Characterizing and interpreting the spatial variation of traffic pollution in urban non-motorized lanes using mobile measurements

AbstractThe ongoing improvement of urban air quality urgently needs refined understanding of air pollution variation. For urban roads, due to the changeable traffic flow and complex road environments, commuters usually confront with a direct but uncertain exposure to traffic-induced air pollutants. However, the current lack of fine-grained measurements and reliable analytical methods restricts our knowledge of road air pollution risk. Therefore, we designed a bicycling experiment to collect fine-scale concentration samples of PM2.5, PM10, and black carbon (BC) in non-motorized lanes beside an expressway. Mobile measurements revealed high particle pollution at the building-intensive roadside, and the background pollution concentration removal clarified high-polluted sections. Generalized additive models demonstrated that the background pollution concentrations dominated the overall pattern of particles, and meteorological factors had significant but varied impacts on local variations of particles. Riverside winds lowered PM2.5 and PM10 levels most time, while BC was more affected by roadside greenery, distance from roadway and diesel vehicles. At the hotspots, an increase of 100 diesel vehicles per hour could increase roadside BC by about 2% per kilometer but brought no obvious increase in PM2.5 and PM10. These results confirm the availability of mobile measurements and generalized additive models in high-resolution pollution analysis, and are beneficial to countermeasures of ...
Source: Air Quality, Atmosphere and Health - Category: Environmental Health Source Type: research