Utilizing K-Means Clustering in Understanding the Relationship between Absorbing Aerosol Index and Selected UV Absorbers over East Africa for the Period 2000 to 2014.

Determination of UV absorbing aerosols such as dust and smoke can be inferred from the absorbing aerosol index (AAI) (also called UV Aerosol Index (UVAI). AAI positive values indicate the presence of selected pollutants among them Ozone (𝑂3) and Sulphur dioxide (𝑆𝑂2) that were retrieved from Ozone Monitoring Instrument (OMI) for the period 2000 to 2014. Selected regions of East Africa, that are known to have been affected anthropogenically are Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0-0.6ºS; 35.1- 35.7ºE), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0ºN, 32.1ºE). The anthropogenic influence that has been promoted by massive deforestation to allow for agriculture and urbanization has positively impacted on the enhancement of pollutants in the regions atmosphere which calls for an inference of ascertaining the relationship between AAI with 𝑂3 and AAI with 𝑆𝑂2. The present study utilizes the K-means clustering technique (algorithm) to establish a pairwise relationship between AAI with 𝑂3 and AAI with 𝑆𝑂2. The pairwise relationship between AAI with 𝑂3 and 𝑆𝑂2 characteristics are mainly controlled by dominant seasons and anthropogenic activities dominating each study site.