Sanitär- und Kommunaltechnik; Umwelttechnik
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Introduction: Effective disinfection is crucial to maintain hygiene and to prevent the spread of infections. Phenotypic heterogeneity in disinfection survival (i.e. tolerance) may result in failure of disinfection, which in turn may foster the evolution of resistance to both disinfectants and antibiotics. However, the consequences of phenotypic heterogeneity for disinfection outcome and resistance evolution are not well understood. Goal: This study investigates the impact of phenotypic heterogeneity on the survival and evolution of Escherichia coli during disinfection with six commonly used substances. Furthermore, the consequences of evolved disinfectant tolerance for antibiotic resistance evolution are studied. Materials & Methods: The extent of population heterogeneity during disinfection is derived by determining time-kill kinetics and analysis with mathematical modelling. The link between population heterogeneity and evolvability of disinfectant tolerance was assessed by laboratory evolution experiments under periodic disinfection. The ability of disinfectant tolerant strains to evolve antibiotic resistance is assessed by serial transfer experiments with increasing concentrations of different antibiotics and by whole genome sequencing. Results: Multi-modal time-kill kinetics in three of the six disinfectants suggest the presence of disinfectant-tolerant subpopulations (i.e. persister cells). Importantly, the ability and extent to evolve population-wide tolerance under periodic disinfection is related with the presence of persister cells and the level of phenotypic heterogeneity during disinfection. Interestingly, the probability of high-level resistance evolution to certain antibiotics is attenuated in disinfectant tolerant strains as compared to the sensitive ancestor. Whole-genome sequencing reveals epistatic interactions between disinfectant tolerance and antibiotic resistance mutations, preventing access to canonical evolutionary paths to resistance. Summary: Our findings suggest that phenotypic heterogeneity can facilitate disinfection survival and the evolution of population wide tolerance, which can impact future antibiotic resistance evolution.
The biogenesis of iron–sulfur (Fe/S) proteins entails the synthesis and trafficking of Fe/S clusters, followed by their insertion into target apoproteins. In eukaryotes, the multiple steps of biogenesis are accomplished by complex protein machineries in both mitochondria and cytosol. The underlying biochemical pathways have been elucidated over the past decades, yet the mechanisms of cytosolic [2Fe-2S] protein assembly have remained ill-defined. Similarly, the precise site of glutathione (GSH) requirement in cytosolic and nuclear Fe/S protein biogenesis is unclear, as is the molecular role of the GSH-dependent cytosolic monothiol glutaredoxins (cGrxs). Here, we investigated these questions in human and yeast cells by various in vivo approaches. [2Fe-2S] cluster assembly of cytosolic target apoproteins required the mitochondrial ISC machinery, the mitochondrial transporter Atm1/ABCB7 and GSH, yet occurred independently of both the CIA system and cGrxs. This mechanism was strikingly different from the ISC-, Atm1/ABCB7-, GSH-, and CIA-dependent assembly of cytosolic–nuclear [4Fe-4S] proteins. One notable exception to this cytosolic [2Fe-2S] protein maturation pathway defined here was yeast Apd1 which used the CIA system via binding to the CIA targeting complex through its C-terminal tryptophan. cGrxs, although attributed as [2Fe-2S] cluster chaperones or trafficking proteins, were not essential in vivo for delivering [2Fe-2S] clusters to either CIA components or target apoproteins. Finally, the most critical GSH requirement was assigned to Atm1-dependent export, i.e. a step before GSH-dependent cGrxs function. Our findings extend the general model of eukaryotic Fe/S protein biogenesis by adding the molecular requirements for cytosolic [2Fe-2S] protein maturation.
Any surface in the environment acts as hotspot for microbial attachment and activity. These biofilms represent the interface between humans and the environment.
While in the past biofilms were often seen as disturbance, we now start to understand the enormous potential of beneficial biofilms. They can be used in a broad range of applications and are sources for new microorganisms and traits. After all, biofilms represent a great example for a collaborative lifestyle.
This presentation provides an introduction and intermediate results of the Horizon-Europe STAR4BBS project.It focuses on how to maximize the potential of Sustainability Certification Schemes (SCS) and labels to support a successful transition to a sustainable bio-based economy by assessing their effectiveness, robustness, and credibility.
Barriers to transitioning to a circular bio-based economy: Findings from an industrial perspective
(2024)
The transition from a linear fossil-based to a circular bio-based economy represents an opportunity and a suitable pathway for achieving several sustainable development goals. However, the transition is a complex process since it requires transformative policies, purposeful innovation, access to finance, risk-taking capacity as well as new and sustainable business models and markets. Accordingly, the first step in this transition process is the identification of barriers that are hampering the transition to a sustainable circular bio-based economy. With this motivation in mind, this study reviews grey literature to identify barriers focusing on four critical sectors facing major challenges within the current linear economy and requiring a sustainable transition most urgently: construction, chemicals, plastics, and textile sectors. Employing an adapted STEEP methodology (Social, Technological, Economical, Environmental, Political), a total of 193 different barriers have been identified and clustered under six categories: cultural, technical, economic, environmental, governance, and structural. Regardless of the sector, cultural and structural barriers are identified as the most prominent; the lack of incentives for consumer behaviour change and lack of stakeholder collaboration were the most cited barriers among the literature records. From a value chain perspective, most of the barriers are related to the material processing and product manufacturing stage. Finally, potential solutions, extracted from the grey literature, are proposed to fill the gaps and overcome the identified barriers. Many of the identified barriers are common across the four investigated sectors, indicating the solutions or measures can be applicable in a wider perspective to promote the transition in the right direction.
The Microplastic Microbiome
(2024)
Microplastics represent man-made and newly emerging surfaces in our ecosystems, where they interact with microorganisms. The ecosystem in focus of this presentation will be the aquatic environment. It will be portrayed, which microorganisms use microplastics as a habitat, how environmental factors shape this colonization, and why the biodegradation of plastics in the ocean is an overall unlikely process. We will also discuss whether potentially pathogenic microorganisms use microplastics as a raft. Finally, possible adaptation mechanisms of plastic-colonizing microorganisms will be presented, such as the production of photoreactive molecules. The microplastic microbiome has a large potential to harbor so far unknown species with curious traits, representing an exciting research topic for the future.
We introduce a passive smart dust concept as a novel solution for environmental monitoring. Utilizing chemical reagents like colorimetric indicators and other chemosensors, these particles detect varying environmental conditions. We developed paper-based sensors that are both cost-effective and eco-friendly. In practical tests, these sensors, dispersed over a designated area, successfully identified hazardous substances by changing their color when exposed to acids or bases. This color change was remotely detectable using a drone-mounted color camera. The data thus obtained was processed through specialized software, accurately pinpointing areas of contamination. This method proves the efficacy and scalability of passive smart dust technology for real-time, environmentally sustainable remote sensing of hazardous materials
Use/distribution of cost-effective and biocompatible pieces of cellulose paper as passive optical chemosensors and readout by the camera system.
Modification of the paper surface using various chemically sensitive dyes (indicators) provides an optically detectable reaction and conclusions about the target substances and precise location.
Revolutionizing our polymer industry for adaption to a sustainable carbon circular economy has become one of today’s most demanding challenges. Exploiting renewable resources to replace fossil-fuel—based plastics with biopolymers such as poly(lactic acid) (PLA) is inevitable while using waste streams as a raw material resource at least is promising. When it comes to using PLA as technical polymer, its high flammability must be addressed by flame retardants compatible with the thermoplastic processing of PLA and its compostability. This study proposes microalgae enriched with phosphorus from wastewater (P-Algae) as an elegant way towards a kind of sustainable organophosphorus flame retardant. The concept is demonstrated by investigating the processing, pyrolysis, flammability, and fire behavior of PLA/P-Algae, while varying the P-Algae content and comparing P-Algae with four alternative bio-fillers (phosphorylated lignin, biochar, thermally treated sewage sludge, and metal phytate) with different P-contents as meaningful benchmarks.
This paper outlines significant advancements in our previously developed aerial gas tomography system, now optimized to reconstruct 2D tomographic slices of gas plumes with enhanced precision in outdoor environments. The core of our system is an aerial robot equipped with a custom-built 3-axis aerial gimbal, a Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor for CH4 measurements, a laser rangefinder, and a wide-angle camera, combined with a state-of-the-art gas tomography algorithm. In real-world experiments, we sent the aerial robot along gate-shaped flight patterns over a semi-controlled environment with a static-like gas plume, providing a welldefined ground truth for system evaluation. The reconstructed cross-sectional 2D images closely matched the known ground truth concentration, confirming the system’s high accuracy and reliability. The demonstrated system’s capabilities open doors for potential applications in environmental monitoring and industrial safety, though further testing is planned to ascertain the system’s operational boundaries fully.
Gas Distribution Mapping (GDM) is essential in monitoring hazardous environments, where uneven sampling and spatial sparsity of data present significant challenges. Traditional methods for GDM often fall short in accuracy and expressiveness. Modern learning-based approaches employing Convolutional Neural Networks (CNNs) require regular-sized input data, limiting their adaptability to irregular and sparse datasets typically encountered in GDM. This study addresses these shortcomings by showcasing Graph Neural Networks (GNNs) for learningbased GDM on irregular and spatially sparse sensor data. Our Radius-Based, Bi-Directionally connected GNN (RABI-GNN) was trained on a synthetic gas distribution dataset on which it outperforms our previous CNN-based model while overcoming its constraints. We demonstrate the flexibility of RABI-GNN by applying it to real-world data obtained in an industrial steel factory, highlighting promising opportunities for more accurate GDM models.
Per- and polyfluoroalkyl substances (PFAS) were classified as a group of highly concerning chemicals over the last decades. Because of the high persistence of PFAS, their previous use led to contamination of the environment and human population. Due to ongoing use and incomplete remediation or destruction methods, the PFAS background in the environment is growing continuously.
The presence of ultrashort PFAS (with ≤3 carbon atoms) in the environment is often overlooked despite their contributions to PFAS levels. These compounds may directly contaminate the environment and arise from degradation of polyfluorinated compounds as well as incomplete PFAS destruction in certain industrial processes. Nonetheless, few approaches for targeted analysis of ultrashort PFASs have been developed, except for trifluoroacetic acid (TFA). Beside liquid (LC-MS/MS), supercritical fluid (SFC-MS/MS), and ion chromatography (IC-MS)-based systems, gas chromatography coupled with mass spectrometry (GC-MS) is a promising method for detection and quantification of ultrashort PFAS.
The goal of this study was to develop a simple headspace GC-MS method for the quantification of ultrashort perfluorocarboxylic acids (PFCAs) and polyfluorinated alcohols (PFOHs) in water samples. In contrast to PFOHs, functionalization of PFCAs was required for quantification. This was done by esterification with methanol at 80 °C, which can be carried out directly in the headspace GC-MS system.
Moreover, several parameters were optimized to achieve a low limit of quantification (LOQ) for the analytes used: i) The ratio of the aqueous solution, methanol, and available gas phase within the analysis vessel, ii) the concentration of additional acid in esterification mixtures of PFCAs, iii) shaking frequency and iv) shaking time before analysis. After optimizing the procedure, we were able to quantify ultrashort PFCAs and PFOHs. Thus, our developed headspace GC-MS method has the potential to be used as an alternative target analysis for ultrashort-chain PFCAs and PFOHs in various water samples (groundwater, wastewater).
Monitoring of microplastics in food matrices is crucial to determinate the human exposure. By direct ingestion microplastics could be released in the food during the production, through packaging and by consumer’s use. The absence of standard methods to quantify and detect different size range and type of microplastics has led to difficult and time consuming procedural steps, poor accuracy and lack of comparability. In this work, matrix characterization and laboratory experiments were used to investigate the efficiency of sample preparation in milk powder. This information is crucial to compile a standard procedure for sample preparation and digestion of common milk powder to detect different particle sizes and types of polymers. Charaterisation is done by TGA and TOC measurements.
Following the recommendation of the European Chemicals Agency, on 25 September 2023 the European Commission passed a comprehensive new regulation to reduce emissions of microplastics (MP) into the environment, which includes the sale and use of intentionally added MP.1,2 This also applies to the application of synthetic rubber granulate infill in artificial turf systems and will ultimately have an impact on recreational sports. In Germany, rubber granulate made of ethylene-propylene-diene-monomer rubber (EPDM) is currently predominantly used. So far, there is no sufficient database for estimating MP emissions from artificial turf pitches into the environment and thus their relevance as a source of MP pollution.3 This topic is controversially discussed due to the complexity of sampling and analytics. To close this research gap, this project has the goal to determine mass balances for the emissions of MP from artificial turf pitches to allow an estimation of the amount of MP released per artificial turf pitch and year.
Within this study, MP emissions of three artificial turf scenarios at different time states (unaged, artificially aged and real-time aged) are compared: the past (old turf: fossil based, synthetic infill), present (most commonly installed in Europe: fossil based, EPDM infill), and the future (turf with recycled gras fibres, no synthetic infill). To simulate the outdoor weathering during the lifespan of an artificial turf of approx. 15 years, brand-new artificial turf and EPDM rubber granulate were accelerated aged by means of UV weathering and mechanical stress. Potential MP emissions into surface and groundwater are simulated by lysimeter and shake experiments. MP mass contents are subsequently determined by Thermal Extraction Desorption Gas Chromatography/Mass Spectrometry. Using special microfilter crucibles allows the estimation of the particle sizes of the emitted MP, which is a fundamental requirement for an assessment of potential health hazards for humans.
This study explores the acceleration of material design in the concrete industry, focusing on improving carbonation resistance, a key factor in the durability of concrete structures. Traditional tests for carbonation resistance are lengthy, but with the construction industry aiming for sustainable production, finding a balance between carbonation resistance and CO2 footprint is crucial. Our research employs two innovative methods: 1. Applying the Sequential Learning App for Materials Discovery (SLAMD), an AI materials design framework, to an extensive dataset of real-world concrete compositions to selectively test materials that meet market demands: maximum durability, optimal eco-durability, and the best cost-durability trade-off. 2. Investigating 1H Nuclear Magnetic Resonance (NMR) relaxometry as a quick alternative for characterizing carbonation behavior, as it saves time compared to traditional tests and assesses the complete material's pore space. Specific NMR features are then integrated into the material design model, with the model's performance compared against traditional approaches. The results of our study are compelling, demonstrating that materials can be precisely tailored to meet specific requirements with minimal data points. This marks a significant stride in the concrete industry, indicating that NMR-based, low-fidelity surrogate characterizations, combined with a focused, data-driven design approach, can substantially accelerate the development of durable, sustainable concrete mixtures.
Volatile organic compounds (VOCs) emitted by furniture and building materials can cause health issues. For an improvement of indoor air quality low emitting materials should be used. Quality assurance and –control (QA/QC) measures require an emission reference material (ERM) with a predictable emission rate of VOCs. The idea is to use porous materials as ERM, which store the VOCs inside their pores and emit them constantly.
Interlaboratory studies are common tools for collecting comparable data to implement standards for new materials or testing technologies. In the case of construction materials, these studies form the basis for recommendations and design codes. Depending on the study, the amount of data collected can be enormous, making manual handling and evaluation difficult. On the other hand, the importance of the FAIR (findable, accessible, interoperable, and reusable) principles for scientific data management, published by Wilkinson et al. in 2016, is constantly growing and changing the view on data usage.
The benefits of using data management tools such as data stores/repositories or electronic laboratory notebooks are many. Data is stored in a structured and accessible way (at least within a group) and data loss due to staff turnover is reduced. Tools usually support data publishing and analysis interfaces. In this way, data can be reused years later to generate new knowledge with future insights. On the other hand, there are many challenges in setting up a data repository, such as selecting suitable software tools, defining the data structure, enabling data access, and understanding by others and
ensuring maintenance, among others.
This talk discusses the advantages and challenges of setting up and applying a data repository using the interlaboratory study on the mechanical properties of printed concrete structures carried out in RILEM TC 304-ADC as example. First, the definition of a suitable data structure including all information is discussed. The tool-dependent upload process is then described. Here, the data
management system openBIS (open source software developed by ETH Zurich) is used. Since in most cases an open compute platform allowing access from different organisations is not possible or available due to data protection and maintenance issues, tool-independent export options are discussed and compared. Finally, the different query and analysis possibilities are demonstrated.
Homochirality is an obvious feature of life on Earth. On the other hand, extraterrestrial samples contain largely racemic compounds. The same is true for any common organic synthesis. Therefore, it has been a perplexing puzzle for decades how these racemates could have formed enantiomerically enriched fractions as a basis for the origin of homochiral life forms. Numerous hypotheses have been put forward as to how preferentially homochiral molecules could have formed and accumulated on Earth. In this article, it is shown that homochirality of the abiotic organic pool at the time of formation of the first self-replicating molecules is not necessary and not even probable. It is proposed to abandon the notion of a molecular ensemble and to focus on the level of individual molecules. Although the formation of the first self-replicating, most likely homochiral molecule is a seemingly improbable event, on a closer look, it is almost inevitable that homochiral molecules have formed simply on a statistical basis. In this case, the non-selective leap to homochirality would be one of the first steps in chemical evolution directly out of a racemic “ocean”. Moreover, most studies focus on the chirality of the primordial monomers with respect to an asymmetric carbon atom. However, any polymer with a minimal size that allows folding to a secondary structure, would spontaneously lead to asymmetric higher structures (conformations). Most of the functions of these polymers would be influenced by this inherently asymmetric folding. To summarize, simple and universal mechanisms may have led to homochiral self-replicating systems in the context of chemical evolution. A homochiral monomer pool is deemed unnecessary and probably never existed on primordial Earth.
Organotin compounds (OTCs) have been widely used in anti-fouling paints, pesticide formulations, and as stabilizers in polyvinyl chloride over the past century. In marine ecosystems, OTCs can cause severe damage to biodiversity, leading up to the extinction of vulnerable species. Due to the extensive use of tributyltin (TBT) as a biocide on ship hulls, it has been considered one of the most hazardous substances intentionally introduced into the aquatic environment. This resulted in a global ban on TBT-containing products in the 2000s. However, recent studies indicate the emerging presence of organotin pollutants.
OTCs are known to persist and accumulate in marine sediments, posing a long-term threat to the environment. These harmful substances can be set free and dispersed even after several decades. Therefore, analyzing sediment probes is imperative for a thorough monitoring of pollution. However, species-specific analysis of OTCs at required concentration levels in complex environmental matrices remains challenging. Chromatographic systems are commonly used for their analysis, but the required sample preparation is time-consuming and prone to contamination and analyte loss. The coupling of electrothermal vaporization and inductively coupled plasma-mass spectrometry (ETV/ICP-MS) demonstrates high potential as a rapid, convenient, and chemical-saving scanning tool for environmental samples.
This method enables the direct on-line fractionation of organic compounds from an inorganic fraction and provides element-specific detection at ultra-trace levels without complex sample preparation. Since OTCs are generally more toxic than ionic or elemental tin, analyzing them as a sum parameter is advantageous. Additionally, the determination of both organic and inorganic tin, rather than just organic tin, reveals valuable information about the fate of OTCs. The main challenge in obtaining accurate quantitative data using direct solid sampling techniques like as ETV/ICP-MS is applying a suitable calibration strategy. Our isotope dilution approach overcomes matrix effects in ETV/ICP-MS analysis and is compatible with commercial systems.