A Modelling Study of Road Traffic Contributions to Ambient PM2.5 Concentrations in Lagos
Abstract
As the fastest growing city in Africa, Lagos experiences extremely high levels of air pollution. While there are many sources of air pollution in Lagos, road traffic has been widely reported as the most prominent.
Due to a dearth of studies on modelling of pollutant dispersions from vehicular emissions, this study adapted the OSCAR System to model the contributions of road traffic to ambient concentrations of PM2.5 in the megacity.
The model was evaluated by comparing its predicted PM2.5 concentrations with the observed concentrations in the study area. This comparison was carried out using a number of conventional statistical parameters: model bias, normalised mean square error, fractional bias, correlation coefficient (R) and factor of 2 analysis (F2). The evaluation showed aggregate R and F2 values of 0.66 and 0.80 respectively. This implies a good level of agreement between the measured and the predicted PM2.5 concentrations.
For November 2018, the model predicted mean traffic increment of 28.1µg/m3 (37.2%) - 29.3 µg/m3 (38.2%) along the Mile 12 – Ikorodu road. However, the predicted increment around the Expressway (a busier road) was 36.5 µg/m3 (43.5%). The Ikorodu -Mile 12 road is a very important traffic corridor in the Lagos Metropolitan Area – being the pioneering route for the government’s Bus Rapid Transit scheme.
A scenario analysis carried out in this study shows that under a fixed meteorological condition, traffic contributions (to ambient concentrations of PM2.5) would increase by a factor of 7 (from November 2010 to November 2018) near the Ikorodu road. Further, it reveals that cars are the highest emitters of PM2.5 along the Ikorodu road. Hence, the government’s “Non- Motorised Transport (NMT)” policy could enhance reduction of PM2.5 emission along the Ikorodu road.
Publication date
2019-10-30Published version
https://doi.org/10.18745/th.22818https://doi.org/10.18745/th.22818
Funding
Default funderDefault project
Other links
http://hdl.handle.net/2299/22818Metadata
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