Numerical prediction of the chemical composition of gas products at biomass combustion and co-combustion in a domestic boiler
Czestochowa University of Technology, Faculty of Production Engineering and Materials Technology, Department of Industrial Furnaces and Environmental Protection, Al. A. Krajowej 19, 42-201 Czestochowa, Poland
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In recent years the numerical modelling of biomass combustion has been successfully applied to determine the combustion mechanism and predict its products. In this study the influence of the addition of waste glycerin in biomass wood pellets on the chemical composition of exhaust gases has been investigated. The pellets have been prepared from spruceand pine wood sawdust without and with addition of waste glycerin. The waste glycerol is a undesirable by-product of biodiesel transesterification at oil manufacturing. The produced pellets were being burned in the 10 kW domestic boiler adapted to wood pellets combustion. The possibilities of pollutants generation (CO2, CO, NOx SOx and compounds containing chlorine) in the exhaust gases coming from the boiler were numerically calculated using the latest version of CHEMKIN-PRO software, introduced by the American company Reaction Design. The results of the calculations correspond to the data obtained on a real object, in particular: combustion temperature, gas pressure, residence time of fuel in the burner, air flow, fuel consumption, as well as elementary composition of fuel supplied into the boiler. The proposed method of predicting the chemical composition of exhaust gases allows proper control of the combustion process and can be considered as an important step in reducing the pollutants (lower emission of NOx, SOx and CO2 neutral) and thus to contribute to the improvement of the environmental quality. In addition, knowledge of the amounts of Clbased compounds produced in combustion process (under given conditions), can serve as an important hint in terms of corrosion prevention of boiler- and chimney steels.
© The Authors, published by EDP Sciences, 2017
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