ISSN: 2959-7676 (Online)
2959-7668 (Print)
Clean Energy and Sustainability (CES) aims to be an international, peer-reviewed and open access journal that publishes original theoretical and experimental research in all aspects of clean energy.
A smooth transition towards a clean and sustainable environment will heavily rely on the continuous increase of renewable energy (RE) integration. Malaysian authorities have set targets to increase the RE capacity to 31% by the end of 2025 and achieve 40% by 2035, specifically through the power generation plan. Solar PV systems have been widely used, from industries to residential homes, because Malaysia receives a high irradiation potential of up to 5000 Wh/year. The increase in the potential of solar PV usage has allowed solar companies to provide this system regardless of its complexity and system size. However, a drop in efficiency due to system parameters within the photovoltaic (PV) system is evident over time. This study aims to analyze the relationship between solar PV system parameters and their energy performance, particularly in a tropical climate region, for a large-scale solar (LSS) plant. This project was undertaken with two objectives: First, it is to develop an optimum solar PV system by adhering to and implementing GCPV standards in Malaysia. Stage 1 will primarily focus on managing and manipulating various PV system parameters to ensure the optimum energy yield received from the plant. The system parameters analyzed are tilt angle, module technology and its effect on different temperatures, the effect of the optimizer, sizing and thermal loss. Stage 2 will then incorporate the industry data of the LSS plant by creating a Pearson’s Correlation model on how energy yield is correlated against real time system parameter values obtained. An optimum tilt angle of 10°, monocrystalline module and inclusion of optimizer increases the overall energy production from 88,986 MWh/year to 89,782 MWh/year and performance ratio (PR) from 78.9% to 79.8%. The outcome of this study demonstrates the significant parameters of the PV system to maximize the energy output to the grid. This will further support the government’s plan to reduce GHG emissions by 45% through the use of renewable energy, with the aim of producing up to 2.5 GW from LSS systems by 2030.
This paper elucidates the development of electricity production and distribution in Greece from the 1950s to date, in correlation with national and European energy policy. During this period, Greece experienced a multifaceted energy transition, including both the transition of ownership of energy generation companies from public to private and a transition from an energy mix in which coal (lignite) served as a major and inexpensive resource to a mix in which wind power, solar power and natural gas gained a primary role, but with high costs for energy generation. The correlation between electrical energy consumption and economic growth is explored in this context, revealing an increase in consumption before the 2009 recession and a decline thereafter. The study investigates the correlation between escalating electricity prices and legislative dependencies that mandated the purchase of wind- and solar-generated electricity at exorbitant rates, the closure of cost-effective lignite units, and the reliance on natural gas—a commodity susceptible to geopolitical shifts. It also shows that, given the structure of the Greek energy mix, the increase in the share of wind and solar energy in the mix is directly related to the increase in the price of electricity. Highlighting the importance of energy costs for prosperity, this paper underscores, through the detailed review of the Greek energy “landscape”, that the major determinants of electricity prices are both the accessibility to natural resources but also their proper and judicious management.
The aggregate upsurge in carbon dioxide emissions (CO2) witnessed through environmental degradation and global climate change is a call for great concern. This, therefore, calls for the enactment, utilization and implementation of provisions and policies geared towards curbing this global economic bad without impeding global economic growth rates. This study ascertains the extent to which renewable energy consumption (REC), economic growth (GDP), population growth (POP), globalization (GLO), and financial development (FD) affect carbon dioxide emissions (CO2) in selected G7 economies (France, Germany, Canada, Italy, and the United Kingdom) from 1990–2020. The Dynamic Fixed Effect Autoregressive Distributive Lag (DFE-ARDL) and the Pooled Mean Group ARDL (PMG-ARDL) methods were employed for analysis. The empirical findings for DFE-ARDL showed that REC, GDP, and POP have an adverse association with CO2 in the long-term. However, in the short-term, REC and FD improve the environment, while GDP and POP drive CO2. It is observed that the result for REC in the short and long-run is consistent. The PMG-ARDL results revealed that REC and GLO negatively affect CO2 in the long-run, and in the short-run, GDP spurs CO2, while FD reduces it. The result summary of both methods employed demonstrates that REC, GLO, and FD benefit the environment. At the same time, GDP and POP harm the environment in the short-run but reduce CO2 in the long-run. Conclusively, the research recommends increasing the utilization of renewable energy and policies that enable economic growth and CO2 to move in the opposite direction.
This study investigates the distinct impacts of electricity and petroleum consumption on economic growth in Eastern Africa. Using a Panel Autoregressive Distributed Lag Model and data for a period spanning 2000 to 2021, the study examines both the short-run and long-run effects of these energy sources on Gross Domestic Product. The findings reveal that petroleum consumption has a statistically significant and positive impact on GDP in both the short run and long run. In contrast, while electricity consumption shows a positive but statistically insignificant effect on GDP in the short run, it exhibits a negative and statistically significant impact in the long run. These results suggest that policymakers in Eastern Africa should prioritize sustainable petroleum management to maximize its economic benefits while mitigating potential environmental risks. While the negative coefficient of electricity implies a corrective response of the variables to long-run equilibrium in the face of short-term shocks. As a result, it is recommended that economic shocks caused by energy consumption be considered in terms of their relationship to economic growth, whether positive or negative in the long or short term, as decision makers need to address their impact and limit such shocks on economic growth.
Hydrogen energy offers a significant potential for reducing carbon emissions and integrating clean energy across sectors such as heavy-duty vehicles, energy-intensive industries, and building heating. This study analyzes the energy efficiency and emissions of grey and blue hydrogen supply chains, identifying key issues such as high energy consumption and losses in transportation, steam methane reforming, and liquid hydrogen storage. Truck transportation emerges as the highest emitter, with emissions ranging from 0.140 to 0.150 kg CO2e per kg of hydrogen. Using a bi-objective Dijkstra Algorithm, the study identifies the most energy-emissions-efficient pathways and reveals a trade-off between energy efficiency and greenhouse gas emissions. Grey hydrogen shows higher energy efficiency (38.0%) but higher emissions (0.1689 kg CO2e per kg of hydrogen). In contrast, with 60% and 90% carbon capture and storage, blue hydrogen has slightly lower energy efficiencies (37.5% and 36.9%) but reduced emissions (0.1564 and 0.1514 kg CO2e per kg of hydrogen). Liquefied natural gas and hydrogen offer high energy efficiency but increase emissions, while compressed natural gas and hydrogen slightly reduce efficiency but nearly halve emissions. Hence, compressed options are preferable for an energy-emissions-efficient shortest path.
Urban energy models (UEMs) simulate energy use at the urban scale and are used to inform urban planning, policy development, infrastructure development, and digital twin monitoring and forecasting. Recent technological improvements have spurred interest in large, multi-domain UEMs, which analyse multiple interconnected parts of these energy systems, such as geography, transport, and buildings. Reviews have focussed on single domains or aspects of UEM data. However, multi-domain UEMs require detailed multi-domain data inputs to provide accurate results. This paper provides a comprehensive review of data requirements and a repository of data-specific information for researchers, including data formats, sources, acquisition methods, bridging methods, and challenges. The review was conducted using academic search engines and the authors’ direct research experience. Domains are characterised by Climate, Geographic, Building, Transportation, Demographics, Energy Networks and Consumption, and Distributed Energy Resources. Additionally, challenges common to multiple sectors are identified, and methods for addressing these are proposed. The paper concludes with a series of recommendations drawing from the general and sector-specific challenges. Overall, a large amount of data exists, but their use by urban energy modellers is limited due to lack of coordination and standardisation, and concerns over privacy and commercial interests. Coordinated public effort is required to overcome these limitations and improve the results of UEMs in the future.
Hydrogen (H2) emerges as a promising clean energy source, but its efficient purification from various sources needs advanced separation technologies. This study explores the use of CO2-selective membranes, especially mixed matrix membranes (MMM) incorporating KAUST-7 metal-organic framework (MOF), for hydrogen purification. The MMM was fabricated with various KAUST-7 content in a polymer matrix (Pebax 1657) and characterized via Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and gas permeation tests. The XRD analysis confirms the incorporation of KAUST-7 into the MMM, while SEM reveals a homogeneous particle distribution at low content (below 10%) but agglomeration at higher ones (above 10%). FTIR confirms good interfacial interactions between the MOF and polymer matrix. TGA results show that the MMM thermal stability slightly decreases with increasing MOF content. Gas permeation results reveal improved CO2 permeability (79%) and CO2/H2 selectivity (19%) for MMM compared to neat Pebax membranes, with an optimal performance observed at 10 wt.% KAUST-7. Beyond this threshold, the performance deteriorates, possibly due to polymer rigidity and MOF agglomeration. Overall, the study highlights the potential of KAUST-7/Pebax MMM for enhanced hydrogen purification.
Considering the healthiness of the atmosphere in mining activities (e.g., tunnelling), two of the most important parameters to be monitored are the concentration of oxygen and the presence of harmful gases such as CO2. Traditional methods for their measurement are fixed platforms and portable gas detectors carried by miners; they are incapable of recognizing sudden or short-term pollution events or correctly accounting for the spatial scarcity of gases. A UAV (Unmanned Aerial Vehicle) device capable of guaranteeing the measurement and continuous monitoring of concentrations has been designed. By using innovative technologies, it promotes digitization in the mining sector. This approach replaces current methods that, while effective at detecting and measuring environmental parameters, are slow, routine, and heavily reliant on human input. It saves productive expenses in the sector since it reduces costs compared to hiring a field technician for activities such as analysis of environmental conditions. This saving is about 110 euros daily, representing a 32% saving per working day for each mining technical responsible for environmental control. It also obtains a 3D spatial distribution of contaminants, a high sample resolution and a high sample resolution.. It reduces inspection time in mining works and the data collection time by more than 50%. The ECODRONE project constitutes a contribution to the MINE THE GAP challenge is a project financed with European funds whose line of desire aims to combine the innovation and development of SMEs or business groups from different regions of the mining, raw materials and materials sector. This program is aimed at strengthening the existing value chains and developing new industrial ones while designing new procedures, automated technologies, information and communication flows, which increase efficiency in the consumption of resources. All of the above implies integration with a circular economy and respect for European and global efficiency policies aimed at sustainability, industrial modernization, human health and the environment.
Mineralogical and chemical analyses of the major constitutive minerals from granite des Crêtes collected near the thermal site of Plombières-les-Bains (Vosges Mountains, eastern France) clearly show that recently circulating thermal waters up to 90 °C do not impact them. Even the constitutive minerals smaller than 2 microns are not affected. As a result, all minerals reflect the entire complex tectonic-thermal history of the granitic massif rather than just the recent thermal impact. Only the open faults and natural drains contain calcite from recent thermal waters. This is confirmed by similar calcite deposits with the same elemental contents sampled in the pipes of thermal installations. As a complementary conclusion, storage of containers of nuclear waste that diffuse an overall temperature up to 100 °C will not alter the potential sealing properties of a plutonic host massif, of course, without any recent thermal drainage that could potentially spread radioactive waste. This conclusion was already obtained on a moderately faulted sedimentary environment after a one-year in-situ heating experiment at about 100 °C. Calcium is a key indicator of low thermal impact. After an initial decrease, its levels rose significantly in the most "altered" granite samples, inducing calcite precipitation, even in the water pipes at the thermal site. The negligible impact of a hydro-thermal activity at a maximum of about 100 °C in a granitic material represents, indeed, a piece of useful information, as deep sites for nuclear waste in plutonic host rocks appear to act, also, as potential isolated host systems.
Climate change is one of the most critical sustainability challenges facing the humanity. International communities have joined forces to mitigate climate change impact and aim to achieve carbon neutrality in the coming decades. To achieve this ambitious goal, life cycle thinking can play critical roles. Specifically, life cycle thinking helps evaluate the true climate impacts to avoid shifting emissions across processes in a product life cycle. It can also help inform consumers with carbon footprint information to make climate-conscious choices. Finally, it can help identify key processes dominating the carbon footprint of a product so that future improvement can set priorities. High quality data is required for accurate and timely carbon footprint accounting and critical challenges exist to obtain and share such data.
Dairies which produce cheese and milk products can, however, produce large volumes of wastewater that require treatment, usually via activated sludge treatment. Disposal of the resulting activated sludge to land is viewed favorably as the sludge is rich in phosphorus (P) and nitrogen (N) and enables nutrient recycling. Nonetheless, sludge management can significantly influence the greenhouse gas (GHG) emissions to the atmosphere. This manuscript has modelled the GHG emissions arising from two sludge management strategies currently adopted by Danish dairies whereby: (i) sludge is stored and later applied to fields; or (ii) sludge is treated by anaerobic digestion (AD), stored, and the digestate will later be applied to fields. This is compared to (iii) an alternative sludge management strategy with treatment by Hydrothermal Carbonization (HTC). HTC is a technologically simple sludge treatment that could lower the cost for dewatering dairy sludge, forming a biochar-like material known as hydrochar. The produced hydrochar can be applied to the land for the purpose of carbon sequestration, P and N recycling. Our calculations indicate that GHG balances of HTC sludge management can result in a net carbon sequestration of 63 kg CO2eq per ton sludge, as opposed to net emissions of 420 and 156 kg CO2eq per ton sludge for strategies (i) and (ii), therefore offering significant reductions GHG emissions for the dairy sector.
The transition to clean and sustainable energy sources is crucial for combating the challenges posed by climate change. Green hydrogen, produced through renewable energy-driven electrolysis, holds significant promise as a viable clean energy carrier. The study introduces a system that leverages abundant solar energy and utilizes seawater as the feedstock for electrolysis, potentially offering a cost-effective solution. A comprehensive mathematical model, implemented in MATLAB, is employed to simulate the design and operational efficiency of the proposed green hydrogen production system. The system’s core components include solar panels as a clean energy source, an advanced MPPT charge controller ensuring optimal power delivery to the electrolyzer, and a seawater tank serving as the electrolyte source. The model combines these elements, allowing for continuous operation and efficient hydrogen production, addressing concerns about energy losses and cost-effectiveness. Results demonstrate the influence of solar irradiance on the system’s performance, revealing the need to account for seasonal variations when designing green hydrogen production facilities. Theoretical experiments are conducted to evaluate the behavior of a lithium battery, essential for stabilizing the system’s output and ensuring continuous operation during periods of low solar radiation.
Nowadays, increasing attention is directed towards the sustainable use of raw materials. For a circular economy, recovery from spent devices represents a fundamental practice. With the transition to electric mobility, an increasing number of devices powered by lithium batteries are produced. Indeed, this is the fastest growing sector producing spent batteries, which are an important secondary source of critical raw materials, such as lithium, cobalt, graphite, and nickel. Therefore, this work aims to quantify the economic impact of recovering raw materials from lithium batteries used in the electric vehicles sector. Based on the chemical composition of the various lithium batteries and their market diffusion, the intrinsic economic value of this waste has been estimated to be around 6500 €/ton. Starting from the literature data on the global energy demand from lithium batteries and deriving the trend of their specific energy over time, the mass of material introduced into the market annually is estimated to reach 60 Mton/year by 2040. The annual amount of end-of-life lithium batteries was calculated by applying the Weibull distribution to describe the probability of failure, yielding 10 Mton/year by 2040. Finally, based on these results, the economic impact of the recovery market was assessed for two different scenarios.
This study explores the transient characteristics of a drain water heat recovery (DWHR) device employed for heat recovery from warm grey water in buildings. Experimental measurements were conducted to investigate the response time of the DWHR device under various flow conditions. The thermal performance of the system was assessed using both transient and steady-state effectiveness analyses. The findings reveal that the response time is influenced by the water volume within the system, with an increase observed, and by the water flow rate, which leads to a decrease in response time. Additionally, a decrease in effectiveness is noted when hot water is used in short and frequent intervals. Furthermore, an economic analysis demonstrates that considering the transient behavior of the device results in a significant overall decrease of 37% in annual savings. Specifically, the usage of sinks exhibits a reduction in annual savings by 56%, while showers show a decrease of 13% in annual savings.
Numerical simulation is a widely used tool for studying CO2 storage in porous media. It enables the representation of trapping mechanisms and CO2 retention capacity. The complexity of the involved physicochemical phenomena necessitates multiphase flow, accurate fluid and rock property representation, and their interactions. These include CO2 solubility, diffusion, relative permeabilities, capillary pressure hysteresis, and mineralization, all crucial in CO2 trapping during carbon storage simulations. Experimental data is essential to ensure accurate quantification. However, due to the extensive data required, modeling under uncertainty is often needed to assess parameter impacts on CO2 trapping and its interaction with geological properties like porosity and permeability. This work proposes a framework combining laboratory data and stochastic parameter distribution to map uncertainty in CO2 retention over time. Published data representing solubility, residual trapping, and mineral trapping are used to calibrate prediction models. Geological property variations, like porosity and permeability, are coupled to quantify uncertainty. Results from a saline sandstone aquifer model demonstrate significant variation in CO2 trapping, ranging from 17% (P10 estimate) to 56% (P90), emphasizing the importance of considering uncertainty in CO2 storage projects. Quadratic response surfaces and Monte Carlo simulations accurately capture this uncertainty, resulting in calibrated models with an R-squared coefficient above 80%. In summary, this work provides a practical and comprehensive framework for studying CO2 retention in porous media, addressing uncertainty through stochastic parameter distributions, and highlighting its importance in CO2 storage projects.
Oil is an unsustainable energy since it is non-renewable. However, oil may not be completely replaced in a short time, so the environmental problems caused by the oil development still require our attention. The oily sludge is a kind of hazardous waste produced during the oil development. To reduce the environmental impact caused by oily sludge, low-carbon and sustainable treatment technologies need to be selected. The incineration, chemical extraction and thermal desorption are common technologies for treatment of oily sludge. We calculated the carbon emissions of these technologies. Then the index evaluation system of oily sludge treatment technology was established with the environmental, economic, social, and technical factors. And the weight of evaluation index was determined by the analytic hierarchy process (AHP). Through the investigation of industry experts, we evaluated the treatment technologies by the fuzzy comprehensive evaluation method (FCE). The results showed that the carbon emissions of incineration are 42.70 t CO2-eq/t which is the highest. Meanwhile, it is 4.80 t CO2-eq/t and 0.10 t CO2-eq/t for chemical extraction and thermal desorption, respectively. The comprehensive scores of incineration, chemical extraction and thermal desorption were 4.59, 5.16 and 4.95, respectively. Therefore, the chemical extraction technology is an optimal treatment technology for oily sludge with the relatively low carbon emission and the highest comprehensive technical score. At the same time, the thermal desorption technology has strong application potential with the lowest carbon emissions. This result provides a reference for achieving clean and sustainable energy development processes.
Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation techniques, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES while alleviating grid-connect issues. Microgrids are interconnected RESs and electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate independently and be grid-connected. The paper presents a review and performance assessment of renewable energy-based microgrids under various operating scenarios in stand-alone, grid-connected, and transitioning modes of operation. Fault occurrences, an increase in micro-source generation, a load increase, and the sudden disconnection of a micro-source are some of the simulated scenarios. Microgrid network components’ performance, such as the bidirectional DC-DC converter and energy storage system (ESS), was evaluated. The simulated microgrid architecture includes a small hydroelectric plant, wind farm, and ESS. The work provides valuable information to energy stakeholders on the performance of microgrids in low-voltage distribution networks. The microgrid is coupled to a low-voltage distribution network (0.415 kV) via a PCC. The system under investigation is modeled and simulated using MATLAB/Simulink. From the simulation analysis, the fault effect was felt on the utility and did not escalate to the microgrid side during stand-alone operation. Power quality issues, such as voltage rise, are some of the challenges identified during the transition from one mode of operation to another. However, the energy storage system responds to disturbances and maintains system stability. The originality of this paper is based on evaluating different modes of operation of microgrids and comparing system performances under various operating conditions.
Seawater desalination plays a vital role in addressing the increasing global demand for freshwater. However, the energy-intensive nature of desalination processes and the generation of brine by-products pose environmental challenges. In Western Australia (WA), approximately 48% of freshwater is supplied by two seawater desalination plants employing the energy-intensive seawater reverse osmosis (SWRO) method. These plants are powered by a combination of renewable and conventional energy sources. Typically, the most efficient approach for desalination plants involves a blend of renewable energy sources. Salinity gradient energy (SGE) harnessed through the reverse electrodialysis (RED) system, which derives energy from mixing waters with varying salinities, has emerged as a potential solution. RED utilizes ion-exchange membranes to convert the chemical potential difference between two solutions into electric power. The net specific energy of SGE, calculated based on the Gibbs free energy associated with mixing seawater and wastewater, is estimated at approximately 0.14 kWh per cubic metre of brine for SWRO desalination plants. The combined SGE potential of WA’s two desalination facilities theoretically amounts to approximately 87.4 MWh of energy. However, due to the inherent limitations of the RED system’s current energy efficiency, only about 2.5% of the desalination plant’s energy requirements can be met through this technique. This paper addresses a significant gap in the literature by analyzing the technical and economic constraints of utilizing salinity gradient energy (SGE) through the reverse electrodialysis (RED) system for seawater desalination plants. This marks the first examination of its kind, shedding light on both the technical feasibility and economic challenges of SGE-RED application in this context. The scientific contribution lies in its innovative approach, integrating technical and economic perspectives to provide an understanding of SGE-RED technology’s potential drawbacks and opportunities. By identifying and tackling these challenges, this paper aims to pave the way for optimizing SGE-RED systems for practical implementation in seawater desalination plants.
Dairies which produce cheese and milk products can, however, produce large volumes of wastewater that require treatment, usually via activated sludge treatment. Disposal of the resulting activated sludge to land is viewed favorably as the sludge is rich in phosphorus (P) and nitrogen (N) and enables nutrient recycling. Nonetheless, sludge management can significantly influence the greenhouse gas (GHG) emissions to the atmosphere. This manuscript has modelled the GHG emissions arising from two sludge management strategies currently adopted by Danish dairies whereby: (i) sludge is stored and later applied to fields; or (ii) sludge is treated by anaerobic digestion (AD), stored, and the digestate will later be applied to fields. This is compared to (iii) an alternative sludge management strategy with treatment by Hydrothermal Carbonization (HTC). HTC is a technologically simple sludge treatment that could lower the cost for dewatering dairy sludge, forming a biochar-like material known as hydrochar. The produced hydrochar can be applied to the land for the purpose of carbon sequestration, P and N recycling. Our calculations indicate that GHG balances of HTC sludge management can result in a net carbon sequestration of 63 kg CO2eq per ton sludge, as opposed to net emissions of 420 and 156 kg CO2eq per ton sludge for strategies (i) and (ii), therefore offering significant reductions GHG emissions for the dairy sector.utf-8
The transition to clean and sustainable energy sources is crucial for combating the challenges posed by climate change. Green hydrogen, produced through renewable energy-driven electrolysis, holds significant promise as a viable clean energy carrier. The study introduces a system that leverages abundant solar energy and utilizes seawater as the feedstock for electrolysis, potentially offering a cost-effective solution. A comprehensive mathematical model, implemented in MATLAB, is employed to simulate the design and operational efficiency of the proposed green hydrogen production system. The system’s core components include solar panels as a clean energy source, an advanced MPPT charge controller ensuring optimal power delivery to the electrolyzer, and a seawater tank serving as the electrolyte source. The model combines these elements, allowing for continuous operation and efficient hydrogen production, addressing concerns about energy losses and cost-effectiveness. Results demonstrate the influence of solar irradiance on the system’s performance, revealing the need to account for seasonal variations when designing green hydrogen production facilities. Theoretical experiments are conducted to evaluate the behavior of a lithium battery, essential for stabilizing the system’s output and ensuring continuous operation during periods of low solar radiation. utf-8
Nowadays, increasing attention is directed towards the sustainable use of raw materials. For a circular economy, recovery from spent devices represents a fundamental practice. With the transition to electric mobility, an increasing number of devices powered by lithium batteries are produced. Indeed, this is the fastest growing sector producing spent batteries, which are an important secondary source of critical raw materials, such as lithium, cobalt, graphite, and nickel. Therefore, this work aims to quantify the economic impact of recovering raw materials from lithium batteries used in the electric vehicles sector. Based on the chemical composition of the various lithium batteries and their market diffusion, the intrinsic economic value of this waste has been estimated to be around 6500 €/ton. Starting from the literature data on the global energy demand from lithium batteries and deriving the trend of their specific energy over time, the mass of material introduced into the market annually is estimated to reach 60 Mton/year by 2040. The annual amount of end-of-life lithium batteries was calculated by applying the Weibull distribution to describe the probability of failure, yielding 10 Mton/year by 2040. Finally, based on these results, the economic impact of the recovery market was assessed for two different scenarios.utf-8
Climate change is one of the most critical sustainability challenges facing the humanity. International communities have joined forces to mitigate climate change impact and aim to achieve carbon neutrality in the coming decades. To achieve this ambitious goal, life cycle thinking can play critical roles. Specifically, life cycle thinking helps evaluate the true climate impacts to avoid shifting emissions across processes in a product life cycle. It can also help inform consumers with carbon footprint information to make climate-conscious choices. Finally, it can help identify key processes dominating the carbon footprint of a product so that future improvement can set priorities. High quality data is required for accurate and timely carbon footprint accounting and critical challenges exist to obtain and share such data.utf-8
This article presents the opportunities for constructing a global data base picturing underlying trends that drive global climate change. Energy-related CO2 emissions currently represent the key impact on climate change and thus become here the object of deep, long-term and historiographic analysis. In order to embrace all involved domains of technology, energy economy, fuel shares, economic efficacity, economic structure and population, a “Global Change Data Base” (GCDB) is suggested, based on earlier worldwide accepted data repositories. Such a GCDB works through regressions and statistical analysis of time series of data (on extensive magnitudes such as energy demand, population or Gross Domestic Product, GDP) as well as generation of derived data such as quotients of the former, yielding intensive magnitudes that describe systems and their structural properties. Moreover, the GCDB sets out to compute the first and second time derivatives of said magnitudes (and their percentual shares) which indicate new long-term developments already at very early phases. The invitation to participate in this foresight endeavour is extended to all readers. First preliminary GCDB results quantitatively portray the evolutionary structural global dynamics of economic growth, sectoral economic shifts, the shifts within energy carriers in various economic sectors, the ongoing improvements of energy intensity and energy efficiency in many economic sectors, and the structural changes within agricultural production and consumption systems.utf-8
Numerical simulation is a widely used tool for studying CO2 storage in porous media. It enables the representation of trapping mechanisms and CO2 retention capacity. The complexity of the involved physicochemical phenomena necessitates multiphase flow, accurate fluid and rock property representation, and their interactions. These include CO2 solubility, diffusion, relative permeabilities, capillary pressure hysteresis, and mineralization, all crucial in CO2 trapping during carbon storage simulations. Experimental data is essential to ensure accurate quantification. However, due to the extensive data required, modeling under uncertainty is often needed to assess parameter impacts on CO2 trapping and its interaction with geological properties like porosity and permeability. This work proposes a framework combining laboratory data and stochastic parameter distribution to map uncertainty in CO2 retention over time. Published data representing solubility, residual trapping, and mineral trapping are used to calibrate prediction models. Geological property variations, like porosity and permeability, are coupled to quantify uncertainty. Results from a saline sandstone aquifer model demonstrate significant variation in CO2 trapping, ranging from 17% (P10 estimate) to 56% (P90), emphasizing the importance of considering uncertainty in CO2 storage projects. Quadratic response surfaces and Monte Carlo simulations accurately capture this uncertainty, resulting in calibrated models with an R-squared coefficient above 80%. In summary, this work provides a practical and comprehensive framework for studying CO2 retention in porous media, addressing uncertainty through stochastic parameter distributions, and highlighting its importance in CO2 storage projects. utf-8
Seawater desalination plays a vital role in addressing the increasing global demand for freshwater. However, the energy-intensive nature of desalination processes and the generation of brine by-products pose environmental challenges. In Western Australia (WA), approximately 48% of freshwater is supplied by two seawater desalination plants employing the energy-intensive seawater reverse osmosis (SWRO) method. These plants are powered by a combination of renewable and conventional energy sources. Typically, the most efficient approach for desalination plants involves a blend of renewable energy sources. Salinity gradient energy (SGE) harnessed through the reverse electrodialysis (RED) system, which derives energy from mixing waters with varying salinities, has emerged as a potential solution. RED utilizes ion-exchange membranes to convert the chemical potential difference between two solutions into electric power. The net specific energy of SGE, calculated based on the Gibbs free energy associated with mixing seawater and wastewater, is estimated at approximately 0.14 kWh per cubic metre of brine for SWRO desalination plants. The combined SGE potential of WA’s two desalination facilities theoretically amounts to approximately 87.4 MWh of energy. However, due to the inherent limitations of the RED system’s current energy efficiency, only about 2.5% of the desalination plant’s energy requirements can be met through this technique. This paper addresses a significant gap in the literature by analyzing the technical and economic constraints of utilizing salinity gradient energy (SGE) through the reverse electrodialysis (RED) system for seawater desalination plants. This marks the first examination of its kind, shedding light on both the technical feasibility and economic challenges of SGE-RED application in this context. The scientific contribution lies in its innovative approach, integrating technical and economic perspectives to provide an understanding of SGE-RED technology’s potential drawbacks and opportunities. By identifying and tackling these challenges, this paper aims to pave the way for optimizing SGE-RED systems for practical implementation in seawater desalination plants.utf-8
This study explores the transient characteristics of a drain water heat recovery (DWHR) device employed for heat recovery from warm grey water in buildings. Experimental measurements were conducted to investigate the response time of the DWHR device under various flow conditions. The thermal performance of the system was assessed using both transient and steady-state effectiveness analyses. The findings reveal that the response time is influenced by the water volume within the system, with an increase observed, and by the water flow rate, which leads to a decrease in response time. Additionally, a decrease in effectiveness is noted when hot water is used in short and frequent intervals. Furthermore, an economic analysis demonstrates that considering the transient behavior of the device results in a significant overall decrease of 37% in annual savings. Specifically, the usage of sinks exhibits a reduction in annual savings by 56%, while showers show a decrease of 13% in annual savings.utf-8
Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation techniques, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES while alleviating grid-connect issues. Microgrids are interconnected RESs and electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate independently and be grid-connected. The paper presents a review and performance assessment of renewable energy-based microgrids under various operating scenarios in stand-alone, grid-connected, and transitioning modes of operation. Fault occurrences, an increase in micro-source generation, a load increase, and the sudden disconnection of a micro-source are some of the simulated scenarios. Microgrid network components’ performance, such as the bidirectional DC-DC converter and energy storage system (ESS), was evaluated. The simulated microgrid architecture includes a small hydroelectric plant, wind farm, and ESS. The work provides valuable information to energy stakeholders on the performance of microgrids in low-voltage distribution networks. The microgrid is coupled to a low-voltage distribution network (0.415 kV) via a PCC. The system under investigation is modeled and simulated using MATLAB/Simulink. From the simulation analysis, the fault effect was felt on the utility and did not escalate to the microgrid side during stand-alone operation. Power quality issues, such as voltage rise, are some of the challenges identified during the transition from one mode of operation to another. However, the energy storage system responds to disturbances and maintains system stability. The originality of this paper is based on evaluating different modes of operation of microgrids and comparing system performances under various operating conditions.utf-8