Statistical evaluation of quality parameters of olive stone to predict its heating value

Identificadores
URI: http://hdl.handle.net/10498/33299
DOI: 10.1016/j.fuel.2013.06.019
ISSN: 0016-236
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Mostrar el registro completo del ítemFecha
2013Departamento/s
Ingeniería Química y Tecnología de AlimentosFuente
Fuel, Vol. 113, 2013, pp. 750-756Resumen
In Andalusia, residual biomass produced in the olive sector results from the large amount of olive groves
and olive oil manufacturers that generate byproducts with a potentially high energy content, suitable for thermal and electrical energy production. The main residue, olive stone, is an important solid biofuel and is widely generated and consumed. Consequently, olive stone quality parameters must be studied in
order to achieve an optimum energetic efficiency. Therefore, the main objective of this study is to describe olive stone energetic properties and to evaluate variability of these parameters before
consumption. For this purpose, mean values, normal distributions, intervals and deviations of these
parameters have been obtained and studied. Concerning to statistical results, climate and geographical
variability of quality parameters has been described. Furthermore, variations between olive stone
physicochemical parameters supplied by both olive oil factories and distribution companies have been
calculated. Finally, a correlation between the ultimate analysis and higher heating values (HHV) of olive
stone has been determined. Results obtained show that olive stone pretreatments developed by
distribution companies have a significant effect on quality parameters such as moisture content and
low heating value. Moreover, olive stone properties dependence on factors such as rainfall or soil type
has not been confirmed. Lastly, the calculated correlation based on ultimate analysis (i.e. HHV(MJ/
kg) = 0.401C - 0.164H + 0.493N + 2.381S + 0.791) has been developed and validated with olive stone
samples with HHV range from 20 to 21 MJ/kg (dry weight). Correlation has a mean absolute error
(MAE) of 0.43% and a mean bias error (MBE) of -0.12% which indicate that it can be successfully used
as a more economical and faster tool to accurately estimate olive stone HHV. The HHV prediction
accuracies of 14 other correlations introduced by other researchers are also compared in this study.
Materias
Higher heating value (HHV); Ultimate analysis; Proximate analysis; Solid biofuels; Olive residuesColecciones
- Artículos Científicos [11977]
- Articulos Científicos Ing. Quim. [313]
- Artículos Científicos IVAGRO [733]






