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 goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.

Abstract: Finding a correspondence between soil hydraulic properties, such as saturated hydraulic conductivity (Ks) and apparent electrical conductivity (ECa) as an easily measurable parameter, may be a way forward to estimate the spatial distribution of hydraulic properties at the field scale. In this study, the spatial distributions of Ks, of soil ECa measured by a DUALEM-21S sensor and of soil physical properties were investigated in a sandy grassland. To predict field scale Ks, the statistical relationship between co-located soil Ks, and EMI-ECa was evaluated. Results demonstrated the large spatial variability of all studied properties with Ks being the most variable one (CV = 86.21%) followed by ECa (CV >= 53.77%). A significant negative correlation was found between In-transformed Ks and ECa (r = 0.83; P <= 0.01) at two depths of exploration (0-50 and 0-100 cm). This site specific relation between In Ks and ECa was used to predict saturated hydraulic conductivity over 0-50 cm depth for the whole field. The empirical relation was validated using an independent dataset of measured Ks. The statistical results demonstrate the robustness of this empirical relation with mean estimation error MEE = 0.46 (cm h(-1)), root-mean-square estimation errors RMSEE = 0.74 (cm h(-1)), coefficient of determination r(2) = 0.67 and coefficient of model efficiency Ce = 0.64. The relationship was then used to produce a detailed map of Ks for the whole field. The result will allow model predictions of spatially distributed water content in view of irrigation management. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Supported carbon nanosheets and carbon nanotubes served as sacrificial templates for preparing spacious TiO2 photocatalytic thin films. Amorphous TiO2 was deposited conformally on the carbonaceous template material by atomic layer deposition (ALD). Upon calcination at 550 °C, the carbon template was oxidatively removed and the as-deposited continuous amorphous TiO2 layers transformed into interlinked anatase nanoparticles with an overall morphology commensurate to the original template structure. The effect of type of template, number of ALD cycles and gas residence time of pollutant on the photocatalytic activity, as well as the stability of the photocatalytic performance of these thin films was investigated. The TiO2 films exhibited excellent photocatalytic activity toward photocatalytic degradation of acetaldehyde in air as a model reaction for photocatalytic indoor air pollution abatement. Optimized films outperformed a reference film of commercial PC500.

Abstract: We propose the concept of a ‘rainbow’ photocatalyst that consists of TiO2 modified with gold-silver alloy nanoparticles of various sizes and compositions, resulting in a broad plasmon absorption band that covers the entire UV–vis range of the solar spectrum. It is demonstrated that this plasmonic ‘rainbow’ photocatalyst is 16% more effective than TiO2 P25 under both simulated and real solar light for pollutant degradation at the solid-gas interface. With this we provide a promising strategy to maximize the spectral response for solar to chemical energy conversion.

Abstract: Transparent photocatalytic TiO2 thin films hold great potential in the development of self-cleaning glass sur-
faces, but suffer from a poor visible light response that hinders the application under actual sunlight. To alleviate this problem, the photocatalytic film can be modified with plasmonic nanoparticles that interact very effectively with visible light. Since the plasmonic effect is strongly concentrated in the near surroundings of the nano- particle surface, an approach is presented to embed the plasmonic nanostructures in the TiO2 matrix itself, rather than deposit them loosely on the surface. This way the interaction interface is maximised and the plasmonic effect can be fully exploited. In this study, pre-fabricated gold nanoparticles are made compatible with the organic medium of a TiO2 sol-gel coating suspension, resulting in a one-pot coating suspension. After spin coating, homogeneous, smooth, highly transparent and photoactive gold-embedded anatase thin films are ob- tained.

Abstract: Photocatalysis assisted oxidation of carbon black was performed using TiO2 photocatalyst under UV illumination in an atmosphere with NO, O-2 and water vapor at 150 degrees C. Carbon is oxidized mainly to CO2 while NO is selectively converted to N-2. Enhanced O-2 and NO concentrations have a positive effect on the carbon oxidation rate. At a concentration of 3000 ppm NO and 13.3% O-2 in the gas phase the carbon oxidation rate reaches 2.3 mu g(carbon)/mg(TiO2) h, at a formal electron/photon quantum efficiency of 0.019. HR SEM images reveal uniform gradual reduction of the carbon particle size irrespective of the distance to TiO2 photocatalyst particles in the presence of NO, O-2 and H2O. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: In this paper, the reaction mechanism of the photocatalytic oxidation of ethylene is elucidated by means of an in-house developed FTIR in situ reactor. This reactor allowed us to look at the catalytic surface at the moment the reactions actually occur. This new approach gave some exciting new insights in how ethylene is photocatalytically oxidised. It was found that there is a change in dipole moment of the ethylene molecule when it is brought in the neighbourhood of the catalyst. From this finding, a hypothesis was formulated on how the CC-bond from ethylene will break. It was found that the aforementioned interaction between the catalyst and the molecule, allows the excited electrons from the UV irradiated catalyst to occupy the lowest unoccupied molecular orbital (LUMO) of the ethylene molecule through a process known as backdonation. Following this hypothesis, it was found that the degradation occurs through the formation of two intermediates: formaldehyde and formic acid, for which formaldehyde is bound in two different ways (coordinatively and as bidentate). Finally CO2 and H2O are found as end products, resulting in the complete mineralisation of the pollutant.

Abstract: Research has shown the potential of photofuel cells (PFCs) for waste water treatment, enabling the (partial) recovery of the energy released from the degraded compounds as electricity. Literature on PFCs targeting air pollution on the other hand is extremely scarce. In this work an autonomously operating air purification device targeting sustainable electricity generation is presented. Knowledge on gas phase operation of PFCs was gathered by combining photocatalytic and photoelectrochemical measurements, both for TiO2 and WO3-based photocatalysts. While TiO2-based photocatalysts performed better in direct photocatalytic experiments, they were outperformed by WO3-based photoanodes in all-gas-phase PFC operation. Not only do WO3-based photocatalysts generate the highest steady state photocurrent, they also achieved the highest fuel-to-electricity conversion (>65 %). The discrepancies between gas phase photocatalytic and photoelectrochemical processes highlight the difference in driving material properties. This study serves as a proof-of-concept towards development of an autonomous, low-cost and widely applicable waste gas-to-electricity PFC device.

Abstract: The increasing focus on circular economy at the level of governments and policy requires the development of appropriate indicators to effectively monitor the progress towards the circular economy. Currently two very different types of indicator areas are under development: (i) monitoring frameworks based on macro indicators that summarize the progress at (supra)national level, and (ii) micro indicators tailored towards assessing circularity at the level of products. It is not possible to obtain sufficiently direct feedback about the impact of policy interventions by either macro or micro indicators alone. In this paper, a conceptual approach is developed that aims to bridge the gap between the micro and macro level with meso level indicators, and thus ultimately deliver more direct feedback for policymakers, via the insertion of an extra level of meso indicators in between the macro and the micro level. These indicators have been extracted from a dedicated workshop that involved policy, sector and societal stakeholders. The aim of these indicators is to report on progress towards circular economy objectives based on the fulfillment of societal needs. In this way the consumption perspective is given a central position, and the role of circular business models is acknowledged. Following the development of the concept, the next steps towards tailored, flexible and agile monitoring frameworks for circular economy at (supra)national and regional level are outlined. The paper concludes with an illustrative example of the framework applied to the mobility system.

Abstract: In a circular economy (CE), materials, components and products should be kept at the highest level of functionality, while phenomena like dilution, mixing and contamination, often referred to as the loss of resources, should be avoided. One method that can assess the performance of systems to concentrate or avoid dilution of resources is Statistical Entropy Analysis (SEA). Up till now, the method has been applied on the substance level (elements and compounds) only, but showed its applicability to various scales and a variety of systems. Further development of the method allowed to consider information on the product, component and material levels, which makes the method applicable to different combinations of CE strategies, both destructive (e.g. recycling) and non-destructive (e.g. reuse). The method is demonstrated on a simplified vehicle life-cycle, which is modeled through four component groups and six materials. It shows that the method allows to evaluate different CE strategies and identify critical stages which lead to the most severe resource and functionality losses. Based on the methods results, it is possible to determine a perfect circularity reference level, representing a system state that preserves functionality and avoids resource losses. The introduction of a circularity reference level enables the establishment of a framework for resource effectiveness in which diluting and concentrating effects of activities (e.g. sorting) are quantified. The distance of a system to an ideal circular state determines the deviation from a resource-effective system that maintains the original product functionality over a maximum period of time, with minimal efforts.

Abstract: The COVID-19 pandemic had large repercussions for our economy and organizations. Improved resilience can give organizations the ability to withstand crises and build back better and faster. This article assesses resilience of organizations and sole proprietorships in the context of the COVID-19 pandemic with eight circular strategies as explanatory variables. Furthermore, these eight circular strategies are also used to assess the organizations' and sole proprietorships' resilience outside of the COVID-19 pandemic. This analysis is conducted to explain how circular strategies can help companies and sole proprietorships maintain stability. The analysis was performed by means of a survey conducted between May and June 2020 in Flanders (Belgium), using a sample of 542 respondents. After performing a regression analysis combined with expert opinions collected through interviews, we find that companies and sole proprietorships with a higher circularity score have a significantly higher resilience score during crises and during normal times, compared to less circular companies. Furthermore, we find that the size of the company does not matter during a crisis to adapt and react flexibly, while it is important when there is no crisis. Finally, we argue that it is the combination of different circular strategies which yields to the highest results for the organizations' resilience and we provide policy recommendations based on the most asked support measures.

Abstract: Resource-efficient nutrient management is key to secure food production in the context of a growing global population, rising resource scarcity and increasing pressure on the environment. To map the potential towards increasing nutrient use efficiencies and reduce environmental losses, a high-resolution insight of the nitrogen (N) and phosphorus (P) nutrient streams is pivotal. In this study, a substance flow analysis for N and P is presented for the nutrient intensive region of Flanders (6,211,065 inhabitants) in Belgium for the year 2009. A set of 160 nutrient fluxes was quantified throughout 21 economic and environmental compartments, with a particular focus on 10 waste management processes. A total nutrient load of 20 kg N cap(-1) yr(-1) (ca. 73% to the air and 28% to surface waters) and 0.53 kg P cap(-1) yr(-1) (to surface waters) is emitted to the environment; with crop and livestock production as the main contributors (49% of N and 36% of P). The food supply chain revealed a fertilizer-to-consumer efficiency of 14% for N as well as for P, with important losses embedded in waste streams such as excess manure. Advanced manure and waste processing facilities nevertheless offer the opportunity for enhanced nutrient recycling to increase the nutrient use efficiencies and reduce the dependency of inorganic fertilizers. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: The European automotive sector is faced with potentially disruptive challenges. In particular, the projected increase in the share of electric vehicles (EVs) and calls to prepare for the implementation of more circular economy (CE) strategies are increasingly demanding systemic adaptations. Given the goals of the CE, the adaptations should enable a maximal preservation of the function and value of products (e.g. extension of lifetime), components (e.g. reuse of parts) and materials (e.g., material recycling), thus saving on the energy, materials and effort that would be required to restore the lost functionalities. In this context, statistical entropy analysis (SEA) is proposed as a methodology to assess the effort needed for preserving and restoring functionality at different product, component and material life cycle stages. Effort is measured as changes in statistical entropy that are caused by concentration and dilution activities in the production – consumption – End-of-Life (EoL) system. SEA was applied to a generic model of the European automotive system, in combination with a stock-driven model and a material flow analysis (MFA), allowing statistical entropy changes to be projected over time. The paper demonstrates how SEA can facilitate decision making on the transition towards a more circular economy by quantifying the effects of particular CE strategies and their combinations. The results show that without any additional system adaptations, an increasing share of EVs towards the year 2050 will lead to substantially increased effort in production as well as end-of-life vehicle treatment.

Abstract: Sustainable Materials Management (SMM) strategies, such as reuse, recycling and energy recovery aim, to capture more of the embedded resource or material value in products and waste streams. Reuse, recycling and energy recovery are existing activities in every society but they are poorly reflected in official statistics. Reaching higher levels of reuse, recycling and energy recovery may provide economic and environmental opportunities (i.e., in terms of GDP, jobs, reduced impacts), but not all options will have a net win-win-win property in practice, as they reduce the need for producing new commodities. In open economies, many primary resources, components and products are imported from abroad, and many goods produced are exported abroad. This paper describes a top-down methodology for estimating the substitution potential of intensifying specific SMM-strategies and material efficiency strategies. We combined both regional and multi-regional EE-IO (environmentally extended input-output) models to link industrial sectors to SMM-strategies. Our method enables us to compare the different SMM and material efficiency strategies in terms of the maximum available budgets for reaching them on a break even basis, maximum savings in global warming emissions and substituted employment effects, both through a regional and global perspective. We add a case on Flanders (Northern region in Belgium) to illustrate the methodology. Flanders is currently developing a policy for SMM. Selecting new regional actions for a Sustainable Materials Management policy can benefit from a good understanding of the international entangled value chains. It is important to understand how much of the chain is within reach of domestic policies and also to assess the consequences in terms of potential winners and losers, regarding GDP, jobs and environmental impacts, both domestically and abroad. We illustrated the potential outcomes for Flanders from four generic SMM-strategies: energy recovery, food waste prevention, recycling and reuse. From a strict regional self-interest perspective, it is preferable to substitute foreign value chains with local economic activities. Reuse creates by far the largest budget for new activities to realize the strategy (31.2% of Flemish GDP compared to 8.3% for food waste prevention, 6.2% for energy recovery and 4.2% for recycling). All four strategies have similar and significant potentials to reduce greenhouse gas emissions. However, food waste prevention and reuse have higher potentials to reduce Flemish territorial GHG-emissions. From a pure Flemish employment perspective, the energy recovery and recycling strategies could replace the fewest Flemish jobs, and from a global perspective, all strategies most likely imply losses of jobs abroad. (C) 2015 Elsevier B.V. All rights reserved.