Back to Search
Start Over
Thermo-Optical and Particle Number Size Distribution Characteristics of Smoldering Smoke from Biomass Burning.
- Source :
- Applied Sciences (2076-3417); Dec2019, Vol. 9 Issue 23, p5259, 14p
- Publication Year :
- 2019
-
Abstract
- Controlled laboratory combustion experiments were conducted in the fire test room to mimic freshly emitted smoldering smoke of biomass burning in China. The biomass components were determined by ultimate analysis and proximate analysis before experiments. The particle number size distribution (PNSD) between 5 and 1000 nm of smoke was measured by a high sampling frequency size spectrometer. A cavity-enhanced aerosol albedometer with wavelength of 532 nm was used to measure scattering coefficients, extinction coefficients, and single scattering albedo (SSA) of smoldering smoke. The PNSDs of smoldering smoke from the burning of agricultural straw could be fitted with a bimodal lognormal distribution as modes around 10 nm (nucleation mode) and 60 nm (Aitken mode). The PNSDs of wood sawdust could be fitted with a trimodal lognormal distribution, while the two modes were in nucleation mode, and one was in Aitken mode. The bulk optical properties (scattering and extinction coefficients) of smoldering smoke had strong correlations with particle number concentrations of sizes bigger than 100 nm. The correlation between SSA and fixed carbon (FC) was strong (the correlation coefficient is 0.89), while the correlation between SSA and volatile matter (VM) or ash was weak. The relationship between SSA and N (or S) showed a positive correlation, while that of SSA and C showed a negative correlation. The relationship between SSA and VM/FC (or N) showed a strong linear relationship (r<superscript>2</superscript> > 0.8). This paper could improve understanding of the relationship between the optical and particle size distribution properties of smoke from biomass burning and the components of biomass materials under similar combustion conditions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 9
- Issue :
- 23
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 140256063
- Full Text :
- https://doi.org/10.3390/app9235259