Search Results (427)

Increased market demand for plant herbs has prompted growers to ensure a continuous and assured supply of superior nutritional quality over the years. Apart from the nutritional value, culinary herbs contain phytochemical benefits that can improve human health. However, a significant amount of research has focused on enhancing yield, frequently overlooking the impact of production practices on the antioxidant and phytonutritional content of the produce. Thus, the study aimed to evaluate the yield, phytonutrients, and essential mineral profiling in selected aromatic herbs and their intricate role in nutritional quality when grown under different production systems. Five selected aromatic herbs (coriander, rocket, fennel, basil, and moss-curled parsley) were evaluated at harvest when grown under three production systems: in a gravel-film technique (GFT) hydroponic system and in soil, both under the 40% white shade-net structure, as well as in a soilless medium using sawdust under a non-temperature-controlled plastic tunnel (NTC). The phytonutritional quality properties (total phenolic, flavonoids, β-carotene-linoleic acid, and condensed tannins contents) as well as 1,1-diphenyl-2-picrylhydrazyl (DPPH) were assessed using spectrophotometry, while vitamin C and β-carotene were analyzed using HPLC-PDA, and leaf mineral content was evaluated using ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry). The results show that the health benefits vary greatly owing to the particular culinary herb. The fresh leaf mass (yield) of coriander, parsley, and rocket was not significantly affected by the production system, whereas basil was high in soil cultivation, followed by GFT. Fennel had a high yield in the GFT system compared to in-soil and in-soilless cultivation. The highest levels of vitamin C were found in basil leaves grown in GFT and in soil compared to the soilless medium. The amount of total phenolic and flavonoid compounds, β-carotene, β-carotene-linoleic acid, and DPPH, were considerably high in soil cultivation, except on condensed tannins compared to the GFT and soilless medium, which could be a result of Photosynthetic Active Radiation (PAR) values (683 μmol/m²/s) and not favoring the accumulation of tannins. Overall, the mineral content was greatly influenced by the production system. Leaf calcium and magnesium contents were highly accumulated in rockets grown in the soilless medium and the GFT hydroponic system. The results have highlighted that growing environmental conditions significantly impact the accumulation of health-promoting phytonutrients in aromatic herbs. Some have positive ramifications, while others have negative ramifications. As a result, growers should prioritize in-soil production systems over GFT (under the shade-net) and soilless cultivation (under NTC) to produce aromatic herbs to improve the functional benefits and customer health. Full article

The failure of traditional drought indices to capture the dynamic supply–demand imbalance in socio-hydrological systems hinders proactive water management and necessitates novel assessment frameworks. The reservoir drought warning water level, serving as a dynamic threshold indicating supply–demand imbalance, provides a critical basis for drought early warning. From a socio-hydrological drought perspective, this study develops a framework for determining staged and graded soft partition thresholds for reservoir drought warning water levels, encompassing three key stages: water stress analysis, phase classification, and threshold determination. First, water demands for the ecological, agricultural, and domestic sectors were quantified based on hydrological analysis and official operational rules. Second, an optimized KPCA-Fisher model delineated the intra-annual supply–demand dynamics into distinct periods. Thirdly, the soft partition thresholds were formulated by coupling these multi-sectoral demands with water deficit rates using a triangular membership function. Applied to the Xianan Reservoir, the framework yielded distinct drought warning thresholds for the identified main flood, critical demand, and dry seasons. Validation against historical droughts (2019 and 2022) confirmed that these soft thresholds more accurately tracked the drought evolution process compared to traditional hard partitions. Furthermore, a sensitivity analysis identified the ecological water demand methodology as a key factor influencing the thresholds, particularly during the critical demand period. The proposed framework for determining staged and graded reservoir drought warning water levels better reflects the complexity of socio-hydrological systems and provides a scientific basis for refined reservoir drought early warnings and management under changing environments. Full article

The increasing penetration of distributed energy resources (DERs) and power electronic loads challenges the modeling and control of modern distribution networks (DNs). The traditional models often fail to capture the complex aggregate dynamics required for advanced control strategies. This paper proposes a novel framework for DN power regulation based on Neural Ordinary Differential Equations (NODEs) and Model Predictive Control (MPC). NODEs are employed to develop a data-driven, continuous-time dynamic model capturing the aggregate relationship between the voltage at the point of common coupling (PCC) and the network’s power consumption, using only PCC measurements. Building upon this NODE model, an MPC strategy is designed to regulate the DN’s active power by manipulating the PCC voltage. To ensure computational tractability for real-time applications, a local linearization technique is applied to the NODE dynamics within the MPC, transforming the optimization problem into a standard Quadratic Programming (QP) problem that can be solved efficiently. The framework’s efficacy is comprehensively validated through simulations. The NODE model demonstrates high accuracy in predicting the dynamic behavior in a DN against a detailed simulator, with maximum relative errors below 0.35% for active power. The linearized NODE-MPC controller shows effective tracking performance, constraint handling, and computational efficiency, with typical QP solve times below 0.1 s within a 0.1 s control interval. The validation includes offline tests using the NODE model and online co-simulation studies using CloudPSS and Python via Redis. Application scenarios, including Conservation Voltage Reduction (CVR) and supply–demand balancing, further illustrate the practical potential of the proposed approach for enhancing the operation and efficiency of modern distribution networks. Full article

Green Stormwater Infrastructure (GSI), as a nature-based solution, has gained widespread recognition for its role in mitigating urban flood risks and enhancing resilience. Equitable spatial distribution of GSI remains a pressing challenge, critical to harmonizing urban hydrological systems and maintaining ecological balance. However, the complexity of matching GSI supply with urban demand has limited comprehensive spatial assessments. This study introduces a quantitative framework to identify priority zones for GSI deployment and to evaluate supply–demand dynamics in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) using a coupled coordination simulation model. Clustering and proximity matrix analysis were applied to map spatial relationships across districts and to reveal underlying mismatches. Findings demonstrate significant spatial heterogeneity: over 90% of districts show imbalanced supply–demand coupling. Four spatial clusters were identified based on levels of GSI disparity. Economically advanced urban areas such as Guangzhou and Shenzhen showed high demand, while peripheral regions like Zhaoqing and Huizhou were characterized by oversupply and misaligned allocation. These results provide a systematic understanding of GSI distribution patterns, highlight priority intervention areas, and offer practical guidance for large-scale, equitable GSI planning. Full article

The shortage of freshwater resources has become the core bottleneck of global sustainable development. Traditional freshwater harvesting technologies are restricted by geographical conditions and environmental limitations, making them increasingly difficult to satisfy the growing water demand. In this study, based on the synergistic coupling mechanism of photothermal conversion and radiative cooling, a solar auto-tracking assisted selective solar absorber and radiative cooling all-weather freshwater harvesting device was innovatively developed. The prepared selective solar absorber achieved a high absorptivity of 0.91 in the solar spectrum (0.3–2.5 μm) and maintained a low emissivity of 0.12 in the mid-infrared range (2.5–20 μm), significantly enhancing the photothermal conversion efficiency. The radiative cooling film demonstrated an average cooling effect of 7.62 °C during typical daytime hours (12:00–13:00) and 7.03 °C at night (22:00–23:00), providing a stable low-temperature environment for water vapor condensation. The experimental results showed that the experimental group equipped with the solar auto-tracking system collected 0.79 kg m⁻² of freshwater in 24 h, representing a 23.4% increase compared to the control group without the solar auto-tracking system. By combining theoretical analysis with experimental validation, this study presents technical and economic advantages for emergency water and island freshwater supply, offering an innovative solution to mitigate the global freshwater crisis. Full article

With the development of urban construction and the improvement of residents’ quality of life, the focus of governance has shifted to a people-centered approach. In the core area of Beijing, there is a mismatch between the existing large comprehensive hospitals (LCHs) and the current demand for medical technology and services. Therefore, this study focuses on tertiary LCHs in the core area of Beijing from the perspective of supply and demand (SD) and explores in depth the problem of matching the crowd concentration and the SD of the surrounding public service facilities in the process of seeking medical treatment. By comprehensively analyzing the public service facilities within a 15-min walking distance around the hospital and considering demand, supply, and transport factors, this study identifies 15 key indicators, constructs an SD coupling model (SDCM) evaluation system, and systematically evaluates the space of public service facilities around an LCH. The results show that the higher the spatial coupling and coordination of these facilities around the LCH, the more tightly the system is connected, and the more pronounced the coupling effect is in the vicinity of the hospital, which suggests that the hospital has a clustering effect on its radiating area. Full article

To tackle the problems of high scheduling costs and low photovoltaic (PV) accommodation rates in port microgrids, which are caused by the coupling of uncertainties in new energy output and load randomness, this paper proposes an optimized scheduling method that integrates scenario analysis with multi-energy complementarity. Firstly, based on the improved Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA) clustering algorithm and backward reduction method, a set of typical scenarios that represent the uncertainties of PV and load is generated. Secondly, a multi-energy complementary system model is constructed, which includes thermal power, PV, energy storage, electric vehicle (EV) clusters, and demand response. Then, a planning model centered on economy is established. Through multi-energy coordinated optimization, supply–demand balance and cost control are achieved. The simulation results based on the port microgrid of the LEKKI Port in Nigeria show that the proposed method can significantly reduce system operating costs by 18% and improve the PV accommodation rate through energy storage time-shifting, flexible EV scheduling, and demand response incentives. The research findings provide theoretical and technical support for the low-carbon transformation of energy systems in high-volatility load scenarios, such as ports. Full article

Cultural ecosystem services (CES) in urban parks, as a vital component of urban ecosystem services (ES), are increasingly recognized as an important tool for advancing urban sustainability and implementing nature-based solutions (NbS). The supply–demand relationship of CES in urban parks is strongly shaped by sociocultural and spatial geographic factors, playing a crucial role in optimizing urban landscape structures and enhancing residents’ well-being. However, current research generally lacks adaptive evaluation frameworks and quantitative methods, particularly for cities with significant spatial and cultural diversity. To address this gap, this study examines the central district of Lhasa as a case study to develop a CES supply–demand evaluation framework suitable for plateau river valley cities. The study adopts the spatial integration analysis method to establish an indicator system centered on “recreational potential–recreational opportunities” and “social needs–material needs,” mapping the spatial distribution and matching characteristics of supply and demand at the community scale. The results reveal that: (1) in terms of supply–demand balance, 25.67% of communities experience undersupply, predominantly in the old city cluster, while 16.22% experience oversupply, mainly in key development zones, indicating a notable supply–demand imbalance; (2) in terms of supply–demand coupling coordination, 55.11% and 38.14% of communities are in declining and transitional stages, respectively. These communities are primarily distributed in near-mountainous and peripheral urban areas. Based on these findings, four urban landscape optimization strategies are proposed: culturally driven urban park development, demand-oriented park planning, expanding countryside parks along mountain ridges, and revitalizing existing parks. These results provide theoretical support and decision-making guidance for optimizing urban park green space systems in plateau river valley cities. Full article

Under China’s dual-carbon strategy, the construction sector still lacks a systematic quantitative view of what drives its shift to a circular economy. This study couples the Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Total Adversarial Interpretive Structural Modeling (TAISM) to build a weighted, multi-layer model of the policy–market–organization–technology chain. DEMATEL measures causal strengths, and TAISM arranges the variables into five levels without subjective thresholds, revealing a five-stage activation pathway. Fiscal incentives and regulations start the cascade; market demand amplifies their effect into a “resonant resilience” mechanism that improves cost performance. Robustness tests show 87% hierarchy stability and causal variation within ±0.6%. Sensitivity checks indicate that policy support must supply at least 30% of total network weight, because market capital alone cannot meet circular-construction costs. A three-tier intervention—policy incentives, financial amplification, and digital decomposition via green finance, BIM, and material passports—is therefore recommended. Full article

Due to the unbalanced temporal and spatial distribution of the passenger flow on metro lines during peak hours, the implementation of passenger flow control strategies effectively ensures operational safety and travel efficiency for passengers. In this study, we analyze the coupling relationship between trains and passengers, introduce train-stopping state variables, and synergistically optimize both train operation schedules and station passenger flow control. Aiming to minimize the total passenger delay time and maximize the number of boarding passengers, we consider four constraints: the train operation process, the passenger entry process, the passenger–train interaction process, and system constraints. This framework enables us to construct a cooperative passenger flow control optimization model for oversaturated metro lines. Subsequently, we propose an improved artificial bee colony algorithm to solve this model. We utilize evolutionary operators and an enhanced tabu search to create new food sources for employed bees and enhance their local search capabilities during the employed phase. Finally, Shanghai Metro Line 9 is used as a case study for the model validation. The computational results indicate that the proposed Collaborative passenger flow control strategy significantly reduces the number of stranded passengers on platforms and decreases the total passenger delay time by 36.26% compared to the existing passenger flow control strategy. The findings demonstrate that the cooperative control strategy proposed in this paper can effectively alleviate the pressure from passenger flow on oversaturated lines, balance the asymmetry between supply and demand, and markedly improve both safety and efficiency in the metro system during peak hours. Full article

Complex feedback mechanisms and interdependencies exist among the water–energy–food–ecosystems (WEFE) nexus. In water-scarce regions, fluctuations in the supply or demand of any single subsystem can destabilize the others, with water shortages intensifying conflicts among food production, energy consumption, and ecological sustainability. Balancing the synergies and trade-offs within the WEFE system is therefore essential for achieving sustainable development. This study adopts the natural–social water cycle as the core process and develops a coupled simulation model of the WEFE (CSM-WEFE) system, integrating food production, ecological water replenishment, and energy consumption associated with water supply and use. Based on three performance indices—reliability, coupling coordination degree, and equilibrium—a coordinated sustainable development index (CSD) is constructed to quantify the performance of WEFE system under different scenarios. An integrated evaluation framework combining the CSM-WEFE and the CSD index is then proposed to assess the sustainability of WEFE systems. The framework is applied to the Beijing–Tianjin–Hebei (BTH) region, a representative water-scarce area in China. Results reveal that the current balance between water supply and socio-economic demand in the BTH region relies heavily on excessive groundwater extraction and the appropriation of ecological water resources. Pursuing food security goals further exacerbates groundwater overexploitation and ecological degradation, thereby undermining system coordination. In contrast, limiting groundwater use improves ecological conditions but increases regional water scarcity and reduces food self-sufficiency. Even with the full operation of the South-to-North Water Diversion Project (Middle Route), the region still experiences a 16.4% water shortage. By integrating the CSM-WEFE model with the CSD evaluation approach, the proposed framework not only provides a robust tool for assessing WEFE system sustainability but also offers practical guidance for alleviating water shortages, enhancing food security, and improving ecological health in water-scarce regions. Full article

Water scarcity has become a critical global challenge, particularly in rapidly developing regions where water demand often exceeds sustainable supply capacities. Traditional “demand-driven” water management approaches have proven inadequate to address this imbalance, necessitating the development of more sophisticated “supply-driven” solutions. This study presents a groundbreaking System Dynamics (SD)-Feedback-Hierarchical Water Demand (SD-F-HWD) model that advances water resources management through three contributions. First, the model substantially extends conventional water demand hierarchy methods by developing a comprehensive classification framework with enhanced sector-specific criteria for industrial, agricultural, and ecological needs. Second, the innovative feedback regulation mechanism resolves persistent challenges from previous studies, including ambiguous control parameters and system instability. Third, the model establishes a unified analytical platform that effectively integrates these components for robust supply–demand equilibrium analysis. Validation in Wu’an City, Hebei Province—a representative water-stressed industrial region in northern China—demonstrated the model’s effectiveness. Under low-flow conditions (P = 75%), total water demand decreased by 11.24% while rigid demand was reduced by 8.50%. For normal flow conditions (P = 50%), corresponding reductions reached 9.88% and 6.99%, respectively. Crucially, all adjustments remained within practical policy implementation boundaries, demonstrating the model’s real-world applicability. The SD-F-HWD model offers a practical and scalable solution for sustainable water allocation in water-stressed regions through its integrated methodological framework. Full article

As a decentralized energy management paradigm, micro-energy grid (MEG) clusters enable synergistic operation of heterogeneous distributed energy assets, particularly through multi-energy vector coupling mechanisms that enhance distributed energy resource (DER) utilization efficiency in next-generation power networks. While individual MEGs demonstrate limited capability in responding to upper-grid demands using surplus energy after fulfilling local supply/demand balance, coordinated cluster operation significantly enhances system-wide flexibility. This paper proposes a two-stage robust optimization model that systematically addresses both the synergistic complementarity of multi-MEG systems and renewable energy uncertainty. First, the basic operation structure of MEG, including distributed generation, cogeneration units, and other devices, is established, and the operation mode of the MEG cluster responding to host utility grid flexibly is proposed. Then, aiming to reduce operation expenses, an optimal self-scheduling plan is generated by establishing a MEG scheduling optimization model; on this basis, the flexibility response capability of the MEG is measured. Finally, to tackle the uncertainty issue of wind and photovoltaic power generation, the two-stage robust theory is employed, and the scheduling optimization model of MEG cluster flexibility response to the host utility grid is constructed. A southern MEG cluster is chosen for simulation to test the model and method’s effectiveness. Results indicate that the MEG cluster’s flexible response mechanism can utilize individual MEGs’ excess power generation to meet the host utility grid’s dispatching needs, thereby significantly lowering the host utility grid’s dispatching costs. Full article

As a vital bridge linking human well-being with ecological processes, cultural ecosystem services (CESs) play a pivotal role in understanding the equilibrium of social–ecological systems. However, the spatial supply–demand relationships of CESs remain underexplored in rapidly urbanizing regions. This study establishes an integrated framework by synthesizing multi-source geospatial data, socioeconomic indicators, and the Maximum Entropy (MaxEnt) model to investigate the spatial dynamics of CESs in Taiyuan City. Key findings include the following: (1) A pronounced spatial heterogeneity in CES supply distribution, exhibiting a core-to-periphery diminishing gradient, with inverse correlations observed among different CES categories. (2) Accessibility, topographic features, and fractional vegetation cover emerged as primary drivers of spatial supply differentiation, while climatic factors and elevation exerted non-negligible influences on this Loess Plateau urban system. (3) Four spatial mismatch patterns were identified through the supply–demand analysis: high supply–high demand (38.1%), low supply–low demand (37.2%), low supply–high demand (13.6%), and high supply–low demand (10.9%). The coupling coordination degree of CESs in Taiyuan City indicated moderate coordination, with severe imbalances observed in urban–rural transitional zones. This study reveals nonlinear interactions between natural landscapes and anthropogenic factors in shaping CES spatial distributions, particularly the trade-offs between esthetic value and transportation constraints. By integrating big data and spatial modeling, this research advances CES quantification methodologies and provides actionable insights for optimizing green infrastructure, prioritizing ecological restoration, and balancing urban–rural CES provision. These outcomes address methodological gaps in coupled social–ecological system research while informing practical spatial governance strategies. Full article

China’s electric vehicle (EV) fleet has reached 30 million, and the effective utilization of their charging and discharging capabilities can provide substantial regulation support to restore supply–demand balance. A prerequisite to achieving this benefit is the proper estimation and utilization of the regulation potential inherent in EVs. This paper focuses on charging stations and introduces a station-aggregator response resource trading mechanism considering energy–power coupling of response capability. First, the response capacity of charging stations is estimated from both energy and power perspectives. Next, trading behavior models are developed separately for charging stations and aggregators. Finally, a joint resource trading mechanism based on a Stackelberg game is proposed to coordinate responses between these entities. Simulation results validate the effectiveness of the proposed estimation method and the economic advantages of the trading mechanism, thereby realizing a win–win outcome. Full article