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Concentrations of various particulate matter (PM) in urban areas have attracted great attention, due to the increasing demand on life quality. Many studies have highlighted the spatial variability of PM2.5 in urban areas, and found that there are significant differences between residents' exposure and background levels. Different from the strategy of establishing large-scale Airbox stations or utilizing mobile stations with portable instruments to measure residents' exposures, this study develops an on-vehicle monitoring system (OVMS), which is based on the technology of Internet of Things, to increase the spatial resolution of the monitoring data in an economical way. The parameters measured by the OVMS include PM2.5, time, location, moving speed, ambient temperature, and relative humidity. According to the experimental results, the effects of the moving speed of the OVMS on PM2.5 measurements are negligible (r =0.024), when the moving speed is below 57 km/hr. The correlation between the dynamic measurements provided by the OVMS and a standard instrument is high (r =0.601). These results show that the OVMS can accurately monitor PM2.5 as it moves. The data of PM2.5 obtained by the OVMS also reveal the impacts of traffic and community pollution in urban areas on residents' exposure. In addition, this study proposes a visualized map that shows real-time PM2.5 measurements as the OVMS travels. Map users can choose a less-polluted path to get to their destinations based on the PM2.5 information. In addition, the OVMS measurements can be integrated with the Airbox measurements, so the visualized map can provide detailed spatial interpolation results on PM2.5 exposures. Thus, the OVMS can be a great help in evaluating the PM2.5 levels in certain areas of urban streets where Airbox stations are not installed.

Mobile Measurement of Particulate Matter Concentrations on Urban Streets: System Development and Field Verification