At public bus stops, NOX pollutants discharged by regularly stopping buses quickly accumulate, exposing waiting passengers to high levels of air pollutants, which creates a threat to public health. The environmental protection agency (EPA) presents air quality standards for NOX, a significant pollutant that causes lung diseases such as asthma when exposed to the human body. To handle this problem, air purification systems are installed inside bus stops in many public places. However, it is challenging to maintain a low concentration of NOX inside public bus stops due to the persistent inflow of bus exhaust gas. Therefore, it is crucial to design an optimal location for an air purification system to meet air environment standards for respiratory areas. This study proposed a computational fluid dynamics (CFD)-based optimal installation strategy for an air purification system to minimize NOX exposure inside a public bus stop. The CFD model was developed to numerically analyze NO2 exposure with the actual design value for a public bus stop in Ulsan, South Korea. The local NO2 concentration was evaluated in the human breathing zone. The case study was performed according to the locations of the inlet and outlet of the air purification system. A transient CFD simulation was performed to analyze the effect of the air purification system on pollutants generated from the stationary bus by time flow in various cases. NO2 concentration and exposure reduction effectiveness (ERE) were analyzed and compared for each case in the breathing zone. In the optimal case, the ERE of NO2 was confirmed to be 35.9 %, and the NO2 concentration according to the air quality standards of EPA could be maintained at 0.1 ppm or less. The theoretical framework proposed in this study can be generalized to design air purification systems for general external facilities.
|Publication status||Published - 2022 Nov|
Bibliographical noteFunding Information:
This work was supported by the Korean Institute of Industrial Technology within the framework of the following projects: “Development and application of AI-based microbubble-scrubber system for simultaneous removal of air pollutants [grant number KM-22–0015]”.
© 2022 The Author(s)
All Science Journal Classification (ASJC) codes
- Environmental Science(all)