The article discusses corporate governance, which is a core area of corporate social responsibility (CSR) currently receiving a lot of attention from both researchers and practitioners. The article aims to assess corporate governance in the water and wastewater sector within the context of CSR. The rationale for researching this topic was the lack of scientific studies in this area. The rationale for researching this topic was the lack of scientific studies in this area. To this end, in accordance with the developed research methodology, a literature analysis was used to demonstrate the originality of the problem, as well as the case study method to analyze complex phenomena. To achieve this goal, a survey was conducted of a selected company from the water and sewage industry. Statistical analysis methods were used to verify the research hypotheses. The results show that corporate governance and its individual factors are at a relatively high level. This indicates that the way the organization is managed enables the effective implementation and monitoring of activities related to CSR. From a practical perspective, it is important to further strengthen internal communication, increase legal awareness among staff, and develop managerial skills in the area of employee motivation. The research conducted makes a significant contribution to the development of science, confirming the importance of corporate governance, in which ethics and legal compliance play a key role in shaping a socially responsible organization.

The increasing global shift towards electric vehicles (EVs) has led to a surge in demand for lithium-ion batteries (LIBs), which serve as the primary energy storage solution for modern EVs. However, with this growth comes significant challenges related to battery performance, sustainability, and end-of-life (EOL) management. This article provides a comprehensive review of battery technologies, focusing on advancements in lithium-ion batteries, their degradation mechanisms, and the environmental impact of battery disposal. Additionally, it examines the challenges in EV battery recycling, including safety hazards, disassembly complexities, and economic feasibility. The study explores second-life applications of retired EV batteries in energy storage systems, microgrids, and hybrid renewable energy solutions, emphasizing their potential to extend battery usability while minimizing waste. Furthermore, advanced screening, refurbishment, and material recovery techniques are analyzed to improve resource efficiency and reduce the need for new raw material extraction. By proposing a systematic framework for sustainable battery lifecycle management, this research aims to promote a circular economy, optimize battery reusability, and support the transition towards a cleaner, more sustainable future in electromobility.

This paper explores the application of explainable artificial intelligence (XAI) as a supportive tool for the K-means clustering algorithm which analyze electric vehicles (EVs) chagrining station energy data. Under the investigation the Decision Tree were used to explain the process of clustering assignment. Under the case study investigation six real EVs charging station data were used in area-related approach. The results indicated that proposed solution for arearelated approach can be implemented for real case objects and using XAI. Also the results of clustering indicated the real working condition of ECs charging station that are supportive in decision making.

This study evaluates the feasibility of using pretreated domestic wastewater (PDW) for food production in a hydroponic system. In the face of increasing water shortage problems and rising fertilizer costs, PDW combined with a limited amount of fertilizer is evaluated for its effects on plant growth, biomass yield, and product safety. The results showed that lettuce grown with PDW and mineral fertilizers reached a fresh weight of 116, while the use of organic fertilizers increased the yield to 127 g, compared to only 54 g with raw water. Nitrate concentration (NO3) was higher in lettuce grown with organic fertilizers (1044.33 ± 144.04 mg/kg) than with mineral fertilizers (623.33 ± 85.62 mg/kg), but the values remained well below the acceptable limit of 5000 mg/kg for safe consumption. Analysis of heavy metals confirmed that levels of arsenic, cadmium, mercury, and lead were significantly lower than the maximum permissible values set by FAO and EU regulations. In addition, no phthalates were detected in the lettuce biomass, confirming the safety of the materials used in the hydroponic system. The use of PDW in hydroponic crops significantly reduces dependence on potable water and synthetic fertilizers, contributing to sustainable resource management. This approach not only reduces production costs, but also reduces the water footprint of crops, which is crucial in the context of global water availability problems. The findings support the validity of using PDW in decentralized food production as a sustainable solution for regions facing water and fertilizer shortages. Further research will focus on optimizing nutrient management and environmental conditions to increase system efficiency and food safety.

IntroductionAnalysis of aboveground vegetation and soil seed bank is an important source of data on the state and dynamics of vegetation. It is especially important in landscapes exposed to disturbances, which have lost their functions. For our research, a post-mining area in the region of the Upper Silesian Black Coal Basin was selected, whose relief and ecosystems are strongly disturbed by underground mining and are currently also affected by ongoing climate change.MethodData collection for our research took place in the territory of two waterlogged subsidence basins in the Karvina region, Czech Republic. We evaluated 30 phytosociological releves using techniques of Zurich – Montpellier school and 540 soil cores using cultivation and extraction method.ResultsIn the above-ground vegetation, 115 plant species were identified. By cultivating soil samples, we determined 60 species from 1,487 seedlings, by extraction method 66 species from 5,999 seeds. A statistically significant effect of the presence of the tree layer on the number of species obtained by the extraction method was demonstrated. There is also a statistically significant difference between the selected analysis methods in terms of the length of the captured seeds and their seed mass.DiscussionThe construction of a rarefaction curve demonstrated that the use of cultivation and extraction methods leads to a greater capture of soil seed bank species. The similarity between the species composition of aboveground vegetation and the soil seed bank correspond to similarities observed in other studies from degraded habitats. Very low similarity between the species of the soil seed bank from cultivation and extraction method is probably caused by the highly variable distribution of seeds in the soil in time and space.

The rapid advancement and adoption of electric vehicles (EVs) necessitate innovative solutions to address integration challenges in modern charging infrastructure. Dynamic wireless charging (DWC) is an innovative solution for powering electric vehicles (EVs) using multiple magnetic transmitters installed beneath the road and a receiver located on the underside of the EV. Dynamic charging offers a solution to the issue of range anxiety by allowing EVs to charge while in motion, thereby reducing the need for frequent stops. This manuscript reviews several pivotal areas critical to the future of EV DWC technology such as authentication techniques, blockchain applications, driver identification systems, economic aspects, and emerging communication technologies. Ensuring secure access to this charging infrastructure requires fast, lightweight authentication systems. Similarly, blockchain technology plays a critical role in enhancing the Internet of Vehicles (IoV) architecture by decentralizing and securing vehicular networks, thus improving privacy, security, and efficiency. Driver identification systems, crucial for EV safety and comfort, are analyzed. Additionally, the economic feasibility and impact of DWC are evaluated, providing essential insights into its potential effects on the EV ecosystem. The paper also emphasizes the need for quick and lightweight authentication systems to ensure secure access to DWC infrastructure and discusses how blockchain technology enhances the efficiency, security, and privacy of IoV networks. The importance of driver identification systems for comfort and safety is evaluated, and an economic study confirms the viability and potential benefits of DWC for the EV ecosystem.

This paper explores the application of the K-means clustering algorithm to analyze household energy data, focusing on electricity demand, photovoltaic (PV) generation, and electric vehicle (EV) charging. The objective is to identify distinct patterns of energy usage and generation, which can inform better energy management and decision-making strategies. Using data from a London household, we apply K-means clustering to segment the energy usage into meaningful clusters. The analysis reveals distinct profiles corresponding to different times of day and types of energy consumption and generation. Key findings suggest that clustering can effectively differentiate between high and low usage periods, the impact of PV generation on household energy dynamics, and the charging patterns of EVs. The results of this study provide valuable insights into how households can optimize energy consumption and leverage their PV and EV systems more effectively. Additionally, the paper discusses the implications of these findings for future energy policy and smart grid development. Recommendations are offered for integrating advanced data analytics into residential energy management systems to enhance sustainability and efficiency.

Sentiment analysis (SA) of several user evaluations on e-commerce platforms can be used to increase customer happiness. This method automatically extracts and identifies subjective data from product evaluations using natural language processing (NLP) and machine learning (ML) methods. These statistics may eventually reveal information on the favourable, neutral, or negative attitudes of the consumer base. Due to its capacity to grasp the complex links between words and phrases in reviews as well as the emotions they imply, deep learning (DL) is very useful for SA tasks. A unique approach termed Weighted Parallel Hybrid Deep Learning-based Sentiment Analysis on E-Commerce Product Reviews (WPHDL-SAEPR) is introduced by the proposed system. Accurately distinguishing between distinct sentiments found in online store reviews is the aim of the WPHDL-SAEPR technique. Additional data pre-processing processes are implemented within the WPHDL-SAEPR architecture to guarantee compatibility. Words are embedded into the paper using the word2vec model, while sentiment is classified using the WPHDL model. The Restricted Boltzmann Machine (RBM) and Singular Value Decomposition (SVD) models are combined in this model. The results of the WPHDL-SAEPR approach’s simulation were assessed using a consumer review database, with the results being emphasized at each stage.

The paper deals with electricity production from unused energy at the water management company. We have practical experience with using biogas produced by wastewater treatment plants for the production of electricity and with using drinking water stored in reservoirs for the production of electricity. In the first part, technology of the biogas production in a waste water treatment plant is described, technology of the water storage and pipelines is described and then production of electricity and bargain redemption price are discussed.

Hydrogen is considered a powerful fuel for the future. Hydrogen production technologies vary widely. Green hydrogen is generated by electrolyzing water with electricity produced from renewable energy sources. According to the stoichiometry reaction, 9 kg of water is consumed to produce 1 kg of hydrogen. The water to be electrolysed has to meet stringent requirements and its preparation generates large quantities of wastewater, which should be managed appropriately. The objective of this research is to examine the methods by which water is prepared depending on its source and to determine the level of wastewater generated by its treatment. The results of the analyses carried out indicate that the water abstraction associated with green hydrogen production is significantly higher than the 9 kg per 1 kg of hydrogen value reported in numerous studies.

Energy management in enterprises is an important issue in the context of improving energy efficiency, energy use, and energy consumption. This is consistent with the Sustainable Development Goals. The purpose of this study was to evaluate the energy management system of water and wastewater utility in the context of sustainable development based on the opinions of managers and employees. The results indicate the involvement of the surveyed enterprise in energy management system development activity. This demonstrates the orientation of the surveyed enterprise to support activities to improve energy performance in line with the implementation of sustainable development. The added value is that the developed research tool can be used in studies of other enterprises to assess the level of energy management.

Waste Water Treatment Plant (WWTP) belong to the so-called �critical infrastructure�, which are so essential that their continued operation is required to ensure the security of a people. Energy is the most important operating utilities of WWTP. The specific electric energy consumption of WWTP depending on many factors including the inflow quality, WWTP�s scale, the technology used and climate. High energy consumption indirectly produces ecological damage, accelerates the energy crisis, and increases carbon emissions. The article will present data on analysis electricity consumption and carbon footprint at a small wastewater treatment plant in southern Poland. Electricity consumption of the analyzed wastewater treatment plants in 2019-2021 ranged from 221 714 to 248 824 kWh/year, with an average value of electricity consumption rate per m3 of wastewater: 1.15 kWh/m3. Rising amount of pollutants conducted into the treatment plant results in an increased energy demand. However, this correlation does not take a linear character.

The challenge of achieving and measuring urban water sustainability is hard because of its complex nature. The sustainability of urban drinking water system (UDWS) is no exception, as integration of technical, environmental, social, economic, and institutional elements of sustainability is defying and perplexing in terms of its application and evaluation. This paper deals with the technical aspects related to the design, construction, operation, and maintenance factors of a UDWS. Measurement of the status of such factors is almost impossible in generic formats. Therefore, a list of measurable sub factors was developed through an extensive literature survey and refined by involving appropriate stakeholders. This led to the development of a hierarchy from criteria to factors and from factors to sub factors, making a case for the utilization of an analytic hierarchy process (AHP) for multicriteria analysis (MCA). Appropriate stakeholders were included in this research to address the issues for which there were major gaps in the literature. A set of guidelines were developed for the evaluation of the status of various sub factors in a quantitative format. It is concluded that a trans disciplinary framework, the involvement of stakeholders, and guidelines for adopting appropriate processes and techniques may improve the sustainability of stressed urban water systems.

The usage of plastic materials in our daily life is increasing day by day. These plastic materials are somehow beneficial for us, but the disposal of waste plastic materials has become a serious problem. The use of plastic not only enhances road construction but also helps extend the life of roads and improves the environment. Waste plastics use in roads increases durability and also reduces water retention. This research reviews the use of waste plastics in asphalt pavement. In this study, the properties such as Marshall stability, flow, resilient modulus, fatigue, etc., are studied to boost the usage of waste plastic in asphalt pavements. It is concluded that with the use of waste plastic in asphalt pavement, the quality of roads will be enhanced, and it will also be very beneficial for our environment. The other major advantage is that it will be very cost-effective for underdeveloped countries.

Study region: Bisham Qilla and Doyian stations, Indus River Basin of Pakistan Study focus: Water pollution is an international concern that impedes human health, ecological sustainability, and agricultural output. This study focuses on the distinguishing characteristics of an evolutionary and ensemble machine learning (ML) based modeling to provide an in-depth insight of escalating water quality problems. The 360 temporal readings of electric conductivity (EC) and total dissolved solids (TDS) with several input variables are used to establish multiexpression programing (MEP) model and random forest (RF) regression model for the assessment of water quality at Indus River. New hydrological insight for the region: The developed models were evaluated using several statistical metrics. The findings reveal that the determination coefficient (R2) in the testing phase (subject to unseen data) for the all the developed models is more than 0.95, indicating the accurateness of the developed models. Furthermore, the error measurements are much lesser with root mean square logarithmic error (RMSLE) nearly equals to zero for each developed model. The mean absolute percent error (MAPE) of MEP models and RF models falls below 10% and 5%, respectively, in all three phases (training, validation and testing). According to the sensitivity study of generated MEP models about the relevance of inputs on the predicted EC and TDS, shows that bi-carbonates and chlorine content have significant influence with a sensitiveness score more than 0.90, whereas the impact of sodium content is less pronounced. All the models (RF and MEP) have lower uncertainty based on the prediction interval coverage probability (PICP) calculated using the quartile regression (QR) approach. The PICP% of each model is greater than 85% in all three stages. Thus, the findings of the study indicate that developing intelligent models for water quality parameter is cost effective and feasible for monitoring and analyzing the Indus River water quality.

Smart agriculture is a concept that refers to a revolution in the agriculture industry that promotes the monitoring of activities necessary to transform agricultural methods to ensure food security in an ever-changing environment. These days, the role of technology is increasing rapidly in every sector. Smart agriculture is one of these sectors, where technology is playing a significant role. The key aim of smart farming is to use the technologies to increase the quality and quantity of agricultural products. IOT and digital image processing are two commonly utilized technologies, which have a wide range of applications in agriculture. IOT is an abbreviation for the Internet of things, i.e., devices to execute different functions. Image processing offers various types of imaging sensors and processing that could lead to numerous kinds of IOT-ready applications. In this work, an integrated application of IOT and digital image processing for weed plant detection is explored using the Weed-ConvNet model to provide a detailed architecture of these technologies in the agriculture domain. Additionally, the regularized Weed-ConvNet is designed for classification with grayscale and color segmented weed images. The accuracy of the Weed-ConvNet model with color segmented weed images is 0.978, which is better than 0.942 of the Weed-ConvNet model with grayscale segmented weed images.

Precipitation is the main source of recharge of water resources, thus guaranteeing their renewability. Not only hydrometeorological changes, but also anthropogenic factors exacerbate the above-mentioned effects. The increase in the level of investment seen especially in recent years in urban agglomerations through the intensification of development, increased development of impervious and paved surfaces, the use of vacant land, and thus the reduction of biologically active areas has resulted in an increase in rainwater runoff into the urban drainage system. As a result, this has caused temporary local urban flooding, or sewer flooding, and has thus become a common problem in today's cities. Prevention has forced the need to pay attention to issues related to the causes of and compensation for water deficits through corrective measures involving the development of effective methods of prevention and counteraction. A change in the approach hitherto prevailing in urban planning has also become a fundamental factor. The traditional approach to the disposal of surface runoff assumed only that rainwater should be discharged as quickly as possible into a receiving body. Traditional sewer systems served this purpose. The purpose of this paper is to perform a review of current solutions in the field of rainwater management and to carry out a technical and economic use of them in relation to the traditional model of the sewerage system.

The article is focused on the issue of blackouts in a water industry and the selection of a renewable energy source for a water treatment plant. In the case of power outage, it is necessary to constantly ensure the supply of a drinking water, if this requirement would not be met, it could cause of deterioration of hygiene and health of the population. To be able to convey drinking water during a blackout, it is mandatory to have a backup power supply. The state of the current water treatment plants in the Czech Republic is that they are using diesel generators as backup power supply, which causes air pollution. There are other options of power supply that can be used, such as renewable energy sources. By using a multi-criteria analysis method, renewable energy sources were analyzed for a water treatment plant in the selected region. Based on the results, it seems that the most suitable choice is a small hydro power plant at the entry points of water treatment plant. Other possibilities of renewable energy sources that may be suitable for a water treatment plant and the usage of a multi-criteria analysis method for a water treatment plant in other countries are also discussed.

The article concerns the energy security of a wastewater treatment process caused by unforeseen situations related to the risk of electrical power outages. In this case, renewable energy sources based on distributed generation power systems can solve this problem in each wastewater treatment plant. The article highlights e related challenges and proposes the direction of solutions in this regard based on Czech conditions. The first part of the paper deals with the consequences of long-term outage of wastewater treatment plants on the population and the environment. There are several solutions presented for blackout conditions, and model calculations are made based on data from a Czech wastewater treatment plant. Diesel engine-generators, biogas as a cogeneration source of heat and electricity, solar panels with storage systems and combined biogas and solar systems were considered as approaches to provide energy autonomy during a blackout in a wastewater treatment plant. Special attention was paid to a combination of CHP units with solar panels and batteries. The results were evaluated for three different locations for this combination. It was concluded that biogas combustion in the CHP unit was the most profitable option, allowing the production of electricity independently of the grid for its own consumption and possibly for other operations. The last part of the paper deals with the transition to island operation, which must occur during a blackout. This transition is more difficult for both solar panels and cogeneration units if they were to supply electricity to the grid before a blackout. The transition to energy island operation could be ensured by frequency relay and processor devices to control the circuit breaker. Then, to maintain island operation, it would be necessary to have an automatic load shedding/application system.