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Defining the Mathematical Dependencies of NOx and CO Emission Generation after Biomass Combustion in Low-Power Boiler

Author(s): (Technical university of Košice , Faculty of Materials, Metallurgy and Recycling, Institute of Metallurgy , Letná 9, 042 00 Košice , Slovak Republic)
(Technical university of Košice , Faculty of Materials, Metallurgy and Recycling, Institute of Metallurgy , Letná 9, 042 00 Košice , Slovak Republic)
(Technical university of Košice , Faculty of Materials, Metallurgy and Recycling, Institute of Metallurgy , Letná 9, 042 00 Košice , Slovak Republic)
(Department of Ecology, Heat Transfer and Labour Protection , National Metallurgical Academy of Ukraine , Gagarine av. 4, Dnipro , Ukraine)
Medium: journal article
Language(s): English
Published in: Civil and Environmental Engineering Reports, , n. 3, v. 29
Page(s): 153-163
DOI: 10.2478/ceer-2019-0031
Abstract:

The paper deals with the study of the influence of various factors, which have an impact on emissions such as NOx, CO, which have been verified by measurements. Biomass in the form of wood chips as fuel of different moisture content from 9% to 25% has been tested at various boiler outputs. The presented work also defines the mathematical dependencies of NOx and CO emission generation by using regression analysis from measured data after biomass combustion in low-power boilers. The paper also describes a mathematical model of biomass combustion. The mathematical model was created to verify the measured data and prediction of emission generation in the process of biomass combustion. This model consists of combustion of stoichiometry, calculation of combustion temperatures, obtained regression equations of NOx and CO. At the end of this paper, the obtained results are compared with the calculated models as well as the results of the defined dependencies from the regression analysis.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.2478/ceer-2019-0031.
  • About this
    data sheet
  • Reference-ID
    10705186
  • Published on:
    19/02/2023
  • Last updated on:
    19/02/2023
 
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