Application of Data Envelopment Analysis (DEA) in determining GHG emission and carbon sequestration in small-scale maize production in Niger State, Nigeria

This research empirically estimates potential energy utilization and GHG emission sequestration in small-scale maize production in Niger State, Nigeria using Data Envelopment Analysis (DEA). Data for the study were obtained from Kuta agricultural zone in Niger State; 120 maize farmers were randomly selected through multi-stage sampling technique, and data collected with the aid of pre-tested questionnaire coupled with interview schedule. Energy efficiency of maize farmers was studied and degrees of overall technical efficiency (CCR), pure technical efficiency (BCC) and scale efficiency (SE) were determined using a neoclassical non-parametric model called Data Envelopment Analysis (DEA). Additionally, wasteful uses of energy by inefficient DMUs (farms) were examined, and energy saving of different sources estimated. Furthermore, the effect of energy optimization on greenhouse gas (GHG) emission was investigated and the total amount of GHG emission of efficient DMUs (farms) was compared with inefficient DMUs. Results revealed that approximately 9.2% of the farmers were technically efficient with an estimated mean TE of 0.68. Furthermore, when BCC model was assumed, 24 farmers (DMUs) were identified to be locally efficient (20%), with mean PTE of 0.78. From the results, it was inferred that 32% (768.89MJ ha-1) of overall input energies can be saved if the performance of inefficient DMUs (farms) rose to a high level. Finally, by energy optimization the total GHG emission can be reduced to an estimated value of 394.91 kg CO2eq