Energy Content Estimation in Waste Saw Dust, Maize Cobs and Rice Husks Using Multiple Regression Analysis

Solid wastes are produced and accumulated due to human activities. Energy recovery from the wastes is considered a sound waste management practice. Energy recovery process can be anaerobic digestion, incineration, pyrolysis and gasification among others. It is important to estimate the theoretical energy content of the wastes in order to accurately determine system performances and process efficiency. This is important during planning of waste to energy strategies. Saw dust, maize cobs and rice husks waste were sampled from dumpsites, dried and stored in contamination free environment. Samples were analyzed for the concentration of moisture, Carbon (C), Nitrogen (N), Hydrogen (H), oxygen (O) and sulfur (S). Saw dust contained 49.080.07 % C, 6.040.05 % H, 40.890.18 % O, 0.250.06 %N and 0.0780.01 % S, while rice husk contained 42.90.71 % C, 4.060.07 % H, 35.980.11 % O, 1.020.02 % N and 0.20.01 % S. A model for estimation of municipal solid waste energy content was developed using input parameters of the waste composition. Based on the results of regression analysis, a mathematical model equation was developed which was used to predict the higher heating value (HHV). The results of this model compares well with experimental data and the Du Long formula. The model provides a quick and accurate method of higher heating value determination where the elemental composition of the wastes is known and can be applied for segregated wastes and mixed waste.