Combining the effects of pulping severity and alkali concentration to optimize the lignocellulose-based AlkaPolP biorefinery concept.

Within the framework of the development of a novel lignocellulose biorefinery concept alkaline polyol pulping (AlkaPolP) of Pinus sylvestris was performed at different alkali concentrations. The obtained experimental data were used to develop simple mathematical models that allow the prediction of product yields and properties in dependence on a single parameter combining the effects of time, temperature and catalyst concentration. For this purpose the usual approach expressing the pulping severity R0 had to be complemented by the alkali concentration resulting in a modified severity factor R₀('). The found regression models in the form of functions f(R₀(')) can be used as a tool for the identification of those pulping conditions giving the desired product characteristics. Because the yields of the biorefinery products reach their maxima at different pulping conditions the optimization of the whole process turned out to be a multi-objective optimization problem.
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