International Journal of Environment and Pollution Research (IJEPR)

EA Journals

concentration level

Contribution of Vehicular Emissions to Climate Change in Nigeria: A Closer Look (Published)

Climate change is fast becoming a global challenge, as most countries in the world have continue to increase their industrial capacities, resulting in increase in greenhouse gas emissions in the atmosphere. Also, the increase in human population in Nigeria has caused increase in motor vehicles, thereby resulting to release of more gaseous pollutants to the atmosphere. This study examined contributions of vehicular emissions to climate change in Port Harcourt, Nigeria. The concentration of air particulate matter and pollutants were monitored in three locations (Rumuokoro, Rumuola and Ada George) selected on the basis of traffic density. Air quality was monitored with MX6 Ibrid Multi gas monitors, MET ONE GT 321 for particulate matter, Davis Vantage Vue Weather Station for metrological parameters. Data on meteorological factors such as air temperature, wind speed, relative humidity were collected from the nearest weather station in Port Harcourt. Traffic records were taken at the designated locations using a close circuit television (Plate 5.1) in the morning, afternoon and evening respectively. All the parameters were monitored in each location, five days in a week every month for two years (2016-2017). The result of the analysis revealed that 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 and change in climatic conditions. This implies that emission rate from vehicles will continue to increase and contribute significantly to climate change, except measures are put in place to mitigate it.

Citation: Ucheje O.O. and Okolo O.J.  (2023) Contribution of Vehicular Emissions to Climate Change in Nigeria: A Closer Look, International Journal of Environment and Pollution Research, Vol.11, No.1 pp.43-62

Keywords: Air pollutants, Climate Change, concentration level, traffic volume, vehicular emission

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

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.

Keywords: Air pollutants, Modeling, Traffic, concentration level, vehicular volume

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