Assessment of transport emissions impact and the associated social cost for Chengdu, China

ABSTRACT

Chengdu, the capital city of Sichuan province, is the fourth biggest city in China with over 15 million residents and 3.4 million vehicles. In Chengdu, transport and other mobile sources accounted for over 27% of the city's PM_2.5 emissions (CDEPB, 2016), posing negative impacts on public health, local environment, and the climate. This study estimated impacts from transport-related emissions (CO₂, CH₄, N₂O, PM₁₀, PM_2.5, NO_X, SO_X, CO, and HC) and evaluated the associated social cost for Chengdu from 2005 to 2013. The study also assessed the city's transport performance in terms of its eco-efficiency with the socioeconomic and environmental concerns. The activity-based methodology was adopted to produce the emission inventories, while utilizing meta-analysis and localizing the emission social cost factors based on Chengdu's economic and demographic reality to support social cost assessment. The study marks the first attempt in literature to evaluate Chengdu's transport emission social cost. The following were observed in the study: (i) in 2013, the social cost of all transport emissions in Chengdu was around US$3 billion, with the lowest estimate of US$449 million and the highest estimate of US$4.7 billion; (ii) trucks, private cars, and motorcycles were the major contributors, while NO_X, PM_2.5, and CO were the key pollutants to public health; (iii) if GHGs (CO₂, CH₄, and N₂O) were excluded, the upper range of social cost of transport air pollutants would be from US$2.4 billion to US$4.1 billion, or 1.6%–2.8% of the Chengdu's GDP.

KEYWORDS:

• Chengdu
• eco-efficiency
• public health
• social cost
• transport emissions

Acknowledgments

This study was under the World Resources Institute's Sustainable and Livable Cities Program. The author appreciates Chengdu Municipal Development and Reform Commission and Chengdu Transport Development Research Institute for their supports during the study. Special thanks are conveyed to Mr. Zhou Laidong from Chengdu Academy of Environmental Sciences for his technical comments. The author also thanks YCC Transport & Climate Change Center for providing social costs database, and Ms. Xiaoxi (Harriet) Yu for proof reading.

Funding

The author would like to thank Caterpillar Foundation for providing the fund.