DETERMINATION AND PREDICTION OF BIOGAS PRODUCTION POTENTIAL FROM SELECTED BIOMASSES AS ALTERNATIVE RENEWABLE ENERGY SOURCE IN NIGERIA

ABSTRACT

Biomass is renewable energy sources which are not exhaustible in nature .There are different varieties of biomass in Nigeria. The Nigerian government over the years has made concerted effort to salvage the power sector. Inspite of government efforts, there are lots of challenges facing the power sector. A major challenge facing the power sector is the insufficient energy supply. There is therefore the need to diversify the energy sources to increase energy supply. The aim of this study was to determine and predict biogas production potential from selected biomasses as alternative renewable energy source in Nigeria.

Three selected biomasses: Pennisetum purpureum, Polyscias balfouriana and Breynia nivosa were subjected to physiochemical analysis comprising of proximate and ultimate analysis. The energy content of the samples was determined. From further investigation from the experimental study using mono and co - digestion fermentation in a total of 22 digesters each of 10 liter capacity for retention period of 60 days, the following additional parameters were obtained: the volume .composition of biogas, temperature and COD removal. The moisture content and volatile solid ranged from 62.11% - 83.72% and 65.99% - 87.79%. The ash content and total solid ranges were 1.75% – 22.2% and 17.61% – 84.24 respectively. The carbon and nitrogen content were 26.25% - 45.61% and 0.99% - 2.19%. The energy content varied between 13.95 – 17.21 kJ/kg. The mean volume of biogas for mono and co digested samples were 14,337.20 ml and 19,820.81 ml respectively. The maximum cumulative composition of methane for co – digested and mono digested samples were 75.3% and 54.6% respectively. The temperature of the various digesters in the study varied within the mesophilic temperature range of 20⁰C - 37⁰C. The COD removal was above 80% for co-digested samples and varied between 50% - 68%. The modified Gompertz and Logistic models were more reliable in predicting the biogas potential yield in this study.