Analysis of transportation CO 2 emission efficiency in the Yangtze River Economic Belt in China

Abstract

ABSTRACTThe transportation industry’s CO2 emissions and its main drivers are important for achieving sustainable development. With data from the Yangtze River Economic Belt (YEB) between 2004 and 2020, the efficiency of CO2 emissions is investigated by the super efficiency epsilon-based measurement method (super-EBM) and the Global Malmquist Luenberger Productivity Index (GML). The influencing factors on the different efficiency levels are explored by the panel quantile regression. This study shows that the overall CO2 emissions efficiency is not high, and the efficiency in different regions is largely consistent with the regional economy level. COVID-19 may reduce urban transport carbon emissions in the Yangtze River Economic Belt in 2020, as reflected by the reductions in average emissions and emissions efficiency. Findings also suggest that the influence of the number of private vehicles per 10,000 people on efficiency is positive at low and middle quantiles, and negative at high quantiles. Besides, the per-capita GDP, energy intensity, and transportation service structure negatively influence the efficiency at all quantiles, whereas urbanization and transportation intensity are positively related to the emissions efficiency.KEYWORDS: Transportation industryCO2 emissions efficiencysuper-EBM modelGML indexpanel quantile regressionYangtze River Economic Belt Consent to Participate and PublishThe manuscript is approved by all authors for participation and publication.Ethical ApprovalThe manuscript has no ethical concerns.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.Additional informationFundingThis study was supported by the National Natural Science Foundation of China [Grant no. 71974121], [Grant no. 72374131] and the Soft Science key program of the “Technology and Innovation Action Plan” of the Shanghai Scientific and Technological Committee [Grant no. 22692104600].