Defining the Mathematical Dependencies of NOx and CO Emission Generation after Biomass Combustion in Low-Power Boiler
| Author(s): |
Ladislav Lukáč
(Technical university of Košice , Faculty of Materials, Metallurgy and Recycling, Institute of Metallurgy , Letná 9, 042 00 Košice , Slovak Republic)
Ján Kizek (Technical university of Košice , Faculty of Materials, Metallurgy and Recycling, Institute of Metallurgy , Letná 9, 042 00 Košice , Slovak Republic) Gustáv Jablonský (Technical university of Košice , Faculty of Materials, Metallurgy and Recycling, Institute of Metallurgy , Letná 9, 042 00 Košice , Slovak Republic) Yevgeniy Karakash (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, September 2019, 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. |
- About this
data sheet - Reference-ID
10705186 - Published on:
19/02/2023 - Last updated on:
19/02/2023
