ArticleInternational journal of environmental research and public health2016
A Two-Stage Method to Estimate the Contribution of Road Traffic to PM₂.₅ Concentrations in Beijing, China.
Article in International journal of environmental research and public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- The influence of urban haze pollution on urban shrinkage in China-an analysis of the mediating effect of the labor supply.Environmental science and pollution research international · 2021Article
- Micro- and Nanosized Substances Cause Different Autophagy-Related Responses.International journal of molecular sciences · 2021Review
- The critical role of endothelial function in fine particulate matter-induced atherosclerosis.Particle and fibre toxicology · 2020Review
- Impact of Commuting Mode on Obesity Among a Working Population in Beijing, China: Adjusting for Air Pollution.Diabetes, metabolic syndrome and obesity : targets and therapy · 2020Article
- Effect of Urban Greening on Incremental PMFrontiers in public health · 2020Article
- Solid Particle Number (SPN) Portable Emissions Measurement Systems (PEMS) in the European Legislation: A Review.International journal of environmental research and public health · 2019Review
- Solid Particle Number Emission Factors of Euro VI Heavy-Duty Vehicles on the Road and in the Laboratory.International journal of environmental research and public health · 2018Article
- Curcumin pretreatment protects against PM2.5‑induced oxidized low‑density lipoprotein‑mediated oxidative stress and inflammation in human microvascular endothelial cells.Molecular medicine reports · 2017Article
- Socioeconomic Drivers of PM2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China.International journal of environmental research and public health · 2016Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFine 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.
objectiveTo develop a simplified and indirect method to estimate the contribution of traffic to PM2.5 concentration in Beijing, China.
methodsHourly 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.
resultsThe 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.
conclusionsTraffic 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.
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