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Open AccessArticle

A Two-Stage Method to Estimate the Contribution of Road Traffic to PM2.5 Concentrations in Beijing, China

Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 17177, Sweden
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Department of Epidemiology and Biostatistics, Institute of Basic Medicine Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
Clinical Epidemiology and Biostatistics, Faculty of Medicine and Health, Örebro University, Örebro 70281, Sweden
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: P. Grady Dixon and Scott C. Sheridan
Int. J. Environ. Res. Public Health 2016, 13(1), 124;
Received: 10 November 2015 / Revised: 4 January 2016 / Accepted: 6 January 2016 / Published: 13 January 2016
Background: Fine particulate matters with aerodynamic diameters smaller than 2.5 micrometers (PM2.5) have been a critical environmental problem in China due to the rapid road vehicle growth in recent years. To date, most methods available to estimate traffic contributions to ambient PM2.5 concentration are often hampered by the need for collecting data on traffic volume, vehicle type and emission profile. Objective: To develop a simplified and indirect method to estimate the contribution of traffic to PM2.5 concentration in Beijing, China. Methods: Hourly PM2.5 concentration data, daily meteorological data and geographic information were collected at 35 air quality monitoring (AQM) stations in Beijing between 2013 and 2014. Based on the PM2.5 concentrations of different AQM station types, a two-stage method comprising a dispersion model and generalized additive mixed model (GAMM) was developed to estimate separately the traffic and non-traffic contributions to daily PM2.5 concentration. The geographical trend of PM2.5 concentrations was investigated using generalized linear mixed model. The temporal trend of PM2.5 and non-linear relationship between PM2.5 and meteorological conditions were assessed using GAMM. Results: The medians of daily PM2.5 concentrations during 2013–2014 at 35 AQM stations in Beijing ranged from 40 to 92 μg/m3. There was a significant increasing trend of PM2.5 concentration from north to south. The contributions of road traffic to daily PM2.5 concentrations ranged from 17.2% to 37.3% with an average 30%. The greatest contribution was found at AQM stations near busy roads. On average, the contribution of road traffic at urban stations was 14% higher than that at rural stations. Conclusions: Traffic emissions account for a substantial share of daily total PM2.5 concentrations in Beijing. Our two-stage method is a useful and convenient tool in ecological and epidemiological studies to estimate the traffic contribution to PM2.5 concentrations when there is limited information on vehicle number and types and emission profile. View Full-Text
Keywords: PM2.5 concentration; road traffic contribution; atmospheric dispersion model; generalized additive mixed model PM2.5 concentration; road traffic contribution; atmospheric dispersion model; generalized additive mixed model
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Fang, X.; Li, R.; Xu, Q.; Bottai, M.; Fang, F.; Cao, Y. A Two-Stage Method to Estimate the Contribution of Road Traffic to PM2.5 Concentrations in Beijing, China. Int. J. Environ. Res. Public Health 2016, 13, 124.

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