Seasonal variations of atmospheric pollutants in Oil producing communities of Rivers State using Satellite application.

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Okoro, Goodluck

Seasonal variations of atmospheric pollutants in Oil producing communities of Rivers State using Satellite application.

Keywords : Pollutants, Concentration, BTEX, Simulation, Satellite data and Communities Introduction


Abstract

This study is aimed at demonstrating the application of satellite data in analysing the seasonal pattern of air pollution in the Oil producing communities in Rivers State with a view of providing valuable information for effective adaptation mechanisms to the residents. Air quality satellite data was collected from NASA Goddard Earth Sciences database using the ground coordinates of the study areas (Ebocha, Mgbede and Okwuzi) which was got from field work. Parameters of concern for which data were collected are SO2, PM2.5 and VOC as Formaldehyde (HCHO) from December, 2018, January and February, 2019 for the dry season while June, July and August 2019 for the wet (rainy) season. The data were extracted from the dataset using python programming language. The analytical techniques were descriptive using tables and percentages and trend analysis. In this study, hot spots are areas with high perceived level of air pollution whereas cold spots are with perceived low level of air pollution. Ebocha community is mostly polluted among the three communities during the dry season with values of SO2=1.65378E-06kg/m2,1.15342E-06 kg/m2,9.15046E-07 kg/m2 , PM2.5 = 2.08793E-05 kg/m2, 2.99876E-06 kg/m2,3.62596E-06 kg/m2, and HCHO= -7.68E+17 molec/cm2,-1.29E+18 molec/cm2,-8.58E+17 molec/cm2 while Okwuzi is most polluted during the wet (rainy) season with SO2 levels = 8.94634E-08 kg/m2, 8.5244E-12 kg/m2 ,7.81415E-08 kg/m2, PM2.5= 1.25707E-05 kg/m2, 6.01465E-06 kg/m2, 2.86769E-06 kg/m2 and HCHO= -2.68E+17 molec/cm2 -3.08E+17 molec/cm2 -4.92E+17 molec/cm2 . In both seasons, pollutants in Mgbede community are lowest. Ebocha and Okwuzi communities are known as the pollution hot spots while Mgbede community as the pollution cold spot in the study area. It is therefore recommended that real time air quality monitoring facilities and alert systems should be installed across the study area and environmental education strengthened as ways of adaptation during the peak pollution periods.

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