The permanent protection of groundwater and surface sources of drinking water in the required raw water quality from contamination is the primary foundation of preserving the life of society and the entire engineering infrastructure operability not only in the Czech Republic but also in other countries of the world. One of the basic ways of contamination prevention enhancement and risk mitigation of putting a water source out of operation is the identification of the given risk as well as soil contamination monitoring. The purpose of this study is to understand specific aspects of contamination threats to drinking water sources and determine possible solutions to eliminate the risk, shown in the example case study in the Czech Republic conditions. Based on the findings, a proposal to enhance the prevention of water source contamination has been elaborated in the form of recommendations regarding the ways and means used to monitor the risk areas and to implement technical measures so as to eliminate or terminate the specified risk. A complex approach based on the integration of interdisciplinary factors and methodology is required to minimize the threats of aquatic ecosystems contamination in the Czech Republic.

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.

UV-A (ca. 365 nm wavelength, a.k.a. 'black light') photocatalysis has been investigated to comprehensively mitigate odor and selected air pollutants in the livestock environment. This study was conducted to confirm the performance of UV-A photocatalysis on the swine farm. The objectives of this research were to (1) scale-up of the UV-A photocatalysis treatment, (2) evaluate the mitigation of odorous gases from swine slurry pit, and (3) test different UV sources, (4) evaluate the effect of suspended particulate matter (PM), and (5) conduct preliminary economic analyses. We tested UV-A photocatalysis at a mobile laboratory-scale capable of treating ~0.2 - 0.8 m3·s-1 of barn exhaust air. The targeted gaseous emissions of barn exhaust air were significantly mitigated (p < 0.05) up to 40% reduction of measured odor; 63%, 44%, 32%, 40%, 66%, and 49% reduction of dimethyl disulfide, isobutyric acid, butanoic acid, p-cresol, indole, and skatole, respectively; 40% reduction of H2S; 100% reduction of O3; and 13% reduction of N2O. The PM mitigation effect was not significant. Formaldehyde levels did not change, and a 21% generation of CO2 was observed. The percent reduction of targeted gases decreased as the airborne PM increased. Simultaneous chemical and sensory analysis confirmed that UV-A treatment changed the overall nuisance odor character of swine barn emissions into weaker manure odor with 'toothpaste and 'mint' notes. The smell of benzoic acid generated in UV-A treatment was likely one of the compounds responsible for the less-offensive overall odor character of the UV-treated emissions. Results are needed to inform the design of a farm-scale trial, where the interior barn walls can be treated with the photocatalyst, and foul air will be passively treated as it moves through the barn.

Environmental impact associated with odor and gaseous emissions from animal manure is one of the challenges for communities, farmers, and regulatory agencies. Microbe-based manure additives treatments are marketed and used by farmers for mitigation of emissions. However, their performance is difficult to assess objectively. Thus, comprehensive, practical, and low-cost treatments are still in demand. We have been advancing such treatments based on physicochemical principles. The objective of this research was to test the effect of the surficial application of a thin layer (¼"; 6.3 mm) of biochar on the mitigation of gaseous emissions (as the percent reduction, % R) from swine manure. Two types of biochar were tested: highly alkaline and porous (HAP) biochar made from corn stover and red oak (RO), both with different pH and morphology. Three 30-day trials were conducted with a layer of HAP and RO (2.0 & 1.65 kg∙m^-2, respectively) applied on manure surface, and emissions of ammonia (NH₃), hydrogen sulfide (H₂S), greenhouse gases (GHG), and odorous volatile organic compounds (VOCs) were measured. The manure and biochar type and properties had an impact on the mitigation effect and its duration. RO significantly reduced NH₃ (19-39%) and p-cresol (66-78%). H₂S was mitigated (16~23%), but not significantly for all trials. Significant (66~78%) reductions for p-cresol were observed for all trials. The phenolic VOCs had relatively high % R in most trials but not significantly for all trials. HAP reduced NH₃ (4~21%) and H₂S (2~22%), but not significantly for all trials. Significant % R for p-cresol (91~97%) and skatole (74~95%) were observed for all trials. The % R for phenol and indole ranged from (60~99%) & (29~94%) but was not significant for all trials. The impact on GHGs, isobutyric acid, and the odor was mixed with some mitigation and generation effects. However, larger-scale experiments are needed to understand how biochar properties and the dose and frequency of application can be optimized to mitigate odor and gaseous emissions from swine manure. The lessons learned can also be applicable to surficial biochar treatment of gaseous emissions from other waste and area sources.

Background: Online survey-based observational cross-sectional study aimed at elucidating experience and attitudes of unstructured population regarding diagnostic imaging. Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p &lt; .0001), magnetic resonance imaging (MRI) (p &lt; .001), and ultrasound (p &lt; .05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p &lt; .05). Every tenth respondent received MRI, CT, and ultrasound on paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p &lt; .05). MRI and CT availability differed between respondents in urban and rural areas (p &lt; .0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p &lt; .05). Conclusions: Preparedness to future pandemics requires development of community-based outreach programs focusing on people's awareness regarding medical imaging safety and diagnostic value.

The research is focusing on analyzing the concentrations of particulate matter (PM) next to a highly congested road section, with 39,900 as a maximum number of vehicles per 24 h, in the vicinity of Timisoara, Romania. Concentrations have been measured in multiple episodes using two different measurement methods, gravimetric and dynamic light scattering, showing a disperse range of PM concentrations. Presence of metal particles in the samples have been analyzed using an electron microscope. Additionally, impact on human health is described by evaluating results for inhalable, thoracic, and alveolar sized particles.

Oil spillage over a sea or ocean’s surface is a threat to marine and coastal ecosystems. Spaceborne synthetic aperture radar (SAR) data has been used efficiently for the detection of oil spills due to its operational capability in all-day all-weather conditions. The problem is often modeled as a semantic segmentation task. The images need to be segmented into multiple regions of interest such as sea surface, oil spill, look-alikes, ships and land. Training of a classifier for this task is particularly challenging since there is an inherent class imbalance. In this work, we train a convolutional neural network (CNN) with multiple feature extractors for pixel-wise classification; and introduce to use a new loss function, namely ‘gradient profile’ (GP) loss, which is in fact the constituent of the more generic Spatial Profile loss proposed for image translation problems. For the purpose of training, testing and performance evaluation, we use a publicly available dataset with selected oil spill events verified by the European Maritime Safety Agency (EMSA). The results obtained show that the proposed CNN trained with a combination of GP, Jaccard and focal loss functions can detect oil spills with an intersection over union (IoU) value of 63.95%. The IoU value for sea surface, look-alikes, ships and land class is 96.00%, 60.87%, 74.61% and 96.80%, respectively. The mean intersection over union (mIoU) value for all the classes is 78.45%, which accounts for a 13% improvement over the state of the art for this dataset. Moreover, we provide extensive ablation on different Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) based hybrid models to demonstrate the effectiveness of adding GP loss as an additional loss function for training. Results show that GP loss significantly improves the mIoU and F1 scores for CNNs as well as ViTs based hybrid models. GP loss turns out to be a promising loss function in the context of deep learning with SAR images.

Understanding platelet functionality has undergone a sea change in the last decade. No longer are platelets viewed simply as regulators of haemostasis; they are now acknowledged to be pivotal in coordinating the inflammatory and immune responses. This expanded role for platelets brings new opportunities for controlling a range of health conditions, targeting platelet activation and their interactions with other vascular cells. Antiplatelet drugs may be of wider utility than ever expected but often cause too strong a platelet suppression to be used out of clinical settings. Dietary antiplatelets represent a nutritional approach that can be efficacious while safe for general use. Here we review potential new uses for dietary antiplatelets outside the field of cardiovascular health, with specific reference to the water-soluble tomato extract Fruitflow®. Uses in different aspects of inflammation and immune function are discussed, highlighting exercise-induced inflammation, mediating the effects of air pollution, and controlling thrombotic aspects of the immune response. Potential future developments in women’s health, erectile dysfunction, and the allergic response give an indication of how wide-ranging the utility of dietary antiplatelets can possibly be.

Increased exposure to artificial light at night can affect human health including disruption of melatonin production and circadian rhythms and extend to increased risks of hormonal cancers and other serious diseases. In addition, multiple negative impacts on fauna and flora are well documented, and it is a matter of fact that artificial light at night is a nuisance for ground-based astronomy. These impacts are frequently linked to the colour of the light or more specifically to its spectral content. Artificial light at night is often mapped by using space borne sensors, but most of them are panchromatic and thus insensitive to the colour. In this paper, we suggest a method that allows high resolution mapping of the Artificial light at night by using ground-based measurements with the LANcube system. The device separates the light detected in four bands (Red, Green, Blue, and Clear) and provides this information for six faces of a cube. We found relationships between the LANcube’s colour ratios and 1- the Melatonin Suppression Index, 2- the StarLight Index and 3- the Induced Photosynthesis Index. We show how such relationships combined with data acquisition from a LANcube positioned on the top of a car can be used to produce spectral indices maps of a whole city in a few hours.

Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2 (PLF) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM2.5), 10 μm or less (PM10), and nitrogen dioxide (NO2), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r<0.4). Moderate correlation was observed for one PLF unit at indoor location and two units at roadside location, when measuring PM2.5, but not for PM10 and NO2 concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R2 values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.

Ecological Society is based on socioeconomic systems directed to the equilibrium of inter-relationships between environment, climate, production systems, technologies and human communities to promote the overall well-being of people and the Earth planet. It has a main goal for supporting sustainable development and equitable societies and achieving optimal health outcomes recognizing the interconnection between people, technologies, animals, plants, and their shared environment for the one health. Using data of scientific publications and patents until the year 2024, this study shows new technologies that can support the energy transition with the shift from fossil fuels to renewable energy sources in an effort to reduce CO₂ emissions for an ecological society having, whenever possible, zero-carbon economies to reduce environmental pollution and climate change and foster health and wellbeing of people. Results reveal that sustainable technologies supporting the transformation of the energy sector, economies and societies, and having a rapid growth, are blue hydrogen, floating photovoltaic systems, carbon capture and utilization, green hydrogen and liquid metal batteries. These findings can guide decisions of policymakers and stakeholders towards fruitful investments driving the transition from fossil-based to zero-carbon socioeconomic systems to have a long-run sustainable development of overall world system that has to direct towards an ecological society associated with one health.

The increasing frequency of male cancer coupled with the reduction in male fertility seen worldwide motivated us to seek a potential evolutionary link between these two phenomena, concerning the reproductive transcriptional modules observed in cancer and the expression of cancer-testis-antigens (CTA). The phylostratigraphy analysis of the human genome allowed us to link the early evolutionary origin of cancer by reproductive life cycles of the unicellulars and early multicellulars, potentially driving soma-germ transition, female meiosis and parthenogenesis of polyploid giant cancer cells (PGCCs), with the expansion of the CTA multi-families, very late during evolution. CTA adaptation was aided by retrovirus domestication in the unstable genomes of mammals, for protecting male fertility in stress conditions, particularly that of humans, as compensation for the energy consumption by a large complex brain which also exploited retrotransposition. We found that the early and late evolutionary branches of human cancer are united by the immunity-proto-placental network, which evolved in the Cambrian and shares stress regulators with the finely-tuned sex determination system. We further propose that social stress and endocrine disruption caused by environmental pollution with organic materials, which alter sex determination in male foetuses and further spermatogenesis in adults, bias the development of PGCC-parthenogenetic cancer by default.

The article discusses determinants of living environment in Central and Eastern Europe. As an example, the city of Radzionkow was chosen, with 16 thousand inhabitants, located in the Silesia agglomeration in southern Poland, in the area where hard coal has been mined for almost two hundred years, which largely serves as a source of heating for houses and flats. 360 buildings in 6 groups of 60 buildings were examined in the selected city, which allowed to distinguish 3 different areas in terms of the quality of the living environment depending on the technical condition of buildings, the method of heating and location. To a large extent, determinants are the existing spatial and geophysical conditions of a given location. Many research and reports on the living environment do not take into account the factors mentioned, focusing only on the statistical data of pollution, excluding spatial factors. In the research presented, the author, taking into account location variables, shows differences in the measurements of air pollution in relation to the designated location zones depending on the morphological structure of the building, the degree of its modernization and the types of heating used in buildings.

Air pollution has been a major environmental issue worldwide from the last few decades. It is a man-made issue that has a serious harmful impact on the environment and the health of humans. There are different sources of emission, but industrial processes and motor vehicles contribute to a chief part of air pollution. It has acute as well as chronic effects on the health of humans and affects different organs. It is thought the main environmental risk factor in the incidence and progression of several diseases such as lung cancer, asthma, Alzheimer's and Parkinson's diseases. Long-term exposure to air pollution has different toxicological impacts on humans such as respiratory and cardiovascular diseases, neuropsychiatric complications, eye irritation and skin diseases. As per the study by the World Health Organization (WHO), nitrogen oxides (NOx), carbon monoxide (CO), ozone (O₃), sulfur dioxide (SO₂), volatile organic compounds (VOCs) and heavy metals are the major air contaminants. These pollutants are different in their properties, composition and time of disintegration. The aim of this study is to review the different sources, types, impacts, challenges and mitigation of air pollution in detail.

Background: This study examines the relationship between energy usage, health issues, and pro-environmental behavior (PEB) in Kyrgyzstan, amidst the country's commitment to transition from coal-based energy to renewable sources in line with the Paris Agreement. The purpose is to investigate citizens' attitudes towards PEB and their intentions to engage in environmentally friendly actions, focusing on gas, electricity, and coal. Methods: Drawing upon the Theory of Planned Behavior (TPB) framework, a survey was conducted among 1,455 respondents to explore attitudes towards PEB and energy sources' impact on health issues. Results: Decarbonization efforts in Kyrgyzstan and Central Asia are in their early stages, with coal remaining a primary energy source. The study emphasizes the importance of governmental policies and citizen action in achieving decarbonization goals. Rising electricity costs outweigh the increase in indirect energy costs for food, posing challenges for households in adapting to changing energy dynamics. Conclusions: Targeted interventions and communication strategies are crucial to promote pro-environmental behavior and facilitate the transition to sustainable energy sources. Understanding the relationships between health concerns, air pollution awareness, PEB, and energy source choices can inform policymakers and organizations in their efforts to ensure a sustainable and healthy future for Kyrgyzstan and other Central Asian countries.