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Electroplating generates high volumes of rinse water that is contaminated with heavy metals. This study presents an approach for direct metal recovery and recycling from simulated rinse water, made up of an electroplating electrolyte used in industry, using reverse osmosis (RO). To simulate the real industrial application, the process was examined at various permeate fluxes, ranging from 3.75 to 30 L·m−2·h−1 and hydraulic pressures up to 80 bar. Although permeance decreased significantly with increasing water recovery, rejections of up to 93.8% for boric acid, >99.9% for chromium and 99.6% for sulfate were observed. The final RO retentate contained 8.40 g/L chromium and was directly used in Hull cell electroplating tests. It was possible to deposit cold-hued chromium layers under a wide range of relevant current densities, demonstrating the reusability of the concentrate of the rinsing water obtained by RO.
Resilience in the urban context can be described as a continuum of absorptive, adaptive, and transformative capacities. The need to move toward a sustainable future and bounce forward after any disruption has led recent urban resilience initiatives to engage with the concept of transformative resilience when and where conventional and top-down resilience initiatives are less likely to deliver effective strategies, plans, and implementable actions. Transformative resilience pathways emphasize the importance of reflexive governance, inclusive co-creation of knowledge, innovative and collaborative learning, and self-organizing processes. To support these transformative pathways, considering techno-social co-evolution and digital transformation, using new data sources such as Volunteered Geographic Information (VGI) and crowdsourcing are being promoted. However, a literature review on VGI and transformative resilience reveals that a comprehensive understanding of the complexities and capacities of utilizing VGI for transformative resilience is lacking. Therefore, based on a qualitative content analysis of available resources, this paper explores the key aspects of using VGI for transformative resilience and proposes a comprehensive framework structured around the identified legal, institutional, social, economic, and technical aspects to formalize the process of adopting VGI in transformative resilience initiatives.
Surrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations have become state of the art in algorithm design for solving real-world optimization problems. Still, it is difficult for practitioners to get an overview that explains their advantages in comparison to a large number of available methods in the scope of optimization. Available taxonomies lack the embedding of current approaches in the larger context of this broad field. This article presents a taxonomy of the field, which explores and matches algorithm strategies by extracting similarities and differences in their search strategies. A particular focus lies on algorithms using surrogates, nature-inspired designs, and those created by automatic algorithm generation. The extracted features of algorithms, their main concepts, and search operators, allow us to create a set of classification indicators to distinguish between a small number of classes. The features allow a deeper understanding of components of the search strategies and further indicate the close connections between the different algorithm designs. We present intuitive analogies to explain the basic principles of the search algorithms, particularly useful for novices in this research field. Furthermore, this taxonomy allows recommendations for the applicability of the corresponding algorithms.
Changing our unsustainable linear water management pattern is necessary to face growing global water challenges. This article proposes an integrated framework to analyse and understand the role of different contextual conditions in the possible transition towards water circularity. Our framework combines a systematic multi-level perspective to explore the water system and the institutional work theory for technology legitimation. The framework consists of the following stages: (1) describing and understanding the water context, (2) assessment of the selected technologies’ circularity level, (3) assessment of the alternative circular technologies’ legitimacy, and (4) identification of the legitimation actions to support the upscale of alternative circular technologies. The practical applicability of the integrated assessment framework and its four assessment stages was demonstrated in the exploration of circular water technologies for the horticulture sector in Westland, the Netherlands. The results revealed the conditions that hinder or enable the legitimation of the circular water technologies, such as political environmentalism, trust in water governing authorities, and technical, financial, and knowledge capabilities.
Climate change includes the change of the long-term average values and the change of the tails of probability density functions, where the extreme events are located. However, obtaining average values are more straightforward than the high temporal resolution information necessary to catch the extreme events on those tails. Such information is difficult to get in areas lacking sufficient rain stations. Thanks to the development of Satellite Precipitation Estimates with a daily resolution, this problem has been overcome, so Extreme Precipitation Indices (EPI) can be calculated for the entire Colombian territory. However, Colombia is strongly affected by the ENSO (El Niño—Southern Oscillation) phenomenon. Therefore, it is pertinent to ask if the EPI’s long-term change due to climate change is more critical than the anomalies due to climate variability induced by the warm and cold phases of ENSO (El Niño and La Niña, respectively). In this work, we built EPI annual time series at each grid-point of the selected Satellite Precipitation Estimate (CHIRPSv2) over Colombia to answer the previous question. Then, the Mann-Whitney-Wilcoxon test was used to compare the samples drawn in each case (i.e., change tests due to both long-term and climatic variability). After performing the analyses, we realized that the importance of the change depends on the region analyzed and the considered EPI. However, some general conclusions became evident: during El Niño years (La Niña), EPI’s anomaly follows the general trend of reduction -drier conditions- (increase; -wetter conditions-) observed in Colombian annual precipitation amount, but only on the Pacific, the Caribbean, and the Andean region. In the Eastern plains of Colombia (Orinoquía and Amazonian region), EPI show a certain insensitivity to change due to climatic variability. On the other hand, EPI’s long-term changes in the Pacific, the Caribbean, and the Andean region are spatially scattered. Still, long-term changes in the eastern plains have a moderate spatial consistency with statistical significance.
The management of the liquid fraction of digestate produced from the anaerobic digestion of biodegradable municipal solid waste is a difficult affair, as its land application is limited due to high ammonium concentrations and the municipal waste that water treatment plants struggle to treat due to high pollutant loads. The amount of leachate and the pollutant load in the leachate produced by landfills usually decreases with the time, which increases the capacity of landfill leachate treatment plants (LLTPs) to treat additional wastewater. In order to solve the above two challenges, the co-treatment of landfill leachate and the liquid fraction of anaerobic digestate in an industrial-scale LLTP was investigated along with the long-term impacts of the liquid fraction of anaerobic digestate on biocoenosis and its impact on LLTP operational expenses. The co-treatment of landfill leachate and liquid fraction of anaerobic digestate was compared to conventional leachate treatment in an industrial-scale LLTP, which included the use of two parallel lanes (Lane-1 and Lane-2). The average nitrogen removal efficiencies in Lane-1 (co-treatment) were 93.4%, 95%, and 92%, respectively, for C/N ratios of 8.7, 8.9, and 9.4. The average nitrogen removal efficiency in Lane-2 (conventional landfill leachate treatment), meanwhile, was 88%, with a C/N ratio of 6.5. The LLTP’s average chemical oxygen demand (COD) removal efficiencies were 63.5%, 81%, and 78% during phases one, two, and three, respectively. As the volume ratios of the liquid fraction of anaerobic digestate increased, selective oxygen uptake rate experiments demonstrated the dominance of heterotrophic bacteria over ammonium and nitrite-oxidising organisms. The inclusion of the liquid fraction of anaerobic digestate during co-treatment did not cause a significant increase in operational resources, i.e., oxygen, the external carbon source, activated carbon, and energy.
Concept for Combining LCA and Hazardous Building Material Assessment for Decision Support Using BIM
(2022)
AbstractThe construction and building sector is responsible for a large part of the world’s resource and energy consumption and is considered the largest global emitter of greenhouse gas (GHG) emissions. Hazardous and toxic substances in building materials affect indoor air quality as well as the environment and thus have a high impact on human health, as we spend around 90 percent of our lives in buildings. Life cycle assessment (LCA) and hazardous building material requirements of green building certification systems allow to reduce the environmental and health impacts of building products and materials. However, they are usually very complex and time-consuming to perform and require expert knowledge to use the results for decision support. Digital approaches to support the simplified application of these methods and intuitive visualization of results are becoming increasingly important. Especially Building Information Modeling (BIM) offers a high potential for this purpose, as the integration and linking of geometric and semantic information in 3D-models for LCA and hazardous building material assessment can be done much more efficiently and intuitively. Within the scope of this work, the following three objectives were pursued (1) development of a method for combining LCA and hazardous building material assessment, (2) simplification of the results by converting them into comprehensible indicators for decision support, and (3) implementation of the method in a BIM-based digital assistant for intuitive visualization and communication. The preliminary results show a concept for combined use of LCA and hazardous building material assessment in Germany with differentiation in six use cases. A prototypical implementation as BIM-integrated digital assistant was developed for one of these use cases. For the first time, this prototype provides understandable feedback in real time of LCA and hazardous building material requirements. This research project contributes to the awareness in the context of embodied impacts and low emitting materials in buildings and advances the current digitalization potentials.
Remaining-useful-life (RUL) prediction of Li-ion batteries is used to provide an early indication of the expected lifetime of the battery, thereby reducing the risk of failure and increasing safety. In this paper, a detailed method is presented to make long-term predictions for the RUL based on a combination of gated recurrent unit neural network (GRU NN) and soft-sensing method. Firstly, an indirect health indicator (HI) was extracted from the charging processes using a soft-sensing method that can accurately describe power degradation instead of capacity. Then, a GRU NN with a sliding window was applied to learn the long-term performance development. The method also uses a dropout and early stopping method to prevent overfitting. To build the models and validate the effectiveness of the proposed method, a real-world NASA battery data set with various battery measurements was used. The results show that the method can produce a long-term and accurate RUL prediction at each position of the degradation progression based on several historical battery data sets.
The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.