title: A Two-Stage Method to Estimate the Contribution of Road Traffic to PM₂.₅ Concentrations in Beijing, China.
abstract: 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.
authors.affiliation: Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 17177, Sweden. xin.fang@ki.se.
authors.forename: Xin
authors.initials: X
authors.lastname: Fang
authors.affiliation: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. yang.cao@ki.se.|State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China. yang.cao@ki.se.
authors.forename: Runkui
authors.initials: R
authors.lastname: Li
authors.affiliation: Department of Epidemiology and Biostatistics, Institute of Basic Medicine Sciences, Chinese Academy of Medical Sciences &amp; School of Basic Medicine, Peking Union Medical College, Beijing 100005, China. xuqun@ibms.cams.cn.
authors.forename: Qun
authors.initials: Q
authors.lastname: Xu
authors.affiliation: Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 17177, Sweden. matteo.bottai@ki.se.
authors.forename: Matteo
authors.initials: M
authors.lastname: Bottai
authors.affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden. fang.fang@ki.se.
authors.forename: Fang
authors.initials: F
authors.lastname: Fang
authors.affiliation: Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 17177, Sweden. lirk@ucas.ac.cn.|Clinical Epidemiology and Biostatistics, Faculty of Medicine and Health, Örebro University, Örebro 70281, Sweden. lirk@ucas.ac.cn.
authors.forename: Yang
authors.initials: Y
authors.lastname: Cao
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis* / Q000706:statistics & numerical data; D000068476:Beijing; D004784:Environmental Monitoring / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D052638:Particulate Matter / Q000032:analysis*; D001335:Vehicle Emissions / Q000032:analysis*
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D001335:Vehicle Emissions
keywords: PM2.5 concentration; atmospheric dispersion model; generalized additive mixed model; road traffic contribution