Assessing the influence of biomass properties on the gasification process using multivariate data analysis

摘要: Abstract Multivariate analysis was used to study the influence of biomass characteristics on gasification process. Ten lignocellulosic samples (almond shells –AS–, chestnut sawdust –CHE–, torrefied –CHET–, cocoa –CS–, grape pomace –GP–, olive stones –OS–, pine cone leafs –PCL–, –PIN–, –PINT–, and kernel –PKS–) were gasified in a bubbling fluidized bed gasifier under an air-steam atmosphere. Statistical applied variables that described results process, i.e., gas concentration, production (moles), calorific value product gas, energy density, cold efficiency, together with main properties, such as those derived from elemental proximate analyses, higher heating (HHV), particle composition ashes. Hierarchical cluster (HCA) principal component (PCA) data properties parameters order elucidate which feedstock features had more determinant Both HCA PCA revealed clear separation into two groups basis results. The indicated PKS, PCL, PINT, OS PIN biomasses characterized by high combustible gases, CO CH4, conversion efficiency during gasification. This most important for promoting production, C H contents HHV biomass. However, CS GP mainly H2 concentration H2/CO molar ratio product, related H/O K2O ash content negatively O VM Therefore, it can be concluded use multivariate statistical techniques analyzing facilitated draw valuable conclusions about