Using Grey Relational Analysis to Evaluate Energy Consumption, CO2 Emissions and Growth Patterns in China’s Provincial Transportation Sectors

Abstract

The transportation sector is a complex system. Collecting transportation activity and the associated emissions data is extremely expensive and time-consuming. Grey Relational Analysis provides a viable alternative to overcome data insufficiency and gives insights for decision makers into such a complex system. In this paper, we achieved three major goals: (i) we explored the inter-relationships among transportation development, energy consumption and CO2 emissions for 30 provincial units in China; (ii) we identified the transportation development mode for each individual province; and (iii) we revealed policy implications regarding the sustainable transportation development at the provincial level. We can classify the 30 provinces into eight development modes according to the calculated Grey Relational Grades. Results also indicated that energy consumption has the largest influence on CO2 emission changes. Lastly, sustainable transportation policies were discussed at the province level according to the level of economy, urbanization and transportation energy structure.

Intelligent Multi-Objective Public Charging Station Location with Sustainable Objectives

“…The solutions' performances are evaluated by three indicators corresponding to the three objective functions presented in Section 3.2, including the number of CSs, daily average CO 2 emissions reduction (daily ACER, unit: tons per day) and average waiting time (AWT, unit: hours per trip). The number of CSs and AWT are the values of objective functions (1) and (3). Daily ACER is the CO 2 emissions reduction generated by PHEVs in the case area compared to using gasoline in all trips, which is calculated by formula (27).…”

“…The model achieves a balanced trade-off among three sustainable objectives ( f 1 , f 2 , f 3 ) formulated in Equations (1)- (3). f 1 is the number of CSs considering the economy factor.…”

“…The transportation sector accounts for at least a quarter of total greenhouse gas (GHG) emissions in worldwide [2]. And changes in GHG emissions are closely related to the energy consumption [3]. A clean energy revolution is thus taking place around the world.…”

Using Panel Data to Evaluate the Factors Affecting Transport Energy Consumption in China’s Three Regions

“…In addition, EI (ratio of energy consumption to transport ton-km) was the primary factor affecting the reduction of CO 2 emissions from road transport. Yuan et al [16] determined the different trends of EI (ratio of energy consumption to transport ton-km) of different provinces. Lin et al [17] determined that a reduction in the EI was beneficial to China’s transportation industry.…”

Special Issue “Decision Models in Green Growth and Sustainable Development”

“…Wang et al [ 19 ] adopted panel smooth transition regression (PSTR) models to investigate the non-linear relationship between provincial economic growth and carbon emissions in China. Yuan et al [ 20 ] evaluated the interactions among energy consumption, CO emission and growth patterns of the Chinese provincial transportation sector, thereby offering policy implications on provincial transportation sustainable development. Lu [ 21 ] investigated the co-movement and causality between greenhouse gas emissions, energy consumption and economic growth based on the data from 16 Asian countries between 1990–2012.…”