Search Results (5,144)

Yangjiatang Village traces its origins to the late Ming and early Qing dynasties. It has evolved over more than 400 years of history. There are 78 rammed-earth buildings left, making it one of the most complete and largest rammed-earth building complexes in East China. This study investigated the traditional rammed-earth houses in Yangjiatang Village, Songyang County, Zhejiang Province. By combining field investigation, microscopic characterization, and experimental simulation, we systematically revealed the erosion resistance of rammed earth in a subtropical humid climate was systematically revealed. Using a combination of advanced techniques including drone aerial photography, X-ray diffraction (XRD), microbial community analysis, scanning electron microscopy (SEM), and soil leaching simulations, we systematically revealed the anti-erosion mechanisms of rammed-earth surfaces in Yangjiatang Village. The study found that (1) rammed-earth walls are primarily composed of Quartz, Mullite, lepidocrocite, and Nontronite, with quartz and lepidocrocite being the dominant minerals across all orientations. (2) Regulating the community structure of specific functional microorganisms enhanced the erosion resistance of rammed-earth buildings. (3) The surface degradation of rammed-earth walls is mainly caused by four factors: structural cracks, surface erosion, biological erosion and roof damage. These factors work together to cause surface cracking and peeling (depth up to 3–5 cm). (4) This study indicates that the microbial communities in rammed-earth building walls show significant differences in various orientations. Microorganisms play a dual role in the preservation and deterioration of rammed-earth buildings: they can slow down weathering by forming protective biofilms or accelerating erosion through acid production. Full article

Adverse weather events have a negative impact on the productivity of construction site activities. Understanding these effects is essential for developing realistic construction schedules. The influence of weather is shaped by both environmental factors (climate, geography, topography) and construction-related aspects such as technologies, materials, equipment, and site exposure. This paper proposes a model to quantify the influence of adverse weather by estimating monthly intervals of expected days with reduced construction productivity, based on data regarding specific weather events, including precipitation, wind, extreme temperatures, snow cover, fog, and high humidity. Data analysis employs the inclusion–exclusion principle, a combinatorial technique, alongside confidence interval estimation, a standard statistical approach. The model was applied in three Croatian cities to demonstrate its practicality and accuracy. Contractors with extensive on-site experience reviewed the results, providing insights into weather-sensitive activities and organizational practices. Full article

This study examines the effects of climate change on maize production in Romania between 2003 and 2024, focusing on yield dynamics, regional disparities, and economic losses. Maize, a key crop in Romanian agriculture, has become increasingly vulnerable to extreme weather events, particularly droughts, which remain the most frequent risk. The analysis highlights a marked decline in maize yields and cultivated area in recent years, strongly correlated with severe droughts in 2020, 2022, and 2024. The results show that western and northern counties display greater resilience, while southeastern regions face significant yield losses. The economic impact is substantial, with losses exceeding EUR 1 billion. These findings underscore the systemic nature of climate-related risks and call for region-specific adaptation strategies, expanded irrigation infrastructure, and index-based insurance schemes to strengthen resilience and ensure sustainable maize production under changing climatic conditions. Full article

Gasoline is the most common ignitable liquid used to initiate fires, making its detection and identification in fire debris crucial for determining incendiary origins. Fire debris is typically collected after extinguishment and safety clearance, often resulting in gasoline weathering, especially when delayed. Most research on gasoline weathering has been conducted in controlled laboratory settings in temperate climates. However, the effects of tropical conditions on the rate of gasoline weathering and the resulting chemical composition of volatiles remain largely unexplored. Understanding how tropical environmental factors alter gasoline weathering is essential for accurate fire debris interpretation in such regions. This study investigates how tropical climates impact gasoline weathering indoors and outdoors. Weathered samples were prepared by volume reduction method, gradually evaporating gasoline from 10% to 95%. Indoor samples were exposed to room temperature, while outdoor samples were left in open space under natural tropical conditions. Gas Chromatography/Mass Spectrometry (GC-MS) analysis revealed chromatographic shifts in heavier compounds (C₃–C₄ alkylbenzenes) compared to lighter ones like toluene as weathering progressed. Correlation between indoor and outdoor samples was high (>0.970) at 10–50% weathering but declined (<0.600) at 90–95%, indicating differing patterns. All target compounds remained detectable across all samples. Full article

The acceleration of climate change and increasing weather-related disasters require more active utilization of renewable energy. To maximize the use of renewable energy, energy storage is an essential part. Liquid piston gas compressors have recently drawn attention because of their applicability to compressed air-based energy storage. Aqueous foam can be used to enhance the efficiency of liquid piston gas compression by boosting heat transfer. To validate the effectiveness of the combination of liquid piston and aqueous foam in a multi-stage compression system, which can contribute to higher efficiency, the present work performed experimental study at various pressure levels. Compressions were performed with and without aqueous foam at three different initial pressure levels of 1, 2, and 3 bars. For each cycle of compression, a pressure ratio of 2 was used, and the impact of pressure levels on compression efficiency was measured. With the use of foam, isothermal efficiencies of 91.4, 88.2, and 86.6% were observed at 1, 2, and 3 bar(s), which improved by 2.2, 2.1, and 1.3% compared to the baseline compressions. To identify the cause of the effectiveness variations, the volume changes in the foam at the different pressure levels were visually compared. In higher-pressure tests, a significant reduction in the foam amount was observed, and this change may contribute to the decreased effectiveness of the technique. Full article

Climate change in Antarctica has profound global implications, influencing sea level rise, atmospheric circulation, and the Earth’s energy balance. This study presents a data-driven baseline analysis of meteorological observations from a British Antarctic Survey automatic weather station (2020–2024). Temporal and seasonal analyses reveal strong insolation-driven variability in temperature, snow depth, and solar radiation, reflecting the extreme polar day–night cycle. Correlation analysis highlights solar radiation, upwelling longwave flux, and snow depth as the most reliable predictors of near-surface temperature, while humidity, pressure, and wind speed contribute minimally. A linear regression baseline and a Random Forest model are evaluated for temperature prediction, with the ensemble approach demonstrating superior accuracy. Although the short data span limits long-term trend attribution, the findings underscore the potential of lightweight, reproducible pipelines for site-specific climate monitoring. All analysis codes are openly available in github, enabling transparency and future methodological extensions to advanced, non-linear models and multi-site datasets. Full article

The precision of ERA5 reanalysis datasets and their applicability in the mountainous regions of central China are essential for weather forecasting and climate change research in the transitional zone between northern and southern China. This study employs three months of continuous measurements collected from a high-precision remote sensing platform located in a representative mountainous valley (Xinyang city) in central China, spanning December 2024 to February 2025. Our findings indicate that both horizontal and vertical wind speeds from the ERA5 dataset exhibit diminishing deviations as altitude increases. Significant biases are observed below 500 m, with horizontal mean wind speed deviations ranging from −4 to −3 m/s and vertical mean wind speed deviations falling between 0.1 and 0.2 m/s. Conversely, minimal biases are noted near the top of the boundary layer. Both ERA5 and observations reveal a dominance of northeasterly and southwesterly winds at near-surface levels, which aligns with the valley orientation. This underscores the substantial impact of heterogeneous mountainous terrain on the low-level dynamic field. At an altitude of 1000 m, both datasets present similar frequency patterns, with peak frequencies of approximately 15%; however, notable discrepancies in peak wind directions are evident (north–northeast for observations and north–northwest for ERA5). In contrast to dynamic variables, ERA5 temperature deviations are centered around 0 K within the lower layers (0–500 m) but show a slight increase, varying from around 0 K to 6.8 K, indicating an upward trend in deviation with altitude. Similarly, relative humidity (RH) demonstrates an increasing bias with altitude, although its representation of moisture variability remains insufficient. During a typical cold event, substantial deviations in multiple ERA5 variables highlight the needs for further improvements. The integration of machine learning techniques and mathematical correction algorithms is strongly recommended as a means to enhance the accuracy of ERA5 data under such extreme conditions. These findings contribute to a deeper understanding of the use of ERA5 datasets in the mountainous areas of central China and offer reliable scientific references for weather forecasting and climate modelings in these areas. Full article

The purpose of this study was to examine the role of traditional fire management practices in the general mitigation of wildfire risk in Greece. Major emphasis was placed on assessing people’s opinions about the perceived effectiveness of traditional fire management strategies that were historically and culturally employed by local communities—such as weather condition monitoring, prescribed burning, proper land use planning, and mosaic burning—in the general mitigation of wildfire risks. An online questionnaire was used to collect data from 397 environmental experts in Greece. The study shows that traditional fire control methods reduce wildfire risk. First, weather monitoring was found to be crucial to wildfire forecasting and prevention. The results showed that early warning, successful firefighting, and fire prevention depend on meteorological data. Additionally, prescribed burning was revealed to have reduced wildfire risk. Respondents accepted that they could reduce unprescribed fires, protect natural ecosystems, remove wildfire-prone areas, and regulate flame intensity. This suggests that scheduled burning in Greece may reduce wildfire damage. The study underlines the importance of including conventional fire management in the wildfire mitigation strategy of Greece. The aforementioned activities may help the environment and civilization progress by safeguarding ecosystems and reducing wildfire damage. These techniques, combined with community engagement and improved early warning systems, may help manage climate change-induced wildfires. Overall, the study contributes to wildfire management in Greece and other Mediterranean countries. The study emphasizes the need to incorporate traditional fire practices into Greece’s wildfire risk reduction strategies. Taking into account the success rates of these practices in other areas, as well as Greece’s old tradition of conducting fire, this paper stresses that further studies and policy developments be made in order to reinstate these practices in today’s wildfire management. Full article

The integration of Internet of Things (IoT) technologies in agriculture has facilitated real-time environmental monitoring, with low-cost IoT-enabled agrometeorological stations emerging as a valuable tool for climate-smart farming. This systematic review examines low-cost IoT-based weather stations by analyzing their hardware and software components and assessing their potential in comparison to conventional weather stations. It emphasizes their contribution to improving climate resilience, facilitating data-driven decision-making, and expanding access to weather data in resource-constrained environments. The analysis revealed widespread adoption of ESP32 microcontrollers, favored for its affordability and modularity, as well as increasing use of communication protocols like LoRa and Wi-Fi due to their balance of range, power efficiency, and scalability. Sensor integration largely focused on core parameters such as air temperature, relative humidity, soil moisture, and rainfall supporting climate-smart irrigation, disease risk modeling, and microclimate management. Studies highlighted the importance of usability and adaptability through modular hardware and open-source platforms. Additionally, scalability was demonstrated through community-level and multi-station deployments. Despite their promise, challenges persist regarding sensor calibration, data interoperability, and long-term field validation. Future research should explore the integration of edge computing, adaptive analytics, and standardization protocols to further enhance the reliability and functionality of IoT-enabled agrometeorological systems. Full article

The three-dimensional (3D) structure of clouds is a key factor in atmospheric processes, profoundly influencing solar radiation transfer, weather patterns, and climate dynamics. However, accurately representing this complex structure in radiative transfer models remains a significant challenge. As part of the Deep 3D Scattering of Solar Radiation in the Atmosphere due to Clouds (D3D) project, we conducted a comprehensive study on the role of all-sky imagers (ASIs) in reconstructing observational 3D cloud fields and integrating them into advanced 3D cloud modeling. Since November 2022, a network of four ASIs has been operating across the broader Patras region in Greece, continuously capturing atmospheric measurements over an area of approximately 50 km². Using simultaneously captured images from the ASIs within the network, a 3D cloud reconstruction was performed utilizing advanced image processing techniques, with a primary focus on cumulus cloud scenarios. The Structure from Motion (SfM) technique was employed to reconstruct the 3D structural characteristics of clouds from two-dimensional images. The resulting 3D cloud fields were then integrated into the MYSTIC three-dimensional radiative transfer model to simulate and reconstruct solar irradiance fields. Full article

Surface pretreatment significantly influences the hygroscopic behavior of wood, which in turn affects surface stability when exposed to variable climatic conditions. This study focuses on how different surface pretreatment methods impact the performance of protective coating applied on spruce wood (Picea abies (L.) Karst.) during one year of natural weathering. Samples were prepared using various surface treatments: milling and sanding with grit sizes P40, P80, and P120, respectively. Two types of coatings were applied: a solventborne coating (ADLER Pullex Plus-Lasur) and a waterborne coating (DColor FK 47 UV Protect). The samples were exposed for 12 months at an outdoor testing site in Suchdol, Czech. Surface properties were assessed through color changes in the CIE Lab* space, gloss measurements (ISO 2813), contact angle analysis, and visual inspection. The results showed that exposure to UV radiation and microbial activities led to the gradual degradation of the optical properties and aesthetic appearance of the wood. Surfaces with greater roughness preserved their aesthetic properties more effectively, indicating a higher absorption of the coating. Untreated wood exhibited low water repellency, while the coated surface demonstrated enhanced hydrophobicity. Notably, the waterborne coating showed a temporary increase in contact angle around the sixth month, indicating surface clogging by dust particles. In contrast, the solventborne coating had a rapid decrease in wettability during the first nine months. These findings suggested the importance of surface pretreatment and coating type in maintaining the long-term performance and aesthetic appearance for wood used in exterior conditions. Full article

The global rapid urbanization intensifies environmental challenges related to climate change, such as air pollution and the urban heat island (UHI) effect in built environments. The need to optimize nature-based solutions (NBSs) is imperative to mitigate climate change and adapt to extreme weather phenomena. Against this background, this review offers an analysis regarding the integration of vertical greenery systems (VGSs) into urban environments so as to capitalize on their environmental, social, and economic benefits. Key aspects of the review include the positive role of VGSs in UHI mitigation, air quality improvement, stormwater management, and biodiversity enhancement, while examining social aspects (i.e., improved well-being and mental health, noise reduction, and urban built aesthetics). Finally, parameters related to economic benefits and energy efficiency are assessed. The submission further analyses the significant challenges that VGSs face, such as high maintenance costs, structural risks, plant health issues, fire hazards, and other limitations (legislative and technical). The crucial need for interdisciplinary collaborations among urban planners, architects, environmental engineers, and stakeholders is highlighted, in order to successfully integrate VGSs into urban buildings. Thus, this paper aims to identify key strategies for optimizing VGSs’ implementation and provide valuable insights for policymakers and researchers aiming to enhance urban sustainability through vertical greening. Full article

Climate change and extreme weather compromise building energy performance and Heating, Ventilation, and Air Conditioning (HVAC) systems, impacting occupant wellbeing and health. However, occupants can naturally adapt through their behaviors, representing a form of intrinsic resilience that enhances the building’s capacity to handle thermal extremes. This study explores the role of occupants in buildings’ thermal resilience; it begins by investigating passive and active strategies commonly discussed in the literature, then analyzes whether occupants are treated as passive or active subjects with adaptive capacity. Four databases were consulted, and 22 peer-reviewed papers were screened based on the following criteria: a clear definition of thermal resilient buildings, inclusion of at least one quantitative method for assessing whole-building resilience, original scientific contribution, and a focus on whole-building rather than component-level resilience. Analysis highlights that the intrinsic thermal resilience of occupants has received limited importance in current discourse on building resilience; in most studies (12 out of 22), occupants are treated as passive thermal loads, with no adaptive behavior considered. This study also suggests examining strategies traditionally used in energy efficiency and indoor comfort as a preliminary approach to encourage adaptive behaviors, and, above all, opens a discussion on integrating occupant behavior into resilience strategies. Full article

Increased precipitation and extreme weather due to climate change can remobilize recent and legacy environmental contaminants from soil, sediment, and sewage overflows. Heavy metals are naturally distributed in Earth’s crust, but anthropogenic activity has resulted in concentrated emissions of toxic heavy metals and deposition in surrounding communities. Cities around the world are burdened with heavy metal pollution from past and present industrial activity. The city of Camden, NJ, represents a valuable case study of climate impacts on heavy metal mobilization in stormwater runoff due to similar legacy and present-day industrial pollution that has taken place in Camden and in many other cities. Various studies have shown that lead (Pb) and other toxic heavy metals have been emitted in Camden due to historic and recent industrial activity, and deposited in nearby soils and on impervious surfaces. However, it is not known if these heavy metals can be mobilized in urban stormwater, particularly after periods of high precipitation. In this study, Camden, NJ stormwater was collected from streets and parks after heavy rain events in the winter and spring for analysis with inductively coupled plasma-mass spectrometry (ICP-MS) to identify lead (Pb), mercury (Hg), cadmium (Cd), and arsenic (As). Lead was by far the most abundant of the four target elements in stormwater samples followed by Hg, Cd, and As. The locations with the highest Pb concentrations, up to 686.5 ppb, were flooded allies and streets between commercial and residential areas. The highest concentrations of Hg (up to 11.53 ppb, orders of magnitude lower than Pb) were found in partially flooded streets and ditches. Lead stormwater concentrations exceed EPA safe drinking levels at the majority of analyzed locations, and Hg stormwater concentrations exceed EPA safe drinking levels at all analyzed locations. While stormwater is not generally ingested, dermal contact and hand-to-mouth behavior by children are potential routes of exposure. Heavy metal concentrations were lower in stormwater collected from parks and restored areas of Camden, indicating that these areas have a lower heavy metal exposure risk. This study shows that heavy metal pollution can be mobilized in stormwater runoff, resulting in elevated exposure risk in industrial cities. Full article

Camelina (Camelina sativa) is an oilseed crop of increasing importance, valued not only for its adaptability to diverse environmental conditions and potential for sustainable agriculture but also for its economic advantages, including low input requirements and suitability for biofuel production and niche markets. This study examines the relationship between camelina yield and climatic variables—specifically temperature and precipitation—based on a ten-year field experiment conducted in Poland. To capture the temporal dynamics of weather conditions, Functional Data Analysis (FDA) was applied to daily temperature and precipitation data. The analysis revealed that yield variability was strongly influenced by the length of the vegetative period and specific weather patterns in April and July. Higher yields were recorded in years characterized by moderate spring temperatures, elevated temperatures in July, and evenly distributed rainfall during the early generative growth stages. The Maximal Information Coefficient ($\mathrm{M}\mathrm{I}\mathrm{C}$) confirmed the relevance of these variables, with the duration of the vegetative phase showing the strongest correlation with yield. Cluster analysis further distinguished high- and low-yield years based on functional weather profiles. The FDA-based approach provided clear, interpretable insights into climate–yield interactions and demonstrated greater effectiveness than traditional regression models in capturing complex, time-dependent relationships. These findings enhance our understanding of camelina’s response to climatic variability and support the development of predictive tools for resilient, climate-smart crop management. Full article