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2021 | OriginalPaper | Chapter

Quantification of Carbon Footprint of Highway Pavement via Streamlined LCA: A Case Study of Zhuhai City, China

Authors : Qian Liu, Ning Zhang, Jingjing Geng, Huabo Duan

Published in: Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Publisher: Springer Singapore

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Abstract

Transport infrastructure construction is very resource and energy intensive. While highway has the characteristics of flexibility and adaptability, however, it faces many problems such as poor pavement flatness, low speed, and serious environmental impact. Meanwhile, Zhuhai City as an important part of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), its sustainable development index’ ranks higher than in many cities in China. This is also inseparable from the development model of Zhuhai City’s construction sector. In this study, the carbon emission of highway pavement was quantified through SLCA. Specifically, the life of highway pavement includes the material stage, construction stage, maintenance stage. The preliminary results show that the CF of highway pavement is over 50 thousand tonnes of CO2eq in 2017. The CF from per kilometer of expressway pavement is more than 3,000 tonnes CO2eq. The largest contributor is the material consumption stage, which accounts for 78%, followed by the construction stage (10%), the maintenance stage (12%). The highway density in Zhuhai City is 83 km/100 (km)2, which is at a lower level than other cities in GBA. This paper also uses scenario analysis to estimate and predict the CF of the highway pavement system in Zhuhai City (by 2030). Current findings have a certain significance for environmental protection research in the construction of transportation infrastructure in GBA. The method can also be applied to the quantification of CF of other cities or whole GBA highway pavement construction assessment.

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Metadata
Title
Quantification of Carbon Footprint of Highway Pavement via Streamlined LCA: A Case Study of Zhuhai City, China
Authors
Qian Liu
Ning Zhang
Jingjing Geng
Huabo Duan
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-8892-1_32