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: Air pollution caused by particulate matter (PM) is a well-known health issue in urban environments. Urban green infrastructure offers opportunities as a nature-based solution to urban PM pollution. Green walls have advantages over other types of urban green infrastructure, since they can be applied to the enormous available wall area in cities and since they do not interfere with the prevailing ventilation resulting in elevated PM levels. However, this has raised questions about the effectiveness of GW in removing PM and this could explain the limited applicability of green walls to tackle PM pollution. Nevertheless, it is suggested that green walls have a significant unexploited potential and this review article aims to address current knowledge gaps and to propose future research requirements for the implementation of green walls to mitigate urban PM pollution. An in-depth analysis is given of the mechanisms behind PM deposition and the influence of vegetation properties on this process, as well as the practices followed to model PM dispersion and deposition. It was suggested that particle deposition on green walls depends on the green wall species, pollution level, and the residence time of PM in a street (canyon). Rainfall plays an important role in the PM pathway, although it is not a necessary requirement to sustain PM deposition on plant leaves. There are still some discrepancies in the literature about the ideal plant characteristics for PM deposition in terms of the macro- and microstructures that require further investigation, especially in comparison with tree and shrub species. In addition, extensively validated models are required to accurately calculate the impact of green walls on air flow and the PM concentration on site.

Abstract: Vegetables and fruits are an important part of a healthy food diet, however, the eco-sustainability of the production of these can still be significantly improved. European farmers and consumers spend an estimated Euro15.5 billion per year on inorganic fertilizers and the production of N-fertilizers results in a high carbon footprint. We investigated if fertilizer type and medium constituents determine microbial nitrogen conversions in organic growing media and can be used as a next step towards a more sustainable horticulture. We demonstrated that growing media constituents showed differences in urea hydrolysis, ammonia and nitrite oxidation and in carbon dioxide respiration rate. Interestingly, mixing of the growing media constituents resulted in a stimulation of the function of the microorganisms. The use of organic fertilizer resulted in an increase in amoA gene copy number by factor 100 compared to inorganic fertilizers. Our results support our hypothesis that the activity of the functional microbial community with respect to nitrogen turnover in an organic growing medium can be improved by selecting and mixing the appropriate growing media components with each other. These findings contribute to the understanding of the functional microbial community in growing media and its potential role towards a more responsible horticulture.

Abstract: Ca-containing particles, especially CaSO4 particles, have been encountered in several atmospheric aerosol studies. An overview is given of the different sources of airborne Ca-containing particles, The North Sea atmosphere is studied to identify the different Ca-containing particle types and to find the correlation between their occurrence and the source regions of the corresponding air masses. About 50000 individual aerosol samples were collected above the Southern Eight of the North Sea for several wind directions and analyzed for their composition using electron probe X-ray microanalysis. Nonhierarchical cluster analysis is performed on the data to reveal the different particle types, their relative abundances and their sources. CaSO4 in most cases constitutes the largest fraction of the Ca-containing particles. Extremely high numbers of CaSO4 particles are found for northeastern winds, coming from the central part of Germany, suggesting that a great fraction is derived from anthropogenic sources located in this region. Among the other Ca-containing particle types are the aluminosilicates, CaCO3, Fe-Ca-rich particles, and CaSO4 or CaCO3 in combination with NaCl.

Abstract: Sixty-two samples of total sediments and the separated clay/silt size fractions were analysed by energy-dispersive X-ray fluorescence spectrometry to evaluate the pollution level and the trends in samples collected along the Belgian coast over a period of 6 yr and at four stations located in the Scheldt estuary where two of these were sampled periodically for 4 yr. Three correction methods for grain size effects were applied, either to the bulk sediment samples or to the clay/silt size fractions, and the results were compared. Local variations on the concentrations in some of the elements determined were used to establish whether they result from an anthropogenic or natural origin. The level of pollution was assessed as a function of the location, sampling date, and depth.

Abstract: The methodology of direct hair analysis by energy-dispersive x-ray fluorescence was studied. The effect on the XRF result of having a non-homogeneous radial distribution of the analyte in a single hair strand and the macroscopic effects in a bundle of hairs were calculated to evaluate possible systematic errors. The detection limits were mapped as a function of the target thickness and surface fraction. It appeared that a 10 mg cm−2 sample thickness, i. e. a target with about four layers of hair strands, is recommended. The standard deviation of this simple direct analytical method is 619% for some important elements. Discrepancies with neutron activation analysis had a mean value of around 15%. About twelve elements can be determined simultaneously on a routine basis.

Abstract: We present a computational model for simulating the dispersion of traffic emitted particulate matter inside a road tunnel, with an emphasis on the number concentration of ultrafine particles (UFP). The model primarily calculates the size distribution of the particle number concentration at each location inside the tunnel. The proposed model differs from existing models in the sense that it uses a continuous representation of the size distribution based upon the high-order finite element method and that it solves the governing equations using the state-of-the-art discontinuous Galerkin method. Next to the traditional transport processes, the model also implements the most important aerosol transformation processes such as coagulation, condensation and dry deposition. It is shown that based upon parametrisations found in literature, the process of condensation in a traffic tunnel cannot properly be modelled. Therefore, we present a correction factor that allows for a better parametrisation. The adequate performance of the model is demonstrated by both a verification study and a validation study. For the verification we show that the discretisation error converges consistently while for the validation we compare the modelled results with a suitable set of data from a UFP measurement campaign in a Taiwanese traffic tunnel. The model is shown to correctly simulate the observed behaviour and by applying a statistical model evaluation we demonstrate that the proposed model meets widely accepted air quality model acceptance criteria. (C) 2012 Elsevier Ltd. All rights reserved.