Considerable Environmental Impact Research Articles

Evaluation of Steel Slag as a Sustainable Alternative Aggregate for Railway Ballast: A Shakedown Theory-Based Approach

Recent advancements in railway construction have emphasized environmental sustainability, integrating considerations of environmental impact into the planning and execution of infrastructure projects to reduce costs and mitigate adverse effects. This study investigates the use of steel slag as a sustainable alternative for railway ballast, grounded in shakedown theory. The characterization of the aggregates was performed in accordance with NBR 5564 and AREMA standards, confirming that the material meets most requirements. The mechanical behavior of the ballast was analyzed under cyclic loading conditions, assessing permanent deformation and the material’s ability to achieve stability (shakedown). Triaxial tests with repeated loading simulated real railway conditions, applying vertical stresses up to 600 kPa and confining pressures ranging from 35 to 200 kPa. The results indicate that steel slag aggregates exhibited promising performance, with seven specimens achieving stable deformation levels, characterized by residual deformations of less than 2.5 mm. Notably, these specimens approached deformations on the order of 10−7, indicating stability under cyclic loading. Furthermore, a comparative analysis of shakedown criteria proposed by various authors revealed variations in limits for granular materials, enhancing the understanding of steel slag aggregate behavior. The experimental results were validated through numerical simulations conducted with Systrain software 2.0, which simulated a loading condition of 32.5 tons per axle, confirming the observations with maximum principal stresses ranging from 166 to 184 kPa in the ballast. The analysis showed that steel slag aggregates can withstand stress levels higher than those of granodiorite, reinforcing their viability as a sustainable alternative for railway ballast.

Integration of investor behavioral perspective and climate change in reinforcement learning for portfolio optimization

Addressing environmental impact is increasingly imperative for individual investors and large financial institutions, making it a key objective of socially responsible investing. However, there is a noticeable gap in research on integrating sustainability and low-carbon considerations into machine learning-based portfolio optimization. To meet this challenge, this study introduces a Portfolio Emissions Sentiment Attention Aware Reinforcement Learning (PESAARL) model based on the Proximal Policy Optimization (PPO) algorithm to optimize a portfolio of Dow Jones Industrial Average (DJIA) stocks. PESAARL uniquely integrates environmental impact considerations, specifically carbon footprint using the firm level scope 1 and scope 2 emissions data, alongside firm-level investor sentiment and attention, into the investment decision-making process. Through multiple experiments, PESAARL demonstrates significant advantages, in terms of financial and environmental performance, over the benchmarks.

Models of forming logistics infrastructure for complex equipment recycling

Subject matter: models for forming the logistics infrastructure for complex equipment recycling. The work aims to create optimization models that consider key factors in forming recycling infrastructure and combine centralized and decentralized elements to enhance the efficiency of this process. Tasks: analyze modern approaches to organizing complex equipment recycling; identify criteria and factors for optimizing recycling infrastructure; develop a multi-level recycling infrastructure; formulate optimization models for recycling infrastructure, taking into account enterprise production capacities, logistical costs, environmental impact, and other factors. Methods: a systems approach, structural modeling, optimization models. Research results: approaches to organizing recycling infrastructure were analyzed: centralized, distributed, and combined; the selection of a combined approach for creating logistics infrastructure for complex equipment recycling was justified; a structural multi-level model of recycling infrastructure was developed with a lower level (sorting enterprises), middle level (processing enterprises), and upper level (organizational management); mathematical models for optimizing recycling infrastructure were formulated, considering enterprise production capacities, logistical costs, and environmental impact. The conclusions: proposed structural multi-level model of complex equipment recycling infrastructure combines the advantages of centralized and decentralized management, ensuring flexibility, system reliability against external influences, cost minimization, and sustainable process control. The application of the developed optimization models allows for consideration of enterprise production capacities, logistical costs, environmental impact, and other factors to find the most effective configuration of recycling infrastructure. Implementation of the proposed recycling infrastructure will ensure the formation of coherent interaction between government bodies, enterprises, public organizations, and international partners.

Fluid selection and parametric analysis of organic Rankine cycle applicable to the turboshaft engine with a recuperator

With ever increasing fossil fuel price and growing demands in cutting emissions, waste heat recovery (WHR) appears as a promising pathway to improve propulsion system performance, which can be potentially achieved by incorporating a recuperator. This paper explores the advantages and potentiality of further recovering exhaust heat from recuperated turboshaft engine through the concept of organic Rankine cycle (ORC) to improve fuel economy and thermal efficiency. For the intended application, working fluid selection is conducted after systematic consideration of thermophysical properties, environmental impact, health and safety issues. Furthermore, parametric analysis is carried out from the viewpoint of thermodynamics, and the genetic algorithm is also employed to obtain the maximum net power output. Targeting the implicit coupling between recuperator effectiveness and ORC performance, the potential advantages of the combined engine-ORC system are comprehensively evaluated at different operational regimes. The influence of flight condition is also discussed through sensitivity simulations for different altitudes. Results reveal that the combination of the recuperated engine with ORC cycle operated using acetone generally offers the greatest benefits, significantly reducing specific fuel consumption by 46%–59 % relative to the baseline simple-cycle engine, depending on the availability of heat source. This analytical work contributes to provide valuable insights into WHR technologies in the aviation industry.

Stability Evaluation of Lanedada Twin Tunnel in KTFT

The construction of underground tunnels, particularly in roadway systems, is a highly complicated and demanding process, necessitating careful consideration of geological variability, environmental impact, and safety concerns. This thesis emphasizes the critical importance of determining the optimal separation between twin tunnels, balancing the need for environmental conservation, economic efficiency, and structural stability. The study particularly focuses on the Kathmandu Terai/Madhesh Fasttrack (KTFT), a major expressway project in Nepal, which includes twin tunnels at three different sites under varying geological conditions. A detailed case study is conducted on the Lanedada Twin Tunnel, spanning 1.430 kilometers through the Siwalik Hill. Various methodologies, including empirical, analytical, and numerical approaches, are employed to assess tunnel stability. The findings reveal discrepancies in predictions of tunnel squeezing, with Singh et al.'s method indicating no squeezing potential, while Goel et al.'s method identifies squeezing in half of the evaluated sections. Additionally, the approaches by Hoek and Marino (2000) and Shrestha and Panthi (2015) are applied to estimate tunnel deformation at six specific locations. An analysis of rock support systems using the Rock Massm Rating (RMR) classification and the Q system is presented. Special attention is given to the section at 34+160, where the RS2 software is utilized to simulate varying pillar widths between the twin tunnels, allowing for a comparative analysis of different scenarios. This research aims to contribute to the understanding and implementation of safer, more feasible twin tunnel constructions, thereby enhancing the effectiveness of large-scale infrastructure projects.

Anesthesia and its environmental impact: approaches to minimize exposure to anesthetic gases and reduce waste.

In today's era of modern healthcare, the intersection between medical practices and environmental responsibility has gained significant attention. One such area of focus is the practice of anesthesia, which plays a crucial role in various surgical procedures. Anesthetics such as nitrous oxide and volatile halogenated ethers (desflurane, isoflurane, sevoflurane) are examples of medical gases that are strong greenhouse gases that contribute to global warming. During medical procedures, most of these anesthetic agents are released into the atmosphere, which exacerbates their influence on the environment. Also anesthesia delivery systems have traditionally utilized high flow rates of gases, leading to not only excessive consumption but also a considerable environmental impact in terms of greenhouse gas emissions. However, the emergence of low-flow anesthesia (LFA) presents a promising solution for achieving emission reduction and cost savings, thereby aligning healthcare practices with sustainability goals. Understanding LFA involves the administration of anesthetic gases to patients at reduced flow rates compared to conventional high-flow methods. This practice requires precision in gas delivery, often incorporating advanced monitoring and control systems. By optimizing gas flow to match the patient's requirements, LFA minimizes wastage and excessive gas release into the environment, subsequently curbing the carbon footprint associated with healthcare operations. Decreasing volatile anesthetic delivery provides safe and effective strategies for anesthesia providers to decrease costs and reduce environmental pollution. Current literature support in favor of LFA represents an area of cost containment and an opportunity to lessen the environmental impact of anesthesia. This article will cover the concept of LFA, the distinctions between low flow and minimal flow, and the potential advantages of LFA, such as those related to patient safety, the environment, and the economy.

How to choose between single-use and reusable medical materials for sustainable nursing: Methodological lessons learned from a national study.

To demonstrate and reflect upon the methodological lessons by which healthcare organizations can address questions of environmental sustainability related to single-use healthcare materials. A cross-sectional multi-centre study in hospitals was performed, followed by an exploratory analysis of the sustainability of commonly used healthcare materials. A hospital survey was conducted to collect the procurement data for single-use medical materials. Based on consumption and cost, five single-use medical materials with sustainable alternatives were selected using different reuse strategies. Single-use and reusable materials were assessed through an exploratory literature review and document study based on four parameters: environmental sustainability, safety, cost and efficiency. A pragmatic method emerged from this study, providing healthcare facilities with tools to select environmentally sustainable alternatives to replace single-use options. First, an inventory of single-use medical materials consumed was collected. Next, single-use materials were prioritized for further study based on criteria such as cost, volume of the material, feasibility and input of stakeholders. We then analysed the prioritized single-use materials and their alternatives based on life cycle assessments or available information on their different life stages. Finally, we assessed safety, costs and efficiency related to the process following the use of the medical material. This pragmatic method can guide healthcare institutions in making the most sustainable choices of medical materials and achieving sustainability goals within their institutions and nationwide. Patient care involves a large consumption of single-use medical materials with considerable environmental impact. A pragmatic method was developed to guide healthcare institutions in making the most sustainable choices regarding the use of single-use healthcare materials. Healthcare institutions, ideally represented by a green team including nurses and other relevant professionals, can use this method to reduce the use of single-use medical materials, thereby yielding positive outcomes for the entire population. No patient or public contribution.

Optimal sizing and economic assessment of grid connected active distribution network for reliable rural electrification in India

Majority of rural areas in India have already been electrified, yet the disparity between demand and supply is considerably higher and broadened due to which nation’s rapid financial growth as well as rising standards of living in both the urban as well as rural areas. Hence, the utilisation of renewable resources is rising steadily for the mitigation of such energy crisis. It has become necessity to use a hybrid sustainable energy system by exploiting the strengths of each source in combination with one another to minimise the dependence on the congested power grid. For the efficient use of readily available renewable energy and sustainable rural electrification, this study proposes an effective Active Distribution Network (ADN). A comprehensive techno-economic analysis has been performed on the design of an ADN system that includes the exploitation of solar and biomass energy as sources of power for sustainable rural electrification. In the proposed work, performance assessment elements such as output responses, component costs, feasibility and sensitivity of the project, emissions, inflation rate, and changing the pricing of integrant have been taken into consideration and analysed. Results shows the improvement in rural electrical system while lowering system energy costs along with consideration of environmental impact.

A mini-review on data science approaches in crop yield and disease detection

Agriculture constitutes a sector with a considerable environmental impact, a concern that is poised to increase with the projected growth in population, thereby amplifying implications for public health. Effectively mitigating and managing this impact demands the implementation of intelligent technologies and data-driven methodologies collectively called precision agriculture. While certain methodologies enjoy widespread acknowledgement, others, despite their lesser prominence, contribute meaningfully. This mini-review report discusses the prevalent AI technologies within precision agriculture over the preceding five years, with a specific emphasis on crop yield prediction and disease detection domains extensively studied within the current literature. The primary objective is to give a comprehensive overview of AI applications in agriculture, spanning machine learning, deep learning, and statistical methods. This approach aims to address a notable gap wherein existing reviews predominantly focus on singular aspects rather than presenting a unified and inclusive perspective.

Working Fluid Selection for High-Temperature Heat Pumps: A Comprehensive Evaluation

Heat pumps have the potential for several applications across various industrial sectors, showcasing significant promise, especially in sectors such as pulp and paper, food and beverage, chemical, non-metallic minerals, and machinery. Envisioning the near future, there is confidence that heat pumps can achieve temperatures above 200 °C, offering substantial potential for utilization in these sectors. Nevertheless, a crucial aspect for the advancement of high-temperature heat pumps is the selection of the fluid. Fluid selection involves considerations of both thermodynamic efficiency and environmental impact, requiring fluids with zero ODP, negligible GWP, and no PFAS. Moreover, it is essential to consider the risks to human health associated with a specific fluid. Despite extensive research, particularly in the realm of vapour compression heat pumps, choosing the most suitable working fluid for these applications is a complex undertaking. Therefore, this paper conducts a theoretical analysis to evaluate potential fluids with suitable thermodynamic properties for high-temperature heat pumps (HTHPs). The comparative results gleaned from this study provide valuable insights for the comprehensive analysis of fluids, showing promise within temperature ranges dictated by specific applications. The metrics employed in the comparison emphasise the merits of fluids in terms of the overall performance, dimensions, and operating ranges of applicable compressor, heat exchange capacity, transport properties, and safety. One noteworthy finding from the analysis is that maintaining a constant HTHP lift (at 40 K) results in having the highest COP across all fluids when the condensing temperature ranges between 85% and 90% of their respective critical temperatures. According to the results of the analysis, natural fluids, including water and alcohols like ethanol or methanol, emerge as particularly compelling candidates.

Silver‐doped alginate cryogels as new generation current collectors for lithium‐ion batteries: Structural and electrochemical analysis

AbstractThe development of next‐generation materials for essential components in lithium‐ion batteries, such as collectors, is crucial owing to considerations of performance, cost, and environmental impact. From this perspective, new‐generation material studies are being carried out to increase the performance of current collectors and reduce environmental damage. In this study, a novel biodegradable Ag nanoparticle‐doped calcium alginate cryogel was produced and used as the current collector for Li‐ion batteries to improve performance, reduce environmental damage, and develop new‐generation batteries. The synthesis of Ag NPs was achieved using an inexpensive and environmentally friendly chemical reduction method, followed by their incorporation into the gels. Freeze‐drying was employed to obtain cryogels without the inclusions on the current collector. Structural analysis of both the particles and gels was performed via XRD, SEM, EDS, and FTIR, DSC respectively. The results showed that the synthesized Ag NPs were spherical with an average diameter of 10 nm. The cryogels exhibited desirable chemical structures, as indicated by FTIR analysis. The addition of Ag NPs led to changes in peak positions and intensities, indicating crosslinking homogenization and increased hydrophobicity. Galvanostatic Charge/Discharge Analysis was conducted to evaluate the electrochemical performance of the cryogels as current collectors. The cryogels demonstrated balanced lithiation/delithiation behavior but had a limited operational duration, likely due to structural instability. Postmortem analysis conducted by FTIR and DSC analysis for disassembled cryogels showed the presence of lithium salts from the electrolyte in the structure, and the usage of a solid electrolyte was recommended to improve the system's performance.

Unveiling the Potential of Secang (Caesalpinia sappan L.) as a Novel Tanning Agent: A Promising Alternative for the Leather Industry

The exploration of vegetable tanning's natural resources is fascinating as an alternative to basic chromium sulfate for its natural abundance and considerable environmental impact. In this work, an attempt has been made to extract vegetable tannin from Caesalpinia sappan L. bark using water as a solvent with different levels of temperatures and incubation times. The highest yield efficiency was observed at 80 °C for 4 hours. The presence of tannin content and polyphenolic compounds were screened by the phytochemical analysis using Iron (III) chloride (FeCl3), sodium hydroxide (NaOH), and ensured by the thin layer chromatography (TLC), and the Fourier transform infrared (FTIR). The extracts were then determined by percentage of extract yield, phytochemical, tannin type, moisture, total solids, and tannin characteristics. The findings indicate that the extract of Secang contains 4.98±0.28% total moisture, 95.02 ± 0.28% total solids, and 72.12 ± 2.81% total soluble solids, 52.28 ± 1.79% tannins, and 19.84 ± 1.41% non-tannin. Moreover, Fourier transform infrared (FTIR) analysis revealed a clear functional group within Caesalpinia sappan L., as evidenced by the type of tannin that is condensed. The TLC assay exhibited a considerable intensity under UV lights. It included several shades of light blue and blue, which could indicate the presence of secondary metabolites and tannin. Compared to mimosa, as the commercial standard for tanning agents in the leather industry, Caesalpinia sappan L. presents promise as an eco-friendly substitute for basic chromium sulfate and a new alternative source of vegetable tannin for the leather industry.

Classification of acid sulfate soils and soil materials in Finland and Sweden: Re-introduction of para-acid sulfate soils

Established international soil classification systems have not properly accommodated acid sulfate soils (ASS) and soil materials in Finland and Sweden because: (1) in these soils some diagnostic ASS properties are too deep to meet the depth requirements, and (2) there is a lack of defined diagnostic soil classification criteria for acidic and potentially acidic soil materials that do not completely fulfill the diagnostic pH-criterion of pH < 4.0. In this paper, two new ASS materials are introduced with the prefix “para” for parasulfuric material (oxidized material) and parahypersulfidic material (reduced material). These materials have diagnostic pH-criteria of pH 4.0–4.5 and 3.0–3.5 (field-pH for parasulfuric material and incubation-pH for parahypersulfidic material) for mineral and organic soil materials (here defined as > 20% organic matter; peat and gyttja), respectively. The term “para-acid sulfate soil (para-ASS) material” is introduced for soil materials which may have a considerable environmental impact due to mobilization of acidity and dissolved metals. Because organic acids may lower pH to values below the established pH-value of < 4.0 for ASS materials, a pH of < 3.0 is used in the Finnish-Swedish ASS classification for organic soil materials. These changes and new additions to existing diagnostic ASS materials have consequently also led to a slight modification of the required field-pH values of the existing terms “hypersulfidic material” and “sulfuric material”. The Finnish-Swedish ASS classification further includes a systematic way for classification of the entire soil profile and no depth requirements for diagnostic ASS materials are present; what matters is the current or potential environmental impact that the soil has or may have. It is proposed that the Finnish-Swedish ASS classification may serve as a framework for establishing a unified ASS classification globally and that the new diagnostic ASS materials are included in relevant international soil classification systems.

Towards Sustainable Last-Mile Delivery: Introducing an Off-Peak Urban Policy to Mitigate Environmental and Social Impacts

In recent years, last-mile delivery research has shifted from focusing solely on cost minimization to a broader consideration of sustainability and environmental impact. This paper explores the novel trend of evaluating the social impact of last-mile delivery, emphasizing factors such as road safety, congestion, and noise pollution. A key strategy that has garnered attention in addressing these multifaceted concerns is Of-Peak Hours Delivery (OPHD), which involves scheduling deliveries during non-peak hours, often in the evenings or at night. This study investigates implementing a city-wide policy inspired by OPHD, strategically encouraging or discouraging deliveries in specific urban areas and time slots. The objectives of such a policy span from environmental considerations to nuanced social factors, potentially leading to dynamic shifts in time slot preferences. Adopting such a policy aligns with the growing citizen concern for environmental and social issues, leveraging changing attitudes toward sustainable practices. To evaluate this policy, we formalize it as a bi-objective mixed-integer programming model, aiming to strike a balance between the economic interests of retailers and the municipality’s overarching goals. Through realistic instances, the paper offers managerial insights, providing valuable perspectives on the practical effects of the proposed policy on delivery operations. This facilitates a deeper understanding of the ramifications of integrating social considerations into the optimization framework.

Sustainable leather tanning with Pontederia crassipes tannin: A promising eco-friendly alternative

Considering the considerable environmental impact resulting from basic chromium sulfate, the exploration of vegetable tanning materials as an eco-friendly alternative has gained substantial interest. This study endeavors to extract tannins from Pontederia crassipes using various solvents (water, acetone, methanol, and ethanol) and evaluate their potential as a vegetable tanning agent for leather processing. Among the solvents, methanol exhibited the highest extraction efficiency at 26.34%. UV–Vis spectroscopy, FT-IR spectroscopy, and titrimetric analysis confirmed the presence of total tannins at 152.25 mg/g, which encompassed polyphenolic compounds such as epicatechin, catechin hydrate, and catechol. The antimicrobial behavior of the extracted tannin was confirmed by antimicrobial analysis. Notably, leather tanned with Pontederia crassipes tannin displayed an impressive shrinkage temperature of 83.31 °C, tensile strength 286.33 kg/cm2, and elongation 63.33%. This innovative tanning approach also yielded enhanced properties such as tensile strength, Bauman tear strength, stitch tear strength, tongue tear strength, and percentage of elongation, surpassing those of traditional vegetable-tanned leather. A closer look at the surface of the tanned leathers using Scanning electron microscopy (SEM) revealed compact fiber structures and uniform surface. Moreover, the Fourier-transform infrared spectroscopy (FTIR) analysis revealed clear functional groups within the Pontederia crassipes tanned leather, as evidenced by the broad peak observed. These results collectively imply that Pontederia crassipes tannin presents promise as an eco-friendly substitute for basic chromium sulfate and a novel reservoir of vegetable tannins for the leather sector.

Sustainable Approaches to Medical Tourism: Strategies for Central Macedonia/Greece

The study of health and medical tourism is a multifaceted and intricate field. Nevertheless, it is a swiftly expanding global industry with considerable economic prospects. This sector involves the exchange of services, blending two of the world’s major domains: healthcare and tourism. This research aims to evaluate the strengths of medical tourism service providers in the Central Macedonia Region while shedding light on various challenges that could impede the sector’s growth. Additionally, it investigates crucial sustainability factors and opportunities within the Greek medical tourism industry that can effectively address obstacles, both domestic and international, to enhance sustainable medical services. The study delves into the reasons why the Central Macedonia Region can attract both local and international medical travelers seeking healthcare solutions. With this aim in mind, both Systematic Literature Review (SLR) and primary quantitative research methods were employed. The SLR aimed to locate pertinent scientific literature, which, when integrated with the outcomes of the quantitative research, facilitated the analysis, description, and interpretation of data for the formulation of conclusive findings. In brief, this article aims to contribute scientific value by engaging in interdisciplinary research and demonstrating originality through innovative approaches to sustainable development. It seeks to make a significant contribution to the field by presenting practical strategies and insights that strike a balance between the economic advantages of medical tourism and the crucial considerations of environmental and social impact.

Enhancing Indoor Environmental Quality and Sustainability in Post-Pandemic Office Settings: A Study on Displacement Ventilation Feasibility

The COVID-19 pandemic has catalyzed global efforts toward transitioning to a sustainable society, driving rapid innovation in building technologies, working practices, building design, and whole life cycle environmental impact consideration. In this pursuit, this study explores the enduring impact of these on an alternative ventilation approach for both existing building renovations and new building implementations. Comparing displacement ventilation to mixed-mode ventilation in a Finnish office building with varying occupancy densities, this study examines indoor air quality (IAQ), thermal comfort, total building energy performance, and embodied carbon. The findings reveal that the basic case of mixed ventilation has a specified system primary energy value of 38.83 kWh/m2 (with 28 occupants) and 39.00 kWh/m2 (with 24 occupants), respectively. With the displacement ventilation alternative, it reduces this by 0.3% and 0.1%, enhancing thermal comfort and decreasing turbulence as well as having a marginal decrease in embodied carbon. In general, the study offers three-fold contributions: insights into post-pandemic office mechanical ventilation design with an emphasis on sustainability and ecological footprint considerations, a concrete case study addressing climate action and human-centric IAQ design, and a multifaceted analysis using the Environmental, Social, and Governance (ESG) paradigm, contributing to the groundwork for associated future research and policy progress.

ENHANCING ENERGY EFFICIENCY WITH AI: A REVIEW OF MACHINE LEARNING MODELS IN ELECTRICITY DEMAND FORECASTING

This study presents a comprehensive review of the impact of artificial intelligence (AI) and machine learning (ML) on enhancing energy efficiency, particularly in the context of electricity demand forecasting. The review systematically explores the paradigm shift brought about by the emergence of AI in energy efficiency, focusing on the role of AI in electricity demand forecasting and the historical evolution of forecasting techniques. A critical analysis of various ML models is conducted, examining their theoretical underpinnings, selection criteria, and performance in diverse scenarios. Key insights reveal that ML models, especially those incorporating deep learning and big data analytics, significantly outperform traditional forecasting methods in accuracy and adaptability. These models are adept at handling complex, nonlinear relationships and large datasets, making them particularly effective in the dynamic and increasingly renewable-focused energy markets. The review also highlights the importance of selecting appropriate ML models based on criteria such as accuracy, adaptability to forecasting periods, data handling capabilities, and environmental impact considerations. The study further delves into the technological, economic, and environmental impacts of ML in energy efficiency. It underscores the potential of ML to drive innov4eations in energy forecasting, contributing to more sustainable and efficient energy management. However, challenges such as data privacy, cybersecurity, and the need for skilled professionals are identified as critical areas requiring attention. Strategic recommendations are provided for practitioners and policymakers, emphasizing the need for investment in AI and ML training, development of supportive regulatory frameworks, and fostering collaborations across sectors. The review concludes with a future outlook, suggesting directions for future research in AI and energy efficiency, particularly in developing robust and scalable ML models that can integrate with renewable energy sources and smart grid technologies. This study serves as a valuable resource for researchers, practitioners, and policymakers engaged in the field of energy efficiency and AI-driven forecasting.
 Keywords: Machine Learning, Energy Efficiency, Demand Forecasting, Artificial Intelligence.

Optimization of Cable Layout With Consideration of Environmental Impact

Optimization of Cable Layout With Consideration of Environmental Impact

Exploring chlorination as a removal process for antiretroviral drugs (Nevirapine and Efavirenz) from water: Effect of operational parameters, kinetics, and trihalomethane formation

This study investigates the removal of antiretroviral drugs (ARVs), Nevirapine (NVP) and Efavirenz (EFV), from drinking water through chlorination, focusing on the influence of pH, temperature, chlorine concentration, and ARV initial concentration on the degradation kinetics and trihalomethane (THM) formation. At 25 °C and an initial concentration of 100 μg/L, the degradation trends for both ARVs were examined across varying pH levels. EFV exhibited greater pH sensitivity, with removal increasing from 37 % at pH 5.5 to 68 % at pH 8, while NVP removal increased only from 40 % at pH 5.5 to 48 % at pH 8. Temperature also played an essential role, as the removal of both ARVs increased with rising temperature, indicating an endothermic reaction. Higher chlorine concentrations resulted in increased removal, >90 % at 5 mg/L for both ARVs. Kinetic analysis revealed second-order behaviour, with higher rate constants observed at pH 5.5–7 for NVP and pH 7–8 for EFV. The intrinsic chlorination rate constants for both ARVs were estimated. The calculated half-lives indicated slow removal. The study also assessed contact time for NVP and EFV in a plug-flow reactor (PFR) and continuous stirred tank reactor model (CSTR). Also considering hydraulic residence time (HRT) rather than reaction time to assess the average amount of time that the ARVs spent in the selected reactors. The HRT for a CSTR was lower than the PFR, and the estimated HRT for a CSTR was a feasible value. The minimum HRT came out to 1.56 h (pH 7.5 and a temperature of 25 °C) for NVP and 1.07 h (pH 7 and a temperature of 25 °C) for EFV. Finally, THM formation was observed, with chloroform, dibromochloromethane and bromoform detected. Among the three THMs, the most significant change occurred between 4 and 6 h, with chloroform levels increasing from 31.59 μg/L to 63.49 μg/L. This study underscores the influence of operational parameters on ARV removal via chlorination. Highlighting pH sensitivity, temperature control, precise chlorine dosage, and environmental concerns such as trihalomethane formation ensures effective disinfection while minimizing negative impacts on both water quality and the environment. Emphasizing the importance of a comprehensive approach to ARV removal in water treatment processes is a proactive measure that integrates considerations of environmental impact, public health, regulatory compliance, and long-term sustainability into the design and operation of water treatment facilities.