Dataset of PM10 Level and Predictors in Addis Ababa

The dataset for PM10 concentration prediction was compiled from 25 predictor variables and PM10 measurements from 11 monitoring stations in Addis Ababa. The final dataset consists of 38,408 observations spanning two years, from August 2021 to August 2023. The predictor variables encompass various factors impacting PM10 levels, including atmospheric conditions such as atmospheric density (AD), temperature (Ta), wind exposure (WEX), wind speed (WS), and rainfall (RF); urban features like night light (NL), land surface temperature (LST), urban index (UI), road density (RD), and building density (BD); terrain characteristics such as elevation (ELV), slope (SLP), topographic wetness index (TWI), terrain roughness index (TRI), and Soil-Adjusted Vegetation Index (SAVI); and proximity to potential PM10 sources including airports, petrol stations, roads, quarries, railways, markets, waste sites, bus stations, construction sites, and industries. This dataset facilitates the development of robust predictive models and supports the creation of effective air quality management strategies for Addis Ababa and other urban areas facing similar challenges.