Over the past decade, as traffic demand surged, vehicle emissions and influence on environment have received increasing attention, especially in urban areas. In order to dig into the impact of traffic emissions on the microenvironment, this paper designed and implemented mobile measurement with portable detector and collected high-resolution spatial data of PM10 and PM2.5 concentrations, temperature, humidity, ambient configuration was recorded and evaluated by score refer to land use regression . The Kriging interpolation and natural neighbors interpolation method was used for data visualization and multiple linear regression model for PM2.5 and PM10 (R2=0.536 and R2=0.549) including temperature, humidity, traffic flow, diffusion condition, signal control, parking lot, construction, lanes, congestion demonstrated traffic flow, diffusion condition and congestion highly associated with pollutants concentrations and significant contribution of signal control, parking lot, congestion to pollutants. Keywords: air pollution; traffic emissions; kriging; multiple linear regression

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