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A Two-Stage Method to Estimate the Contribution of Road Traffic to PM(2).(5) Concentrations in Beijing, China
Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 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, China.
Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
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2016 (English)In: International Journal of Environment and Bioenergy, ISSN 1832-2077, E-ISSN 1660-4601, Vol. 13, no 1, E124Article in journal (Refereed) Published
Abstract [en]

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 mug/m(3). 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.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPIAG , 2016. Vol. 13, no 1, E124
Keyword [en]
Air Pollutants/*analysis Air Pollution/*analysis/statistics & numerical data, Beijing Environmental Monitoring/*methods Models, Statistical Models, Theoretical Particulate Matter/*analysis, Vehicle Emissions/*analysis, PM2.5 concentration, atmospheric dispersion model, generalized additive mixed model, road traffic contribution
National Category
Medical and Health Sciences Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Epidemiology
Identifiers
URN: urn:nbn:se:oru:diva-54070DOI: 10.3390/ijerph13010124ISI: 000374186100061PubMedID: 26771629ScopusID: 2-s2.0-84954444807OAI: oai:DiVA.org:oru-54070DiVA: diva2:1057804
Note

Funding Agencies:

Junior Faculty Research Grants of the Institute of Environmental Medicine, Karolinska Institutet 

fund for PhD research (KID-funds) of Karolinska Institutet, Sweden 

travel (KI-foundations & funds) of Karolinska Institutet, Sweden 

Public Welfare Research Program of National Health and Family Planning Commission of China 

Opening Project of Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3)

Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2017-02-07Bibliographically approved

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CiteExportLink to record
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