Next Article in Journal
The Effect of Parental Economic Expectation on Gender Disparity in Secondary Education in Ghana: A Propensity Score Matching Approach
Next Article in Special Issue
Long-Term Forecast of Energy and Fuels Demand Towards a Sustainable Road Transport Sector in Ecuador (2016–2035): A LEAP Model Application
Previous Article in Journal
The Spatial Pattern of Urban Settlement in China from the 1980s to 2010
Previous Article in Special Issue
Towards Carbon-Neutral Mobility in Finland: Mobility and Life Satisfaction in Day-to-Day Life
Article

Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation

1
State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2
China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200030, China
3
Traffic and Transportation Research Center, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
4
Shanghai Institute of Tourism, Shanghai Normal University, Shanghai 200234, China
5
School of Media & Communication, Shanghai Jiao Tong University, Shanghai 200240, China
6
School of Design, Shanghai Jiao Tong University, Shanghai 200240, China
*
Authors to whom correspondence should be addressed.
Sustainability 2019, 11(23), 6705; https://doi.org/10.3390/su11236705
Received: 18 September 2019 / Revised: 7 November 2019 / Accepted: 15 November 2019 / Published: 27 November 2019
Research assessing on-road emission flow patterns from motor vehicles is essential in monitoring urban air quality, since it helps to mitigate atmospheric pollution levels. To reveal the influence of vehicle induced turbulence (VIT) caused by both front- and rear-vehicles on traffic exhaust and verify the applicability of the simplified line source emission model, a Computational Fluid Dynamics (CFD) numerical simulation was used to investigate the micro-scale vehicle pollutant flow patterns. The simulation results were examined through sensitivity analysis and compared with the field measured carbon monoxide (CO) concentration. Conclusions indicate that the vehicle induced turbulence caused by the airflow blocking effect of both front- and rear-vehicles impedes the diffusion of front-vehicle traffic exhaust, compared with that of the rear vehicle. The front-vehicle isosurface with the CO mass fraction of 0.0012 extended to 6.0 m behind the vehicle, while that of the rear-vehicle extends as far as 12.7 m. But for the entire motorcade, VIT is beneficial to the diffusion of pollutants in car-following situations. Meanwhile, within the range of 9 m behind the rear of the lagging vehicle lies a vehicle induced turbulence zone. Furthermore, the influence of vehicle induced turbulence on traffic exhaust flow pattern is obvious within a range of 1 m on both sides of the vehicle body, where the concentration gradient of on-road emission is larger and contains severe mechanical turbulence. As a result, in the large concentration gradient area of the pollutant flow field, which accounts for 99.85% of the total concentration gradient, using the line source models to represent the on-road emission might introduce considerable errors due to neglecting the influence of vehicle induced turbulence. Findings of this study may shed lights on predicting emission concentrations in multiple locations by selecting appropriate on-road emission source models. View Full-Text
Keywords: urban traffic; vehicle induced turbulence; CFD numerical simulation; traffic emission; car following situations; line source emission model urban traffic; vehicle induced turbulence; CFD numerical simulation; traffic emission; car following situations; line source emission model
Show Figures

Figure 1

MDPI and ACS Style

Shi, X.; Sun, D.; Fu, S.; Zhao, Z.; Liu, J. Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation. Sustainability 2019, 11, 6705. https://doi.org/10.3390/su11236705

AMA Style

Shi X, Sun D, Fu S, Zhao Z, Liu J. Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation. Sustainability. 2019; 11(23):6705. https://doi.org/10.3390/su11236705

Chicago/Turabian Style

Shi, Xueqing, Daniel Sun, Song Fu, Zhonghua Zhao, and Jinfang Liu. 2019. "Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation" Sustainability 11, no. 23: 6705. https://doi.org/10.3390/su11236705

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop