Influence of Weather Parameters on Vehicular Air Pollutants at a Select Road in Nairobi, Kenya

Abstract

Atmospheric pollution is an existential threat to people particularly those residing in urban areas. It affects lives in different ways including health, water and food resources. The abundance of air pollutants in urban areas has been associated in many studies with vehicular emission rates linked to transport infrastructure. This study sought to investigate the influence of ambient weather parameters on vehicular pollutants concentrations at Junction mall on Ngong road, Nairobi. Data used in this study included pollutants concentration data of ground level ozone (O3), Sulphur dioxide (SO2) and PM2.5 and ambient weather parameters including temperature, relative humidity, solar radiation, wind speed and atmospheric pressure collected for a period of 120 hours from 24th to 28th December 2015. The study also used archived datasets of gridded weather parameters (atmospheric pressure, wind direction, wind speed, temperature and humidity) for trajectory analysis from the National Oceanic and Atmospheric Administration (NOAA) website on the Global Data Assimilation System (GDAS) for the same period of time. The study objectives were analyzed using a wide range of methods including time series analysis, correlation analysis, regression analysis and trajectory analysis using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Further, statistical metrics of Noise to signal ratio (NSR), Coefficient of determination (R2) and Index of agreement (d) were used to evaluate the goodness of the established models and relationships. Diurnal patterns were observed in O3 and SO2 with rising concentrations observed from early morning hours, dropping concentrations in the late afternoon hours and weakly enhanced concentrations from 8 pm local time to mid night. There were no discernible patterns for PM2.5. Trajectory analysis further showed that the South Western part of the city was the most affected by air pollutants both in the morning and evening hours. Sulphur dioxide showed a significant positive correlation with temperature and solar radiation and significant negative correlation with relative humidity, O3 showed a significant negative correlation with relative humidity and a significant positive correlation with wind speed, temperature and solar radiation. PM2.5 showed a significant positive correlation with wind speed. Regression analysis showed that the ambient variance of O3 concentration is best explained with weather parameters at 88.1% followed by variance of SO2 at 66.7% and PM2.5 at 46.7%. These findings show that weather parameters have a modulator relationship on ambient vehicular air pollutants concentration and their dispersion in the atmosphere. While the evidence is substantial, there is need to include non-meteorological factors such as traffic flow intensity and volume and widen the data collection period to cover other seasons in Nairobi to understand the unexplained percentage of variation in the vehicular air pollutants concentration.