Traffic Maps and Smartphone Trajectories to Model Air Pollution, Exposure and Health Impact
Author(s) -
Erik Skjetne,
Hai-Ying Liu
Publication year - 2017
Publication title -
journal of environmental protection
Language(s) - English
Resource type - Journals
eISSN - 2152-2219
pISSN - 2152-2197
DOI - 10.4236/jep.2017.811084
Subject(s) - pollution , air pollution , environmental science , traffic congestion , meteorology , population , speed limit , environmental engineering , transport engineering , engineering , geography , environmental health , medicine , ecology , chemistry , organic chemistry , biology
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.
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