Assessment of Climate Change Impacts on Particulate Matter Air Pollution- Induced Human Health in Kenya
Mutai, Bethwel Kipkoech
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Several studies have reported an increase In air pollution in urban centers especially in developing co untries, leading to cardio-respiratory diseases. According to World Health Organisation (WHO), air pollution is estimated to cause about two million premature deaths worldwide annually. This study sought to assess the impacts of climate change on particulate matter (PM) levels and distribution and the concomitant human health effects in Kenya. The data used included temperature, rainfall, aerosol optical depth and respiratory-related diseases. These data sets were collected and analysed for four selected areas within the entire study domain. Short-Cut Bartlett test was employed in the data homogeneity test. Temporal distribution of these datasets was determined using time series analysis. The spatial variation of the same data was obtained by the use of Surfer software (version 8). Pearson's correlation analysis method was used to establish the relationship among the variables. The combined effect of weather and PM on human respiratory health was assessed through the use of multivariate linear regression analysis. From time series analysis seasonality is evident in all the mean monthly datasets. Highest well defined peak in aerosol optical depth (AOO) was observed during June-June-August season due to thermal inversion that results in less atmospheric mixing, increased fuel combustion for domestic heating. Over all the stations except Garissa AOD loading depict significant decreasing trend. Generally, a peak in the number of respiratory cases was observed during March-April- May season over Nyeri due to pollen. The observed seasonality implied that weather has a direct effect on health outcome. Hospital admission was higher among male cohort at about 82% due to increased occupational exposure. Generally, more hospital admission and mortality was reported in the under five due to their vulnerability. From the analysis of minimum temperature, well-defined urban heat island is observed over Eastleigh due city's population build-up. The northern and north eastern parts of the country are centres of heavy AOO loadings due to geographical effects i.e. semi-arid dust. A peak in the number of respiratory cases-was reported over Nyeri due to heavy AOD loading as a result of tree and grass pollen, high population, increased occupational exposure, rural solid fuel use and high reporting rates. A minimum was recorded over Garissa even with cold weather and heavy dust loading due to relatively low urban population, less windy conditions, less dust suspension, natural immunity to pathogens and low reporting rate. The nature of correlation obtained between variables varied in both strength and direction. Temperature showed a stronger correlation with AOD compared to rainfall over Nairobi. The negative relationship was attributed to enhanced pollutant mixing due to instability. Rainfall depicted a weaker but significant correlation. This implied that atmospheric pollutant mixing is dominant over rain/wash-out AOD removal mechanism. Although the individual correlations were not particularly high, they illustrate that one variable is affected differently by different parameters over different locations due to varying seasonal conditions. The present study showed weather and PM accounts for over 84% variance in the number of reported respiratory cases over Nairobi and Nyeri. The least variation in respiratory incidences of about 53% is explained over Mombasa. Even though the slope varied in both strength and direction, AOD had the most strong and positive influence. However the weather variables made a statistically significant contribution. The fact that temperature and rainfall explained the pattern of respiratory diseases showed that thermal environment has significant influence on the occurrence of respiratory diseases. Moreover, the seasonal variation in the occurrence of respiratory diseases considered in this study confirmed the role of seasonal weather conditions in the occurrence of respiratory diseases.