PM_2.5 concentrations in London for 2008–A modeling analysis of contributions from road traffic

Abstract

We report on the analysis of contributions from road traffic emissions to fine particulate matter (PM_2.5) concentrations within London for 2008 with the OSCAR Air Quality Assessment System. A spatiotemporal evaluation of the OSCAR system has been conducted with measurements from the London air quality network (LAQN). For the predicted and measured hourly time series of concentrations at 18 sites in London, the medians of correlation, mean absolute error, index of agreement, and factor of two (FAC2) of all stations were 0.80, 4.1 μg/m³, 0.86, and 74%, respectively. Spatial evaluation of modeled and observed annual mean concentrations also showed a fairly good agreement, with all the values falling within the FAC2 range. According to model predictions, the urban increment (including the contributions from urban traffic and other urban sources) was evaluated to be on the average 18%, 33%, 39%, and 43% of the total PM_2.5 in suburban environments, in the urban background, near roads, and near busy roads, respectively. However, the highest values of the urban traffic increment can be around 50% of the total PM_2.5 concentrations near motorways and major roads. The total concentrations (including regional background, and the contributions from urban traffic and other urban sources) can therefore be almost three times the regional background. The total urban increment close to busy roads was around 7–8 μg/m³, in which the estimated traffic contribution is more than 2 μg/m³. On the average, urban traffic contributes approximately 1 μg/m³ of PM_2.5 to the urban background across London. According to modeling, approximately two-thirds of the traffic increment originated from exhaust emissions and most of the rest was due to brake and tire wear.

Implications: 

The urban increment and traffic contribution to the total PM_2.5 are significant and spatially heterogeneous across London. The highly heterogeneous distribution of PM_2.5 hence requires detailed modeling studies to be carried out at high spatial resolution, which can be particularly important for exposure and health impact assessment. This type of information can be used to quantify health impacts resulting from specific sources of PM_2.5 such as traffic emissions, to aid city and national decision makers when formulating pollution control strategies.

Funding

This work was supported by 7th Framework Programme project TRANSPHORM (grant agreement 243406) and the APTA project funded by the Academy of Finland.

Additional information

Notes on contributors

Vikas Singh

Vikas Singh is a research fellow and Ranjeet S. Sokhi is a research professor and director of the Centre of Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, UK.

Ranjeet S. Sokhi

Vikas Singh is a research fellow and Ranjeet S. Sokhi is a research professor and director of the Centre of Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, UK.

Jaakko Kukkonen

Jaakko Kukkonen is a research professor at the Finnish Meteorological Institute in Helsinki, Finland.