Modeling of gaseous pollutants (CO and NO2) emission from an industrial stack in Kano city, northwestern Nigeria

In this study, we derived an analytical solution from the Gaussian approach and used it to estimate or predict the concentration of gaseous pollutants (CO and NO2) emitted from an industrial stack in northwestern Nigeria. The model results were compared with experimental data collected from the Terytex industry, Nigeria in Kano city using Altair 5X multi-gas detector for one year. The device is a portable handheld digital gas sensor meter that determines the concentrations of up to five gases simultaneously. The dispersion pattern of the pollutants was 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. The measured and modeled averaged results ranged from 20.0 to 52.0 μg/m3 for NO2 and 8.0–16.0 μg/m3 for CO which are within the World Health Organization guideline and Nigeria Ambient Air Quality Standards except for CO values which were at some points higher than the set limits of (11.4 μg/m3). Statistical tools were also applied to test the model derived, and our findings revealed that the applied model was very useful under neutral conditions and in predicting the gaseous pollutants. We recommended that the concentration levels of CO and NO2 emissions control through complete combustion or industrial gas absorbers and the use of low-NOX burner (LNB) that operate at cooler temperatures to minimize the formation of thermal NOX. This will eliminate the consequences of effects on biological systems. •Modeling of CO & NO2 emission from an industrial stack has been carried out.•The high emission levels of CO & NO2 captured in the study area is a staid problem.•The applied model is found useful for CO & NO2 estimation in absence of in situ data.•The study provided baseline data for continuous monitoring of the study area.•We recommended measures that can mitigate the effects of these pollutants in the air.