Statiatical modeling of relationships among road traffic noise, air quality and Urban form Indicators

Recently, in urban areas, continuous monitoring and scientific management of environmental noise and air quality are considered more important for people's health impact and well-being. Especially, the road traffic which is one of major urban form indicators such as population, building, transportation, land-use, and etc. is the common emission source of urban noise and air pollution. Therefore for more efficient city planning it is necessary to figure out air- and noise-combined relationship because the road traffic and other urban form indicators are interrelated. The purpose of this study is to investigate the relationships among road traffic noise, air quality and urban form indicators. First, using GIS and LiDAR data, the noise level and the concentration of PM2.5 exposed to residents are calculated. Second, the representative values of the noise level, concentration of PM2.5 and urban form indicators are averaged over grid cells of 200 m × 200 m for the study area. And then, the relationships among noise, air quality and urban form indicators are statistically estimated by spatial statistical model. This well-estimated model could make it possible to design integrated and systematic planning.