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.

Description

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. cc-by

Keywords

Chinese transport sector, CO2emissions, Energy consumption, Grey relational analysis, Province-level, Sustainable policy

Citation

Yuan, C., Wu, D., & Liu, H.. 2017. Using grey relational analysis to evaluate energy consumption, CO2 emissions and growth patterns in China’s provincial transportation sectors. International Journal of Environmental Research and Public Health, 14(12). https://doi.org/10.3390/ijerph14121536

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