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INTRODUCTION AND OBJECTIVE: Snow cover serves as a unique indicator of environmental pollution in both urban and rural areas. As a seasonal cover, it accumulates various pollutants emitted into the atmosphere, thus providing insight into air pollution types and the relative contributions of different pollution sources. The aim of the study is to analyze the distribution of trace elements in snow cover to assess the anthropogenic influence on pollution levels, and better understand ecological threats. MATERIAL AND METHODS: The study was conducted in rural areas around the village of Wólka in the Lublin Province of eastern Poland, and in urban districts of the city of Lublin, capital of the Province. Samples were analyzed using Inductively Coupled Plasma-Mass Spectrometry, the Enrichment Factor (EF), and ecological risk indices (RI), were calculated to evaluate the contamination and potential ecological risks posed by the metals. RESULTS: The findings indicate higher concentrations of metals like sodium and iron in urban areas, likely due to road salt use and industrial activity, respectively. Enrichment factors showed significant anthropogenic contributions, particularly for metals like sodium, zinc, and cadmium, which had EF values substantially above natural levels. The potential ecological risk assessment highlighted a considerable ecological threat in urban areas compared to rural settings, primarily due to higher concentrations of metals. CONCLUSIONS: The variation in metal concentrations between urban and rural snow covers reflects the impact of human activities on local environments. Urban areas showed higher pollution levels, suggesting the need for targeted pollution control policies to mitigate the adverse ecological impacts. This study underscores the importance of continuous monitoring and comprehensive risk assessments to effectively manage environmental pollution.

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INTRODUCTION AND OBJECTIVE: The article analyzes the content of heavy metals and standard physical as well as chemical pollution indicators in different types of sediments from stormwater, combined sewer and sanitary sewer systems. MATERIAL AND METHODS: Nickel, lead, chromium, copper, zinc and cadmium, as well as standard physical and chemical pollution indicators, were determined in sewage sediments. Aqueous extracts of sediments samples, taken from storm water sewer inlet sediments traps, storm sewers, sanitary sewers and combined sewers, were prepared in accordance with PN-EN 12457-2:2006. After mineralization, the concentrations of the metals: nickel, lead, chromium, copper, zinc and cadmium in the extracts were determined using the inductively coupled plasma emission spectroscopy technique. RESULTS: The results were analyzed with a non-metric multidimensional scaling algorithm. The heavy metal content was variable depending on the sediments collection site. The heavy metals nickel, lead, chromium, copper, zinc and cadmium were found in the sediments from stormwater inlets, storm sewer and sanitary sewer channels, with variability in the concentration of individual metals. The sediments from the flushing of sanitary sewers and combined sewers did not contain cadmium. CONCLUSIONS: The content of heavy metals in sediments varied depending on the sampling location and type of sewer system, indicating the need for detailed monitoring to identify the sources of emissions. Sediments from stormwater sewers have higher concentrations of heavy metals, with those from sewer inlets showing zinc concentrations exceeding regulatory limits, highlighting the variability and potential environmental impact of different sewer systems.

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Currently, e-noses are used for measuring odorous compounds at wastewater treatment plants. These devices mimic the mammalian olfactory sense, comprising an array of multiple non-specific gas sensors. An array of sensors creates a unique set of signals called a "gas fingerprint", which enables it to differentiate between the analyzed samples of gas mixtures. However, appropriate advanced analyses of multidimensional data need to be conducted for this purpose. The failures of the wastewater treatment process are directly connected to the odor nuisance of bioreactors and are reflected in the level of pollution indicators. Thus, it can be assumed that using the appropriately selected methods of data analysis from a gas sensors array, it will be possible to distinguish and classify the operating states of bioreactors (i.e., phases of normal operation), as well as the occurrence of malfunction. This work focuses on developing a complete protocol for analyzing and interpreting multidimensional data from a gas sensor array measuring the properties of the air headspace in a bioreactor. These methods include dimensionality reduction and visualization in two-dimensional space using the principal component analysis (PCA) method, application of data clustering using an unsupervised method by Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, and at the last stage, application of extra trees as a supervised machine learning method to achieve the best possible accuracy and precision in data classification.

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INTRODUCTION AND OBJECTIVE: The identification and understanding of interactions between contaminants present in sediments from stormwater and combined sewer systems is a prerequisite for their proper management, and provides a basis for developing effective strategies to minimize their negative impact on humans and the environment. The studypresents the method described in PN-EN 12457-2:2006 as a possible technique for studying the mobility of heavy metals in sediments from stormwater and combined sewer systems. MATERIAL AND METHODS: The presented PN-EN 12457-2:2006 method is a relatively simple technique for preparing extracts for the determination of heavy metals in sediments from stormwater and combined sewer systems, consisting of one-step leaching, which is quick to perform. In addition, it allows determination of the characteristics of the samples to be analyzed, and indicates procedures and tests for evaluating hazardous substances released from solid waste. RESULTS: The results of the concentrations of leached heavy metals: chromium, copper, nickel, lead and zinc, obtained in the study, corresponded to the concentrations of the exchange fraction of sludge when using the recommended method with sequential extraction (Student's t-test, p=0.263). In the literature review conducted, no papers were found on the application of the leaching method to prepare extracts for the determination of heavy metals in sediments from stormwater and combined sewer systems. CONCLUSIONS: The PN-EN 12457-2:2006 method is capable of providing important data on the potential risks to humans and the environment from the presence of contaminants in sewage sludge.

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Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors' applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.

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Macrophytes are one of the important indicators used in assessing the anthropic impact on aquatic ecosystems. The structure of macrophyte communities of two rivers were compared by species composition, dominant species and projective cover using statistical methods. It is shown that the influence of storm runoff on these rivers is manifested in the form of a change in the dominant species composition. Based on the statistical analysis carried out, it can be argued that, despite the peculiarities of the flora composition of each of the rivers, the influence of storm runoffs largely neutralizes this specificity, determining the situation in local areas immediately below the runoff. In the area of the effluent discharge the dominance of individual species and an increase in the area overgrown with macrophytes was observed. In the area of stormwater discharge on the Psel River, species were usually present: Nuphar lutea, Ceratophyllum demersum, Myriophyllum spicatum and on the Bystrica River-Glyceria maxima, Sagitaria sagittiformis, Stuckenia pectinata and Potamogeton crispus. The use of the NMDS method has been found to provide good insight into the structural rearrangements in macrophyte communities affected by runoff from stormwater systems.

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The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.

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The work represents a successful attempt to combine a gas sensors array with instrumentation (hardware), and machine learning methods as the basis for creating numerical codes (software), together constituting an electronic nose, to correct the classification of the various stages of the wastewater treatment process. To evaluate the multidimensional measurement derived from the gas sensors array, dimensionality reduction was performed using the t-SNE method, which (unlike the commonly used PCA method) preserves the local structure of the data by minimizing the Kullback-Leibler divergence between the two distributions with respect to the location of points on the map. The k-median method was used to evaluate the discretization potential of the collected multidimensional data. It showed that observations from different stages of the wastewater treatment process have varying chemical fingerprints. In the final stage of data analysis, a supervised machine learning method, in the form of a random forest, was used to classify observations based on the measurements from the sensors array. The quality of the resulting model was assessed based on several measures commonly used in classification tasks. All the measures used confirmed that the classification model perfectly assigned classes to the observations from the test set, which also confirmed the absence of model overfitting.

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The protection of building elements exposed to the weather using hydrocarbon-based agents is a comprehensive group of analyses. These agents are characterized by very high chemical resistance, waterproofness, as well as adhesion to surfaces made of various materials, i.e., concrete, steel, ceramics and wood. Modification of adhesion, which ultimately leads to an increase in the durability of a protective/face coating made of such a material, can lead to a longer life of these layers and a less frequent need for replacement or restoration. The following paper describes an experimental research program on the possibility of increasing the adhesion and durability of epoxy resin modified with the use of powder fillers. The resin can be used as a protective or top coat on the surface of concretes or mortars. The main objective of the study was to increase the adhesion of the resin to the concrete substrate, modified by grinding and sandblasting to increase the roughness. For the series studied, both the changes in physicochemical parameters, which determine how the resin penetrates the irregularities of the substrate and mechanical parameters, which mainly determine the durability of the layer made in this way, were identified. A modified version of the pull-off test was used as a method to directly evaluate the effectiveness of the modified resins.

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An original method for analyzing the influence of the meteorological, as well as physical-geographical conditions on the flooding of stormwater in small urban catchment areas is proposed. A logistical regression model is employed for the identification of the flooding events. The elaborated model enables to simulate the stormwater flooding in a single rainfall event, on the basis of the rainfall depth, duration, imperviousness of the catchment and its spatial distribution within the analyzed area, as well as the density of the stormwater network. The rainfall events are predicted considering the regional convective rainfall model for 32 rain gauges located in Poland, based on 44 years of rainfall data. In the study, empirical models are obtained to calculate the rainfall duration conditioning the flooding of stormwater in a small urban catchment area depending on the characteristics of the examined urban basins. The empirical models enabling to control the urbanization process of catchment areas, accounting for the local rainfall and meteorological characteristics are provided. The paper proposes a methodology for the identification of the areas especially sensitive to stormwater flooding in small urban catchment areas depending to the country scale. By employing the presented methodology, the regions with most sensitive urban catchments are identified. On this basis, a ranking of towns and cities is determined from the most sensitive to flooding in small urban catchment areas to the regions where the risk of flooding is lower. Using the method developed in the paper, maximum impervious catchment area are determined for the selected regions of the country, the exceedance of which determines the occurrence of stormwater flooding.

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In this study, the possibility of using mixing water containing O2 and O3 micro-nano bubbles (M-NBs) in concrete technology was investigated. In particular, the effect of micro-nano bubbles on the durability and frost resistance of concrete was analyzed. Concretes with two types of micro-nano bubbles were studied. The physical properties of both the modified concretes and the reference concrete were determined, i.e., specific and apparent density, porosity, weight absorption and coefficient of water absorption. Mechanical parameters based on compressive and flexural strength were tested after 14 and 28 days of curing. Concrete durability was determined on the basis of frost resistance and resistance to salt crystallization. The pore distribution in the cement matrix was determined based on porosimetry studies. The use of water with micro-nano bubbles of O2 and O3, among others, contributed to a reduction in the water absorption coefficient from 42.7% to 52.3%, in comparison to the reference concrete. The strength characterizing the concrete with O3 increased by 61% after 28 days, and the frost resistance after 150 F-T cycles increased by 2.4 times. Resistance to salt crystallization improved by 11% when water with O3 was used.

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A method for assessing the degree of impact of wastewater treatment plant discharge on receiving rivers was proposed, based on the structural indicators of the population of ciliated protozoa. It was shown that the ratio of attached, crawling and free-swimming forms in bottom sediments changes under the influence of discharge. In the points subject to organic pollution, the share of attached filter-feeding bacteriovorous ciliates increases in the assemblage of ciliated protozoa. The proposed Attached Form Index (AFI) takes this ratio into account. The use of AFI makes it possible to assess the restructuring of the assemblage of ciliated protozoa under the influence of point sources of pollution, to establish a zone of negative influence of runoff, to assess the degree of restoration of the aquatic ecosystem, as the influence of the pollution source weakened.

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Illitic clays are the commonly used material in building ceramics. Zeolites are microporous, hydrated crystalline aluminosilicates, they are widely used due to their structure and absorption properties. In this study, illitic clay (Füzérradvány, Hungary) was mixed with natural zeolite (Nizný Hrabovec, Slovakia) with up to 50 wt.% of zeolite content. The samples were submitted to thermal analyses, such as differential thermal analysis, differential scanning calorimetry, thermogravimetry, and dilatometry. In addition, the evolution of thermal diffusivity, thermal conductivity, and specific heat capacity in the heating stage of firing were measured and discussed. The amount of the physically bound water in the samples increased along with the amount of zeolite. The temperature of the illite dehydroxylation (peak temperature) was slightly shifted to lower temperatures, from 609 °C to 575 °C (for sample IZ50). On the other hand, the mass loss and the shrinkage of the samples significantly increased with the zeolite content in the samples. Sample IZ50 reached 10.8% shrinkage, while the sample prepared only from the illitic clay contracted by 5.8%. Nevertheless, the temperature of the beginning of the sintering (taken from the dilatometric curves) decreased from 1021 °C (for illitic clay) to 1005 °C (for IZ50). The thermal diffusivity and thermal conductivity values decreased as the amount of zeolite increased in the samples, thus showing promising thermal insulating properties.

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The article concerns the issue of non-invasive moisture sensing in building materials. Two techniques that enable evaluating the value of the relative permittivity of the material, being the measure of porous material moisture, have been utilized for the research. The first is the microwave technique that utilizes the non-contact measurement of velocity of microwave radiation across the tested material and the second is the time domain reflectometry (TDR) technique based on the measurement of electromagnetic pulse propagation time along the waveguides, being the elements of sensor design. The tested building material involved samples of red ceramic brick that differed in moisture, ranging between 0% and 14% moisture by weight. The main goal of the research was to present the measuring potential of both techniques for moisture evaluation as well as emphasize the advantages and disadvantages of each method. Within the research, it was stated that both methods provide similar measuring potential, with a slight advantage in favor of a microwave non-contact sensor over surface TDR sensor designs.

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The demand for water and energy in today's developing world is enormous and has become the key to the progress of societies. Many methods have been developed to desalinate water, but energy and environmental constraints have slowed or stopped the growth of many. Capacitive Deionization (CDI) is a very new method that uses porous carbon electrodes with significant potential for low energy desalination. This process is known as deionization by applying a very low voltage of 1.2 volts and removing charged ions and molecules. Using capacitive principles in this method, the absorption phenomenon is facilitated, which is known as capacitive deionization. In the capacitive deionization method, unlike other methods in which water is separated from salt, in this technology, salt, which is a smaller part of this compound, is separated from water and salt solution, which in turn causes less energy consumption. With the advancement of science and the introduction of new porous materials, the use of this method of deionization has increased greatly. Due to the limitations of other methods of desalination, this method has been very popular among researchers and the water desalination industry and needs more scientific research to become more commercial.

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The article concerns the electric techniques of moisture detection that are based on the evaluation of the apparent permittivity of the tested medium. The main goal of the research was to evaluate the non-invasive Time Domain Reflectometry (TDR) sensors' sensitivity by measuring the span of elements and material moisture. To that aim, two non-invasive sensor designs were investigated for their sensitivity in the evaluation of the apparent permittivity value of aerated concrete. Sensors A and B were characterized by the spacing between the measuring elements equal to 30 mm and 70 mm, respectively. The tested samples differed in moisture, ranging between 0 and 0.3 cm3/cm3 volumetric water content. Within the research, it was stated that in the case of the narrower sensor (A), the range of the sensor equals about 30 mm, and in the case of the wider design (B), it equals about 50 mm. Additionally, it was stated that material moisture influences the range of sensor influence. In the case of the dry and low-saturated material, it was not possible to evaluate the range of sensor sensitivity using the adopted method, whereas the range of sensor signal influence was visible for the moist material.

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The aim of the research presented in the article was to check the differences in the hygro-thermal and mechanical properties of hemp-lime composites with different shives fractions, depending on the direction of mixture compaction. The research part of the paper presents the preparation method and investigation on the composites. Thermal conductivity, capillary uptake, as well as flexural and compressive strengths were examined. Additionally, an analysis of the temperature distribution in the external wall insulated with the tested composites was performed. The results confirm that the direction of compaction influences the individual properties of the composites in a similar way, depending on the size of the shives. The differences are more pronounced in the case of the composite containing longer fractions of shives. Both thermal conductivity of the material and the capillary uptake ability are lower in the parallel direction of the compaction process. Composites exhibit greater stiffness, but they fail faster with increasing loads when loaded in the direction perpendicular to compaction.

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The paper presents the experimental studies on the effect of the water containing micro-nano bubbles of various gases on the physico-mechanical properties of lime-cement mortars. In total, 7 types of mortars were prepared: with water containing the micro-nano bubbles of O2, O3 or CO2 as 50% or 100% substitute of ordinary mixing water (tap water) and the reference mortar prepared using tap water. In order to determine the influence of water with micro-nano bubbles of gases, the consistency of fresh mortar and the physical properties of hardened mortar, i.e., specific and apparent density, total porosity, water absorption by weight and capillary absorption, were established. The mechanical strength of the considered mortars was studied as well by conducting the tests for flexural and compressive strengths following 14, 28 and 56 days. Reduced workability and capillary absorption were observed in the modified mortars within the range of 0.9-8.5%. The mortars indicated an increase in the flexural strength after 28 days ranging from 3.4% to 23.5% and improved compressive strength in 1.2-31%, in comparison to the reference mortar. The conducted studies indicated increased flexural and compressive strengths along with the share of micro-nano bubbles of gases in the mixing water.

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The paper presents the results of research concerning three fiber materials-mineral wool, hemp fiber and wood wool-as loose-fill thermal insulation materials. The analysis used the material parameters determined in previous works conducted by the authors, such as thermal conductivity and air permeability in relation to bulk density. These materials exhibit open porosity; thus, convection is an essential phenomenon in the heat transfer process. The paper aimed at conducting thermal simulations of various frame wall variants which were filled with the above-mentioned insulation materials. The simulations were performed with the Control Volume Method using the Delphin 5.8 software. The studies accounted for the effect of wind pressure and the time of its influence on a wall insulated by means of fiber material with a thickness of 150 as well as 250 mm. The simulation enabled us to obtain such data as maximal R-value reduction and time to return to equilibrium after filtration for the analyzed materials. The study proved that heat transfer in these insulations strongly depends on the bulk density, thickness of the insulation and wind pressure. The decrease in R is reduced as the density increases. This results from the decreased air permeability characterizing the material. Wind washing causes lower R reduction than air filtration in all models. The greater the thickness, the longer it takes for the models to return to the equilibrium state following air filtration (and wind washing). This period is comparable for air filtration and wind washing. Hemp fibers were characterized with the strongest susceptibility to air filtration; in the case of wood wool, it was also high, but lower than for hemp fibers, while mineral wool was characterized with the lowest.

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The effects of two powdered mineral materials (powdered ceramsite and powdered limestone) on aerobic granulation of sludge were evaluated. The experiment was conducted on a laboratory scale bioreactors treating wastewater for 89 days. Three granular sequencing batch reactors (GSBRs) were operated at the lowest optimal organic loading rate (OLR) of 2.55 g COD/(L∙d). In the control reactor (R1), the mean diameter (d) of the biomass ranged from 124.0 to 210.0 µm, and complete granulation was not achieved. However, complete granulation did occur in reactors to which either ceramsite (251.9 µm < d < 783.1 µm) or limestone (246.0 µm < d < 518.9 µm) was added. Both powdered materials served as a ballast for the sludge flocs making up the seed sludge. Ceramsite particles also acted as microcarriers of granule-forming biomass. The granules in the reactors with added powdered materials had nonfibrous and smoother surfaces. The reactor with ceramsite exhibited the highest average efficiencies for COD, total nitrogen, and total phosphorus removal (85.4 ± 5.4%, 56.6 ± 10.2%, and 56.8 ± 9.9%, respectively). By contrast, the average nitrification efficiency was 95.1 ± 12.8%.