Tesis
Modelación de la dispersión de contaminantes atmosféricos SO2 y PM10, emitidos por la Refinería Estatal de Esmeraldas en el año 2015.
Fecha
2017-08Registro en:
Reyes Vera, Carlos Humberto. (2017). Modelación de la dispersión de contaminantes atmosféricos SO2 y PM10, emitidos por la Refinería Estatal de Esmeraldas en el año 2015. Escuela Superior Politécnica de Chimborazo. Riobamba.
Autor
Reyes Vera, Carlos Humberto
Resumen
The dispersion modeling of atmospheric pollutants SO2 and PM10, emitted by the Esmeraldas refinery in the year 2015 was carried out. For this, a data base in Excel of the concentrations of ug/m3 oh the pollutants was carried out, depending on the geographical distribution of themonitoring stations located in the study area, an exploratory analysis to the data from a box diagram in Infostat software was applied, to determine the correlation, variability and atypical values; debugged the information was implemented a geo-statistical analysis of the data with the tool Geostatistical Analyst Software ArcMap 10.2.2. of ESRI, it was assessed whether the data have a normal distribution and trend: after the process was implemented the kriging interpolation model to predict the dispersion of the pollutants and the IDW model to shape areas with lower or higher concentration, the result obtained are raster images representing the distribution of pollutants, each pixel that forms the image Contains the concentration that the model generated from base data, it was determined that form the year 2015 the monitoring stations exceeded the maximum permissible limit of 50 ug/m3, Mirador Tercer Piso – 55.92 ug/m3 and Playas Hamacas 58.33 ug/m3; for SO2 no stations exceeded the standard which is 60 ug/m3; The stations that exceeded the limits are located in the urban area of Esmeraldas Canton, where the highest vehicular traffic affected the high concentrations registered, with respect to the Refinery none of the stations around it exceeded the norm, this being an indicative of the good environmental management that is given. It is recommended to extend the present investigation with the implementation of other methods of prediction that allow to make statistical comparisons with the result here obtained.