Tailpipe emissions from vehicles consist of CO2 and other greenhouse gases, which contribute immensely to the rise in global temperatures. Green hydrogen produced from the gasification of biomass can reduce the amount of CO2 emissions to zero. This study aims to provide a modelling framework to optimize the production of hydrogen from biomass waste obtained from different cities, for use in the road transport sector in Nigeria. A gasification model with post-treatment shift conversion and CO2 removal by adsorption is proposed. In this study, six cities are simulated based on technical and environmental considerations, using the Aspen Plus software package. The results revealed that Kaduna has the highest hydrogen generation potential of 0.148 million metric tons per year, which could reduce CO2 emissions to 1.60 and 1.524 million metric tons by the displacement of an equivalent volume of gasoline and diesel. This amounts to cost savings of NGN 116 and 161.8 billion for gasoline and diesel, respectively. In addition, the results of the sensitivity analysis revealed that the steam-to-biomass ratio and the temperature of gasification are positively correlated with the amount of avoided CO2 emissions, while the equivalence ratio shows a negative correlation.

Criteria weights exert much influence on the final outcome of a decision-making process, and with regards to obtaining accurate measurements of criteria weights, the use of the combined weight method, which integrates the subjective and objective weights into a single component has been investigated in the literature.  The recalculated weight method, which is derived from the application of the Bayes theorem, proposes a more accurate determination of the weights of criteria used in Multi-criteria decision-making. Previous studies on the accuracy of criteria weight determination focus on the combined weight method, where the subjective and objective criteria weights are integrated into a single component, thereby creating a gap in the literature for the exploration of more accurate methods for criteria weight determination. In this paper, the decision matrix used in the recalculated weight method is obtained from the results of the simulation conducted in a slum settlement in Nigeria, with the use of the HOMER software. The objective weights and subjective weights are obtained initially from the AHP/Fuzzy AHP and Critic/Entropy methods. PROMETHEE method is used to rank the best hybrid renewable energy technology and a comparative analysis between the recalculated weight method and the combined weight method is carried out to determine their level of accuracy. The results obtained are validated with the use of the VIKOR and TOPSIS outranking methods. Findings from the result reveal that with the recalculated weight method there is 92% accuracy in criteria weight measurement.

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