Abstract: When Fe(II) bearing groundwaters surface in streams, particulate authigenic Fe-rich material is produced by oxidation. Such freshly precipitated Fe minerals may be transported as suspended sediment and have a profound impact on the fate of trace metals and nutrients in rivers. The objective of this study was to monitor changes in mineralogy and composition of authigenic material from its source to streams of increasing order. Groundwaters, surface waters, and suspended sediment in streams of different order were sampled in the Kleine Nete catchment (Belgium), a lowland with Fe-rich groundwaters (3.5-53.8 mg Fe/L; pH 6.3-6.9). Fresh authigenic material (>0.45 mu m) was produced by oxidising filtered (<0.45 mu m) groundwater and surface water. This material contained, on average, 44% Fe, and smaller concentrations of C, P, and Ca. Iron EXAFS (Extended X-ray Absorption Fine Structure) spectroscopy showed that the Fe was present as poorly crystalline hydrous ferric oxides with a structure similar to that of ferrihydrite. The Fe concentration in the suspended sediment samples decreased to 36-40% (stream order 2), and further to 18-26% (stream order 4 and 5). Conversely, the concentrations of organic C, Ca, Si, and trace metals increased with increasing stream order, suggesting mixing of authigenic material with suspended sediment from a different source. The Fe speciation in the suspended sediment was similar to that in fresh authigenic material, but more Fe-Fe interactions were observed, i.e. it was increasingly hydrolysed, suggesting ageing reactions. The suspended sediment in the streams of order 4 and 5 is estimated to contain between 31% and 59% of authigenic material, but more data are needed to refine this estimate. The authigenic material is an important sink for P in these streams which may alleviate the eutrophication risk in this catchment. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract: The latest life-cycle assessment methods account for land use, due to the production, use and disposal of products and services, in terms of ecosystem damage. The process of brownfield remediation converts otherwise idle urban space into productive space. The value to ecosystems in this context is of course limited since the brownfield site remains urban. When evaluating brownfield remediation technologies, the availability of space on-site is dependent on the duration of time required by the remediation technology to reach the remediation target. Remediation technology alternatives tend to vary largely in terms of duration. Comparative life-cycle assessments of remediation technologies, to date, present the large variations between alternatives in terms of remediation duration but do not translate this into an impact or parameter. The restored subsurface zone is often defined as a functional unit, when in fact the surface area is the resource restored by the remediation service. The economic benefits of making land resources available are particularly important considerations in the context of brownfield remediation. The research proposes an innovative impact assessment approach that allows land to be considered as a finite resource. The method is applied in a comparative life-cycle assessment of two potential remediation scenarios for an idle brownfield in the Brussels region of Belgium. The results show that there is a trade-off between greenhouse gas emissions and land availability and that both are largely dependent on the efficiency of the contaminant extraction mechanism. The results also raise the question as to whether the economic valuation of land, like precious metals and fossil fuels, provides an accurate reflection of the true value of the resource. Considering land as a resource at the midpoint level is also relevant in other urban contexts where competition exists between different land-uses, where urban sprawl is detrimental to undeveloped areas and where urban intensification is a policy objective. (C) 2015 Elsevier Ltd. All rights reserved.

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: 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.