ANALYTICAL MODELING OF INDUSTRIAL EMISSIONS FROM NORTHERN NIGERIA
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An analytical model was derived from the Gaussian-AERMOD approach and used to estimate or predict the concentration of fine particulate matter (PM2.5 and PM10), and some gaseous pollutants namely CO, SO2 and NO2 emitted from selected industrial stacks in the major northern Nigeria industrial cities of Kano, Kaduna and Jos. The model results were correlated with experimental data collected from six industries which were selected two each from Kano, Kaduna and Jos for one year using Altair 5X multi-gas detector, Gasman monitors, and HAT 200 PMX detector which are digital meters that sense and di...
An analytical model was derived from the Gaussian-AERMOD approach and used to estimate or predict the concentration of fine particulate matter (PM2.5 and PM10), and some gaseous pollutants namely CO, SO2 and NO2 emitted from selected industrial stacks in the major northern Nigeria industrial cities of Kano, Kaduna and Jos. The model results were correlated with experimental data collected from six industries which were selected two each from Kano, Kaduna and Jos for one year using Altair 5X multi-gas detector, Gasman monitors, and HAT 200 PMX detector which are digital meters that sense and display the concentrations of gases and fine particulates matter on the screen when switched on. The results showed that there exists a strong positive correlation between the measured and modeled results with correlation coefficient R ranging from 0.7-1.0 for all the pollutants investigated. The dispersion pattern of pollutants were also studied by considering the effects of some parameters such as stack height, stack exit velocity, stack emission rate, temperature, solar radiation, wind speed and direction, and were found to vary significantly under space, months and seasons.
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