Back to Page Authors: Hojun Yoo, Sungjin Hong, Wooyoung Yeom, Jenoga Kim, Intai Kim

Keywords: vehicle-based measuring system, road suspended dust, PM10, street canyon level, estimation model

Abstract: Various studies are being conducted to reduce road dust on roadsides generated by vehicles as it poses a physical risk to road users. In Korea, the government is implementing a policy to reduce fine dust through road cleaning, but as it is managed at the network level. And the fine dust concentration provided by the observatory is installed on the rooftops of tall buildings, but expected to be much higher felt by pedestrians near the side of the road. Therefore, it is essential to estimate real-time road suspended dust to present efficient management measures for continuous project-level reduction of road pollution. This study is a development of a suspended dust estimation model of roads in the urban to examines various factors that can, directly and indirectly, affect road suspended dust by devising a Vehicle-Based measuring system. Further, it is also intended to present quantitative indicators for the development of a model for estimating the concentration of road dust by analyzing the related factors of influence on the road suspended dust. The measurement results showed that as traffic flow and vehicle speed increased, the higher the road suspended dust and the higher the street canyon level, which means the building was located nearby, the higher the road suspended dust concentration was formed. Moreover, the results also confirmed that the elapsed time after rain, Street Canyon Level and wind speed, traffic and vehicle speed, and the background concentration of the stations had a direct effect on the suspended dust concentration, and that the air temperature and relative humidity had a sensitive effect on the atmospheric dust concentration. By measuring the suspended dust in the streets of the urban shows the difference from the concentration of fine dust in the surrounding monitoring stations were analyzed, and expected through a quantitative analysis to determine the sensitivity of the concentration that change depending on the traffic (traffic volume,vehicle speed, etc.) and meteorological (temperature, wind speed) and environmental (Street canyon and pavement conditions) factors.