This paper evaluates the effects of long-range transport patterns of air trajectories arriving at a rural ground based station, ICIPE Mbita 1125 meters above mean sea level. Mass concentration data of fine mode AOD, coarse mode AOD and fine mode fraction AOD were combined with back-trajectory cluster analysis. The Potential Source Contribution Function (PSCF) model and Concentration-Weighted Trajectory (CWT) method were used to evaluate the transport pathways and Potential Source Areas (PSA) affecting AOD loadings in western parts of Kenya during wet (MAM) and dry (JJA) seasons. The main sources and paths of advection to source and receptor regions and its relation to AOD concentration were identified. Using these methods, the Geographic Information System (GIS) based software and MeteoInfo was used for query and computation of potential source contribution function and concentration weighted trajectory analyses when the measurement data were included. The results for both PSCF and CPF were sufficient indicators that pollutants originated from two main sources, that is, northeastern and southeast directions from the site.

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The origins and pathways of atmospheric aerosols in Kenya are examined in Nairobi for the three years (2015-2017) using HYSPLIT model and meteorological data. Aerosol concentrations in Kenya depended on the frequency of the air mass from the northeastern Asian Continent and southeastern Madagascar Island. There was a direct correlation of more pollutants during dry and hot seasons (JJA) of the year. To study the reasons for the seasonal variations, the origins of the air mass flowing to Nairobi were analyzed by backward air mass trajectory analysis. Monthly variations revealed that aerosols are transported from different directions due to variation of winds flowing and peak values were during July because of the increased emissions due to higher temperature and stronger solar radiation during heating, while the lowest value found in April was probably due to rain wash.

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Today, traditional media is still a significant part of disseminating weather and climate information, still they have not been able to reach out to all users of the target audience alone. On the other hand, social media platforms such as Twitter, Facebook, YouTube, Instagram, etc. are used as a tool of communicating weather and climate information to various users in a well-organized manner like never before. Using a scientific research methodology of case study, the research was designed to explore how the Kenya Meteorological Department (KMD) is using Twitter and Facebook accounts for weather and climate information dissemination to various users.