The urgent global challenges of climate change and environmental issues have catalyzed the development of CO2-capture-ready technologies incorporating fluidization, such as fluidized bed (FB) and circulating fluidized bed (CFB) combustion under oxy-fuel conditions, chemical looping combustion (CLC), chemical looping with oxygen uncoupling (CLOU), in-situ gasification chemical looping combustion (iG-CLC), and calcium (or carbonate) looping (CaL) systems. While these technologies have the potential to reduce CO2 emissions significantly, the persistent presence of nitrogen oxides (NOx = NO + NO2) as pollutants remains a critical environmental concern.This paper introduces a comprehensive fuzzy logic-based model for predicting NOx emissions (FuzzyNOx model) from solid fuel combustion in fluidized beds of chemical looping systems. This innovative model takes into account a wide range of operating parameters, including fuel type, fuel particle size, fuel moisture content, air/fuel ratio, and temperature. It also explores advanced coal and biomass combustion modes, including air-firing, oxyfuel, iG-CLC, and CLOU. Furthermore, it delves into the intricacies of two distinct facilities: the 5 kWth dual-fluidized bed Chemical-Looping-Combustion of Solid-Fuels (DFB-CLC-SF) facility at Czestochowa University of Technology, Poland, and the calcium looping dual-fluidized bed (CaL DFB) facility at Niigata University, Japan.Bituminous coal, semi-anthracite, and wood chips are utilized as fuels. Moreover, three various oxygen carriers (OCs) for chemical looping combustion were employed, namely ilmenite, copper oxide (60 % wt.) supported by carbonate waste from ore flotation, and copper oxide (60 % wt.) supported by ilmenite (20 % wt.) and fly ash. Bituminous coal, semi-anthracite, and wood chips are utilized as fuels.The developed knowledge-based fuzzyNOx model allows the optimization of operating parameters to reduce NOx emissions from CO2 capture technologies.
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