application of grey models.</p>

Study on the Factors Influencing on the Carbon Emissions of Shaanxi Province’s Transportation Industry in China

Carbon peaking in the transportation industry is of great significance to achieving the goals of carbon peaks and carbon neutrality. By correcting the energy consumption data of Shaanxi province’s transportation industry in China, adding the energy consumption data of non-operating vehicles to the total energy consumptions and building a more accurate calculation model for the carbon emissions of provincial transportation industry, this paper studies the contribution of the population size, the economic growth, the energy intensity, the energy structure, and the industrial scale of transportation to the carbon emissions, respectively, through the construction of a Logarithmic Mean Divisia Index (LMDI) model. The result shows that the carbon emissions of Shaanxi province’s transportation industry in China increased from 15.730 million tons to 24.652 million tons from 2009 to 2019. Among them, the carbon emissions of the non-operating activities grew rapidly, increasing from 2.694 million tons to 10.334 million tons in the past 10 years. Within the research range, the economic growth effect is the most important factor driving the growth of the carbon emissions of Shaanxi province’s transportation industry in China, increasing total carbon emissions by 22.701 million tons. The energy intensity effect and the industrial scale effect of transportation play the main role in inhibiting the carbon emissions of Shaanxi province’s transportation industry in China, with a cumulative reduction in the total carbon emissions by 13.869 million tons.

The Shared Transportation Industry in China: Examining the Influence of Regional Environmental Factors on New Venture Formation

China’s shared transportation industry is leading innovation, driving employment, and promoting regional economic growth. China’s aggressive efforts to promote the development of various transportation sectors motivate our investigation of this emerging industry. We examine the influence of regional environmental factors on new venture formation using a dataset encompassing newly established bike-sharing startups in 257 cities in China from 2015 to 2019. The empirical results show that entrepreneurial capital, entrepreneurial support policies, and urban auxiliary infrastructure positively impact the formation of new ventures. However, no significant relationship exists between industrial policy, competitive urban infrastructure, and new business formation. This study expands the scope of the existing research studying the characteristics of entrepreneurial space, offers inspiration for future startups entering the field of shared transportation in choosing entrepreneurial locations, and provides theoretical guidance for the government in formulating policies to attract entrepreneurial activities.

A Race Between Economic Growth and Carbon Emissions: How Will the CO2 Emission Reach the Peak in Transportation Industry?

Promoting carbon emissions of the transportation industry to reach the peak as soon as possible is an effective way to control carbon emissions in China. Combined with the logarithmic mean Divisia index (LMDI) model and the Tapio decoupling model, this paper tries to predict and analyze the time, path, and quality of carbon peaking in the transportation industry in China and its eastern, central, and western regions. The research shows the following: 1) Under the “benchmark scenario,” the transportation industry in China and its three regions will not achieve the international commitment of achieving peak carbon emissions by 2030. 2) Under the “radical scenario,” the peak time of China’s transportation industry can be reached in 2027, which is 5 years earlier, 10% peak value lower than that in the “benchmark scenario.” In that scenario, in transportation industry, the eastern region will reach the carbon peak in 2025 and the central and western regions will both reach the carbon peak in 2028. By then, the peak quality of carbon emissions will be better than that under the “benchmark scenario” in transportation industry. This paper can provide theoretical support for promoting carbon emission reductions and carbon peaking in China’s transportation industry.

The Carbon Emission Reduction Effect of Technological Innovation on the Transportation Industry and Its Spatial Heterogeneity: Evidence from China

The carbon reduction effect of technological innovation in the transportation industry is conducive to China’s anticipated realization of carbon neutrality. Therefore, we evaluated carbon emission reduction effect of technological innovation in the transportation industry in China. Based on the panel data of 30 sample provinces in China (excluding Hong Kong, Macao, Taiwan and Tibet) from 2012 to 2018, using the Moran’I index and Getis-Ord Gi index, this paper analyzes the evolutionary trend and spatial autocorrelation of carbon emission in the transportation industry, and analyzes the impact of technological innovation on carbon emission levels of the transportation industry and its spatiotemporal differences by using the geographical and temporal weighted regression (GTWR) model by using ArcGIS 10.4 software. The conclusions are as follows: The carbon emission level of China’s transportation industry generally has been rising steadily, showing a spatial distribution pattern of high emissions in the east and low emissions in the west. The cold spots are concentrated in the western region, and the hot spots are situated in the central and eastern regions. Technological innovation has a carbon reduction effect on the transportation industry in the eastern and north-eastern regions, while the effect in other regions is not obvious. However, there is an obvious “inverted U-shaped” relationship between technological innovation and the transportation industry’s carbon emissions. The technological innovation in the transportation industry will have a significant carbon reduction effect after breaking through the technical pain points. This carbon reduction effect has a higher effect on the western region than on the eastern region. In addition, the economic development level, the fiscal expenditure proportion of the transportation industry, the higher education level, and the proportion of fixed asset investment in the transportation industry have played a positive role in reducing carbon in the transportation industry, but the spatial heterogeneity of this carbon reduction effect is relatively strong. Therefore, during the “14th Five-Year Plan” development period in China, it is necessary to continuously promote the low-carbon development of the transportation industry with technological innovation, while highlighting the differentiated carbon reduction governance, and consolidating the role of talents and fiscal support.

Impact of COVID-19 pandemic on energy consumption and carbon dioxide emissions in China's transportation sector

The COVID-19 pandemic has put the whole world in a great lockdown and greatly changed our lives. The lockdown caused by the COVID-19 pandemic has greatly affected the transportation industry in China. In this paper, energy consumption and carbon dioxide emissions of fuel vehicles and battery electric vehicles in China during the COVID-19 pandemic was estimated and analyzed. The impact of COVID-19 pandemic was analyzed. The study period is taken from September 2019 to April 2020, and the period from September 2018 to August 2019 is taken for comparison. Moreover, energy consumption and CO2 emissions of fuel vehicles during SARS epidemic was also analyzed. The related study period is taken from January 2003 to August 2003. The results show COVID-19 has a much larger impact on transportation energy consumption and CO2 emissions than SARS. After the COVID-19 pandemic, energy conservation and emission reduction still have a long way to go. Determining the energy consumption and emissions in transportation sector during the COVID-19 pandemic will provide the government with a reference for future energy conservation and emission reduction in transportation sector and the further promotion of battery electric vehicles.

Treatment Design and Construction Strategy for Tunnel Mud and Water Inrush Disaster

With the rapid development of the transportation industry in China, the number and scale of tunnel construction are increasing. Tunneling through fault zones and other complex geological environments is becoming more and more common. In the construction of highway tunnels, due to the special geographical environment and complex geological conditions, mud and water inrush often occur in the tunnel. Water inrush disasters pose a major risk to the construction of highway tunnels and affect the normal construction of highway tunnels. This paper combines the engineering background of the tunnel mud and water inrush accidents, carries out evaluation on the accident treatment measures and the treatment efficiency, and summarizes the main concerns in the construction process and the technical guidelines for dealing with the tunnel mud and water inrush.

Stepwise Improvement for Environmental Performance of Transportation Industry in China: A DEA Approach Based on Closest Targets

Transportation is regarded as an industry with high energy consumption and high CO2 emissions. Little attention has been paid to the environmental performance improvement of China’s transportation industry, especially in a stepwise improvement way. In this study, we first apply the closest targets DEA method to evaluate the environmental performance in the transportation industry of 30 provincial-level regions in China’s mainland from 2010 to 2017. Then, we incorporate the closest targets and context-dependent DEA model and thus conform a stepwise projection path for each inefficient province to improve environmental performance with less effort by the way of identifying a sequence of intermediate closest targets. The empirical study shows that the environmental performance of the transportation industry obtained from the closest targets model is greater than that obtained from the SBM model for each province. Among the three areas, the eastern area performs the best in environmental performance followed by the central region and western region. Shanghai has the best environmental performance. Additionally, compared with conventional DEA models, the proposed stepwise improvement method can generate easier and closer achieved targets for the inefficient provinces. Hainan, Yunnan, and Xinjiang provinces have the lowest environmental performance, which need four steps to achieve efficiency.

Study on safety evaluation of hazardous chemicals transportation industry in Capital city based on principal component analysis and cluster analysis

With the reform of chemical transportation industry accelerating, the safety evaluation of chemical transportation industry in China is becoming more and more standardized. Based on the theory of big data analysis and SPSS software as a platform, first of all, of the Beijing 91 the system construction and management of dangerous chemicals transportation enterprises, safety culture, safety production standardization 24 safety evaluation indexes such as principal component analysis, it is concluded that safety training basic requirements, loading and unloading operation, parking lot, civil air defense, vehicle dynamic supervision, system construction and management, safety production standardization, pilot eight kinds of factors as the main indexes for safety assessment. After using the eight indexes of 91 clustering analysis for transport enterprises, the enterprise is divided into five clusters of reasonable results, through the summary of common characteristics within the same cluster enterprises, it is concluded that the handling operation index plays an important role in classification for transport enterprises such as conclusion, can provide reference for other areas. At the same time, the conclusion can be used as a reference for the follow-up safety evaluation of hazardous chemical transportation enterprises, so as to achieve the purpose of targeted safety inspection.

Total-factor energy efficiency change of the road transportation industry in China: A stochastic frontier approach

The mismatch between the supply and consumption of energy indicates that it is important to promote energy efficiency in the road transportation industry which is high in energy consumption. This paper employs a stochastic frontier approach to measure the total-factor energy efficiency (TFEE) change of the road transportation industry in China. Then, a novel two-dimensional matrix is used to illustrate the energy efficiency of the road transportation industry in China’s eight economic areas. The combination of these approaches leads to the following conclusions: (a) The annual TFEE growth rate of Chinese road transportation systems has slowed down in recent years, but the average annual TFEE growth has reached 17.34%. (b) Both technological change and scale efficiency change boost the TFEE growth, and technical efficiency change hinders the TFEE growth. (c) Almost all regional road transportation industry TFEE scores increased during the study period, but the growth rates were significantly higher in the Northern Coastal and Eastern Coastal areas than in other areas. Finally, this paper suggests increasing investment in highways to expand the operation scale, developing advanced technology for high-quality development of the industry, and carefully designing measures to improve transportation technical efficiency according to regional economic development orientations.

Exploring the growth-adjusted energy-emission efficiency of transportation industry in China

Abstract China's transportation industry has achieved significant progress but also proved one of China's primary energy- and carbon-intensive industries. Under this circumstance, it is necessary to assess the level of energy-saving and emission reduction (ESER) of China's transportation industry. Therefore, based on the panel data of China's 30 provinces during 2008–2017, this paper develops a new DEA model to evaluate the growth-adjusted energy-emission efficiency of transportation industry in China. The results show that, first of all, the growth-adjusted energy-emission efficiency of China's transportation industry is approximately 0.5543 during the sample period, and the provinces with high efficiency in their transportation industries are mainly concentrated in the central region and the Beijing-Tianjin-Hebei region; in particular, the central region takes the lead in low-carbon and energy-saving (LCES) technology of transportation industry. Second, during the sample period, the overall growth-adjusted energy-emission efficiency of China's transportation industry improves by 7.08% on average. The efficiency of the transportation industry in the eastern region improves the most, i.e., 28.99%. Finally, when evaluating the energy and/or environment-related efficiency of transportation industry, ignoring the transportation growth factors will underestimate the sustainability of transportation industry.

Measuring performance of road transportation industry in China in terms of integrated environmental efficiency in view of Streaming Data

Road transportation industry not only promotes economic development, but also brings many environmental issues in China. It is necessary to evaluate the integrated environmental efficiency of road transportation industry, including carbon dioxide emissions, traffic accident and traffic noise which is a Steaming Data. In this study, a parallel DEA model with sub-system preference is proposed to measuring the integrated environmental efficiency of road transportation industry in 2013–2017 considering various undesirable outputs. Then, the convergence analysis approach is employed to investigate the regional differences in terms of efficiency of road transportation. The empirical results show that the overall integrated environmental efficiency underperformed nationwide, and the passenger transportation sub-system outperformed freight transportation when the latter is restricted in some hours. From a regional perspective, the efficiency performances show downward trends in areas eastern, central and western. The passenger transportation sub-system outperforms in eastern area and the freight transportation outperforms in central area. Furthermore, the convergence analysis results indicate that the integrated environmental efficiency in eastern and western areas not only converged to their own stable levels but also that the differences in the integrated environmental efficiency between eastern and western areas are condensing. The contributions of this study lie in not only proposing a parallel DEA model with sub-system preference and considering the streaming data, but also providing suggestions to improving the road transportation industry in terms of integrated environmental efficiency. Finally, the research limitations and further research directions were conducted.