Aqueous-phase reforming of renewables for selective hydrogen production in the presence of supported platinum catalysts

The evolution of our society is impossible without a constant progress in life-important areas such as chemical engineering and technology. Innovation, creativity and technology are three main components driving the progress of chemistry further towards a sustainable society. Biomass, being an attractive renewable feedstock for production of fine chemicals, energy-rich materials and even transportation fuels, captures progressively new positions in the area of chemical technology. Knowledge of heterogeneous catalysis and chemical technology applied to transformation of biomass-derived substances will open doors for a sustainable economy and facilitates the discovery of novel environmentally-benign processes which probably will replace existing technologies in the era of biorefinary. Aqueous-phase reforming (APR) is regarded as a promising technology for production of hydrogen and liquids fuels from biomass-derived substances such as C3-C6 polyols. In the present work, aqueous-phase reforming of glycerol, xylitol and sorbitol was investigated in the presence of supported Pt catalysts. The catalysts were deposited on different support materials, including Al2O3, TiO2 and carbons. Catalytic measurements were performed in a laboratory-scale continuous fixedbed reactor. An advanced analytical approach was developed in order to identify reaction products and reaction intermediates in the APR of polyols. The influence of the substrate structure on the product formation and selectivity in the APR reaction was also investigated, showing that the yields of the desired products varied depending on the substrate chain length. Additionally, the influence of bioethanol additive in the APR of glycerol and sorbitol was studied. A reaction network was advanced explaining the formation of products and key intermediates. The structure sensitivity in the aqueous-phase reforming reaction was demonstrated using a series of platinum catalysts supported on carbon with different Pt cluster sizes in the continuous fixed-bed reactor. Furthermore, a correlation between texture physico-chemical properties of the catalysts and catalytic data was established. The effect of the second metal (Re, Cu) addition to Pt catalysts was investigated in the APR of xylitol showing a superior hydrocarbon formation on PtRe bimetallic catalysts compared to monometallic Pt. On the basis of the experimental data obtained, mathematical modeling of the reaction kinetics was performed. The developed model was proven to successfully describe experimental data on APR of sorbitol with good accuracy.

Mathematical modeling and optimal control of malaria

Malaria continues to infect millions and kill hundreds of thousands of people worldwide each year, despite over a century of research and attempts to control and eliminate this infectious disease. Challenges such as the development and spread of drug resistant malaria parasites, insecticide resistance to mosquitoes, climate change, the presence of individuals with subpatent malaria infections which normally are asymptomatic and behavioral plasticity in the mosquito hinder the prospects of malaria control and elimination. In this thesis, mathematical models of malaria transmission and control that address the role of drug resistance, immunity, iron supplementation and anemia, immigration and visitation, and the presence of asymptomatic carriers in malaria transmission are developed. A within-host mathematical model of severe Plasmodium falciparum malaria is also developed. First, a deterministic mathematical model for transmission of antimalarial drug resistance parasites with superinfection is developed and analyzed. The possibility of increase in the risk of superinfection due to iron supplementation and fortification in malaria endemic areas is discussed. The model results calls upon stakeholders to weigh the pros and cons of iron supplementation to individuals living in malaria endemic regions. Second, a deterministic model of transmission of drug resistant malaria parasites, including the inflow of infective immigrants, is presented and analyzed. The optimal control theory is applied to this model to study the impact of various malaria and vector control strategies, such as screening of immigrants, treatment of drug-sensitive infections, treatment of drug-resistant infections, and the use of insecticide-treated bed nets and indoor spraying of mosquitoes. The results of the model emphasize the importance of using a combination of all four controls tools for effective malaria intervention. Next, a two-age-class mathematical model for malaria transmission with asymptomatic carriers is developed and analyzed. In development of this model, four possible control measures are analyzed: the use of long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic, and screening and treatment of asymptomatic individuals. The numerical results show that a disease-free equilibrium can be attained if all four control measures are used. A common pitfall for most epidemiological models is the absence of real data; model-based conclusions have to be drawn based on uncertain parameter values. In this thesis, an approach to study the robustness of optimal control solutions under such parameter uncertainty is presented. Numerical analysis of the optimal control problem in the presence of parameter uncertainty demonstrate the robustness of the optimal control approach that: when a comprehensive control strategy is used the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the design of cost-effective strategies for disease control with multiple interventions, even under considerable uncertainty of model parameters. Finally, a separate work modeling the within-host Plasmodium falciparum infection in humans is presented. The developed model allows re-infection of already-infected red blood cells. The model hypothesizes that in severe malaria due to parasite quest for survival and rapid multiplication, the Plasmodium falciparum can be absorbed in the already-infected red blood cells which accelerates the rupture rate and consequently cause anemia. Analysis of the model and parameter identifiability using Markov chain Monte Carlo methods is presented.

Green supplier selection via Multiple Criteria Data Envelopment Analysis

An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a “virtual” best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.

Geochemistry and water quality of Lake Qarun, Egypt

Water geochemistry is a very important tool for studying the water quality in a given area. Geology and climate are the major natural factors controlling the chemistry of most natural waters. Anthropogenic impacts are the secondary sources of contamination in natural waters. This study presents the first integrative approach to the geochemistry and water quality of surface waters and Lake Qarun in the Fayoum catchment, Egypt. Moreover, geochemical modeling of Lake Qarun was firstly presented. The Nile River is the main source of water to the Fayoum watershed. To investigate the quality and geochemistry of this water, water samples from irrigation canals, drains and Lake Qarun were collected during the period 2010‒2013 from the whole Fayoum drainage basin to address the major processes and factors governing the evolution of water chemistry in the investigation area. About 34 physicochemical quality parameters, including major ions, oxygen isotopes, trace elements, nutrients and microbiological parameters were investigated in the water samples. Multivariable statistical analysis was used to interpret the interrelationship between the different studied parameters. Geochemical modeling of Lake Qarun was carried out using Hardie and Eugster’s evolutionary model and a model simulated by PHREEQC software. The crystallization sequence during evaporation of Lake Qarun brine was also studied using a Jänecke phase diagram involving the system Na‒K‒Mg‒ Cl‒SO4‒H2O. The results show that the chemistry of surface water in the Fayoum catchment evolves from Ca- Mg-HCO3 at the head waters to Ca‒Mg‒Cl‒SO4 and eventually to Na‒Cl downstream and at Lake Qarun. The main processes behind the high levels of Na, SO4 and Cl in downstream waters and in Lake Qarun are dissolution of evaporites from Fayoum soils followed by evapoconcentration. This was confirmed by binary plots between the different ions, Piper plot, Gibb’s plot and δ18O results. The modeled data proved that Lake Qarun brine evolves from drainage waters via an evaporation‒crystallization process. Through the precipitation of calcite and gypsum, the solution should reach the final composition "Na–Mg–SO4–Cl". As simulated by PHREEQC, further evaporation of lake brine can drive halite to precipitate in the final stages of evaporation. Significantly, the crystallization sequence during evaporation of the lake brine at the concentration ponds of the Egyptian Salts and Minerals Company (EMISAL) reflected the findings from both Hardie and Eugster’s evolutionary model and the PHREEQC simulated model. After crystallization of halite at the EMISAL ponds, the crystallization sequence during evaporation of the residual brine (bittern) was investigated using a Jänecke phase diagram at 35 °C. This diagram was more useful than PHREEQC for predicting the evaporation path especially in the case of this highly concentrated brine (bittern). The predicted crystallization path using a Jänecke phase diagram at 35 °C showed that halite, hexahydrite, kainite and kieserite should appear during bittern evaporation. Yet the actual crystallized mineral salts were only halite and hexahydrite. The absence of kainite was due to its metastability while the absence of kieserite was due to opposed relative humidity. The presence of a specific MgSO4.nH2O phase in ancient evaporite deposits can be used as a paleoclimatic indicator. Evaluation of surface water quality for agricultural purposes shows that some irrigation waters and all drainage waters have high salinities and therefore cannot be used for irrigation. Waters from irrigation canals used as a drinking water supply show higher concentrations of Al and suffer from high levels of total coliform (TC), fecal coliform (FC) and fecal streptococcus (FS). These waters cannot be used for drinking or agricultural purposes without treatment, because of their high health risk. Therefore it is crucial that environmental protection agencies and the media increase public awareness of this issue, especially in rural areas.