Using Grey Relational Analysis to Evaluate Energy Consumption, CO 2 Emissions and Growth Patterns in China’s Provincial Transportation Sectors

Changwei Yuan, Dayong Wu and Hongchao Liu
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Changwei Yuan: School of Economics and Management, Chang’an University, Xi’an 710064, China
Dayong Wu: Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock 79409, TX 79409, USA
Hongchao Liu: Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock 79409, TX 79409, USA

IJERPH, 2017, vol. 14, issue 12, 1-16

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 CO 2 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 CO 2 emission changes. Lastly, sustainable transportation policies were discussed at the province level according to the level of economy, urbanization and transportation energy structure.

Keywords: Grey Relational Analysis; energy consumption; CO 2 emissions; Chinese transport sector; province-level; sustainable policy (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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