PUBLICATIONS

Aerosol Optical Depth Patterns Associated with Urbanization and Weather in Nairobi and Lamu

Volume 8:3
https://doi.org/10.20987/jmrs.2016.02.803
Cohen Ang’u, Nzioka J. Muthama and Bethwel K. Mutai
University of Nairobi
CORRESPONDING AUTHOR
Cohen Ang’u
University of Nairobi
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Cell: +254704739039

 

 (Received 9 June 2015, Received in revised form 18 February 2015, Accepted 2 March 2016)

Abstract

The massive increase in emissions of air pollution due to economic and industrial growth over the last century has made air pollution an environmental problem throughout the world. This study investigated the spatial-temporal characteristics of particulate air pollutants and its association with rainfall and wind variation over Nairobi and the upcoming Lamu city. The study utilized daily wind speed and direction, population data, land surface reflectivity, aerosol optical thickness and rainfall data. Wind rose plot view was used to analyze wind speed and direction. Time series and correlation analyses were done using R programming environment for statistical computing and graphics. Population and land surface reflectivity were used as indicators of urbanization. The dominant winds over Nairobi were found to be east-north-easterlies while southerlies and easterlies were found to be dominant over Lamu. Wind speed and direction does not seem to change significantly. Aerosol optical thickness and rainfall showed a significant correlation. In Lamu County high values of aerosol optical thickness were recorded over Witu division. In the neighborhood of Nairobi, South eastern parts had high concentration of aerosols. Seasonally, the JJA (June July August) season had the highest values of aerosol optical thickness. These findings will be useful to researchers and ministries interested in environmental and air pollution matters concerning Nairobi and the Lapsett project.
Key words: urbanization, aerosol optical thickness, pollution, R programming
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