Wet Oxidation of Concentrated Wastewaters: Process Combination and Reaction Kinetic Modeling

The accumulation of aqueous pollutants is becoming a global problem. The search for suitable methods and/or combinations of water treatment processes is a task that can slow down and stop the process of water pollution. In this work, the method of wet oxidation was considered as an appropriate technique for the elimination of the impurities present in paper mill process waters. It has been shown that, when combined with traditional wastewater treatment processes, wet oxidation offers many advantages. The combination of coagulation and wet oxidation offers a new opportunity for the improvement of the quality of wastewater designated for discharge or recycling. First of all, the utilization of coagulated sludge via wet oxidation provides a conditioning process for the sludge, i.e. dewatering, which is rather difficult to carry out with untreated waste. Secondly, Fe2(SO4)3, which is employed earlier as a coagulant, transforms the conventional wet oxidation process into a catalytic one. The use of coagulation as the post-treatment for wet oxidation can offer the possibility of the brown hue that usually accompanies the partial oxidation to be reduced. As a result, the supernatant is less colored and also contains a rather low amount of Fe ions to beconsidered for recycling inside mills. The thickened part that consists of metal ions is then recycled back to the wet oxidation system. It was also observed that wet oxidation is favorable for the degradation of pitch substances (LWEs) and lignin that are present in the process waters of paper mills. Rather low operating temperatures are needed for wet oxidation in order to destruct LWEs. The oxidation in the alkaline media provides not only the faster elimination of pitch and lignin but also significantly improves the biodegradable characteristics of wastewater that contains lignin and pitch substances. During the course of the kinetic studies, a model, which can predict the enhancements of the biodegradability of wastewater, was elaborated. The model includes lumped concentrations suchas the chemical oxygen demand and biochemical oxygen demand and reflects a generalized reaction network of oxidative transformations. Later developments incorporated a new lump, the immediately available biochemical oxygen demand, which increased the fidelity of the predictions made by the model. Since changes in biodegradability occur simultaneously with the destruction of LWEs, an attempt was made to combine these two facts for modeling purposes.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.

Market anomalies and tactical asset allocation: Utilising market anomalies in multiple asset class portfolios with the Black−Litterman model

This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.