Simulation and measurement of air quality in the traffic congestion area

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 PM2.5 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 PM2.5 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− 3, respectively. On weekdays, the vehicle speed and the natural wind were 60 km h− 1 and 2.0 m s− 1, respectively. On weekdays, the SOx, CO, NO, and PM2.5 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− 3, respectively. The UAV was used to verify that the PM2.5 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− 3, respectively. In addition, the predicted PM2.5 concentrations were 40–45, 25–30, 45–48, and 45–50 μg m− 3 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.

Simulation of Submicron Particulate Matter (PM1) Dispersion Due to Traffic Rerouting to Establish a Walkable Cultural Tourism Route in Ratchaburi’s Old Town, Thailand

“…These model performance evaluation indicators were all close to the ideal values (NMSE and FB = 0.0) [51]. The results were comparable to previously reported PM levels due to road traffic activities, simulated using a line source dispersion model, CALINE 4 (NMSE = 0.08 and FB = −0.01) [52], and a Lagrangian particle model, (GRAL) (NMSE = 0.04 and FB = 0.13) [53]. The simulation performance in our study is better than the performance reported in previous work using the WinOSPM, ADMS-Urban, and AEOLIUS models (in which NMSE ranged from 0.11 to 0.23 and FB ranged from −0.08 to 0.26) [54].…”

Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries

“…Another novel application of LCPMS was in measuring the three-dimensional distribution of air pollutants aboard a drone. This setup was used to measure the three-dimensional distribution of PM 2.5 concentrations along a tunnel in Taiwan using two kinds of sensors previously calibrated against Taiwan EPA instruments [50]. The measurements were also used to validate the results of CALINE4 simulations that were aimed at providing air quality forecasts for the area.…”

Chemical Composition, Source Appointment and Health Risk of PM2.5 and PM2.5-10 during Forest and Peatland Fires in Riau, Indonesia

“…High values of BC, OC, and K are indicators of BB (Lestari and Mauliadi, 2009). (Yu et al, 2021), SA, and SD, in contrast to the PM2.5 source contributions obtained without the OC data.…”