Forecast of Transportation CO 2 Emissions in Shanghai under Multiple Scenarios

Liping Zhu (), Zhizhong Li, Xubiao Yang, Yili Zhang and Hui Li
Additional contact information
Liping Zhu: College of Air Transportation, Shanghai University of Engineering Science, Shanghai 201620, China
Zhizhong Li: College of Air Transportation, Shanghai University of Engineering Science, Shanghai 201620, China
Xubiao Yang: College of Air Transportation, Shanghai University of Engineering Science, Shanghai 201620, China
Yili Zhang: Faculty of Economics and Management, East China Normal University, Shanghai 200062, China
Hui Li: School of Management, Anshan Normal University Liaoning China, Anshan 114007, China

Sustainability, 2022, vol. 14, issue 20, 1-18

Abstract: A reduction in CO 2 emissions from transportation is of great significance to achieve the goal of “peak carbon and carbon neutrality” in China. For 2003–2019, this paper calculates the transportation CO 2 emissions in Shanghai and constructs an extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model for forecasting. The result shows that from 2003 to 2019, total and per capita CO 2 emissions from Shanghai’s transportation sector increased, but the rate of growth decreased. Oil consumption was the main source of emissions, accounting for more than 92%. The study extended the STIRPAT model to analyze the driving factors for emissions. It shows that population size, passenger turnover, per capita GDP, transportation intensity, and energy intensity are positively correlated with emissions. Energy structure (the proportion of clean energy) has a negative impact, restraining growth. Under multiple scenarios, the forecast shows that Shanghai’s transportation sector can reach a CO 2 emissions peak before 2030. However, overgrowth of the transportation sector should be avoided. Progress in green and low-carbon technology is particularly important to achieve China’s peak carbon goal. Shanghai should actively build an efficient green transportation system, continue to optimize the transportation energy structure, and promote green and low-carbon travel for residents.

Keywords: transportation sector; CO 2 emissions; STIRPAT model; peak carbon; scenario forecast (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/20/13650/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/20/13650/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:20:p:13650-:d:949495

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().