Search Results (3,675)

With accelerating urbanization and global climate warming, Urban Heat Islands (UHIs) pose serious threats to urban development. Existing UHI research mainly focuses on inland regions, lacking systematic understanding of coastal city heat island mechanisms. We selected eight Chinese coastal cities with different backgrounds, quantitatively assessed urban heat island intensity based on summer 2023 Landsat 8 remote sensing data, established block-LCZ spatial analysis units, and employed a combination of machine learning models and causal inference methods to systematically analyze the regional differentiation characteristics of Urban Heat Island Intensity (UHII) and the influence mechanisms of multi-dimensional driving factors within land–sea interaction contexts. The results revealed the following: (1) UHII in the study area presents obvious spatial differentiation, with the highest value occurring in Hong Kong (2.63 °C). Northern cities generally had higher values than southern ones. (2) Different Local Climate Zone (LCZ) types show significant differences in thermal contributions, with LCZ2 (compact midrise) blocks presenting the highest UHII values in most cities, while LCZ G (water) and LCZ A (dense trees) blocks exhibit stable cooling effects. Nighttime light (NTL) and distance to sea (DS) are dominant factors affecting UHII, with NTL marginal effect curves generally presenting hump-shaped characteristics, while DS shows different response patterns across cities. (3) Causal inference reveals true causal driving mechanisms beyond correlations, finding that causal effects of key factors exhibit significant spatial heterogeneity. The research findings provide a new cognitive framework for understanding the formation mechanisms of thermal environments in Chinese coastal cities and offer a quantitative basis for formulating regionalized UHI mitigation strategies. Full article

Background/Objectives: Coupling mobile health (mHealth) technology with community-based nutrition programs may enhance diet quality in adolescents. This pilot study evaluated the feasibility, acceptability, and preliminary efficacy of integrating PortionSize Ed (PSEd), an image-assisted dietary assessment and education app, into the six-week Hawaiʻi Food and Lifeskills for Youth (HI-FLY) curriculum delivered via Supplemental Nutrition Assistance Program Education (SNAP-Ed). Methods: Adolescents (grades 6–8) from two classrooms were cluster-randomized into HI-FLY or HI-FLY + PSEd. Both groups received HI-FLY and completed Youth Questionnaires (YQ) and food records (written or app-based) at Weeks 0 and 7. Feasibility and acceptability were assessed via enrollment, attrition, and User Satisfaction Surveys (USS). Diet quality was measured using Healthy Eating Index-2020 (HEI-2020) scores and analyzed via mixed-effects models. Results: Of 50 students, 42 (84%) enrolled and attrition was minimal (2.4%). The sample was 49% female and 85% at least part Native Hawaiian or Pacific Islander (NHPI). PSEd was acceptable, with average USS scores above the scale midpoint. No significant HEI-2020 changes were observed, though YQ responses indicated improvements in sugary drink intake (p = 0.03) and use of nutrition labels in HI-FLY + PSEd (p = 0.0007). Conclusions: Integrating PSEd into SNAP-Ed was feasible, acceptable, and demonstrated potential healthy behavior change among predominantly NHPI youth in Hawaiʻi. Full article

Urban green spaces are essential for mitigating the heat island effect, supporting ecosystem services, and maintaining biodiversity. The distribution, fragmentation, and connection of the green spaces significantly impact the behavior of species in cities, serving as key indicators of environmental resilience and ecological benefits. However, current studies, as well as planning standards, often prioritize green spaces independently through their coverage or density, overlooking the importance of continuity and its impact on thermal regulation and accessibility. In this research, urban “hidden green corridors” refer to the unrecognized but functionally significant pathways that link fragmented green spaces through ecological behaviors, which enhance both biological and human habitats. This research focuses on developing an agent-based simulation (ABS) model based on the Physarealm plugin in Rhino, which can assess the effectiveness of these hidden corridors in different urban settings by integrating geographic information systems (GIS) and space syntax. Based on three case studies in Italy (Lambrate District, Bolognina, and Ispra), the simulation results are further interpreted through the AI agentic workflow “SOFIA”, developed by IMM Design Lab, Politecnico di Milano, and compared using manual analysis as well as mainstream large language models (ChatGPT 4.0 Web). The findings indicate that the “hidden green corridors” are essential for urban heat reduction, enhancement of urban biodiversity, and strengthening ecological flows. Full article

Land Surface Temperature (LST) is a critical parameter for analyzing urban heat islands, surface–atmosphere interactions, and environmental management. This study enhances the temporal resolution of LST data by leveraging machine learning and deep learning models. A novel methodology was developed using Landsat 8 thermal data and Sentinel-2 multispectral imagery to predict LST at finer temporal intervals in an urban setting. Although Sentinel-2 lacks a thermal band, its high-resolution multispectral data, when integrated with Landsat 8 thermal observations, provide valuable complementary information for LST estimation. Several models were employed for LST prediction, including Random Forest Regression (RFR), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) network, and Gated Recurrent Unit (GRU). Model performance was assessed using the coefficient of determination (R²) and Mean Absolute Error (MAE). The CNN model demonstrated the highest predictive capability, achieving an R² of 74.81% and an MAE of 1.588 °C. Feature importance analysis highlighted the role of spectral bands, spectral indices, topographic parameters, and land cover data in capturing the dynamic complexity of LST variations and directional patterns. A refined CNN model, trained with the features exhibiting the highest correlation with the reference LST, achieved an improved R² of 84.48% and an MAE of 1.19 °C. These results underscore the importance of a comprehensive analysis of the factors influencing LST, as well as the need to consider the specific characteristics of the study area. Additionally, a modified TsHARP approach was applied to enhance spatial resolution, though its accuracy remained lower than that of the CNN model. The study was conducted in Tehran, a rapidly urbanizing metropolis facing rising temperatures, heavy traffic congestion, rapid horizontal expansion, and low energy efficiency. The findings contribute to urban environmental management by providing high-temporal-resolution LST data, essential for mitigating urban heat islands and improving climate resilience. Full article

Anthropogenic ponds have the potential to shape the post-industrial landscape and mitigate the effects of climate change, particularly in urban heat island-threatened areas. However, decisions regarding their inclusion in blue–green infrastructure networks require balancing costs and benefits while considering potential pollution risks. The objectives of this study are: (i) to develop an efficient decision-making framework based on standard aquatic science tools; (ii) to apply this framework to a specific artificial pond in the Upper Silesian Industrial Region, Poland, in order to optimize actions based on resources, advantages, limitations, and informativeness of the data. Eighteen methods, grouped into five categories, including historical document analyses, hydroacoustic and modeling methods, multiparametric water quality measurements, and ecotoxicological tests, were used. Optimization-focused analysis indicated that investigating historical documents should precede further testing, as it enables decision-makers to select the most effective methods to assess the pond’s value for blue–green infrastructure. In this case, the tests based on metal pollution, bathymetry, and biodiversity appeared sufficient. The presented approach offers a straightforward screening method for assessing reservoirs in post-industrial areas. Full article

With worldwide development of wind energy, birds have grown increasingly vulnerable to collisions with wind turbines. For several species of eagles, which in many countries are accorded special protection due to a host of anthropogenic threats, accurate estimates of collision mortality are needed to assess impacts and to formulate appropriate mitigation strategies. Unfortunately, estimates of wind turbine collision mortality are often biased low by failing to account for carcasses that fall beyond the fatality search area boundary, B. In some instances, carcass density is modeled across the fatality search area to adjust for these undetected fatalities. Yet for more accurate fatality estimates, it is important to determine $\widehat{B}$, the search area boundary within which all carcasses could be found. We used eagle carcass data from multi-year fatality studies conducted at the Island of Smøla, Norway, and the Altamont Pass Wind Resource Area, California, USA, to assess carcass density (i) as a contributor to mortality estimation (ii) as a predictor variable of B, and (iii) to test whether the cumulative carcass counts with increasing distance from the wind turbine can predict $\widehat{B}$. We found that carcass counts within 5 m annuli change little with increasing distance from modern wind turbines, and that carcass density is largely a function of the area calculated. Characterization of the spatial distribution of carcasses within the search area varies with the search radius that determines B. However, this may not represent the true spatial distribution of carcasses, including those found beyond B. We assert that the available data are unsuitable for predicting the number of eagle carcasses within and beyond a given search area, nor for determining $\widehat{B},$ but they do indicate that $\widehat{B}$ lies much farther from wind turbines than previously assumed. Ultimately, modeling available carcass distribution data cannot replace the need for searching farther from wind turbines to account for the true number of eagle collision victims at any given wind project. Full article

Climate change and urbanization are intensifying the urban heat island effect and negatively impacting outdoor thermal comfort in cities. Innovative planning strategies are required to design more livable and resilient urban spaces. Building on a state of the art of current Urban Digital Twins (UDTs) for outdoor thermal comfort analysis, this paper presents the design and implementation of a functional UDT prototype. Developed for a pilot area in Huelva, Spain, the system integrates real-time environmental data, spatial modeling, and simulation tools within an open-source architecture. The literature reveals that while UDTs are increasingly used in urban management, their application to outdoor thermal comfort remains limited and technically challenging, especially in terms of real-time data, modeling accuracy, and user interaction. The case study demonstrates the feasibility of a modular, open-source UDT capable of simulating mean radiant temperature and outdoor thermal comfort indexes at high resolution and visualizing the results in a 3D interactive environment. UDTs have strong potential for supporting microclimate-sensitive planning and improving outdoor thermal comfort. However, important challenges remain, particularly in simulation efficiency, model detail, and stakeholder accessibility. The proposed prototype addresses several of these gaps and provides a basis for future improvements. Full article

Background/Objectives: The COVID-19 (Coronavirus Disease, 2019) pandemic affected all countries in a variety of ways, and forced policymakers to adapt national health infrastructure. In this context, the strategic adaptation and policy evolution of small island states are understudied. Therefore, the objective of this study was to quantitatively analyse the relationship between confirmed COVID-19 cases and health policy decisions in Northern Cyprus. We also examined the shifting management strategies employed during the pandemic using a replicable statistical analysis framework. Methods: In this mixed-methods study, we used systematic thematic analysis to categorise official policy decisions from March 2020 to December 2022. Yearly linear regression models using SPSS and Python correlated the monthly number of decisions with the number of confirmed COVID-19 cases. The analyses included R² values, p-values, and visualisations with 95% confidence intervals. Results: The findings of this study highlight a three-phase strategic period. In 2020, the results (R² = 0.03, p = 0.63) showed no significant relationship, indicating initial uncertainty. The results (R² = 0.60, p = 0.003) indicate a strong negative correlation in 2021, which reflects the consistency of the proactive suppression strategies adopted. Conversely, for 2022, the results (R² = 0.79, p < 0.001) show a strong positive correlation representing the shift to a reactive mitigation strategy, in which the government responded based on case peaks. Conclusions: This study’s primary finding is that strategic agility was key to managing the pandemic. For small island states in particular, the effectiveness of geographic advantages like border control depends on a coherent strategy that transcends initial uncertainty. Our data-driven framework provides a tool for analysing this strategic evolution and guiding responses to future pandemics. Full article

This paper evaluates Urban Heat Island (UHI) mitigation strategies in Florence’s historical centre, characterized by relevant cultural heritage value and significant tourist fluxes but increasingly susceptible to heatwaves. The research work focused on the evaluation of both current microclimate conditions and mitigation solutions for UHI-related issues, using ENVI-met microclimate modelling software as a simulation tool. Different models, featuring a 2 m grid resolution and detailed material properties, were produced to assess outdoor air temperature (Ta), mean radiant temperature (MRT), and Universal Thermal Climate Index (UTCI), chosen as reference parameters for human thermal sensation. Diversified conditions induced by the peculiarities of the urban layout were highlighted, with current Ta up to 32 °C and MRT exceeding 55 °C in paved open areas. Site-specific measures and their expected effectiveness were hence analyzed. De-paving and greening yield modest local cooling (Ta reduction up to −0.25 °C, MRT up to −1.75 °C), while tree installation ensures that MRT decreases by −7.50 °C to −12.00 °C. Most effectively, suspended shading fabrics preventing direct radiation can act on Ta (−0.09 °C to −0.25 °C) and provide substantial MRT reductions (−7.50 °C to −17.00 °C), significantly improving thermal comfort. The findings emphasize the potentialities of site-specific, reversible interventions in historic centres to combine climate adaptation and heritage preservation. Full article

This study models different hybrid systems based on renewable energies that can be supported by diesel generators to meet the energy needs of isolated homes in the Canary Islands. The research will cover the energy requirements of a residential house, including the production of fresh water using a reverse osmosis desalination plant. The system is designed to operate independently of the electrical grid. The HOMER software package was used to model and optimize the hybrid systems. The model was fed with data on the electrical demands of residential homes (including the consumption by the small reverse osmosis desalination plant) as well as the technical specifications of the various devices and renewable energy sources, such as solar radiation and wind speed potentials. The software considers various configurations to optimize hybrid systems, selecting the most suitable one based on the available renewable energy sources at the selected location. The data used in the research were collected on the eastern islands of the Canary Islands (Gran Canaria, Lanzarote and Fuerteventura). Based on the system input parameters, the simulation and optimization performed in HOMER, taking into account the lowest “Levelized Cost of Energy”, it can be concluded that the preferred hybrid renewable energy system for this region is a small wind turbine with a nominal power of 1.9 kW, eight batteries, and a small diesel generator with a nominal power of 1.0 kW. The knowledge from this research could be applied to other geographical areas of the world that have similar conditions, namely a shortage of water and plentiful renewable energy sources. Full article

Agriculture is Ireland’s largest sector with agri-food exports amounting to EUR 15.2B in 2021. However, agriculture is also Ireland’s largest contributor to GHGs, accounting for 37.4% of emissions in 2020. Developing indigenous renewable energy sources is a national objective towards reducing GHG emissions. The National Policy Statement on the Bioeconomy of Ireland advises a cascading principle of biomass use, where higher-value applications are derived from biomass before energy generation. This research quantifies and characterises biomass wastes at farms, food production, and forestry settings in counties Monaghan and Tipperary, Ireland. Value chains, along with Sankey diagrams, are presented, which identify biomass that can be exploited for valorisation and show their fates in industry/environment. The quantity of biomass wastes available for valorisation under Business as Usual (BAU) vs. Best-Case Scenario (BCS) models is presented. BCS assumes a co-operative system to increase the feedstock available for valorisation. In Monaghan, 73 t of biomass waste vs. 240 t are available for valorisation under Scenario A vs. Scenario B, respectively. In contrast, in Tipperary, a 7-fold increase in biomass waste is achieved, comparing Scenario A (126 t) against Scenario B (905 t). This highlights the importance of engaging local stakeholders to build co-operative models for biomass valorisation. Not only is this environmentally beneficial, but also socially and economically advantageous. Creating indigenous fertiliser and energy sources is important for the island of Ireland, not only in meeting market demand, but also in reducing greenhouse gas (GHG) emissions and achieving emission reduction targets. Full article

Understanding the regulatory effects of lakes on land surface temperature is critical for assessing regional climatological and ecological dynamics on the Tibetan Plateau (TP). This study investigates the spatiotemporal variability in the thermal effect of lakes across the TP from 2000 to 2022 using the MODIS land surface temperature product and a model-based lake surface water temperature product. Our results show that the lake–land temperature difference (LLTD) within 10 km buffer zones surrounding lakes ranges from −2.8 °C to 3.4 °C. A declining trend in 79.2% of the lakes is detected during 2000–2022, with summer contributing most significantly to this decrease at a rate of −0.56 °C per decade. Assessments of the spatial extent of lake thermal effects show that the “warm island” effect in autumn (5.5 km) influences a larger area compared to the “cold island” effect in summer (1.3 km). Furthermore, southwestern lakes exhibit stronger warming intensities, while northwestern lakes show more pronounced cooling intensities. Correlation analyses indicate that lake thermal effects are significantly related to lake depth, freeze-up start date, and salinity. These findings highlight the importance of lake thermal regulation in heat balance changes and provide a foundation for further research into its climatic and ecological implications on the Tibetan Plateau. Full article

This study aims to establish an energy assessment system and provide low-carbon design strategies for block-scale science and technology industrial parks in the Yangtze River Delta region of China. To investigate low-carbon design strategies for these parks, the impact of solar energy utilization potential and heat island effect on the energy consumption of buildings is taken as the entry point. Through an analysis of the spatial characteristics of twenty block-scale science and technology industrial parks in the Yangtze River Delta region of China, two types of idealized park models comprising a total of eighteen variations were established. The simulation process involved six key morphological parameters to describe the specific shape of the parks quantitatively. The Ladybug Tools 1.6.0, Radiance 5.4a, and URBANopt v0.9.2 software were used to simulate the potential for photovoltaic power generation and the energy consumption of the parks. Net Energy Use Intensity (NEUI) and Potential Utilization Ratio of Renewable Energy (PURRE) were selected as the final evaluation indexes to represent the integrated energy performance of the park. The results show that for the park with a circular layout, the optimal integrated energy performance is achieved when the building density is between 35% and 40%; the average building height is designed with lower values within the range of 20 m to 24 m, and the height-to-depth ratio is around 0.3. Finally, based on the results of the analysis, four major low-carbon design strategies were proposed: high-density development, courtyard layout, supporting-function centralized layout, and carbon sink enhancement. Full article

The relationship between the seismic regime and humidity, pressure, temperature, and wind speed measured at a network of stations on the Japanese islands was studied for the period from 1973 to 2025. For each of the parameters, weighted average time series were constructed using the principal component method and then subjected to wavelet decomposition. For wavelet decomposition levels, the amplitudes of the envelopes and the points of their local extrema were found and compared with the times at which earthquakes occurred. The problem of estimating an advanced measure of envelope extremum points relative to earthquake moments was considered using a model of interacting point processes. For a sequence of 213 strong earthquakes with a magnitude of at least 6.5, the same numbers for the largest local maxima and the smallest local minima were selected for the extrema of the envelope amplitude of each parameter. It turned out that the largest advance measures occurred for the seventh level of decomposition (the period from 16 to 32 days). Two advance mechanisms were identified: one mechanism is associated with the trigger effect of cyclones on seismicity, and the second is associated with the occurrence of atmospheric earthquake precursors. Full article

As crucial transportation hubs and economic nodes, the underwater security and infrastructure maintenance of harbors are of paramount importance. Harbors are characterized by high vessel traffic and complex underwater environments, where traditional underwater inspection methods, such as diver operations, face challenges of low efficiency, high risk, and limited operational range. This paper introduces a collaborative survey and disposal system that integrates a deformable unmanned surface vehicle (USV) with a lightweight remotely operated vehicle (ROV). The USV is equipped with a side-scan sonar (SSS) and a multibeam echo sounder (MBES), enabling rapid, large-area searches and seabed topographic mapping. The ROV, equipped with an optical camera system, forward-looking sonar (FLS), and a manipulator, is tasked with conducting close-range, detailed observations to confirm and dispose of abnormal objects identified by the USV. Field trials were conducted at an island harbor in the South China Sea, where simulated underwater objects, including an iron drum, a plastic drum, and a rubber tire, were deployed. The results demonstrate that the USV-ROV collaborative system effectively meets the demands for underwater environmental measurement, object localization, identification, and disposal in complex harbor environments. The USV acquired high-resolution (0.5 m × 0.5 m) three-dimensional topographic data of the harbor, effectively revealing its topographical features. The SSS accurately localized and preliminarily identified all deployed simulated objects, revealing their acoustic characteristics. Repeated surveys revealed a maximum positioning deviation of 2.2 m. The lightweight ROV confirmed the status and location of the simulated objects using an optical camera and an underwater positioning system, with a maximum deviation of 3.2 m when compared to the SSS locations. The study highlights the limitations of using either vehicle alone. The USV survey could not precisely confirm the attributes of the objects, whereas a full-area search of 0.36 km² by the ROV alone would take approximately 20 h. In contrast, the USV-ROV collaborative model reduced the total time to detect all objects to 9 h, improving efficiency by 55%. This research offers an efficient, reliable, and economical practical solution for applications such as underwater security, topographic mapping, infrastructure inspection, and channel dredging in harbor environments. Full article