# Modelling spatio-temporal trends of air pollution in Africa

arXiv: https://arxiv.org/abs/2208.12719 · HTML: https://mlsanity.com/paper/2208.12719/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 21 references that are in the map.
- First posted on arXiv 21 Aug 2022.

## Builds on (most cited first, 1 of 1)

- [Trend analysis and forecasting air pollution in Rwanda](https://mlsanity.com/paper/2205.10024/) (2022)

## Built on by (most cited first, 1 of 1)

- [Modelling and characterization of fine Particulate Matter dynamics in Bujumbura using low cost sensors](https://mlsanity.com/paper/2312.12003/) (2023)

## Abstract (arXiv)

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 μ g/m3 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 μ g/m3 and 38.65 μ g/m3 for Kigali. In countries located in the central region of Africa, the highest daily average concentration of PM2.5 of 90.075 μ g/m3 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.