Ionic liquid mediated biomass deconstruction: from analysis challenges to fermentable sugars

Ionic liquids, ILs, have recently been studied with accelerating interest to be used for a deconstruction/fractionation, dissolution or pretreatment processing method of lignocellulosic biomass. ILs are usually utilized combined with heat. Regarding lignocellulosic recalcitrance toward fractionation and IL utilization, most of the studies concern IL utilization in the biomass fermentation process prior to the enzymatic hydrolysis step. It has been demonstrated that IL-pretreatment gives more efficient hydrolysis of the biomass polysaccharides than enzymatic hydrolysis alone. Both cellulose (especially cellulose) and lignin are very resistant towards fractionation and even dissolution methods. As an example, it can be mentioned that softwood, hardwood and grass-type plant species have different types of lignin structures leading to the fact that softwood lignin (guaiacyl lignin dominates) is the most difficult to solubilize or chemically disrupt. In addition to the known conventional biomass processing methods, several ILs have also been found to efficiently dissolve either cellulose and/or wood samples – different ILs are suitable for different purposes. An IL treatment of wood usually results in non-fibrous pulp, where lignin is not efficiently separated and wood components are selectively precipitated, as cellulose is not soluble or degradable in ionic liquids under mild conditions. Nevertheless, new ILs capable of rather good fractionation performance have recently emerged. The capability of the IL to dissolve or deconstruct wood or cellulose depends on several factors, (e.g. sample origin, the particle size of the biomass, mechanical treatments as pulverization, initial biomassto-IL ratio, water content of the biomass, possible impurities of IL, reaction conditions, temperature etc). The aim of this study was to obtain (fermentable) saccharides and other valuable chemicals from wood by a combined heat and IL-treatment. Thermal treatments alone contribute to the degradation of polysaccharides (e.g. 150 °C alone is said to cause the degradation of polysaccharides), thus temperatures below that should be used, if the research interest lies on the IL effectiveness. On the other hand, the efficiency of the IL-treatment can also be enhanced to combine other treatment methods, (e.g. microwave heating). The samples of spruce, pine and birch sawdust were treated with either 1-Ethyl-3-methylimidazolium chloride, Emim Cl, or 1-Ethyl-3-methylimidazolium acetate, Emim Ac, (or with ionized water for comparison) at various temperatures (where focus was between 80 and 120 °C). The samples were withdrawn at fixed time intervals (the main interest treatment time area lied between 0 and 100 hours). Double experiments were executed. The selected mono- and disaccharides, as well as their known degradation products, 5-hydroxymethylfurfural, 5-HMF, and furfural were analyzed with capillary electrophoresis, CE, and high-performance liquid chromatography, HPLC. Initially, even GC and GC-MS were utilized. Galactose, glucose, mannose and xylose were the main monosaccharides that were present in the wood samples exposed to ILs at elevated temperatures; in addition, furfural and 5-HMF were detected; moreover, the quantitative amount of the two latter ones were naturally increasing in line with the heating time or the IL:wood ratio.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.