Abstract: The feasibility of algae harvesting with submerged flat panel membranes was investigated as pre-concentration step prior to centrifugation. Polishing of the supernatant coming from the centrifuge was evaluated as well. The effect of membrane polymer (polyvinyl chloride [PVC], polyethersulfone polyvinyl-pyrollidone [PES-PVP], poly vinylidene fluoride [PVDF]), pore size (microfiltration [MF], ultrafiltration [UF]), algae cell concentrations and species were investigated at lab-scale. In addition, backwashing as fouling control was compared to standard relaxation. PVDF was the superior polymer, and UF showed better fouling resistance. Backwashing outperformed relaxation in fouling control. The backwashable membranes allowed up to 300% higher fluxes compared to commercial flat panel benchmark (PVC) membranes. Estimations on energy consumption for membrane filtration followed by centrifugation revealed relatively low values of 0.169 kW h/kg of dry weight of algae compared to 0.5 kW h/kg for algae harvesting via classical centrifuge alone. (C) 2012 Elsevier Ltd. All rights reserved.

Abstract: The Robin problem for the Helmholtz equation in normal-polar annuli is addressed by using a suitable Fourier-Hankel series technique. Attention is in particular focused on the wide class of domains whose boundaries are defined by the so-called superformula introduced by Gielis. A dedicated numerical procedure based on the computer algebra system Mathematica© is developed in order to validate the proposed methodology. In this way, highly accurate approximations of the solution, featuring properties similar to the classical ones, are obtained.

Abstract: The effective air-filled porosity and the gas diffusion coefficient are important soil parameters determining the success of soil bioremediation projects such as (bio)venting and (bio)sparging methods in combination with soil vapor extraction. We have developed a new method to sequentially measure the effective air-filled porosity and the soil gas diffusion coefficient of a soil sample. During the purging of the sample, a fast and accurate measurement of the effective air-filled porosity can be obtained. The subsequent diffusion measurement does not require a zero-O(2) concentration in the soil sample. The procedure further allows the calculation of the soil gas diffusion coefficient before an equilibrium O(2) concentration has been reached. The results are obtained by combining the data of the inlet and outlet compartment in a single equation. A stable reading is reached when the results for the inlet and outlet compartment coincide with the results from the combined equation. The analysis time is reduced by 89 to 96% compared with methods that run until an equilibrium concentration has been reached. Moreover, combining data from inlet and outlet compartments increases the accuracy of the diffusivity measurement by a factor of two compared with previous methods.

Abstract: A shift from batch processing towards continuous processing is of interest in the pharmaceutical industry. However, this transition requires detailed knowledge and process understanding of all consecutive unit operations in a continuous manufacturing line to design adequate control strategies. This can be facilitated by developing mechanistic models of the multi-phase systems in the process. Since modelling efforts only started recently in this field, uncertainties about the model predictions are generally neglected. However, model predictions have an inherent uncertainty (i.e. prediction uncertainty) originating from uncertainty in input data, model parameters, model structure, boundary conditions and software. In this paper, the model prediction uncertainty is evaluated for a model describing the continuous drying of single pharmaceutical wet granules in a six-segmented fluidized bed drying unit, which is part of the full continuous from-powder-to-tablet manufacturing line (Consigma (TM), GEA Pharma Systems). A validated model describing the drying behaviour of a single pharmaceutical granule in two consecutive phases is used. First of all, the effect of the assumptions at the particle level on the prediction uncertainty is assessed. Secondly, the paper focuses on the influence of the most sensitive parameters in the model. Finally, a combined analysis (particle level plus most sensitive parameters) is performed and discussed. To propagate the uncertainty originating from the parameter uncertainty to the model output, the Generalized Likelihood Uncertainty Estimation (GLUE) method is used. This method enables a modeller to incorporate the information obtained from the experimental data in the assessment of the uncertain model predictions and to find a balance between model performance and data precision. A detailed evaluation of the obtained uncertainty analysis results is made with respect to the model structure, interactions between parameters and uncertainty boundaries. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The state-of-the-science in sustainability assessment of soil and groundwater remediation is evaluated with the application of four decision support systems (DSSs) to a large-scale brownfield revitalization case study. The DSSs were used to perform sustainability appraisals of four technically feasible remediation alternatives proposed for the site. The first stage of the review compares the scope of each tool's sustainability indicators, how these indicators are measured and how the tools differ in terms of standardization and weighting procedures. The second stage of the review compares the outputs from the tools and determines the key factors that result in differing results between tools. The evaluation of indicator sets and tool structures explains why the tools generate differing results. Not all crucial impact areas, as identified by sustainable remediation forums, are thoroughly considered by the tools, particularly with regard to the social and economic aspects of sustainability. Variations in boundary conditions defined between technologies, produce distorted environmental impact results, especially when in-situ and ex-situ technologies are compared. The review draws attention to the need for end users to be aware of which aspects of sustainability are considered, how the aspects are measured and how all aspects are ultimately balanced in the evaluation of potential remediation strategies. Existing tools can be improved by considering different technologies within the same boundary conditions and by expanding indicator sets to include indicators deemed to be relevant by remediation forums. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Soot deposition has the negative ability to devalue the aesthetic appearance of buildings. Titanium dioxide applied on the building material is one way to counteract this problem as it provides air-purifying and self-cleaning properties due to its photocatalytic activity. In literature, photocatalytic soot oxidation was described, but until now, little information was available about the influence of process parameters on the photocatalytic degradation efficiency. The influence of three process parameters was tested in this study, namely TiO2 concentration, soot concentration and water-to-cement ratio (WIC-ratio) of the mortar substrates. The results revealed 50 mu gTiO(2) cm(-2) is better to use on the cementitious materials than 250 mu gTiO(2) cm(-2). The soot concentrations occurring in real-world situations will not inhibit the photocatalyst to be activated by light. Furthermore, the photonic efficiency increases slightly for lower WIC-ratios. This can be of interest for structural building applications, since a lower WIC-ratio results in a lower porosity of the samples and consequently in an increase in mortar strength. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Immobilization of photocatalytic powder is crucial to obtain industrially relevant purification processes. To achieve this goal, self-supporting TiO2 foams were manufactured by a polyacrylamide gel process. These gels were calcined at different temperatures to study the effect of the calcination temperature on foam characteristics (rigidity, crystallinity, and porosity) and its influence on photocatalytic activity. The results show that an optimal degradation is achieved for those foams calcined between 700 and 800°C. Calcination at higher temperatures results in a steep decrease in activity, explained by stability issues of the material due to formation of Na2SO4 phases and a larger rutile fraction.

Abstract: In the commercialisation of photocatalytic air purifiers, the performance as well as the cost of the catalytic material plays an important role. Where most comparative studies only regard the photocatalytic activity as a decisive parameter, in this study both activity and cost are taken into account. Using a cost-effectiveness analysis, six different commercially available TiO2-based catalysts are evaluated in terms of their activities in photocatalytic degradation of acetaldehyde as a model reaction for indoor air purification.

Abstract: The effects on river water quality of sewer overflows are not well known. Since the duration of the overflow is in the order of magnitude of minutes to hours, continuous measurements of water quality are needed and traditional grab sampling is unable to quantify the pollution loads. The objective of this paper was to demonstrate the applicability of high frequency measurements for assessing the impacts of waste water treatment plants on the water quality of the receiving surface water. In our in situ water quality monitoring setup, two types of multiparameter sensors mounted on a floating fixed platform were used to determine the dynamics of dissolved oxygen, specific conductivity, ammonium-N, nitrate-N and dissolved organic carbon downstream of a waste water treatment plant (WWTP), in combination with data on rainfall, river discharge and WWTP overflow discharge. The monitoring data for water quantity and water quality were used to estimate the pollution load from waste water overflow events and to assess the impact of waste water overflows on the river water quality. The effect of sewer overflow on a small river in terms of N load was shown to be significant. The WWTP overflow events accounted for about 1/3 of the river discharge. The NH4-N loads during overflow events contributed 29% and 21% to the August 2010 and June 2011 load, respectively, in only 8% and 3% of the monthly time span. The results indicate that continuous monitoring is needed to accurately represent the effects of sewer overflows in river systems.

Abstract: EU strategies for waste management have long recognized the key role of recycling to move towards sustainable consumption and production. This resulted in a range of regulatory measures, among which the Waste Electrical and Electronic Equipment (WEEE) directive, which sets weight-based targets for recovery, preparation for re-use and recycling. The increasing strategic relevance of the supply of raw materials has, however, spurred a more integrated approach towards resource efficiency. In addition to the prevention of disposal, recycling practices are now also meant to contribute to sustainable materials management by pursuing (i) a higher degree of material cycle closure, (ii) an improved recovery of strategically relevant materials, and (iii) the avoidance of environmental burdens associated with the extraction and refining of primary raw materials. In response to this evolution, this paper reports about the development of an indicator set that allows to quantitatively demonstrate these recycling benefits, hence going further than the weight-based objectives employed in the WEEE directive. The indicators can be calculated for WEEE recycling processes for which information is available on both input and output fractions. It offers a comprehensive framework that aims to support decision making processes on product design, to identify opportunities for the optimization of WEEE End-of-Life scenarios, and to assess the achieved (or expected) results of implemented (or planned) recycling optimization strategies. The paper is illustrated by a case study on the recycling of LCD televisions. (C) 2014 Elsevier Ltd. All rights reserved.

Abstract: The growing concern for the increase of the global warming effects due to anthropogenic activities raises the challenge of finding novel technological approaches to stabilize CO2 emissions in the atmosphere and counteract impinging interconnected issues such as desertification and loss of biodiversity. Biological-CO2 mitigation, triggered through biological fixation, is considered a promising and eco-sustainable method, mostly owing to its downstream benefits that can be exploited. Microorganisms such as cyanobacteria, green algae and some autotrophic bacteria could potentially fix CO2 more efficiently than higher plants, due to their faster growth. Some examples of the potential of biological-CO2 mitigation are reported and discussed in this paper. In arid and semiarid environments, soil carbon sequestration (CO2 fixation) by cyanobacteria and biological soil crusts is considered an eco-friendly and natural process to increase soil C content and a viable pathway to soil restoration after one disturbance event. Another way for biological-CO2 mitigation intensively studied in the last few years is related to the possibility to perform carbon dioxide sequestration using microalgae, obtaining at the same time bioproducts of industrial interest. Another possibility under study is the exploitation of specific chemotrophic bacteria, such as Ralstonia eutropha (or picketii) and related organisms, for CO2 fixation coupled with the production chemicals such as polyhydroxyalkanoates (PHAs). In spite of the potential of these processes, multiple factors still have to be optimized for maximum rate of CO2 fixation by these microorganisms. The optimization of culture conditions, including the optimal concentration of CO2 in the provided gas, the use of metabolic engineering and of dual purpose systems for the treatment of wastewater and production of biofuels and high value products within a biorefinery concept, the design of photobioreactors in the case of phototrophs are some of the issues that, among others, have to be addressed and tested for cost-effective CO2 sequestration.

Abstract: The selection and identification of a suitable hydrological model structure is a more challenging task than fitting parameters of a fixed model structure to reproduce a measured hydrograph. The suitable model structure is highly dependent on various criteria, i.e. the modeling objective, the characteristics and the scale of the system under investigation and the available data. Flexible environments for model building are available, but need to be assisted by proper diagnostic tools for model structure selection. This paper introduces a qualitative method for model component sensitivity analysis. Traditionally, model sensitivity is evaluated for model parameters. In this paper, the concept is translated into an evaluation of model structure sensitivity. Similarly to the one-factor-at-a-time (OAT) methods for parameter sensitivity, this method varies the model structure components one at a time and evaluates the change in sensitivity towards the output variables. As such, the effect of model component variations can be evaluated towards different objective functions or output variables. The methodology is presented for a simple lumped hydrological model environment, introducing different possible model building variations. By comparing the effect of changes in model structure for different model objectives, model selection can be better evaluated. Based on the presented component sensitivity analysis of a case study, some suggestions with regard to model selection are formulated for the system under study: (1) a non-linear storage component is recommended, since it ensures more sensitive (identifiable) parameters for this component and less parameter interaction; (2) interflow is mainly important for the low flow criteria; (3) excess infiltration process is most influencing when focussing on the lower flows; (4) a more simple routing component is advisable; and (5) baseflow parameters have in general low sensitivity values, except for the low flow criteria. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: In this study a numerical groundwater reactive transport model of a shallow groundwater aquifer contaminated with volatile organic compounds is developed. In addition to advective-dispersive transport, the model includes contaminant release from source areas, natural attenuation, abiotic degradation by a permeable reactive barrier at the site, and dilution by infiltrating rain. Aquifer heterogeneity is parameterized using pilot points for hydraulic conductivity, specific yield and groundwater recharge. A methodology is developed and applied to estimate the large number of parameters from the limited data at the field site (groundwater levels, groundwater concentrations of multiple chemical species, point-scale measurements of soil hydraulic conductivity, and lab-scale derived information on chemical and biochemical reactions). The proposed methodology relies on pilot point parameterization of hydraulic parameters and groundwater recharge, a regularization procedure to reconcile the large number of spatially distributed model parameters with the limited field data, a step-wise approach for integrating the different data sets into the model, and high performance computing. The methodology was proven to be effective in reproducing multiple contaminant plumes and in reducing the prior parameter uncertainty of hydraulic conductivity and groundwater recharge. Our results further indicate that contaminant transport predictions are strongly affected by the choice of the groundwater recharge model and flow parameters should be identified using both head and concentration measurements. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The use of temperature-time series measured in streambed sediments as input to coupled water flow and heat transport models has become standard when quantifying vertical groundwater-surface water exchange fluxes. We develop a novel methodology, called LPML, to estimate the parameters for 1-D water flow and heat transport by combining a local polynomial (LP) signal processing technique with a maximum likelihood (ML) estimator. The LP method is used to estimate the frequency response functions (FRFs) and their uncertainties between the streambed top and several locations within the streambed from measured temperature-time series data. Additionally, we obtain the analytical expression of the FRFs assuming a pure sinusoidal input. The estimated and analytical FRFs are used in an ML estimator to deduce vertical groundwater-surface water exchange flux and its uncertainty as well as information regarding model quality. The LPML method is tested and verified with the heat transport models STRIVE and VFLUX. We demonstrate that the LPML method can correctly reproduce a priori known fluxes and thermal conductivities and also show that the LPML method can estimate averaged and time-variable fluxes from periodic and nonperiodic temperature records. The LPML method allows for a fast computation of exchange fluxes as well as model and parameter uncertainties from many temperature sensors. Moreover, it can utilize a broad frequency spectrum beyond the diel signal commonly used for flux calculations.