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Abstract: Abstract To address the multifaceted challenge of sustainability posed by human interventions and climate change, the urgent need to harness agroforestry for biomass production, carbon sequestration, and the integration of the water-food-energy nexus has been recognized. This approach has not only provided innovative solutions but also highlighted the complexities and difficulties inherent in achieving sustainable development. This systematic literature review provides a comprehensive overview of research spanning 24 years, elucidating the role of agroforestry in mitigating climate change impacts, enhancing biomass provision, carbon sequestration, and optimizing the water-food-energy nexus. Various forms of agroforestry systems exhibit differing capacities to supply biomass and sequester carbon. In a study of a poplar-based agroforestry system, the dry biomass yield of poplar ranged from 69.90 to 207.98 Mg ha−1 aboveground and 13.46 to 36.69 Mg ha−1 belowground across five different planting geometries. The total carbon storage, encompassing both above and belowground biomass, varied among spacing configurations, with values of 112.48, 101.80, 84.87, 77.28, and 38.84 Mg C ha−1, respectively. Further, agroforestry (sapota-cowpea-castor) decreased soil loss and runoff by 37.7 and 19.1%, respectively, compared to sole crop cultivation. Similarly in another study, the Karanda (Carissa sp.) based agroforestry system with a mung bean-potato system achieved the highest net return (3529.1 US$ ha−1) and water use efficiency (33.0 kg ha-mm−1). The review synthesizes findings from diverse studies highlighting the multifunctional benefits of agroforestry systems across various geographical regions and agroecological contexts. Key themes explored include biomass production, carbon sequestration potential, and the intricate linkages between water, food, and energy security within agroforestry landscapes. Through a synthesis of empirical evidence, the review underscores the capacity of agroforestry to enhance ecosystem resilience, mitigate greenhouse gas emissions, and foster sustainable livelihoods for rural communities. Moreover, it examines the synergies and trade-offs inherent in agroforestry interventions, considering factors such as species selection, management practices, and socio-economic considerations. The review also identifies gaps in current knowledge and areas requiring further research attention, such as the scaling up of agroforestry practices, socio-economic impacts on local communities, and policy frameworks for mainstreaming agroforestry into national and international climate and development agendas. Overall, this review underscores the pivotal role of agroforestry as a holistic approach to achieving multiple SDGs, particularly in the face of climate change. By integrating biomass provision, carbon sequestration, and optimizing resource use through the water-food-energy nexus, agroforestry offers a sustainable pathway toward resilient and equitable development. PubDate: 2024-08-06
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Abstract: Abstract The adverse consequences of hazardous environmental contaminants, at minimal concentration also constitute a major threat to both human health and the ecosystem. Multiple techniques are investigated to remove contaminants. Among these techniques, microbial bioremediation has emerged as an appealing method because of its removal efficacy, affordability, and environmental friendliness. This review is an overview of the major environmental pollutants such as plastics, heavy metals, and dyes with their source and toxicity towards both humans and the environment. The summary of the beneficial microbes like bacteria, fungi, and algae that employ remediation techniques like biosorption, bioaccumulation, bioleaching, biodeterioration, bio-fragmentation, and biotransformation to convert the toxic compounds to non-toxic compounds has been discussed. During the degradation process factors like temperature, pH, initial concentration, O2 concentration, N2 addition, soluble salts, pollutants both chemical and physical structure, and hydrophobic properties play a major role. The enzyme present in the microbes helps in the quick and complete breakdown of the pollutants, emerging advancement techniques like genetic engineering are implied to generate desired compounds or enzymes to attain pollutant removal. As with other removal techniques, like immobilization, the recent advancements are also explained. The review majorly states the efficiency of microbial remediation toward environmental sustainability. PubDate: 2024-07-23
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Abstract: Abstract Air pollution causes around seven million deaths annually worldwide, yet research on the combined impacts of urban pollutants is limited, hindering effective mitigation strategies. This is a concern in Kigali and the East Africa region, where a notable lack of detailed long-term data, limited studies on their health impacts, and a lack of comprehensive methods for assessing urban air pollution impacts and environmental-health risks. This study addresses these gaps, specifically targeting personal exposure to PM10 and NO2, monitored across six stations in Kigali throughout 2021. These pollutants were selected due to their long-term data availability and significant health-impacts. Utilizing computational analysis of the urban air quality method, we identified vulnerable zones, quality indicators, and impacts and risks associated with urban air pollution. Results reveal that PM10 levels (42.0–56.0 µg m− 3 and NO2 levels (15.5–20.4 µg m− 3) have quality exceeding WHO-2021 guidelines (PM10: 15 µg m− 3 and NO2: 10 µg m− 3) indicating severe air quality issues in Kigali. The variation between monitoring stations was statistically significant (p < 0.05), indicating notable spatial differences within the study area. The probability of exposure by zones (0.14–0.3) is linked to traffic and household emissions. The identified high-impact for PM10 suggests more significant concerns and the need for mitigation, while the low-risk for both pollutants indicates a relatively low immediate health threat. These findings highlight the need for strategic mitigation measures and targeted air quality management policies to control traffic and household emissions, which are essential for improving Kigali’s air quality and safeguarding public health. PubDate: 2024-07-18
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Abstract: Abstract The seedling of Nicotiana tabacum L. (N. tabacum) holds strategic and economic importance in the product chain due to its vital contributions to agronomical yield and the characteristics of the final product. This study assessed the environmental life cycle impacts of three technologies for N. tabacum seedlings (traditional seedbed, technified, and tray-based). This assessment considered the main activities within the studied system boundaries, insecticides, fertilizers, fungicides, infrastructure, energy, seedling and composting, irrigation, and land use. In this context, relevant scenarios were examined for the Cuban context. The findings reveal that tray-based technology exhibited lower environmental burdens due to reduced consumption of insecticides, fungicides, and fertilizers in N. tabacum phytotechnology, as well as lower diesel consumption in water pumping for irrigation. Energy consumption was the highest contributing factor in 10 out of the 18 impact categories (with values of up to 90%), associated with the emissions from electricity consumption in a fossil fuel-based energy matrix. Additionally, Seedling and composting showed higher impacts in five impact categories (with values of up to 99.8%) due to emissions of nitrogen oxides and acephate into the air. The implementation of cleaner production strategies resulted in a significant reduction of impacts compared to the baseline scenario, particularly through a combination of photovoltaic energy generation for water irrigation pumping and optimized soil tillage (reducing diesel consumption), leading to a reduction of up to 73%. These results not only benefit researchers and farmers but also provide valuable insights for decision-makers, supporting the implementation of renewable energy sources in agriculture. PubDate: 2024-07-08
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Abstract: Abstract Oil spills are of great concern because oily wastewater disrupts the aquatic ecosystem, causes mutations in animals, contaminates surface water resources, and causes diseases such as cancer in humans. Current efforts are geared towards recovering spilled oil from aquatic environments and ensuring the effective separation of oil and water in the collected emulsion. After oil separation from the emulsion, a polishing step is required to treat the residual oil in the water before discharging the effluent into the aquatic environment. Oily wastewater treatment methods such as electrochemical treatment, membrane filtration, flocculation, membrane bioreactor, and advanced oxidation processes are intricate, costly, and achieve varying removal efficiencies. Adsorption using environmentally friendly and cost-effective adsorbents is seen as an attractive option. This paper provides an overview of oily wastewater treatment using adsorption. Recent adsorption studies have focused on optimizing parameters such as adsorbent dosage, pH, initial oil concentration (IC), and contact time (CT) to enhance treatment efficiency. Principal component analysis was conducted based on previous studies to understand the key parameters influencing adsorption and gain insights into the interactions between these operating variables. The findings indicated a strong positive correlation between the first principal component (PC1) CT and IC, with coefficients of 0.704 and 0.702, respectively. This suggests that positive values of CT and IC significantly contribute to the variance in PC1, meaning that the variation in PC1 is closely linked to the variation in CT and IC. New materials could be produced to enhance selectivity to target specific pollutants in oily wastewater. PubDate: 2024-07-02
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Abstract: Abstract The utopia-tracking method, used to find compromise solutions or trade-offs in multi-objective problems, is proposed as a tool to assign economic and environmental values to user behavior. To this end, an optimal design model of an isolated energy supply system is proposed that selects, using continuous variables, different technologies to integrate a photovoltaic system. The nonlinear programming model computes the size of the system, including the storage unit. The design is approached using a base demand, which corresponds to the real data obtained from the case study, and subsequently the optimal user behavior is calculated to reduce the total annual cost of the system and the equivalent emissions, obtaining a demand coupled to the operation and optimal system design. The relevance of penalties such as the carbon tax on renewable systems is evaluated. The results indicate that the use of carbon penalties does not have a significant effect on emissions control and that, by modifying user behavior, reductions of 8 % in the system cost and just over one ton of CO \(_2 eq\) per year in emissions. Finally, the calculation of compromise solutions is presented as more effective ways to reduce emissions than the use of emissions monetization. PubDate: 2024-06-06 DOI: 10.1007/s40974-024-00330-y
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Abstract: This work aims to propose earth-abundant materials for CO2 photoreduction to generate renewable solar fuels to provide practical solutions to global warming. The selected material in this case is cuprous oxide (Cu2O), one of the most promising photocatalysts for CO2 photoreduction due to its high affinity to solar radiation and electronic properties. Cu2O nanoparticles (NPs) were synthesized using Psidium guajava residue for the photocatalytic CO2 reduction. The aqueous residue of the Psidium guajava fruit proved to be suitable for stabilizing and acting as a reducing agent for the synthesis of Cu2O NPs. The XRD analysis confirmed the formation of the cubic structure of Cu2O. The nanoparticles absorb light from 430 nm with a direct bandgap value of around 1.8 eV. Cu2O NPs exhibited activity for CO2 photoreduction, whose efficiency was optimized by an orthogonal Taguchi L9 design. The factors studied were catalyst loading, air flow, and temperature. During the use of Cu2O NPs in the CO2 photoreduction HCOOH was identified as the main product, with an optimized production of 103.4 µmol h− 1 under visible light. Also, it was demonstrated the photocatalytic activity of the Cu2O NPs for H2 evolution by water splitting. Graphical PubDate: 2024-06-06 DOI: 10.1007/s40974-024-00331-x
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Abstract: Abstract This study examines the intricate dynamics between oil prices and renewable energy investments in Italy during the initial phase of the CoronaVirus Disease 2019 pandemic, a period characterized by significant economic and social upheaval. Utilizing advanced empirical techniques, such as Partial Wavelet Coherency analysis, Time-Varying Granger Causality, and Robinson Log-Periodogram tests, as well as Machine Learning (ML) regressions, this research uncovers nuanced insights into the interplay between oil prices and renewable energy series including biomass, solar, hydro, wind, and geothermal. Key findings indicate a predominant in-phase relationship with oil prices leading most renewable energy series, and unidirectional causality from renewables to oil prices in several instances, highlighting the potential influence of renewable energy on oil market dynamics. In robustness checks, ML models further elucidate the impact, with solar, hydro, and geothermal sources showing significant importance scores. These insights are critical for policymakers and stakeholders aiming to enhance energy security and transition towards sustainable energy sources amidst global crises. PubDate: 2024-06-03 DOI: 10.1007/s40974-024-00325-9
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Abstract: Abstract As a potential substitute to conventional concrete, slag-based geopolymer concrete can be a promising material towards green and low carbon building approach. However, the lack of understanding of its performance subjected to sulphate environment can prohibit its use to some extent. This study examines the properties of conventional concrete exposed to a severe sulphate environment in comparison with slag-based geopolymer (SGPC). Plain cement concrete (PCC) also known as conventional concrete was cast using ordinary Portland Cement (OPC) as a binder. The durability of both types of concrete was examined by immersing test specimens in sulphate solutions (for varied salt concentrations of 2 and 4 g/l) for different curing ages up to a year. The performance of both types of concrete was studied for both mechanical and durability properties. Mechanical properties included compressive, tensile and flexural strengths (FS), while durability consisted of sorptivity, chloride diffusion, corrosion, EDS and SEM studies. The outcomes of this study revealed that the compressive (CS) and split tensile strengths (STS) of both OPC and SGPC decreased with the increase in magnesium sulphate salt concentrations and curing age. After being exposed to a 4% sulphate solution for 365 days, a decrease in the compressive strength was observed by 36.53% in SGPC and 55.97% in OPC, and a similar trend was found for the FS and STS. Rapid chloride permeability (RCPT) and sorptivity test results showed an increased diffusion with age and thus supported the findings of the compressive strength. Micro-structural properties were also studied, and observations showed that the formation of Sodium alumino-silicate hydrate (N–A–S–H) and Calcium alumino-silicate hydrate (C–A–S–H) was more obvious with the curing age in SGPC. At the same time, C–S–H gel formation decreased in conventional concrete with an increase in sulphate salt concentration. The cumulative effect of all these factors led to a much higher corrosion rate of rebars embedded in conventional concrete than in SGPC. Therefore, slag-based geopolymer concrete performed better than conventional concrete in an aggressive sulphate environment for all curing periods. PubDate: 2024-06-01 DOI: 10.1007/s40974-023-00300-w
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Abstract: Abstract Fully considering income inequality (ICIE) and its potential environmental effects can help achieve the goal of reducing carbon emissions. Based on this, to effectively explore the nexus between ICIE and carbon dioxide (CO2) emissions, we first deduce the theoretical framework and then empirically check the spatial impact of ICIE on greenhouse effect based on a global dataset from 1995 to 2016. In addition, this study also conducts the regional heterogeneous analysis and further detects the causal mediating route (i.e., indirect route) between variables. The findings suggest that: (i) Rising ICIE affects CO2 emissions positively; in other words, narrowing income gap can effectively mitigate greenhouse effect across the globe; (ii) In countries with high gross domestic product (GDP) level, expanded ICIE will exacerbate the greenhouse effect, while in low-GDP countries, ICIE is negatively correlated with CO2 emissions; and (iii) ICIE can indirectly influence greenhouse effect through substantial economic and technical routes, while the composition route is insignificant. Finally, this paper highlights policy suggestions for carbon reduction by adjusting income distribution, formulating targeted strategies in various countries, and promoting technical innovation. PubDate: 2024-06-01 DOI: 10.1007/s40974-023-00315-3
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Abstract: Abstract Since the construction industry is one of the major sectors responsible for the overexploitation of natural resources and the production of greenhouse gases, there is an urgent need to adopt a sustainable and environmental friendly approach to mitigate climate degradation. Research has explored the potential of recycled aggregate (RA) as a viable alternative to natural aggregate in concrete production. Currently, several treatment methods are being employed to enhance the efficient incorporation of RA into concrete, aiming to address this issue. However, the effective utilization of RA in place of NA remains uncommon. In this study, an effort has been made to develop a low-carbon recycled aggregate concrete by utilizing 100% carbonation treated recycled coarse concrete aggregate (CRCCA) in place of natural coarse aggregate (NCA) and alccofine as mineral admixture. A comprehensive analysis was performed, comparing the properties of CRCCA to those of untreated recycled coarse concrete aggregate. This analysis covered changes in weight, bulk density, water absorption, crushing value, and microstructure. Furthermore, five different concrete mixes were prepared, each varying in the proportion of natural coarse aggregate (NCA), untreated RCCA, and CRCCA. These mixes also incorporated alccofine as a mineral admixture. The evaluation process involved assessing the effectiveness of carbonation treatment and alccofine addition through tests on the workability, water absorption, density, and compressive strength of the concrete mixes. The study demonstrated that carbonation treatment of RCCA resulted in substantial improvements in crushing value and water absorption of CRCCA, alongside enhanced workability, reduced water absorption, and increased density in CRCCA concrete. Moreover, CRCCA concrete exhibited notable compressive strength gains at both 28 and 90 days compared to untreated RCCA concrete. Furthermore, the use of CRCCA and alccofine contributed to reducing GHG emissions associated with cement production, emphasizing the environmentally friendly attributes of this low-carbon concrete formulation. PubDate: 2024-06-01 DOI: 10.1007/s40974-023-00299-0
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Abstract: Abstract Integration of photovoltaic modules into greenhouse roofs is a novel and intriguing method. The cost of products grown in greenhouses is particularly high because of their high energy consumption for heating and cooling, and at the same time the increase in demand for available land, increasing its cost and creating spatial issues, the integration of photovoltaics on the roof of greenhouses is a highly viable solution. Simultaneously, the use of solar radiation is critical to maintain optimal crop development, while also being a renewable energy source. However, photovoltaics reduce the incoming solar radiation in the greenhouse, due to their shade. Shading can be either beneficial for the crops or not, depending on the crop type, thus it is vital to find the shading caused by photovoltaics both temporally and spatially. In this study, a model calculating the shading in a greenhouse due to roof-integrated photovoltaics is developed, based on the Sun position, the geometry of both the greenhouse and of the roof-integrated photovoltaics and their position on the greenhouse roof. Calculating the coefficient of variation of radiation data, for the shaded and unshaded areas using the proposed algorithm, it was found the coefficient of variation for the shaded areas is lower than that for the unshaded areas for a least 76% of the time. Also, the radiation values under the shaded area are more uniform. The proposed model is a tool for PV designers, operators, and owners, in order to optimize the potential of their solar panel installations. PubDate: 2024-06-01 DOI: 10.1007/s40974-023-00306-4
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Abstract: Ordinary Portland cement is a construction material that is widely utilized all over the world. Aside from deforestation and fossil fuel combustion, the cement manufacturing industry contributes significantly to carbon dioxide emissions, which questions the viability of using Portland cement (PC) in concrete construction. Therefore, finding an alternative to the existing one becomes crucial. Geopolymer concrete (GPC) is a relatively advanced and innovative form of concrete that can be prepared without the use of PC. The present research emphasizes the assessment of the strength and durability of GPC containing fly ash (FA), ground-granulated blast furnace slag (GGBS), and dolomite as binders. The control mix consists entirely of FA as a binder, while five additional mixes are prepared by replacing 20% FA with either GGBS or dolomite or in varying combinations. The slump test is used to assess the workability of the concrete. Key mechanical properties such as compressive strength and split tensile strength are also determined, along with non-destructive tests including ultrasonic pulse velocity and electrical resistivity. To assess GPC durability, initial surface absorption and capillary suction absorption tests are conducted at various curing ages. The findings demonstrate that incorporating GGBS and dolomite into FA-based GPC results in notable improvements in both strength and durability. However, this enhancement reduces the workability compared to the control mix. The addition of GGBS and dolomite yields remarkable enhancements in compressive strength, showing an impressive surge of up to 67%, and a substantial reduction in initial surface absorption, up to 65%, as compared to the control mix over a period of 56 days. The most favorable results in terms of both strength and durability are achieved when FA is replaced with 20% of GGBS. Also, the mix containing a combination of 10% GGBS and 10% dolomite yields comparable results to the mix with 20% GGBS, making it a cost-effective alternative. Graphical abstract PubDate: 2024-06-01 DOI: 10.1007/s40974-023-00309-1
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Abstract: Abstract This study assessed the effect of implementing multiple circuit connections and operating parameters (hydraulic retention time (HRT), organic loading rate (OLR), and external resistance) on the improvement of up-flow constructed wetland-microbial fuel cell (UFCW-MFC) in treating the mixed azo dyes wastewater and bioelectricity generation. The multiple-circuits UFCW-MFC facilitated the organic substrate degradation, which improved the removal efficiency of dyes by 8% and COD by 7%, as well as power production by 6.5 times, compared to single-circuit UFCW-MFC. The prolonged HRT from 1 to 3 d extended the interaction time between the pollutants and microbes, which further enhanced the removal efficiency of dyes by 9% and COD by 6%. The decrease in power generation by 1.3 times could be ascribed to the lower OLR at a higher HRT (0.864–0.288 g COD/d when HRT extended from 1 to 3 d) as the utilization of electrons was prioritized for decolorization compared to bioelectricity generation. The increase in OLR (0.288 to 0.754 g COD/d) with the same HRT (3 d) exhibited an improvement of 4% in decolorization and 2.4 times in power generation. This could be attributed to more electron production from the higher COD removal. The lower external resistance benefited the UFCW-MFC performance, where the best performance was obtained at 200 Ω as it approached the internal resistance (150 Ω). PubDate: 2024-06-01 DOI: 10.1007/s40974-023-00314-4
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Abstract: Abstract This study utilizes natural dye extracts from inthanin and mahogany, along with synthesized TiO2QD as the photoanode, to increase the photoconversion productivity and performance of DSSC. TiO2QD was produced using the sol-gel technique. Titanium (IV) isopropoxide (TTIP) and isopropanol underwent hydrolysis with constant stirring for 48 h. The TiO2QD was characterized using SEM. The structure and size of TiO2QD were determined using SEM analysis, which showed an average crystallite size ranging from 5 to 8.5 nm. A UV-Vis spectrophotometer determined the absorption wavelength of the dye extract. The efficiency and performance of DSSCs enhanced with synthetic TiO2QD were evaluated by current-voltage (J-V) measurements. The DSSC using mahogany dye extract demonstrated superior photoconversion efficiency, achieving a Voc (open-circuit voltage) of 0.878 V, Isc (short-circuit current) of 0.775 mA/cm2, FF (fill factor) of 83%, and η (overall efficiency) of 0.967%. In comparison, the inthanin dye extract achieved an overall efficiency of 0.783%. The longstanding performance of solar cells, which was improved using a TiO2QD photoanode and natural dye extracts, was evaluated using a stability test. The test evaluated the long-term performance, stability, and durability of solar cells. Utilizing natural dye extracts and TiO2QD holds great potential for improving the efficiency and performance of DSSCs. The objective of this study is to upgrade the advancement of DSSC technology by investigating the utilization of its components and their long-term durability. PubDate: 2024-05-27 DOI: 10.1007/s40974-024-00326-8
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Abstract: Abstract The Indonesian government is implementing the national biomass co-firing program to rapidly reduce greenhouse gas emissions in power plants on a significant scale in a short time. Unfortunately, the environmental impacts of this program, under actual conditions, have not yet been thoroughly assessed and evaluated. This study involved collaborating with a coal-fired power plant (CFPP) operator in Banten to study actual conditions using life cycle assessment analysis with a cradle-to-gate system. The product category rules were used to determine the environmental impact category. Operational data was used from two coal-fired power plant units, each operating coal-firing and sawdust co-firing with a co-firing ratio (CR) of 11.80%. The results of comparing both units revealed a reduction in the impact of global warming potential by − 19.83%, acidification potential by − 27.67%, eutrophication potential by − 10.85%, photochemical ozone formation potential by − 28.73%, abiotic depletion potential (ADP) fossil by − 7.35%, water scarcity by − 3.05%. However, there were increases in ADP elements by 69.66%, ozone depletion potential (ODP) by 36.30%, and land use (LU) by 1926.74%. A sensitivity analysis was conducted to analyze the environmental impact of increasing the CR from 11.80 to 20.0%, where the study results showed the highest increase in LU. A scenario analysis was employed to estimate the environmental impact of fuels, where the results were sequential as follows: coal, rice husk pellets, sawdust, and woodchips co-firing, with values of 1.23, 1.03, 0.99, and 0.98 kg-CO2-eq, respectively. Based on the actual conditions, this study's results provide insight into the environmental impact of biomass co-firing operations. It is expected that the results will be used as a reference for developing a strategy to maintain the sustainability of this program for the long term. PubDate: 2024-05-27 DOI: 10.1007/s40974-024-00329-5
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Abstract: Abstract The integration of advanced technologies into manufacturing processes is critical for addressing the complexities of modern industrial environments. In particular, the realm of human–robot interaction (HRI) faces the challenge of ensuring that human operators can effectively collaborate with increasingly sophisticated robotic systems. Traditional interfaces often fall short of providing the intuitive, real-time interaction necessary for optimal performance and safety. To address this issue, we introduce a novel system that combines digital twin (DT) technology with augmented reality (AR) to enhance HRI in manufacturing settings. The proposed AR-based DT system creates a dynamic virtual model of robot operations, offering an immersive interface that overlays crucial information onto the user’s field of vision. This approach aims to bridge the gap between human operators and robotic systems, improving spatial awareness, task guidance, and decision-making processes. Our system is designed to operate at three distinct levels of DT functionality: the virtual twin for in-situ monitoring, the hybrid twin for intuitive interaction, and the cognitive twin for optimized operation. By leveraging these levels, the system provides a comprehensive solution that ranges from basic visualization to advanced predictive analytics. The effectiveness of the AR-based DT system is demonstrated through a human-centric user study conducted in manufacturing scenarios. The results show a significant reduction in operational time and errors, alongside an enhancement of the overall user experience. These findings confirm the potential of our system to transform HRI by providing a safer, more efficient, and more adaptable manufacturing environment. Our research contributes to the advancement of smart manufacturing by evidencing the synergistic benefits of integrating DT and AR into HRI. PubDate: 2024-05-25 DOI: 10.1007/s40974-024-00327-7
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Abstract: Abstract This study performed the Indonesian EEIO model development by using the Indonesian economic I/O table and Indonesian energy balance. This study also emphasized the importance of considering Scopes 1, 2, and 3 CO2 emissions. Based on this analysis, Indonesia’s total embodied CO2 emissions in 2016 from 185 sectors were 533 million tons, mostly driven by fossil fuel usage. Considering the economic activities and transactions, sectors like ‘services’, ‘mining’, and ‘metal & heavy industries’ stand out due to their high emission intensity per unit of output. The CO2 emissions intensity for ‘services’, ‘metal & heavy industries’, and ‘mining’ were 2,306, 605.68, and 580.71 kg CO2/million IDR, respectively. Meanwhile, based on annual total CO2 emissions, ‘services’, ‘energy’, and ‘building, road & construction’ sectors contribute the most to the country’s total CO2 emissions. They emitted 113, 90, and 89 million tons of life cycle CO2 emissions based on EEIO analysis. Finally, the Indonesian EEIO framework established in this study offers a valuable tool for policymakers to mitigate climate change while pursuing economic goals. PubDate: 2024-05-23 DOI: 10.1007/s40974-024-00328-6
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Abstract: Abstract Building materials and their centennial metabolic patterns offer a perspective from which to understand a city’s past, present, and future, but existing studies mostly focus on short-term metabolism. By investigating Hong Kong’s building material stock and flow (or building material metabolism, BMM), this study aims to understand the centennial evolution of a city with a rich history, international status, advanced economy, and close connection with the world. We quantify BMM using the stock-driven approach, derive flows based on stock changes, and interpret its patterns based on temporal and correlation (with socioeconomic factors) analyses, respectively. We find that, by the mid-2030s, total building material stock may saturate at around 417.93 Mt with a rough inflow–outflow balance of 13.29 Mt/year, but stock per capita has plateaued at about 53.67 t/capita since the mid-2010s. The long-term changes in both building material stock and flow comply with an S-curve, shaped mainly by industrialization and subsequent deindustrialization but also fluctuating due to key socioeconomic events. Based on a stock productivity comparison, we also find that Hong Kong has achieved and sustained an advanced economy via a lower BMM requirement than other typical developed economies, indicating a more material-efficient development pathway. These findings not only provide insights into the centennial BMM trajectory and its interaction with socioeconomic factors, but also offer historical experience and sustainable development implications for developing economies, especially those in mainland China and throughout Asia. PubDate: 2024-04-17 DOI: 10.1007/s40974-024-00322-y
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Abstract: Abstract In line with Industry 5.0 principles, energy systems form a vital part of sustainable smart manufacturing systems. As an integral component of energy systems, the importance of Lithium-Ion (Li-ion) batteries cannot be overstated. Accurately predicting the remaining useful life (RUL) of these batteries is a paramount undertaking, as it impacts the overall reliability and sustainably of the smart manufacturing systems. Despite various existing methods have achieved good results, their applicability is limited due to the data isolation and data silos. To address the aforementioned challenges, this paper presents a novel federated learning (FL)-based approach that predicts the RUL of Li-ion batteries, thereby contributing to the sustainability of smart manufacturing. Firstly, a denoising recursive autoencoder-based transformer (DRAT) model is devised, focusing on extracting robust and latent features for RUL prediction under various conditions. Secondly, we propose an adaptive DRAT-based federated RUL framework (Fed-DRAT) for the collaborative modeling of Li-ion batteries RUL prediction for different energy systems. Specifically, an innovative adaptive model aggregation strategy is developed to equalize the contribution weights of different participating systems and improve model performance. Our extensive experiments with Li-ion batteries datasets indicate that our proposed DRAT significantly outperforms existing methods and demonstrates superior performance in different scenarios. PubDate: 2024-04-17 DOI: 10.1007/s40974-024-00323-x