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Prediction of carbon, hydrogen, and oxygen compositions of raw and torrefied biomass using proximate analysis.

Authors :
Nhuchhen, Daya Ram
Source :
Fuel. Sep2016, Vol. 180, p348-356. 9p.
Publication Year :
2016

Abstract

Elemental compositions of biomass are essential for designing energy conversion systems. Only a few correlations to estimate the elemental compositions using the proximate analysis of raw biomass have been published so far. Recently researches on biomass torrefaction have been increasing significantly, which require performing an elemental analysis of the torrefied biomass. Torrefaction affects both the proximate and elemental analyses of biomass. Therefore, this study examines if the existing correlations can be deployed or not for estimating carbon, hydrogen, and oxygen compositions of the torrefied biomass. For this, estimation errors were calculated for the existing correlations using data from the torrefied biomass. Results suggest that existing correlations were not suitable for predicting the elemental compositions of the torrefied biomass. New correlations were proposed using a wide range biomass, including both raw and torrefied biomass (447 samples). New correlations C = - 35.9972 + 0.7698 VM + 1.3269 FC + 0.3250 ASH , H = 55.3678 - 0.4830 VM - 0.5319 FC - 0.5600 ASH , and O = 223.6805 - 1.7226 VM - 2.2296 FC - 2.2463 ASH were selected for future use. These correlations have the MAE of 2.58%, 0.41%, 2.60%, the AAE of 5.23%, 9.94%, 8.79%, the ABE of 0.45%, 2.82%, 2.01%, and the R 2 of 0.83, 0.70, 0.84 corresponding to the measured values of C , H , and O , respectively. The selected correlations were also validated and compared with the existing correlations using another set of data that includes raw, washed, torrefied, and carbonized biomass. Selected new correlations could be used for predicting carbon, hydrogen, and oxygen compositions in the raw and torrefied biomass, especially those biomasses which have negligible nitrogen and sulfur contents. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00162361
Volume :
180
Database :
Academic Search Index
Journal :
Fuel
Publication Type :
Academic Journal
Accession number :
115110387
Full Text :
https://doi.org/10.1016/j.fuel.2016.04.058