Abstract
In this study, we have assessed the three-dimensional (3-D) spatial extent of near-road air pollution around a signalized intersection in a densely populated area using collaborating methodologies of stationary measurements, drone monitoring, and atmospheric dispersion modeling. Stationary measurement data collected in the roadside apartment building showed a substantial effect of emitted pollutants, such as nitrogen oxides (NOx), black carbon (BC), and ultrafine particles (UFPs), especially during the morning rush hours. Vertical drone monitoring near the road intersection exhibited a steeper decreasing trend with increasing altitude for BC concentration rather than for fine particulate matter (PM2.5) concentration below the apartment building height. Atmospheric NOx dispersion was simulated using the weather research and forecasting (WRF) and computational fluid dynamics (CFD) models for the drone measurement periods. Based on the agreement between the measured BC and simulated NOx concentrations, we concluded that the air pollution around the road intersection has adverse effects on the health of residents living within the 3-D spatial extent within at least 120 m horizontally and a half of building height vertically during the morning rush hours. The comparability between drone monitoring and WRF-CFD modeling can further guarantee the identification of air pollution hotspots using the methods.
Highlights
The urban proportion of the global population is 55% and is expected to increase to 68% by2050 [1]
Air pollutants emitted from vehicles, such as nitrogen oxides (NOx ), carbon monoxide (CO), black carbon (BC), and ultrafine particles (UFPs) with a diameter less than
In the computational fluid dynamics (CFD) simulations, NOx is regarded as the no-reactive primary pollutant and has the zero background concentration to identify the 3-D spatial extent of near-road air pollutant focusing on traffic emission and dynamical and thermal dispersion [38,39]
Summary
The urban proportion of the global population is 55% and is expected to increase to 68% by. Air pollutant concentrations near hotspots such as road intersections show high spatiotemporal variabilities, simultaneous measurement of these concentrations at fixed locations to demonstrate the three-dimensional (3-D) spatial distribution is extremely challenging, especially in urban areas. To solve this problem, a computational fluid dynamics (CFD) model that simulates the airflow and pollutant distribution at road and building scales has been utilized [22,23,24]. We use collaborating methodologies of stationary and mobile monitoring together with the coupled WRF-CFD modeling to quantitatively assess the 3-D spatial extent of near-road air pollution near an intersection in an urban residential area.
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