Traffic Maps and Smartphone Trajectories to Model Air Pollution, Exposure and Health Impact

Erik Skjetne; Hai-Ying Liu

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Traffic Maps and Smartphone Trajectories to Model Air Pollution, Exposure and Health Impact

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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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《环境保护（英文）》 |2017年第11期|1372-1392|共21页
作者
Erik Skjetne; Hai-Ying Liu;
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作者单位

Non-Affiliated;

Ræ

lingen;

Norway;

NILU—Department of Environmental Impacts and Sustainability;

Norwegian Institute for Air Research;

Kjeller;

Norway;

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原文格式 PDF
正文语种 chi
中图分类肿瘤学;
关键词
Traffic; Map; Smartphone; Location; Service; Trajectory; Traffic; Pollution; Public; Health; Road; Traffic; Exposure; Analytics; Big; Data;

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Traffic Maps and Smartphone Trajectories to Model Air Pollution, Exposure and Health Impact

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