Urban air pollution is a significant threat to both the environment and public health. Primarily originating from traffic emissions, particulate matter is identified as the most prevalent and toxic pollutant in cities. In recent years, street vegetation has emerged as a nature-based solution to improve urban air quality. However, to achieve this goal, proper placement of vegetation is crucial. This study critically investigates how different street tree placement strategies affect the local air quality, based on a model calibrated using existing air quality measurements from one of the most polluted streets in Glasgow. We then test the local air quality effects of tree orientation, spacing, shape, porosity, size, species, and wind directions. The findings suggest that trees effectively enhance air quality, particularly when implemented on the leeward side of the street. To achieve optimal effectiveness, the spacing of trees require careful alignment with the aspect ratio, as haphazard planting could lead to unfavorable results. The insights on improving air quality in Glasgow's street canyons, complements the objectives of the ‘Glasgow Avenues Programme’ and can be included in its Low Emission Zones to co-benefit the environment and the wellbeing of the local community.

This study addresses the pressing need for flood extent and exposure information in data-scarce and vulnerable regions, with a specific focus on West Africa, particularly Senegal. Leveraging the Google Earth Engine (GEE) platform and integrating data from Sentinel-1 SAR, Global Surface Water, HydroSHEDS, Global Human Layer Settlement, and MODIS Land Cover, our primary ob-jective is to delineate flood extents and compare them with centennial flood-prone areas, offering a comprehensive assessment of exposure during the period from July to October 2022 across Sen-egal's 14 regions. The findings underscore a total inundation area of 2 951 square kilometers, impacting 297 142 people, 175 square kilometers of urban and 16 square kilometers of crops. Notably, August wit-nessed the largest flooded areas, reaching 780 square kilometers, constituting 0.40% of the coun-try's surface. Subsequent regions, including Saint-Louis, Ziguinchor, Fatick, and Matam, experi-enced varying extents of flooding, with August data showing a 1.34% overall overlap compared to centennial flood-prone areas derived from hydrological and hydraulic modeling. This low per-centage reveals the distinct purposes and natures of the two approaches (remote sensing and modeling), as well as their complementarity. Turning to flood exposure, August emerges as the most critical month, affecting 76 595 people (0.43% of the total population). Dakar, Diourbel, Thiès, and Saint-Louis regions bore substantial impacts, affecting 100 707, 57 648, 31 579, and 26 581 people, respectively. These findings emphasize the imperative for comprehensive disaster preparedness and mitigation efforts. The study provides a crucial national-scale perspective to guide Senegal's authorities in formulating effective flood management, intervention, and adaptation strategies.

The emission of sulphur dioxide (SO2) from mining activities presents a substantial risk to public health, especially in populations located near mine industrial regions. This study investigated the potential correlation between exposure to sulphur dioxide (SO2) and its effects on respiratory health in Kankoyo Township, Zambia. A variety of methodologies were employed in this study, encompassing community participation, expert interviews, spatial analysis, and a retrospective examination of health and SO2 data for Kankoyo spanning 15 years. The results of our research indicated a worrisome correlation between the community and the presence of SO2, which has had a significant impact on their lives. The expert interviews also emphasized the effects of SO2, with respiratory cases accounting for approximately 75% of the reported cases. Additionally, the clinic officer observed that asthma cases have decreased following the implementation of a monitoring station in the community. Furthermore, overall emissions of SO2 have decreased since the upgrade of the smelter operation. A probable association was identified in the retrospective analysis between exposure to SO2 and the occurrence of asthma, respiratory non-pneumonia, and pneumonia infections. The findings of the retrospective research revealed a substantial association between SO2 concentrations and the susceptibility of individuals aged 5 years and older to asthma, respiratory non-pneumonia, and pneumonia infections. The results of the spatial study indicated that Kankoyo exhibited a significant level of SO2 pollution, above the established limitations set by the Zambian Environmental Management Agency (ZEMA) by an alarming margin of 1713%. In response to the challenges identified, this study proposed several measures. These measures encompassed the implementation of a requirement for regulators such as ZEMA and local communities to have access to real-time pollution data from mines, to enhance transparency. Additionally, the deployment of affordable air quality sensors, the resolution of medication shortages, the establishment of specialized respiratory health clinics, the initiation of IT-driven public awareness campaigns, and the expansion of research to investigate additional pollutants and confounding factors were also recommended.

This article presents a low-cost insurance system developed for small-hold farms in disaster-prone regions, primarily using free Earth Observation (EO) data and Free Open Source Software (FOSS) – collectively termed sustainable geoinformatics - with a proprietary mobile phone app that enables verification. The study examined 30 farms in Risaralda department, Colombia. A Digital Elevation Model (12.5m pixels) from the ALOS PALSAR satellite sensor was used with a Geographical Information System (GIS) to map the terrain, drainage and geohazards of each farming district. Google Earth Engine (GEE) was used to carry out Time Series Analysis of 15 EO and weather datasets for 1998 to 2020. This analysis enabled the levels of risk from hydrometeorological hazards to be determined for each farm of the study, providing key data for the setting of insurance premiums. A parametric insurance product was piloted using GPS-tagged, time-stamped mobile phone photos to verify crop health. Key features of this insurance system are its low operational cost and rapid damage verification, relative to conventional approaches to farm insurance. It is an affordable form of insurance for small-scale farmers, with the rapid verification and payment of claims. This relatively fast, low-cost and affordable approach to insurance for small-scale farming enhances sustainable development by enabling policy-holder farmers to recover more quickly from disasters.

In 2011, commercial aviation contributed approximately 3.5% of global anthropogenic climate change through the emission of greenhouse gases during flight and operational non-CO2 climate effects. Over the last few years, numerous aviation-related organisations have set goals to reduce aviation’s climate impact. These goals, however, lack alignment, are poorly or ambiguously defined, or are internally inconsistent. This increases uncertainty about what aviation should work towards, how various stakeholders can contribute, and introduces problems with respect to accountability. In order to address this issue, this paper presents a comprehensive definition of a climate neutral air transport system as an “air transport system of which the climate effects of all its greenhouse gases and non-carbon dioxide effects throughout the entire life-cycle of each element of the system is balanced”. The proposed definition spans relevant system and encompasses all life cycle phases. To achieve a climate neutral air transport system by 2050, all life-cycle greenhouse gas emissions and non-CO2 climate effects remaining after in-sector reduction should be neutralised, as should all remaining non-CO2 climate forcing from emissions prior to 2050. Clarity on governance is furthermore needed, as the goal and associated targets proposed should be adopted globally.

BACKGROUND AND OBJECTIVE: The use of biomass for cooking carries significant health implications and can lead to adverse environmental issues such as deforestation, greenhouse gas emissions, and erosion. Despite these concerns, there is a lack of information about the nature and extent of cooking emissions in many developing countries. To address this gap, a study was conducted to assess cooking emission levels and their associated health effects among households in Dodoma City, Tanzania. METHODS: A descriptive cross-sectional design was conducted, involving 285 households in the peri-urban area of Dodoma City, Tanzania. A combination of questionnaires, observational checklists, and sampling devices (Aeroqual series 500 for Carbon Monoxide and Temptop PMD 351 for Particulate Matters) were employed for data collection, adhering to established protocols. Additionally, lung function tests were conducted with consent from the primary household cooks. Collected data were entered into an Excel spreadsheet and analyzed using STATA 17 software. FINDINGS: Out of 285 participants, 74.7% predominantly use charcoal for cooking, with 68.4% having outdoor kitchen setups. Significant differences in pollutant concentrations were observed across various fuel types (P=0.0001), with firewood emitting higher levels of particulate matter and carbon monoxide. Carbon monoxide concentrations during cooking were 6 times higher for firewood, 5 times higher for charcoal-gas, and 3 times higher for charcoal compared to WHO daily average limits. Additionally, a positive correlation between pollutant concentrations was noted (P-value = 0.0000). Lung problems 17.8% followed by eye irritation 15.7% were mentioned by those who claimed to know the health effects associated with cooking emissions. In addition, the spirometry test indicated that the majority of the participants had % predicted >80 while only 19% had % predicted below 50. CONCLUSION: Charcoal and firewood remain the primary cooking fuels in the study area despite their significant negative impacts. Our findings highlight a lack of awareness among community members regarding the health effects of biomass cooking emissions and insufficient guidance on constructing healthy kitchens. To address this, enforcing building standards, raising health awareness, and ensuring affordable access to modern fuels are crucial steps. These measures are essential for promoting healthier cooking practices and mitigating the adverse effects on households.

Raw earth bricks made from the soil of the Chalky Champagne region (France) have been used for at least two millennia in construction, a promising heritage in the context of reducing the carbon emissions of buildings. The present experimental study aims at measuring the physical, mechanical, thermal, and hydric properties of adobes collected from a local village barn. Results show a high chalk content estimated at 71%, and a clay content, acting as binder, at 14%. Despite limited load-bearing capacity, these lightweight adobes are suitable for current single-story constructions, while their hydrothermal properties classify them as excellent moisture regulators for occupants. In association with other bio-sourced materials such as starch-beet pulp bricks, Chalky Champagne adobes yield promising insulating properties, and meet the criteria defined by current energy standards.

Acute and chronic respiratory diseases impose a significant economic and health burden. Distal small airway assessment requires invasive procedures such as a bronchoscopy and bronchoalveolar lavage. The Particles in Exhaled Air (PExA) device provides a non-invasive means of assessing small airways; it captures distal airway particles sized around 0.5-7m and contains particles of respiratory tract lining fluid (RTLF) that originate during airway closure and opening. The PExA device can measure particle count and mass according to particle size. Subsequent capture of particles in a thin membrane enables application of various analytical methods to assess a broad range of biomolecules including phospholipids, proteins, inflammatory profile, and other metabolites to characterise inflammation and diseases processes such as asthma, chronic obstructive pulmonary disease, acute respiratory distress syndrome, lung cancer, and more recently acute infections such as COVID-19. PExA analysis provides a promising alternative to traditional investigative methods in the assessment, diagnosis, and management of respiratory conditions. By evaluating specific biomarkers in the RTLF associated with airway inflammation, PExA may offer a more accurate and comprehensive understanding of the molecular-level changes in the small airways of patients with acute and chronic lung diseases.

Fungi are ubiquitous and metabolically versatile. Their dispersion has important scientific, environmental, health, and economic implications. They can be dispersed through the air by the aerosolization of near surfaces or transported from distant sources. Here, we tested the contribution of local (scale of meters) versus regional (kilometers) sources by analyzing airborne fungal community by ITS sequencing around a copper mine in the North of Chile. The mine was the regional source, whereas soil and vegetal detritus were the local sources at each point. The airborne community was highly homogeneous in ca. 2,000 km2, impeding the detection of regional or local contributions. Ascomycota was the dominant phylum in the three communities. Soil and vegetal detritus communities had lower alpha-diversity, but some taxa had abundance patterns related to the distance to the mine and altitude. On the contrary, the air was compositionally even and unrelated to environmental or spatial factors, except for altitude. The presence of plant pathogens in the air suggests that other distant sources contribute to this region's airborne fungal community and reinforces the complexity of tracking the sources of air microbial communities in a real world where several natural and human activities coexist.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system adjustments and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs. generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO₂ emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and the Rest of PJM region leading to scenario-varying changes in the plant-level release of several air pollutants. Due to air pollution chemistry and transport and socio-demographics, these changes in turn give rise to a reduction of 10 to 182 PM_2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Scenarios that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, vulnerable populations—in both PA and Rest of PJM—benefit most in scenarios that prioritize plant closures in PA near Environmental Justice Areas. These results demonstrate the importance of considering cross-regional linkages and socio-demographics in designing equitable retirement strategies.

Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to landscapes, infrastructure, and human life. Triggered by factors such as intense precipitation, seismic activities, or volcanic eruptions, these events can cause extensive damage and endanger nearby communities. A comprehensive understanding of landslide characteristics, including spatio-temporal patterns, dimensions, and morphology, is vital for effective landslide-disaster management. Existing Remote Sensing approaches mostly use either optical or Synthetic Aperture Radar (SAR) sensors. Integrating information from both these types of sensors promises greater accuracy for identifying and locating landslides. This study proposes a novel approach, the ML-LaDeCORsat (Machine Learning-based coseismic Landslide Detection using Combined Optical and Radar Satellite Imagery), that integrates freely available Sentinel-1, Palsar-2, and Sentinel-2 imagery data, along with relevant spectral indices and suitable bands using machine-learning-based classification for coseismic landslide detection implemented in Google Earth Engine (GEE). The approach includes a robust and reproducible training and validation strategy. Using landslides from four different earthquake case studies, we demonstrate the superiority of our approach over existing solutions in coseismic landslide iden-tification and localization, providing a detection accuracy of 87-92%. ML-LaDeCORsat can be adapted to other landslide events (GEE script is provided). Transfer learning experiments proofed that our model can be applied to other coseismic landslide events without the need for additional training data. Our novel approach therefore facilitates quick and reliable identification of co-seismic landslides, highlighting its potential to contribute towards more effective disaster management.

Quaking aspen (Populus tremuloides Michx.) is an important deciduous species in western U.S. forests. Existing maps of aspen distribution are based on Landsat imagery and often miss small stands (<0.09 ha or 30 m²), which rapidly regrow when managed or following disturbance. In this study, we present methods for deriving a new regional map of aspen forests using one year of Sentinel-1 (S1) and Sentinel-2 (S2) imagery in Google Earth Engine. We assessed the annual phenology of aspen in the Southern Rockies and leveraged the frequent temporal resolution of S1 and S2 to create ecologically relevant seasonal composites. Additionally, we derived spectral indices and radar textural features targeting the canopy structure, moisture, and chlorophyll content. Using spatial block cross-validation and Random Forests, we assessed the accuracy of different scenarios and selected the best performing set of features for classification. Comparisons were then made with existing landcover products across the study region. The resulting map improves on existing landcover products in both accuracy (average F1-score = 93.1%) and detection of smaller forest patches. These methods enable accurate mapping at spatial and temporal scales relevant to forest management for one of the most widely distributed tree species in North America.

The scope of this work is to empirically check and prove the practical applicability of the Primordially Hydridic Earth (hereinafter PHE) concept for early exploration of the resources of naturally occurring hydrogen. With the PHE concept postulates interpreted within the local geological, tectonic, petrological and geophysical context, the reconnaissance plan, as well as the field exploration and data acquisition programs, were put together and implemented in the field. The results obtained from the surface (

The main source of electricity worldwide stems from fossil fuels, contributing to air pollution, global warming, and associated adverse effects. This study explores wind energy as a potential alternative. Nevertheless, the variable nature of wind introduces uncertainty in its reliability. Thus, it is necessary to identify an appropriate machine learning model capable of reliably forecasting wind speed under various environmental conditions. This research compares the effectiveness of artificial neural networks (ANN) and convolutional neural networks (CNN) in predicting wind speed across three locations in South Africa, characterised by different weather patterns. Empirical results show that CNN outperforms ANN in accurately forecasting wind speed under different weather conditions. This superiority is likely due to the inherent architectural attributes of CNNs, including feature extraction capabilities, spatial hierarchy learning, and resilience to spatial variability. These results could be useful to decision-makers in the energy sector.

Melioidosis is an endemic infectious disease caused by Burkholderia pseudomallei bacteria, which contaminates soil and water. To better understand the environmental changes that have contributed to melioidosis outbreaks, this study used spatiotemporal analyses to clarify the distribution pattern of melioidosis and the relationship between melioidosis morbidity rate and local environmental indicators (land surface temperature, normalised difference vegetation index, normalised difference water index) and rainfall. A retrospective study was conducted from January 2013 to December 2022, covering data from 219 sub-districts, with each exhibiting varying morbidity rate of melioidosis on a monthly basis. Spatial autocorrelation was determined using local Moran’s I, and the relationship between melioidosis morbidity rate and the environmental indicators was evaluated using geographically weighted Poisson regression. The results revealed clustered spatiotemporal patterns of melioidosis morbidity rate across sub-districts, with hotspots predominantly observed in the northern region. Furthermore, we observed a range of coefficients for the environmental indicators, varying from negative to positive, which provided insights into their relative contributions to melioidosis in each local area and month. These findings highlight the presence of spatial heterogeneity driven by environmental indicators and underscore the importance of public health offices implementing targeted monitoring and surveillance strategies for melioidosis in different locations.

Algeria, the main fire hotspot on the southern rim of the Mediterranean Basin, lacks complete fire dataset with official fire perimeters, and the existing one contains inconsistencies. Preprocessed global and regional burned area (BA) products provide valuable insights into fire patterns, characteristics and dynamics over time and space, and into their impact on climate change. Nevertheless, they exhibit certain limitations linked with their inherent spatio-temporal resolutions. To address the need for reliable BA information in Algeria, we systematically reconstructed, validated and analyzed a 40-year (1984–2023) BA product (NEALGEBA; North Eastern ALGeria Burned Area) at 30-m spatial resolution in the typical Mediterranean Ecosystems of this region, following international standards. We used Landsat data and the BA Mapping Tools (BAMTs) in the Google Earth Engine (GEE) to map BAs. The spatial validation of NEALGEBA, performed for 2017 and 2021 using independent 10-m spatial resolution Sentinel-2 reference data, showed overall accuracies > 98.10 %; commission and omission errors < 8.20 %; Dice coefficients > 91.90 %, and relative biases < 3.44 %. The temporal validation, however, using MODIS and VIIRS active fire hotspots, emphasized the limitation of Landsat-based BA products in temporal fire reporting accuracy terms. The intercomparison with five readily available BA products for 2017, by using the same validation process, demonstrated the overall outperformance of NEALGEBA. Furthermore, our BA product exhibited the highest correspondence with the ground-based BA estimates. NEALGEBA currently represents the most extensive and reliable time series of BA history at fine spatial resolution for NE Algeria, offering a significant contribution for further national and international fire hazard and impact assessments and acts as a reference dataset for contextualizing future weather extremes, such as the 2023 exceptional heat wave, which we show not to have led to the most extreme fire year over the last four decades.

This study investigates the mean annual water temperature trends at the confluence of the Sava and Danube Rivers, along with air temperature trends at the Belgrade meteorological station, spanning from 1956 to 2020. Results reveal a consistent increase in temperature across all three measuring stations, with the Danube experiencing a rise of 0.34°C/10 years, the Sava at 0.44°C/10 years, and Belgrade's air temperature increasing by 0.39°C/10 years. Employing the RAPS method, sharp rises in water temperature were pinpointed in 1989 for the Sava and 1990 for the Danube, while Belgrade's air temperature surge began in 1998. The highest intensity of air temperature increase within the recent period (1998-2020) was observed at the Belgrade observatory, reaching 0.76°C/10 years. Notably, the Sava exhibited a faster increase in water temperature over the last thirty years compared to the Danube. August marked the peak average water temperature for both rivers, while July recorded the highest average air temperature in Belgrade. Despite differing flow rates, both rivers exhibit similar hydrological regimes, with maximum flows occurring in April and minimum flows in August for the Sava, and October for the Danube. Seasonal temperature increases were most pronounced in summer, notably in August, with the smallest rises occurring during cold periods. Additionally, an inverse proportional relationship between mean annual water temperatures and discharges was observed at both river stations.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

This paper studies the maximum reliability of multi-hop relay UAV, in which UAV provides wireless services for remote users without direct communication link on the ground as a coded cooperative relay. In this paper, the analytical expressions of total power loss and total bit error rate are derived as reliability measures. Firstly, based on the environmental statistical parameters, a LOS probability model is proposed. Then the problem of minimizing the bit error rate of static and mobile UAVs is studied. The goal is to minimize the total bit error rate by jointly optimizing the height, elevation, power and path loss, and subject to the maximum allowable path loss con-straints, transmission power allocation constraints and UAV height and elevation constraints. At the same time the total path loss is minimized to achieve maximum ground communication cov-erage. However, the formulated joint optimization problem is non-convex and generally difficult to solve. Therefore, we decomposed the problem into two subproblems and proposed an effective joint optimization iteration algorithm. Finally, the simulation results are given, and the analysis shows that the optimal height of different reliability measures is slightly different, and using the mobility of UAVs can improve the reliability of communication performance.

Inhaled particulate matter (PM) is a key player in the millions of yearly deaths worldwide related to air pollution. The oxidative potential of PM provides an indication of its ability to promote an oxidative environment. When the human lungs are exposed to PM, the reactive oxygen species (ROS) generated in such oxidative environment, if excessive, may lead to cell damage via oxidative stress. Inflammation, endoplasmic reticulum stress, airway remodeling, and many different cell death modes (apoptosis, ferroptosis, pyroptosis, among others) can be triggered by oxidative stress via complex molecular pathways, which also involve the adaptive cellular response. But ROS can also directly interact with macromolecules such as proteins and lipids, as well as nucleic acids, having been reported to induce DNA damage and epigenetic modifications, which jeopardizes homeostasis. These facts have been extensively studied in in vitro models and confirmed in in vivo models.In this review, we delve beyond conventional assessments of airborne particles, discussing their oxidative potential and the PM-induced ROS-mediated cellular damage observed in in vitro models. The close link between oxidative stress and inflammation, and the manifestation of different cell death modes is highlighted by reviewing the latest literature. The effects of ROS on the balance of DNA damage and repair, carcinogenicity and epigenetics interplay are then analyzed. Finally, we expand on the latest reports on the antioxidants’ potential to counteract the deleterious effects of ROS, and disclose future perspectives for the topic.

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The early part of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns have been quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology-air pollution relationships have been visualised/interpretated on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs elevated PM10 pollution in the valley. Two local meteorological patterns, the hot-dry-northwesterly wind conditions and the hot-dry-calm conditions, were found most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of eastward migrating continental high pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere.

This research presents a comprehensive framework for efficiently generating forest fire datasets from Google Earth Engine data sources. The primary contribution of this work lies in providing a methodology to swiftly extract forest fire factors without the need for permissions or access to private datasets, rendering the dataset openly accessible and shared without barriers. Furthermore, given that the remote sensing data used is a global dataset, it can be applied in any region without restrictions. In this study, Peninsular Malaysia is chosen as a case study to demonstrate the framework's effectiveness. The generated dataset includes essential variables including the climate and environment, landcover, topography, and anthropogenic factors facilitating the analysis of fire occurrences. The methodology empowers data scientists, enabling them to leverage their analytical skills on the extracted dataset without requiring specialized remote sensing knowledge. Additionally, this study also showcases the adoption of large language models, specifically GPT-4 with the Noteable plugin, as a tool for conducting preliminary analyses on the generated dataset. Sample analyses reveal that several key features, including the KBDI, LST, PDSI, climate water deficit, and precipitation, significantly impact forest fire occurrences in Peninsular Malaysia. Despite the successful application of the GPT-4 with Noteable plugin, certain limitations and challenges are identified, highlighting the necessity for further validation of the tool's applicability and limitations. This study encourages future research to (1) adopt the proposed framework in other regions, (2) explore more detailed analyses encompassing all variables, and (3) leverage machine learning for advanced forecasting.

The effects of rare earth Ce on the microstructure and properties of cast pure copper were investigated through thermodynamic calculations, XRD analysis, mechanical testing, metallographic microscopy, and scanning electron microscopy (SEM). The experimental results demonstrate that the reaction between rare earth Ce and oxygen as well as sulfur in copper exhibits a significantly negative Gibbs free energy value, indicating a strong thermodynamic driving force for deoxidation and desulfurization reactions. Ce is capable of removing trace amounts of O and S from copper. Moreover, the maximum solid solubility of Ce in Cu falls within the range of 0.009% to 0.01%. Furthermore, Ce can refine columnar grains while enlarging equiaxed grains in as-cast copper.Upon addition of rare earth Ce, the tensile strength increased by 8.45%, elongation increased by 12.1%, and microhardness rose from 73.5HV to 81.2HV-an increase of 10.5%. Overall, rare earth Ce has been found to enhance both the microstructure and mechanical properties of cast pure copper.

Point defects induced by doping rare earth elements RE (Nd, Er) into the magnesium oxide host were investigated by classical atomistic simulations utilising the General Utility Lattice Program (GULP). Formation and association energies were calculated for the potential defect structures. Both isolated defects and defect complexes were considered. The most energetically favourable structures of defect complexes were found for rare earth doped and Li co-doped systems. The correlation between the association energy and the structure of the defect complex was investigated. The influences of Li were revealed with respect to energy and structure. The simulation results contribute to the understanding of the point defects of doped MgO and how Li influences the doping of rare earth elements in the MgO host.

Atmospheric turbulence characteristics are essential in determining the quality of astronomical images and implementing adaptive optics systems. In this study, the vertical distributions of optical turbulence at the Peak Terskol observatory (43.27472 ° N 42.50083 ° E, 3127 m a.s.l.) using the Era-5 re-analysis and scintillation measurements are investigated. For the closest reanalysis grid node to the observatory, vertical profiles of the structural constant of the air refractive index turbulent fluctuations Cn2 were obtained. The calculated Cn2(z) vertical profiles are compared with the vertical distribution of turbulence intensity obtained from tomographic measurements with Shack-Hartmann sensor. The atmospheric coherence length at the location of Terskol Peak was estimated. Using combination of atmospheric models and scheme paramaterization of turbulence, Cn2(z) profiles at Mt. Kurapdag were obtained. The values of atmospheric coherence length at the Peak Terskol are compared with estimated values of this length at the ten astronomical sites including Ali, Lenghu and Daocheng.

Non-exhaust road transport emissions in cities contribute to poor air quality and create health impacts. This paper presents a new study of the emitted particles due to the tyres-road wear ‘TRWP’ in real driving and gives their emission factors EF. The most frequently observed particles were &lt;1 µm; followed by particles size between [1µm, 4µm] for urban, suburban and highway areas. These particle sizes are well-known to have a higher degree of toxicity. An overall analysis of all the measured pollutants gave EF equal to 30 10+12 #/km and 35 10+12 #/km, respectively for urban and sub-urban areas; and 5 10+12 #/km on highway. The analysis of the 19 most emitted pollutants, taken individually, showed that their EFs ranged from 0.003 to 18.142 10+12#/km. The obtained EF are above the value of the Euro standard for vehicles, but are below the values for vehicles unequipped with a particle filter. Significant test analysis confirmed that inertia of chemical pollutants is homogeneous. EF assessment of the PM10 and PM2.5 emitted is equal to 1.45 mg/km and 0.35 mg/km respectively. These results should contribute to the emergence of future regulations of non-exhaust emissions and should help to analyse the exposure-impact relationship to TRWP.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

In urban areas like Chicago, daily life extends above ground level due to prevalence of high-rise buildings where residents and commuters live and work. This study examines the variation in fine particulate matter (PM2.5) concentrations across building stories. PM2.5 levels were measured using PurpleAir sensors, installed between April 8 and May 7, 2023, on floors one, four, six, and nine of an office building in Chicago. Additionally, data were collected from a public outdoor PurpleAir sensor on the fourteenth floor of a condominium located 800 meters away. Results show that outdoor PM2.5 concentrations peak at 14 meters height, then decline by 0.11 μg/m3 per meter elevation, especially noticeable from midnight to 8 AM under stable atmospheric conditions. Indoor PM2.5 concentrations increase steadily by 0.02 μg/m3 per meter elevation, particularly during peak work hours, likely caused by greater infiltration rates at higher floors. Both outdoor and indoor concentrations peak around noon. We find that indoor and outdoor PM2.5 are positively correlated, with indoor levels consistently remaining lower than outside levels. These findings align with previous research suggesting decreasing outdoor air pollution concentrations with increasing height. The study informs decision-making by community members and policymakers regarding air pollution exposure in urban settings.

Two heating surfaces with longitudinal fins are located within the closed channel inside the housing made of thermal insulation material. The air flow inside the channel was carried out by an axial fan. The heating of the fins is established by using two positive temperature coefficient heating elements (PTC). Air flows circularly from one finned surface to another, and after reaching the required temperature, it leaves the housing. In the heating system conceived in this way, a methodology based on transient thermal irreversibility of heating sources and circular air flow has been established. Volumetric air flow and circulation time within the channel were varied. The total entropy generated does not include hydraulic irreversibility, but transient thermal irreversibility of the air and heat sources. For conducting analytical modeling, the temperature of the PTC heater was considered constant at 423K and 473K. Volumetric air flow varied in the interval from 0.00001m3s-1 to 0.00006m3s-1. The experimental determination of the transient thermal entropy was performed at a much higher air flow rate of 0.005m3s-1 inside the closed channel. Due to the continuous increase in air temperature, the temperatures of both PTC heaters increased within the examined time interval of 300s. According to experimental testing, the total transient thermal entropy of the described heating system has a minimum after 175s from the start of the circular heating of the air. The minimum of transient entropy also implies the optimal time of channel opening and exit of heated air.

There are several challenges on how to attain energy efficiency while maintaining balance among factors affecting energy consumption such as power rating and temperature setpoints of cooling units, room temperature and humidity, and indoor air quality (IAQ). A real-time energy and IAQ monitoring system were installed in an educational building to profile the operational power consumption of inverter-based air condition unit (ACU) installed in each room. Polynomial curve and neural fitting regression analysis were applied to the real-time power consumption, indoor temperature and humidity, and carbon dioxide (CO2) level data. The derived models were able to provide the stabilizing indoor thermal and air conditions of the room to reach steady state ACU power consumption. These collected data and calculated parameters can be used to define rules in automating control of cooling appliances for an efficient energy utilization. The regression approaches, using real-time data, have determined the influence of indoor heat conditions and carbon dioxide levels on ACU power consumption. These parameters were utilized to establish consistent values for temperature, humidity, and carbon dioxide levels under stable settings of inverter-based air conditioning units.

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, the study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation R² = 0.879, compared to Landsat R² = 0.663. The application of supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations, manifested as a 70.3% increase in urban land, concurrently with a decrement in vegetative cover, especially 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09°C and 2.16°C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30°C and 2.24°C, with the bare land class showing the highest fluctuation 2.46°C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p &gt; 0.05 for both monthly and annual data sets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as warmest classes with 39.51°C, 38.20°C and water by 35.96°C and dense vegetation 35.52°C, sparse vegetation 37.71°C as coldest, a trend consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects.

Objectives: Recently, desert dust in Europe has been recognized as a cardiovascular health problem. In Spain, desert dust inflows in recent years have been associated with worsening air quality. The present study examines whether desert dust events are related to the incidence of acute coronary syndrome (ACS) in patients under 55 years of age. Methods: Data from 2416 consecutive patients admitted to a tertiary hospital due to ACS were prospectively analyzed. A case-crossover time-stratified design using Poisson conditional regression models was applied to estimate the impact of desert dust events involving particulate matter concentrations of aerodynamic diameter < 10 μm (PM10) on the incidence of ACS. Results: Desert dust intrusion on days 0 to 5 after ACS onset showed no significant association with the incidence of ACS in patients under 55 years of age. The incidence rate ratios of PM10 concentrations 1, 2, 3, 3, 4 and 5 days before ACS onset (for changes of 10 µg/m3) were 1.02 (95% CI 0.97-1.1; p = 0.41), 1.01 (95% CI 0.96-1.07; p = 0.66), 0.99 (95% CI 0.94-1.05; p = 0.78), 0.96 (95% CI 0.9-1.02; p = 0.18) and 0.97 (95% CI 0.91-1.04; p = 0.41). Conclusions: Our findings suggest that desert dust is unlikely to be related to the incidence of premature coronary heart disease.

This article introduces a novel payload structure, which has been experimentally proven to have smaller impact force while the carried internal electronics remains intact. The study describes in details how materials and geometric structures were chosen based on information analysis. It is clarified how possible geometric structures and materials can be chosen to yield optimal efficiency. Finite element method simulations were carried out to investigate the mechanical properties of several geometric structures, which has led to the dodecahedron form. For the frame, Polylactic Acid were chosen as an optimal material. A low air pressure test for parts of the structure, and also the whole structure were carried out with successful results. Drop tests, with force measuring sensors and high speed videos, were carried out for measuring and comparing the maximal impact force of classical payloads and the novel one. Laboratory and real life tests demonstrated that the developed new structure is safer and it is applicable.

Background: Asthma is a widespread chronic respiratory disease that poses a significant public health challenge. The current study investigated the associations between air pollution and asthma severity among individuals residing near the Sohar industrial port (SIP) in Oman. Despite the presence of multiple major industrial complexes in Oman, limited knowledge regarding their impact on respiratory health is accredited. Hence, the primary objective of this study is to offer valuable insights into the respiratory health consequences of industrial air pollution in Al Batinah North. Methods: The state health clinics' records for patient visits related to asthma were collected for the timeframe spanning 2014 to 2022. Exposure was defined as the distance from SIP, Majan Industerial Area (MIA) and Sohar Industerial Zone (SIZ) to determine high, intermediate, and low exposure zones (12 km, respectively). Exposure effect modifications by age, gender, and smoking status were also examined. Results: The conducted cross-sectional study of 410 patients (46.1% males and 53.9% females) living in over 17 areas around SIP revealed that 73.2% of asthmatics were under 50 years old, with severity significantly associated with closeness to the port. Risk ratios were estimated to be (RR:2.42; CI95%: 1.01–5.78), (RR:1.91; CI95%: 1.01–3.6), and (RR:1.68; CI95%: 0.92–3.09) for SIP, MIP and SIZ areas, respectively, compared to the control area. Falaj Al Qabail (6.4 km) and Majees (6 km) had the highest number of asthma patients (N. 69 and N. 72), and highest percentages of severe asthma cases among these patients (28% and 24%) with significant risk ratios (RR:2.97; CI95%: 1.19–7.45 and RR:2.55; CI95%: 1.00–6.48), correspondingly. Moreover, severe asthma prevalence peaked in the 25-50 age group (RR:2.05; CI95%: 1.26–3.33), and this linkage between asthma and age was much more pronounced in males than females. Smoking and exposure to certain contaminant (dust and smoke) increased also the risk of severe asthma symptoms, but their effects were less important in the high risk zone, suggesting much more important risk factor. A neural network model accurately predicted asthma risk (94.8% accuracy), with proximity to Sohar Industrial Port as the most influential predictor. Conclusion: The study highlights the High asthma burden near Sohar Industrial Port, linked to port proximity and smoking and wind direction as major risk factors. These findings inform vital public health policies to reduce air pollution and improve respiratory health in the region, prompting national policy review.

Two coupled climate models which participated the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0) and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3), were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air-sea heat flux, radiation penetration and absorption, melt ponds, ice-ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis product from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes of spatial pattern of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have potential for broad application in climate models, especially for those with underestimated SIT.

Rare earth elements (REEs) are a type of new material resources, which have attracted significant attention in recent years. REEs have emerged as essential metals in modern-day technology due to their unique functions. Long-term large-scale mining and utilization of rare earths have caused serious environmental pollution and constitutes a global health issue, which raised concerns about human health safety. However, the toxicity profile of suspended particulate matter of REEs in the environment interacts with the human body in remain largely unknown. Studies have shown that REEs can enter the human body through a variety of pathways, leading to a variety of organ and system dysfunctions through changes in genetics, epigenetics, and signaling pathways. Through an extensive literature search and critical analysis, we provide a comprehensive overview of the available evidence, identify knowledge gaps, and make recommendations for future research directions.

Studies on Medical Geology have up till recently tended to emphasise the harmful effects of geological material and processes. This is perhaps justifiable, given the realisation that many environmental diseases could have causal links with some geo-environmental variables as co-factors, making such studies extremely valuable in the improvement of diagnoses and therapy. However, this review aims to show that in addition to the high value of such research, studies conducted on the beneficial properties of Earth materials also have considerable merit, given their enormous potential for assuaging a wide range of environmental health disorders. For instance, certain geological materials including clay minerals contain active substances that show considerable promise in various applications such as pharmaceutical formulations, aesthetic medicine, and indigenous medicine. This review synthesises current knowledge of how certain geological materials can be exploited in formulating remedies for some human health problems. Reports of the therapeutic uses of clay minerals, zinc oxide (zincite), zeolite, and kaolin are appraised. The review shows that ancient and contemporary use of geological materials such as clay minerals have played crucial roles in the treatment of several human diseases, with recent and ongoing research revealing further development in these applications. Well strategised clinical trials using available resources could give impetus to further research in elucidating the potential of various geomaterials as innovative clinical remedies for some human diseases and infections as well as aid the proper scientific documentation of their natural uses.

To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load aggregation modelling of air conditioning and electric vehicles was conducted, and the complementarity of the power consumption behaviour of different types of flexible loads was used to improve the responsiveness of the load aggregator. Second, considering demand-side responses and taking into account the interests of both supply and demand, the load fluctuation and peak-to-valley difference on the network side are reduced, and a flexible load double-layer optimization model incorporating the peak-to-valley smoothing benefit is established. Finally, the effectiveness of the proposed optimization model is verified by using the KKT condition and the big M method to evaluate this two-layer optimization problem as a single-layer optimization problem. Comparative examples demonstrate that the proposed two-layer optimization method can improve the revenue of the distribution network operators and the load aggregators by using the complementary nature of the load response characteristics of electric vehicles and air conditioners. Moreover, the proposed method can effectively reduce the load peak-to-valley difference and load fluctuation of the distribution network by introducing the peak-to-valley smoothing benefit model.

The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedure for color detection and quantification (including calibration processes), and their application to different target gases. The performance of the methods - whenever available - is presented regarding the analytical specifications selectivity, sensitivity, and limit of detection in comparison with other color evaluation methods of passive samplers. Practical aspects like requirements of instrumentation and ease of use will be outlined in view of the potential employment in education and citizen science projects. In one section of the review the inconsistent terminology of passive and diffusive sampling is discussed in order to clarify the distinction of information obtained from the uptake of the passive samplers between gas-phase concentration and the accumulated deposition flux of gaseous analytes. Colorimetric gas sensors are included in the review when applied in passive sampling configurations and evaluation is performed with smartphone-based color evaluation. Differences in the analytical procedures employed after the passive sampling step and prior to the detection of the colored compounds are also presented.

Background: The study aimed to investigate the association between environmental tobacco smoke exposure and the risk of wheezing among rural and urban preschool children in Mpumalanga province, South Africa, an area associated with poor air quality. Methods: In this study, parents/caregivers of preschool children (n=3145) completed a modified International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. Data were analysed using multiple logistic regression models. Results: The overall prevalence of Wheeze ever was 15.14%, with a higher prevalence in urban pre-schoolers than rural pre-schoolers (20.71% vs 13.30 %, P<0.000). Moreover, the total prevalence of asthma ever was 2.34%. The prevalence was greater in urban pre-schoolers than in rural pre-schoolers (3.92% vs 1.81%, P<0.001). In the final adjusted model, both urban and rural area children who lived with one or more people who smoked in the same household (WE: OR 1.44, 95% CI 1.11-1.86) (CW: OR 2.09, 95% CI 1.38-3.16) and (AE: OR 2.49, 95% CI 1.12-5.54) were found to have an increased likelihood of having Wheeze Ever, Current Wheeze and Asthma Ever as compared to those who lived with non-smokers. Conclusions: The implementation of smoking limits and prohibition is crucial in areas that are frequented or utilized by children. Hence, it is imperative for healthcare providers to actively champion the rights of those who do not smoke within the society, while also endorsing legislative measures aimed at curtailing the extent of tobacco smoke exposure.

It is concerning that Cameroon's urban centers are experiencing an alarming rise in air pollution as a result of urbanization, population growth, industrial activity, and transportation emissions. We examined the causes, health impacts, research methodology, case studies, and government measures to address the urgent issue of air pollution in Cameroon's urban regions. We have emphasized how Cameroon's air pollution levels have significantly increased as a result of causes like population expansion, urbanization, industrial emissions, and automobile exhaust A thorough discussion of the negative health impacts of extended exposure to air pollution is included, with special attention to the sensitivity of the old and young. These effects include respiratory disorders, cardiovascular ailments, and early mortality. We emphasized the pressing need for all-encompassing strategies to address air pollution, such as increased public awareness campaigns, stronger emissions regulations, the development of renewable energy sources, and better waste management. The techniques employed in studies on air pollution, like as epidemiological research and air quality monitoring, are also explained to provide light on the unique health dangers that Cameroonian urban dwellers must contend with. We emphasized in our conclusion the significance of joint efforts by legislators, medical professionals, and the general people to reduce air pollution and protect public health in Cameroon in order to create a cleaner and healthier future. In order to protect public health in the future, it is imperative that Cameroon's air pollution be addressed.

The hospital indoor environment plays a significant role in shaping the microbial exposures that humans encounter. Resistance to antibiotics is one of the mechanisms employed by bacteria to develop resilience against stress in indoor environments. The extensive usage of antibiotics has been a key factor in driving changes in the ecological function of antibiotic resistance genes (ARGs) and their acquisition by pathogenic bacteria. By integrating the 16S rRNA Illumina sequencing and high throughput-qPCR approaches with water and air dust samples across seven departments at Peking University Shenzhen Hospital, China, this study yielded intriguing findings regarding the department-specific variation, transmission, and correlation of bacteria, ARGs and MGEs within the hospital indoor environment. One notable observation was that the seasonal variation played a vital role in shaping the bacterial composition in the overall hospital indoor environment across seven studied departments. Nevertheless, a similar significant seasonal impact was only observed in the blood test room and emergency departments, rather than in the other five departments. Another intriguing finding was the correlation between ARGs and MGEs abundance. This correlation was evident in the overall hospital indoor environment, which was conversely not found in the emergency, pneumology and gynecology departments. Additionally, while there was no significant relationship that occurred between bacterial communities and ARGs/MGEs within the hospital, the gynecology department demonstrated a close link between bacterial communities and the presence of ARGs/MGEs. Notably, the gynecology department also stood out as an important source of bacteria and ARGs/MGEs for other departments. This study underscores the need for careful surveillance and monitoring of antibiotic resistance, particularly in Legionella spp. in man-made water systems. The findings also show the importance of monitoring and understanding the genetic elements such as Tp614 involved in gene transfer and recombination, as well as their impact on antimicrobial treatment efficacy.

Environment pollution is the major problem for all the sectors. In environment pollution there are different types of pollution is included such as air pollution, water pollution, soil pollution etc. In these types of pollution most of it is air pollution. There are many reasons for pollution of air. Human advance in science but one of the major draw backs of science is the pollution of air rapidly. Air pollution is injurious to health. Every year a large number of people died for the effects of air pollution. It can be improved in many ways among these ways technology upgradation plays a major role here. There are various method that prevent air pollution. Many researchers tried and is trying to prevent the air pollution in many ways. In this review paper I summarise the existing research on different ways for preventing air pollution in addition I will discuss the gaps and future aspect on this topic.

In light of the critical and emerging global challenge posed by the increasing frequency and severity of heatwaves in recent decades, this study demonstrates a practical and robust workflow that bridges the gap in understanding how the effective integration of remote sensing data with ground-based observations can facilitate a comprehensive assessment of spatiotemporal heatwave patterns and trends in the central region of Thailand. This research transcends traditional methods, utilizing air temperature (Tair) and satellite-derived land surface temperature (LST) data from 1981 to 2019. Results exhibit that an analysis of Tair indicates increasing daytime heatwaves in peri-urban areas, with significant trends in heatwave number (HWN), heatwave frequency (HWF), and heatwave duration (HWD), heatwave amplitude (HWA) rises in urban settings while nighttime heatwaves significantly intensify in rural locales. Notably, LST trends reveal varied patterns, with peri-urban areas showing marked daytime increases in heatwave magnitude (HWM), HWA, and HWF. Correlation analysis (p=0.05) highlights strong daytime associations between Tair and LST in rural (HWN, HWF, HWD, r&gt;0.90) and peri-urban (HWM, HWA, r&gt;0.65) regions. Overall, this study advances approaches to the adaptable measurement and spatial-temporal pattern of heatwave-related risk areas, providing insights for decision-makers to develop sustainable practices and strategies for climate change adaptation.

This study aims to reveal the revolutionary Gamma Distribution Manifold (GDM) info-geometric analysis combined with potential Gamma distribution (GD) applications to advance Satellite Earth Observations (SEOs). An exposition of the GDM Fisher Information Matrix (FIM) was undertaken, together with the analytic investigation of the existence of FIM’s inverse. The derivation of GDM’s Geodesic Equations (GEs) is undertaken. The solution of the obtained Geodesic Equations is optimally complicated, and it provides more extensions to numerous open problems. Notably, the current paper provides a first-time unification between three multi-interdisciplinary fields, namely, information geometry theory, probability theory, and Satellite earth observations. Looking at the other side of the coin, the provided revolutionary approach in this current work reports the significant impact of info-geometric analysis on the probabilistic dynamics as well as the influential role of information geometry on satellite and space industry. This poses numerous open issues that initiates a new form of contemporary unification between these inter-disciplinaries to discover another visionary thinking out of traditional statistical frames. In other words, refraining ourselves from using classical statistical frames of thinking and delving into a new info-geometric vision of statistical distributions as well as examining real life applications of information geometry to advance satellite earth observations. The curtain is drawn on this paper by providing several challenging open problems in combination with a concluding remark and the next phase of research.

Decarbonization of air mobility requires the decarbonization of its energy. While biofuels will play an important role, other low carbon energy carriers based on electricity are considered: battery electrification, liquid hydrogen (LH₂) or eFuel, a hydrogen-based energy carrier. Each energy carrier has its own conversion steps and losses and its own integration effects with the aircraft. These combinations lead to different energy requirements and must be understood to compare their cost and CO₂ emissions. Since they are all electricity-based, this study compares these energy carriers using the well to rotor methodology when applied to a standard Vertical Take-Off and Landing (VTOL) air mobility mission. This novel approach allows one to understand that the choice of the energy carrier dictates the propulsive system architecture, leading to integration effects with the aircraft which can significantly change the energy required, from 400 to 2665 kWh for the same mission. These deviations lead significant differences in CO₂ emissions and costs. Battery electrification is impacted by the battery manufacturing but has the lowest electricity consumption. It is an optimum solution but only until the battery weight can be lifted. In all scenarios eFuel is more efficient than LH₂. We conclude that carrying the most efficient molecule in an aircraft pays the extra energy cost spent on the ground. Finally, we found that for each of these energy carriers, it is the electricity carbon intensity and price which will dictate the cost and CO₂ emissions of an air mobility mission.

In this study, we adopt a unique approach by utilizing the responses of human autonomic systems to gauge the abundance of pollutants in inhaled air. Air pollution has numerous impacts on human health on a variety of time scales. This study uses biometric observations of the human autonomic response on the second timescale to investigate how the human body autonomically responds to inhaled pollutants in microenvironments, including particulate matter. PM1 and PM2.5, carbon dioxide (CO2), nitrogen dioxide (NO2), and nitric oxide (NO) on small temporal and spatial scales. These pollutants are exemplars of the wider human exposome. We compare two experimental approaches that use a similar methodology, employing a biometric suite to capture the physiological responses of cyclists and sensors to monitor the pollutants in the air surrounding them. We employ machine learning algorithms to estimate the levels of these pollutants and decipher the body’s automatic reactions to them. We observed high precision in predicting PM1, PM2.5 and CO2 using a limited set of biometrics from participants. Although the predictions for NO2 and NO were reliable at lower concentrations, the precision varied throughout the data range. This discrepancy suggests the potential to improve our models with more comprehensive data collection or advanced machine learning techniques.

Air pollution, climate change and global warming show direct linkage. Introduction - Background: Research in the field has proposed and demonstrated their link to increased allergenicity in plants, leading to increased allergic diseases. Allergen patterns are changing in response to climate change. Across Europe, up to 12% of the population suffers from allergic diseases (bronchial asthma and allergic rhinitis) caused by the pollen grains. The medical costs of these types of allergies are enormous and are increasing with the spread of common ragweed - Ambrosia artemisiifolia* in Europe. In practice, more and more patients are turning to allergists. Methods: Based on these data, the research aims to identify safety measures and specific legislation to control and eradicate common ragweed in the countries most affected by the spread of this plant in Europe, increase in population exposure in countries affected by the presence of common ragweed and the socio-economic impact of allergic rhinitis and bronchial asthma at European level.[1][2] Our database search did not reveal any other research that has addressed this topic to date. Results: This research identifies specific legislation to the countries most affected by the spread of this plant pollen grains at European level, changes in allergen patterns and monitoring/safety eradication measures decided by local authorities, and data on the spread of common ragweed over the last two decades, costs per treatment, increased allergic rhinitis and bronchial asthma morbidity in the most affected areas. Conclusions: At European level, there are no universally valid models for eradicating this weed. Various methods can be used to limit the spread of common ragweed and its pollen production (e.g. mowing once or twice a year of overgrown land, ploughing, chemical control, public information, etc.). Local and regional cooperation should be considered essential to promote phytosanitary &amp; safety measures and exchange of information on methods to identify and manage the spread of common ragweed. Unified legislation at European level would help all affected countries; reduce morbidity from respiratory allergic diseases and the costs of treating these diseases.

For the last two decades, an increasing demand for low-cost adsorbents for drinking water treatment has been challenged in the rural areas of developing countries that have problems with arsenic (As) contamination. In this work, spent bleaching earth (SBE), a residual material that is formed during the process of refining vegetable oil, has been utilized to prepare the new magnetic adsorbent Fe-SBE/C by modifying its surface area through calcination and co-precipitation with iron. The experimental results demonstrate that Fe-SBE/C exhibits a substantial adsorption capacity towards both arsenite (As(III)) and arsenate (As(V)). Optimal pH conditions were found to be pH 10 for As(III) and pH 3 for As(V), resulting in adsorption percentages of 76.7% and 94.1%, respectively. Other experimental parameters such as calcination conditions, adsorbent dosage, iron-loading ratio, and the presence of co-existing ions were thoroughly investigated. The kinetic study revealed that the adsorption processes follow the Elovich and intraparticle diffusion models, suggesting a combined adsorption mechanism of boundary layer control and chemisorption. Furthermore, the isotherm followed the Langmuir model with a maximum adsorption capacity of 202.61 μg g-1 for As(III) and 187.61 μg g-1 for As(V). Through thermodynamic analysis and reinforcement by activation energy data, this research validates that the observed adsorption process is indicative through chemisorption. The regeneration study revealed the potential for multiple cycles of arsenic removal, highlighting the practical applicability of Fe-SBE/C in environmental contexts. In conclusion, the findings of this study underscore the efficacy of Fe-SBE/C in arsenic removal and present it as a promising and environmentally friendly solution for mitigating arsenic pollution.

Heterometallic rare-earth clusters have garnered much attention because of their interest-ing solid-state structures and versatile applications in catalysis and material and polymer chemistry over the last four decades. Particular interest is rare earth–transition metal co-ordination compounds that behave as single-molecule magnets (SMMs) because of their potential use in information storage, spintronic devices, and magnetic refrigeration sys-tems. Another implementation involves using lanthanide clusters in luminescent-based sensing for environmental protection and security screening or in photocatalytic energy conversion reactions. Heterometallic rare earth complexes offer the promise of catalytic performance of many organic reactions due to their high oxygenophilicity, Lewis acidity, high coordination numbers, and ability to change the coordination environment quickly. Therefore, they are commonly applied as catalysts in asymmetric synthesis, oxidation re-actions, and CO2 conversions or as initiators in ring-opening polymerization and copoly-merization of cyclic monomers. They are also attractive single-source molecular precur-sors for functional inorganic materials. This review focused on the unique features and properties of the heterometallic rare earth complexes, which are closely correlated with their molecular structure. Our summary is a valuable resource, providing researchers with an insightful exploration of the heterometallic rare-earth complexes that demonstrated multimetallic synergy and cooperativity effects in various applications.

The boosted interest in the use of rare earth elements (REEs) in modern technologies had also increase the necessity of their recovery from various sources, including raw materials and wastes. Though Hydrometallurgy plays a key role in these recovery processes, some drawbacks (apparent or not) of these processes, had led to the development of a more environmental friendship subclass named Solvometallurgy, in which non-aqueous solvents substituted to the aqueous media of the hydrometallurgical processing. The non-aqueous solvents chosen for these usages are, besides ionic liquids (ILs), the so-named Deep Eutectic Solvents (DEEs). The utilization of DEEs included the leaching of REEs from the different sources containing them, and also in the separation-purification steps necessary for the yielding of these elements, normally as oxides or salts, in the most purified form. This work reviewed the most recent literature (2023 year) about the utilization of deep eutectic solvents in the recovery of REEs from various sources, and in the coupling of these two (DESs and REEs) to derived compounds to be used in other fields.

The ongoing expansion in volume, velocity and variety of geospatial data has stimulated the development of artificial intelligence applications and associated online cartographic visualizations. In this context, the cartographic communication through peer-reviewed media evolved to incorporate Findability, Accessibility, Interoperability and Re-usability (FAIR) principles. In this paper, we review the functionalities proposed by current international peer-reviewed media for accessing, exploring and re-using geospatial data, and situate them on a diagram conceived for peer-reviewed cartography in the artificial intelligence era. We then present an overview of the cartographic infrastructure and workflow currently available in the Terra Digitalis journal for the online publication of massive spatiotemporal data. This free and opensource based solution allows a smooth integration, from data submission to final peer reviewed publication, of dynamic, interactive 2D and 3D maps. As a proof of concept, we present two maps derived from massive spatiotemporal data, related, respectively, to a climate numerical model (raster data) and a bike sharing system’s origin-destination dataset (vector data). We argue that the combination of technologies used in the journal provides an efficient and low-cost solution, unmatched by other publication media, to boost the accessibility and FAIR principles for geospatial big data.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

In the current work, the stable queueuing system's Generalised Z-Entropy (GZE) of Rényian formalism is examined in its fractal dimension. Notably, fractal dimension’s resulting behaviour that corresponds to the GZE parameters is examined through numerical tests. This research makes a substantial generalization in the literature by fusing fractal geometry and information theory to shed light on how entropy and complexity interact. More fundamentally, the significant role of fractal dimension to advance Big Data Analytics(BDAs) is highlighted. Closing remarks combined with open problems and the next phase of research are provided.

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.

Estimating the infection risks in indoor environments comprises the assessment of the behavior of virus-laden aerosols, i.e. spreading, mixing, removal by air purifiers etc. A promising experimental approach is based on using non-hazardous surrogate aerosols of similar size, e.g. salt particles, to mimic the virus aerosol behavior. This manuscript addresses the issue how a successful transfer of such experiments can be accomplished. Corresponding experiments in two very different environments, a large community hall and a seminar room, with optional use of air purifiers in various constellations were conducted. While high particle concentrations are advantageous in terms of avoiding influence of background aerosol concentrations, it is shown that appropriate consideration of aggregation and settling are vital to theoretically describe the experimentally determined course of particle concentrations. A corresponding model equation for a well-mixed situation is derived and the required parameters are thoroughly determined in separate experiments independently. It is demonstrated that clean air delivery rates (CADR) of air purifiers determined with this approach may differ substantially from common approaches not explicitly taking into account aggregation.

Cuba is struggling with a growing environmental problem: the uncontrolled spread of the allochthonous weed species marabou (Dichrostachys cinerea) throughout the country. Over the last 70 years, marabou has become a formidable invasive species that poses a threat to Cuban biodiversity and agricultural productivity. In this paper, we present a free and affordable method for regularly mapping the spatial distribution of the marabou based on the Google Earth Engine platform and ecological surveys. To test its accuracy, we develop an 18-year analysis (2000–2018) of marabou dynamics using the Valle de los Ingenios, a Cuban UNESCO World Heritage Site, as an experimental model. Our spatial analysis reveals clear patterns of marabou distribution and highlights areas of concentrated growth. Temporal trends illustrate the dynamic nature of the species, identifying periods of expansion and decline. In addition, our system is able to detect specific, large-scale human interventions against the marabou plague in the area. The results highlight the urgent need for remedial strategies to maintain the fragile balance in the region.

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

The air transport industry has experienced important transformations over the last decades, despite its continuous global trend of growth. After air transport liberalization process, the present market situation depicts a reduced number of large hub & spoke airlines and an important number of so-called low-cost carriers (LCC). One may wonder why airlines that were once thriving and profitable before liberalization have disappeared, some even recently amid an expansion in demand. To answer that question and others related to it, this paper proposes a management model focused on the airline business, putting in relation the main variables defining the business behavior of an airline. The lessons learned from the past, and the solutions gathered from the model related with, will provide a sound basis to address the new challenges for the next years to come, as it is the case of the new environmental regulations focused on the air transport decarbonization.

Cooling fans are one of the critical components of air-forced (AF) dry-type transformers for regulating internal temperatures. Therefore, effective malfunction detection is crucial to maintain the transformer temperature within an acceptable range and prevent overheating. Regular maintenance occurs periodically and issues with cooling fans may arise between maintenance periods, leading to prolonged operation under malfunctioning conditions and potential failures. In addition, utilities typically have online information about whether a fan works or not without providing information about cooling fan malfunctioning circumstances. To address these challenges, this study proposes learning-based online monitoring techniques to detect malfunctions in AF transformer cooling fans. Random forests (RFs) and convolutional neural networks (CNNs) are developed to classify the audio signals from cooling fans into normal and malfunctioning classes. Unlike RFs, which require separate feature extraction, CNNs are trained based on spectrogram images derived from audio signals. Thus, various time-frequency techniques are utilized for feature extraction in RFs. Besides, multiple data augmentation techniques are employed to enhance the dataset size and diversity. Algorithmic performance is optimized through hyperparameter tuning and classifier threshold adjustment. Simulations reveal that CNNs outperform RFs, whereas the latter provides superior interpretability of acoustic features compared to the former.

The aim of this work is to provide a full description of how air temperature and solar radiation induce changes in the land cover over an Antarctic site. We use shortwave broadband albedo (albedo integrated in the range 300-3000 nm) from a spaceborne sensor and from field surveys to calculate the monthly relative abundance of landscape units. Field albedo data were collected using a portable albedometer over seven landscape units: clean fresh snow; clean old snow; rugged landscape composed of dirty snow with disperse pyroclasts and rocky outcrops; dirty snow; stripes of bare soil and snow; shallow snow with small bare soil patches; bare soil. MODIS MCD43A3 daily albedo product was downloaded using the Google Earth Engine API from the 2000-2001 season to the 2020-2021 season. Each landscape unit was characterized by an albedo normal distribution. The monthly relative abundance of the landscape units were calculated by fitting a linear combination of the normal distributions to the histogram of the MODIS monthly mean albedo. The monthly relative abundance of the landscape unit consisting of rugged landscape composed of dirty snow, with dispersed clasts and small rocky outcrops exhibits a high linear positive correlation with the monthly mean albedo (R2=0.87) and a high linear negative correlation with the monthly mean air temperature (R2= 0.69). The increase of the solar radiation energy flux from September to December coincides with the decrease of the relative abundance of the landscape unit composed of dirty snow with dispersed clasts and small rocky outcrops. We propose a mechanism to describe the evolution of the landscape: uncovered pyroclasts act as melting centres favouring the melting of surrounding snow. Ash does not play a decisive role in the melting of the snow. The results also explain the observed decreasing of the thaw depth of the permafrost on the island in the period 2006-2014, resulting from an increase in the snow cover over the whole island.

Background: Parkinson's disease (PD) is a global disease. However, there is a lack of research specifically focused on the AfrAbia population. Climate change, driven mainly by global warming, is linked to detrimental health impacts, including an increased frequency and intensity of heat waves. Neurological diseases, including neurodegenerative syndromes like Alzheimer's disease, Parkinson's disease, and motor neuron illnesses, have been increasingly seen and recorded in scientific literature. Although there is much literature demonstrating the growth in neurodegenerative disorders, the relationship between environmental variables such as global warming, air pollution, heavy metals, and pesticides and the higher occurrence of these illnesses is still unknown. Objective: The current article primarily aims to examine the relationship between climatic changes, air pollution, pesticides, heavy metals, and the occurrence of PD. Initially, we evaluate the influence of exposure to these variables on the cause or origin of Parkinson's disease. In addition, we will investigate how these variables disrupt processes such as excitotoxicity, oxidative stress, and neuroinflammation, all of which are strongly linked to Parkinson's disease (PD). Conclusions: This research presents a plausible rationale for the adverse effects of environmental influences on the brain, which are pivotal in the progression or onset of Parkinson's disease from an AfrAbian standpoint.

Recent advancements have revolutionized interplanetary spacecraft missions by combining low-thrust propulsion systems with planetary Gravity-Assist (GA) maneuvers. This study investigates/improved a novel dual-step efficient-robust homotopy algorithm, grounded in indirect optimal control principles, to analyze fuel-optimal bang-bang control problems. The methodology integrates efficient techniques, including the homotopic method, compatible normalization, and improved switching function detection, aimed at enhancing optimal convergence in solving low-thrust gravity-assist spacecraft missions. To illustrate practical application, an Earth-to-Jupiter interplanetary scenario utilizing Mars-GA is examined. Results demonstrate the algorithm's superior efficacy in achieving fuel efficiency, robust convergence, and remarkable accuracy compared to existing solutions.

Abstract: Earth’s Phanerozoic history is marked by about 100 major events (“golden spikes”) indicating the beginnings of new stages in the Geologic Time Scale (GTS). Stage boundaries signify major deterministic events that are relatively well-known and can be correlated worldwide, mostly on the basis of appearances or disappearances of fossil species. The latest stage (Anthropocene) is human-made and currently involves rapid (approximately linear) increase in average atmospheric temperature. The main cause of Earth’s past and current temperature increases is addition of CO2 to the atmosphere. There is continuous exchange of greenhouse gases between atmosphere and oceans, which (per unit of volume) contain 50 to 60 times as much CO2 as the atmosphere. Abundance of new very precise worldwide observations is allowing multifractal modeling of weather and climate during the latest Quaternary stages during which some variables like temperature of the atmosphere and frequency of forest fires can be described by using the Pareto-lognormal frequency distribution model with parameters that are subject to continuous (deterministic) changes, similar to those in the earlier Phanerozoic.

The Self-Forming Dynamic Membrane BioReactor (SFD MBR) is a cost-effective alternative to conventional MBR, where the synthetic membrane is replaced by the “cake layer”, an accumulation of the biological suspension over a surface of inert low-cost support, caused by a suction force. Under optimized conditions, the cake layer reveals easy to remove and quick to form again, resulting a “dynamic membrane”. The permeate of SFD MBR has chemo-physical characteristics comparable to those of conventional MBR. In this paper, two nylon meshes with a pore-size of 20 and 50 µm respectively were tested in a bench scale SFD MBR where a periodic air mass load (AML) was supplied tangential to the filtration surface to maintain filtration effectiveness. The SFD MBR equipped with the 20 µm nylon mesh coupled to 5 min of AML every 4 hours showed the best performance both ensuring a permeate with turbidity values always below 3 NTU and revealing no critical fouling. A benchmark test, conducted in the same experimental time, with identical operating conditions, and the only difference of a suction break (relaxation) instead of the AML. This latter test produced a permeate of very good quality, but it needed frequent mesh cleanings, showing that a periodic AML coupled with the use of a 20 µm mesh can be a good strategy for long term operation of SFD MBR.

The rescue, digitisation, quality control, preservation and utilization of long and high quality meteorological and climate records, particularly related to historical marine data, are crucial for advancing our understanding of the Earth's climate system. In combination with land and air measurements, the historical marine records serve as foundational pillars in linking present and past weather and climate information, offering essential insights into natural climate variability, extreme events in marine areas, baseline data for assessing current changes, and inputs for en-hancing predictive climate models and reanalyses. This paper provides an overview of marine data rescue activities covering the past centuries, presents and highlights several ongoing projects across the world and how the data are used in an integrative and international framework. Current and future continuous efforts in data rescue, digitisation, quality control and the de-velopment of temporally high resolution meteorological and climatological observations from the Sea, will greatly help to further complete our understanding and knowledge of the Earth system including extremes, as well as improving the quality of reanalysis.

Space–air–ground integrated network (SAGIN) is considered as an enabler for the sixth-generation (6G) networks. By integrating terrestrial and non-terrestrial (satellite, aerial) networks, SAGIN seem to be a quite promising solution to provide reliable connectivity everywhere and all the time. Their availability can be further enhanced if hybrid free space optical (FSO)/radio frequency (RF) links are adopted. In this paper, the performance of a hybrid FSO/RF communication system operating in SAGIN has been analytically evaluated. In the considered system, a high altitude platform station (HAPS) is used to forward the satellite signal to the ground station. Moreover, the FSO channel model assumed takes into account the turbulence, pointing errors and path losses, while for the RF links, a relatively new composite fading model has been considered. In this context, a new link selection scheme has been proposed that is designed to reduced the signaling overhead required for the switching operations between the RF and FSO links. The analytical framework that has been developed is based on the Markov chain theory. Capitalizing on this framework, the performance of the system has been investigated using the criteria of outage probability and the average number of link estimations. The numerical results presented reveal that the new selection scheme offers a good compromise between performance and complexity.

The presented work is aimed at studying the gas transport characteristics of polymeric hollow-fibre gas separation membranes. Such materials as: polysulfone (PSF), polyphenylene oxide (PFO), polyetherimide (PEI), polyetherimide with polyimide (PEI+PI) were studied on the example of air mixture separation. The values of the permeances of pure gases O2 and N2 and the mixed permeances of oxygen and nitrogen during air separation were obtained. Mathematical models of the gas separation process built on the basis of these values show significant discrepancies. To obtain a gas mixture with 95 mol.% nitrogen from air, taking into account the mixture permeance, 15.8% more PSF membrane area is required than taking into account the permeance of pure gases. For a PPO membrane this value is 13.9%, for PEI 19.8% less area is required, and for PEI+PI 15.9% less. In the design of industrial or semi-industrial membrane installations, such discrepancies can lead to significant errors, including technical and economic ones.

For colloids of NaYF4:Yb3+/Tm3+ nanoparticles in DMSO by the method of time-resolved lumi-nescence spectroscopy with nanosecond pulsed excitation at a wavelength of 975 nm the photo-physical processes that determine the course of kinetic curves have been revealed. It has been found that the luminescence rise time decreases with an increase of the concentration of activators and sensitizers due to increase of the efficiency of energy transfer from sensitizers to activators. Cross-relaxation of the excited states of activators provides a decrease of the lumi-nescence decay time with an increase of the concentration of activators and a constant concentration of the sensitizer. There was no correlation between the time of luminescence decay with the change of the concentration of sensitizers and constant concentration of activators due to the competition of the processes of energy back transfer from activators to sensitizers and the "feeding" of activators by excitations coming from remote sensitizer ions.

A survey of the trends in metal-ligand coordination and hydrogen bonding has been carried out on complexes of singly deprotonated cyanuric acid CY− and alkaline earth metals, synthesised from aqueous solution and characterised by X-ray crystallography. Involvement of cyanurate in the metal coordination increases from Mg through Ca and Sr to Ba relative to coordination by water, in parallel with the increasing ionic radius and coordination number. The incidence of bridging of metal centres by both water and cyanurate also increases in this series. The Mg complex contains hexaaqua-coordinated cations, uncoordinated CY− anions, and additional water molecules. Ca and Sr complexes feature polymeric chains of coordinated metal ions, the Ca complex with uncoordinated anions and the Sr complex with all potential ligands coordinated. The Ba complex has a two-dimensional coordination network. Extensive hydrogen bonding plays a key role in generating a three-dimensional network in all four structures. The competition between cyanurate and water for coordination to the alkaline earth metal cations, and that between coordination and hydrogen bonding propensities of the cyanurate anion, appear to be finely balanced, with the structural outcomes depending on the relative sizes and degrees of hardness of the four cations of the group.

The Sm3+/Gd3+ co-doped glasses in the B2O3–GeO2–PbO and B2O3–GeO2–Bi2O3 systems have been synthesized in the composition range of 40B2O3–40GeO2–(15-17)PbO(Bi2O3)–(3-2)Sm2O3–(2-1)Gd2O3 and 42.5B2O3–42.5GeO2–(11.25-12.75)PbO(Bi2O3)–(2.25-1.5)Sm2O3–(1.5-0.075)Gd2O3. The physical, structural, and spectral properties of the produced glasses have been studied. The fabricated glass samples demonstrated changes in temperature-sensitive luminescence parameters in 298-673 K temperature range. We found out several photoluminescence bands attributed with transitions from different Stark sublevels. By using a combination of two temperature sensitive and one non-sensitive transitions we calculated fluorescence intensities ratio (FIR). This procedure made it possible to increase the sensitivity of luminescence thermometry in several times. Such method could be very useful for the luminescent thermometry materials based on Ln3+ ions with multiplied f-f transitions.

Exploring effective oxygen reduction reaction (ORR) electrocatalysts is crucial for progress in solid-state alkaline zinc-air batteries (ZAB). In this paper, silver-manganese dioxide-carbon nanotubes (SMC) ternary composites, which function as Electrocatalyst for air Electrodes, was produced via the pyrolysis of silver permanganate under microwave irradiation in one step. A scanning electron microscope (SEM), X-ray diffraction (XRD), and an energy dispersion spectrometer (EDS) have consistently determined that SMC consists of silver and alpha-manganese dioxide, which anchored on the surface of CNTs. Through polarization and chronoamperometery curves, the electrocatalytic activity of SMC for ORR was examined. The results reveal that SMC has higher catalytic activity than the chemically produced electrocatalyst for ORR in alkaline condition. Finally, a solid-state zinc-air cell with an electrocatalyst was constructed and tested. Constant current discharge curve of the zinc-air cell with SMC has a long discharge voltage plateau and a 60.03 mAh capacity at 30 mA · cm−2 . The mechanism of improvement in electrocatalytic activity was also discussed. In a summary, the strategy described in this study and the electrocatalyst produced can be regarded as an effective method for making a robust oxygen reduction catalyst toward solid-state zinc-air batteries.

The earth pressure acting on soilbag reinforced retaining structures subjected to surcharge loads under non-limited states, is crucial for designing these structures. In this study, the earth pressures are investigated through model tests of the soilbag reinforced retaining wall. Findings from these tests reveal a non-linear distribution of lateral earth pressure on the wall when subjected to surcharge loads in non-limited states, with an observed escalation in pressure corresponding to increased surcharge loads. Compression tests on soilbags were conducted to analyze their lateral stress-strain behavior. Insights from these tests facilitated the development of a predictive method for estimating lateral pressure on soilbag reinforced retaining walls under similar conditions. This method, rooted in the principle of force equilibrium in differential elements, has its accuracy and reliability substantiated by the alignment of its predictions with the model test outcomes.

Indoor comfort is a critical determinant of the holistic educational experience, significantly influencing the well-being, concentration, and performance of students within the confines of school environments. Despite the widespread implementation of heating, ventilation, and air conditioning (HVAC) systems in educational institutions, achieving satisfactory thermal conditions, acceptable acoustics, and optimal daylight levels for occupants continues to pose a considerable challenge. In this review, we specifically delves into the parameters characterizing Italian school environments, recognizing their direct impact on students’learning and concentration. The primary objectives of this review are conducting a thorough examination of the current acustic conditions in Italian schools. The initial phase of our search strategy involved retrieving data from key databases, namely, Scopus, Web of Science, ScienceDirect, PubMed, and Google Scholar. Following the elimination of duplicate articles (n = 289), a total of 135 distinct papers remained for analysis. A critical review of the existing literature is presented based on these criteria, offering guidelines and recommendations for forthcoming studies. The critical review underscores various shortcomings in the current design, deployment, and documentation of multi-domain studies, signaling the need for enhanced quality in future research efforts.

Fractal analysis of time series aims to extract the hidden or complex structures issued from the associated real data, such as scaling laws, non-stationary, dynamics, and so on. In the present work, the air quality index and its components are considered as time series owing fractal structures. To understand their underlying dynamics, wavelet multifractal approach is applied starting with a wavelet multifractal spectrum test to confirm the multifractality of the underlying data. Next, a new model is introduced improving the classical minmax one, provided with a statistical measure for the adequacy of the new model. The theoretical findings are applied to the north west Tabuk region of Saudi Arabia for environmental and climate data related to pollutants and factors involved in the estimation of the air quality index.

This paper deals with a method of calculating the self and mutual inductances of various air coils located arbitrarily in space. Known elementary solutions (the Biot-Savart formulas) were used to determine the magnetic field of infinitely thin current loops and infinitely thin wires of finite length linking magnetically other coils. Unlike commonly used algorithms, these elementary solutions were not extensively transformed analytically but were used to perform calculations by direct numerical integration. This enabled very quick and accurate obtaining of the self-inductance values as well as determining the dependence of mutual inductances on the position of both coils. This method allows analysis of different coil configurations (misaligned coils, inclined to each other, etc.) that other methods do not cover. It also enables the determination of the forces acting on the coils, as well as the calculation of the magnetic field distribution from any coil configuration. The obtained results were compared with those presented by other authors.

Highly transparent, conductive nanosheets are extremely attractive for advanced optoelectronic applications. Previously, we have demonstrated that transparent, conductive Au nanosheets can be prepared by UV irradiation of Au nanoparticle (AuNP) monolayers spread on water, which serves as the subphase. In this study, we show that this UV irradiation technique can easily be extended as a nanosheet modification method by using subphases containing metal ions. That is, aqueous solutions containing Au and Ag ions are effective in modifying Au nanosheets. HAuCl4 solutions increased Au nanosheet thickness, which improved conductivity, but reduced transparency. On the other hand, use of aqueous AgNO3 and CH3COOAg solutions yielded Au-Ag hybrid nanosheets; however, their morphologies depended on the electrolytes used. Homogeneous Au-Ag nanosheets from AgNO3 and AuNPs covered with an Ag nanosheet from CH3COOAg were also produced. Further, these Au-Ag hybrid nanosheets had high conductivity without reduced transparency. Therefore, this UV irradiation method, modified by adding metal ions is quite effective at improving and diversifying properties of Au nanosheets.

The paper describes and analyzes the performance of a new thermoelectric generation system based on the use of Peltier cells inserted in the ducts of the air conditioning equipment. The hot and cold air streams that flow in the two separated sections of an air conditioning system are used to create a thermal gradient between the two faces of the Peltier cells. Hot and cold air flow inside the A/C unit are driven to a built in thermal chamber where the Peltier cells are placed. Peltier cells are incrusted into an insulation wall that separates the two sections of the chamber through which hot and cold air streams are flowing. The so designed configuration allows the Peltier cells to generate electric current. The study has been run for constant cold air temperature and variable hot air temperature, resulting in a variable performance of the thermoelectric generator. Theoretical study has been completed with experimental tests to determine real performance of the thermoelectric unit. Efficiency of the thermoelectric generator has been found to be linearly dependent on the temperature difference between hot and cold air subsections of the chamber. Maximum efficiency, however, is limited by the hot air stream temperature, since in real conditions ambient temperature cannot overpasses a specific value. For standard operational conditions, 5º C and 45º C for the cold and hot air streams, the thermoelectric generator operates at 44% of the maximum efficiency attainable.

The feasibility of replacing the toxic chlorobenzene antisolvent with the environmentally friendly anisole in the fabrication of planar triple cation perovskite solar cells was explored. The successful integration of anisole not only ensures comparable device performance but also contributes to the development of more sustainable and green fabrication processes for next-generation photovoltaic technologies. Nevertheless, to ensure the possibility to achieve well-functioning unencapsulated devices, at any time of the year, with changed temperature and relative humidity, several batches with different cesium concentration were realized. We found that 10% of CsI in the precursor solution makes devices with low hysteresis index and sustained performance stability over a 90-day period both with cholorobenzene and anisole antisolvent. However the use of anisole as a green antisolvent ensures enhanced performance.

Over the last few decades, there is a remarkable increase in air traffic worldwide; however, despite of rapid technological development and improved airport infrastructure, there is still an increasing number of aviation accidents and fatalities. In order to meet safety demands of Air Traffic Control (ATC), Machine Learning (ML) based aircraft conflict detection techniques are focused to predict events before they come to reality. This research presents a systematic literature review (SLR) about the applications of ML techniques in safety prediction of ATC system. Initially, the existing aircraft conflict prediction models are classified into three broad categories; logical, geometric and probabilistic. A formal process of SLR is then conducted which is initiated with preprocessing and effective searching. A series of filtering called title, abstract and objective-based are then applied to extract the most relevant articles. Detailed and critical reviews of selected articles are performed to identify challenges which are segregated into dataset, model and evaluation techniques, furthermore, the optimal solutions for each are proposed. Finally the matrices to map the identified challenged with their proposed solutions are constructed. This research serves as a foundation for future research and towards integration of ML based safety prediction techniques into modern ATC system.

3D printing with earth-based mortar is still under development and faces challenges. Optimizing the mortar mixture, improving structural strength, determining the relationship between printing speed and the amount of extruded material, and ensuring long-term durability are areas that are still being refined. Additionally, regulatory and certification issues must also be considered to ensure the safety and compliance of 3D printed structures. This paper presents for discussion the records, analyses, studies, and considerations regarding the initial initiatives involving 3D printing with the extrusion of earth-based mortar developed at the Faculty of Engineering of the University of Porto - FEUP. Through this work, it is possible to strengthen and reaffirm that 3D printing with earth-based mortar has significant potential in the construction industry and that the incorporation of dispersed kraft paper fibres from the recycling of cement bags is an excellent resource to achieve good constructability in 3D printing with earth-based mortar.

The identified Urban Heat Island (UHI) phenomenon, coupled with diminished vegetation and anthropogenic heat release, poses a significant environmental challenge for major urban centers. Particularly worrisome is the UHI effect in hot and temperate climates such as the Mediterranean region during the summer season. This exacerbates discomfort and heightens the risks of diseases linked to high temperatures. Additionally, it contributes to environmental consequences, including elevated electricity consumption due to increased demand for cooling [1]. The utilization of Remotely Sensed imagery for estimating Land Surface Temperature has become more prevalent in various applications associated with evaluating urban micro-climates and the Urban Heat Island (UHI) phenomenon. This study presents an algorithm for the automatic mapping of Land Surface Temperature (LST) from Landsat-8 data using a vegetation index-based technique in the Google Earth Engine (GEE) platform. The primary aim is to discern patterns and trends in LST over a 5-year period, from 2017 to 2021. The application was tested in the urban area of Thessaloniki, Northern Greece, which is particularly representative of the Mediterranean urban environment. Computation of Normalized Difference Indices (NDVI, NDBI, NDWI) for the study area was also performed within the GEE platform and correlation analysis was implemented to evaluate the impact of the urban landscape on the distribution of LST.

Today, air pollution is the greatest threat to organismal healthspan. The environment of our planet earth, the habitat of over eight billion humans and estimated twenty billion billions other animals, is contaminated with a wide variety of pollutants. Unfortunately, humans, out of billions and billions of living organisms on earth, are solely responsible for polluting the environment through emitting pollutants like particulate matter from industry, fuel engine vehicles, biomass combustion, toxic fumes from blasting, and wildfire. In the modern world, human-caused air pollutants induce massive oxidative stress and inflammation, the major contributors in initiation and progression of many diseases including pulmonary, cardiovascular, renal, hepatic, reproductive, neurological, mental, and accelerated biological aging. The provocative question is the following: how can we solve this human-created problem? As it is not realistic to clean the environment at once from human-caused pollution, initiatives have been undertaken to develop novel therapeutic approaches to control air-pollutant-induced oxidative stress and inflammation to protect humans from pollution-induced devastating diseases. In this article, I discuss the key findings of numerous recent preclinical studies documenting first, the role of air pollutant PM2.5 in augmentation of inflammation, oxidative stress, and associated diseases; and second, the efficacies of different natural and synthetic compounds in amelioration of PM2.5-induced oxidative stress, inflammation, pyroptosis, and associated pathologies.

Multiple sources influence air quality and regional climate in complicated atmospheric emission situations like urban agglomerations. To resolve pollution plumes and source influences in polluted areas, a comprehensive chemical fingerprinting of sources utilizing non-methane hydrocarbons (NMHCs) and the identification of acceptable tracer molecules and emission ratios is required, in contrast to pristine locations, where reliance on a single or a few chemical tracers is frequently sufficient. We have characterized the prevalence of NMHCs fingerprints in the urban areas and quantified the correlation of windspeed with the concentration of these pollutants. eNose sensors and Air quality management stations provide the data to identify the emission sources of such pollutants. Based on our analysis, the average NMHC concentration in 2021 has been recorded 0.424 ppm at point 1 AQMS whereas at point 2 AQMS it was 0.256 ppm. Such outcomes could be attributed to the proximity of emissions sources, the direction and speed of the wind, or both. Moreover, traffic can be a major contributor to pollution levels in any urban area. More research based on a larger dataset is required before definitive conclusions can be drawn, and viable solutions can be proposed.

This article examines air sampling as an environmental surveillance strategy for early pathogen detection and offers a preliminary comparison of air and wastewater surveillance. Air sampling involves collecting bioaerosols to analyze the microbial composition of the air, utilizing techniques like PCR and metagenomic sequencing. Air sampling appears especially promising for detecting respiratory pathogens and highly transmissible pandemic agents, as these spread primarily via aerosols and droplets. The article details various air sampling techniques, their efficiency, and practical considerations, categorizing them into filtration, impaction, impingement, electrostatic precipitation, and condensation methods. It also explores the composition of airborne microbes, emphasizing the low concentration of viral nucleic acids and the challenges this poses for metagenomic sequencing. The selection of sampling locations, including indoor environments and airplanes, is discussed as critical for effective pathogen detection. Finally, the article contrasts air and wastewater sampling, concluding that while both methods should ideally be explored as layered defenses, air sampling does not collectively appear more promising than wastewater sampling.

CubeSats, known for their compact size and cost-effectiveness, have gained significant popularity. However, their limited size imposes restrictions on optical aperture and, consequently, Ground Resolution Distance in Earth Observation missions. To overcome this limitation, the concept of deployable optical payloads with segmented primary mirrors which can unfold like petals has emerged, enabling larger synthetic apertures and enhanced spatial resolution. This study explores the potential benefits of leveraging Additive Manufacturing (AM) and Topology Optimization (TO) in the realm of ultra-precision machining, specifically single point diamond machining. The goal is to reduce fixture weight while improving stiffness to minimize deformations caused by rotational and cutting forces which compromise optical performance. Through Finite Element Analysis, this research compares conventionally machined fixtures with those produced using AM and TO techniques. The results reveal that concept designs created through TO can achieve a remarkable 68% reduction in weight. This reduction makes the assembly, including the machining fixture and 12U deployable segments, manageable by a single operator without the need for specialized lifting equipment. Moreover, these innovative designs lead to substantial reductions of up to 86% and 51% in deformation induced by rotational and cutting forces, respectively.

Higher traffic density in Russian cities and less uniform traffic due to congestions are reasons for increased emissions of pollutants contained in exhaust gases of vehicles. The paper presents the modeling results of pollutant dispersion in Magnitogorsk. The analysis of these results shows that now many blocks of flats and social infrastructure of the city are in a zone with an excess of maximum allowable concentration of pollutants. Having summarized the methodological framework formulated by Russian and foreign researchers, the authors systemized the existing methods used to decrease pollutants produced by vehicles. It is proposed to choose an optimal combination of such methods applying a developed mathematical model. By adopting an optimal combination of the methods, it is possible to ensure minimum air pollutant emissions from vehicles, allocating limited financial resources. The mathematical modeling of the solutions on changing traffic density and structure and implementing methods used to decrease pollutants on one of the Magnitogorsk crossroads with the heaviest traffic is used to draw a conclusion about efficiency of the designed model used as a tool for strategic planning of development and transformation of street networks.

In this study, the extraction of rare earth elements (REEs) from chloride solutions containing mixtures of these metals with solutions of the mixtures of P507 and Cyanex 272 (1:1) of various concentrations was experimentally studied. It was shown that the distribution coefficients of all REEs decrease with increasing concentration of these metals in the initial solution, which is associated with the loading of the organic phase. The most significant improvement in the extraction is observed for heavy group of rare earth elements. The extractability of REEs enhances with increasing atomic number of the element, as is typical for the extraction of these metals with acidic organophosphorus extractants. The data obtained show that separation factors of adjacent rare earth elements mainly decrease with increasing concentration of metals in the initial aqueous solution. Increasing the concentration of the extractant mixture does not have a significant effect on the values of the adjacent REE separation factors. Analysis of the experimental results shows that two commercial products can be obtained from a concentrate of the medium-heavy group. In the first cascade, yttrium can be separated, in the second, a concentrate of dysprosium and terbium can be obtained.

The chemical reaction of ion-adsorption type rare earth during in-situ leaching process is accompanied by ion migration and charge movement, making the leaching process electrochemical in nature. The chemical reaction rate plays an important role in the leaching rate of rare earth elements. In this work, electrochemical impedance spectroscopy (EIS) was used to reveal characteristics of electrical resistance alteration and leaching rate of rare earth elements during in-situ leaching. The equivalent circuit model of the leaching process was established, and two critical parameters of solution resistance Rs and charge transfer resistance Rt were analyzed to reflect the electrochemical characteristics. According to the characteristics of electrical resistance alteration, the leaching process was divided into four stages: wetting, reaction, equilibrium, and top water stage. The resistance parameters Rs and Rt decreased first and then increased during the leaching process. The maximum value of Rs was 1330Ω∙cm2 at the end of the top water stage, and the minimum value was 135Ω∙cm2 at the beginning of the equilibrium stage. The maximum value of Rt was 8310Ω∙cm2 at the beginning of the leaching stage, and the minimum value was 21Ω∙cm2 at the end of the reaction stage. Rs and Rt were negatively correlated with the pore size and chemical reaction rate during leaching. With increasing of pore size and reaction rate , the resistance parameter decrease. This study provide a new idea for intelligent monitoring of rare earth ore.

Mineral extraction is one of the most important for the economies of different countries, and Brazil is one of the world's primary iron ore producers. Unfortunately, the dams are still the main problem, mainly in Minas Gerais, especially after the Fundão Dam rupture happened in 2015. Additionally, there is still a massive presence of buildings produced on earth throughout the Minas Gerais mining region, built from the 18th century to today. Investigating the potential of IOT to be incorporated into traditional earthen construction techniques in regions affected by dam ruptures presents a relevant and innovative research approach. In addition, the local reuse of these sediments should be the priority. Thus, the main objective of this work was to collect, characterize, and analyze the possibilities of application of these tailings to produce RE. XRD, XRF, granulometry, porosity, specific density, toxicity, and MEV/EDS were performed on the samples collected at three points. To analyze the soil-IOT compatibility, representative mixtures of RE were produced, and the specific mass, compaction, and compressive strength were performed. It was observed that the IoT samples have a high silica content and that the mixtures of IOT-soil, even without cement, reached compressive strength values above the current international standards.

Earth is a complex material with a mechanical and physical behavior that differs from modern building materials. The conservation of rammed earth (RE) constructions presents specific difficulties that are challenging to overcome. The lack of knowledge about RE due to its abandonment for decades and attempts to adopt materials and repair methodologies designed for new building products has led to inadequate interventions. In the case of historic defensive constructions, the doubts and technical difficulties are even greater due to the nature of the so called military RE (with physical and mechanical characteristics significantly different from those of civil, more common, RE) and, not least, due to the historical and cultural heritage value of these constructions. Some important interventions have been carried out recently and others are underway or in the planning stage, and there is a constant lack of information and technical data on the best ways to intervene. To fill this gap, the state of conservation of the RE defensive structures and the results of interventions carried out throughout history in the southwest of the Iberian Peninsula are being assessed. This article sets out the framework of the subject, identifies the material and construction techniques, and recognizes the main causes of its deterioration and decay. With special focus on the most frequent damages detected in historic military defensive structures built with RE, it analyses and discuss the most common techniques that have been used for the repair and conservation of these particular structures.

This study focuses on the synthesis, characterization and study of a new perovskite-type materials as cathode in SOFC. The synthesized doped perovskites have been successfully synthesized with high purity. The electrochemical performance of these materials was extensively examined through the characterization of I-V-P and EIS curves at the three temperatures: 750, 800 and 850 °C. Where it is revealing a substantial reduction of total resistances by approximately 50% and 70%, accom-panied by an impressive increase in power densities by around 200% and 300%, respectively. The cell featuring Sm0.01Sr0.99Fe0.5Co0.5O3 exhibited the most commendable electrochemical properties at each temperature, following closely were Pr0.01Sr0.99Fe0.5Co0.5O3 and La0.01Sr0.99Fe0.5Co0.5O3.

Background: SARS-CoV-2 continues to impact human health globally, with airborne transmission being a significant mode for transmission. In addition to tools like vaccination and testing, counter-measures that reduce viral spread in indoor settings are critical. This study aims to assess the efficacy of UV-C light, utilizing the Violett sterilization device, as a countermeasure against airborne transmission of SARS-CoV-2 in the highly susceptible Golden Syrian hamster model. Methods: Two cohorts of naïve hamsters were subjected to airborne transmission from experimentally infected hamsters; one cohort was exposed to air treated with UV-C sterilization, while the other cohort was exposed to un-treated air. Results: Treatment of air with UV-C light prevented the airborne transmission of SARS-CoV-2 from experimentally exposed hamster to naïve hamsters. Notably, this protection was sustained over a muti-day exposure period during peak viral shedding from hamsters. Conclusion: These findings demonstrate the efficacy of the UV-C light to mitigate airborne SARS-CoV-2 transmission. As variants continue to emerge, UV-C light holds promise as a tool to reduce infections in diverse indoor settings, ranging from healthcare facilities to households. This study reinforces the urgency of implementing innovative methods to reduce airborne disease transmission and safeguard public health against emerging biological threats.

In this work, we present preliminary results of radar observations of near-Earth Objects (NEOs) carried out by European radio telescopes in the framework of the European Space Agency (ESA) project “NEO observation concepts for radar systems”, which was aimed to derive the functional requirements of a radar system, evaluate the available European assets to perform NEO radar observations and carry out test radar campaigns. In the first part of the project, we carried out the performance analysis of a possible European planetary radar system. Instrumental features, as much as issues like the impact of weather conditions on signal propagation at different radio frequencies, were considered. This paper is focused on the test campaigns, performed in the years 2021-22 in collaboration with the Jet Propulsion Laboratory (JPL), which led to the observation of several asteroids including 2021 AF8, (4660) Nereus and 2005 LW3, which allowed us to derive astrometric measurements, as well as to measure physical properties, such as rotation periods, and detect an asteroid’s satellite. The obtained results demonstrate that European radio astronomical dishes, although employed only as receivers (in bistatic or multistatic configurations) and for a limited amount of time, are able to provide a significant contribution to the constitution of a European network to increase the opportunities for NEO monitoring and studies, if a transmitting antenna - equipped with a suitable high-power transmitter - were made available.

Different coffee drying technologies face complex task in ensuring an acceptable final seed moisture content. Drying technology of agricultural commodities aims to maintain and improve the quality of the agricultural products themselves. In addition to maintaining quality, especially from other bacterial attacks, it can last for a long time before further processing. Coffee commodities are promising for the welfare of coffee farmers. Drying technology plays a major role in determining the quality of coffee. Various drying models are applied including the traditional model that until now is still applied, direct drying under solar radiation. However, this drying process is less hygienic and requires a large area. Thus, one of the drying technologies that can accelerate drying time is to vary the air flow in the drying chamber so that the coffee can be determined to reduce the water content with a certain temperature. In this study, it was found that the moisture content of coffee beans dried using a dryer on air flow with variations of velocity in solar collector 1 (DB1) air velocity of 1.0m/s obtained the final mass = 732.249 gr, solar collector 2 (DB2) with air velocity 1.5 m/s obtained the final mass = 774.70 gr, solar collector 3 (DB3) with air velocity 2.0 m/s obtained the final mass = 855.10 gr, solar collector 4 (DB4) with air velocity 2.5 m/s obtained the final mass = 745.79 gr, and solar collector 5 (DB5) with air velocity 3.0 m/s obtained the final mass = 786.40 gr. Water Content DB1=12.0%, DB2=13.6%, DB3=18.5%, DB4=12.9% and DB5=15.2%. The time required for 25 hours with a maximum radiation of 586.9 w/m2, total heat utilized from solar radiation in 3 days =16.663128 MJ/m2. from the initial weight of 1500gr coffee bean samples and dried in five solar collectors with parallel simultaneously. The evaporated water content DB1=51.18%, DB2=48.35%, DB3=42.96%, DB4=50.28% and DB5=47.57%. Based on this research, it was found that the most optimum quality of coffee was by using solar collector 2 (DB2), namely with air flow of 1.5 m/s with average temperature in the drying box DB2=43.68°C, with the quality content of the coffee, Protein content=12.2%, Carbohydrate=22.8% and Free Fatty Acid (ALB) content=0.05%.

Transportation is the primary consumer of oil, accounting for a significant portion of global energy consumption (34%) and CO2 emissions (40%). Electrifying road transportation is crucial to mitigate the effects of global warming. The abundant potential of renewable energy sources like solar and wind is hindered by their intermittent nature and incongruity with peak energy demands. This calls for the development of sophisticated energy storage solutions. Metal-air batteries (MABs), emerging as viable alternatives to lithium-ion batteries (LIBs), have attracted considerable attention due to their promising applications in the transportation sector. Despite substantial progress in MAB development over the past two decades, overcoming critical challenges such as electrolyte decomposition, carbon cathode degradation, anodic dendrite growth, and air impurities remains essential for their commercial viability. This mini-review provides a comprehensive overview of MAB fundamentals and the challenges associated with their development. The insights presented in this review serve to illuminate the current landscape and future prospects of MABs in the transportation sector.

Currently, many researchers have an interest in the investigation of the electric field in the fair-weather electric environment, along with its diurnal and seasonal variations across all regions of the world. However, a similar study in the southern part of Siberia has not yet been carried out. In this regard, the study aims to estimate the mean values of the electric field and their variations in the mountain and steppe landscapes using measurement data from the Khakass-Tyva expedition in 2022. The maximum values of positive ion density were noted at the site in the Iyussko-Shirinsky steppe between Belyo and Tus salt lakes in the Khakass-Minusinsk ba-sin. The maximum values of negative ion density were observed at site in the Shol tract in the center part of the Tyva depression. The potential gradient tends to increase with altitude and reaches a maximum in the highlands. The maximum values of the potential gradient were noted in the highlands plateau near the Mongun-Taiga mountain massif and Khindiktig-Khol lake. The diurnal cycles of potential gradient at different observation sites were divided into two groups: 1) a diurnal cycle in the form of a double wave; 2) a daily cycle with a more complex course due to the strong influence of local factors.

DNA extraction for downstream molecular diagnostic applications can be an expensive, time-consuming process. We devised a method to quickly extract genomic DNA from environmental samples based on sodium hydroxide lysis of cells with or without capture by magnetic beads, for subsequent PCR or quantitative PCR. The final DNA extraction method using NaOH is extremely low-cost and can be completed in 10 minutes at room temperature. NaOH extraction was effective for Gram-negative and Gram-positive bacteria in samples from air, soil, sewage, food, laboratory surfaces, and chicken cloacal swabs. The NaOH extraction method was comparable to commercial kits for extraction of DNA from pig fecal samples for 16S amplicon sequencing analyses. We demonstrate that an impinger and portable pump can efficiently capture bacteria in poultry facilities for rapid DNA extraction for quantification of total bacteria and for detection of specific species using qPCR. The air sampling and NaOH extraction procedures are well-suited for routine, high throughput screening, and for metagenomic analyses for specific pathogens, even in resource-limited situations.

Two pre-pulses focused at different positions and at different time moments were used to enhance THz emission generated by the main pulse. The emission of THz radiation from air breakdown regions of focused ultrashort fs-laser pulses (800 nm/35 fs) at shockwave front prepared by pre-pulses was investigated, and a 3D spatio-temporal control was established for the most intense emission. The laser pulse-induced air breakdown forms a ~120 micrometers-long focal volume and generates a shockwave that delivers denser air into the focal region of the main pulse for enhanced generation of THz radiation at 0.1-2.5 THz spectral window. The intensity of pre- and main-pulses was at the tunneling ionisation intensities (1-3)x10¹⁶ W/cm² and corresponded to sub-critical (transparent) plasma in air. Polarisation analysis revealed that the orientation of the air density gradients generated by pre-pulses and their time-space placement defined the ellipticity of the generated THz electrical field. The rotational electric current is the origin of THz radiation. The current is created by non-parallel gradients of electron density and temperature. Scaling dependencies of THz emission control are established.