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Simulation and measurement of air quality in the traffic congestion area.

Authors :
Yu, Shin
Chang, Chang Tang
Ma, Chih Ming
Source :
Sustainable Environment Research (2468-2039); 7/28/2021, Vol. 31 Issue 1, p1-18, 18p
Publication Year :
2021

Abstract

The traffic congestion in the Hsuehshan tunnel and at the Toucheng interchange has led to traffic-related air pollution with increasing concern. To ensure the authenticity of our simulation, the concentration of the last 150 m in Hsuehshan tunnel was simulated using the computational fluid dynamics fluid model. The air quality at the Toucheng interchange along a 2 km length highway was simulated using the California Line Source Dispersion Model. The differences in air quality between rush hours and normal traffic conditions were also investigated. An unmanned aerial vehicle (UAV) with installed PM<subscript>2.5</subscript> sensors was developed to obtain the three-dimensional distribution of pollutants. On different roads, during the weekend, the concentrations of pollutants such as SOx, CO, NO, and PM<subscript>2.5</subscript> were observed to be in the range of 0.003–0.008, 7.5–15, 1.5–2.5 ppm, and 40–80 μg m<superscript>− 3</superscript>, respectively. On weekdays, the vehicle speed and the natural wind were 60 km h<superscript>− 1</superscript> and 2.0 m s<superscript>− 1</superscript>, respectively. On weekdays, the SOx, CO, NO, and PM<subscript>2.5</subscript> concentrations were found to be in the range of 0.002–0.003, 3–9, 0.7–1.8 ppm, and 35–50 μg m<superscript>− 3</superscript>, respectively. The UAV was used to verify that the PM<subscript>2.5</subscript> concentrations of vertical changes at heights of 9.0, 7.0, 5.0, and 3.0 m were 45–48, 30–35, 25–30, and 50–52 μg m<superscript>− 3</superscript>, respectively. In addition, the predicted PM<subscript>2.5</subscript> concentrations were 40–45, 25–30, 45–48, and 45–50 μg m<superscript>− 3</superscript> on weekdays. These results provide a reference model for environmental impact assessments of long tunnels and traffic jam-prone areas. These models and data are useful for transportation planners in the context of creating traffic management plans. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
24682039
Volume :
31
Issue :
1
Database :
Complementary Index
Journal :
Sustainable Environment Research (2468-2039)
Publication Type :
Academic Journal
Accession number :
151648745
Full Text :
https://doi.org/10.1186/s42834-021-00099-3