Author(s)

Erik Skjetne¹, Hai-Ying Liu^2*

¹Non-Affiliated, Rælingen, Norway.
²NILU—Department of Environmental Impacts and Sustainability, Norwegian Institute for Air Research, Kjeller, Norway.

In this study, we explored to combine traffic maps and smartphone trajectories to model traffic air pollution, exposure and health impact. The approach was step-by-step modeling through the causal chain: engine emission, traffic density versus traffic velocity, traffic pollution concentration, exposure along individual trajectories, and health risk. A generic street with 100 km/h speed limit was used as an example to test the model. A single fixed-time trajectory had maximum exposure at velocity of 45 km/h at maximum pollution concentration. The street population had maximum exposure shifted to a velocity of 15 km/h due to the congestion density of vehicles. The shift is a universal effect of exposure. In this approach, nearly every modeling step of traffic pollution depended on traffic velocity. A traffic map is a super-efficient pre-processor for calculating real-time traffic pollution exposure at global scale using big data analytics.

Traffic Map, Smartphone, Location Service, Trajectory, Traffic Pollution, Public Health, Road Traffic Exposure, Analytics, Big Data

Skjetne, E. and Liu, H. (2017) Traffic Maps and Smartphone Trajectories to Model Air Pollution, Exposure and Health Impact. Journal of Environmental Protection, 8, 1372-1392. doi: 10.4236/jep.2017.811084.