作者机构：
[Qian Wang] School of Architecture, Changsha University of Science and Technology, Changsha, 410076, PR China;[Ping Zhao; Xiuhua Zhao; Liwei Zhu] South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, PR China;[Xia Chen] College of forestry and biotechnology, Zhejiang A&F University, Hangzhou, 311300, PR China
通讯机构：
[Ping Zhao] S;South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, PR China
摘要：
Exotic broadleaf Acacia mangium Willd., native broadleaf Schima wallichii Choisy, and native coniferous Cunninghamia lanceolata (Lamb.) Hook are main species for vegetation restoration in southern China. To assess whether these plantations remain suitable for continued planting after more than 30 years on degraded hilly lands, we investigated the hydrological effects of their canopy, litter, and soil layers. Canopy interception was calculated by subtracting measured throughfall and stemflow from total rainfall, while the water-holding capacities of litter and soil were measured using indoor immersion and ring knife methods, respectively. Our results show that the hydrological effects of the canopy and litter layers in the two broadleaf plantations were superior to those in the coniferous C. lanceolata plantation. In 2017 and 2018, the canopy interception/precipitation ratios ranked: S. wallichii (13.1–20.7%)> A. mangium (16.2–10.2%) > C. lanceolata (11.3–11.6%). Among the three plantations, the native broadleaf species S. wallichii exhibited the highest canopy interception under extreme rainfall, suggesting it may be better suited for afforestation in southern China, where extreme rainfall events are becoming increasingly frequent. For the total effective water storage capacity of litter, the ranking was: A. mangium (4.6±2.4 t·hm⁻²) > S. wallichii (2.7±1.8 t·hm⁻²) > C. lanceolata (2.4±1.4 t·hm⁻²). Exotic A. mangium had the highest water-holding capacity in both undecomposed and decomposed litter layers, and its soil water-holding capacity was superior to the native species. These results indicate that A. mangium improves hydrological functions in litter and soil layers, conserving water, delaying surface runoff, and reducing soil erosion, while its potential invasive risks to biodiversity and ecosystem stability should also be considered. For average soil water storage capacity, the ranking was: A. mangium (6373.0±54.4 t hm -2 ) > C. lanceolata (5955.1±43.0 t hm -2 ) > S. wallichii (5909.8 ±102.4 t hm -2 ). Since there were no significant differences in soil hydrological effects between S. wallichii and C. lanceolata, C. lanceolata exhibited the weakest overall hydrological benefits. Our findings highlight the critical importance of selecting appropriate species for afforestation projects to optimize hydrological functions and adapt to changing rainfall patterns in southern China.
Exotic broadleaf Acacia mangium Willd., native broadleaf Schima wallichii Choisy, and native coniferous Cunninghamia lanceolata (Lamb.) Hook are main species for vegetation restoration in southern China. To assess whether these plantations remain suitable for continued planting after more than 30 years on degraded hilly lands, we investigated the hydrological effects of their canopy, litter, and soil layers. Canopy interception was calculated by subtracting measured throughfall and stemflow from total rainfall, while the water-holding capacities of litter and soil were measured using indoor immersion and ring knife methods, respectively. Our results show that the hydrological effects of the canopy and litter layers in the two broadleaf plantations were superior to those in the coniferous C. lanceolata plantation. In 2017 and 2018, the canopy interception/precipitation ratios ranked: S. wallichii (13.1–20.7%)> A. mangium (16.2–10.2%) > C. lanceolata (11.3–11.6%). Among the three plantations, the native broadleaf species S. wallichii exhibited the highest canopy interception under extreme rainfall, suggesting it may be better suited for afforestation in southern China, where extreme rainfall events are becoming increasingly frequent. For the total effective water storage capacity of litter, the ranking was: A. mangium (4.6±2.4 t·hm⁻²) > S. wallichii (2.7±1.8 t·hm⁻²) > C. lanceolata (2.4±1.4 t·hm⁻²). Exotic A. mangium had the highest water-holding capacity in both undecomposed and decomposed litter layers, and its soil water-holding capacity was superior to the native species. These results indicate that A. mangium improves hydrological functions in litter and soil layers, conserving water, delaying surface runoff, and reducing soil erosion, while its potential invasive risks to biodiversity and ecosystem stability should also be considered. For average soil water storage capacity, the ranking was: A. mangium (6373.0±54.4 t hm -2 ) > C. lanceolata (5955.1±43.0 t hm -2 ) > S. wallichii (5909.8 ±102.4 t hm -2 ). Since there were no significant differences in soil hydrological effects between S. wallichii and C. lanceolata, C. lanceolata exhibited the weakest overall hydrological benefits. Our findings highlight the critical importance of selecting appropriate species for afforestation projects to optimize hydrological functions and adapt to changing rainfall patterns in southern China.
期刊：
Systems and Soft Computing,2025年:200269 ISSN：2772-9419
通讯作者：
Hui Tang
作者机构：
College of Architecture and Urban Planning, Hunan City University, Yiyang, 413000, China;[Wenxing You] Beijing Century Chief International Architecture Design Co., Ltd, Beijing, 110000, China;[Lu Ou] School of Architecture, Changsha University of Science & Technology, Changsha, Hunan 410000, China;Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, 413000, China;School of Architecture and Planning, Hunan University, Changsha, 410000, China
通讯机构：
[Hui Tang] C;College of Architecture and Urban Planning, Hunan City University, Yiyang, 413000, China<&wdkj&>Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, 413000, China
摘要：
Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and organizing data, then applying supervised, unsupervised, or reinforcement learning models. Supervised learning uses labeled data while unsupervised learning detects patterns in unlabeled data. Reinforcement learning optimizes rewards through trial-and-error interactions. Machine learning assists in meeting intensifying urbanization and climate change challenges. Leveraging advances in sensors, IoT, and computing enables tasks like image labeling and semantic segmentation. The techniques facilitate resilience through real-time data analytics for informed decision-making and responsive disaster management.
Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and organizing data, then applying supervised, unsupervised, or reinforcement learning models. Supervised learning uses labeled data while unsupervised learning detects patterns in unlabeled data. Reinforcement learning optimizes rewards through trial-and-error interactions. Machine learning assists in meeting intensifying urbanization and climate change challenges. Leveraging advances in sensors, IoT, and computing enables tasks like image labeling and semantic segmentation. The techniques facilitate resilience through real-time data analytics for informed decision-making and responsive disaster management.
通讯机构：
[Zheng, BH ] C;Cent South Univ, Sch Architecture & Art, Changsha 410083, Peoples R China.
关键词：
Urban microclimate;Outdoor thermal comfort;Street interface;Universal thermal climate index (UTCI);ENVI-met;Old city of Changsha
摘要：
The challenge of the urban thermal environment stands as a pivotal obstacle in enhancing urban habitation, with its most conspicuous manifestation occurring during the summer months. The urban configuration intertwines with the thermal milieu, and its meticulous refinement is critical to ameliorating thermal conditions. Notably, streets, constituting two-thirds of the urban expanse, assume paramount importance. Delving into the nexus between street interface morphology and the thermal environment carries practical implications. The current corpus of street form research exhibits a conspicuous oversight in attending to the street interface, with a noticeable need for more exploration into its symbiosis with the thermal ambience. This study, therefore, directs its focus toward the nuanced examination of street interface morphology. Employing the method of constructing morphological models, we utilize ENVI-met software to simulate and analyze the thermal environment. The Universal Thermal Climate Index (UTCI) serves as the yardstick for evaluating thermal conditions, elucidating the influence of street interface morphology on the summer thermal environment of streets. The findings unveil a discernible correlation: for east-west streets, diminished interface density and concavity, coupled with an augmented street aspect ratio and interface height dislocation, yield superior street pedestrian thermal comfort. The interface height ratio index emerges as a particularly noteworthy factor, with the nadir of thermal comfort occurring at an interface height ratio1. Moreover, streets boasting elevated interfaces on the north side exhibit enhanced thermal comfort within similar interface height ratios. In the case of north-south streets, heightened interface density and street aspect ratio, juxtaposed with diminished interface concavity and height dislocation, parallelly yield enhanced thermal comfort. Optimal thermal comfort materializes when the interface height ratio equals 1. Moreover, streets featuring elevated interfaces on the east side manifest superior thermal comfort within equivalent interface height ratios. The culminating phase of this inquiry entails the optimization simulation of select streets within the ancient precincts of Changsha. The outcomes underscore a discernible enhancement in the thermal comfort of both east-west and north-south streets post-optimization, affirming the efficacy of street interface shape transformations in efficaciously augmenting the summer thermal environment of urban streets.
The challenge of the urban thermal environment stands as a pivotal obstacle in enhancing urban habitation, with its most conspicuous manifestation occurring during the summer months. The urban configuration intertwines with the thermal milieu, and its meticulous refinement is critical to ameliorating thermal conditions. Notably, streets, constituting two-thirds of the urban expanse, assume paramount importance. Delving into the nexus between street interface morphology and the thermal environment carries practical implications. The current corpus of street form research exhibits a conspicuous oversight in attending to the street interface, with a noticeable need for more exploration into its symbiosis with the thermal ambience. This study, therefore, directs its focus toward the nuanced examination of street interface morphology. Employing the method of constructing morphological models, we utilize ENVI-met software to simulate and analyze the thermal environment. The Universal Thermal Climate Index (UTCI) serves as the yardstick for evaluating thermal conditions, elucidating the influence of street interface morphology on the summer thermal environment of streets. The findings unveil a discernible correlation: for east-west streets, diminished interface density and concavity, coupled with an augmented street aspect ratio and interface height dislocation, yield superior street pedestrian thermal comfort. The interface height ratio index emerges as a particularly noteworthy factor, with the nadir of thermal comfort occurring at an interface height ratio1. Moreover, streets boasting elevated interfaces on the north side exhibit enhanced thermal comfort within similar interface height ratios. In the case of north-south streets, heightened interface density and street aspect ratio, juxtaposed with diminished interface concavity and height dislocation, parallelly yield enhanced thermal comfort. Optimal thermal comfort materializes when the interface height ratio equals 1. Moreover, streets featuring elevated interfaces on the east side manifest superior thermal comfort within equivalent interface height ratios. The culminating phase of this inquiry entails the optimization simulation of select streets within the ancient precincts of Changsha. The outcomes underscore a discernible enhancement in the thermal comfort of both east-west and north-south streets post-optimization, affirming the efficacy of street interface shape transformations in efficaciously augmenting the summer thermal environment of urban streets.
摘要：
This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.
This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.
通讯机构：
[Wang, CAN ] W;Wuhan Univ, Sch Urban Design, Wuhan 430072, Peoples R China.
关键词：
sustainable conservation;destruction of stone artifacts;temperature and humidity damage to stones;black stain on stone;stone damage by air pollutants;monuments weather damage
摘要：
Around the world, a large number of stone artifacts have been exposed to air for long periods of time, showing multiple types of deterioration that have attracted widespread attention. Among them, there is an often overlooked deterioration of stone artifacts, i.e., black stains on the surface of the calcareous stone, which are tightly bonded to the substrate as a result of the long-term deposition of air pollution. However, due to the current lack of a clear understanding of the black stains, people often tend to use the wrong cleaning and conservation methods, which is not conducive to sustainable conservation. Therefore, there is an urgent need to comprehensively recognize the black stains in terms of material properties and environmental sustainability to guide scientific sustainable conservation methods. To this end, in this paper, we take the black stains observed on marble buildings in the Xianling Tomb, China, as an example, and for the first time, we aim to create a comprehensive understanding of black deposition from the aspects of material properties and environmental characteristics. Multi-analytical approaches, including polarized light microscopy, X-ray fluorescence (XRF), and scanning electron microscopy with energy dispersive X-ray spectrometry (SEM-EDS), were employed to discern the differences between the substrate and black stains. The results revealed that the formation of black stains was attributed to prolonged exposure to various air pollutants (PM, SO2, NO2, CO, and O3). Subsequently, observational data from 2015 to 2023 were utilized to investigate the temporal evolution of local air pollutants and their coupled resonances. Multi-scale variations (annual, seasonal, monthly, weekly, and daily) of pollutant concentration sequences were identified, which helps us to have a clearer perception and to proactively control air pollutants in the region from different cycles. In addition, wavelet coherence (WTC) demonstrated significant time-scale dependency in correlation with air pollutants, which provides effective data support for the coordinated control of air pollutants. This study reveals the mechanism of black stain deterioration on stone artifact surfaces, provides data support for the control and prediction of air pollutants oriented to the sustainable conservation of stone artifacts, and provides a novel and comprehensive approach to the scientific knowledge and sustainable conservation of stone artifacts.
通讯机构：
[Tian, Y ] C;Changsha Univ Sci Technol, Coll Architecture, Changsha, Hunan, Peoples R China.
摘要：
Ensuring pedestrian safety is crucial for establishing fair and sustainable transportation systems. However, certain demographics face disproportionately higher risks, necessitating age-appropriate policy and design strategies. This study provides a comprehensive analysis of the relationships between objectively measured road infrastructure attributes and pedestrian accident frequencies involving vulnerable groups in Hunan Province, China. By leveraging detailed historical crash records linked to spatially-explicit infrastructure data, the research team employed advanced count regression modeling techniques, including negative binomial (NB) and zero truncated tail negative binomial (ZTNB) specifications, to systematically evaluate the safety impacts of roadway functional classification, intersection design, traffic controls, alignment geometry, pedestrian segregation, land use context, and traffic volumes. The results revealed that the ZTNB approach, which accounted for the excess zero observations inherent to the crash data, provided statistically superior model fit compared to the standard NB formulation. The ZTNB estimation results offered robust empirical evidence regarding key infrastructure risk factors, highlighting that while higher-order roadways exhibited lower pedestrian accident likelihoods, elements such as multi-leg intersections, lack of traffic controls, curved alignments, and absence of segregated facilities correlated with elevated hazards. Older adults and children are particularly susceptible to accidents on major highways and are more prone to traffic incidents on regular roads as opposed to specialized areas like tunnels and intersections. Importantly, the analysis revealed varying safety impacts among different user groups, underscoring the significance of considering the unique requirements and vulnerabilities of diverse pedestrian populations in transportation planning and design. Overall, the findings offer robust empirical evidence to guide development of tailored interventions that consider the unique capacities and exposures of different pedestrian populations. The age-segmented analyses also contribute transportation equity insights for achieving Vision Zero goals through inclusive infrastructure design.
摘要：
Understanding the tourism resource network attention is crucial for promoting sustainable tourism development. This study utilized multi-source data to assess tourism resource network attention in Western Hunan, with GIS spatial analysis and the Geodetector method applied to identify spatial patterns and influencing factors. The results indicate a distinct “dual-core” spatial clustering in network attention, with natural landscape resources centralized in Zhangjiajie and cultural landscape resources in Xiangxi Prefecture. Recreational tourism resources exhibit a similar clustering pattern around these primary and secondary centers. The factors and intensities influencing network attention differ by tourism resource type. For overall tourism resources, natural landscapes, and cultural landscapes, tourist attractions rating (X11) and attraction clustering degree (X12) are the primary drivers, with the strongest impact on natural landscapes (q = 0.648, 0.373), followed by overall resources (q = 0.361, 0.216) and cultural landscapes (q = 0.311, 0.206). In contrast, recreational resources are most influenced by nearby attractions and tourism service capacity (q(X12) = 0.743, q(X15) = 0.620), alongside notable effects from regional factors related to economic development, industrial structure, and tourism development (X1–X9). The interaction between inherent tourism resource characteristics (X10–X15) and regional environmental factors (X1–X9) enhances the driving effect on tourism resource network attention. These findings inform differentiated, resource-specific tourism planning strategies for sustainable development in Western Hunan, promoting balanced regional growth and optimized resource management through a data-driven approach.
作者：
He, Peng;Ali, Ali B. M.;Hussein, Zahraa Abed;Singh, Narinderjit Singh Sawaran;Bains, Pardeep Singh;...
期刊：
Energy and Buildings,2025年332:115428 ISSN：0378-7788
通讯作者：
He, P;Baghoolizadeh, M
作者机构：
[He, P; He, Peng] Changsha Univ Sci & Technol, Sch Architecture, Changsha 410076, Peoples R China.;[He, P; He, Peng] Hunan Planning Inst Land & Resources, Hunan Key Lab Land Resources Evaluat & Utilizat, Changsha 410119, Peoples R China.;[Ali, Ali B. M.] Univ Warith Al Anbiyaa, Coll Engn, Air Conditioning Engn Dept, Karbala, Iraq.;[Hussein, Zahraa Abed] Al Manara Coll Med Sci, Amarah, Maysan, Iraq.;[Singh, Narinderjit Singh Sawaran] INTI Int Univ, Fac Data Sci & Informat Technol, Nilai 71800, Malaysia.
通讯机构：
[He, P ] C;[Baghoolizadeh, M ] S;Changsha Univ Sci & Technol, Sch Architecture, Changsha 410076, Peoples R China.;Hunan Planning Inst Land & Resources, Hunan Key Lab Land Resources Evaluat & Utilizat, Changsha 410119, Peoples R China.;Shahrekord Univ, Dept Mech Engn, Shahrekord 8818634141, Iran.
摘要：
The present research work develops a new approach for the optimization of thermostat setting and insulation designs in residential buildings located in various Iranian climates, including hot-humid, arid, temperate, and cool regions. The objective functions are set to minimize the construction cost, consumed electricity cost, and PPD to improve thermal comfort. Advanced computational techniques are integrated in a structured way to achieve the mentioned objectives. Numerical modeling is done through the simulation of building energy performance and thermal comfort using EnergyPlus. The exact mathematical relations between design variables and objective functions, which were heating setpoint and cooling setpoint, insulation thickness, and thermal conductivity, were identified using Multi-Polynomial Regression. MPR model has been validated respect to a wide set of statistical measures that included but were not limited to R², RMSE, and MAE for its high predictive accuracy. Then, multi-objective optimization is performed through NSGA-II, a well-known multi-objective optimization algorithm, which provides a Pareto front of optimal solutions balancing energy efficiency, cost, and comfort. Shannon's entropy method assigns weights to the Pareto-optimal solutions, whereas the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) selects the most suitable configurations for each city. Calculations show a great reduction in energy consumption to up to 82.66% at Bandar Abbas, with very important improvements in comfort, where the PPD is reduced between 31.1% to 56.3%. The predictive capacity of the MPR model was confirmed by this study, from the value of R², close to 1. The cost-effectiveness of the proposed solutions is underlined by minimizing construction and energy costs while preserving occupant comfort. This innovative approach adapts optimization strategies to regional climatic characteristics, providing practical solutions for sustainable and cost-effective building designs. The integration of advanced machine learning and genetic algorithms offers a scalable framework for future energy-efficient construction practices worldwide, contributing to reduced carbon footprints and enhanced occupant well-being. By addressing the limitations of previous studies and introducing a clear, structured methodology, this research provides valuable insights and practical tools for optimizing residential building performance in diverse climates.
The present research work develops a new approach for the optimization of thermostat setting and insulation designs in residential buildings located in various Iranian climates, including hot-humid, arid, temperate, and cool regions. The objective functions are set to minimize the construction cost, consumed electricity cost, and PPD to improve thermal comfort. Advanced computational techniques are integrated in a structured way to achieve the mentioned objectives. Numerical modeling is done through the simulation of building energy performance and thermal comfort using EnergyPlus. The exact mathematical relations between design variables and objective functions, which were heating setpoint and cooling setpoint, insulation thickness, and thermal conductivity, were identified using Multi-Polynomial Regression. MPR model has been validated respect to a wide set of statistical measures that included but were not limited to R², RMSE, and MAE for its high predictive accuracy. Then, multi-objective optimization is performed through NSGA-II, a well-known multi-objective optimization algorithm, which provides a Pareto front of optimal solutions balancing energy efficiency, cost, and comfort. Shannon's entropy method assigns weights to the Pareto-optimal solutions, whereas the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) selects the most suitable configurations for each city. Calculations show a great reduction in energy consumption to up to 82.66% at Bandar Abbas, with very important improvements in comfort, where the PPD is reduced between 31.1% to 56.3%. The predictive capacity of the MPR model was confirmed by this study, from the value of R², close to 1. The cost-effectiveness of the proposed solutions is underlined by minimizing construction and energy costs while preserving occupant comfort. This innovative approach adapts optimization strategies to regional climatic characteristics, providing practical solutions for sustainable and cost-effective building designs. The integration of advanced machine learning and genetic algorithms offers a scalable framework for future energy-efficient construction practices worldwide, contributing to reduced carbon footprints and enhanced occupant well-being. By addressing the limitations of previous studies and introducing a clear, structured methodology, this research provides valuable insights and practical tools for optimizing residential building performance in diverse climates.
通讯机构：
[Wang, JJ ] H;[Liu, YY ] C;Changsha Univ Sci & Technol, Sch Architecture, Changsha 410114, Peoples R China.;Changsha Univ Sci & Technol, Res Ctr Human Settlements & Land Spatial Planning, Changsha 410076, Peoples R China.;Hunan Univ, Coll Environm Sci & Engn, Changsha 410082, Peoples R China.
关键词：
Single-atom catalysts;Peroxymonosulfate;Antibiotic contamination;Singlet oxygen;High-value metal-oxygen specie
摘要：
Atomic clusters have been recognized for boosting interactions with single-atom sites and activating peroxymonosulfate (PMS) to degrade pollutants. However, research on the synergies between different metals in these clusters and their impact on enhancing single-atom activity remains limited. This paper introduces an iron-cluster-modified manganese single-atom catalyst (FeMn ac -NC) exhibiting exceptional catalytic activity. At low doses of the catalyst (FeMn ac -NC, 0.05 g/L) and the oxidant (PMS, 0.2 g/L), the FeMn ac -NC/PMS system recorded an impressive removal efficiency of 91.0 % in 5 min, exhibiting a k obs of 0.1038 min −1 . Within this system, the active oxygen species identified included singlet oxygen and high-valent metal–oxygen species. X-ray photoelectron spectroscopy analysis revealed a significant presence of pyrrolic nitrogen in the material, which binds with Mn to create the primary active site. Based on calculations using the density functional theory, the redox cycling between iron clusters and manganese single atoms has been proved to improve the activation efficiency of the system. The system demonstrates high tolerance to environmental media containing anions and dissolved organic matter, showing notable degradation performance over a wide pH range. This research provides valuable insights for the development of high-performance catalysts that is well-suited for practical environmental purification applications.
Atomic clusters have been recognized for boosting interactions with single-atom sites and activating peroxymonosulfate (PMS) to degrade pollutants. However, research on the synergies between different metals in these clusters and their impact on enhancing single-atom activity remains limited. This paper introduces an iron-cluster-modified manganese single-atom catalyst (FeMn ac -NC) exhibiting exceptional catalytic activity. At low doses of the catalyst (FeMn ac -NC, 0.05 g/L) and the oxidant (PMS, 0.2 g/L), the FeMn ac -NC/PMS system recorded an impressive removal efficiency of 91.0 % in 5 min, exhibiting a k obs of 0.1038 min −1 . Within this system, the active oxygen species identified included singlet oxygen and high-valent metal–oxygen species. X-ray photoelectron spectroscopy analysis revealed a significant presence of pyrrolic nitrogen in the material, which binds with Mn to create the primary active site. Based on calculations using the density functional theory, the redox cycling between iron clusters and manganese single atoms has been proved to improve the activation efficiency of the system. The system demonstrates high tolerance to environmental media containing anions and dissolved organic matter, showing notable degradation performance over a wide pH range. This research provides valuable insights for the development of high-performance catalysts that is well-suited for practical environmental purification applications.
摘要：
This comprehensive review critically examines current methodologies and optimization strategies for designing indoor thermal environments in educational buildings amid the challenges of global climate change and energy demands. The paper evaluates existing research methods, such as numerical simulations, data-driven models, and field measurements, revealing significant limitations in addressing the complex and dynamic nature of educational environments. It highlights the overemphasis on energy efficiency while neglecting user comfort and individual differences, such as students' physiological and psychological needs. The review underscores the necessity of integrating human-centered design strategies, climate adaptability, and interdisciplinary approaches to improve building performance and enhance student well-being. Future research should focus on developing multimodal data fusion frameworks, applying AI-based optimization, and incorporating emerging technologies like BIM and IoT for dynamic management. By advocating for more adaptable and sustainable thermal environment strategies, this study provides a foundation for advancing educational building design in response to climate change and energy crises.
期刊：
FRONTIERS IN PLANT SCIENCE,2025年16:1533251 ISSN：1664-462X
通讯作者：
Zhuo, ZH
作者机构：
[Gan, Tingjiang] Mianyang Teachers Coll, Engn Res Ctr Chuanxibei Rural Human Settlement RHS, Mianyang, Peoples R China.;[He, Zhipeng; Zhang, Honghua; Zhuo, Zhihang; Xu, Danping; Wei, Xinju; Zhuo, ZH] China West Normal Univ, Coll Life Sci, Nanchong, Peoples R China.;[Chen, Juan] Changsha Univ Sci & Technol, Coll Architecture, Changsha, Peoples R China.
通讯机构：
[Zhuo, ZH ] C;China West Normal Univ, Coll Life Sci, Nanchong, Peoples R China.
关键词：
H. rhamnoides;biomod2;climate change;environmental variable;potential distribution
摘要：
INTRODUCTION: Hippophae rhamnoides, a temperate species with a transcontinental distribution spanning Eurasia, demonstrates preferential establishment in water-limited ecosystems (arid/semi-arid zones), particularly occupying high-elevation niches with skeletal soils and high solar flux. This ecologically significant plant, prized for dual ecological provisioning and economic services, shows biogeographic concentration in China's northern desertification belts, northwestern Loess Plateau, and southwestern montane corridors. Studying the possible areas where H. rhamnoides may be found can offer a scientific foundation for the protection and sustainable management of its resources. METHODS: This study utilized the biomod2 software to assess an integrated model based on 312 distribution points and 23 environmental factors. Furthermore, a modeling analysis was conducted to examine how the geographical distribution of H. rhamnoides changes over time under the SSP245 scenario. RESULTS: The findings show that the distribution of H. rhamnoides is primarily affected by three factors: annual mean temperature, temperature seasonality and mean temperature of the coldest quarter. Currently, H. rhamnoides is predominantly distributed in the provinces of Shanxi, Shaanxi, Gansu, Hebei, Yunnan, Xinjiang, Tibet, Sichuan, Qinghai, and Ningxia. The suitable habitat covers an area of 212.89×10⁴ km², which represents 22.15% of China's total land area. Within this region, high, medium, and low suitability areas make up 23.15%, 22.66%, and 54.20% of the suitable habitat, respectively. DISCUSSION: In the future, the centroid of the suitable habitat for H. rhamnoides is expected to gradually shift northwest, with a trend of increasing suitability in the west and decreasing suitability in the east. This study aims to provide an in-depth exploration of the distribution of H. rhamnoides and the influence of environmental factors on it from a geographical perspective. These results are important for improving the conservation, management, cultivation, and propagation of H. rhamnoides, while also offering a scientific foundation for the research of other valuable plant species.
摘要：
Excessive environmental vibrations generated by urban traffic pose adverse effects on nearby structures and residents. These vibrations are predominantly carried by surface waves, which are localized within the surface layer of soil. The isolation of surface waves through the embedding of periodic wave barriers in soils between the source and the receiver has gained significant attention in recent years. In this paper, a novel approach is proposed for isolating surface waves induced by urban traffic through the use of variable depth infilled trenches. This innovative design not only achieves efficient surface wave isolation but also minimizes the consumption of structural materials. Based on the measured dominant frequency range of rail transit and the available soil parameters, variable depth infilled trenches are designed with suitable dimensions. The eigenvalue equation is solved using the finite element method to derive the dispersion relations and bandgap of identical regularly spaced trenches. To study the efficacy of the proposed structure, a finite element model of the soil-infilled trench system is developed using COMSOL. The mechanism underlying the isolation of surface wave is elucidated, and the effect of variable angle alpha on the isolation efficiency within 40-50 Hz eta((40-50Hz)) of surface waves is studied. The results of this study reveal that for variable angle alpha of 15 degrees, the surface wave isolation efficiency within 40-50 Hz eta((40-50Hz)) is 90.9 % and 92.5 % for uniformly increasing depth infilled trenches and uniformly decreasing depth infilled trenches, respectively. Although the surface wave isolation efficiencies predicted for the variable depth infilled trench arrangements are only 93.8 % and 95.5 % of those predicted for the regularly spaced identical infilled trenches, the variable depth arrangements result in a remarkable 34 % reduction in material usage. These findings highlight the potential of the proposed variable depth infilled trenches as a cost-effective and efficient solution for surface wave isolation.
摘要：
Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns. Understanding the differential influences of road physical design attributes on crash frequencies for these two groups is critical for developing targeted safety interventions. Considering that the zero-truncated characteristic of the data is uncertain, the results of the zero-truncated negative binomial models and traditional negative binomial models are calculated to seek the better model. The result revealed that the road surface conditions and vertical and horizontal curvature have greater influence on both pedestrian and driver compared to number of lanes and speed limit. And speed limits were more pronounced for pedestrian crash frequency than driver group. Conversely, the effect of different types of intersections was stronger for driver crash frequency. The differential influences of road physical design attributes on traffic crash frequencies for pedestrians versus drivers highlight the importance of adopting a user-centric approach to transportation safety planning and infrastructure design. Tailoring interventions to address the unique needs and vulnerabilities of different road user groups can lead to more effective safety improvements and better overall traffic safety outcomes.
摘要：
In response to worldwide calls for promoting health and well-being, there is growing interest in creating restorative environments. Although restorative environments can be perceived by multiple sensory modalities, visual studies dominated the majority of restorative research, while olfaction is a frequently overlooked yet important sense. Grounded in Attention Restoration Theory (ART) and cross-modal interaction of olfaction and vision, this research seeks to investigate the independent and interactive effects of vision and olfaction on the perceived restorativeness of a Metasequoia walkway in urban green space. The visual stimulus was a 360-degree virtual reality (VR) tour in a 200-meter-long Metasequoia walkway, and the olfactory stimulus was Metasequoia essential oil extracted from the tree leaves. Based on a stress recovery experiment, 120 participants were randomly assigned to one of four groups: control, vision, olfaction, and combination. Psychological evaluations (semantic differential scale [SDS] and perceived restorativeness scale [PRS]) and physiological measurements (systolic blood pressure [SBP], diastolic blood pressure [DBP], heart rate [HR] and blood oxygen level [BOL]) were used as indicators of restorative effects. The findings reveal that a combination of visual and olfactory stimulation can contribute more to restorative effects compared to a single stimulus, in terms of both physiological and psychological indicators. This calls for a greater focus on the effects of vision and olfaction towards more sustainable landscape design and management.
In response to worldwide calls for promoting health and well-being, there is growing interest in creating restorative environments. Although restorative environments can be perceived by multiple sensory modalities, visual studies dominated the majority of restorative research, while olfaction is a frequently overlooked yet important sense. Grounded in Attention Restoration Theory (ART) and cross-modal interaction of olfaction and vision, this research seeks to investigate the independent and interactive effects of vision and olfaction on the perceived restorativeness of a Metasequoia walkway in urban green space. The visual stimulus was a 360-degree virtual reality (VR) tour in a 200-meter-long Metasequoia walkway, and the olfactory stimulus was Metasequoia essential oil extracted from the tree leaves. Based on a stress recovery experiment, 120 participants were randomly assigned to one of four groups: control, vision, olfaction, and combination. Psychological evaluations (semantic differential scale [SDS] and perceived restorativeness scale [PRS]) and physiological measurements (systolic blood pressure [SBP], diastolic blood pressure [DBP], heart rate [HR] and blood oxygen level [BOL]) were used as indicators of restorative effects. The findings reveal that a combination of visual and olfactory stimulation can contribute more to restorative effects compared to a single stimulus, in terms of both physiological and psychological indicators. This calls for a greater focus on the effects of vision and olfaction towards more sustainable landscape design and management.
摘要：
With the changes in global climate and rapid urbanization, identifying the contribution of urban morphology to the thermal environment under different scenarios could be helpful in proposing differentiated optimization responses of different scenarios for improving the thermal environment by means of natural cooling. This study calculated 2D and 3D metrics and retrieved surface temperature based on building vector data, land use, electronic map, the remote sensing images. Then, the study of spatial scale sensitivity was developed to build a nested multi-scale Local Climate Zone (LCZ) (NMSLCZ) map. Finally, the eXtreme Gradient Boost (XGBoost) regression model was performed to explore the relative contributions of 2D and 3D morphologies of different LCZ scenarios to surface temperatures. The results of scale sensitivity analysis showed the size of the optimal spatial scale decreased with the increase in building height. The 3D morphologies show more significant effects on LST variations than 2D morphologies. The surface temperature mainly by built type is significantly higher than that mainly by land cover type. Scenarios representing dense trees, shrubs, low vegetation, and water have significant cooling effects. In the scenarios of built types, the surface temperature of compact and large low-rise buildings is higher than that of the other building forms. Our findings provide a new perspective for LCZ mapping of scale optimization of the thermal environment. Meanwhile, the contributions of 2D and 3D morphologies on LSTs could help urban planners and managers understand the impacts of climate change and propose relevant strategies toward sustainable cities.
With the changes in global climate and rapid urbanization, identifying the contribution of urban morphology to the thermal environment under different scenarios could be helpful in proposing differentiated optimization responses of different scenarios for improving the thermal environment by means of natural cooling. This study calculated 2D and 3D metrics and retrieved surface temperature based on building vector data, land use, electronic map, the remote sensing images. Then, the study of spatial scale sensitivity was developed to build a nested multi-scale Local Climate Zone (LCZ) (NMSLCZ) map. Finally, the eXtreme Gradient Boost (XGBoost) regression model was performed to explore the relative contributions of 2D and 3D morphologies of different LCZ scenarios to surface temperatures. The results of scale sensitivity analysis showed the size of the optimal spatial scale decreased with the increase in building height. The 3D morphologies show more significant effects on LST variations than 2D morphologies. The surface temperature mainly by built type is significantly higher than that mainly by land cover type. Scenarios representing dense trees, shrubs, low vegetation, and water have significant cooling effects. In the scenarios of built types, the surface temperature of compact and large low-rise buildings is higher than that of the other building forms. Our findings provide a new perspective for LCZ mapping of scale optimization of the thermal environment. Meanwhile, the contributions of 2D and 3D morphologies on LSTs could help urban planners and managers understand the impacts of climate change and propose relevant strategies toward sustainable cities.
摘要：
As China declared COVID-19 a "Category B disease," marking the conclusion of a three-year pandemic prevention and control effort, rural communities—especially those involved in Poverty Alleviation Relocation (PAR) projects—have received limited research attention despite significant economic and psychological impacts. This study investigates how COVID-19 affected social integration between locals and migrants within these relocated rural communities. Using a PAR community typology based on spatial and demographic patterns, four types were identified: centralized, adjacent, enclave, and infill. Socio-spatial isolation indices assessed social and spatial isolation levels among migrants across three phases: 2019 (before the pandemic), 2021 (during the pandemic), and 2023 (after the pandemic). Comparative analysis across phases and community types revealed varying impacts of COVID-19 prevention measures. Key findings include: 1) COVID-19 temporarily enhanced social integration, with a V-shaped evolution in social isolation levels—an initial decrease followed by an increase. 2) Centralized communities demonstrated the most sustained integration, while adjacent and infill types were moderately affected in the short term, and enclave communities were the least affected. 3) Factors such as "inequality between inside and outside groups," enhanced telecommunications, pandemic-related public activities, and spatial characteristics promoted interaction between locals and migrants. This study enriches the understanding of COVID-19's social impacts on vulnerable communities, offering insights for disaster risk assessment and sustainable development strategies in pro-poor communities.
As China declared COVID-19 a "Category B disease," marking the conclusion of a three-year pandemic prevention and control effort, rural communities—especially those involved in Poverty Alleviation Relocation (PAR) projects—have received limited research attention despite significant economic and psychological impacts. This study investigates how COVID-19 affected social integration between locals and migrants within these relocated rural communities. Using a PAR community typology based on spatial and demographic patterns, four types were identified: centralized, adjacent, enclave, and infill. Socio-spatial isolation indices assessed social and spatial isolation levels among migrants across three phases: 2019 (before the pandemic), 2021 (during the pandemic), and 2023 (after the pandemic). Comparative analysis across phases and community types revealed varying impacts of COVID-19 prevention measures. Key findings include:
1) COVID-19 temporarily enhanced social integration, with a V-shaped evolution in social isolation levels—an initial decrease followed by an increase.
2) Centralized communities demonstrated the most sustained integration, while adjacent and infill types were moderately affected in the short term, and enclave communities were the least affected.
3) Factors such as "inequality between inside and outside groups," enhanced telecommunications, pandemic-related public activities, and spatial characteristics promoted interaction between locals and migrants.
This study enriches the understanding of COVID-19's social impacts on vulnerable communities, offering insights for disaster risk assessment and sustainable development strategies in pro-poor communities.
