ABSTRACT The work is focused on determining the energy transfer from EV’s to grid for different operating conditions. The study has been simulated on a scaled model and later validated through experimental tests on batteries of 20 kWh, 40 kWh, 60 kWh and 80 kWh for EV’s energy rates from 130 Wh/km to 180 Wh/km. Tests have been developed to evaluate the energy transfer from driving distance between 0 and 50 km. Results have proved there is a linear dependence between energy transfer and energy rate. Experimental and simulated values have been correlated showing a 99.6% accuracy. The ratio of energy transfer to battery energy capacity depends not only on this latter parameter, but also on the energy rate of the electric vehicle. Experimental tests have shown a variation from a minimum transfer ratio of 54.1% for the highest electric vehicle energy rate and lowest battery energy capacity and power transfer to grid rate to a maximum of 88.6% for the highest power transfer to grid rate and battery energy capacity and lowest electric vehicle energy rate.

There are different ways to analyse energy absorbance (EA) in the human auditory system. In previous research, we developed a complete finite element model (FEM) of the human auditory system. In this mentioned work, the external auditory canal (EAC), middle ear, and inner ear (spiral cochlea, vestibule, and semi-circular canals) were modelled based on human temporal bone histological sections. Multiple acoustic, structure and fluid-coupled analyses were conducted using the FEM to perform harmonic analyses in the 0.1–10 kHz range. Once the FEM had been validated with published experimental data, the FEM numerical results were used to calculate the EA or energy reflected (ER) by the tympanic membrane. This EA was also measured in clinical audiology tests which were used as a diagnostic parameter. A mathematical approach was developed to calculate the EA and ER, with numerical and experimental results showing adequate correlation up to 1 kHz. Another published FEM had adapted its boundary conditions to replicate experimental results. Here, we recalculated those numerical results by applying the natural boundary conditions of human hearing and found that the results almost totally agreed with our FEM. This boundary problem is frequent and problematic in experimental hearing test protocols: the more invasive they are, the more the results are affected. One of the main objectives of using FEMs is to explore how the experimental test conditions influence the results. Further work will still be required to uncover the relationship between the middle ear structure and EA to clarify how to best use FEMs. Moreover, the FEM boundary conditions must be more representative in future work to ensure their adequate interpretation.

The sustainable development of an area is highly dependable on reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for the active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller's performance is evaluated in MATLAB environment and simulation results show the proposed scheme's superiority under different operating conditions.

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

In these times electricity is big trouble of problem facing by the world. Therefore, there is necessitating for the property basis of energy that is employed for as bio-electricity. Many of the scientists and researchers are trying to find out the sustainable energy generates with the help of plant microbial fuel cell. Plant microbial fuel cell (P-MFCs) could be feasibility technology approach of bio-electricity generation which is mutualism interaction of the plants along with their rhizospheric bacteria. In the present study, Plant-microbial fuel cell was observed in grass e-table evaluated in term of bioelectricity generation from Cynodon dactylon (Dooba Ghas). This e-table was connected with electrode and different condition (physical and chemical) to detect the change in bioelectric potential. It was found that maximum voltage generated among all the conditions was 4.24 ±2V at 15 days by using Cynodon dactylon through P-MFCs. The potential difference generated through P-MFCs was measured using a multimeter. The generation of bioelectricity was observed under different conditions like exposure to light and shade condition measured for voltage was found to be significantly different parameters. The maximum recorded under light and shade conditions were 3.82 ±2 V and 4.25 ±2 V respectively at 15 days of incubation.

This paper deals with the problem of real-time management of Smart Grids. For this sake, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. The proposed technique is tested with the help of an academic microgrid, so the results may be replicated.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

In this paper, the linear nonequilibrium thermodynamic approach is used to analyze energy processes in the wind energy conversion system (WECS), with a directly connected vertical axis wind turbine (VAWT) and vector controlled permanent magnet synchronous generator (PMSG). Both elements are considered as linear universal energy converters (EC) linearized at the points of the given range of common to VAWT and PMSG angular velocity. The dependences on the angular velocity of the coupling coefficients between the ECs input and output and the dimensionless parameters of their operating modes were received. This allows for choosing the optimal points of ECs operation according to the specified criteria and obtaining indicators of their maximum efficiency. To assess the quality of the cascade connection of two ECs, the appropriate coefficient was introduced, the dimensionless parameters and characteristics of the equivalent EC were obtained, and the conditions of its maximum efficiency were determined. Analysis of the VAWT-PMSG connection quality showed reserves for improving WECS efficiency. The impact of VAWT and PMSG variable parameters on the quality of this connection is studied, and further research directions are shown. The proposed thermodynamic approach allows an effective search for solutions for the efficiency improvement of various systems with energy transfer and transformation.

Designing the future energy supply in accordance with ambitious climate change mitigation goals is a challenging issue. Common tools for planning and calculating future investments in renewable and sustainable technologies are often linear energy system models based on cost optimisation. However, input data and the underlying assumptions of future developments are subject to uncertainties that negatively affect the robustness of results. This paper introduces a quadratic programming approach to modifying linear, bottom-up energy system optimisation models in order to take cost uncertainties into account. This is accomplished by implementing specific investment costs as a function of the installed capacity of each technology. In contrast to established approaches like stochastic programming or Monte Carlo Simulation, the computation time of the quadratic programming approach is only slightly higher than that of linear programming. The model’s outcomes were found to show a wider range as well as a more robust allocation of the considered technologies than the linear model equivalent.

Incorporating renewables in the power grid presents challenges for stability, reliability, and operational efficiency. Integrating Energy Storage Systems (ESS) offers a solution by managing unpredictable loads, enhancing reliability, and serving the grid. Hybrid storage solutions have gained attention for specific applications, suggesting higher performance in some respects. This paper compares the performance of hybrid energy storage systems (HESS) to single battery, evaluating their energy supply cost and environmental impact through optimization problems. The model generates an optimized dispatch, minimizing cost or environmental impact of supplying energy to a generic load while considering battery degradation. Seven technologies are assessed, with an example applied to an industrial site contrasting vanadium redox flow (VRFB) and lithium batteries considering the demand of a local load (building). The results also indicates that efficiency and degradation curves have the highest impact in the final costs and environmental functions on the various storage technologies assessed. For the simulations of the example case, a single system only outperforms the hybrid system in cases where lithium efficiency is higher than approximately 87% and vanadium is lower approximately 82%.

The paper describes and analyzes the performance of a new thermoelectric generation system based on the use of Peltier cells inserted in the ducts of the air conditioning equipment. The hot and cold air streams that flow in the two separated sections of an air conditioning system are used to create a thermal gradient between the two faces of the Peltier cells. Hot and cold air flow inside the A/C unit are driven to a built in thermal chamber where the Peltier cells are placed. Peltier cells are incrusted into an insulation wall that separates the two sections of the chamber through which hot and cold air streams are flowing. The so designed configuration allows the Peltier cells to generate electric current. The study has been run for constant cold air temperature and variable hot air temperature, resulting in a variable performance of the thermoelectric generator. Theoretical study has been completed with experimental tests to determine real performance of the thermoelectric unit. Efficiency of the thermoelectric generator has been found to be linearly dependent on the temperature difference between hot and cold air subsections of the chamber. Maximum efficiency, however, is limited by the hot air stream temperature, since in real conditions ambient temperature cannot overpasses a specific value. For standard operational conditions, 5º C and 45º C for the cold and hot air streams, the thermoelectric generator operates at 44% of the maximum efficiency attainable.

The transportation sector is a significant source of greenhouse gas emissions. Electric vehicles (EVs) have gained popularity as a solution to reduce emissions, but the high load of charging stations poses a challenge to the power grid. Nuclear-Renewable Hybrid Energy Systems (N-RHES) present a promising alternative to support fast charging stations, reduce grid dependency, and decrease emissions. However, the intermittent problem of renewable energy sources (RESs) limits their application, and the synergies among different technologies have not been fully exploited. This paper proposes a predictive and adaptive control strategy to optimize the energy management of N-RHES for fast charging stations, considering the integration of nuclear, photovoltaics, and wind turbine energy with a hydrogen storage fuel cell system. The proposed dynamic model of a fast-charging station predicts electricity consumption behavior during charging processes, generating probabilistic forecasting of electricity consumption time-series profiling. Key performance indicators and sensitivity analyses illustrate the practicability of the suggested system, which offers a comprehensive solution to provide reliable, sustainable, and low-emission energy to fast-charging stations while reducing emissions and dependency on the power grid.

To help reduce the impact of geohazards, an innovative landslide early-warning technology based on an energy demodulation-based fiber optic sensing (FOS-LW for short) technology, is introduced in this paper. FOS-LW measures the energy change in a sensing fiber at the segment of micro-bending, which can be caused by landslide movements, and automatically raises an alarm as soon as the measured signal intensity in the fiber reaches a pre-set threshold. Based on the sensing of micro-bending losses in the fiber optics, a two-event sensing algorithm has been developed for the landslide early-warning. The feasibility of the FOS-LW technology is verified through laboratory simulation and field tests. The result shows that FOS-LW has some unique features such as the graded alarm, real-time responses, remote monitoring, low cost and passive optical network, and can be applied in the early-warning of landslides.

Off-grid electrification planning increasingly recognizes the importance of productive use of electricity (PUE) to promote community value creation and (financial) project sustainability. To ensure a sustainable and efficient integration in the community and energy system, PUE assets must carefully be evaluated to match both the community needs and the residential electricity demand patterns. We propose a novel methodology interlinking qualitative interviews, statistical analysis, and energy system modelling to optimize decision-making for PUE integration in off-grid energy systems in rural Madagascar by aligning relevant PUE effectively with anticipated residential electricity demand patterns based on socio-economic determinants of the community. We find that a possible contribution of the PUE to reducing the electricity costs depends signifi-cantly on three factors: 1. the residential electricity consumption patterns that are influenced by the socio-economic composition of the community, 2. the degree of flexibility of i) PUE assets and ii) operational preferences of the PUE user, and 3. the capacity of community members to finance and operate PUE assets. Our study demonstrates that significant cost reductions for PUE-integrated off-grid energy systems can be achieved by applying our proposed methodology. When matching PUE and residential consumption patterns, the integration of PUE assets in residential community energy system can reduce the financial risk of operators, provided the PUE enterprise operates reliably and sustainably. We highlight that the consideration of local value chains and co-creation approaches are essential to ensure the energy system is addressing the community’s needs, creates value for the community, enhances the project´s financial sustainability, and is achieving the overall objectives of decentralized energy system planning.

The hybrid personal cooling system (HPCS) consisted of ventilation fans and phase change materials (PCMs) covered with insulation pads is a promising wearable cooling system to mitigate heat strain and heat-related illnesses of occupational workers with heavy labor in hot environments. Effects of clothing characteristics (e.g., thermal resistance of insulation pads, latent heat and melting temperature of PCMs) on the thermal performance of the HPCS have been investigated in detail in our previous study. Apart from the aforementioned factors, environmental conditions, i.e., environmental temperature and relative humidity, also significantly affect the thermal performance of the HPCS. In this paper, a numerical parametric study was performed to investigate the effects of the environmental temperature and relative humidity (RH) on the thermal management of the HPCS. Five levels of air temperature under environmental RH=50% were chosen (i.e., 32, 34, 36, 38 and 40 ºC) to study the impact of environmental temperature on the HPCS’s cooling performance. In addition, four levels of environmental RH at ambient temperatures of 36 and 40 ºC were selected (i.e., 30, 50, 70 and 90%) to examine the effect of RH on cooling performance of the HPCS. Results show that high environmental temperatures could accelerate the PCM melting process and thereby weaken the cooling performance of HPCS. In the moderately hot environment (36 °C), the HPCS presented good cooling performance with the maximum core temperature at around 37.5 °C during excise when the ambient RH≤70%, whereas good cooling performance could be only seen under RH≤50% in the extremely hot environment (40 °C). Thus, it may be concluded that the maximum environmental RH for the HPCS exhibiting good cooling performance decreases with the increase in the environmental temperature.

Excess energy from photosynthesis can be collected through biophotovoltaic platforms to generate green electrical power. This research evaluated the in-situ performance of different CAM (Crassulaceae acid metabolism) plants from Calama city located in the Atacama Desert for energy recovery as biophotovoltaic cell (BPV) using AISI 316L and Cu as electrodes. The species evaluated were Aloe perfoliata, Cereus jamacaru, Austrocylindropuntia subulata, Agave potatorum, Malephora crocea, and Kalanchoe daigremontiana. The results indicate that K. daigremontiana can be used as in-situ BFV because it has a maximum cell potential of 0.248 V and a minimum of 0.139 V with a recurrence close to 89% in the ranges [0.2 - 0.25] V. This is one of the few investigations that evaluate the potential of native CAM plants as BFV energy sources, providing new knowledge for the development of sustainable alternatives for horticultural crop production systems.

We introduce a total energy and environmental evaluation method in the manufacturing industry. The method gives us a series of descriptive indexes to assess the overall environmental effect level on materials, energy, wastes and products in the life cycle process. Meanwhile, the method uses partial indexes, environmental effect factors, and correction offsets into the quantitative model to analyze the learning process and rebound effect on the energy and environment at each procedure. In this work, we choose S-shaped learning curves to describe how to decrease energy consumption and improve the technical learning by doing for recent 30 years. Also, we draw the different rebound effect curves of the total energy-environmental evaluation with technical learning method, which use the annual industrial production growth rate to show that it's significant to estimate its effect on technology changes. The ideas about the interaction of energy and production environment from material flows to energy consumption, direct us to build an example to estimate quantitatively the results with different condition factors, and realize the process improvement and develop new products.

This panel study investigates the relationship between green logistics indices, economic, environmental, and social factors in the perspective of Asian emerging economies. This study adopted FMOLS and DOLS methods to test research hypothesis, catering the problem of endogenity and serial correlation. The results suggest that logistics operations, particularly LPI2 (efficiency of customs clearance processes), LPI4 (quality of logistics services) and LPI5 (trade and transport-related infrastructure), are positively and significantly correlated with per capita income, manufacturing value added and trade openness. While, greater logistics operations are negatively associated with social and environmental problems including, climate change, global warming, carbon emissions, and poisoning atmosphere. In addition, human health is badly affected by heavy smog, acid rainfall, and water pollution. The findings further extend and reveal that political instability, natural disaster and terrorism are also a primary cause of poor economic growth and environmental sustainability with poor trade and logistics infrastructure. Further, the application of renewable energy resources and green practices can mitigate negative effects on social and environmental sustainability without compromising the performance of economic growth. There is very limited empirical work presented in literature using renewable energy and green ideology to solve macro-level social and environmental problems, while this study will assist the policymakers and researchers to understand the importance of green concept in improving countries’ social, economic and environmental performance.

As the EU is moving towards a low carbon economy and seeks to further develop its renewable energy policy, this paper quantitatively investigates the impact of plausible energy market reforms from the perspective of bio-renewables. Employing a state-of-the-art biobased variant of a computable general equilibrium model, this study assesses the perceived medium-term benefits, risks and trade-offs which arise from an advanced biofuels plan, two exploratory scenarios of a more 'sustainable' conventional biofuels plan and a 'no-mandate' scenario. Consistent with more recent studies, none of the scenarios considered present significant challenges to EU food-security or agricultural land usage. An illustrative advanced biofuels plan simulation requires non-trivial public support to implement whilst a degree of competition for biomass with (high-value) advanced biomass material industries is observed. On the other hand, it significantly alleviates land use pressures, whilst lignocellulose biomass prices are not expected to increase to unsustainable levels. Clearly, these observations are subject to assumptions on technological change, sustainable biomass limits, expected trends in fossil fuel prices and EU access to third-country trade. With these same caveats in mind, the switch to increased bioethanol production does not result in significant market tensions in biomass markets.

This paper proposed a damping method for enhancing oscillatory stability performance of power systems with high penetration of renewable energy by a resilient wide-area multi-mode controller. The resilient wide-area multi-mode controller is used as an additional controller in a renewable energy system with a battery energy storage to enhance the damping of the critically weak modes. The weak modes are likely to be triggered in the event of line outages or any other disturbances, and the system may become unstable in the absence of proper corrective and preventive control. A firefly algorithm has been employed to design such a controller. Eigenvalue analysis and time-domain simulation are used to analyze the performance of the proposed controller in a realistic representative power system. From the simulation results, it is evident that the oscillatory stability performance of the renewable rich power system can be enhanced with the proposed control to keep the damping on critical modes to the industrial standards. Furthermore, renewable energy penetration can be increased significantly in the realistic representative system by introducing the proposed controller without disturbing the oscillatory stability margin.

The research investigates the role the environmental manager plays to ensure a successful (or not) implementation of environmental performance within an organization. It is based on interviews of 5-7 actors per company within a sample of 7 companies (42 interviews). We build upon bias of perception of the various actors interviewed within each company to define 4 paradoxes related to the roles and mission of the environmental manager that hinder proper efficiency of environmental management at company level. Paradox 1 is that no one takes ownership of environmental performance within the organization. Paradox 2 is that the environmental manager is in an awkward situation vis-à-vis his boss. Paradox 3 is that the role of the environmental manager is ambiguous vis-à-vis employees. Paradox 4 is that corporate and product approaches are decoupled. We suggest that these paradoxes interact and form a vicious cycle that may in part be responsible for the environmental decoupling phenomenon – the fact that companies often adopt a sustainability policy symbolically without implementing it substantively. Our research suggests that, by leveraging the leadership of the environmental manager through organizational and motivational measures, the vicious cycle can be transformed into a virtuous cycle and the human motivation can become a driver for green change within corporations. We proposed the SEA (Shaping Environmental Action) model based of 4 pillars: information, motivation, organization and strategy.

There has been a growing awareness of the need to implement environmentally friendly operations in the hotel industry, but most studies focus on guest behaviors. Only a few studies investigate employees’ willingness to comply with hotels’ green practices. This study seeks to further the investigation from the human resource perspective. Using alumni from a tourism and hospitality programs, this study collected 233 responses. The study hypothesizes that the employees’ green ability consisting of environmental awareness, environmental knowledge, and environmental skill creates a positive impact on hotels’ green ability. The results indicate that employees contribute approximately a fifth of hotels’ ability to implement greener practices.

Huge amounts of wastes are generated during shrimp processing, representing approximately 65% of the initial shrimp weight, which can become an environmental problem when accumulated. Residues such as shrimp shells can be processed to obtain value-added products such as chitin, chitosan, astaxanthin, and a nitrogenous extract under the biorefinery concept. In this work, the economic evaluation and the techno-economic sensibility analysis for a mass integrated biorefinery based on shrimp were developed to determine the economic feasibility of the project and to identify the critical techno-economic variables that affect the profitability of the process. The results showed that a biorefinery for the annual processing of 4,113.09 tons of fresh shrimp in Colombia is profitable, with a return on investment percentage (%ROI) equal to 65.88% and a net present value (NPV) of 10.40 MM USD. The process supports decreases of up to 28% in capacity of production and increases of 12% and 11% in the cost of raw materials and variable operating costs without incurring losses, respectively. However, the decrease over 500 USD/t in the shrimp meat selling price is not supported, thus it is mainly recommended to increase the selling price of this product.

Delivering effective messages is critical to creating a more sustainable and resilient culture. The explosion of social media has enhanced information access but has often reinforced and polar-ized pre-existing viewpoints and norms. In contrast, digital signs are an “in your face in your space” technology that has the potential to deliver common content to a diverse local audience. Environmental Dashboard (ED) is a communications platform and set of content applications that combines information on current environmental conditions, real-time resource consumption, positive actions being taken by community members, and a community calendar. We conducted a longitudinal study to assess whether ED content delivered via digital signs in public locations would result in desirable psychological changes within a community. Participants completed surveys in six designated signage locations prior to installation (N = 174) and following two years of continuous exposure (N = 133). We observed: increases in pro-environmental social norms among people of color (a demographic emphasized); enhanced awareness of and sense of connection with the local community and ecology; increased self-reported electricity conservation; and increased perception of youth engagement (another demographic emphasized). Changes were mediated by exposure to digital signage. These findings support the hypothesis that content delivered through digital signs can strengthen pro-environmental and pro-social culture within communities.

To support the integration of renewable energy sources and preserve grid stability, this study examines several approaches for controlling the temperature of Battery Energy Storage Systems (BESS) in modern energy settings. Specifically, the usage of BESS in Virtual Power Plants (VPPs) is the focus of this study. The effectiveness, safety features, dependability, affordability, and suitability for VPP applications of these systems are examined. Among the various hybrid cooling alternatives, two particularly promising combinations emerge. Firstly, the integration of heat pipes and phase change materials leverages their ability to conduct heat efficiently away from heat sources with minimal temperature differences, making them excellent for rapid heat transfer. Secondly, an approach employing heat pipes and liquid passive cooling a combination that capitalizes on the efficient heat transfer capabilities of heat pipes and the consistent cooling offered by liquid passive systems. The study underscores the importance of improving BESS performance and sustainability within VPPs by providing useful recommendations for choosing the best thermal management system depending on climate conditions and geographic location.

With the increasing prominence of renewable energy sources providing flexibility to the power grid, there is a growing recognition of the need to expand virtual Energy Storage Systems (ESS) to replace traditional ESS, which faces challenges in terms of supply and scalability. Grid-connected microgrids can supply power stably and are being built, so they can be used as virtual ESS to provide flexibility to the power system. This study proposes an approach to determine the optimal Power Conversion System (PCS) and battery capacity for a Virtual Energy Storage System(VEES) based on a grid-connected microgrid incorporating Photovoltaic (PV) and ESS. In this paper, it is assumed that microgrids can provide flexibility to the grid by participating in the energy trading market, there are corresponding profits and penalties for order. Numerical examples are performed to demonstrate the effectiveness of the proposed method.

Water is one of the most critical factors affecting environmental health. For this reason, estimating and monitoring the behavior of water in nature and preventing water pollution before it occurs are advantageous to avoid problems that may occur in terms of environmental health. In order to predict the behavior of water, the hydrological cycle needs to be evaluated on a basin basis. At this point, hydrological models can be used to make mathematical representations of hydrologi-cal processes. These models play an essential role in predicting and monitoring problems such as poor water quality, pollution, particle and sediment transport, and proliferation of oil and petro-leum derivatives among frequently encountered issues in environmental health. In this study, a 2D surface water model was created using soil and water assessment tool (SWAT) to simulate the lotic ecosystem and existing water quality in Tatlıçay Basin and to propose solutions for im-proving environmental health in Cankiri provincial center in Türkiye. The accuracy of the input data and the validity of the model were checked with the calibration and validation studies by using the monthly or 3-monthly observation data of the General Directorate of State Hydraulic Works’ flow observation & water quality stations from 2016 to 2020. The aim was to provide the opportunity to produce fast, accurate, and practical solutions in the face of negative scenarios with this model. This modelling study obtained successful results in the calibration and valida-tion process with very few observed data. With this study, a significant contribution to the litera-ture on environmental health is made, as there aren't many examples of hydrological modeling from the Middle East.

The purpose of this paper is to describe a new way of producing renewable energy based on fjords as a water heater. We will call this system the Water-thermal Energy Production System (WEPS), because the basic idea is to extract heating and cooling energy from water. Although a prototype of WEPS has existed in Norway for more than ten years, a WEPS currently in operation has not been financially analyzed in the literature. Coastal parts of Norway have a potential of 5 TWh of profitable WEPS-facilities [9], due to convenient access to fjords containing water with stable all-season temperatures of about 4–12C when the depth of the water is about 50 meters. This stability of the water temperature makes it possible to extract energy from the fjord in a very efficient way. The potential for economically-profitable WEPS in other parts of the world has not been estimated. In order to answer such a question, more research is required. We have conducted a case study of a WEPS located in the Norwegian municipality of Eid. This is the first full-scale Norwegian WEPS, and it has been operating since 2006. The nascent years have passed, and the technology has been in operation for some years. In this paper, we have made an estimate of the business profitability and the external effects based on past empirical evidence and some assumptions about future development in some key figures. The results suggests that WEPS-Eid has been a profitable investment carrying a positive internal rate of revenue, even if the present underutilization in production capacity will continue in the future. Stability in energy prices for heating purposes has also gained customers compared to the more volatile prices of alternative renewable energy, like hydropower or wind turbines. The negative, external effects in the operating phase from WEPS-Eid are insignificant. Despite the significant profitability of the WEPS facility in Eid, there are two main obstacles for new entrants. There is a lack of relevant operational information for potential investors due to few facilities. This leads to uncertainty, and investments in WEPS appear as a risky business. Secondly, construction of a WEPS requires both big financial investments in digging and facilitating long trenches for a pipeline system and time and effort spent on acquiring the licenses needed for doing this work. A coordinating unit is probably required in order to get the necessary public and private licenses and to reduce fixed costs by coordinating other tasks in the same trenches, like pipes for water and sewer, fiber cables and tele-cables. In Eid, the local municipal administration was the coordinating unit.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

Coastal wave modeling and forecasting are essential in oceanography, sustainable marine energy, and ocean engineering. Precise forecasting of wave speed and direction are crucial for offshore operations, marine energy, risk management, environmental management, coastal and sustainable maritime management. The coastline of Brunei Darussalam can generate between 15 and 126 Giga Watt of wave energy. In this experimental research, we used two numerical approaches, the finite difference, and spectral element methods, to model and simulate wave speed and direction. We calculated the mean error between numerical and analytical solutions. We proposed a novel, promising, univariate time series forecasting model by combining the Long Short-Term (LSTM) with KerasTuner hyperparameters tuning and optimization techniques. This method helps us to improve the accuracy and efficiency of time-series forecasting.. The experimental data was computed from high-precision Acoustic Doppler Current Profiler (ADCP) sensor data. This research is part of the preliminary feasibility analysis of wave energy production in Brunei Darussalam and net zero commitment for a sustainable environment. Seven independent forecast experiments were performed for wave speed and direction in degree and radian units for 1, 3, 6, 8, 10, 12, and 24 hours. Mean squared error (MSE) was adopted as a metric for both training and testing. The experimental results reveal that the wave speed forecast has the lowest MSE compared to direction, regardless of the unit of measure, but has a longer duration. In addition, the direction forecast in the degree unit has the lowest errors compared to the unit of radians; the latter has a longer running time than the former. The model has delivered optimal results throughout the experiments with minor training and test errors. We conducted a thorough evaluations on two benchmark time series datasets, which include the study dataset and air quality index dataset, to validate the performance of the proposed model with other models. The proposed model outperforms cutting-edge forecasting models, such as the conventional LSTM, ARIMA, and Prophet. The model has the slightest forecast error compared to the existing literature’s result.

This study focused on the predictive models incorporating machine learning techniques that induce new dynamics for forecasting energy generation, enabling effective planning, financing, and system monitoring. The research developed a machine learning-based power generation prediction model tailored explicitly for Kenya's Garissa solar power plant. The selected model demonstrated a root mean squared error of 5.23 during evaluation, resulting in a prediction accuracy of 90.42%. This high accuracy indicates that the model can be relied upon for precise generation prediction, facilitating effective planning, and system performance monitoring

This study aimed to evaluate a cantilever beam-type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. The harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress were calculated with greater precision using eigenfrequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.

Thermoelectric (TE) waste heat recovery has attracted significant attention over the past decades, owing to its direct heat-to-electricity conversion capability and reliable operation. However, methods of system-level TE design optimization for specific application systems have not been thoroughly investigated. This work theoretically studies the performance optimization and exergy analysis of TE systems for recovering waste heat from the exhaust ducts of a gas turbine power plant. A numerical tool has been developed to solve the coupled charge and heat current equations with temperature-dependent material properties and convective heat transfer at the interfaces. Our calculations show that at the optimum design with 50 % fill factor and 6-mm leg thickness made of state-of-the-art Bi2Te3 alloys, the proposed system can reach power output of 10.5 kW for the TE system attached on a 2 m-long, 0.5 x 0.5 m2-area exhaust duct with system efficiency of 5 % and material cost per power of 0.23 $/W. Moreover, our extensive exergy analysis reveals that only 1 % of the exergy content of the exhaust gas is exploited in this heat recovery process and the exergy efficiency of the TE system can reach 8 % with improvement potential of 85 %.

This paper is regarding design and program an Micro-controller Arduino Uno board by using Arduino software to work as a photo-sensor(Active) single axial solar tracker system(SASTS). A solar panel, two photo-resistors (LDR) in two sides (north/south) of the photo-voltaic(PV) and a servo motor are connected to the Uno board, which is running a code that prepared by Arduino software IDE in advanced then it works as a tracking system. Here, the LDRs send the signal of presence or absence of the light to the board and based on that sent signal the Uno reflects a new signal to the servo motor to rotate and finds the light source. Lastly, the photo-sensor single axis tracker is made while Continuously, the system tries to face the panel to the sun and whilst changing the irradiance intensity it starts searching to find the angle of highest irradiance. Based on results that are extracted from the data, the tracker system significantly boosts the output efficiency of the solar panel. By using the Micro-controller Uno board, LDRs, servo motor and special designed mechanical base, the tracking system is constructed, based on acquired data the influence of the STS on the increasing the solar panel efficiency is more obvious. Significantly, the tracker system rises the efficiency of the PV .

IoT system becomes hot topic nowadays for smart home, IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circular polarized array rectenna system to harvest enough power from any direction to increase life time of the batteries used in IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node and low power microcontroller are used to operate in lower power modes. The proposed system has an 84.6 days lifetime which is approximately 10 times the lifetime for similar system. On the other hand, the proposed power management circuit operated at 0.3 V DC to boost the voltage to ~3.7V from radio frequency energy harvesting and manage battery level to increase the batteries lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a non-static plan, approve energy consumption and avoiding failure of sensor nodes in smart home.

This conceptual article is aimed at evaluating the COVID19 impacts on the global economy and to postulating an ‘economic paradigm shift’. We argue that the existing economic, political, and trade principles have been challenged due to the global pandemic issue. We also compare the COVID19 impact on Western countries and Eastern countries with their control mechanisms. The emerging of new economies is due to the travel restrictions and disrupt of the global economies are discussed that pave a gateway to the economic paradigm shift. The article finally assesses the advent of 5G technology and its implications to face any future health threats that will lead to the next economic paradigm shift in the modern world.

The imperfection of theoretical and methodological approaches to regulate the jump process transition when combining differentiated energy resources is a pressing issue. The goal of this paper is to develop a theory and a method to regulate the integration-balancing processes of combining diversified resources. The concept of combining integration and balancing models has been substantiated by methods of transforming multidimensional space and approximating generalized functions that represent jump-like processes. Theoretical and operational-regulatory models of economic sustainability have been developed, substantiating new concepts, patterns, properties, dependencies and indicators of the dynamics of the processes of combination; the optimality conditions for the number of approximations of generalized functions, interpreting the effects of control functions of combining resources, are determined. New methods for solving problems have been developed: the organization of the energy technology complex of facilities for enhanced resource diversification and the Center for Sustainability, improving the quality of managing dynamic processes in terms of combining and diversifying resources.

Many factors drive land desertification, especially in arid and semi-arid regions. However, the numerous driving factors of desertification make analyses computer expensive. Cloud computing comes along to address this problem, especially in developing countries. The objective of this work was to assess the sensitivity of the East Atlantic Basin, Brazil, to desertification using the Mediterranean Desertification and Land Use (MEDALUS) model and Google Earth Engine (GEE). The model is composed of four environmental Quality Indices (QIs) associated with soil (SQI), vegetation (VQI), climate (CQI) and management (MQI), and contains factors influencing the desertification process. Digital databases of the factors were pre-processed and uploaded to GEE for analysis. We report Environmentally Sensitive Areas (ESAs) and Environmentally Critical Factors (ECF) maps of the East Atlantic Basin, which showed that most of the basin is in either critical (49.4%) or fragile (35.7%) state of sensitivity. In contrast, only a smaller portion of the area is unaffected (5%) or potentially affected (10.1%). Sensitivity to desertification was inversely correlated with the presence of vigorous vegetation. A joint analysis of ESAs and ECF shed light on the importance of each factor in the sensitivity to desertification. The East Atlantic Basin shows a high degree of sensitivity to desertification, thereby demanding more attention and establishment of measures to mitigate the negative impacts of the desertification process.

Many factors drive land desertification, especially in arid and semi-arid regions. However, the numerous driving factors of desertification make analyses computer expensive. Cloud computing comes along to address this problem, especially in developing countries. The objective of this work was to assess the sensitivity of the East Atlantic Basin, Brazil, to desertification using the Mediterranean Desertification and Land Use (MEDALUS) model and Google Earth Engine (GEE). The model is composed of four environmental Quality Indices (QIs) associated with soil (SQI), vegetation (VQI), climate (CQI) and management (MQI), and contains factors influencing the desertification process. Digital databases of the factors were pre-processed and uploaded to GEE for analysis. We report Environmentally Sensitive Areas (ESAs) and Environmentally Critical Factors (ECF) maps of the East Atlantic Basin, which showed that most of the basin is in either critical (49.4%) or fragile (35.7%) state of sensitivity. In contrast, only a smaller portion of the area is unaffected (5%) or potentially affected (10.1%). Sensitivity to desertification was inversely correlated with the presence of vigorous vegetation. A joint analysis of ESAs and ECF shed light on the importance of each factor in the sensitivity to desertification. The East Atlantic Basin shows a high degree of sensitivity to desertification, thereby demanding more attention and establishment of measures to mitigate the negative impacts of the desertification process.

Introduction: Different factors such as rapid growth of population, urbanization and industrialization of communities have detrimental effects on the environment. In regard to the importance of the environment and its fundamental role in sustainable development along with the awareness and attitude of the people of Yazd which has not yet been assessed, this study aims to assess the level of awareness, attitude and environmental literacy of the people of Yazd in relation to environmental issues and challenges in the year 2017. Materials and methods: In this descriptive-analytical study, the sample size was obtained from 410 Yazd city residents through prior studies and the Cochran formula. The sample was then selected by the stratified random sampling method. The data selection tool was a questionnaire with questions on demographic characteristics, awareness level, attitude and practices in relation to menopause. The data was analyzed upon collection by the SPSS-20 software and Mann-Whitney, Kruskal-Wallis, and Chi-Square non-parametric tests along with the Spearman correlation test. In this study, the significance level was considered as 0.05. Results: In this study, a total of 404 questionnaires were completed and evaluated. Based on the obtained results, 224 individuals (55.4%) male, 53.3% married, 31.2% had at least a bachelor’s degree and the majority of individuals (40.1%) were in the 18-27 age group. In terms of area of residence, 64.1% reside in region 2. From all the participants, 51.3% of the participants believed that the main environmental issue in Yazd was water deficiency and pollution. The awareness score was statistically significant with the age, education level and employment status variables. Attitude only had significant relationship with the employment status variable. The relationship between the practices score was statistically significant with the age, marital status, and area of residence variables. There is a significant relation between age, income level and knowledge level but there is no significant relation with attitude levels. There is no significant relation between gender, education level, marital status, area of residence, awareness and attitude levels (p-value > 0.05). There is a positive correlation between awareness, attitude and practices scores. The results indicated that the attitude score of most participants (51.5%) was lower than the average score but the awareness and practices score of most participants was average. Conclusion: Based on the results of this study, although the awareness of Yazdi citizens on some environmental issues and institutions that are active in the environmental pollution control field in the country appears low, but in general, the awareness of the people of Yazd, specifically regarding health issues stemming from pollution was assessed as adequate. Considering the importance of environmental factors’ role in communities’ health and its continuous improvement, due to the expansion of automated life namely in large cities within the country, it is necessary to conduct various researches to identify and control these factors and to carry out interventional studies to determine suitable solutions before implementing them.

This comprehensive critical review shows how green buildings and energy optimization solutions improve indoor air quality as well as environmental quality (IEQ) and human health. Electricity-efficient green buildings create a better indoor atmosphere and save electricity. Green buildings improve occupant well-being through IAQ, thermal comfort, acoustics, and lighting. Renewable energy, green construction materials, and intelligent technologies increase sustainability and reduce environmental impact. Environmental hazards, architectural design, and societal variables can improve indoor air quality and subsequently reduce health risks linked with poor air quality. The evaluation highlights the pros and cons of low-cost IAQ sensors and equipment. These devices provide valuable insights, but calibration and validation using reference equipment are necessary to ensure accuracy and reliability. Architects, engineers, environmentalists, and policymakers are essential in creating green buildings with high IEQ. Prioritizing occupant comfort, health, and productivity ensures a sustainable and healthy future for future generations. However, continual monitoring and research are needed to improve green building practices and overcome construction problems. Intelligent models for continual on-field calibration of low-cost sensors may improve performance. Green buildings benefit occupants and the environment by optimizing energy use and using IAQ monitoring technologies.

The rationale of this study is to explore underlying sustainability assessment constructs in the context of WCSM implementation as a key focus by manufacturing industries in the journey of achieving world-class status in their manufacturing operations. This study primarily intends to collect primary data from 143 plant managers and supervisors through the structured questionnaires at select manufacturing companies in south India on the basis of area-cum-purposive sampling technique. The survey questionnaire is designed exclusively to reflect the sustainability assessment dimensions in terms of social, economic and environmental issues to examine the impetus of WCSM implementation on the competitive advantage of manufacturing companies. The empirical findings of this study clearly revealed that sustainable manufacturing practices, sustainability programs, creation of sustainable products, safety for employee, community and product, operational efficiency and integration of sustainability goals in day-to-day manufacturing activities were considered to be the key indicators by the manufacturing firms in their never-ending journey towards becoming the world class. Moreover, the WCSM practices & techniques adopted by sample manufacturers have a substantial positive influence on the achievement of competitive advantage in their manufacturing and business operations.

Keywords: Energy harvesting, Hybrid, Medical Wearable Sensor Nodes, Health Monitoring, Power Management

In recent years, the application of Indoor Positioning Systems (IPS) has experienced a significant increase in demand, with the aging of the world’s population and their changing lifestyles. While outdoor positioning systems, such as the Global Positioning System (GPS), have significantly advanced over the years, indoor positioning has been restrained by the limitations of the employed technologies. This paper presents a hybrid wireless positioning system able to locate wearables indoor accurately. It is based on the Wi-Fi and Bluetooth technologies, by using trilateration to determine the position of Bluetooth low energy (BLE) wearable devices with an accuracy of up to 1.8 meters. A graphical user interface (GUI) was used to illustrate the performance of the proposed systems, by allowing users to visualize the captured data in two dimensions and three- dimensions in real-time.

We present a method to turn results of model-based optimisations into resilient and comprehensible control strategies. Our approach is to define priority lists for all available technologies in a district energy system. Using linear discriminant analysis and the results of the optimisations, these are then assigned to discrete time steps using a set of possible steering parameters. In contrast to the model-based optimisations, the deduced control strategies do not need perfect foresight but solely rely on data about the present. Our result indicate that the results of the control strategies obtained using the proposed method are comparable to the results of the linear optimisations, in our case in terms of emissions and prices.

The scientific community has shown considerable interest in Industry 4.0 due to its capacity to revolutionise the manufacturing sector through digitalisation and data-driven decision-making. However, the actual implementation of Industry 4.0 within complex industrial settings presents obstacles that are typically beyond the scope of mainstream research articles. In this paper, a comprehensive case-study detailing our collaborative partnership with a leading medical device manufacturer is presented. The study traces their evolution from a state of limited digitalisation to the development of a digital intelligence platform that leverages data and machine learning models to enhance operations across a wide range of critical machines and assets. The main business objective was to enhance the energy efficiency of the manufacturing process, thereby improving its sustainability measures while also saving costs. The project encompasses energy modelling and analytics, Fault Detection and Diagnostics (FDD), renewable energy integration and advanced visualisation tools. Together, these components enable informed decision making in the context of energy efficiency.

Sustainability means that the current use of resources does not compromise the well-being of future generations. Ever since Malthus (1798) forecast that population tends to grow faster than the growth of resources to support the population, people have claimed that current resource use is unsustainable, so future generations will be materially worse off than those in the present, yet for more than two centuries this has not been the case. The reason is that markets, and market prices, act to conserve scarce resources, and in market economies, entrepreneurs have an incentive to discover more efficient ways to use resources. The claim that twenty-first century market economies are not sustainable is not supported by the evidence. This paper explains why entrepreneurship in market economies produces sustainable economic progress.

The increasing deployment of intermittent renewable energy sources necessitates effective methods for balancing the electrical grid to ensure stability and safety. Energy storage systems that can store excess electrical power during periods of low demand and release it during high demand are crucial for both short-term and long-term applications. Power-to-Gas is an innovative energy storage solution that converts surplus renewable electricity into gas fuels, such as hydrogen, which can be stored and used later. This hydrogen can serve multiple purposes, including energy storage and as fuel for transportation modes like cars, trams, trains, and buses. While most hydrogen today is derived from fossil fuels, solid-oxide electrolysis (SOE) offers a cleaner alternative by producing hydrogen without harmful emissions. SOE is also the most efficient method of electrolysis. This study aims to determine the operational parameters for an SOE system, including lower heating value (LHV)-based efficiency and total input power, using a mathematical model. Results are presented for three different operating temperatures and four different steam utilization ratios. The paper is structured as follows: the introduction provides the context and motivation for the study; the second section outlines the fundamentals of electrolysis and its various types; the third section delves into solid-oxide electrolysis and electrolyser systems; the fourth section describes the methodology, including the mathematical formulation and simulation software used; the fifth section presents the calculation results and conclusions; and the final section summarizes the findings.

The advent of remote work has ushered in a new era of economic transformation, redefining the dynamics of local economies, and unleashing the multiplier effect on a national scale. This abstract explores the profound implications of remote work on local economies, dissecting how the multiplier effect operates within a nation's economic landscape. The multiplier effect is a fundamental economic concept that highlights how changes in spending and investment can create a ripple effect, leading to a magnified impact on an economy. This concept gains new significance in the context of remote work, as it triggers a chain reaction of economic activities that radiate from remote workers to their local communities. The increased flexibility and reduced geographical constraints of remote work have reshaped the allocation of resources. The continued reliance on remote work may lead to a reduction in demand for commercial real estate in urban centers, necessitating adaptive urban planning strategies. In conclusion, the rise of remote work has initiated a transformative era for local economies, driven by the multiplier effect. By amplifying the impacts of spending and investment, remote work fosters job diversification, innovation, and infrastructure development within communities. As remote work continues to reshape the landscape of work and life, understanding and harnessing its multiplier effect remains paramount for policymakers, businesses, and local communities alike. The multiplier effect is a concept in economics that illustrates how changes in spending can lead to larger impacts on a nation's economy through a chain reaction of economic activities. It demonstrates that an initial injection of spending, whether from government expenditure, investment, or consumption, doesn't just have a one-time impact. Instead, it sets off a series of interconnected spending and income-generation processes that result in a larger overall increase in economic activity. t's important to note that the multiplier effect can work in reverse as well. If there's a decrease in spending, it can lead to a decrease in economic activity and income through the same chain reaction process. This concept highlights the interconnected nature of economic activities and emphasizes the significance of changes in spending patterns on a nation's overall economic health. The magnitude of the multiplier effect is influenced by factors such as the marginal propensity to consume (the proportion of additional income that households spend), leakages (savings and taxes that reduce the multiplier effect), and the extent to which additional spending creates additional production capacity within the economy. Understanding the multiplier effect is essential for policymakers, as it helps them gauge the potential impacts of changes in fiscal and monetary policies on the economy.

Uzbekistan, as an emerging national economy, aims to attract foreign direct investment (FDI) to foster the development of its free economic zones (FEZs). While recent policy reforms have enhanced the country's appeal to investors and facilitated the inflow of international capital, challenges persist in attracting investment. This study employs an economic geographical approach to analyze and propose solutions to these obstacles. By examining the spatial patterns of FEZs and FDI through a comprehensive geographical lens, this research utilizes document analysis as an alternative to empirical analysis, considering the broader context rather than focusing on a specific FEZ. The findings reveal that the insufficiency of an innovation-driven environment, logistical systems, energy resource-related issues, among others, negatively impact the inflow of FDI into FEZs. Moreover, the study underscores the significance of economic geography in understanding these factors. Finally, relevant insights and recommendations are provided from an economic geographical perspective.

Introduction: Pre-Exposure Prophylaxis (PrEP) for HIV prevention has been implemented in several countries. Previous literature has shown that its cost-effectiveness (and, under some specifications, cost-saving character) is dependent on the reduction in price due to generics, the time-horizon and its effectiveness. The intervention has never been studied in Catalonia, a territory with extensive implementation. Methods: Economic evaluation of the implementation of HIV pre-exposition prophylaxis using administrative data from Men who have Sex with Men (MSM) who receive the treatment (at the generic price). A deterministic compartmental model and a social perspective with a micro-costing approach over the time horizon 2022-2062 are used. A baseline 86% effectiveness of PrEP is assumed. Results: Daily oral PrEP is found to be cost-saving: discounted savings in costs are attained after 16 years, and after 40 years they reach 81 million euros. In terms of health indicators, 10,322 additional discounted QALYs are generated by the intervention. Results are sensitive to sexual behavioral patterns among MSM, the price of PrEP (reduced if offered on-demand), its effectiveness and the discount rate. Conclusions: The use and promotion of PrEP in Catalonia is predicted to result in substantial health and monetary benefits because of reductions in HIV infections. Short-term investments in the promotion of PrEP will result in important cost-savings in the long term.

This study was conducted to propose the Green Economic Development Plan for Manufacturing S.M.E.s based on financial performance and operations thru Green Initiatives. The descriptive survey method used to gather data to determine the green initiative's implementation of small and medium (S.M.E.s) manufacturing enterprises. Green initiatives use as a basis for crafting a green economic development plan. Document analysis was also employed to obtain data from any available printed materials and records provided by the respondents. Such methods of gathering information used to validate data gathered from local and foreign-related literature. The observation also employed to survey the assets owned and validate any green initiatives practiced, including their implementation. The study's findings show that among the green initiatives implemented by SMMEs, which resulted in the reduction of total costs and expenses, were the proper disposal and segregation of waste materials, water management by recycling wastewater and using water-efficient equipment, natural resources, and raw materials management. SMMEs should encourage active participation and support of suppliers and customers in achieving G.E.D.'s objectives by developing incentive schemes.Furthermore, SMMEs should continue to benchmark with G.E.D. Practitioners are operating locally and abroad to adopt best greening strategies and regularly network with concerned government agencies for continuous updating on G.E.D. Initiatives that may benefit the firm. Further research may be conducted on green initiatives implemented by small and medium enterprises in other industry sectors.

The pressure on freshwater resources is leading to diminishing flows in some of the critical river systems across the globe and India is no exception and this is mainly because of water withdrawal for irrigation, which is often to the tune of 70% to 80% with some proportion for domestic and industrial use. While graduating from the concept of environmental flows and its assessment methodologies in India, the water-managers, the researchers and the conservationists are now moving towards answering the next question if the rivers are to be revived, then where will the water come from, especially in the case of over-allocated rivers, including the river Ganga. While the logical way is to look at the biggest user of water, i.e. irrigation, it remains to be seen whether the irrigation water savings will actually lead to enhancing flows in a river, complementing the efforts towards maintaining e-flows in rivers, or whether it will lead to more area under agriculture, bring changes in cropping patterns towards more water-intensive crops or result in something else. This is a growing debate across the globe, where India is no exception, and there has been a wide range of opinions in this regard. This paper discusses the process, findings and lessons from a joint initiative involving farmers, the Uttar Pradesh state Irrigation and Water Resources Department, Bijnor District Administration and a conservation organisation to enhance flows in a rivulet, called karula River, which is part of the Ganga river system.

Static voltage stability has become one of the significant risks faced by large-scale renewable energy integration. However, traditional methods for static voltage stability analysis are often overly complex. This paper constructs an equivalent impedance model for renewable energy integrated distribution power systems, proposing a static voltage analysis method for renewable energy integrated distribution power systems based on impedance model index. This method has been verified to be applicable not only to renewable energy single-infeed system but also to multi-infeed system. Furthermore, an analysis is conducted on the influence of the integration capacity, location of renewable energy, and the topology of networks on impedance model index, indicating that a higher impedance model index corresponds to greater static voltage stability margins in the system. Hence, during the planning of renewable energy integration, the plan with the highest impedance model index should be selected. Finally, the accuracy of the analysis methods and conclusions in this paper was validated based on the IEEE 14-node system.

Since the energy sector is the main source of greenhouse gases, it has the highest potential for improvement. Improvements can be achieved by generating energy from renewable sources. Combined with thermal energy storage, concentrating solar power plants represent a promising technology for dispatchable renewable energy, ensuring a stable energy supply even in remote areas without contributing to greenhouse gas emissions during operation. However, it is important to note that greenhouse gases and other polluting emissions may occur during the manufacturing process of concentrating solar power plant components. This work analyses the design of the receiver to produce thermal energy for the existing solar dish CSP plant at the Energy Center of the Politecnico di Torino. The objective of this plant is to produce hot water for a small case study. Considering the average solar irradiance for Turin equal to 800 W/m2, the surface heat flux was obtained from the first part of the analysis, which was used to obtain the maximum internal temperature in the receiver equal to 873.7 °C. The maximum temperature obtained was a constraint for the selection of the material for the solar receiver. Of the various possibilities, copper was chosen. In the second part of the work, a Life Cycle Assessment was carried out to compare the emissions generated during the production of the main components of the CSP plant with the emissions generated by the methane-fuelled water heater that produces the same amount of water as the CSP plant. It can be concluded that the manufacture of the main components of the CSP plant results in lower greenhouse gas emissions than the operational phase of a conventional natural gas-fired water heater (1.6 kg CO2/day).

This study quantified effluents generated during processing in three industry types, estimated the energy potential from the quantified effluents in form of biogas generation, and determined the economic viability of the biogas recovered. Data were procured from relevant scientific publications to quantify the effluents generated from the production processes in the industry types examined using industrial process calculations. The effluent data generated was used on the 2-module biogas energy recovery model to estimate the bioenergy recovery potential within it. Economic and financial analysis was based on cash flow comparison of all costs and benefits resulting from its activities. The effluents generated average daily biogas of 2559 Nm³/gVS, having a daily potential combined heat and power of 0.52 GWh and 0.11 GWh respectively. The Life Cycle Analysis and cost-benefit analysis show the quantity of avoided emissions from using the effluents to generate heat and power for processes, and also the profitability of the approach. Conclusively, the study shows the use of biomass effluents to generate biogas for CHP is a viable one based on the technologies of a reciprocating engine, gas turbine, microturbine, and fuel cell. However, it is recommended that the theoretical estimation be validated using a field-scale project.

In recent years, unquestionable warnings like the negative impacts of CO2 emissions, the necessity of utilizing sustainable energy sources, and the rising demand for municipal electrification have been issued. In this study, by incorporating two significant assumptions, such as electricity production in close proximity to the business location and only renewable energy resource usage, a modest off-grid hybrid energy system is designed. To construct the system, a number of elements such as wind generators (WG), photovoltaic arrays (PV), battery banks, and bi-directional converters are taken into account. Moreover, a real case in Malmö, Sweden, is considered. To optimize the system, a bi-objective problem is developed, and it is solved by proposing a particle swarm optimization (PSO) approach to provide the load requirements (with a maximum allowance of 0.1% unmet) for a nearby supermarket (approximately 1000 m2). Moreover, to verify the obtained results, the developed system is simulated using HOMER Pro software, and the results are compared and discussed. The contribution of this study is to provide off-grid or local clients around the world with a dependable and affordable option by minimizing both the baseline cost of energy and the net current expenditure in the desired system. The best-obtained results by the proposed PSO offered 160 PVs, 5 WGs, and 350 batteries, respectively, while the best solution found by the simulation method was using 384 PVs, 5 WGs, and 189 batteries for the considered off-grid system.

Intended for the high voltage gain and wide-range operation of DC/DC converters for photovoltaic energy storage systems, a topology for four-phase interleaved DC/DC converters for photovoltaic power generation is proposed. This topology increases output voltage for output in series, and reduces the input current ripple by paralleling the input. Compared with traditional boost converter topology, the proposed topology reduces the output current and output voltage ripple, reduces the stress of the switching device, and reduces the withstanding voltage of the output capacitor under the premise of ensuring the boost ratio. Experimental results show that the maximum efficiency of the converter reaches 95.37%. Compared with traditional boost converters, the proposed converter offers obvious advantages in efficiency under the conditions that the output voltage and load are variable.

This article aims to investigate gaps in the law and policies on e-waste management in communi-ties of Thailand and suggests a guideline for improving, developing, and designing legal measures and state policies for more effective enforcement of the law on e-waste management in communities. The findings reveal that the currently applicable law of Thailand lacks effective approaches and rules for e-waste management. Also, there is not any implementation of key envi-ronmental principles for e-waste management in communities, such as the Polluter Pays Principle (PPP) that requires manufacturing companies to take part in being responsible for disposal ex-penses or the Public Participation principle that requires users, manufacturers, distributors, and government agencies to take parts in disposing e-waste. As a result, problems of e-waste in com-munities of Thailand have been continuously increasing. According to such problems, the authors suggest that legal measures on e-waste management in communities should be specifically de-signed by implementing key environmental principles as a basis in determining formats and guidelines of e-waste management, especially participation of all sectors that can help in solving and reducing e-waste in communities that is harmful to health, sanitation, and environment.

We conduct a thematic analysis of a U.S. adult sample’s self-reported motives and perception of environmental activists’ motives to engage in pro-environmental behavior via a qualitative online survey. We identified themes using a two-stage coding procedure, whereby the research team first helped to code all content into one or more of 17 inductive content categories, then the lead investigator examined themes in each of the categories and created 5 themes based on both inductive and theoretical (e.g., moral foundations theory) considerations: a) harm and care, b) purity, c) waste and efficiency, d) spreading awareness, and e) self-interest (mostly non-financial). Endorsement of themes were qualitatively similar across individuals’ own self-described motives and perceptions of environmental activists’ motives.

Economic theory states that incineration and landfill taxation can effectively diminish the environmental impacts of pollution and resource use by reducing their associated pollutants while stimulating the reuse and recycling of materials, and therefore, fostering a circular economy. The aim of this research is to assess the economic and environmental effects of these taxes in Spain under different scenarios with a detailed dynamic computable general equilibrium (CGE) model, as there are no studies analyzing this in detail. We focus on the economic impact on GDP and sectorial production and the environmental impact on different categories: global warming potential, marine eutrophication potential, photochemical ozone formation potential, particulate matter, human toxicity (cancer and noncancer), ecotoxicity, and depletion of fossil resources. We find in all scenarios that these taxes have a limited economic impact while reducing all of the environmental impact categories analyzed. The study reinforces the theory that policy makers need to impose taxes on landfill and incineration to reinforce the circularity of the economy and reduce environmental burdens, but also demonstrates that they can improve their design without additional costs.

This study focused on the assessment of folk media aimed at Environmental Communication (EC) in the Guna Community and suggested the dominant Guna Community folk media for environmental communication and preservation to conserve Mount Guna. Guna Mount is the home of different biodiversity and the tower of water, but it is becoming degraded. Folk media are operative in environmental communication and preservation. They have the power to transmitted environmental messages that incorporate cultural values, beliefs, and attitudes with societal needs. Folk media are locally oriented, easily accessible, flexible, portable, inclusive, and relatively inexpensive. A qualitative research approach was employed for this research. Ethnographic research design, snowball, and purposive sampling techniques were used to select the respondents. The researchers were gathered the data through in-depth interviews, focus group discussion, and observation. For this survey, 16 FGDs, 45 individual in-depth interviews, and participant observation were employed. Guna community has unique and indigenous folk media that use as a source of entertainment, information, and education. Their folk music, songs, dances, campfire storytelling, traditional motifs, fairs, and festivals, and folk poems are the dominants. Using folk media for operative ecology preservation is vital in the form of EC that inspires and develops positive behavior in the community by educating about environmentalism in the method of facilitating environmental issues incorporating the latest message. Finally, we recommended some folk media for developmental activities that use inform of advocacy regarding recommended reasons

Infectious disease like COVID-19 will have a great impact on human society. An effective prevention and control measure is to quickly isolate the source and reduce the population’s exposure to the infection. Therefore, it is very important to quickly trace and identify the virus carrier and its close contacts in order to effectively suppressing transmission. This article provides a method, system and storage medium for locating the source of infection based on big data. We adopt the method of combining Bluetooth and GPS positioning to track the action trajectory of each individual. The method stores the close contact and location information locally and update on the cloud platform for an appropriate period of time. The method and system can provide personal risk levels and regional risk levels through related algorithms. When entering a high-risk area or if the personal risk level within the Bluetooth interconnection range is greater than the set threshold, an alarm function is provided. We can also generate reports on the spread of the epidemic over a period of time. As a result, the system can quickly locate the source of infection and close contacts, providing a reference for quick and highly efficient epidemic prevention and control.

The utilization of fuel cells (FC) in automotive technology has experienced significant growth in recent years. Fuel cell hybrid electric vehicles (FCHEVs) are powered by a combination of fuel cells, batteries, or/and ultracapacitors (UCs). By integrating power converters with these power sources, the FCHEV system can overcome the limitations of using them separately. The performance of an FCHEV is influenced by the efficiency of the power electronics converter controller, as well as the technical efficiency of the power sources. FCHEVs need intricate energy management systems (EMSs) to function effectively. Poor EMS can lead to low efficiency and accelerated fuel cell and battery degradation. The literature discussed various types of EMSs, such as equivalent consumption minimization strategy, classical PI controller, fuzzy logic controller, and Mutative Fuzzy Logic Controller (MFLC). However, comparing different EMSs can be challenging due to the varying vehicle and system parameters, which might lead to false claims being made regarding system performance. This research aims to categorize and discuss the various topologies of FCHEVs, highlighting their pros and cons, and comparing several EMSs based on performance metrics such as State of Charge (SOC) and FC deterioration.

The purpose of this paper is to summarize and share the field experiment results of KEPCO's project consortium to create a TSO-DSO-DERA interaction scheme. The field experiment was conducted based on the prequalification algorithm proposed in the previous research from the same consortium and was designed to verify the validity of the algorithm under realistic grid conditions. In addition, during the course of the field experiment, it was found that points that were missed or not given much importance in the existing prequalification algorithm could affect the completeness of the overall system, and then practical improvements were made to improve it. The demonstration results confirm that the proposed algorithm is effective in real-world grid environments and can help DSOs ensure the reliability of the distribution system while supporting DERA's participation in the wholesale market using the proposed prequalification scheme.

This paper aims at presenting an energy management strategy (EMS) based upon optimal control theory for a battery-supercapacitor hybrid power system. The hybrid power system consists of a Lithium-ion battery and a supercapacitor with associated bidirectional DC/DC converters. The proposed EMS aims at computing adaptive gains using salp swarm algorithm and load following control technique to assign the power reference for both the supercapacitor and the battery while achieving optimal performance and stable voltage. The DC-DC converter model is derived utilizing the first-principles method and compute the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power ele-ments’ life expectancies and supplies the power system with the required power

The goal of farmers operating in a market economy is to maximise profit. In the face of the changing political situation, the main social interest, besides food security, should be energy security. This article aims to indicate the direction of agricultural policy development so that it guarantees both the economic security of producers—farmers—and Europe’s energy security. The work uses data obtained from the agri benchmark Cash Crop database. DEA method and stepwise multiple regression were used. The research showed that plants are already grown in Europe which will ensure high energy efficiency of production without compromising farm financial results (including oats, peas and winter rye) and that improving the involvement of certain inputs results in improved production efficiency (among others, by expenditure on agricultural advisory services). The significance of the presented research results from the fact that the recent COVID pandemic and escalation of the military conflict in Ukraine have led to a renewed interest in the concept of EU energy security, i.e. generation of generating the greatest possible amount of energy within the EU, to be used both for food and non-food purposes.

Despite the wide variety of variables commonly applied to measure different aspects of rehabilitation, the assessment and subsequent definition of indicators of environmental rehabilitation status are not simple tasks. The main challenges are comparing rehabilitated sites with target ecosystems as well as integrating individual environmental and eventually collinear variables into a single tractable measure of the state of a system before effective indicators that track rehabilitation may be modeled. For that, a consensus is lacking regarding which and how many variables need to be surveyed. Our approach considered ecological processes, vegetation structure, and community diversity from nonrehabilitated, rehabilitating and reference sites. We applied this approach to a curated set of 32 environmental variables retrieved from nonrevegetated, rehabilitating and reference sites associated with iron ore mines from the Urucum Massif, Mato Grosso do Sul, Brazil. By integrating variables from a single attribute or the entire set of variables into a single estimation of rehabilitation status, the proposed multivariate approach is straightforward and able to adequately address collinearity among variables. The proposed approach allows for the identification of biases towards single variables, surveys or analyses, which is necessary to rank environmental variables regarding their importance to the assessment. Furthermore, we show that bootstrapping permitted the detection of the minimum number of environmental variables necessary to achieve reliable estimations of the rehabilitation status. Finally, we show that the proposed variable integration enables the definition of environmental indicators for more comprehensive monitoring of mineland rehabilitation. Thus, the proposed multivariate ordination represents a powerful tool to outline the benefits of rehabilitating sites for the maintenance of biodiversity and ecosystem functions and services provided that sufficient environmental variables related to ecological processes, diversity and vegetation structure are gathered from nonrehabilitated, rehabilitating and reference study sites. By identifying deviations from predicted rehabilitation trajectories and providing assessments for environmental agencies, this proposed multivariate ordination increases the effectiveness of (mineland) rehabilitation.

The present article is dealing with the state of question about building-energy monitoring systems used for data collection to estimate the Heat Lost Coefficient (HLC) with existing methods and so determinate buildings’ Envelope Energy Performance (EEP). In addition, the data requirements of HLC estimation methods are related with commonly used methods for fault detection, calibration and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests since 1978, a qualitative and quantitative analysis of Monitoring and Controlling System (MCS) specifications has been carried out. Although most actual Buildings Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply the HLC estimation methods.

Abstract: Field studies with large-stemmed plants Artemisia dubia (wormwood) have been carried out at Vėžaičiai Branch LAMMC since 2018. According to three years of experimental results, annual dry matter (DM) yield varied from 7.94 to 10.14 t ha-1. Growing conditions, nitrogen ap-plication level and harvesting time had significant impacts on Artemisia dubia productivity. This article presents the results of research on preparation and use of Artemisia dubia biomass for en-ergy conversion and evaluation of technological-technical and environmental parameters of these plants utilization for solid biofuel. For experiments were used 6 variants of Artemisia dubia samples, which were grown in 2021: plants were cut three times and two fertilization options were used: (1) no fertilization and (2) fertilization with 180 kg ha-1 of nitrogen fertilizer. These harvested plants were chopped, milled and were pressed into the pellets. The physi-cal-mechanical characteristics (mоisture content, density and strength) of Artemisia dubia pellets were investigated. During this study, it was found that the density in dry mass (DM) of pellets ranged from 1119.86 to 1192.44 kg m-3. The pellet moisture content ranged from 8.80 to 10.49%. After testing of pellet strength, it was found that the pellets which were made from plant bio-mass PK-1-1, were the most resistant to compression, they withstood 560.36 N of pressure. Dry fuel lower heating value (LHV) of pellets was sufficiently high and was very close to pine saw-dust pellets, it varied from 17.46±0.25 MJ kg-1 to 18.14±0.28 MJ kg-1. The ash content of burned pellets ranged from 3.62±0.02% to 6.47±0.09%. Emissions of harmful pollutants – CO2, CO, NOx and unburnt hydrocarbons (CxHy) did not exceed the maximum permissible levels. Summariz-ing the results of investigated properties, cоmbustion and emissiоns of Artemisia dubia pellets, it can be concluded that this biofuel can be used for production of pressed biofuel and it is charac-terized by sufficient high quality, efficient combustion and permissible emissions to the envi-ronment.

Societies around the world face serious energy problems related to the consumption of fossil fuels and the emission of dangerous radiation. To solve these problems, a new superconductor exhibiting a critical temperature higher than room temperature has been pursued but not achieved. This paper proposes a new energy generation system based on a circuit approach. Secondary to this process, a new type of superconductivity without refrigeration is demonstrated. In our previous paper [1], this system was proposed, but it did not describe the underlying theory in detail and did not mention an actual method to generate energy from the system. The present paper describes the theory of the existence of divergent current density and new superconductivity with no refrigeration. Moreover, the present paper proposes a method for extracting energy from the system by employing a voltage-controlled current source (i.e., a voltage–current converting method).The principle of the system is based on a circuit of two loops and independent current sources. First, the two electric loops are prepared, each with 4 diodes, where the diodes are oriented in the same direction within each loop, but their direction is opposite from loop to loop; four independent current sources connect the loops. In this circuit system, current is added iteratively as it flows along the loop according to Kirchhoff’s circuit law. As a result, a large current and electric potential are present along the loop. To confirm that this system works properly, it is necessary to demonstrate the presence of divergent currents in the transient state, and to do this, the present paper employs the Dirac equation and Lorentz conservation. Electric circuit software is employed to demonstrate that the presented method generates energy actually from our system.Our results confirm the presence of divergent current at a connected point of an independent current source in the transient state. Moreover, in the steady state, the theory demonstrates the Meissner effect (i.e., a London equation) and a new type of macroscopic wave function and condensation. For an initial small input current of 0.1 μA, the simulation reveals a large generating current of 7 kA and electric power of 10¹¹ W, which is much larger than unit of power from an average thermal power station; moreover, the system presents with superconducting electrical transport conditions.The present study is significant because it demonstrates theoretically the existence of divergent current density and a new type of superconductivity requiring no refrigeration. Secondly, the simulations show the generation of a large energy density that can be obtained in a small laboratory room with minimal cost.

Parental stresses are normal responses to raising children. They are affected by stresses parents and children accumulate and bring to their interrelations. Background factors like economic difficulties or the relations between the parents may affect parental stresses as well as demographic and environmental factors like noise and access to urban parks. Most studies on parental stress are based on a verified psychological questionnaire. We suggest using frequency domain heart rate variability index (HRV) to measure parental stress enabling, by thus, the measurement of physiological aspects of stress and risk to health. Parental stress is measured as the difference between HRV accumulated at home while staying with the children and without the husband and HRV measured in the neighborhood while staying without the children and the husband. We use the index to compare differences among Muslim and Jewish mothers in exposure to maternal stress at their homes and to expose the factors that predict differences in maternal stress. We found that Muslim mothers suffer from home-related maternal stress while Jewish mother do not. Number of children and ethnically related environmental aspects predict differences in maternal stress between Muslim and Jewish mothers. Muslims' lower access to parks stems from lack of home garden and parks in their neighborhoods in the Arab towns but mainly by restrictions on Muslim women's' freedom of movement to parks. Despite differences in levels of noise at home and in the status of the mother in the household, these factors did not predict differences in parental stress. Instead, the study highlights the crucial role of greenery and freedom of movement to parks in moderating home-related maternal stress.

The energy crisis is currently a major topic in scientific and managerial discussions in the building and construction industry. While employing low-cost strategies for reducing energy usage is beneficial for principals and decision-makers, the primary purpose of this study is to recommend the use of phase change materials (PCM) to improve cooling and heating load management in buildings. In order to accomplish this, the study applies design-builder simulations to a developing country case study. The results indicate that integrating PCM in buildings can reduce energy usage by around 6 percent. Although this value may be lower than other techniques, it is nevertheless important for reaching green building goals in both developed and developing nations. The case study, which takes place in a four-season region, demonstrates the significant potential of the PCM system for both cooling and heating energy management. In addition, the reciprocal performance improvement of PCMs is a remarkable characteristic, especially when contrasted to some conventional systems that focus on a single energy management objective in buildings. Lastly, it should be underlined that the suggested platform is consistent with Sustainable Development Goal 7 (Affordable and Clean Energy Targets).

Two-wheeler vehicles are the most significant mode of transportation for Kenyans in both rural and urban regions thereby contributing to local air pollution, and greenhouse gas emissions (GHG). The transition to electric two-wheeler vehicles can make a significant contribution to reducing GHG and improving the socio-economic lives of people living in rural Kenya. Re-newable energy systems can considerably contribute to the charging of electric two-wheeled vehicles, thus leading to the reduction of carbon emissions and the expansion of renewable energy penetration in rural Kenya. Therefore, this paper focuses on integrating and modelling electric two-wheeled vehicles (e-bikes) into an off-grid photovoltaic Water-Energy Hub located in the Lake Victoria Region of Western Kenya using the Conventional and Renewable Energy Opti-mization (CARNOT) Toolbox in MATLAB / Simulink. Electricity demand data obtained from the Water-Energy Hub was investigated and analysed. Potential solar energy surplus was identified and electric two-wheeler vehicles were integrated based on the surplus. A field measurement investigation on the energy consumption of the electric two-wheeler vehicles based on the rider’s driving behaviour was also carried. The annual electricity demand of 27,267 kWh, photovoltaic (PV) electricity production of 37,785 kWh with an electricity deficit of 370 kWh were obtained from the simulation results. To reduce the electricity deficit, a load optimisation algorithm was de-veloped to optimally integrate the electric 2-wheeler vehicle into the Water-Energy Hub. It was found that using the load optimisation algorithm, the annual electricity deficit was reduced to 1 kWh and the annual electricity demand was increased by 11% (30,767 kWh) which is enough to charge 4 additional electric two-wheeler batteries daily.

A new model predictive control (MPC) algorithm is used to select optimal air conditioning setpoints for a commercial office building, considering variable electricity prices, weather, occupancy and lighting. This algorithm, Cost-Comfort Particle Swarm Optimization (CCPSO), is the first to combine a realistic, smooth representation of occupants’ willingness to pay for thermal comfort with a bottom-up, non-linear model of the building and air conditioning system under control. We find that using a quadratic preference function for temperature can yield solutions that are both more comfortable and lower-cost than previous work that used a ``brick wall'' preference function with no preference for further cooling within an allowed temperature band and infinite aversion to going outside the allowed band. Using historical pricing data for a summer month in Chicago, CCPSO provided a 3\% reduction in costs vs. a ``brick-wall'' MPC approach with similar comfort and 13\% reduction in costs vs. a standard night setback strategy. CCPSO also reduced peak-hours demand by 3\% vs. the ``brick-wall'' strategy and 15\% vs. standard night-setback. At the same time, the CCPSO strategy increased off-peak energy consumption by 15\% vs. the ``brick-wall'' strategy. This may be valuable for power systems integrating large amounts of renewable power, which can otherwise become uneconomic due to saturation of demand during off-peak hours.

Ecological footprint calculators are digital tools that help individuals calculate their environmental or climate impact, with the aim of stimulating pro-environmental behaviour change. These footprint calculators typically take an information-provision approach, but this strategy assumes that increased levels of knowledge result in increased levels of pro-environmental behaviour (i.e., a reduced footprint). This is not a given – existing literature on the relationship between environmental knowledge and pro-environmental behaviour is inconclusive, and this relationship may be different from that of environmental knowledge and ecological footprint. As such, we investigated the relationship between environmental knowledge and ecological footprint as estimated by a footprint calculator. 448 Dutch participants completed an online survey, including an ecological footprint calculator. We found no evidence for a relationship between environmental knowledge and ecological footprint calculator outcome. Rather, an exploratory analysis of our data showed that environmental values were more important predictors of ecological footprint. The finding that increased levels of knowledge are not related to a reduced ecological footprint suggests that calculators would do well to move beyond information provision, and employ additional behaviour change strategies. Based on our exploratory analysis, we provide several concrete examples of potential strategies.

The efficiencies of conventional triple organic Rankine cycle (TORC) configurations are restricted by the low critical temperatures of common working fluids (＜320 °C). This paper proposes a high-temperature TORC system. A near-azeotropic mixture biphenyl/diphenyl oxide (BDO), which has stellar track record in the high-temperature ORC applications, is innovatively adopted as the top and middle ORC fluid simultaneously. The top cycle evaporation temperature is up to 400 °C in view of BDO’s high stability. Five conventional organic fluids are chosen for the bottom ORC. Fundamentals of the TORC system are illustrated, and mathematical models are built. Thermo-economic performance is investigated. The results hint that the optimal thermodynamic property is achieved on the use of benzene as the bottom fluid. The maximum thermal and exergy efficiencies are respectively 40.86% and 74.14%. The largest irreversible loss occurs inside the heat exchanger coupling the middle and bottom ORCs, accounting for above 30% of the total entropy generation. The levelized energy cost (LEC) is 0.0284 $/kWh. Given the same heat source condition, the TORC system can boost efficiency by 1.02% and drive down LEC by 0.0024 $/kWh compared with a BDO mixture-based cascade ORC.

In a power plant that uses seawater as a coolant, a debris filter is required to remove foreign substances from the seawater, and differential pressure leads to a decrease in the coolant flow rate, leading to a decrease in power generation efficiency. In this study, analysis was performed under different initial flow velocity conditions of 1.5m/s, 2.0m/s, and 2.5m/s for a debris filter used in a power plant to understand flow characteristics in CTCS. The flow and differential pressure characteristics of a CTCS with an installed debris filter were considered in a comparative analysis of velocity, pressure, and turbulent kinetic energy distribution. The results confirmed that a vortex was generated in the pipe with the debris filter, apparently due to the collision of the flow with the bracket of the debris filter. As the flow rate increased, the range of the vortex increased, causing a loss in flow.

This paper describes research on a unique propulsion system design for a low-speed Biomimetic Unmanned Underwater Vehicle (BUUV). It is biomimetic in the sense that it mimics the movement of aquatic organisms. The undulating propulsion system has numerous advantages over the rotary impeller and is becoming more popular in underwater robotics. The analysis of an artificial seal’s propulsion system with two tail fins is described here. The contrast between the previous undulating propulsion system and the new one is detailed using mathematical analysis and experimental data. The experimental comparison was carried out on a laboratory test stand equipped with specialist sensor equipment to determine the energy efficiency of various types of propulsion systems. Due to a patent procedure, the innovative propulsion system presented in this work has never been published previously. The fins have extra joints, which is the subject of patent claims. The extra joint is intended to improve energy efficiency and reduce fatigue wear on the fins.

Based on research data from the renovation of old residential areas in Chengdu, China, this study provides empirical evidence regarding the causal relationship between urban renewal and the transformation of residents' pro-environmental behaviors. The research findings demonstrate a significant enhancement in residents' engagement in pro-environmental behaviors due to the renovation of old residential areas. Robustness tests based on replacement samples and two-stage difference-in-difference models also confirm the reliability of the conclusions. The preliminary mechanism test indicates that the mechanism of the impact of renovation of old residential areas on the transformation of residents' pro-environmental behaviors can be attributed to two main factors. Firstly, the improvement of environmental infrastructure provides residents with better conditions for participating in pro-environmental activities. Secondly, there is an elevation in residents' environmental protection awareness, prompting a more voluntary engagement in pro-environmental behavior. This study suggests that decision-makers should fully recognize that urban renewal activities nationwide are not only a process of improving urban hardware and functionality, but also a realistic and vivid "environmental education" course for the whole nation. Taking urban renewal as an opportunity to enhance citizens' awareness of environmental protection will effectively promote the transformation of pro-environmental behaviors among residents.

This study investigates the impact of General Government Final Consumption Expenditure (GC) on GDP growth in Saudi Arabia during major economic crises from 1990 to 2022, focusing on periods marked by fluctuations in oil and non-oil revenues. By integrating these revenue streams, the research provides a more comprehensive analysis of fiscal policy effectiveness during economic downturns. Using an Autoregressive Distributed Lag (ARDL) model, the study reveals that Government Consumption significantly stabilizes and stimulates the Saudi economy amidst revenue volatility. Key findings highlight the dual role of Government Consumption (GC) as both a buffer against immediate economic shocks and a stimulus for economic recovery. The study contributes to the discourse on fiscal policy in oil-dependent economies by demonstrating the critical role of diversified revenue strategies in enhancing economic resilience. Recommendations are offered for policymakers to optimize fiscal strategies, ensuring robust economic recovery and long-term stability in volatile markets. This research underscores the necessity for Saudi Arabia to refine its fiscal policies towards greater economic diversification and stability.

Keywords: Innovation ecosystems, Economic sustainability, Hydrocarbon-based economies, Economic diversification, Qualitative approach

The Nordic countries are practically always well positioned in the main international economic, social and sustainability indices and recommending the scientific literature that the variables that these indices intend to measure translate into sustainable economic growth, with this unprecedented empirical study we intend to verify through the ARDL methodology for space temporal 2004 -2018 if the maintenance of high scores in these indexes translates into effective economic growth. The ARDL methodology has the advantage of giving us short- and long-term coefficients. Using four of the main international indices, we conclude that for Nordic countries for economic growth, economic freedom is of no significance and business-friendly regulation is the most important variable. A fundamental discovery in our study (in which Granger's Causality complements the ARDL methodology) is that these countries have been able to adapt perfectly to the globalization process and that entrepreneurship has worked as an important contribution to the continued economic and social success of these countries, allowing them to continue to enjoy their “Nordic Welfare States” in these uncertain and troubled times. These variables have contributed to its economic and social sustainability.

Many buildings built before the energy performance regulations are in a situation of thermal discomfort and energy inefficiency. The creation of intelligent environments advances towards new opportunities, based on real-time monitoring and on the development of sensors and technologies. Furthermore, the standards for building automation and electronic systems enable interoperability and interconnection between control devices and systems. The application of soft computing has significantly improved the energy efficiency, however, requires prior assessment to design the automation functions. Temperature, humidity, air quality, occupancy and energy consumption are the most common measured parameters, but the relationship with other operational variables such as occupancy or some building states remains as a research challenge. This article presents a methodology to develop the automatization of an existing large public building. The methodology consists of three stages: 1. Assessment and diagnosis to set appropriate actions using EN ISO 52120-1. 2. EN 50090 for open communication networks, and EN ISO 52120-1 to assign the technical building management. 3. System control deploying of low-cost and low-consumption input and output devices. It has been proved that it is possible to effectively automate an obsolete building with a low cost, open source system that can be easily applied in other buildings.

The development of technology that combines supercapacitors and lithium-ion batteries by externally connecting them in parallel is ongoing. This study examines the correlation between the volume ratio and electrical characteristics of a cell made by internally connecting a battery capacitor with Li4Ti5O12 as the anode active material and a supercapacitor in parallel. It was found that increasing the volume occupied by the battery capacitor in the cell led to increased cell energy and resistance, resulting in decreased output characteristics. Conversely, increasing the volume occupied by the supercapacitor in the cell led to a decrease in the IR drop during discharge and cell temperature when evaluating cycle characteristics with a current of 20C. The study also examined the behavior of the current distributed during the charging and discharging process based on the volume ratio of the supercapacitor and the battery capacitor. Analyzing the correlation between the volume ratio and electrical characteristics of supercapacitors and battery capacitors could potentially lead to the development of a new type of energy storage device.

The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy system models. An increasing complexity constitutes a high computational load that can limit the scale of the energy system model. Especially in microgrid optimisation problems with multiple buildings and energy systems with a number of rival supply, distribution and storage technologies, methods are sought to reduce this complexity. In this paper, we present a new 2-Level Approach to MILP energy system models that determine the system design through a combination of continuous and discrete decisions. On the first level, data reduction methods are used to determine the discrete design decisions in a simplified solution space. Those decisions are then fixed, and on the second level the full dataset is used to extract the exact scaling of the chosen technologies. The performance of the new 2-Level Approach is evaluated for a case study of an urban energy system with six buildings and an island system based on a high share of renewable energy technologies. The results of the studies show a high accuracy with respect to the total annual costs, chosen system structure, installed capacities and peak load with the 2-Level Approach compared to the results of a single level optimization. The computational load is thereby reduced by more than one order of magnitude, while a significantly higher accuracy is reached in comparison to the common time series aggregation approach.

The study presents an efficient computational investigation on the behaviour of the direct-drive system integrated into the offshore 5MW NREL wind turbine model under demanding aerodynamic loading conditions with the aim of optimising and developing more sustainable key structural components. The research was based on computational simulation packages to verify the use of real-world wind data, the loading conditions on the blade structures through aero-elastic simulation studies, as well as analyse the behaviour of the drive system. Through the application of validated aerodynamic loading conditions, resulting normal forces on the blades structure were obtained and applied to a dedicated simplified model that was also previously validated, to estimate the transferred loads into the powertrain. The adopted methodology allowed for the identification of shaft misalignment induced air-gap eccentricity. The impact of shaft deflections on resulting magnetomotive force was considered by making use of the Maxwell stress distribution expression. By taking into account the resulting loading cases on the generator structure, as well as the inherent typical loads generated by the electrical machine, a procedure including structural parametric and topology optimisation was developed and performed, achieving a rotor mass reduction between 8.5 and 9.6% if compared with the original model.

The growing integration of renewable energy sources (RES) into the power system causes congestion to occur more frequently. In order to reduce congestion in the short term and to make the utilization of the power system more efficient in the long term, power flow control (PFC) in the transmission system has been proposed. However, exemplary studies show that congestion will increase also in the distribution system if the transmission system is expanded. For this reason, the potential of PFC to reduce congestion in a model of a real 110 kV distribution system is investigated. Several Unified Power Flow Controller (UPFC) devices are optimized in terms of their number and placement in the power system, their size, control parameters, and costs, by using a Parallel Tempering approach as well as a greedy algorithm. Two optimization variants are considered, one reducing the number of degrees of freedom by integrating system knowledge while the other is not. We find that near a critical grid state and disregarding costs, PFC can reduce congestion significantly (99.13 %). When costs of the UPFCs are taken into account, PFC can reduce congestion by 73.2 %. A basic economic analysis of the costs reveals that the usage of UPFCs is profitable. Furthermore, it is found that the reduction of the solution space of the optimization problem leads to better results faster and that, contrary to expectations, the optimization problem is simple to solve. The developed methods allow not only for the determination of the optimal use of UPFCs to minimize congestion, but also to estimate their profitability.

In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policy-makers and renewable energy experts working on integrating and optimizing renewable energy solutions. While using a case study representative model for Sub-Saharan Africa (SSA) to demonstrate the challenges and opportunities present in introducing optimization methods to bridge power supply deficits and the scalability of the model to other regions, this study presents an agile multi-criteria decision tool that pivots on four key development phases, advancing upon established methodologies and pioneering refined computational techniques, to select optimal configurations from a set of Policy Decision Making Metrics (PDM-DPS). Central to this investigation lies a rigorous comparative analysis of variants of three advanced algorithmic approaches: Swarm-Based Multi-objective Particle Swarm Optimization (MOPSO), Decomposition-Based Multi-objective Evolutionary Algorithm (MOEA/D), and Evolutionary-Based Strength Pareto Evolutionary Algorithm (SPEA2). These are applied to a grid-connected hybrid system, evaluated through a comprehensive 8760-hour simulation over a 20-year planning horizon. The evaluation is further enhanced by a set of refined Algorithm Performance Evaluation Metrics (AL-PEM) tailored to the specific constraints. The findings not only underscore the robustness and consistency of the SPEA2 variant over 15 runs of 200 generations each, which ranks first on the AL-PEM scale but also validate the strategic merit of combining multiple technologies and empowering policymakers with a versatile toolkit for informed decision-making.

We currently face several, interlinked environmental crises, including climate change, habitat destruction and biodiversity loss. However, many governments seem unwilling to take strong and immediate action to address these threats, preferring to promote neoliberal approaches to allow consumers and the general public to make environmentally friendly choices. This is despite neoliberal approaches being much less likely to be successful than government leadership, taxation, subsidies, and legislation in addressing environmental issues. In this study, we examine public perception of environmental threats and solutions to these threats, in a survey, mainly completed in the UK. Climate change is seen as the biggest issue, likely due to recent activist campaigns and subsequent media attention on the issue. Neoliberal attitudes, such as green consumer choices to environmental concerns, do still dominate in a series of possible presented solutions, and score more highly than lifestyle changes such as changing diet. However, when questioned specifically about plastic pollution, government intervention to ban all unnecessary plastic scored very strongly, indicating a shift from a consumer driven response. Furthermore, most participants think they are at best only partly ‘doing their bit’ to protect the environment. The results demonstrate that the public are aware that not enough is happening to protect the environment and provide evidence that there is willingness for stronger government intervention to address environmental issues, although there is potential resistance to major lifestyle changes.

The purpose of this article is to analyze, in a three-stage research, the relationships between environmental expenses, the improvements achieved in 5 environmental variables analyzed and efficiency, from an economic and operational perspective. The stages of this research are analyzing the sustainability reports to determine the level of information, analyzing the economic and operational efficiency, and analyzing the alignment with the environmental priorities of the Eco Ports-ESPO (European Sea Ports Organization). The results reveal that (1) the type of traffic does not condition environmental actions; (2) environmental performance (improvements) depends on environmental expenditures; (3) environmental spending and efficiency in port operations are correlated; and (4) environmental spending and port economic efficiency are correlated.

Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.

The aim of this short communication is to find out the legal set up that complies with the environmental management in the textile sector of Bangladesh. This sector is the one of the biggest contributor to the economy of the nation. This sector contributes 81% to the total export earnings involving an immense number of stakeholders to its production processes. It is also true that this sector is largely responsible for the overall environmental pollution through its effluent discharge. The findings suggest that there are both international and national legal guidelines exist for environmental management in the said sector. In order to improve the environmental standards rehearsing lawful instruments is compulsory for the said industries.

The pollution of the bays in Abidjan is a major concern for the Ivorian policy makers. In fact, the pollution of the bays induce high costs to the society while impacting population health dramatically. As a result, pollution reduction management of production activities has been undertaken in the Cocody Bay area. To our knowledge, no study has yet proposed a model to evaluate the cost-effectiveness of these pollution management strategies. A cost-effectiveness model, based on Monte Carlo simulation, was developed to assess the economic and environmental impacts of various scenarios characterized by a set of production practices, both in the short term and in the long term. The authors discuss the steps and input parameters of the model presented. The proposed model may serve as the basis for identifying an optimal production scenario defined as the scenario with the best incremental cost-effectiveness ratio considering a willingness to pay (WTP) threshold. The WTP, to be estimated based on the gross domestic product of Côte d’Ivoire, represents the opportunity costs associated with selecting the optimal scenario. The current framework can also be applied to other settings facing similar challenge.

Microgrids (MGs) have evolved as critical components of modern energy distribution networks, providing increased dependability, efficiency, and sustainability. Effective control strategies are essential for optimising MG operation and maintaining stability in the face of changing environmental and load conditions. Traditional rule-based control systems are extensively used due to their interpretability and simplicity. However, these strategies frequently lack the flexibility for complex and changing system dynamics. This paper provides a novel method called hybrid intelligent control for adaptive MG that integrates basic rule-based-control and deep learning techniques, including gated recurrent units (GRU), basic recurrent neural network (RNN) and long short-term memory (LSTM). The main target of this hybrid approach is to improve MG management performance by combining the strengths of basic rule-based systems and deep learning techniques. These deep learning techniques readily enhance and adapt control decisions based on historical data and domain-specific rules, leading to increasing system efficiency, stability, and resilience in adaptive MG. Our results show that the proposed method optimises MG operation, especially under demanding conditions such as variable renewable energy supply and unanticipated load fluctuations. This study investigates special RNN architectures and hyper-parameter optimization techniques with the aim of predicting power consumption and generation within the adaptive MG system. Our promising results show the highest-performing models indicating high accuracy and efficiency in power prediction. The finest-performing model accomplishes an R2 value close to 1, representing a strong correlation between predicted and actual power values.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

In this paper, modelling, simulation and verification of multi-agent manufacturing system with application of bio-inspired techniques are addressed. To this end, the new solution of abstract architecture for control and coordination decentralized systems - CODESA is suggested. Centralized architecture suffers from various problems, such as rigidity, scalability, low fault-tolerance or very limited flexibility, agility, energy efficiency and productivity. Prime is concrete application of CODESA in manufacturing domain. The undesirable characteristics of emergent behaviour are the problem to achieve optimization and impossibility to predict future states of the system. CODESA-Prime has been tested by simulations for automatic guided vehicle (AGV) systems guided by magnetic tape in Ella Software Platform.

For water-stressed regions like Iran improving the effectiveness and productivity of agricultural water-use is of utmost importance due to climate change and unsustainable demands. Therefore, a hydro-economic model has been developed here for the Zarrine River Basin with the central concept of that demands are value-sensitive functions, where quantities of water-uses at different locations and times have a changeable economic benefits. To do this, the potential crop yields and the surface and groundwater resources, especially Boukan Dam inflow are simulated using the hydrologic model, SWAT, based on predicted climatic scenarios i.e. quantile mapping-downscaled projections. Then, to allocate the agricultural water based on the agro- economic crop water productivity (AEWP) of crops, a basin-wide water management tool, MODSIM, is customized. Next, a simulation- optimization model has been developed using a coupled CSPSO-MODSIM, to optimize the total AEWP, considering climatic impact and crop pattern scenarios, for 2020-2038, 2050-2068 and 2080-2098 periods. Finally, the optimum crop pattern and crop water irrigation depths are presented for different RCPs and periods. The results indicated that this approach will improve considerably the AEWPs and decrease the agricultural water-use up to 40%. Thus, this integrated model is able to support water authorities and other stakeholder in a water-scarce basin, as is the study area.

The main goal of the review is to provide a summary and an assessment of the potential of fast-growing tree species for suitable transformation of agroforestry areas for biomass production in the Baltic Sea region. The article summarizes the research on the management process of agroforestry zones by establishing short rotation plantations with tree species Salix spp., Populus spp., Alnus spp. and looks at the perspectives of planning of these zones as biomass producers. Short rotation forestry (SRF) with a combination of species and a rotation time of 15 to 30 years, depending on the species used, is the most suitable approach for management of these agroforestry zones. Willows (Salix spp.) and poplars (Populus spp.) are suitable for short rotation coppice (SRC), as these tree species can be harvested at much shorter intervals, respectively, 1–5 and 4–10 years, facilitating their use in agricultural systems. In Alnus spp. short rotation plantation the life cycle for energy wood production is assumed to be 15-30 years. The black alder plantations in agroforestry zones are used for sawnwood and firewood production, with a rotation span of 20–40 years. Calculated economic agroforestry zone repayment period is about 10-15 years, if costs and prices as in 2021 are used.

Ni-Al alloys have good corrosion-resistant properties making them preferable as a material of choice compared to ordinary metals. A good understanding of the phase diagram and thermodynamic properties of the Ni-Al alloy binary system is essential in determining relevant industrial applications of the system. The Ni-Al phase diagram is being reassessed since those found in the literatures are based on very old experimental studies. The phase diagram and thermodynamic properties of the Ni-Al alloy is determined using the Thermo-Calc 2022b software over a temperature range of 200 K to 2000 K and 1 atm of pressure. A total of nineteen fields (including elemental Al and Ni) comprising of five single solid phases, one liquid phase, and twelve double regions was obtained from the equilibrium calculation. The thermodynamic calculation has six invariant reactions comprising of two eutectic reactions (914.83 ± 0.025 K and 1641.80 ± 0.025 K), three peritectic reactions (1123.55 ± 0.025 K, 1400.72 ± 0.025 K and 1642.65 ± 0.025 K), and one peritectoid reaction (913.96 ± 0.025 K). The solubility of Al in Ni is also determined. The Thermo-Calc temperature – composition of the Ni-Al alloy is compared with the existing experimental studies to identify the physical properties of the different thermodynamic properties of the Ni-Al alloy binary system.