Modelling NO2 emissions from Eskom’s coal fired power stations using Generalised Linear Models

Abstract

The aim of this paper is to determine if a Generalised Linear Model (GLM) is a better model over the traditional simple linear regression when fitted to nitrogen dioxide (NO2) emitted into the atmosphere during the production of electricity from 13 Eskom’s coal fuelled power stations. A GLM was fitted to the NO2 emission data using forward and backward selection of variables for the models. A similar model using regression analysis was fitted for comparison. The results show that a GLM can be used to predict and explain NO2 emissions from coal fired electricity stations in South Africa. The Lognormal model was found to be the better model by diagnostic measures including plots that showed improved variance behaviour in the residuals. Various variables such as amount of electricity sent out (in GWhs), age of power station (in years), power station used, and interaction terms such as electricity and station, Age and station can be used in describing/ predicting NO2 emissions (in tons) from Eskom’s coal fuelled power stations.

Keywords

• lognormal distribution
• generalised linear model(s) (GLM)
• nitrogen dioxide (NO2) emissions
• Eskom
• linear regression