Assessment of carbon footprint for electricity generation in Michael Okpara University of Agriculture, Umudike

Abstract

This work forecasts CO₂ emissions from hybrid energy consumption in the Michael Okpara University of  agriculture Umudike. By using primary consumption information from the university to establish carbon emission-based data from grid electricity and fossil energy use, the carbon emission from consumption of energy in MOUAU from January to July 2017 was found to be 705,505.01 kg, of where the carbon emission from fossil and grid electricity consumptions were 609,831.00 kg and 95,674.01 kg, with corresponding proportions of 86.43 % and 13.56 % respectively. The largest amount of carbon emission of 64,079.44 kg was from the Administrative Building with 56,808 kg generated and 7,217.44 kg from the grid. A backward propagation using Artificial Neural Network (ANN) was developed, trained for validation using the CO₂ emission data of MOUAU in predicting the local contribution to global emission data. The results obtained showed that an ANN application is efficient and useful in solving climate pollution problems.