Search Results (69)

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article

Green roofs are increasingly being adopted as sustainable, nature-based solutions for managing urban stormwater, mitigating the urban heat island effect, and saving energy in buildings. However, the long-term performance of their individual components—particularly filter geotextiles—remains understudied, despite their critical role in maintaining system functionality. The filter layer, responsible for preventing clogging of the drainage layer with fine substrate particles, directly affects the hydrological performance and service life of green roofs. While most existing studies focus on the initial material properties, there is a clear gap in understanding how geotextile filters behave after prolonged exposure to real-world environmental conditions. This study addresses this gap by assessing the mechanical and structural integrity of geotextile filters after five years of use in both extensive and intensive green roof systems. By analyzing changes in surface morphology, microstructure, and porosity through tensile strength tests, digital imaging, and scanning electron microscopy, this research offers new insights into the long-term performance of geotextiles. Results showed significant retention of tensile strength, particularly in the machine direction (MD), and a 56% reduction in porosity, which may affect filtration efficiency. Although material degradation occurs, some geotextiles retain their structural integrity over time, highlighting their potential for long-term use in green infrastructure applications. This research emphasizes the importance of material selection, long-term monitoring, and standardized evaluation techniques to ensure the ecological and functional resilience of green roofs. Furthermore, the findings contribute to advancing knowledge on the durability and life-cycle performance of filter materials, promoting sustainability and longevity in urban green infrastructure. Full article

This study assesses the exposure of the 155 Greek seaports to marine flooding and extreme heat under climate change. Flood exposure was estimated through a threshold approach that compared projected mean and extreme sea levels to high-resolution port quay elevation data. It was found that while relatively few ports will face quay inundation, the majority will experience operational disruptions due to insufficient freeboard for berthing of commercial vessels under both the mean (80%) and extreme sea (96%) levels by 2050. For selected ports, 2-D flood modelling was undertaken that showed that the used ‘static’ flood threshold approach likely underestimates flood exposure. Future heat exposure was studied through the comparison of extreme temperature and humidity projections to operational and health/safety thresholds. Port infrastructure and personnel/users will be exposed to large material, operational and health risks, whereas energy demand will rise steeply. Deadly heat days (due to mean temperature/humidity combination) will increase, particularly at island ports: 20% of Greek ports might face more than 50 such days annually by end-century. As ports are associated with large urban clusters, these findings suggest a broader health risk. Our findings suggest an urgent climate adaptation need given the strategic socio-economic importance of ports. Full article

The Solar Reflectance Index (SRI) is a standardized metric used to assess the reflective properties of materials in relation to solar radiation and their capacity to emit absorbed heat, particularly within the infrared spectrum. Materials with high SRI values, often referred to as “cool materials”, contribute to ambient temperature regulation, Urban Heat Island (UHI) mitigation, and cooling energy demand reduction. The effectiveness of SRI depends on factors such as solar incidence angles, intrinsic material properties, and varying environmental conditions. Accurate assessments require the implementation of standardized testing and rating methodologies. This paper reviews and compares North American (ASTM E1980, ASTM C1549, ASTM C1371) and European (EN 15976) standards to determine SRI, focusing on the impacts of weathering and climatic factors on material aging. The study highlights the inadequacy of current practices, which typically measure SRI after only three years of exposure, and advocates for long-term performance monitoring across diverse climates. Key findings reveal that high-SRI materials can reduce surface temperatures by up to 20 °C, significantly lowering cooling energy demands. The study recommends the development of comparable standards to measure solar reflectivity on vertical surfaces, emphasizing the importance of assessing long-term performance across various climatic conditions. Findings underscore the importance of advanced modeling, innovative materials development, and effective maintenance strategies to extend the durability and efficacy of cool materials. The novelty of this work lies in its comprehensive framework for SRI assessment, integrating advanced modeling, innovative materials development, and real-world performance monitoring. This study provides actionable insights for policymakers, urban planners, and architects to enhance building energy efficiency and urban resilience. Full article

Flood risks are escalating globally due to unplanned urban expansion and the impacts of climate change, posing significant challenges for urban areas and necessitating effective mitigation strategies. Nature-based solutions (NBSs) have emerged as innovative and sustainable approaches for managing flood risks. The International Union for Conservation of Nature (IUCN) defines NBSs as actions that conserve, manage, and restore natural and modified ecosystems to address societal concerns while benefiting both people and the environment. This research focuses on developing NBS strategies for the most flood-prone area within Kochi, a city highly vulnerable to flooding. The study begins with a comprehensive site examination to identify flood sources and causes in Kochi, aiding in selecting flood vulnerability indicators. An analytical framework incorporating flood risk assessment and exposure studies using physical and social indicators, alongside GIS mapping techniques, revealed that approximately half of Kochi is affected. The study identified key vulnerability hotspots, particularly within the Central Business District (CBD), where high population density and inadequate infrastructure exacerbate flood risks. Proposed NBS interventions include restoring natural floodplains, enhancing canal capacities, creating urban forests, and establishing green infrastructure like permeable pavements and rainwater harvesting systems. Key findings emphasize the effectiveness of integrating NBSs with traditional flood management strategies, forming a mixed flood control system. These interventions mitigate flood risks, improve biodiversity, reduce the urban heat island effect, and enhance community well-being. Importantly, the research underscores the role of public participation and community-driven maintenance plans in ensuring the sustainability of NBS interventions. Aligning these strategies with Kochi’s Master Plan 2040 ensures coherence with broader urban planning and climate resilience goals. The research anticipates changes in climate, land use patterns, and urban dynamics to inform NBS suitability in Kochi. Ultimately, the research demonstrates how implementing NBSs can deliver a range of socio-environmental benefits, significantly influencing urban development in vulnerable zones. By advocating for the integration of NBSs into urban infrastructure planning, this study offers a blueprint for resilient and sustainable flood management strategies that are applicable to other coastal cities facing similar challenges. Full article

Intensifying heat from warming climates regularly concentrates in urban areas lacking green infrastructure in the form of green space, vegetation, and ample tree canopy cover. Nature-based interventions in older U.S. city cores can help minimize the urban heat island effect, yet neighborhoods targeted for cooling interventions may remain outside the decisional processes through which change affects their communities. This translational research seeks to address health disparities originating from the absence of neighborhood-level vegetation in core urban areas, with a focus on tree canopy cover to mitigate human susceptibility to extreme heat exposure. The development of LiDAR-based imagery enables communities to visualize the proposed greening over time and across seasons of actual neighborhood streets, thus becoming an effective communications tool in community-engaged research. These tools serve as an example of how visualization strategies can initiate unbiased discussion of proposed interventions, serve as an educational vehicle around the health impacts of climate change, and invite distributional and participatory equity for residents of low-income, nature-poor neighborhoods. Full article

Ambient air pollution is the most important environmental factor impacting human health. Urban landscapes present unique air quality challenges, which are compounded by climate change adaptation challenges, as air pollutants can also be affected by the urban heat island effect, amplifying the deleterious effects on health. Nature-based solutions have shown potential for alleviating environmental stressors, including air pollution and heat wave abatement. However, such solutions must be designed in order to maximize mitigation and not inadvertently increase pollutant exposure. This study aims to demonstrate potential applications of nature-based solutions in urban environments for climate stressors and air pollution mitigation by analyzing two distinct scenarios with and without green infrastructure. Utilizing low-cost sensors, we examine the relationship between green infrastructure and a series of environmental parameters. While previous studies have investigated green infrastructure and air quality mitigation, our study employs low-cost sensors in tropical urban environments. Through this novel approach, we are able to obtain highly localized data that demonstrates this mitigating relationship. In this study, as a part of the NERC-FAPESP-funded GreenCities project, four low-cost sensors were validated through laboratory testing and then deployed in two locations in São Paulo, Brazil: one large, heavily forested park (CIENTEC) and one small park surrounded by densely built areas (FSP). At each site, one sensor was located in a vegetated area (Park sensor) and one near the roadside (Road sensor). The locations selected allow for a comparison of built versus green and blue areas. Lidar data were used to characterize the profile of each site based on surrounding vegetation and building area. Distance and class of the closest roadways were also measured for each sensor location. These profiles are analyzed against the data obtained through the low-cost sensors, considering both meteorological (temperature, humidity and pressure) and particulate matter (PM₁, PM_2.5 and PM₁₀) parameters. Particulate matter concentrations were lower for the sensors located within the forest site. At both sites, the road sensors showed higher concentrations during the daytime period. These results further reinforce the capabilities of green–blue–gray infrastructure (GBGI) tools to reduce exposure to air pollution and climate stressors, while also showing the importance of their design to ensure maximum benefits. The findings can inform decision-makers in designing more resilient cities, especially in low-and middle-income settings. Full article

Rapid urbanization has led to increasingly serious problems, such as the heat island effect and environmental pollution, which seriously endanger people’s health. Greenspace exposure behavior, that is, the way and characteristics of people’s contact with greenspace (including frequency and duration of stay), is the key to exerting the health benefits of greenspace. There is little research on the factors influencing greenspace exposure behavior, which cannot reveal the mechanism of maintaining people’s physical and mental health by promoting greenspace exposure behavior. Therefore, using typical urban parks in Fuzhou as a case study, indicators of greenspace availability, accessibility, and visibility were identified from objective park characteristics and subjective crowd evaluation. The factors influencing greenspace exposure behavior were analyzed using bivariate correlation tests and multivariate linear regression analysis. The results indicated that, among objective park characteristics, the per capita green park area negatively impacted greenspace exposure behavior, while the green view index positively influenced it (p < 0.05). Regarding subjective crowd evaluation, subjective indicators positively impacted greenspace exposure behavior except for the condition of activity areas. In addition, subjective factors, especially subjective visibility indicators, are more predictive of greenspace exposure behavior than objective factors. The theoretical contribution of this study lies in further refining the research framework for quantifying and evaluating park greenspace exposure, and enriching the theoretical connotation of research on park greenspace exposure behavior. The research results suggested park greening strategies for the relevant departments, enhanced the greenspace exposure behavior, and improved people’s physical and mental health. Full article

Milk yield and its composition show individual variation due to the effects of the environment. Previous studies suggest that meteorological variables exert negative effects on milk yield and composition, especially during summer. This study aimed to examine the effects of meteorological variables on bulk milk composition in the Sardinian sheep production system. In this work, a total of 218,170 records belonging to 4562 dairy sheep farms were merged with the meteorological data provided by 60 meteorological stations located on Sardinia Island (Italy). Milk composition in the late spring and summer recorded during a 5-year period was used to evaluate the impact of climate exposure on bulk milk traits. The milk quality was analyzed using a linear mixed model that included the fixed effects of the year of sampling, the flock size, the temperature humidity index (THI) and the random effect of the flock. The variability of milk composition explained by flock and management ranged from 30 to 64%. The flock size exerted a significant effect on milk composition: large flocks characterized by advanced management and feeding techniques resulted in higher milk quality (e.g., higher protein and fat, lower lactose) compared to traditionally managed small flocks. The impact of THI on milk composition was statistically significant across different milk quality traits (p < 0.001); the effect of thermal stress varied according to the month of lactation. For instance, milk fat content in May increased by +0.4% for THI > 76. In June, no relevant differences were observed, whereas a decrease in fat percentage was observed in July as THI values increased (up to −0.5% for THI > 76). While somatic cell counts remained relatively stable across different conditions, total bacterial count showed greater seasonal variability, peaking during warmer periods. In addition, using factor analysis, we developed a multivariate meteorological index (MMI), which explained 51% of the variance of the original meteorological data. MMI was highly correlated with THI (r = 0.75). The same linear mixed model applied for modeling THI was used to assess the effect of MMI on milk traits. Fat, protein fractions and lactose showed significant variation across MMI classes (p-value < 0.001) in the same direction as those based on THI. Overall, our findings underscore the impact of both flock size and environmental conditions on milk quality, with heat stress and traditional versus modern management practices leading to measurable differences in milk traits. Full article

Abstract: Objectives: This study aimed to map the distribution of nephrolithiasis’ environmental risk factors (occupational heat and heavy metal exposure and ambient seasonal temperature) and to assess the correlations of these exposures with the best estimates of the reported nephrolithiasis incidence in Canada. Methods: The regional average heat burden was defined as the mean temperature in the hottest three months of the year for 2020, 2021, and 2022. The employment rates in the top five industries with occupational heavy metal (cadmium, lead, and arsenic) and heat exposure were obtained from the Statistics Canada 2021 database. Statistical significance was calculated based on the 95% confidence interval difference from the null hypothesis. Correlation analysis was performed between our rates of nephrolithiasis risk factors and previously published estimates of the stone incidence: kidney stone interventions and acute kidney stone event rates. Results: Lower-latitude provinces had higher overall mean temperatures in 2020 to 2022, with Ontario, Manitoba, and Prince Edward Island having the highest seasonal heat burdens, in this order. Nunavut had the lowest rate of occupational heat exposure, while the remaining regions had similar rates. Yukon, the Northwest Territories, and Nunavut had significantly higher rates of occupational heavy metal exposure compared to the remaining regions. The ambient temperature and occupation heavy metal and heat exposure showed no significant correlation with the estimates of the stone incidence. Conclusions: The occupational heat exposure was relatively similar between regions. Northern Canada had higher occupational heavy metal exposure compared to other regions. Occupational exposures and temperature variations were not associated with the nephrolithiasis incidence in Canada. Full article

Urban heat islands and rising global temperatures are increasing the need for passive cooling solutions in densely populated areas. This study examines the effectiveness of heat-reflective paint in reducing surface and indoor temperatures in a 33-year-old apartment complex in Gumi City, South Korea. Using mock structures to simulate real building conditions, this experiment measured surface and indoor temperatures in both treated and untreated groups. Data collected from thermal imaging cameras and data loggers demonstrated significant temperature reductions on the treated walls, with surface temperatures lowered by an average of 2.2 °C to 4.3 °C and peak reductions of up to 15.3 °C. Internally, the treated structures showed temperature reductions between 2.1 °C and 4.1 °C, with the largest difference of 4.14 °C observed during peak heat hours. The results highlight the effectiveness of heat-reflective paint in mitigating heat stress and improving indoor thermal comfort, particularly in regions with high solar exposure. This study aims to support vulnerable populations, such as the elderly and economically disadvantaged residents, by providing a cost-effective, sustainable solution to reduce heat exposure in aging urban buildings, thereby enhancing their quality of life. Full article

With rapid urbanization, the urban heat island (UHI) effect has intensified, posing challenges to human health and ecosystems. This study explores the impact of sunlight exposure areas of artificial structures and human activities on land surface temperature (LST) in Hefei and Xuzhou, using Landsat 9 data, Google imagery, nighttime light data, and Point of Interest (POI) data. Building shadow distributions and urban road surface areas were derived, and geospatial analysis methods were applied to assess their impact on LST. The results indicate that the sunlight exposure areas of roofs and roads are the primary factors affecting LST, with a more pronounced effect in Xuzhou, while anthropogenic heat plays a more prominent role in Hefei. The influence of sunlight exposure on building facades is relatively weak, and population density shows a limited impact on LST. The geographical detector model reveals that interactions between roof and road sunlight exposure and anthropogenic heat are key drivers of LST increases. Based on these findings, urban planning should focus on optimizing building layouts and heights, enhancing greening on roofs and roads, and reducing the sunlight exposure areas of artificial structures. Additionally, strategically utilizing building shadows and minimizing anthropogenic heat emissions can help lower local temperatures and improve the urban thermal environment. Full article

Global warming and climate change are significantly impacting local climates, causing more intense heat during the summer season, which poses risks to individuals with pre-existing health conditions and negatively affects overall human health. While various studies have examined the Surface Urban Heat Island (SUHI) phenomenon, these studies often focus on small to large geographic regions using low-to-moderate-resolution data, highlighting general thermal trends across large administrative areas. However, there is a growing need for methods that can detect microscale thermal patterns in environments familiar to urban residents, such as streets and alleys. The temperature-humidity index (THI), which incorporates both temperature and humidity data, serves as a critical measure of human-perceived heat. However, few studies have explored microscale THI variations within urban settings and identified potential THI hotspots at a local level where SUHI effects are pronounced. This research aims to address this gap by estimating THI at a finer resolution scale using data from multiple sensor platforms. We developed a model with the random forest algorithm to assess THI trends at a resolution of 0.5 m, utilizing various variables from different sources, including Landsat 8 land surface temperature (LST), unmanned aerial system (UAS)-derived LST, Sentinel-2 NDVI and NDMI, a wind exposure index, solar radiation modeled from aircraft and UAS-derived Digital Surface Models, and vehicle density and building floor area from social big data. Two models were constructed with different variables: Model_natural, which includes variables related to only natural factors, and Model_mix, which includes all variables, including anthropogenic factors. The two models were compared to reveal how each source contributes to the model development and SUHI effects. The results show significant improvements, as Model_natural had a fitting R² = 0.5846, a root mean square error (RMSE) = 0.5936 and a mean absolute error (MAE) = 0.4294. Moreover, when anthropogenic factors were introduced, Model_mix performed even better, with R² = 0.9638, RMSE = 0.1751, and MAE = 0.1065 (n = 923). This study contributes to the future of microscale SUHI analysis and offers important insights into urban planning and smart city development. Full article

Urban disparity has been extensively studied using geospatial technology, yet a comprehensive review of GIS applications in this field is essential to address the current research status, potential challenges, and future trends. This review combines bibliometric analysis from two databases, Web of Science (WOS) and Scopus, encompassing 145 articles from WOS and 80 from Scopus, resulting in a final list of 201 articles after excluding 24 duplicates. This approach ensures a comprehensive understanding of urban disparities and the extensive applications of GIS technology. The review highlights and characterizes research status and frontiers into research clusters, future scopes, and gaps in urban disparity analysis. The use of both WOS and Scopus ensures the review’s credibility and comprehensiveness. Findings indicate that most research has focused on accessibility analysis of urban services and facilities. However, there is a recent paradigm shift toward environmental justice, demonstrated by increasing GIS applications in analyzing pollution exposure, urban heat islands, vegetation distribution, disaster vulnerability, and health vulnerability. Full article

Heat continues to be a hazard in the desert southwestern USA. This study presents the results of a preliminary microclimate field survey in two Avondale, Arizona, neighborhoods developed with artificial wastewater-treatment wetlands and one adjacent desert neighborhood. The preliminary field study reported here measured morning, near-noon, and afternoon air temperatures and, together with other observed variables, calculated mean radiant temperatures (critical to human comfort) at 28 locations across three neighborhoods on a sample day in September of 2018. The aim was to determine cooling effects of blue/green environments and identify benefits for residents. Overall results for September indicate 1–3 °C cooling, which is understandable for this time of year at summer’s end. Mean radiant temperature results are substantially different at lake sites versus dry neighborhood sites (by some 5–20 °C), likely due to the presence of fewer lateral radiant fluxes and cooler exposures at lake sites compared with dry neighborhoods. Cooling benefits likely provide year-round outdoor comfort compared to desert-landscaped communities. The authors reinforce the conclusion that recycled water and treatment systems can reduce local heat island conditions and aid in combating extreme heat in the desert southwest. This study also shows that constructed wastewater-treatment wetlands in desert cities support sustainable residential developments. Full article