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43 pages, 1872 KiB  
Review
From Waste to Wealth: A Circular Economy Approach to the Sustainable Recovery of Rare Earth Elements and Battery Metals from Mine Tailings
by Mohammed Omar Sahed Chowdhury and Deniz Talan
Separations 2025, 12(2), 52; https://doi.org/10.3390/separations12020052 - 14 Feb 2025
Abstract
The increasing global demand for critical minerals, driven by rapid population growth and the widespread adoption of low-carbon technologies, electric vehicles, and clean energy systems, highlights the urgent need for sustainable resource management. Mine tailings, traditionally considered waste, are now being recognized as [...] Read more.
The increasing global demand for critical minerals, driven by rapid population growth and the widespread adoption of low-carbon technologies, electric vehicles, and clean energy systems, highlights the urgent need for sustainable resource management. Mine tailings, traditionally considered waste, are now being recognized as valuable secondary sources for mineral recovery. This paper compiles a comprehensive review of the four short- and mid-term critical minerals (lithium, cobalt, nickel, and rare earth elements) and provides insights regarding their recovery with a focus on the latest technological advancements. By exploring key innovations in separation processes, the review demonstrates how these technologies are addressing supply chain bottlenecks while simultaneously reducing the environmental footprint of mining operations. The paper also advocates for a holistic approach to mine waste management, integrating mineral recovery with environmental remediation. It emphasizes the dual benefits of recovering valuable resources while purifying contaminated water and mitigating pollution risks. The proposed circular economy model suggests a sustainable blueprint for managing mine tailings, emphasizing resource reuse, waste reduction, and economic viability. Full article
15 pages, 238 KiB  
Article
A Manufacturing Industry Perspective on Pandemic-Induced Supply Chain Disruptions
by Baomin Qi, Emma McCauley, Katherine Baxter, Mark Ching-Pong Poo and Yui-yip Lau
Businesses 2025, 5(1), 8; https://doi.org/10.3390/businesses5010008 - 14 Feb 2025
Abstract
This study explores the impact of COVID-19-related supply chain disruptions on manufacturing firms, focusing on external risks: demand, environmental, and supply. Our literature review reveals the general lack of comprehensive disruption plans and exposes the vulnerabilities in manufacturing firms with limited research addressing [...] Read more.
This study explores the impact of COVID-19-related supply chain disruptions on manufacturing firms, focusing on external risks: demand, environmental, and supply. Our literature review reveals the general lack of comprehensive disruption plans and exposes the vulnerabilities in manufacturing firms with limited research addressing this issue. By adopting an interpretive research philosophy and a qualitative, inductive approach, our research delves into the operational challenges and adaptations implemented in the manufacturing sector during the pandemic through case studies. The findings reveal that COVID-19 significantly increased risks, causing demand surges, logistical disruptions, extended lead times, and labour shortages due to lockdowns, necessitating strategic shifts towards localised and digital supply chains in the manufacturing sector. Our study not only enriches the supply chain literature by detailing the pandemic’s effects and emphasising the need for robust disruption plans for enhanced resilience but also offers new insights into managing supply chain disruptions in crises, highlighting the necessity of strategic adaptations for future crisis preparedness across various industries. Full article
25 pages, 13734 KiB  
Article
Equity-Oriented Multi-Objective Optimization Allocation Strategies for Urban Water Resources
by Shicheng Zhou, Dong Wang, Zhen Liu, Yongqiang Ma and Xin Liu
Water 2025, 17(4), 557; https://doi.org/10.3390/w17040557 - 14 Feb 2025
Abstract
Urban water usage spans diverse sectors, requiring effective management strategies to address increasing demand, limited supplies, and sector-specific needs. In this study, a multi-objective urban water resource allocation model is proposed to balance economic, ecological, and social benefits, focusing on social fairness. The [...] Read more.
Urban water usage spans diverse sectors, requiring effective management strategies to address increasing demand, limited supplies, and sector-specific needs. In this study, a multi-objective urban water resource allocation model is proposed to balance economic, ecological, and social benefits, focusing on social fairness. The model considers water availability, demand diversity, and environmental factors for optimized resource allocation. An improved zebra optimization algorithm-based multi-objective evolutionary algorithm (ZOA-MOEA/D) is developed, integrating zebra optimization with a decomposition-based approach to overcome the traditional methods’ limitations, improving solution diversity and convergence. ZOA-MOEA/D consistently outperforms the NSGA-II, MOPSO, and MOEA/D algorithms in solution distribution, convergence, quality, and diversity across multiple test scenarios. By applying the model to Ningbo, China, key trade-offs between economic growth, social fairness, living standards, and ecological protection are revealed. These findings provide useful insights into urban water resource management, offering a flexible framework for balancing multiple objectives and supporting sustainable development. Despite some limitations, the approach can contribute to the ongoing development of urban water resources. Full article
(This article belongs to the Section Urban Water Management)
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24 pages, 2089 KiB  
Article
Planning and Economic Feasibility of Electric-Connected Automated Microtransit First/Last Mile Service Under Uncertainty
by Ata M. Khan
Future Transp. 2025, 5(1), 19; https://doi.org/10.3390/futuretransp5010019 - 14 Feb 2025
Viewed by 101
Abstract
Electric-connected automated vehicle (CAV) shuttles, as a part of the sustainable microtransit system, have the potential to fill public transit service gaps. Following technology and traveler acceptance tests that are underway around the world, mass-produced CAVs will be considered for shared mobility service, [...] Read more.
Electric-connected automated vehicle (CAV) shuttles, as a part of the sustainable microtransit system, have the potential to fill public transit service gaps. Following technology and traveler acceptance tests that are underway around the world, mass-produced CAVs will be considered for shared mobility service, including “first/last mile” travel between public transit hub stations and medical campuses or other activity centres. Thus, there is a need for increased knowledge on treating risk in such applications. This paper covers the planning and economic feasibility of an advanced technology level 4 automated vehicle-based microtransit system, considering uncertain service and economic feasibility factors. The methods used are advanced for addressing uncertainties in travel demand, service factors, and the economic feasibility of investments by public and private sector entities. Specifically, a probability-based macro simulation approach is used to treat demand and supply-side service factors as stochastic, and it is adapted for risk analysis in financial decision-making. The effects of uncertain life-cycle costs on fares and the rate-of-return are described. Results are favourable regarding the technical and economic feasibility of advanced technology-based microtransit first/last mile service. The findings reported here are a contribution to knowledge on the feasibility of implementing CAV-based first/last mile, and other microtransit services, under uncertainty. Full article
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18 pages, 3098 KiB  
Article
A Lightweight Accountable Parallel Blockchain Architecture Based on Redactable Blockchain for Agri-Food Traceability
by Feng Chen, Chunjiang Zhao, Xinting Yang, Na Luo and Chuanheng Sun
Foods 2025, 14(4), 623; https://doi.org/10.3390/foods14040623 - 13 Feb 2025
Viewed by 255
Abstract
Agri-food safety issues have received widespread attention globally. The emergence of blockchain technology (BCT) effectively addresses trust issues in the agri-food supply chain traceability system (AFSCTS). However, the append-only feature of blockchain has led to continuous linear data growth in BCT-based AFSCTSs, which [...] Read more.
Agri-food safety issues have received widespread attention globally. The emergence of blockchain technology (BCT) effectively addresses trust issues in the agri-food supply chain traceability system (AFSCTS). However, the append-only feature of blockchain has led to continuous linear data growth in BCT-based AFSCTSs, which increases the equipment requirements and has become a bottleneck for BCT-based AFSCTS applications. The storage capacity required by BCT-based AFSCTSs can be effectively reduced by deleting expired data, thereby reducing the storage pressure on blockchain devices and lowering the device requirements. In this paper, we propose an AFSCTS architecture that incorporates redactable blockchain and InterPlanetary file system (IPFS) technologies to achieve traceability with low storage pressure, using the wheat supply chain as a proof of concept. Firstly, the key links were analyzed in agri-food traceability and the demand was proposed for agri-food blockchain traceability based on the timeliness of traceability data. Secondly, a lightweight accountable parallel blockchain architecture called LAP-chain is proposed. This architecture utilizes redactable blockchain technology to offload expired agri-food traceability data to IPFS, thereby reducing the storage pressure on blockchain devices and ensuring data accountability through IPFS. Finally, we evaluate the correctness, collision resistance, and storage performance of the LAP-chain built on the Ethereum private chain. The results show that when expired agri-food traceability data are permanently retained, the storage capacity of the proposed architecture is only 52.38% of that of the traditional blockchain traceability architecture, after running continuously for 36 months. When traceability data of expired agri-food are deleted in accordance with the food laws and regulations of various countries, the storage capacity of the proposed architecture can be reduced from a linear level to a constant level compared to the traditional blockchain traceability architecture. The proposed architecture has the potential to contribute to improving the safety and quality of agri-food. Full article
(This article belongs to the Section Food Systems)
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22 pages, 12535 KiB  
Article
Numerical Modelling Assessment of the Impact of Hydrogen on the Energy and Environmental Performance of a Car Using Dual Fuel (Gasoline–Hydrogen)
by Saugirdas Pukalskas, Tadas Vipartas, Alfredas Rimkus, Donatas Kriaučiūnas, Justas Žaglinskis, Saulius Stravinskas, Andrius Ušinskas, Romualdas Juknelevičius, Gabrielius Mejeras, Vidas Žuraulis, Vilius Mejeras and Aleksas Narkevičius
Appl. Sci. 2025, 15(4), 1939; https://doi.org/10.3390/app15041939 - 13 Feb 2025
Viewed by 240
Abstract
The utilization of “green” hydrogen in transportation areas gives rise to production- and supply infrastructure-related challenges; therefore, its wider application in automotive transport would lead to higher demand with cost reduction and a faster expansion of the hydrogen refuelling network. This study presents [...] Read more.
The utilization of “green” hydrogen in transportation areas gives rise to production- and supply infrastructure-related challenges; therefore, its wider application in automotive transport would lead to higher demand with cost reduction and a faster expansion of the hydrogen refuelling network. This study presents energy and environmental performance indicators analyses of a Nissan Qashqai J10 engine during the Worldwide Harmonised Light Vehicles Test Cycle (WLTC), replacing conventional fossil gasoline with dual-fuel (D-F) gasoline and hydrogen. Numerical modelling was conducted using AVL Cruise™ (Version R2022.2) software, utilizing the torque, fuel consumption, and environmental performance data of the HR16DE engine obtained through experimental testing across a wide range of loads and speeds on an engine test bench. The experimental investigation was carried out in two stages: using pure gasoline (G100); injecting a hydrogen additive into the intake air, constituting 5% of the gasoline mass (G95H5). Following similar stages, numerical modelling was conducted using the vehicle’s technical specifications to calculate engine load and speed throughout the WLTC range. Instant fuel consumption and pollutant emissions (CO, CH, NOx) were determined for various driving modes using experimental data maps. CO2 emissions were calculated considering fuel composition and consumption. By integrating the instant values, the total and specific fuel consumption and emissions were calculated. As a result, this study identified the effect of a 5% hydrogen additive in improving engine energy efficiency, reducing incomplete combustion products and lowering greenhouse gas (CO2) emissions under various driving modes. Finally, the results were compared with the requirements of EU standards. Full article
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15 pages, 1906 KiB  
Article
China’s Urban–Rural and Trade Inequality in Water Footprint
by Gang Liu and Yonghua Li
Water 2025, 17(4), 531; https://doi.org/10.3390/w17040531 - 13 Feb 2025
Viewed by 183
Abstract
The economic inequalities impede the equal distribution of water among various household groups, potentially leading to inequal access to this vital resource. By integrating a multi-regional input–output model with household expenditure, we investigate the water footprint (WF) for ten income groups in each [...] Read more.
The economic inequalities impede the equal distribution of water among various household groups, potentially leading to inequal access to this vital resource. By integrating a multi-regional input–output model with household expenditure, we investigate the water footprint (WF) for ten income groups in each of the provinces and evaluate water inequality among regions, households, and expenditure categories comprehensively. Our findings reveal significant disparities in water footprints, with urban households exhibiting nearly three times the WF of rural residents. Wealthier eastern provinces show higher per capita consumption-based WFs compared to the less developed western regions. The interregional trade exacerbates water inequality because water-intensive goods are produced in less developed regions and are being consumed in more developed provinces. This study underscores the importance of targeted policies to address water inequality, achieve sustainable water management, and promote equitable water use in the face of increasing water demand and supply imbalances. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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15 pages, 2260 KiB  
Article
The Application of Fourier Transform Infrared Spectroscopy and Chemometrics in Identifying Signatures for Sheep’s Milk Authentication
by Robert Duliński, Marek Gancarz, Nataliya Shakhovska and Łukasz Byczyński
Processes 2025, 13(2), 518; https://doi.org/10.3390/pr13020518 - 12 Feb 2025
Viewed by 464
Abstract
This study explores the application of Fourier transform infrared (FTIR) spectroscopy combined with chemometric and machine learning techniques for authenticating sheep’s milk and distinguishing it from cow’s milk. The demand for accurate authentication methods is driven by the high production costs of sheep’s [...] Read more.
This study explores the application of Fourier transform infrared (FTIR) spectroscopy combined with chemometric and machine learning techniques for authenticating sheep’s milk and distinguishing it from cow’s milk. The demand for accurate authentication methods is driven by the high production costs of sheep’s milk and the prevalent issue of adulteration with cow’s milk, which can have economic, health, and ethical implications. Our research utilizes exploratory analysis, regression, and classification tasks on spectral data to identify characteristic spectral signatures and physicochemical parameters for sheep’s milk. Key methods included the application of decision trees, random forests, and k-nearest neighbors (KNN), with the random forest model showing the highest predictive accuracy (R2 of 0.9801). Principal Component Analysis (PCA) and analysis of variance (ANOVA) revealed significant spectral and compositional differences, particularly in fat content and wavelengths responsible for amide I and II bands (1454 nm and 1550 nm) correlated with the conformational characteristics of the proteins, with sheep’s milk exhibiting higher values than cow’s milk. These findings indicate the potential of FTIR spectroscopy as a reliable tool for milk authentication. Currently, digitalization within the milk production chain is limited, particularly in the case of regional dairy products. The introduction of integrated photonics, machine learning, and, in the future, telemetry systems would enable dairy farmers to optimize their operations and ensure the origin and quality of the milk supplied to milk producers. Full article
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20 pages, 2131 KiB  
Article
Shale Gas Transition in China: Evidence Based on System Dynamics Model for Production Prediction
by Yingchao Chen and Yang Zhang
Energies 2025, 18(4), 878; https://doi.org/10.3390/en18040878 - 12 Feb 2025
Viewed by 385
Abstract
Abstract: As a clean energy source, shale gas plays a crucial role in mitigating the supply–demand imbalance of natural gas and in facilitating the transition to a low-carbon economy. This study employs a system dynamics model to forecast future production trends in shale [...] Read more.
Abstract: As a clean energy source, shale gas plays a crucial role in mitigating the supply–demand imbalance of natural gas and in facilitating the transition to a low-carbon economy. This study employs a system dynamics model to forecast future production trends in shale gas in China, analyze its implications for the natural gas supply–demand structure, and explore pathways for sustainable development. Firstly, by integrating the characteristics of China’s shale gas resources, market dynamics, and policy frameworks, the key factors influencing production are identified, and their interrelationships are systematically analyzed. Subsequently, a causal loop diagram is constructed using the VENSIM software(VENSIM PLE 9.3.5 x64), a set of representative variables is selected, and the logical relationships among these variables are established through a multivariate statistical analysis, culminating in the development of a production forecasting model for China’s shale gas (stock and flow diagram). Finally, based on parameter assumptions, this study predicts the production trends in shale gas in China under multiple scenarios. The forecasting results reveal that China’s shale gas production is expected to grow at an average annual rate of 3.32% to 8.02%, with production under the reference scenario projected to reach 724.22 × 108 m3 by 2040. However, the growth of shale gas production over the next two decades remains limited, accounting for a maximum of 12.07% of the total natural gas consumption, underscoring its transitional role in the low-carbon transformation. To address these challenges, this study proposes four policy recommendations: (1) prioritize the development of shallow, high-quality gas-bearing blocks while gradually transitioning to deeper formations; (2) intensify technological innovation in deep shale gas extraction to enhance recovery rates and mitigate production decline rates; (3) implement flexible production subsidies and moderately increase natural gas sales prices to incentivize production and optimize resource allocation; and (4) strengthen ecological conservation and improve water resource management to ensure the sustainable development of shale gas. Full article
(This article belongs to the Special Issue Energy and Environmental Economics for a Sustainable Future)
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17 pages, 3431 KiB  
Article
Identification of Key Drivers and Path Transmission of Carbon Emissions from Prefabricated Buildings: Based on System Dynamics
by Jing Cheng, Liping Li, Rui Zhang, Liang Tian and Yanhui Liu
Buildings 2025, 15(4), 562; https://doi.org/10.3390/buildings15040562 - 12 Feb 2025
Viewed by 296
Abstract
In order to achieve the ‘dual carbon’ goal, based on the DEMATEL-ISM model, 19 main factors affecting the carbon emissions of prefabricated buildings were preliminarily identified from five dimensions, including government decision-making, technical environment, social economy, energy consumption, and market supply and demand. [...] Read more.
In order to achieve the ‘dual carbon’ goal, based on the DEMATEL-ISM model, 19 main factors affecting the carbon emissions of prefabricated buildings were preliminarily identified from five dimensions, including government decision-making, technical environment, social economy, energy consumption, and market supply and demand. The logical relationship, hierarchical structure, and importance between the factors were clarified, and finally, the four influencing factors were determined. According to the causal feedback relationship between the above four factors in the system flow from 2010 to 2030, eight different control scenarios were proposed, and the impact and change trend of each control scenario on the reduction of carbon emissions of prefabricated buildings were analyzed. The research results show that the key factors for carbon emissions from prefabricated buildings include 14 outcome factors and 5 cause factors, and that the causal factors are key drivers. They are the standard specification system, the incremental cost of prefabricated buildings, investment in scientific and technological innovation, and the level of prefabricated integrated technology. The key factors were structurally stratified from the essential level to the superficial level in four tiers. The first tier of the standard specification system is the surface causal factor affecting carbon emissions from prefabricated buildings. Investment in scientific and technological innovation in the second and third tiers, and the level of prefabricated integrated technology are the causes of the transition. The incremental cost of prefabricated buildings at the fourth level is the essential causal factor. Finally, based on the data related to carbon emissions of prefabricated buildings in Yunnan, China, and verified in eight regulatory scenarios, the results of the study can effectively reveal the carbon emission reduction transmission path of prefabricated buildings, which can provide a reference for the development of prefabricated buildings and carbon emission reduction strategies. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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28 pages, 4142 KiB  
Article
IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration
by Sami Binyamin and Sami Ben Slama
AI 2025, 6(2), 34; https://doi.org/10.3390/ai6020034 - 12 Feb 2025
Viewed by 389
Abstract
The integration of renewable energy sources and electric vehicles has become a focal point for industries and academia due to its profound economic, environmental, and technological implications. These developments require the development of a robust intelligent home energy management system (IHEMS) to optimize [...] Read more.
The integration of renewable energy sources and electric vehicles has become a focal point for industries and academia due to its profound economic, environmental, and technological implications. These developments require the development of a robust intelligent home energy management system (IHEMS) to optimize energy utilization, enhance transaction security, and ensure grid stability. For this reason, this paper develops an IntelliGrid AI, an advanced system that integrates blockchain technology, deep learning (DL), and dual-energy transmission capabilities—vehicle to home (V2H) and home to vehicle (H2V). The proposed approach can dynamically optimize household energy flows, deploying real-time data and adaptive algorithms to balance energy demand and supply. Blockchain technology ensures the security and integrity of energy transactions while facilitating decentralized peer-to-peer (P2P) energy trading. The core of IntelliGrid AI is an advanced Q-learning algorithm that intelligently allocates energy resources. V2H enables electric vehicles to power households during peak periods, reducing the strain on the grid. Conversely, H2V technology facilitates the efficient charging of electric cars during peak hours, contributing to grid stability and efficient energy utilization. Case studies conducted in Tunisia validate the system’s performance, showing a 20% reduction in energy costs and significant improvements in transaction efficiency. These results highlight the practical benefits of integrating V2H and H2V technologies into innovative energy management frameworks. Full article
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23 pages, 5276 KiB  
Article
How the Topology of the Mitochondrial Inner Membrane Modulates ATP Production
by Raquel Adams, Nasrin Afzal, Mohsin Saleet Jafri and Carmen A. Mannella
Cells 2025, 14(4), 257; https://doi.org/10.3390/cells14040257 - 11 Feb 2025
Viewed by 272
Abstract
Cells in heart muscle need to generate ATP at or near peak capacity to meet their energy demands. Over 90% of this ATP comes from mitochondria, strategically located near myofibrils and densely packed with cristae to concentrate ATP generation per unit volume. However, [...] Read more.
Cells in heart muscle need to generate ATP at or near peak capacity to meet their energy demands. Over 90% of this ATP comes from mitochondria, strategically located near myofibrils and densely packed with cristae to concentrate ATP generation per unit volume. However, a consequence of dense inner membrane (IM) packing is that restricted metabolite diffusion inside mitochondria may limit ATP production. Under physiological conditions, the flux of ATP synthase is set by ADP levels in the matrix, which in turn depends on diffusion-dependent concentration of ADP inside cristae. Computer simulations show how ADP diffusion and consequently rates of ATP synthesis are modulated by IM topology, in particular (i) number, size, and positioning of crista junctions that connect cristae to the IM boundary region, and (ii) branching of cristae. Predictions are compared with the actual IM topology of a cardiomyocyte mitochondrion in which cristae vary systematically in length and morphology. The analysis indicates that this IM topology decreases but does not eliminate the “diffusion penalty” on ATP output. It is proposed that IM topology normally attenuates mitochondrial ATP output under conditions of low workload and can be regulated by the cell to better match ATP supply to demand. Full article
(This article belongs to the Section Mitochondria)
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21 pages, 1104 KiB  
Article
Returns to Higher Education in Mexico: A Cross-Sectional Analysis, 2010–2024
by Janeth Yadira Rodríguez Galván and Juan Francisco Islas Aguirre
Economies 2025, 13(2), 43; https://doi.org/10.3390/economies13020043 - 11 Feb 2025
Viewed by 291
Abstract
This study evaluates the socioeconomic effects of educational policies implemented between 2010 and 2024 within the context of the Fourth Industrial Revolution, focusing on the labor demand for professionals with advanced competencies. Using a quantitative analysis based on microdata from the National Survey [...] Read more.
This study evaluates the socioeconomic effects of educational policies implemented between 2010 and 2024 within the context of the Fourth Industrial Revolution, focusing on the labor demand for professionals with advanced competencies. Using a quantitative analysis based on microdata from the National Survey of Occupation and Employment (ENOE) for 2010–2024, an econometric model is employed to estimate the returns to education and work experience and analyze gender wage gaps and the urban–rural distribution. The findings reveal a 46.3% increase in the labor market participation of individuals with higher education and a rise in wage disparities, particularly in the Information and Communication Technology sector. Limited to ENOE data in Mexico, this research adds value by identifying the mismatch between educational supply and emerging labor market demands. The conclusions suggest adjusting educational policies to reduce gender gaps and better equip graduates to meet current challenges. Full article
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16 pages, 4011 KiB  
Article
Spatio-Temporal Analysis of Drought with SPEI in the State of Mexico and Mexico City
by Mauricio Carrillo-Carrillo, Laura Ibáñez-Castillo, Ramón Arteaga-Ramírez and Gustavo Arévalo-Galarza
Atmosphere 2025, 16(2), 202; https://doi.org/10.3390/atmos16020202 - 11 Feb 2025
Viewed by 240
Abstract
Climate change and increasing water demand are causing supply problems in Mexico City and the State of Mexico. The lack of complete and up-to-date meteorological information makes it difficult to understand and analyze climate phenomena such as droughts. Climate Engine provides decades of [...] Read more.
Climate change and increasing water demand are causing supply problems in Mexico City and the State of Mexico. The lack of complete and up-to-date meteorological information makes it difficult to understand and analyze climate phenomena such as droughts. Climate Engine provides decades of climate data to analyze such changes. These data were used to calculate SPEI (Standardized Precipitation-Evapotranspiration index) at scales of 1, 3, 6, 9, 12, and 24 months between 1981 and 2023 in the study area. The Standard Normal Homogeneity Test (SNHT) indicated greater homogeneity in temperature data, while precipitation data exhibited potential inhomogeneities. The Mann–Kendall test showed no significant trend for precipitation but a clear increasing trend in temperature. Droughts have become more frequent and severe over the last decade, particularly in the western State of Mexico and the southwest of Mexico City. The wettest years within the last 14 years were 2010, 2015, and 2018, while the most severe droughts occurred in 2017, 2019, 2020, 2021, and 2023. The findings suggest intensifying drought conditions, likely driven by rising temperatures and climate variability. These trends emphasize the need for improved water resource management and adaptation strategies to mitigate the growing impact of droughts in central Mexico. Full article
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9 pages, 2367 KiB  
Proceeding Paper
Effective Microorganism (EM) Technology for Lake Conservation and Water Quality Restoration
by Irnis Azura Zakarya, Nursyazarena Azwa Mazwin, Tengku Nuraiti Tengku Izhar, Nur Adlina Mohd Hilmi and Muna’amirah Mohamad
Environ. Earth Sci. Proc. 2025, 33(1), 1; https://doi.org/10.3390/eesp2025033001 - 11 Feb 2025
Viewed by 157
Abstract
Water quality is a crucial determinant in decision-making processes aimed at optimizing resource allocation across various industries. Pollutant impurities that hinder the sufficient supply of water have a deleterious impact on the quality and are damaging to living species, especially aquatic life. Various [...] Read more.
Water quality is a crucial determinant in decision-making processes aimed at optimizing resource allocation across various industries. Pollutant impurities that hinder the sufficient supply of water have a deleterious impact on the quality and are damaging to living species, especially aquatic life. Various chemical and biological treatments are used to reduce water pollution levels. A technology involving a mixture of anaerobic and aerobic beneficial microbes is becoming popular for its eco-friendly characteristics. Effective Microorganism (EM) technology utilizes naturally existing microorganisms that can purify and restore the environment. The study investigated the application of Effective Microorganism-Activated Solution (EMAS), TeMo Decomposer (TeMo), and Lactic Acid Bacteria (LAB) to enhance water quality. Additionally, microbial testing will be carried out to identify bacteria present in each EM. EM-based rehabilitation of polluted and degraded water bodies significantly contributes to the restoration of aquatic habitats and ecosystems. This study aimed to assess the water quality at Tasik Alumni, Kampus Pauh, Perlis, Malaysia. Four sampling points in Tasik Alumni were chosen to reflect the water quality status of the lake. The sampling was conducted once at four points locations in Tasik Alumni. Seven water quality measures, including pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N), total suspended solid (TSS), and turbidity, were analysed ex-situ and categorised according to Water Quality Index (WQI) and National Water Quality Standard (NWQS) classifications. The Tasik Alumni was categorised as mildly contaminated. The results clearly showed the efficiency of this technique in restoring and conserving water quality in a degraded or polluted lake. Full article
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