Modelling and characterization of fine Particulate Matter dynamics in Bujumbura using low cost sensors
This provides the first spatio-temporal analysis of PM2.5 in Bujumbura, addressing air quality monitoring in an understudied urban area, though it is incremental in method.
This study tackled the problem of air pollution in Bujumbura by characterizing PM2.5 dynamics using low-cost sensors, finding that average concentrations (28.3-35.0 μg/m³) exceeded WHO standards, and they used an LSTM model for forecasting.
Air pollution is a result of multiple sources including both natural and anthropogenic activities. The rapid urbanization of the cities such as Bujumbura economic capital of Burundi, is one of these factors. The very first characterization of the spatio-temporal variability of PM2.5 in Bujumbura and the forecasting of PM2.5 concentration have been conducted in this paper using data collected during a year, from august 2022 to august 2023, by low cost sensors installed in Bujumbura city. For each commune, an hourly, daily and seasonal analysis were carried out and the results showed that the mass concentrations of PM2.5 in the three municipalities differ from one commune to another. The average hourly and annual PM2.5 concentrations exceed the World Health Organization standards. The range is between 28.3 and 35.0 microgram/m3 . In order to make prediction of PM2.5 concentration, an investigation of RNN with Long Short Term Memory (LSTM) has been undertaken.