Determination of Traffic Related Air Pollution Status Using Dispersion Modeling: The Case of Megenagna, Addis Ababa, Ethiopia

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Abstract Traffic is now the leading cause of air pollution in growing megacities in the developing world. Because of unimproved old age of the car and poor road conditions in Ethiopia's capital city (Addis Ababa), vehicles are the main cause of air pollution. Megenagna (located between Bole and Yeka sub-cities of Addis Ababa) is one of the city's key hubs squares, with six major road intersections that cause overcrowding and traffic congestion. The objective of this study was to measure and predict air pollution levels in the Megenagna area using the dispersion model (AERMOD). A 43 sampling points were selected with a sample campaign for two months (January and February) was conducted. Particulate matter (PM2.5 and PM10) and gaseous pollutants (SO2 and NO2) were monitored with hand-held Air-test Model-CW-HAT2005 and Aeroqual series 5000, respectively. The difference among sampling locations was statistically significant (p < 0.05), indicating that there is significant spatial variation throughout the study site. The sensitivity change of wind speed 1 m/sec and wind direction 450 in the self-monitored sample site was best fitting for the prediction, calibration, and validation of pollutants in AERMOD. Particulate matter and gaseous pollutants were predicted to vary from sight to sight, with SO2 above the standard value. This study shows that traffic-related emissions in Addis Ababa should be investigated further in terms of spatiotemporal variation.

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