Spatial-temporal Distribution Research Articles

Probing Spatial Energy Flow in Plasmonic Catalysts from Charge Excitation to Heating: Nonhomogeneous Energy Distribution as a Fundamental Feature of Plasmonic Chemistry.

Plasmonic catalysts use light to drive chemical reactions. One critical question is how light energy moves at nanoscales in these complex systems, leading to chemical transformations. In this contribution, we map out this energy flow by developing approaches to measure spatial temperature distributions in heterogeneous plasmonic catalysts, consisting of three-dimensional networks of plasmonic nanoparticles anchored on an oxide support. We survey the local temperatures of molecules adsorbed on catalytically active plasmonic nanoparticles, the nanoparticles themselves, and the catalyst support, under steady-state continuous-wave illumination. We reveal the existence of large temperature gradients, in which the local temperatures of the molecules, nanoparticles, and the surrounding environment can vary greatly. We show that these temperature gradients are a natural consequence of plasmon relaxation, involving the interconversion between electromagnetic light energy, electronic excitations, and heating of various entities as these electronic excitations relax. The presence of these gradients is a fundamental and unique feature of gas-phase plasmonic catalysis.

Modeling Urban Temperature Using Measurements from Mobile and Stationary Monitoring Stations

Heat waves are occurring more frequently worldwide as global warming continues, and urban heat islands can threaten conventional life in cities. Measuring, analyzing, and simulating weather data at fine spatial and temporal scales are essential to prevent and reduce the damage caused by extreme heat waves. In urban environments, handling complex micrometeorological situations using current meteorological stations and global simulation models (e.g., weather research forecasting models) is challenging. In this study, the thermal environments of urban areas were measured using a mobile meteorological measurement platform. Both mobile and stationary datasets were incorporated into the meteorological modeling process to simulate the spatial and temporal distribution of temperature. Additionally, various mobile observation implementation scenarios for temperature modeling were examined. We compared simulation combinations with the temperature field generated from the total dataset to obtain a better sampling campaign and properly incorporate mobile data scenarios. When collecting mobile data, it is important to consider spatial features to improve the efficiency of sampling programs. This can substantially reduce the cost of mobile data collection, together with the sensor error bound.

Ultrastable and Low-Threshold Two-Photon-Pumped Amplified Spontaneous Emission from CsPbBr3/Ag Hybrid Microcavity.

Halide perovskite materials have garnered significant research attention due to their remarkable performance in both photoharvesting photovoltaics and photoemission applications. Recently, self-assembled CsPbBr3 superstructures (SSs) have been demonstrated to be promising lasing materials. In this study, we report the ultrastable two-photon-pumped amplified stimulated emission from a CsPbBr3 SS/Ag hybrid microcavity with a low threshold of 0.8 mJ/cm2 at room temperature. The experimental results combined with numerical simulations show that the CsPbBr3 SS exhibits a significant enhancement in the electromagnetic properties in the hybrid microcavity on Ag film, leading to the uniform spatial temperature distribution under the irradiation of a pulsed laser, which is conducive to facilitate the recrystallization process of the QDs and improve their structural integrity and optical properties. This study provides a new idea for the application of CsPbBr3/Ag hybrid microcavity in photonic devices, demonstrating its potential in efficient optical amplification and upconversion lasers.

Observation of Statistical Characteristics and Vertical Structures of Surface Warm Cyclonic Eddies and Cold Anticyclonic Eddies in the North Pacific Subtropical Countercurrent Region

Conventional wisdom about mesoscale eddies is that cyclonic (anticyclonic) eddies are commonly associated with cold(warm) surface cores. Nevertheless, plenties of surface warm cyclonic eddies (WCEs) and cold anticyclonic eddies (CAEs) in the North Pacific Subtropical Countercurrent (STCC) region are observed by a synergistic investigation based on data from satellite altimetry, microwave radiometer, and Argo float profiles in this study. The results indicate that these two types of abnormal eddies (WCEs and CAEs) are prevalent in the STCC region, comprising approximately 30% of all eddies detected via satellite observations. We then analyze their spatial-temporal distribution characteristics and composite vertical structures. A statistical comparison with surface cold cyclonic eddies (CCEs) and warm anticyclonic eddies (WAEs) reveals notable differences between the anomalous and typical eddies. Additionally, we present the composite vertical structures of temperature and salinity anomalies for the anomalous eddies across five delineated subregions within an eddy-coordinate system. Furthermore, the close relationship between these abnormal eddies and subsurface-intensified mesoscale eddies are discussed.

Spatiotemporal distribution and ecological factors of brucellosis among children from 2016 to 2020 in Inner Mongolia, China

ObjectiveIn recent years, the increasing incidence of brucellosis in children has become more serious. However, relatively few studies have been conducted to characterize the spatialtemporal distribution of brucellosis in children. This study aimed to analyze the spatiotemporal distribution characteristics and ecological influencing factors of brucellosis incidence among children in Inner Mongolia.MethodsThis study used data on brucellosis incidence in children aged 0–14 years reported in Inner Mongolia from 2016 to 2020. A Bayesian model was used to analyze the spatial and temporal distribution of brucellosis in children from 2016 to 2020 in Inner Mongolia. Geographical weighted regression model was used to analyze the ecological factors related to the incidence of brucellosis in children.ResultBayesian spatiotemporal analysis indicated that the highest brucellosis risk and increased disease incidence were observed in Hinggan, Inner Mongolia, in children aged 0–14 years. Alxa had the lowest risk but the incidence rate increased rapidly. The incidence of childhood brucellosis was positively associated with the number of sheep at the year-end (β: 2.5909 ~ 2.5926, P < 0.01), average temperature (β: 2.8978 ~ 2.9030, P < 0.05), and precipitation level (β: 3.3261 ~ 3.3268, P < 0.01).ConclusionFrom 2016 to 2020, the overall incidence of brucellosis in children in Inner Mongolia showed an upward trend, with cases exhibiting spatial aggregation. We should focus on areas where the incidence of brucellosis in children is rising rapidly. The incidence of childhood brucellosis was associated with the number of sheep at the year-end, average temperature and precipitation level.Implications and contributionThe findings suggest that brucellosis in children is not to be taken lightly. For children should also focus on protection, take corresponding protective measures. While we focus on high-risk areas, we must also monitor areas where the risk of disease is low, but the incidence is rising fast, to prevent outbreaks in low-risk areas from becoming high-risk areas.

Research on the Spatial–Temporal Distribution and Morphological Characteristics of Ancient Settlements in the Sichuan Basin

An investigation into the spatial–temporal distribution characteristics of ancient settlements and their relationship with the environment in the Sichuan Basin can enhance our understanding of the evolution of the regional human–land relationship. Utilizing kernel density analysis by GIS, this paper obtained the spatial distribution characteristics of 1100 settlements in the Neolithic, Shang–Zhou, and Qin to Southern Dynasties periods. Subsequently, a GIS spatial analysis was performed to examine the distribution of these settlements in relation to the natural environment, focusing on four aspects: elevation, slope, aspect, and water buffer zone. The results demonstrate that: (1) The distribution of settlements from the Neolithic to the Southern Dynasties has expanded from the Chengdu Plain in the west and the Xiajiang Area in the east to the hilly areas in the center. (2) The settlements in the Neolithic and Shang–Zhou periods are predominantly located at elevations between 300–600 m, slopes between 0–3°, aspects between 135–225°, distances to rivers between 0–1000 m, and soil choice on Luvisols, Cambisols, Regosols, and Anthrosols. The influence of aspect on settlements during the Qin–Southern Dynasties period was notably reduced. The settlements mainly grow in the Chengdu Plain and the smaller plains along the river from the Neolithic to the Southern Dynasties in the Sichuan Basin. (3) The emergence and advancement of primitive agriculture, the construction of early water conservancy facilities, commercial and trade exchanges, and the establishment of regimes led to a shift from a double core to a more dispersed distribution in the Sichuan Basin from the Neolithic to the Southern Dynasties periods. The evolution of settlements reflects the adaption and competition of the residents to the natural environment in the Sichuan Basin. Furthermore, it provides insights into the complex social development in the region, ranging from the formation of early states to the establishment of the Qin and Han Empires.

Effectiveness of natural ventilation in controlling the smoke spread within a refuge floor of a high-rise building

Refuge floors in high-rise buildings ensure a haven for occupants to stay in an emergencyprimarily during a fire breakout. Provisions for natural ventilation of the refuge floor are mandatory in all fire codes as they help release smoke and heat build-up. However, the effectiveness of such provisions has been questioned in many studies. This research employs large eddy simulations based three-dimensional computational fluid dynamics modelling on a real-world high-rise building to investigate the efficacy of natural ventilation in a refuge floor during a fire. Consequently, the performance was assessed by evaluating the temporal and spatial distributions of temperature, visibility, smoke and carbon monoxide concentration. Emphasis was placed on determining the adequacy of window placement and openings. Analysis was started with a code-compliant window configuration. Subsequently the window size and the layout were iteratively modified using simulation results. Seasonal wind variations were also considered. Results showed that a well-engineered natural ventilation strategy can considerably improve the refuge floor habitability. Simulations also revealed limitations of natural ventilation under certain wind conditions, necessitating a backup mechanical system. This also underlined that combining fire analysis with cutting-edge modelling allows tailored natural ventilation for refuge floors, maximising safe occupancy during fires.

Acoustic scene analysis of spatial and temporal distribution of sound arrival direction and frequency spectra

In the outdoor monitoring of aircraft noise, not only the target aircraft sounds to be monitored arrive, but also various environmental sounds also arrive at the monitoring site, and the sound situation changes from moment to moment. The authors have studied and reported on a method to classify environmental sound sources and to evaluate the influence of environmental sounds on aircraft sound monitoring by analyzing the spatial-temporal distribution of sound arrival direction and sound level of various environmental sounds at the monitoring site as a sound scene. This paper will make a report on a result of the acoustic scene analysis by using the sound spectra as additional input data in the scene analysis. We will also explain about a procedure for automatic classification of sound sources using the result of the scene analysis briefly.

Experimental study on laser-assisted machining of SiCp/Al composites considering laser preheating history based on in-situ observation

The application of laser-assisted machining (LAM) has been demonstrated to improve the surface integrity of SiCp/Al composites. The dynamic process of laser preheating affects the deformation mechanism of materials. In this paper, the laser preheating history under different parameters is characterized by the changes in peak temperature and instantaneous preheating temperature. SiCp/Al cutting experiments under different laser preheating histories are carried out based on the high-speed imaging system. The influence of laser preheating history on the shear angle and the spatial–temporal distribution of the physical information in the shear zone are analyzed by the digital image correlation (DIC) method. The deformation characteristics during the SiCp/Al composites cutting process under different laser preheating histories are discussed. Additionally, the influence of the laser preheating history on the surface integrity is analyzed according to the changes of the Al matrix and SiC particles under different combinations of peak temperature and instantaneous preheating temperature. It has been demonstrated that the deformation degree in the shear zone during LAM of SiCp/Al composites is depended on the material softening degree related to the peak temperature and the material deformation temperature dominated by the instantaneous preheating temperature. The deformation uniformity is primarily determined by the deformation temperature. An appropriate material softening degree and deformation temperature can improve the surface integrity. The results provide a foundation for further mechanism studies for cutting load and surface integrity in LAM of SiCp/Al composites.

Spatial conversion characteristics of sulfur and nitrogen via desulfurization denitrification under rapidly changing hydraulic conditions

The sulfur-nitrogen-contained wastewater treatment system needs fast start-up, efficient collaboration, and stability, to break through the application bottleneck of biological desulfurization-denitrification. An integrated sleeve bioreactor was adopted to analyze the coupling performances of sulfate-reduction and sulfide-based denitrification process. The spatial-temporal distribution of functional bacteria and genes was studied under rapidly changing hydraulic conditions. The transformation law of carbon-sulfur-nitrogen was clarified. The removal efficiencies of sulfate, total organic carbon, and nitrite reached 90 %, 98 %, and 99 %, respectively. Thermovirga, Desulfomicrobium and Desulfobulbus were the main functional bacteria in the external sleeve, while Sulfurovum and sulfurimonas were in the internal sleeve. The dominant functional genes sat, sqr, norBC, and nosZ had relative abundances of 1.02 ‰, 3.09 ‰, 0.63 ‰ and 0.51 ‰, respectively. The sleeve alleviated the toxic effects of sulfide and nitrite. It realized the spatial separation and enrichment of different dominant bacteria, improving the load shock resistance of bioreactor. The rapidly changing hydraulic retention time promoted the spatial transference of sulfate-reducing bacteria and brought the appearance of sulfide-based denitrification bacteria in external sleeve. It enhanced the stability of microbial community structure. This optimized microbial community structure provided a rich diversity of functional genes to ensure a collaborating degradation of sulfur and nitrogen. The main transformation pathways included the assimilated sulfate reduction, sulfur partial oxidation and denitrification. Rapidly decreasing hydraulic retention time facilitated the accumulation of elemental sulfur. The unique structure and operation exhibited strong resistance to loads and hydraulic shocks. This work provides a reference value for efficiently removing multiple pollutants in sulfur-nitrogen-polluted wastewater.

Microwave self-healing characteristics of the internal voids in steel slag asphalt mixture subjected to salt-freeze-thaw cycles

Microwave heating technology can be used to repair freeze-thaw (F-T) cycle damage and cracks caused by the use of snow melting salts and de-icers in winter. This study utilized three different gradations of asphalt mixtures: AC-13, SMA-13, and OGFC-13, and enhanced their microwave absorption performance with steel slag (SS). The heating uniformity was evaluated through surface and internal temperature tests. Additionally, the mechanisms of damage and healing of the asphalt mixtures under salt freeze-thaw (S-F-T) damage conditions were explored using S-F-T cycles test and X-ray computed tomography scans (CT). The results showed that OGFC-13 exhibits a significantly higher rate of temperature increase compared to the other two types due to its stronger wave absorption capacity. The thermal hysteresis caused by steel slag leads to uneven spatial temperature distribution. The study recommends an optimal microwave heating time of 40 s for SS asphalt mixtures, which has minimal impact on the mixture structure, by defining an evaluation method for the uniformity index and local overheat ratio. After undergoing S-F-T cycles, the porosity of all three asphalt mixtures increased, particularly at the top and bottom of the specimens. Among them, OGFC-13 exhibited the poorest durability under S-F-T conditions, with the S-F-T cycles having a significant impact on medium-sized voids (0.15–0.6 mm). After microwave heating, AC-13 and SMA-13 showed good repair effects, with porosity levels returning to their initial states. For large voids (>2.36 mm) in OGFC, microwave heating may not effectively reduce the number of voids. Additionally, the healing rate of mixture specimens at certain mid-height ranges is higher due to elevated surface temperatures in these areas, making it especially effective in repairing F-T damage. This study shows that microwave heating of SS asphalt mixtures can improve the durability of pavement in cold regions. However, implementation challenges include the need for specialized equipment and potential uneven heating. Future research should explore optimizing microwave heating techniques to minimize local overheating and investigate the long-term performance of microwave-repaired asphalt pavements under various environmental conditions.

Ship detection in reefs and deep-sea with medium-high resolution images

ABSTRACT Accurate and efficient ship detection is crucial for ocean monitoring and management, especially in reefs and deep-sea, where fishing and illegal activities threaten sustainability of ecosystems. Obtaining the size of ships in reefs and deep-sea helps to identify ship types and to assess the impact of ships on marine ecosystems quantitatively. Ship detections were mainly applied at coast or river of the inland region using high spatial resolution remote sensing data due to its rich details and frequent coverage. However, the ships located in reefs and deep-sea regions were rarely studied because of price, and availability of high spatial resolution remote sensing data. Global covered medium-high resolution (10–30 m) remote sensing data (such as Sentinel-2) makes it possible to obtain the spatial-temporal distribution of ships, especially small ships. This study developed a deep learning ship detection algorithm – an enhanced Rotated-Ship Detector (RShipDet) to detect ships in reefs and deep-sea regions. RShipDet was applied to Nansha Islands based on two medium-high resolution ship detection datasets (Sentinel2-Ship and SDGSAT-Ship). These two datasets include various backgrounds of reefs and deep-sea, and complex scenarios such as cloud cover and parallel ships, adapting RShipDet to ship detection under complex circumstances in reefs and deep-sea. The results showed that: (1) Small gains: gains of 3.3% and 8.7% Average-Precision (AP) compared to Rotation-equivariant Detector (ReDet) and Faster-RCNN on Sentinel2-Ship dataset; (2) Strong generalization capabilities: 77.4% AP on SDGSAT-Ship dataset; (3) Better performance under complex conditions: RShipDet obtained more accurate ship detection results over regions with cloud cover, islands and reefs, deep-sea, and ports compared to other classical detectors. Our algorithm could be applied for better management of ocean resources and activities in reefs and deep-sea.

Laser-induced in-situ electrohydrodynamic jet printing of micro/nanoscale hierarchical structure

With the rapid advancement of micro/nanoscale devices, there is a growing demand for hierarchical micro/nano porous-structure, particularly in fields of high-performance sensors, electrochemical energy storage, and photocatalysis. The fabrication methods for hierarchical micro/nano-porous structures have been limited by complex processes and high costs, making further development and application difficult. In this paper, a novel strategy of laser-induced in-situ electrohydrodynamic jet (E-Jet) printing of hierarchical micro/nano-porous structures was proposed. Based on the mechanism of high-energy laser beam induction on the jet, it successfully fabricated hierarchical porous ZnO structures from nanoscale to dozens of microns. The jet size focusing and solidification behavior were analyzed by combining experimental and simulative exploration. The resultant effects of the thermal field, flow field, and laser field on the spatial temperature distribution and the jetting morphology were examined. Furthermore, the laser-induced influence on the morphology of the printed micro/nano-porous ZnO structures was explored. Meanwhile, the performance of micro/nano-porous ZnO photoelectric sensors printed by E-Jet under different laser powers was investigated. The laser-induced in-situ E-Jet printing method provided an innovative pattern for the high-resolution additive manufacturing of hierarchical porous structures, demonstrating its potential for applications in advanced material and high-performance devices.

Effect of cloud chemistry on seasonal variations of sulfate and its precursors in China

Cloud chemistry is of paramount importance in the secondary production of atmospheric aerosols, influencing the spatial-temporal distribution of gases and aerosols in the atmosphere. Using WRF/CUACE (China Meteorological Administration Unified Atmospheric Chemistry Environment), this study assesses the seasonal impacts of cloud chemistry on the concentrations of SO2, sulfate, as well as two oxidizers, H2O2 and O3, in the most east-central areas of China, including four key pollution zones (the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Sichuan Basin (SCB)). Near the surface, H2O2-oxidation was the dominant pathway for cloud chemistry in four key pollution zones in four seasons. H2O2 consumption is most pronounced in summer, especially in the SCB and NCP, while O3 consumption peaks in autumn, particularly in the PRD and southeastern coastal areas. While at higher altitudes, oxidation by O3 and H2O2 is compatible with the cloud chemistry process. Near the surface, cloud chemistry consumes SO2 ranging from approximately 0.1 ppb–5.0 ppb, resulting in the generation of about 6.0–25.0 μg m−3 of sulfate. Higher SO2 reduction and sulfate increase are in both summer and winter, especially for the SCB and NCP in summer, and the SCB in winter. Vertically, the cloud chemistry process primarily concentrates its influence on SO2 and sulfate concentrations below 5 km, particularly within the turbulent zone of the troposphere below 2 km in all the four pollution zones and four seasons. The most notable seasonal variation occurs in the NCP compared to other zones. This study also shows that cloud chemistry effectively improves the seasonal simulation accuracy of SO2 and sulfate, resulting in improved correlation and a notable reduction in RMSE.

Experimental and numerical simulation study on the mass transfer characteristics of static flash evaporation

Due to the short duration and intense nature of static flash evaporation, and limited by the measurement methods, there is still limited understanding of the inhomogeneous characteristics of mass transfer within the waterfilm. This paper studies the spatiotemporal variation of mass transfer characteristics during static flash using experimental and numerical simulation methods. The formation and evolution mechanism of the bubble layer is analyzed, and its impact on the spatial distribution of temperature within the waterfilm is explained. Firstly, it was found that during the flash process, the temperature difference at different heights of the waterfilm first increases and then decreases. Secondly, during the flash process, there is a maximum value of the vapor generation rate within the waterfilm along the height direction of the flash chamber, and there is a spatial inconsistency between the vapor generation rate and the superheat distribution. Thirdly, reducing the initial waterfilm height can improve the consistency between the maximum superheat and the maximum volume fraction, resulting in a higher vapor generation rate per unit mass and an earlier peak appearance. This study contributes to a deeper understanding of flash mass transfer and provides ideas for the future enhancement of flash evaporation.

Monitoring Blood-Brain Barrier Opening in Rats with a Preclinical Focused Ultrasound System.

The brain has a highly selective semipermeable blood barrier, termed the blood-brain barrier (BBB), which prevents the delivery of therapeutic macromolecular agents to the brain. The integration of MR-guided low-intensity pulsed focused ultrasound (FUS) with microbubble pre-injection is a promising technique for non-invasive and non-toxic BBB modulation. MRI can offer superior soft-tissue contrast and various quantitative assessments, such as vascular permeability, perfusion, and the spatial-temporal distribution of MRI contrast agents. Notably, contrast-enhanced MRI techniques with gadolinium-based MR contrast agents have been shown to be the gold standard for detecting BBB openings. This study outlines a comprehensive methodology involving MRI protocols and animal procedures for monitoring BBB opening in a rat model. The rat model provides the added benefit of jugular vein catheter utilization, which facilitates rapid medication administration. A stereotactic-guided preclinical FUS transducer facilitates the refinement and streamlining of animal procedures and MRI protocols. The resulting methods are characterized by reproducibility and simplicity, eliminating the need for specialized surgical expertise. This research endeavors to contribute to the optimization of preclinical procedures with rat models and encourage further investigation into the modulation of the BBB to enhance therapeutic interventions in neurological disorders.

Spatio-temporal occurrence, burden, risk factors and modelling methods for estimating scrub typhus burden from global to subnational resolutions: a systematic review protocol.

Scrub typhus is a neglected life-threatening vector-borne disease mainly caused by the bacterium Orientia tsutsugamushi, which is occasionally transmitted to humans during feeding of larval mites. It has been estimated that more than 1 billion persons are potentially threatened and 1 million clinical cases occur annually across the world; however, it is unclear how this estimate was computed (and what the original source was) and much remains unknown regarding its global burden and risk factors. This systematic review aims to provide a comprehensive overview of the spatial-temporal distribution of scrub typhus, associated burden and risk factors at global, national and subnational resolutions, and to review the burden estimation models used at those different scales. A systematic search for literature on scrub typhus occurrence, risk factors and modelling methods will be conducted. PubMed and five other databases will be searched for published literature, and Google Scholar and nine other databases will be used to search for grey literatures. All titles/abstracts of the searched records will be separately assessed by two reviewers, who will then screen the full-text of potential records to decide eligibility. A pre-formatted spreadsheet will be used by one reviewer to extract data from qualifying research, with a second reviewer checking the results. Data will be tabulated, synthesized descriptively, and summarized narratively for each review question. Where appropriate, meta-analyses will be conducted. The risk of bias will be assessed, and potential publication bias will be detected. This review will provide a comprehensive understanding of the current occurrence, spatial-temporal distribution, and burden of scrub typhus, identify associated risk factors from global to subnational resolutions, consolidate the best practice modeling framework(s) to estimate the burden of scrub typhus at various geographic/temporal resolutions, and decompose the relative contributions of various risk factors at scale. CRD42022315209.

Metastable CoCu2O3 Nanocrystals from Combustion-Aerosols for Molecular Sensing and Catalysis.

Metastable nanostructures are kinetically trapped in local energy minima featuring intriguing surface and material properties. To unleash their potential, there is a need for non-equilibrium processes capable of stabilizing a large range of crystal phases outside thermodynamic equilibrium conditions by closely and flexibly controlling atomic reactant composition, spatial temperature distribution and residence time. Here, the capture of metastable pseudo-binary metal oxides at room temperature is demonstrated with scalable combustion-aerosol processes. By a combination of X-ray diffraction, electron microscopy and on-line flame characterization, the occurrence of metastable CoCu2O3 is investigated with controlled crystal size (4-16nm) over thermodynamically stable CuO and Co3O4. Immediate practical impact is demonstrated by exceptional sensing and stable catalytic performance for air pollutant detection (e.g., 15 parts-per-billion benzene) shown for, at least, 21 days. This approach can be extended to various binary, ternary and high entropy oxides with even more components. Also, secondary phases can be loaded on such metastable nanocrystals to access novel materials promising for actuators, energy storage or solar cells.

Remote Sensing Monitoring and Multidimensional Impact Factor Analysis of Urban Heat Island Effect in Zhengzhou City

In the 21st century, the rapid urbanization process has led to increasingly severe urban heat island effects and other urban thermal environment issues, posing significant challenges to urban planning and environmental management. This study focuses on Zhengzhou, China, utilizing Landsat remote sensing imagery data from five key years between 2000 and 2020. By applying atmospheric correction methods, we accurately retrieved the land surface temperature (LST). The study employed a gravity center migration model to track the spatial changes of heat island patches and used the geographical detector method to quantitatively analyze the combined impact of surface characteristics, meteorological conditions, and socio-economic factors on the urban heat island effect. Results show that the LST in Zhengzhou exhibits a fluctuating growth trend, closely related to the expansion of built-up areas and urban planning. High-temperature zones are mainly concentrated in built-up areas, while low-temperature zones are primarily found in areas covered by water bodies and vegetation. Notably, the Normalized Difference Built-up Index (NDBI) and the Normalized Difference Vegetation Index (NDVI) are the two most significant factors influencing the spatial distribution of land surface temperature, with explanatory power reaching 42.7% and 41.3%, respectively. As urban development enters a stable stage, government environmental management measures have played a positive role in mitigating the urban heat island effect. This study not only provides a scientific basis for understanding the spatiotemporal changes in land surface temperature in Zhengzhou but also offers new technical support for urban planning and management, helping to alleviate the urban heat island effect and improve the living environment quality for urban residents.

Electric Vehicle Charging Load Demand Forecasting in Different Functional Areas of Cities with Weighted Measurement Fusion UKF Algorithm

The forecasting of charging demand for electric vehicles (EVs) plays a vital role in maintaining grid stability and optimizing energy distribution. Therefore, an innovative method for the prediction of EV charging load demand is proposed in this study to address the downside of the existing techniques in capturing the spatial–temporal heterogeneity of electric vehicle (EV) charging loads and predicting the charging demand of electric vehicles. Additionally, an innovative method of electric vehicle charging load demand forecasting is proposed, which is based on the weighted measurement fusion unscented Kalman filter (UKF) algorithm, to improve the accuracy and efficiency of forecasting. First, the data collected from OpenStreetMap and Amap are used to analyze the distribution of urban point-of-interest (POI), to accurately classify the functional areas of the city, and to determine the distribution of the urban road network, laying a foundation for modeling. Second, the travel chain theory was applied to thoroughly analyze the travel characteristics of EV users. The Improved Floyd (IFloyd) algorithm is used to determine the optimal route. Also, a Monte Carlo simulation is performed to estimate the charging load for electric vehicle users in a specific region. Then, a weighted measurement fusion UKF (WMF–UKF) state estimator is introduced to enhance the accuracy of prediction, which effectively integrates multi-source data and enables a more detailed prediction of the spatial–temporal distribution of load demand. Finally, the proposed method is validated comparatively against traffic survey data and the existing methods by conducting a simulation experiment in an urban area. The results show that the method proposed in this paper is applicable to predict the peak hours more accurately compared to the reference method, with the accuracy of first peak prediction improved by 53.53% and that of second peak prediction improved by 23.23%. The results not only demonstrate the high performance of the WMF–UKF prediction model in forecasting peak periods but also underscore its potential in supporting grid operations and management, which provides a new solution to improving the accuracy of EV load demand forecasting.