Chapter
Aug 12, 2020

Study on CO Emission Factors of Passenger Cars in Urban Highway Tunnels at Different Speeds

Publication: CICTP 2020

ABSTRACT

In order to obtain the relationship between motor vehicle CO emission factors and vehicle speeds in urban tunnels. This paper relies on Nanjing Shengli Road Tunnel, based on the COPERT IV model, combines the characteristics of Chinese vehicles and actual parameters in the tunnel to establish an urban single-vehicle tunnel model. A passenger car is used as a reference object to calculate the baseline emission value of its CO pollutant emission factor. A linear regression method is used to establish a model of the relationship between the CO pollutant emission factor and the speed of a single vehicle in an urban tunnel. The calculated results of the model are compared with the actual collected results. The results show that: (1) The CO emissions are highest when the passenger car speed is 10 km/h; the CO emissions decrease sharply between the driving speeds of 10 and 50 km/h; the CO emissions slowly decrease when the vehicle speed is greater than 50 km/h and gradually stabilized. (2) The error between the CO emission parameters calculated using the model and the measured values is only 13.26%. It is suitable for calculation of CO pollutant emission factors that are popularized in other urban highway tunnels and provides a theoretical basis for the research on the diffusion distribution and purification technology of urban tunnel pollutants.

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Go to CICTP 2020
CICTP 2020
Pages: 1424 - 1434

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Published online: Aug 12, 2020

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1School of Electronic and Control Engineering, Chang’an Univ., P.O. Box 710064, Middle Section of S. 2nd Ring Rd., Xi’an, Shaanxi 710064, China. Email: [email protected]
2School of Electronic and Control Engineering, Chang’an Univ., P.O. Box 710064, Middle Section of S. 2nd Ring Rd., Xi’an, Shaanxi 710064, China. Email: [email protected]
3School of Electronic and Control Engineering, Chang’an Univ., P.O. Box 710064, Middle Section of S. 2nd Ring Rd., Xi’an, Shaanxi 710064, China. Email: [email protected]

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