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Studies on Cement Pastes Exposed to Water and Solutions of Biological Waste
The paper presents studies on the early stages of biological corrosion of ordinary Portland cements (OPC) subjected to the reactive media from the agricultural industry. For ten months, cement pastes of CEM I type with various chemical compositions were exposed to pig slurry, and water was used as a reference. The phase composition and structure of hydrating cement pastes were characterized by X-ray diffraction (XRD), thermal analysis (DTA/TG/DTG/EGA), and infrared spectroscopy (FT-IR). The mechanical strength of the cement pastes was examined. A 10 to 16% decrease in the mechanical strength of the samples subjected to pig slurry was observed. The results indicated the presence of thaumasite (C3S·CO2·SO3·15H2O) as a biological corrosion product, likely formed by the reaction of cement components with living matter resulting from the presence of bacteria in pig slurry. Apart from thaumasite, portlandite (Ca(OH)2)—the product of hydration—as well as ettringite (C3A·3CaSO4·32H2O) were also observed. The study showed the increase in the calcium carbonate (CaCO3) phase. The occurrence of unreacted phases of cement clinker, i.e., dicalcium silicate (C2S) and tricalcium aluminate (C3A), in the samples was confirmed. The presence of thaumasite phase and the exposure condition-dependent disappearance of CSH phase (calcium silicate hydrate), resulting from the hydration of the cements, were demonstrated.
Neural Modelling in the Exploration of the Biomethane Potential from Cattle Manure: A Case Study on Herds Structure from Wielkopolskie, Podlaskie, and Mazowieckie Voivodeships in Poland
In the presented study, data on the size and structure of cattle herds in Wielkopolskie, Podlaskie, and Mazowieckie voivodeships in 2019 were analyzed and subjected to modelling with the use of artificial intelligence, namely artificial neural networks (ANNs). The potential amount of biogas (m3) from cattle manure and slurry for the analyzed provinces was as follows: for the Mazowieckie Voivodeship, 800,654,186 m3; for the Podlaskie voivodeship, 662,655,274 m3; and for the Wielkopolskie voivodeship, 657,571,373 m3. Neural modelling was applied to find the relationship between the structure of the herds and the amount of generated slurry and manure (biomethane potential), as well as to indicate the most important animal types participating in biogas production. In each of the analyzed cases, the three-layer MLP perceptron with a single hidden layer proved to be the most optimal network structure. Sensitivity analysis of the generated models concerning herd structure showed a significant contribution of dairy cows to the methanogenic potential for both slurry and manure. The amount of slurry produced in the Mazowieckie and Wielkopolskie voivodeships was influenced in turn by heifers (both 6–12 and 12–18 months old) and bulls 12–24 months old, and in the Podlaskie voivodeship by calves and heifers 6–12 months old. As for manure, in addition to cows, bulls 12–24 months old and heifers 12–18 represented the main factor for Mazowieckie and Wielkopolskie voivodeships, and heifers (both 6–12 and 12–18 months old) for Podlaskie voivodeship.
Chemical composition of Lavatera thuringiaca L. biomass ash after pre-sowing stimulation of seeds with He–Ne laser light
AbstractThe article presents the effect of pre-sowing Lavatera thuringiaca L. seeds stimulation with He–Ne laser light on the chemical composition (P, S, K, Ca, Mn, Fe, Ni, Cu and Zn content) of ash obtained after combustion of shoots of different ages. Results varied, but it was confirmed that pre-sowing exposure of seeds to this physical factor for 10-min has the most pronounced effect on K, Cu and Mn content increase (6%, 20%, 31% increase respectively) in the ash after the first year of vegetation as well as on Cu, K and Zn content increase (9%, 19%, 22% increase respectively) after the second year of vegetation. However, 30-min stimulation significantly increases Ca (8%), Mn (20%) and Fe (72%) content in ash after the second year as well as results in ash richer in Ca (22%), P (48%), K (70%) and Zn (95%) after the third year of Lavatera vegetation. The pre-sowing application of He–Ne laser light depending on the time of stimulation can intensify the content of preferable macro- and microelement groups in Lavatera ash, in respective cultivation years. It can be an innovative method of biomass ash enhancement and its more effective use in agriculture as commercial fertilizers substitute.
Factors affecting the concentration of metals and metalloids in the kidneys of a top predator, the Eurasian Buzzard (Buteo buteo) wintering in farmland in Poland
AbstractDuring late autumn and winter, raptors in the western Palearctic face challenges due to food scarcity and dropping temperatures. That time they can be exposed to various elements including toxic ones ingested with food. Kidney samples from 22 females and 19 males of a medium-sized raptor, the Common Buzzard Buteo buteo found dead in farmland of Eastern Poland in winter were analyzed for a concentration of 21 elements. Elemental concentrations were analyzed regarding the age and sex of birds. Results revealed that only 4.9% of individuals had kidney lead levels exceeding 8.0 mg, while 9.8% showed cadmium levels above 8.0 mg/kg, indicating potential poisoning. The study also highlighted the limited entry of arsenic into agricultural ecosystems exploited by Common Buzzards. Sex differences were noted, with females accumulating more lead and vanadium than males which can be associated with foraging niche partitioning between sexes driven by body size dimorphism. Sulfur showed complex interactions with cadmium, mercury, and zinc, with a positive correlation between sulfur and zinc levels in the kidneys, emphasizing dietary needs during food scarcity. A positive correlation was found between zinc and lead concentrations, indicating zinc’s role in mitigating lead’s impact. The study also revealed positive correlations between selenium and highly toxic elements like mercury (Spearman correlation, rs = 0.41) and cadmium (rs = 0.51), suggesting a mitigating effect of selenium on exposure to heavy metals. This study enhances understanding of year-round environmental contamination exposure for raptors and sheds light on bioaccumulation in a top predator.
Effects of pH and palmitic acid on the organization and stability of lutein in the phosphatidylcholine membranes – Spectroscopic studies
From Waste to Renewables: Challenges and Opportunities in Recycling Glass Fibre Composite Products from Wind Turbine Blades for Sustainable Cement Production
The progress of civilization, driven significantly by the widespread adoption of electricity, has impacted various aspects of life, from household operations to industrial activities. Consequently, there has been a notable increase in waste production across different sectors of the economy. Among used materials, composite products reinforced with glass fibres stand out due to their prevalent use in numerous industries. While offering strength and durability, they pose disposal challenges due to their complex composition, making recycling difficult and contributing to waste accumulation in landfills or to environmental contamination. Industrialised nations wrestle with balancing economic growth and environmental sustainability, aiming to reduce the ecological footprint of industrial activities. Efforts to promote recycling, develop alternative materials, and improve waste management practices are crucial for mitigating the environmental impact of civilisation’s progress. This article presents methods of disposing of post-operation wind turbine blades, focusing on recycling glass and glass fibre as secondary raw materials. We discuss technological, normative, and economic challenges and emphasise the need for ongoing research and innovation in waste management practices. We examine the use of glass and glass fibres in cement production and advocate for sustainable principles in the renewable energy industry, aligning industrial endeavours with ecological sustainability for a greener future.
Synthesis and Investigation of the Hydration Degree of CA2 Phase Modified with Boron and Fluorine Compounds
This study investigated the effect of fluoride and boron compound additives on the synthesis and hydration process of calcium aluminate (CA2). The analysis showed that the temperature of the full synthesis of CA2 without mineralizing additives was 1500 °C. However, the addition of fluorine and boron compounds at 1% and 3% significantly reduced the synthesis temperature to a range of 1100–1300 °C. The addition of fluoride compounds did not result in the formation of fluoride compounds from CaO and Al2O3, except for the calcium borate phase (Ca3(BO3)2) under certain conditions. In addition, the cellular parameters of the synthesized calcium aluminate phases were not affected by the use of these additives. Hydration studies showed that fluoride additives accelerate the hydration process, potentially improving mechanical properties, while boron additives slow down the reaction with water. These results highlight the relevance of fluoride and boron additives to the synthesis process and hydration kinetics of calcium aluminate, suggesting the need for further research to optimize their application in practice. TG studies confirmed the presence of convergence with respect to X-ray determinations made. SEM, EDS and elemental concentration maps confirmed the presence of a higher Al/Ca ratio in the samples and also showed the presence of hexagonal and regular hydration products.
Neural Modelling from the Perspective of Selected Statistical Methods on Examples of Agricultural Applications
Modelling plays an important role in identifying and solving problems that arise in a number of scientific issues including agriculture. Research in the natural environment is often costly, labour demanding, and, in some cases, impossible to carry out. Hence, there is a need to create and use specific “substitutes” for originals, known in a broad sense as models. Owing to the dynamic development of computer techniques, simulation models, in the form of information technology (IT) systems that support cognitive processes (of various types), are acquiring significant importance. Models primarily serve to provide a better understanding of studied empirical systems, and for efficient design of new systems as well as their rapid (and also inexpensive) improvement. Empirical mathematical models that are based on artificial neural networks and mathematical statistical methods have many similarities. In practice, scientific methodologies all use different terminology, which is mainly due to historical factors. Unfortunately, this distorts an overview of their mutual correlations, and therefore, fundamentally hinders an adequate comparative analysis of the methods. Using neural modelling terminology, statisticians are primarily concerned with the process of generalisation that involves analysing previously acquired noisy empirical data. Indeed, the objects of analyses, whether statistical or neural, are generally the results of experiments that, by their nature, are subject to various types of errors, including measurement errors. In this overview, we identify and highlight areas of correlation and interfacing between several selected neural network models and relevant, commonly used statistical methods that are frequently applied in agriculture. Examples are provided on the assessment of the quality of plant and animal production, pest risks, and the quality of agricultural environments.
Dimension Reduction of Digital Image Descriptors in Neural Identification of Damaged Malting Barley Grains
The paper covers the problem of determination of defects and contamination in malting barley grains. The analysis of the problem indicated that although several attempts have been made, there are still no effective methods of identification of the quality of barley grains, such as the use of information technology, including intelligent sensors (currently, quality assessment of grain is performed manually). The aim of the study was the construction of a reduced set of the most important graphic descriptors from machine-collected digital images, important in the process of neural evaluation of the quality of BOJOS variety malting barley. Grains were sorted into three size fractions and seed images were collected. As a large number of graphic descriptors implied difficulties in the development and operation of neural classifiers, a PCA (Principal Component Analysis) statistical method of reducing empirical data contained in the analyzed set was applied. The grain quality expressed by an optimal set of transformed descriptors was modelled using artificial neural networks (ANN). The input layer consisted of eight neurons with a linear Postsynaptic Function (PSP) and a linear activation function. The one hidden layer was composed of sigmoid neurons having a linear PSP function and a logistic activation function. One sigmoid neuron was the output of the network. The results obtained show that neural identification of digital images with application of Principal Component Analysis (PCA) combined with neural classification is an effective tool supporting the process of rapid and reliable quality assessment of BOJOS malting barley grains.
Interactions between surface properties of pristine coals and the intrinsic microbial communities involved in methane formation
Changes in the Phase Composition of Calcium Aluminoferrites Based on the Synthesis Condition and Al2O3/Fe2O3 Molar Ratio
The presented work concerns the study of the changes in the phase composition of calcium aluminoferrites which depend on the synthesis conditions and the selection of the Al2O3/Fe2O3 molar ratio (A/F). The A/F molar ratio extends beyond the limiting composition of C6A2F (6CaO·2Al2O3·Fe2O) towards phases richer in Al2O3. An increase in the A/F ratio above unity favours the formation of other crystalline phases such as C12A7 and C3A, in addition to calcium aluminoferrite. Slow cooling of melts characterised by an A/F ratio below 0.58, results in the formation of a single calcium aluminoferrite phase. Above this ratio, the presence of varying contents of C12A7 and C3A phases was found. The process of rapid cooling of the melts with an A/F molar ratio approaching the value of four favours the formation of a single phase with variable chemical composition. Generally, an increase in the A/F ratio above the value of four generates the formation of a calcium aluminoferrite amorphous phase. The rapidly cooled samples with compositions of C22.19A10.94F and C14.61A6.29F were fully amorphous. Additionally, this study shows that as the A/F molar ratio of the melts decreases, the elemental cell volume of the calcium aluminoferrites decreases.
Effect of Variable Synthesis Conditions on the Formation of Ye’elimite-Aluminate-Calcium (YAC) Cement and Its Hydration in the Presence of Portland Cement (OPC) and Several Accessory Additives
In the presented study, ye’elimite-aluminate-calcium (YAC) cement was synthesized. Complete synthesis of crystalline phases was achieved at a temperature of 1300 °C, which is 150 °C lower than the temperature standardly used in the processes of obtaining calcium aluminate cements (CAC). The greatest amount of ye’elimite phase (Klein complex), roughly 87% by mass, was acquired utilizing a sulphur ion transporter derived from artificial dihydrate gypsum obtained in the flue gas desulphurization process (variation I). In the case of anhydrite, the amount of synthesized crystalline ye’elimite in the clinker was 67% by weight (variant II). Depending on the synthesis conditions in the clinkers, the quantity of obtained calcium aluminates (C12A7, CA, and CA2) ranged from 20 to 40% by weight. Studies on the hydration process of YAC cement samples showed that the main products are hydrated calcium aluminates and dodecahydrate calcium alumino-sulphate. In sinters of YAC and OPC, no crystalline ettringite was observed. Hydration analysis of Chinese cement revealed the presence of crystalline ettringite and dodecahydrate calcium alumino-sulphate, as well as hydrated calcium silicates of the CSH type accompanied with pseudo-crystalline Al(OH)3. The obtained clinkers from variants I and II constitute a special binder, which, due to its phase composition after hydration, can be used in the construction of reactors for biogas production in eco-energy applications.
Identification of Factors Affecting Environmental Contamination Represented by Post-Hatching Eggshells of a Common Colonial Waterbird with Usage of Artificial Neural Networks
Artificial Neural Networks are used to find the influence of habitat types on the quality of the environment expressed by the concentrations of toxic and harmful elements in avian tissue. The main habitat types were described according to the Corine Land Cover CLC2012 model. Eggs of free-living species of a colonial waterbird, the grey heron Ardea cinerea, were used as a biological data storing media for biomonitoring. For modeling purposes, pollution indices expressing the sum of the concentration of harmful and toxic elements (multi-contamination rank index) and indices for single elements were created. In the case of all the examined indices apart from Cd, the generated topologies were a multi-layer perceptron (MLP) with 1 hidden layer. Interestingly, in the case of Cd, the generated optimal topology was a network with a radial basis function (RBF). The data analysis showed that the increase in environmental pollution was mainly influenced by human industrial activity. The increase in Hg, Cd, and Pb content correlated mainly with the increase in the areas characterized by human activity (industrial, commercial, and transport units) in the vicinity of a grey heron breeding colony. The decrease in the above elements was conditioned by relative areas of farmland and inland waters. Pollution with Fe, Mn, Zn, and As was associated mainly with areas affected by industrial activities. As the location variable did not affect the quality of the obtained networks, it was removed from the models making them more universal.
Germination Energy, Germination Capacity and Microflora of Allium cepa L. Seeds after RF Plasma Conditioning
This paper presents the results of an experiment on the effect of the cold plasma (He+O2 or He+Air) pre-sowing stimulation of seeds of the Wolska cultivar of onion on the process of their germination. Four groups of seeds characterized by different exposure times (60, 120, 240 and 480 s) were used. Untreated seeds were used as a control. The distance between the electrode and the tested material was 50 mm. Pre-sowing plasma stimulation improved germination parameters such as germination capacity and germination energy for all the tested groups relative to the control. The highest fractions of germinated seeds were observed for an exposure time of 120 s. Analysis of the data showed a statistically significant impact of RF plasma on the seed germination parameters of the onion. SEM analysis showed that the interaction with plasma produced tension in the cells, leading to a change in their shape. No visible damage to the onion seed cells was observed, apart from the effect of depletion of the upper wax layer. The best influence on pathogenic fungi was when the group of seeds underwent 240 and 480 s of exposure to plasma fumigation, especially using the He+Air RF plasma jet.
Concentration of metals and metalloids in livers of birds of various foraging guilds collected during the autumn migration period in Poland
Sustainable Management of Photovoltaic Waste Through Recycling and Material Use in the Construction Industry
The rapid expansion of photovoltaic (PV) technology as a source of renewable energy has resulted in a significant increase in PV panel waste, creating environmental and economic challenges. A promising strategy to address these challenges is the reuse of glass waste from decommissioned PV panels as a component of cementitious materials. This review explores the potential of integrating glass waste from PV panels into cementitious materials, focusing on its impact on their mechanical, thermal, and durability properties. This analysis includes various methods of processing PV glass waste, such as crushing and grinding, to obtain the desired particle size for cementitious applications. It goes on to analyze how advances in cementitious materials can facilitate the incorporation of PV glass waste, helping to improve properties such as compressive strength, workability, and setting time. In addition, this review makes a detailed analysis of the long-term sustainability and environmental benefits of PV glass waste, highlighting its potential to reduce the carbon footprint of cementitious materials. Incorporating PV glass waste can improve certain properties of cementitious materials, resulting in increased durability and improved thermal insulation, while contributing to waste reduction and resource conservation. This review highlights the importance of developing standardized recycling methods and integration processes and identifies areas for further research to optimize the use of PV glass waste in cement formulations. Ultimately, the sustainable integration of PV glass panel waste into cementitious materials is a viable approach to promote green building practices and support a circular economy in the construction industry.
