Modelling plume dispersion pattern from a point source using spatial auto-correlational analysis

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Abstract

The main objective of the study is to estimate the rate and model the pattern of plume rise from Dangote Cement Plc. A handheld Garmin GPS was employed for collection of coordinates at a single kilometre graduation from the centre of the factory to 10 kilometres. Plume rate was estimated using the Gaussian model while Kriging, using ArcGIS, was adopted for modelling the pattern of plume dispersion over a 10 kilometre radius around the factory. ANOVA test was applied for statistical analysis of the plume coefficients. The results indicate that plume dispersion is generally high with highest values recorded for the atmospheric stability classes A and B, while the least values are recorded for the atmospheric stability classes F and E. The variograms derived from the Kriging reveal that the pattern of plume dispersion is outwardly radial and omni-directional. With the exception of 3 stability sub-classes (DH, EH and FH) out of a total of 12, the 24-hour average of particulate matters (PM10 and PM2.5) within the study area is outrageously higher (highest value at 21392.3) than the average safety limit of 150 ug/m3-230 ug/m3 prescribed by the 2006 WHO guidelines. This indicates the presence of respirable and non-respirable pollutants that create poor ambient air quality. The study concludes that the use of geospatial technology can be adopted in modelling dispersion of pollutants from a point source. The study recommends ameliorative measures to reduce the rate of plume emission at the factory. © Published under licence by IOP Publishing Ltd.

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APA

Ujoh, F., & Kwabe, D. (2014). Modelling plume dispersion pattern from a point source using spatial auto-correlational analysis. In IOP Conference Series: Earth and Environmental Science (Vol. 18). Institute of Physics Publishing. https://doi.org/10.1088/1755-1315/18/1/012077

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