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Journal of Chemistry
Volume 2018, Article ID 8964852, 11 pages
https://doi.org/10.1155/2018/8964852
Research Article

Vehicle Emission Factors for Particulate and Gaseous Pollutants in an Urban Tunnel in Xi’an, China

Department of Traffic Engineering, Chang’an University, Xi’an 710064, China

Correspondence should be addressed to Hong Chen; moc.621@28nehcgnoh

Received 7 March 2018; Revised 31 May 2018; Accepted 21 June 2018; Published 10 July 2018

Academic Editor: Antonio De Lucas-Consuegra

Copyright © 2018 Danting Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Urban tunnels are generally used to measure traffic-related particles and gas pollutant concentrations. To understand on-road vehicle emissions and update emission factors (EFs), traffic volume data and emissions of particulate matter smaller than 2.5 µm (PM2.5), carbon monoxide (CO), nitrogen oxides (NOX), hydrocarbon (HC), and volatile organic compounds (VOCs) for mixed vehicles were investigated at the Wenchang Gate-Peace Gate Tunnel in Xi’an over 11 days. An average fleet of 14,199 vehicles with mean speeds that ranged from 18 km·h−1 to 46 km·h−1 passed through the tunnel during the sampling period each day. A mass balance model and linear regression analysis were adopted to derive pollutant EFs for mixed vehicles, cars, and taxis, respectively. The results demonstrated that EFs during the night were higher than those during the day because goods vehicles are only allowed to travel from 22:00 to 07:00. Averaged EFs of PM2.5, CO, NOX, HC, and VOCs for the total fleet were 0.006 ± 0.005, 1.097 ± 0.398, 0.159 ± 0.092, 0.179 ± 0.089, and 0.317 ± 0.172 g·veh−1·km−1, respectively, lower than those reported from other literatures owing to the strict requirements of emission standards and improvements in vehicle technology. This method provides an approach to measure the EFs for different types of vehicles in urban traffic and evaluate traffic pollution in distinct areas.