Search Results (87)

Urban areas are facing increasing traffic congestion, pollution, and infrastructure strain. Traditional urban transportation systems are often fragmented. They require users to plan, pay, and travel across multiple disconnected services. Mobility-as-a-Service (MaaS) integrates these services into a single digital platform, simplifying access and improving the user experience. This review critically examines the role of MaaS in fostering sustainable mobility ecosystems. MaaS aims to enhance user-friendliness, service variety, and sustainability by adopting a customer-centric approach to transportation. The findings reveal that successful MaaS systems consistently align with multimodal transport infrastructure, equitable access policies, and strong public-private partnerships. MaaS enhances the management of routes and traffic, effectively mitigating delays and congestion while concurrently reducing energy consumption and fuel usage. In this study, the authors examine MaaS as a new mobility paradigm for a sustainable transportation system in smart cities, observing the challenges and opportunities associated with its implementation. To assess the environmental impact, a sustainability index is calculated based on the use of different modes of transportation. Significant findings indicate that MaaS systems are proliferating in both quantity and complexity, increasingly integrating capabilities such as real-time multimodal planning, dynamic pricing, and personalized user profiles. Full article

Rapid socio-economic development and the impact of human activities have exerted tremendous pressure on the groundwater system of the Dawen River Basin (DRB), the largest tributary in the middle and lower reaches of the Yellow River. Hydrochemical studies on the DRB have largely centered on the upstream Muwen River catchment and downstream Dongping Lake, with some focusing solely on karst groundwater. Basin-wide evaluations suggest good overall groundwater quality, but moderate to severe contamination is confined to the lower Dongping Lake area. The hydrogeologically complex mid-reach, where the Muwen and Chaiwen rivers merge, warrants specific focus. This region, adjacent to populous areas and industrial/agricultural zones, features diverse aquifer systems, necessitating a thorough analysis of its hydrochemistry and origins. This study presents an integrated hydrochemical, isotopic investigation and EWQI evaluation of groundwater quality and formation mechanisms within the multiple groundwater types of the central DRB. Central DRB groundwater has a pH of 7.5–8.2 (avg. 7.8) and TDSs at 450–2420 mg/L (avg. 1075.4 mg/L) and is mainly brackish, with Ca²⁺ as the primary cation (68.3% of total cations) and SO₄²⁻ (33.6%) and NO₃⁻ (28.4%) as key anions. The Piper diagram reveals complex hydrochemical types, primarily HCO₃·SO₄-Ca and SO₄·Cl-Ca. Isotopic analysis (δ²H, δ¹⁸O) confirms atmospheric precipitation as the principal recharge source, with pore water showing evaporative enrichment due to shallow depths. The Gibbs diagram and ion ratios demonstrate that hydrochemistry is primarily controlled by silicate and carbonate weathering (especially calcite dissolution), active cation exchange, and anthropogenic influences. EWQI assessment (avg. 156.2) indicates generally “good” overall quality but significant spatial variability. Pore water exhibits the highest exceedance rates (50% > Class III), driven by nitrate pollution from intensive vegetable cultivation in eastern areas (Xiyangzhuang–Liangzhuang) and sulfate contamination from gypsum mining (Guojialou–Nanxiyao). Karst water (26.7% > Class III) shows localized pollution belts (Huafeng–Dongzhuang) linked to coal mining and industrial discharges. Compared to basin-wide studies suggesting good quality in mid-upper reaches, this intensive mid-reach sampling identifies critical localized pollution zones within an overall low-EWQI background. The findings highlight the necessity for aquifer-specific and land-use-targeted groundwater protection strategies in this hydrogeologically complex region. Full article

The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified water quality classification system was applied, along with statistical methods, including multiple linear regression. The Glubochanka and Krasnoyarka rivers were identified as the most polluted (reaching classes 4–5), with multiple exceedances of Zn (up to 2.96 mg/dm³), Cd (up to 0.8 mg/dm³), and Cu (up to 0.051 mg/dm³). The most stable and highest water quality was recorded in the Oba River, where from 2021 to 2024, water consistently corresponded to Class 2. Regression models of water quality class as a function of time and annual precipitation were constructed to assess the influence of climatic factors. Statistical analysis revealed no consistent linear correlation between average annual precipitation and water quality (correlation coefficients ranging from −0.49 to +0.37), indicating a complex interplay between climatic and anthropogenic factors. Significant relationships were found for the Breksa (R² = 0.903), Glubochanka (R² = 0.602), and Tikhaya (R² = 0.555) rivers, suggesting an influence of temporal and climatic factors on water quality. In contrast, the Oba (R² = 0.130), Ulba (R² = 0.100), and Krasnoyarka (R² = 0.018) rivers exhibited low coefficients, indicating the predominance of other, likely local, sources of pollution. It was found that summer periods are characterized by the highest pollution due to low water flow, while episodes of acid runoff occur in spring. A decrease in pH below 7.0 was first recorded in 2023–2024 in the Ulba and Tikhaya rivers. Forecasts to 2030 suggest relative stability in water quality under current climatic conditions; however, by 2050, the risk of water quality deterioration is expected to rise due to increased precipitation and extreme weather events. This study presents, for the first time, a systematic long-term analysis of small rivers in the East Kazakhstan region, offering deeper insight into the dynamics of surface water quality and providing a scientific foundation for developing adaptive strategies for the protection and sustainable use of water resources under climate change and anthropogenic pressure. The results emphasize the importance of prioritizing rivers with high variability in water quality for regular monitoring and the development of adaptive conservation measures. The research holds strong applied significance for shaping a sustainable water use strategy in the region. Full article

This study presented a comprehensive physical–statistical analysis of atmospheric particulate matter (PM₁₀ and PM_2.5) and trace gases (SO₂ and O₃) over Faial Island in the Azores archipelago during 2024. We collected real-time data at the Espalhafatos rural background station, covering 35,137 observations per pollutant, with 15 min intervals. Descriptive statistics, probability distribution fitting (Normal, Lognormal, Weibull, Gamma), and correlation analyses were employed to characterize pollutant dynamics and identify extreme pollution episodes. The results revealed that PM_2.5 (fine particles) concentrations are best modeled by a Lognormal distribution, while PM₁₀ concentrations fit a Gamma distribution, highlighting the presence of heavy-tailed, positively skewed behavior in both cases. Seasonal and episodic variability was significant, with multiple Saharan dust transport events contributing to PM exceedances, particularly during winter and spring months. These events, confirmed by CAMS and SKIRON dust dispersion models, affected not only southern Europe but also the Northeast Atlantic, including the Azores region. Weak to moderate correlations were observed between PM concentrations and meteorological variables, indicating complex interactions influenced by atmospheric stability and long-range transport processes. Linear regression analyses between SO₂ and O₃, and between SO₂ and PM_2.5, showed statistically significant but low-explanatory relationships, suggesting that other meteorological and chemical factors play a dominant role. This result highlights the importance of developing air quality policies that address both local emissions and long-range transport phenomena. They support the implementation of early warning systems and health risk assessments based on probabilistic modeling of particulate matter concentrations, even in remote Atlantic locations such as the Azores. Full article

Water pollution by antibiotics and heavy metals threatens the ecological environment and human health globally, yet there is no rapid method to detect multiple antibiotics and metal ions simultaneously. A simple, fast, and ultra-sensitive colorimetric chemosensor for the simultaneous detection of moxifloxacin (MOX), ciprofloxacin (CIP), and Cr(III) based on the aggregation of ammonium thioglycolate (ATG)-functionalized gold nanoparticles (ATG-AuNPs) was developed. Following the addition of MOX, CIP, and Cr(III), a color change in the solution was observed from wine-red to blue-grey. The UV–Vis signal of the ATG-AuNPs system blended with MOX, CIP, and Cr(III) in the range of 0~200 µM, 0~100 µM, and 0~5 µM was assessed and measured with detection limits (LODs) of 1.57 µM, 1.30 µM, and 57.1 nM calculated by 3σ/S, respectively. Therefore, this system has the potential to act as an effective colorimetric chemosensor for simultaneously detecting MOX, CIP, and Cr(III) in complex environmental systems. Full article

Plants serve as vital components of ecosystems, with their contamination status acting as sensitive indicators of environmental pollution. Therefore, the precise assessment of plant heavy metal contamination and source identification are crucial for regional ecological conservation and sustainable development. This study investigated heavy metal pollution in four characteristic plant species (Anabasis aphylla L., Alhagi camelorum Fisch., Reaumuria songonica (PalL)Maxim., and Haloxylon ammodendron (C. A. Mey.) Bunge.) within the Kalamaili Mountain Nature Reserve, employing comprehensive methodologies including pollution indices, bioconcentration factors (BCFs), absolute principal component score–multiple linear regression (APCS-MLR), and the random forest model (RF). The key findings revealed the following: The soil exhibited severe Cd and Hg contamination. The plant Cr concentrations exceeded standard limits by 31.89 to 147 fold. The Pb, Hg, and As content in plants showed significant differences. The plants displayed differential metal enrichment capacities, ranked as Cr (BCF = 3.28) > Hg (1.22) > Cd (0.92) > Cu (0.25) > Zn (0.15) > Pb (0.125) > As (0.125), highlighting Cr, Hg, and Cd as priority ecological hazards. Complex interactions were observed, with Reaumuria songonica (PalL)Maxim. showing strong Cd soil–plant correlation (r = 0.78), whereas Alhagi camelorum Fisch. demonstrated negative associations (Cd: r = −0.21). APCS-MLR identified mining/smelting as primary contributors to Cd (63.49%), Zn (55.66%), and Cr (45.51%), while transportation dominated Pb emissions (72.92%). Mercury pollution originated from mixed sources (56.18%), likely involving atmospheric deposition, and RF modeling corroborated these patterns, confirming industrial and transportation synergies for Cd, Zn, Cr, Cu, Hg, and As, with Pb predominantly linked to vehicular emissions. This multidisciplinary approach provides scientific evidence for establishing heavy metal monitoring systems and formulating targeted remediation strategies in arid ecologically fragile regions. Full article

Among the highly toxic heavy metals, cadmium (Cd) is highlighted as a persistent environmental pollutant, posing serious threats to plants and broader ecological systems. Phytochelatins (PCs), which are synthesized by phytochelatin synthase (PCS), are peptides that play a central role in Cd mitigation through metal chelation and vacuolar sequestration upon formation of Cd-PC complexes. PC synthesis interacts with other cellular mechanisms to shape detoxification outcomes, broadening the functional scope of PCs beyond classical stress responses. Plant Cd-related processes have has been extensively investigated within this context. This perspective article presents key highlights of the panorama concerning strategies targeting the PC pathway and PC synthesis to manipulate Cd-exposed plants. It discusses multiple advances on the topic related to genetic manipulation, including the use of mutants and transgenics, which also covers gene overexpression, PCS-deficient and PCS-overexpressing plants, and synthetic PC analogs. A complementary bibliometric analysis reveals emerging trends and reinforces the need for interdisciplinary integration and precision in genetic engineering. Future directions include the design of multigene circuits and grafting-based innovations to optimize Cd sequestration and regulate its accumulation in plant tissues, supporting both phytoremediation efforts and food safety in contaminated agricultural environments. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

This study proposes a simplified mathematical formulation for optimizing isolated microgrids, enhancing computational efficiency while preserving solution quality. The research focuses on the influence of Operation and Maintenance (O&M) costs for Non-Dispatchable Generators (NDGs) and the relationship between costs and pollutant emissions. The proposed simplification reduces computational requirements, improves result interpretability, and increases the scalability of optimization techniques. The O&M costs of photovoltaic and wind systems were excluded from the initial optimization and calculated afterward. A Student’s t-test yielded a p-value of 87.3%, confirming no significant difference between the tested scenarios, ensuring that the simplification does not impact solution quality while reducing computational complexity. For emission-related costs, scenarios with single and multiple pollutant generators were analyzed. When only one generator type is present, modifications are needed to enable effective multi-objective optimization. To address this, two alternative mathematical formulations were tested, offering more suitable approaches for the problem. However, when multiple pollutant sources exist, cost and emission differences naturally define the problem as multi-objective without requiring adjustments. Future work will explore grid-connected microgrids and additional optimization objectives, such as loss minimization, voltage control, and device lifespan extension. Full article

Jet phenomena have significant applications in environmental engineering, chemical process simulations, fluid dynamics, and pollutant dispersion. However, traditional physical models and numerical simulation methods face challenges such as high computational cost and limited accuracy when dealing with complex jet phenomena, such as systems with multiple inclined dense jets. To address this issue, this study proposes a field reconstruction machine learning algorithm to model the concentration field of multiple inclined dense jets. A comprehensive dataset was constructed through computational fluid dynamics (CFD) simulations, and a field reconstruction LightGBM model was trained and compared with field reconstruction approaches based on the XGBoost, GradientBoostingRegressor, and KNN algorithms to validate its superiority in this physical problem. Through testing, the R² value of LightGBM is close to 0.99, and the RMSE value is around 0.001. The results show that the LightGBM model can accurately predict the mixing and diffusion processes of the jets and exhibits higher prediction accuracy and stability compared to other machine learning methods used in this study, particularly in the complex flow environment of high-density jets. This study provides new ideas and tools for researching jet characteristics and offers theoretical support for engineering emission optimization. Full article

With the increasing importance of renewable energy in the global energy transition, the microgrid has attracted wide attention as an efficient and flexible power solution. However, there are some problems in current networked microgrid systems, such as complex structure, numerous parameters, and significant fluctuations in generation capacity. Aiming at the parameter optimization problem of networked microgrids integrating multiple energy generation and energy storage forms, this paper constructs a multi-objective microgrid structure decision-making model. The model comprehensively considers operation and maintenance costs, fuel costs, power abandonment and lack-of-power punishment costs, power transaction costs, and pollution treatment costs, aiming to realize the joint optimization of economic benefits and environmental sustainability. Furthermore, an improved multi-objective particle swarm optimization (IMOPSO) algorithm is designed to solve the model. In order to verify the effectiveness of the model in the scenarios of distributed energy and energy load fluctuation, this paper uses the scenario analysis method to realize the data analysis of 2000 scenarios, and obtains four typical deterministic scenarios for simulation experiments. The experimental results show that, compared with the traditional microgrid, when the capacity configuration is determined by the number of wind driven generators, photovoltaic panels, diesel generators, and batteries being 5, 189, 2, and 107, respectively, the proposed net-connected economic dispatch optimization method based on hybrid renewable energy in this paper reduces the generation cost and environmental cost of the system by 96.76 ¥ to 428.19 ¥, and keeps the load loss rate stable between 0.34% and 4.56%. The utilization rate of renewable energy has been raised to about 95%. Full article

Arsenic (As), a highly toxic and carcinogenic heavy metal, poses significant risks to soil and water quality, while oxytetracycline (OTC), a widely used antibiotic, contributes to environmental pollution due to excessive human usage. Addressing the coexistence of multiple pollutants in the environment, this study investigates the simultaneous adsorption of As(III) and OTC using a novel bimetallic zinc-iron-modified biochar (1Zn-1Fe-1SBC). The developed adsorbent demonstrates enhanced recovery, improved adsorption efficiency, and cost-effective operation. Characterization results revealed a high carbon-to-hydrogen ratio (C/H) and a specific surface area of 1137 m² g⁻¹ for 1Zn-1Fe-1SBC. Isotherm modeling indicated maximum adsorption capacities of 34.7 mg g⁻¹ for As(III) and 172.4 mg g⁻¹ for OTC. Thermodynamic analysis confirmed that the adsorption processes for both pollutants were spontaneous (ΔG < 0), endothermic (ΔH > 0), and driven by chemical adsorption (ΔH > 80 kJ mol⁻¹), with increased system disorder (ΔS > 0). The adsorption mechanisms involved multiple interactions, including pore filling, hydrogen bonding, electrostatic attraction, complexation, and π-π interactions. These findings underscore the potential of 1Zn-1Fe-1SBC as a promising adsorbent for the remediation of wastewater containing coexisting pollutants. Full article

With the growing emphasis on sustainability, awareness of the environmental impacts and negative potential inherent in current business systems has increased. The circular economy (CE) represents an innovative approach that transforms the traditional linear economy into a restorative system, focussing on extending the life cycle of materials through continuous circulation. The Circular B project aims to develop an international framework that considers multiple facets of the CE, including material and asset management and the use of components in the built environment throughout the entire life cycle of the value chain. The primary objective of the CE is to eliminate waste and pollution (e.g., carbon reduction) and strengthen the resilience of the value chain. However, the current implementation of circular strategies has not yet been found to be effective, with several challenges that cause adverse impacts. This study focuses on investigating and analyzing these challenges, particularly in the cultural and societal domains, using both qualitative and quantitative approaches. The scope of the questionnaire was to identify (1) awareness and understanding, (2) cultural attitude, (3) barriers to adoption, (4) incentives and motivations, (5) participation and engagement, and (6) education and training. A questionnaire was distributed to 270 respondents, with anonymous responses collected. The survey included eight questions specifically designed to address cultural and societal challenges. The survey was conducted with participants from various sectors, including academia, local authorities, industry professionals, consultants, and others collected from all over the world, ensuring diverse perspectives. The main weaknesses found based on this survey are related to (1) budget constraints due to high costs of reintegrating in the loop of materials or components due to the complexity of circular processes, (2) applicability on the market remains still limited, (3) the importance of planning and design in the initial phases, (4) the importance of establishing a comprehensive network to enhance collaboration among stakeholders, and (5) inadequate policies. The insights gained from this study will help stakeholders, such as constructors, maintainers, engineers, designers, and consultants, across various organizations in the value chain to develop practical solutions to mitigate these challenges and improve the overall business system. Full article

The complexity of watershed pollution governance necessitates the involvement of multiple stakeholders, with increasing emphasis on public participation. In response, China introduced the river chief system and gradually established civilian river chiefs and environmental supervisors as channels for public engagement. However, questions remain about how to effectively and sustainably engage the public while addressing watershed pollution. To explore this, we employed an action research approach, focusing on a case from Guiyang, which pioneered the “Dual River Chief System” and introduced civilian environmental supervisors, significantly mobilizing public involvement and controlling pollution. By analyzing the selection background, criteria, responsibilities, training, support mechanisms, and fieldwork of civilian environmental supervisors, we found that their primary tasks were monitoring watershed conditions and mobilizing broader public participation, with selection criteria focusing on interest in watershed governance and regional influence. At the same time, training and expert support were provided to enhance their investigative capabilities and ensure accurate results. This also fostered greater commitment and confidence among the supervisors, further promoting public participation in watershed governance. Despite its success, the approach relied heavily on the groundwork and local networks of civilian river chiefs and required significant time and effort in the early stages, posing certain limitations. Full article

Lake water pollution under anthropogenic influences exhibits characteristics of high uncertainty, rapid evolution, and complex control challenges, presenting substantial threats to ecological systems and human health. Quantitative risk prediction provides crucial support for water quality deterioration prevention and management. This study employed the Copula Bayesian Network model to conduct a comprehensive risk assessment of water quality in Qilu Lake, China (2010–2020), incorporating inter-indicator correlations and multiple uncertainty sources. Analysis revealed generally “worse” water quality conditions (5.10 ± 1.35) according to established index classifications, with predicted probabilities of reaching “deteriorated” status ranging from 11.80% to 47.90%. Significant spatial and temporal variations in water quality and pollution risk were observed, primarily attributed to intensive agricultural non-point source loading and water resource deficiency. The study established early warning thresholds through key indicator concentration predictions, particularly for the southern region where “deteriorated” risk levels corresponded to specific ranges: TN (3.42–8.43 mg/L), TP (0.07–1.29 mg/L), and COD_Cr (27.75–67.19 mg/L). This methodology effectively characterizes lake water quality evolution while enabling risk prediction through key indicator monitoring. The findings provide substantial support for water pollution control strategies, risk management protocols, and regulatory decision-making for lake ecosystem administrators. Full article