Modeling of CO and PM2.5 Concentration Level in High Traffic Density Areas, Using Regression Model,

Ucheje, Okoroafor and Emeka, Bright Ogbuene and Ofoezie, Ifeanyi Emmanuel (2021) Modeling of CO and PM2.5 Concentration Level in High Traffic Density Areas, Using Regression Model,. International Journal of Environment and Pollution Research, 9 (3). pp. 33-50. ISSN 2056-7537(print), 2056-7545(online)

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Abstract

The study modeled air pollutants concentration level in selected high traffic density areas of Port Harcourt, Nigeria. It also investigated the factors that affect the concentration of air pollutants and the effects of vehicular density on the daytime, seasonal and annual patterns. This was with the view to ascertain the pattern of air pollutant concentrations in high traffic density areas of the city. Traffic records were taken at the designated locations by counting the number of vehicles passing through a point for two hours in the morning, afternoon and evening, using a close circuit television (Plate 5.1). All the parameters were monitored in each location once every month (Monday to Friday) for two years (2016-2017). Data obtained were analyzed using ANOVA and multiple linear regressions, where appropriate. Results obtained revealed that the concentration of CO and PM2.5varied significantly (p < 0.05) between 2016 and 2017. Traffic volume was found to contribute significantly to the concentration of the air pollutants while meteorological factors such as temperature, humidity and wind speed had significant effects on their dispersion. The study concluded that significant relationship exists between the daytime pattern in vehicular volume and air pollutants concentration in the study area. Also, there was an increase in concentration of average air pollutants across the areas monitored between 2016 and 2017. The variation was attributed to increase in vehicular traffic volume. Furthermore, concentration of air pollutants varied at different degrees of temperature, humidity and wind speed. A model was developed to predict the concentration of CO and PM2.5 at various metrological factors and vehicular volume.

Item Type:	Article
Uncontrolled Keywords:	modeling, concentration level, traffic, vehicular volume, air pollutants
Subjects:	T Technology > TD Environmental technology. Sanitary engineering
Depositing User:	Professor Mark T. Owen
Date Deposited:	01 Apr 2022 14:42
Last Modified:	01 Apr 2022 14:42
URI:	https://tudr.org/id/eprint/213

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