Modelling spatio-temporal trends of air pollution in Africa

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ID: 282673
2022
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Abstract
Atmospheric pollution remains one of the major public health threat worldwide with an estimated 7 millions deaths annually. In Africa, rapid urbanization and poor transport infrastructure are worsening the problem. In this paper, we have analysed spatio-temporal variations of PM2.5 across different geographical regions in Africa. The West African region remains the most affected by the high levels of pollution with a daily average of 40.856 $\mu g/m^3$ in some cities like Lagos, Abuja and Bamako. In East Africa, Uganda is reporting the highest pollution level with a daily average concentration of 56.14 $\mu g/m^3$ and 38.65 $\mu g/m^3$ for Kigali. In countries located in the central region of Africa, the highest daily average concentration of PM2.5 of 90.075 $\mu g/m^3$ was recorded in N'Djamena. We compare three data driven models in predicting future trends of pollution levels. Neural network is outperforming Gaussian processes and ARIMA models.
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ndamuzi2022modelling Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Paterne Gahungu; Jean Remy Kubwimana; Lionel Jean Marie Benjamin Muhimpundu; Egide Ndamuzi
Journal arXiv
Year 2022
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