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The data provided in this article supplements the data information provided in “Techno-economic analysis of electricity and heat production by co-gasification of coal, biomass and waste tyre in South Africa” [1]. The generation of the data considered co-generation of a coal sample (Matla coal) with pine sawdust, sugarcane bagasse, corn cob, and waste tyre at a blend ratio of 1:1, 3:2, and 4:1. The cost evaluation of the use of the feedstocks was considered with feedstock costing (WFC) and without feedstock costing (WOFC). Profitability assessment tools for the case study included NPV, IRR and PBP. The data as contained in this article could be useful for a quick decision making on a similar project by the government and stakeholders in the sector.

Kinetic studies of heterogeneous catalytic reactions form a crucial step necessary for the understanding of catalytic behaviour of a catalyst towards designing, controlling and optimizing a reactor. This study reports kinetics of waste animal fat oil (AFO) transesterification to biodiesel using waste-derived heterogeneous catalyst, hydroxy sodalite (HSOD) in a batch reactor. The catalyst was synthesized from coal fly ash and waste industrial brine via hydrothermal treatment. At a temperature range of 49 - 62 °C and a time range of 30 -120 minutes, the transesterification of animal fat oil to biodiesel was conducted at a fixed methanol/oil mass proportion 9:1, percent mass weight of catalyst 3 (based on the AFO) and stirring intensity of 300-500 rpm. Experimental findings reveal that reaction rate, which is first-order, was anticipated to increase with increasing temperature, resulted in an activation energy and a pre-exponential factor of 58554.65 J mol-1 and 2.83 min-1, respectively. The value of the activation energy suggests that the reaction is endothermic and a minimum energy of 58.55 kJ is required to achieve an effective collision at a frequency of 2.83 min-1. The highest biodiesel yield was 90 % at 62 °C and this corresponds to a highest AFO conversion of 93 % at a reaction time of 120 minutes.

The local sourcing of feedstock for energy generation will reduce costs in the power plant, and promote energy sustainability. Most times, potential investors in this area show interest about understanding the profitability of the business because, the information boosts the confidence of the investors in the project, and gives them the opportunity of making a short and long term plans about the business. The emissions arising from the energy plant is an important aspect of the venture that requires proper attention, otherwise the costs of emission control may consume a greater part of the profit, hence rendering the business un-viable. Nigeria and South Africa (SA) have abundant biomass (e.g. corn cob, sugarcane bagasse, & pine saw dust) coal and tyre that can be used as fuel in an energy plant. A 10 MW CHP plant was fired with coal and biomass, and tyre obtained from Nigeria and South Africa (SA) respectively, at ratios of 1:1, 3:2, and 4:1 to study the emissions and profits in the plant. An empirical model was employed to estimate the annual amount of feedstock and feed rate required for the plant, after which, an artificial neural network (ANN); Levenberg-Marquardt algorithm was used to predict the emissions and profits in the plant for 20-year-investment period with feedstock costing (WFC) and without feedstock costing (WOFC). The profit obtained from the South African feedstock, WFC and WOFC; produced about 45.18 % and 36.83 % ($3, 900, 000.07 and $3, 179, 184.49) higher profits than the Nigerian feedstock, but the CO, NOX, & SO2 emissions from Nigerian feedstock were lower than that of SA. The findings from this study could be used as a platform for decision making by potential investors and stake-holders, and further research and development in the area.