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One of the main preventive measures recognized by WHO and implemented to mitigate the COVID-19 epidemic impact, by controlling the transmission of coronavirus, was the use of a facemask. Since a facemask is an accessory that can be used several hours a day, through which the air we breathe passes, and which is in contact with the face skin, it must not cause discomfort to the wearer and must not contain toxic, irritating or sensitizing substances. Therefore, it is of utmost importance to identify the toxic chemical compounds present in the facemask material. Hence, the present study aims to discuss a proposal for a low-VOC emission label to be assigned to facemasks’ materials in terms of respiratory and skin health. Two types of tests were proposed, one for analysis of VOC emissions, to assess the user exposure by inhalation, and the other for analysis of the VOC content, for evaluating the user exposure by dermal contact. Nine facemasks of different types: surgical (M1–M3), FFP2 (M4–M6) and reusable (M7–M9), were tested according to these methods. Comparing all the analyzed facemask types, the calculated TVOC dose, resulting from the exposure by inhalation, is very diversified, with low and high values, varying between 0 (in M7) and 2374 µg/day (in M6). However, they are consistently higher for the three analyzed self-filtering FFP2 respirators (M4–M6). Concerning dermal exposure, it is not possible to generalize, but the reusable facemasks analyzed in this work (M7–M9) consistently present higher values of skin-sensitizing compounds than the disposable facemasks (M1–M6). An attempt was made to establish criteria for assigning the low-VOC emission label. The proposed values are suggestions, requiring further studies. The authors expect that the results of this study may lead to future implementation of standards and regulations regarding the chemical compounds present in facemasks materials.

Regulative and social changes towards sustainability are promoting a significant growth of the electromobility sector. Lithium-ion batteries play a major role in this context; however its complex and energy-intensive process chain is responsible for a large part of cradle-to-gate impacts of electric vehicles. Therefore, this work discusses the influence of bottleneck reduction on the energy demand to foster energy efficiency in battery manufacturing. Based on data from the Battery LabFactory Braunschweig, a discrete event simulation is applied to identify bottlenecks and different scenarios for bottleneck reduction are analyzed. Next to improving existing process chain, the results may support the planning of new energy efficient installations.

The application of batteries in electric vehicles and stationary energy-storage systems is widely seen as a promising enabler for a sustainable mobility and for the energy sector. Although significant improvements have been achieved in the last decade in terms of higher battery performance and lower production costs, there remains high potential to be tapped, especially along the battery production chain. However, the battery production process is highly complex due to numerous process–structure and structure–performance relationships along the process chain, many of which are not yet fully understood. In order to move away from expensive trial-and-error operations of production lines, a methodology is needed to provide knowledge-based decision support to improve the quality and throughput of battery production. In the present work, a framework is presented that combines a process chain model and a battery cell model to quantitatively predict the impact of processes on the final battery cell performance. The framework enables coupling of diverse mechanistic models for the individual processes and the battery cell in a generic container platform, ultimately providing a digital representation of a battery electrode and cell production line that allows optimal production settings to be identified in silico. The framework can be implemented as part of a cyber-physical production system to provide decision support and ultimately control of the production line, thus increasing the efficiency of the entire battery cell production process.

Lithium-ion batteries are used in a wide range of applications, with the electromobility sector being the main contributor to the increasing demand predicted for the next decade. Although batteries play an important role in decarbonizing the transportation sector, their production includes energy-intensive processes that hinder a more sustainable production. Moreover, the production processes are characterized by a manifold of parameters leading to complex cause–effect relations along the process chain which influences the battery cell quality. Therefore, a sustainable future for battery production and the electromobility sector depends on the environmentally and economically efficient production of high-performance batteries. Against this background, this work presents a digitalization platform based on the coupling of mechanistic models to digitally reproduce the battery cell production and provide a deeper understanding of the interdependencies on the process, production, and product levels. In addition to a description of the individual models contained in the platform, this work demonstrates their coupling on a use case to study the effects of different solids contents of the coating suspension. Besides providing a multilevel assessment of the parameter interdependencies, considering quality, environmental and economic aspects, the presented framework contributes to knowledge-based decision support and improvement of production and battery cell performance.

Aims: Indoor air quality (IAQ) has attracted increased attention with the emergence of COVID-19. Ventilation is perhaps the area in which the most changes have been proposed in response to the emergency caused by this virus. However, other strategies are possible, such as source control and the extraction of pollutants. The latter incorporates clean technologies, an emergent area with respect to IAQ. Method: Various air treatment technologies can be used to control contaminants, which are reviewed and discussed in this work, including physicochemical technologies (e.g., filtration, adsorption, UV-photocatalytic oxidation, ultraviolet disinfection and ionization) and biological technologies (e.g., plant purification methods and microalgae-based methods). Results and interpretation: This work reviews currently available solutions and technologies for “cleaning” indoor air, with a focus on their advantages and disadvantages. One of the most common problems in this area is the emission of pollutants that are sometimes more dangerous to human health than those that the technologies were developed to remove. Another aspect to consider is the limitation of each technology in relation to the type of pollutants that need to be removed. Each of the investigated technologies works well for a family of pollutants with similar characteristics, but it is not applicable to all pollutant types. Thus, the optimal solution may involve the use of a combination of technologies to extend the scope of application, in addition to the development of new materials, for example, through the use of nanotechnology.

The world population is ageing, in particular in the developed world, with a significant increase in the percentage of people above 60 years old. They represent a segment of the population that is more vulnerable to adverse environmental conditions. Among them, indoor air quality is one of the most relevant, as elders spend comparatively more time indoors than younger generations. Furthermore, the recent COVID-19 pandemic contributed immensely to raising awareness of the importance of breathing air quality for human health and of the fact that indoor air is a vector for airborne infections and poisoning. Hence, this work reviews the state of the art regarding indoor air quality in elderly centers, considering the type of pollutants involved, their emission sources, and their health effects. Moreover, the influence of ventilation on air quality is also addressed. Notwithstanding the potential health problems with the corresponding costs and morbidity effects, only a few studies have considered explicitly indoor air quality and its impacts on elderly health. More studies are, therefore, necessary to objectively identify what are the impacts on the health of elderly people due to the quality of indoor air and how it can be improved, either by reducing the pollutants emission sources or by more adequate ventilation and thermal comfort strategies.