Search Results (106)

Objectives: The aim of this study is to investigate the changes in quantitative indices of brain volume and cortex development in preterm infants with enlarged subarachnoid space (ESS). Methods: A single-center retrospective cohort study was performed in Hong Kong University–Shenzhen Hospital from November 2014 to November 2023, involving 200 preterm infants whose brain MRI images were available. Parameters including the volume of cerebrospinal fluid (CSF), brain tissues, total intracranial cavity (ICC), and key indices of cortex maturation (surface area, cortical thickness, cortical volume, mean curvature) were compared between the groups with ESS and without ESS. The retrospective nature of this study may introduce selection bias in the process of enrolling preterm infants with ESS. Results: The groups with severe and mild ESS had a significantly greater ICC volume than the group without ESS (severe: 384.66 ± 30.33 [p < 0.001]; mild: 374.25 ± 26.45 [p < 0.001] vs. no ESS: 356.78 ± 26.03), and the difference was mostly due to the gap in extra-CSF volume among the three groups (severe: 74.20 ± 5.1 and mild: 55.36 ± 3.8 vs. no ESS: 40.54 ± 4.3, p ≤ 0.001). Only the volume of parenchyma of the severe-ESS group was significantly different (severe: 302.35 ± 26.43 vs. no ESS: 312.27 ± 20.75, p = 0.003). Regarding indices of cortex maturation, only the mean curvature showed a significant difference between the three groups, and most of the significant clusters were located around the parietal and temporal lobes. Conclusions: ESS may be associated with impaired early brain maturation in preterm infants after birth. A further neurodevelopmental follow-up study is needed. Full article

China has adopted extensive restoration practices to improve ecosystem function. The efficiency of these restoration efforts remains unclear, which may hinder the supply of ecosystem services (ESs). In this context, this study first employed InVEST models to clarify spatio-temporal changes in five key ESs. The static and dynamic efficiencies of ecosystem service production in 130 cities from 2015 to 2021 in the Yangtze River Economic Belt (YREB) were then measured using the Super-SBM-Malmquist model, with ESs considered as outputs. The results indicated that water conservation (WC), water purification (WP), and soil retention (SR) exhibited overall declining trends, decreasing by 28.32%, 3.22%, and 10.00%, respectively, while carbon storage (CS) and habitat quality (HQ) remained steady. More than 70% of studied cities exhibited static efficiency levels below 50%, which were attributed to inefficient utilization of labor, capital, and technology. Significant spatial heterogeneity was observed, with high-efficiency cities mainly located in mountainous areas and low-efficiency cities concentrated in flat regions. The downward trend in dynamic efficiency has been reversed from a 39.02% decline in 2015–2018 to a 38.31% increase in 2018–2021, despite being adversely affected by technological regression. Finally, several policy implications are proposed, including optimizing resource allocation, introducing advanced technology and setting the intercity cooperation and complementarity mechanisms. Full article

An in-depth understanding of the spatiotemporal heterogeneity of ecosystem service (ES) trade-offs and synergies, along with their driving factors, is crucial for formulating key ecological restoration strategies and effectively allocating ecological environmental resources in the Hulunbuir region. This study employed an integrated analytical approach combining the InVEST model, ArcGIS geospatial processing, R software environment, and Optimal Parameter Geographical Detector (OPGD). The spatiotemporal patterns and driving factors of the interaction of four major ES functions in Hulunbuir area from 2000 to 2020 were studied. The research findings are as follows: (1) carbon storage (CS) and soil conservation (SC) services in the Hulunbuir region mainly show a distribution pattern of high values in the central and northeast areas, with low values in the west and southeast. Water yield (WY) exhibits a distribution pattern characterized by high values in the central–western transition zone and southeast and low values in the west. For forage supply (FS), the overall pattern is higher in the west and lower in the east. (2) The trade-off relationships between CS and WY, CS and SC, and SC and WY are primarily concentrated in the western part of Hulunbuir, while the synergistic relationships are mainly observed in the central and eastern regions. In contrast, the trade-off relationships between CS and FS, as well as FS and WY, are predominantly located in the central and eastern parts of Hulunbuir, with the intensity of these trade-offs steadily increasing. The trade-off relationship between SC and FS is almost widespread throughout HulunBuir. (3) Fractional vegetation cover, mean annual precipitation, and land use type were the primary drivers affecting ESs. Among these factors, fractional vegetation cover demonstrates the highest explanatory power, with a q-value between 0.6 and 0.9. The slope and population density exhibit relatively weak explanatory power, with q-values ranging from 0.001 to 0.2. (4) The interactions between factors have a greater impact on the inter-relationships of ESs in the Hulunbuir region than individual factors alone. The research findings have facilitated the optimization and sustainable development of regional ES, providing a foundation for ecological conservation and restoration in Hulunbuir. Full article

The ecosystem services (ESs) of forests are the benefits that people derive from forest ecosystems. Their precise recognition is important for differentiating and determining the optimal principles of multifunctional forest management. The aim of this study is to identify some important ESs based on a site classification system at the lowest level—i.e., forest stands, at the forest owner level—as a tool for differentiated management. ESs were assessed within the Czech Republic and are expressed in units in accordance with the very sophisticated Forest Site Classification System. (1) Biomass production: The vertical differentiation of ecological conditions given by vegetation tiers, which reflect the influence of altitude, exposure, and climate, provides a basic overview of biomass production; the highest value is in the fourth vegetation tier, i.e., the Fageta abietis community. Forest stands are able to reach a stock of up to 900–1200 m³·ha⁻¹. The lowest production is found in the eighth vegetation tier, i.e., the Piceeta community, with a wood volume of 150–280 m³·ha⁻¹. (2) Soil conservation function: Geological bedrock, soil characteristics, and the geomorphological shape of the terrain determine which habitats serve a soil conservation function according to forest type sets. (3) The hydricity of the site, depending on the soil type, determines the hydric-water protection function of forest stands. Currently, protective forests occupy 53,629 ha in the Czech Republic; however, two subcategories of protective forests—exceptionally unfavorable locations and natural alpine spruce communities below the forest line—potentially account for 87,578 ha and 15,277 ha, respectively. Forests with an increased soil protection function—a subcategory of special-purpose forests—occupy 133,699 ha. The potential area of soil protection forests could be up to 188,997 ha. Water resource protection zones of the first degree—another subcategory of special-purpose forests—occupy 8092 ha, and there is potentially 289,973 ha of forests serving a water protection function (specifically, a water management function) in the Czech Republic. A separate subcategory of water protection with a bank protection function accounts for 80,529 ha. A completely new approach is presented for practical use by forest owners: based on the characteristics of the habitat, they can obtain information about the fulfillment of the habitat’s ecosystem services and, thus, have basic information for the determination of forest categories and the principles of differentiated management. Full article

To address the charging demand challenges brought about by the widespread adoption of electric vehicles, integrated photovoltaic–storage–charging stations (PSCSs) enhance energy utilization efficiency and economic viability by combining photovoltaic (PV) power generation with an energy storage system (ESS). This paper proposes a two-stage data-driven holistic optimization model for the siting and capacity allocation of charging stations. In the first stage, the location and number of charging piles are determined by analyzing the spatiotemporal distribution characteristics of charging demand using ST-DBSCAN and K-means clustering methods. In the second stage, charging load results from the first stage, photovoltaic generation forecast, and electricity price are jointly considered to minimize the operator’s total cost determined by the capacity of PV and ESS, which is solved by the genetic algorithm. To validate the model, we leverage large-scale GPS trajectory data from electric taxis in Shenzhen as a data-driven source of spatiotemporal charging demand. The research results indicate that the spatiotemporal distribution characteristics of different charging demands determine whether a charging station can become a PSCS and the optimal capacity of PV and battery within the station, rather than a fixed configuration. Stations with high demand volatility can achieve a balance between economic benefits and user satisfaction by appropriately lowering the peak instantaneous satisfaction rate (set between 70 and 80%). Full article

As ecologically sensitive interfaces shaped by the interplay of land and sea, coastal zones demand close attention. Uncovering the spatiotemporal evolution of ecosystem service value (ESV) and the intricate interrelations among ecosystem service (ES) functions is imperative for the informed governance of human–land interactions and for fostering sustainable regional development. This study analyzes the spatiotemporal evolution of ESV based on the modified equivalent factor table, combining the Geo-information Tupu, Markov transfer model, and standard deviation ellipse. Additionally, we introduce an ecosystem service tradeoff degree (ESTD) to assess the tradeoffs and synergies among various ESs, and we utilize GeoDetector to elucidate the driving forces behind the spatial disparities in ESV. Our findings reveal that (1) Although the land use composite index in the Liaoning coastal economic belt (LCEB) increased, the pace of land use transformation demonstrated a trend toward stabilization over the study duration. (2) Between 2000 to2020, ESV initially declined but subsequently experienced an upward rebound, resulting in a net gain of approximately 48 billion yuan. Spatial analysis indicated continuous enlargement of the standard deviation ellipse, with its centroid consistently located within Yingkou City and a gradual directional shift toward the southwest. (3) The dominant relationship among ESs showed synergy, with notable tradeoffs between hydrological regulation and other services. (4) Topography and climate factors were the primary drivers of spatial heterogeneity of ESV in the LCEB. The research provides spatial decision support for optimizing the ecological security pattern of the coastal zone. Full article

Conventional approaches for distributed generation (DG) planning often fall short in addressing operational demands and regional control requirements within distribution networks. To overcome these limitations, this paper introduces a cluster-oriented DG planning method. In terms of cluster partitioning, this study breaks through the limitations of traditional methods that solely focus on electrical parameters or single functions. Innovatively, it partitions the distribution network by comprehensively considering multiple critical factors such as system grid structure, nodal load characteristics, electrical coupling strength, and power balance, thereby establishing a unique multi-level grid structure of **distribution network—cluster—node**. This partitioning approach not only effectively reduces inter-cluster reactive power transmission and enhances regional power self-balancing capabilities but also lays a solid foundation for the precise planning of subsequent distributed energy resources. It represents a functional expansion that existing cluster partitioning methods have not fully achieved. In the construction of the planning model, a two-layer coordinated siting and sizing planning model for distributed photovoltaics (DPV) and energy storage systems (ESS) is proposed based on cluster partitioning. In contrast to traditional models, this model for the first time considers the interaction between power source planning and system operation across different time scales. The upper layer aims to minimize the annual comprehensive cost by optimizing the capacity and power allocation of DPV and ESS in each cluster. The lower layer focuses on minimizing system network losses to precisely determine the PV connection capacity of each node within the cluster and the grid connection locations of ESS, achieving comprehensive optimization from macro to micro levels. For the solution algorithm, a two-layer iterative hybrid particle swarm algorithm (HPSO) embedded with power flow calculation is designed. Compared to traditional single particle swarm algorithms, HPSO integrates power flow calculations, allowing for a more accurate consideration of the actual operating conditions of the power grid and avoiding the issue in traditional methods where the current and voltage distribution are often neglected in the optimization process. Additionally, HPSO, through its two-layer iterative approach, is able to better balance global and local search, effectively improving the solution efficiency and accuracy. This algorithm integrates the advantages of the particle swarm optimization algorithm and the binary particle swarm optimization algorithm, achieving iterative solutions through efficient information exchange between the two layers of particle swarms. Compared with conventional particle swarm algorithms and other related algorithms, it represents a qualitative leap in computational efficiency and accuracy, enabling faster and more accurate handling of complex planning problems. Case studies on a real 10 kV distribution network validate the practicality of the proposed framework and the robustness of the solution technique. Full article

A paradigm transition from centralized to decentralized energy systems has occurred, which has increased the deployment of renewable energy sources (RESs) in renewable energy communities (RECs), promoting energy independence, strengthening local resilience, increasing self-sufficiency, and moving toward CO₂ emission reduction. However, the erratic and unpredictable generation of RESs like wind, solar, and other sources make these systems necessary, and a lot of interest in energy storage systems is increasing because they have rapidly become the cornerstone of modern energy infrastructure, and there is a trend towards using more RESs and decentralization, resulting in increased self-sufficiency. Additionally, ESS is increasingly being installed at or close to the point of energy generation and consumption, like within residences, buildings, or community microgrids, instead of at centralized utility-scale facilities, referred to be decentralized. By storing and using energy in the same location, this localized deployment reduces transmission losses, facilitates quicker response to changes in demand, and promotes local autonomy in energy management. Since the production of renewable energy is naturally spread, decentralizing storage is crucial to optimizing efficiency and dependability. This article also focuses on energy storage systems, highlighting the role and scope of ESSs along with the services of ESSs in different parts of the power system network, particularly in renewable energy communities (RECs). The classification of various ESS technologies and their key features, limitations, and applications is discussed following the current technological and significant information trends and discussing the ESS types for the RECs with different options as per the capacity, like small, medium, and large scale. It covers the overall scenario and progress, like overall European ESS installed capacity, and the work relevant to ESSs in RECs with different aspects, following the literature review. Additionally, it draws attention to the gaps and significant challenges related to ESS technologies and their deployment. Key future suggestions have also been given as per the current trends of technological information and significant information that may affect those trends globally in the future and would be helpful in the growth of ESSs integration in RECs. The authors also suggest the role of the government, stakeholders, and supportive policies that can aid in the implementation of ESS technologies in RECs. Full article

With the increasing proportion of Distributed Generation (DG) in distribution networks and growing electricity business expansion demand, the integration of DG and new loads imposes significant impacts on distribution networks. To address the incomplete evaluation of active distribution network acceptance capacity, this paper proposes a multi-modal load acceptance capacity assessment methodology incorporating load growth patterns while comprehensively analyzing DG integration impacts. Firstly, differentiated load dynamic models are established to reveal the spatiotemporal distribution characteristics of multi-type loads. Secondly, a load growth model is presented based on spatiotemporal probability decomposition, accompanied by a multi-constraint acceptance capacity evaluation index system tailored to distribution networks. Moreover, an improved repetitive power flow method is developed, and a proposed acceptance capacity evaluation model is proposed to achieve the comprehensive evaluation of multi-type load acceptance capacity in active distribution networks. Finally, the effectiveness of the proposed acceptance capacity evaluation model is proven by a case study of an IEEE 33-node system, and multidimensional analysis is also conducted to investigate the impacts of DG type, DG installation location, DG proportion, and user-side energy storage system (ESS) access on the distribution network’s load acceptance capacity. Full article

Land use and planning decisions, such as the designation of urban development areas, have a significant impact on ecosystem services (Ess). In urban planning, it is essential to consider the environmental values of ecosystem services when determining urban development zones. Spatial analyses play a crucial role in guiding decision-making processes by balancing environmental value and urban expansion. This study aims to identify areas of alignment or conflict between environmental values derived from ecosystem services and settlement expansion zones according to the Environmental Regulation Plan in the Izmir metropolitan area. The study employs the InVEST^® (Integrated Valuation of Ecosystem Services and Trade-offs) model and Geographic Information Systems (GIS) to map ecosystem services. Environmental values derived from ecosystem services, such as habitat quality, carbon storage and sequestration, and sediment delivery ratio, were analyzed. The results demonstrate a trade-off between high environmental values and settlement expansion zones. The five largest conflict areas with high environmental value are located near the coast and were converted from shrubland and forest areas. This study underscores the importance of identifying and prioritizing conservation sites with high composite environmental value. Full article

Cultural ecosystem services (CESs) reflect the interaction between ecosystems and human well-being. Owing to constraints in data availability and existing methodological limitations, deriving information from non-material ecosystem attributes was inadequate. We took Yulin City, located in the northern Shaanxi Loess Plateau, as a case study. Based on open-source geospatial data and user interaction data from social media, a coupled multi-source model was applied to elucidate the spatial distribution of CESs’ supply–demand flow. The Maxent and LDA model were utilized to quantify CES supply–demand, whereas the breakpoint and gravity model were applied to explain the direction and intensity of CES flow. The results indicated the following: (1) aesthetic was the most perceivable CES in Yulin, with 27% high supply areas and four demand topics. And the perception of the educational CES was the least pronounced, with only 2% of high supply areas and two demand topics. (2) Yulin exhibited a notable mismatching in CES supply–demand, with the supply–demand matching area constituting only approximately 10%. In the center of the city, CESs displayed a spatial pattern of a supply–demand deficit, while areas farther from the city center presented a spatial pattern of a supply–demand surplus. (3) The flow of CESs followed a pattern of movement from peripheral counties to central counties and from less developed counties to more developed counties. We proposed the following targeted recommendations: introducing low-perception CESs to promote the enhancement of ecosystem services (ESs); and alleviating CES supply–demand mismatches by enhancing transportation accessibility and protecting the ecological environment. Simultaneously, attention should be directed towards the developmental disparities between counties, providing differentiated guidance for CES spatial flow. Our study provided a theoretical foundation for understanding CES supply–demand flow and offered scientific insights for the spatial development of urban CES. Full article

This study aims to explore the relationship between the provision of ecosystem services (ESs) and other territorial characteristics. Taking Italian Metropolitan Regions (MRs) as case studies, the gradient of specialization providing a set of ESs in different territorial contexts is examined using the National Strategy for Internal Areas (SNAI) territorial classification. The main objective of this research is to understand whether there is a spatial pattern of location of different ESs within metropolitan SNAI areas. Inspired by Von Thünen’s spatial economic theories, this study explores how proximity to urban centers influences land use and ES specialization. Through land use analysis and the calculation of a SI, we evaluate patterns in ES supply, based on a benefit transfer approach. The results show that the MRs provide about EUR 14.6 billion per year in benefits, equivalent to 15% of the national wealth in environmental goods and services. At the SNAI area scale, internal areas have the highest average economic values per hectare, while the central areas have lower economic values. This trend is confirmed by the calculation of the specialization index (SI) in line with Von Thünen’s theorem as follows: central areas are specialized in the provision of bundles of ESs related to intensive land use (e.g., food production), while the peripheral areas are specialized in the supply of regulation ESs related to more natural areas. The findings underline significant policy implications for metropolitan planning, stressing the need for the balanced management of ESs to address urban demands and enhance resilience. This research contributes to understanding the spatial dynamics of ES supply, offering a basis for tailored interventions in metropolitan and national contexts. Full article

Equilibrating the supply and demand for ecosystem services (ESs) is essential for sustainable development. Nonetheless, elements like policy modifications, land utilization, and climate change are profoundly transforming the dynamics of ecosystem service supply and demand (ESSD). As a result, there is an imperative necessity to methodically evaluate and predict these alterations by including both social and environmental elements. This study utilized the Henan region of the Yellow River Basin (HYRB) as a case study to forecast alterations in the supply and demand for three ESs—water production (WY), carbon storage (CS), and food production (FP)—under three scenarios for 2030 and 2050, grounded in the SSP-RCP framework. We further evaluated the supply–demand equilibrium at both grid and county degrees. The results indicate the following key findings: (1) From 2020 to 2050, there are significant spatial differences in the supply and demand of these services. While the supply of CS and FP exceeds demand, the supply of WY falls short. (2) The supply–demand ratios for WY and CS are projected to decline under all scenarios, whereas FP is expected to continue growing. Surplus areas for WY and CS are aggregated in the northwest, southwest, and central areas, while FP surpluses are found in the eastern and northern plains. Deficits for all three services are primarily located in urban areas. (3) The dominant spatial patterns of supply–demand matching also vary. WY and CS exhibit high–low agglomeration patterns, particularly in the northwest and southwest mountain regions, while FP shows low–low agglomeration, mainly in the southwest and northwest mountain areas. These findings enhance comprehension of the dynamics of ESSD, serving as a foundation for environmental preservation and sustainable advancement in the Yellow River Basin, China. Full article

This paper proposes the integration and operation of lithium-ion battery energy storage systems (ESS) in active distribution networks with high penetration of distributed generation based on renewable energy. The goal is to minimize total system costs, including energy purchasing at the substation node, as well as ESS integration, maintenance, and replacement costs over a 20-year planning horizon. The proposed master–slave methodology uses the Salp Swarm Optimization Algorithm to determine ESS location, technology, and daily operation schemes, combined with a successive approximation power flow to compute the objective function value and enforce constraints. This approach employs a discrete–continuous encoding, reducing processing times and increasing the likelihood of finding the global optimum. Validated on a 33-node test system adapted to Medellín, Colombia, the methodology outperformed five metaheuristic algorithms, achieving the highest annual savings (USD 16,605.77), the lowest average cost (USD 2,964,139.99), and the fastest processing time (345.71 s). The results demonstrate that the proposed methodology enables network operators to reduce distribution network costs effectively, offering high repeatability, solution quality, and computational efficiency. Full article

Ecosystem services (ESs) are increasingly recognized as critical to sustainable development and human well-being and are frequently used as indicators in environmental governance policies. However, existing studies mostly assess the performance of isolated single ESs, ignoring the management data needs of local governments for comprehensive gate-keeping and the easy monitoring of regional ecosystems, and lacking holistic gate-keeping indicators for local ESs. To address these shortcomings, this study assessed the spatial changes in five main ESs in the Yangtze River basin (YTRB) in China by creating a comprehensive ESs indicator (CESI) using multi-source data, and introduced the hotspot analyses and spatial econometric models to explore the driving forces of CESI. Results showed that during the study period, the CESI in the YTRB increased from 0.44 in 2000 to 0.47 in 2020. High-value areas were mainly concentrated in the hilly and mountainous regions, whereas the low-value areas were predominantly situated in the plain areas. From 2000 to 2020, the hot spots of CESI were primarily located in the middle and the lower reaches of the YTRB. Conversely, the cold spots were situated in the upper reaches of the YTRB. The regression analysis revealed a significant negative association between socioeconomic factors and CESI, while a significant positive association between natural background factors and CESI. Of the natural background factors, average precipitation has the largest positive effect on CESI, with each 1% increase resulting in up to 0.369% increase in CESI. In contrast, GDP density had the greatest negative impact on CESI, with each 1% increase triggering a reduction in CESI of up to 6.210%. The findings suggest that CESI, which integrates multiple ESs, can effectively simplify the difficulty of regional ecological regulation. The driving mechanism indicates that environmental protection policies, when combined with the natural conditions and intensity of human activities in the region, would be more coherent with varying regulatory intensities. Full article