| Popis: |
Nitrogen dioxide emission is part of atmospheric pollutant that has been linked to climate change. Artificial neural network model were used to investigate nitrogen dioxide distributions in Nigeria at a selected points. The study areas used in this work are thirty six (36) points over Nigeria as shown in Fig. 1. The data used in this work is a satellite nitrogen dioxide () obtained from Global Monitoring for Environment and Security (GMES) under the programme of Monitoring Atmospheric Composition and Climate (MACC). The data used in this work is a satellite nitrogen dioxide data obtained from 2003-2014. The neural network processed the available data by dividing them into three portions randomly: 70% for the training, 15% for validation and the remaining 15% for testing. Input parameters were chosen to be latitude, longitude, day of the year, year. Observed nitrogen dioxide was inputted as targeted data, while the output nitrogen dioxide data were the estimated data. The results reveal that dry and wet season variations differ in Nigeria. Nitrogen dioxide concentrations were observed to be higher in the North during dry season, but were higher in the South during the wet season. This could imply that weather condition and seasons influences the concentrations and variations of nitrogen dioxide in Nigeria. The similar trend of the estimated and observed nitrogen dioxide of both diurnal and annual distributions suggests good performance of the model. The result shows that high concentrations of nitrogen dioxide contribute to climate change in Nigeria, resulting to global warming. Consequently, if left unchecked, increase in nitrogen dioxide may cause alteration in rainfall regimes and patterns, floods, and so on. These in turn will bring about adverse effects on livelihoods, such as crop production, livestock production, fisheries, forestry and post-harvest activities. Finally, we recommend analysis of nitrogen dioxide distributions in Nigeria to be regular. |
