Cluster-induced desorption/ionization mass spectrometry of highlighter ink: unambiguous identification of dyes and degradation processes based on fragmentation-free desorption

Highlighter inks were analyzed by means of soft Desorption/Ionization induced by Neutral SO2 clusters (DINeC) in combination with mass spectrometry (MS). The dye molecules of the different inks were directly...

Potential Impacts of Climate Change on Land Degradation and Desertification

Land degradation and desertification have been graded as a major environmental and social dispute in most of the emerging countries. Changes in temperature, wind speed, and precipitation patterns will influence plant biomass production, land use, land cover, soil moisture, infiltration rate, runoff and crop management, and ultimately, land degradation. Close relations between climate change and land degradation processes have been perceived in the past decades. Climate change models and land use models should be combined with hydrologic/erosion models to accurately compute or predict climate change impacts on land degradation. This chapter introduces the advancements in modeling of impact of climate changes in land degradation and need for the critical investigation to better understand and forecast the responses of land degradation processes to a changing climate in the future.

Nanotechnology in Fire Protection—Application and Requirements

Nanotechnology is used, to an increasing extent, in practically every aspect of the economy and society. One area where nanotechnology is constantly advancing is fire protection. Nanostructures are found in elements used in direct protection, such as in protective clothing, filters, and helmets. Solutions in the field of nanotechnology are also used in elements reducing the fire risk and increasing the fire safety, such as building materials and structures, paints, coatings, or fire safety equipment (e.g., fire detectors). However, new solutions may also pose a threat to the safety of people and the environment. As a result of operation or combustion and degradation processes, the emission of nano-substances with toxic properties may occur. Therefore, knowledge in this field is necessary, as it allows for the appropriate targeting and use of nanotechnology.

Dynamic Release of Solutes from Roof Bitumen Sheets Used for Rainwater Harvesting

Bitumen waterproof sheets are widely used to seal building roofs. Previous works have focused on the mechanical-physical properties of bitumen sheets, as well as their aging and degradation processes, and their impact on sealing properties of the buildings. Due to a growing need over recent years to use rooftops in urban environments for rainwater harvesting purposes, it is highly important to better characterize the quality of the harvested water from the bitumen covered roofs, and to shed more light on the impact of bitumen degradation processes on the release of various components to the harvested roof water. In the present study, the extracted organic and inorganic solutes from bitumen-covered roofs by water flow on the bitumen sheets were examined through a series of experiments, including measurements from the roofs of buildings in the center of Israel during the winter of 2019–2020. The results indicated high levels of organic and inorganic solute loads in the roof water during the first flush of the first rain of the winter, with maximal electric conductivity readings at the order of 4 dS/m. However, it was shown that following the first flush, a ~20 mm of cumulative rainfall was sufficient to wash off all the summers’ accumulated solutes from the roof. After this solute flushing of the roof, harvested rainwater along the winter was of good quality, with electric conductivity readings in the range of 0.04–0.85 dS/m. Moreover, it was shown that bitumen sheets which were exposed to direct sun radiation emitted greater loads of solutes, likely a result of elevated aging and degradation processes. The findings of the present research point to the need to find efficient ways to isolate roof bitumen sheets from direct sun radiation and to design rainwater harvesting systems that will not collect the water drained from the first flush.

Operando acoustic emission monitoring of degradation processes in lithium-ion batteries with a high-entropy oxide anode

In recent years, high-entropy oxides are receiving increasing attention for electrochemical energy-storage applications. Among them, the rocksalt (Co0.2Cu0.2Mg0.2Ni0.2Zn0.2)O (HEO) has been shown to be a promising high-capacity anode material. Because high-entropy oxides constitute a new class of electrode materials, systematic understanding of their behavior during ion insertion and extraction is yet to be established. Here, we probe the conversion-type HEO material in lithium half-cells by acoustic emission (AE) monitoring. Especially the clustering of AE signals allows for correlations of acoustic events with various processes. The initial cycle was found to be the most acoustically active because of solid-electrolyte interphase formation and chemo-mechanical degradation. In the subsequent cycles, AE was mainly detected during delithiation, a finding we attribute to the progressive crack formation and propagation. Overall, the data confirm that the AE technology as a non-destructive operando technique holds promise for gaining insight into the degradation processes occurring in battery cells during cycling.

Degradation processes in tungsten filaments at high temperatures

Degradation processes in tungsten filaments of lighting lamps under normal operating conditions are experimentally studied. The duration of each measurement in continuous mode is about 18 hours. To increase the measurement accuracy, subtraction (compensation) of the constant component of the voltage is used. To compensate for the constant component of the voltage, a low noise reference DC voltage source is used. Using this scheme allowed decreasing the influence of the inherent noise of power supplies without suppressing degradation processes. It is shown that the relative change in resistance during the measurement does not exceed 2.8·10−3. It is also shown that the joint influence of voltage fluctuations of power supplies and low noise reference voltage source on the measurement results corresponds to a relative change in a resistance equal to 2.8·10−4. The study of degradation processes can be used to assess the reliability (and durability) of products in electrical engineering and radio electronics.

Monitoring of the condition and use of land in settlements (on the example of the city of Tchaikovsky, Perm Krai)

The paper presents a methodology for monitoring the lands of settlements, analyzes the state of the lands of the city of Tchaikovsky by qualitative and quantitative indicators, evaluates the assessment of the actual state of the lands of the city of Tchaikovsky, and develops a set of measures aimed at the rational use of the lands of the city of Tchaikovsky. The calculations carried out on the level of development and intensity of use of the territory over the past 10 years have allowed us to establish that, over the past 7 years, this indicator has hardly changed in the territory of the city of Tchaikovsky, only 1%. According to the results of a qualitative assessment of the state of the land, it was noted that the humus content in the soils is very low: no more than 3%, in heavy varieties, less than 2% - in light ones. Due to the small capacity of the humus horizon, it is completely involved in the arable layer, so it is reduced on the slopes as a result of water erosion. 35.5% of farmlands with a predominance of a weak degree of water erosion are subject to erosion processes. As a result of the assessment of damage from the manifestation of degradation processes, the amount of 60595 thousand rubles was established. As a result of the landscape and ecological zoning of the city territory, violations of the land use regimes within the boundaries of the established zones were established. Based on the comprehensive analysis, measures have been developed aimed at reducing the negative impact of enterprises and degradation processes. A set of measures to stabilize the state of the lands of the studied settlements is proposed.

Microbial Surface Biofilm Responds to the Growth-Reproduction-Senescence Cycle of the Dominant Coral Reef Macroalgae Sargassum spp.

Macroalgae play an intricate role in microbial-mediated coral reef degradation processes due to the release of dissolved nutrients. However, temporal variabilities of macroalgal surface biofilms and their implication on the wider reef system remain poorly characterized. Here, we study the microbial biofilm of the dominant reef macroalgae Sargassum over a period of one year at an inshore Great Barrier Reef site (Magnetic Island, Australia). Monthly sampling of the Sargassum biofilm links the temporal taxonomic and putative functional metabolic microbiome changes, examined using 16S rRNA gene amplicon and metagenomic sequencing, to the pronounced growth-reproduction-senescence cycle of the host. Overall, the macroalgal biofilm was dominated by the heterotrophic phyla Firmicutes (35% ± 5.9% SD) and Bacteroidetes (12% ± 0.6% SD); their relative abundance ratio shifted significantly along the annual growth-reproduction-senescence cycle of Sargassum. For example, Firmicutes were 1.7 to 3.9 times more abundant during host growth and reproduction cycles than Bacteroidetes. Both phyla varied in their carbohydrate degradation capabilities; hence, temporal fluctuations in the carbohydrate availability are potentially linked to the observed shift. Dominant heterotrophic macroalgal biofilm members, such as Firmicutes and Bacteroidetes, are implicated in exacerbating or ameliorating the release of dissolved nutrients into the ambient environment, though their contribution to microbial-mediated reef degradation processes remains to be determined.

Modeling and Monitoring Erosion of the Leading Edge of Wind Turbine Blades

Leading edge surface erosion is an emerging issue in wind turbine blade reliability, causing a reduction in power performance, aerodynamic loads imbalance, increased noise emission, and, ultimately, additional maintenance costs, and, if left untreated, it leads to the compromise of the functionality of the blade. In this work, we first propose an empirical spatio-temporal stochastic model for simulating leading edge erosion, to be used in conjunction with aeroelastic simulations, and subsequently present a deep learning model to be trained on simulated data, which aims to monitor leading edge erosion by detecting and classifying the degradation severity. This could help wind farm operators to reduce maintenance costs by planning cleaning and repair activities more efficiently. The main ingredients of the model include a damage process that progresses at random times, across multiple discrete states characterized by a non-homogeneous compound Poisson process, which is used to describe the random and time-dependent degradation of the blade surface, thus implicitly affecting its aerodynamic properties. The model allows for one, or more, zones along the span of the blades to be independently affected by erosion. The proposed model accounts for uncertainties in the local airfoil aerodynamics via parameterization of the lift and drag coefficients’ curves. The proposed model was used to generate a stochastic ensemble of degrading airfoil aerodynamic polars, for use in forward aero-servo-elastic simulations, where we computed the effect of leading edge erosion degradation on the dynamic response of a wind turbine under varying turbulent input inflow conditions. The dynamic response was chosen as a defining output as this relates to the output variable that is most commonly monitored under a structural health monitoring (SHM) regime. In this context, we further proposed an approach for spatio-temporal dependent diagnostics of leading erosion, namely, a deep learning attention-based Transformer, which we modified for classification tasks on slow degradation processes with long sequence multivariate time-series as inputs. We performed multiple sets of numerical experiments, aiming to evaluate the Transformer for diagnostics and assess its limitations. The results revealed Transformers as a potent method for diagnosis of such degradation processes. The attention-based mechanism allows the network to focus on different features at different time intervals for better prediction accuracy, especially for long time-series sequences representing a slow degradation process.