Search Results (536)

Within the field of the structural monitoring of bridges, numerous technologies and methodologies have been developed. Among these, methods based on synthetic aperture radar (SAR) which utilise satellite data from missions such as Sentinel-1 (European Space Agency-ESA) and COSMO-SkyMed (Agenzia Spaziale Italiana—ASI) to capture displacements, temperature-related changes, and other geophysical measurements have gained increasing attention. However, SAR has yet to establish its value and potential fully; its broader adoption hinges on consistently demonstrating its robustness through recurrent applications, well-defined use cases, and effective strategies to address its inherent limitations. This study presents a systematic literature review (SLR) conducted in accordance with key stages of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework. An initial corpus of 1218 peer-reviewed articles was screened, and a final set of 25 studies was selected for in-depth analysis based on citation impact, keyword recurrence, and thematic relevance from the last five years. The review critically examines SAR-based techniques—including Differential Interferometric SAR (DInSAR), multi-temporal InSAR (MT-InSAR), and Persistent Scatterer Interferometry (PSI), as well as approaches to integrating SAR data with ground-based measurements and complementary digital models. Emphasis is placed on real-world case studies and persistent technical challenges, such as atmospheric artefacts, Line-of-Sight (LOS) geometry constraints, phase noise, ambiguities in displacement interpretation, and the translation of radar-derived deformations into actionable structural insights. The findings underscore SAR’s significant contribution to the structural health monitoring (SHM) of bridges, consistently delivering millimetre-level displacement accuracy and enabling engineering-relevant interpretations. While standalone SAR-based techniques offer wide-area monitoring capabilities, their full potential is realised only when integrated with complementary procedures such as thermal modelling, multi-sensor validation, and structural knowledge. Finally, this document highlights the persistent technical constraints of InSAR in bridge monitoring—including measurement ambiguities, SAR image acquisition limitations, and a lack of standardised, automated workflows—that continue to impede operational adoption but also point toward opportunities for methodological improvement. Full article

Analysis of regional changes in climatic parameters and moistening conditions is a necessary task for obtaining objective data on changes in landscapes. The article analyzes long-term changes in a complex of climatic variables on the south of the Central Russian Upland of the East European Plain in the last decades of the 20th century–the first decades of the 21st century. Opposite trends were identified for heat and moisture supply characteristics. The annual average temperature increased by 2.1 °C between 1980 and 2020. During this same time, the absolute values of the temperature of the warmest and coldest quarters, accumulated temperature over the period with values above 10 °C, increased significantly. The annual average temperature, the average temperature of the warmest and coldest quarters showed a positive, statistically significant trend. Precipitation characteristics, compared with temperatures, showed less pronounced trends during the study period. Annual precipitation and precipitation during the warmest quarter showed a weak negative trend. Precipitation of the coldest quarter showed an increasing trend. Contrasting changes in temperature and precipitation characteristics led to a decrease in moistening indicators during the warm season. The hydrothermal coefficient decreased by more than 18%, and the drought index increased by approximately the same amount. Spatial changes in most climatic parameters are associated with a shift in isolines to the north or northwest. The range of variations in climatic parameters across the region did not undergo significant changes. Full article

The retrieval of precipitable water vapor (PWV) through Global Navigation Satellite System (GNSS) meteorology critically depends on the precise determination of atmospheric weighted mean temperature (Tm). Existing empirical models for Tm retrieval over Europe offer speed but suffer accuracy limitations due to complex local environmental and climatic factors. Aiming to improve Tm model accuracy in Europe, this study constructed the European Tm Enhanced Model (EurTm). The model was constructed based on 2014–2023 radiosonde data from 40 stations across Europe, with its parameters optimized through least squares estimation. The EurTm model integrates multiple factors, including Tm from Hourly Global Pressure and Temperature 2 (HGPT2), the difference between Ts obtained by HGPT2 and Ts measured by radiosonde stations, and diurnal variation. The EurTm model’s accuracy was validated by comparing its outputs with reference values derived from 2024 radiosonde data. The EurTm model underwent comparative analysis against the widely used Bevis, ETmPoly, and HGPT2 models. The EurTm model’s accuracy was 13.2%, 4.1%, and 32.7% higher than the Bevis, ETmPoly, and HGPT2 models at 40 modeling stations. At 13 non-modeling stations, the EurTm model outperformed the Bevis, ETmPoly, and HGPT2 models with accuracy enhancements of 16.1%, 4.7%, and 30.0%, respectively. Theoretical evaluation showed that the EurTm model achieved an RMSE of 0.20 mm and a relative error of 1.11% for GNSS-derived PWV, outperforming all comparative models. In conclusion, the EurTm model not only holds significant application value for GNSS PWV retrieval in Europe but also provides a novel approach for region-specific enhancements of global empirical Tm models by addressing characteristic regional features such as diurnal variations. Full article

The causes of Arctic surface air temperature rise and the corresponding sea ice decline in the early 20th century are still a matter of debate. One hypothesis, considering the major contribution of the internal variability to the early warming event, is the leading one. This study aims to assess the contributions of the Northern Hemisphere’s leading natural variability modes to winter temperature changes in the Arctic during 20th century. Two methodologies were compared to remove externally forced signals from Arctic SAT observations—linear detrending and subtracting the multi-model ensemble mean, thereby isolating internal variability. The study introduces a novel perspective on regional evaluation across four equal-area Arctic sectors (European, Asian, Pacific, and North Atlantic), uncovering a heterogeneous spatial pattern of the Arctic SAT modulation by climate indices. Statistical analysis reveals northern extratropical modes explain 66% (median) of total variance, with dominance of AMO index in HadCRUT5 detrended observations and only 30% with PDO index prominent in observations-CMIP6 residuals. It is revealed that forced-signal removal data outperforms the detrending procedure in isolating unforced internal dynamics. AMO’s susceptibility to external forcings like greenhouse gases/aerosols is also underscored by the results of the study. Future directions advocate dynamic approaches like large initial-condition ensembles prescribing sea surface temperature/sea ice or isolating modes for causal attribution beyond statistical links. Full article

Although the rare plant Cotoneaster integerrimus is distributed across Eurasia, ecological information on its isolated populations at the easternmost range limit in Korea has been entirely lacking. This study was conducted to (1) characterize the environmental characteristics of the habitat of Korean C. integerrimus populations and (2) predict potential habitats via a simple species distribution model (SDM) based on ridge logistic regression and presence–background data, providing a foundation for effective conservation strategies. To this end, we analyzed habitat type, topography, and light conditions through field surveys and combined these data with an SDM fitted to six known occurrences on limestone ridges. Results revealed a clear ecological divergence; the Korean population is biased toward partial shade and north-facing slopes within the forest understory, in contrast to European populations inhabiting open, rocky sites. This distribution pattern is interpreted as a local adaptive strategy that reduces exposure to hot and humid summer conditions. Furthermore, a unique morphological trait not reported in European populations was identified: dense persistent hairs that remain until seed maturity. The SDM analysis showed moderate discrimination (training AUC = 0.784) and indicated that high elevation and ridge topography (Topographical Position Index, TPI) acted as key habitat factors, whereas annual mean temperature was the strongest limiting factor. Mapping the upper decile (top 10%) of predicted suitability within the limestone belt highlighted a small, spatially restricted set of high-elevation ridges as candidate microrefugia and survey priorities. This study suggests that the Korean C. integerrimus population may have undergone local adaptation due to isolation. Furthermore, this population is considered both a Geographical Peripheral Population (GPP) and a glacial relict, and is assessed to be vulnerable to climate change. Given that the SDM is based on only six occurrences and shows variable performance among spatial folds, all spatial predictions and variable effects should be regarded as exploratory and spatially conservative rather than as definitive habitat projections. These findings, therefore, support the urgent need to establish in situ and ex situ conservation strategies that preserve this geographically peripheral population as an irreplaceable component of the species’ genetic diversity. Full article

Seeking solutions that expand the energy market with new possibilities is a natural approach in the context of greenhouse gas emissions and associated climate change. One renewable energy source is water, which, in addition to kinetic energy, can also serve as a source of heat. Having up-to-date hydrological data is crucial for assessing the scale and rate of water circulation in the environment, and subsequently its potential for economic use. This study reconstructs water temperature with the application of the hybrid air2water model for several dozens of rivers in the Odra basin (Central Europe) and, on this basis, estimates heat flux and subsequently its predictability across different temporal scales. The average annual heat flow of all the analyzed rivers was 3.36 × 10⁶ GJ and varied widely, from 0.09 to 51 × 10⁶ GJ, depending on the size of the river. On an annual scale, the heat flow corresponds to the distribution of seasonal changes in key variables (river discharge and water temperature) characteristic of rivers in the temperate zone. The lowest average heat flow was recorded in January (0.74 × 10⁶ GJ), and the highest in July (5.73 × 10⁶ GJ). Considering the obtained results and the spatial distribution of the river network in the analyzed area, it can be concluded that the energy transported by river systems may be regarded as a potential heat source. This is significant in the context of expanding opportunities for obtaining clean energy, which aligns with the current framework of the European Union’s policy aimed at achieving climate neutrality. Full article

Selecting accurate climatic data is crucial for reliable simulations of Renewable Energy Systems (RESs) and the assessment of building energy performance, particularly under ongoing global climate change. Typical Meteorological Year (TMY) datasets are widely used to represent long-term average weather conditions. However, they may not fully capture regional climatic variability, recent temperature or solar radiation trends, potentially leading to substantial discrepancies in simulation outcomes. Despite the widespread use of TMY and reanalysis datasets, limited studies have systematically compared multiple contemporary meteorological databases in the context of RES simulations across Europe. This study evaluates and compares five meteorological databases—Meteonorm, TMY, TMYx, ERA5, and SARAH3—for twenty European capitals located between 38° and 56° N. A transient model developed in TRNSYS was employed to assess the performance of photovoltaic and solar collector systems with different datasets. The results reveal significant differences between datasets, with deviations reaching up to 200–300 kWh/m² in annual total horizontal radiation and 40–50% in simulated useful energy gains. PV efficiency remained relatively stable across Europe (17.7–18.7%) with very low standard deviation (<0.12%), while SC efficiency showed higher variability (25.8–28.7%). The findings demonstrate that the choice of climatic database can substantially influence energy yield predictions, technical optimization, thereby introducing significant uncertainty into the economic bankability assessment of renewable energy projects, especially in Central and Northern Europe, where climatic variability is more pronounced. The study emphasizes the need for careful database selection and periodic validation of TMY datasets in the context of evolving climatic conditions to ensure accurate, risk-aware, and future-proof energy system simulations. Full article

Increasingly stringent energy directives of the European Union, combined with rising cooling demands due to climate change, urge the investigation of energy-efficient cooling solutions. Free cooling offers a viable approach to reducing energy consumption. However, its effectiveness and applicability across different building types remain insufficiently established. This study aims to minimise mechanical cooling energy demand through the implementation of enhanced free cooling (EFC) as an operational control strategy in office, residential, and small commercial buildings. The introduction of the efficiency of EFC (η_fc) supports this analysis by quantifying how effectively EFC exploits free cooling potential in defined thermal and mechanical conditions based on an analytical approach supported by simplified simulations (in Microsoft Excel). The case study indicates that the east-oriented office building with a 40% glazing ratio achieves the highest cooling energy savings (49.63%) on the target summer day. For the residential building, savings are lower (37.78%) but more stable across the hot and the extremely hot days. The results further show that the influence of building orientation diminishes as external temperature increases, while higher glazing ratios stabilise η_fc across the examined thermal conditions. Analysis of the connection between air exchange rate and mechanical cooling energy savings identifies a critical resistance point (n_opt), defined as the ventilation rate beyond which no further cooling energy savings occur. The results enable practical applications in building operation and support both improved energy efficiency and the advancement of sustainable HVAC design. Full article

A sensor network based on 10 stationary nodes distributed in Bari (Southern Italy) has been deployed for urban air quality (AQ) monitoring. The low-cost sensor systems have been installed in specific sites (e.g., buildings, offices, schools, streets, ports, and airports) to enhance environmental awareness of the citizens and to supplement the expensive official air-monitoring stations with cost-effective sensor nodes at high spatial and temporal resolution. Continuous measurements were performed by low-cost electrochemical gas sensors (CO, NO₂, O₃), optical particle counter (PM₁₀), and NDIR infrared sensor (CO₂), including micro-sensors for temperature and relative humidity. The sensors are operated to assess the performance during a campaign (July 2015–December 2017) of several months for citizen science in sustainable smart cities. Typical values of CO₂, measured by distributed nodes, varied from 312 to 494 ppm (2016), and from 371 to 527 ppm (2017), depending on seasonal micro-climate change and site-specific conditions. The results of the AQ-monitoring long-term campaign for selected sensor nodes are presented with a relative error of 26.2% (PM₁₀), 21.7% (O₃), 25.5% (NO₂), and 79.4% (CO). These interesting results suggest a partial compliance, excluding CO, with Data Quality Objectives (DQO) by the European Air Quality Directive (2008/50/EC) for Indicative (Informative) Measurements. Full article

Climate change poses significant challenges to viticulture worldwide, with Eastern European vineyards experiencing increased water stress due to rising temperatures, irregular precipitation patterns, and prolonged drought periods. These climatic shifts hurt vine phenology, grape quality, and overall productivity. In response, adaptive irrigation strategies such as Regulated Deficit Irrigation (RDI) have gained attention for optimizing water use while preserving grape quality. Concurrently, the adoption of smart agriculture technologies—including soil moisture sensors, automated weather stations, remote sensing, and data-driven decision support systems—enables precise monitoring and real-time management of vineyard water status. This review synthesizes recent studies from Eastern Europe, emphasizing the necessity of integrating climate adaptation measures with intelligent irrigation management to enhance vineyard resilience and sustainability under increasing climate variability. Full article

This study presents a comprehensive analysis of key meteorological parameters at the Lenghu site, a premier astronomical observing location, with particular emphasis on understanding their variability patterns and long-term trends. The research systematically investigates regional distribution characteristics, periodic variations, seasonal changes, and the temporal evolution of critical atmospheric parameters that influence astronomical observations. Furthermore, this study explores the potential connections between these parameters and major climate oscillation patterns, including ENSO (El Niño–Southern Oscillation), PDO (Pacific Decadal Oscillation), and AMO (Atlantic Multidecadal Oscillation). Utilizing ERA5 (the fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts) reanalysis data, we examine the regional atmospheric conditions (82°–102° E and 31°–46° N) surrounding the Lenghu site from 2000 to 2023 (24 years). The analysis focuses on fundamental meteorological parameters: precipitable water vapor (PWV), temperature, wind speed at 200 hPa ($W_{200}$), and total cloud cover (TCC). For the Lenghu site specifically, we extend the temporal coverage to 1990–2023 (34 years) to include additional parameters such as high cloud cover (HCC) and total column ozone (TCO). The analysis reveals that the ENSO and PDO indices are negatively correlated with $W_{200}$. The AMO index has a positive correlation with PWV and a slight positive correlation with $W_{200}$, temperature, and TCO. Moreover, a comparative analysis of Lenghu, Mauna Kea, and Paranal reveals distinct variation trends across sites due to regional climate differences. Notably, while all observatory sites are affected by global climate change, their response patterns and temporal characteristics exhibit subtle variations. Full article

The transformation of energy systems towards low emission is one of the key assumptions of the climate and energy policy of the European Union and many countries around the world. These changes include not only the power and transport sectors but also the heating of residential buildings, which consume significant amounts of energy and emit large amounts of greenhouse gases. This article presents a detailed comparative analysis of the costs of heating using an air-to-water heat pump and a condensing gas boiler. The study concerned a retrofitted single-family building from the 1990s, located in southern Poland. The calculations were made taking into account daily meteorological data for two full heating seasons: 2022/2023 and 2023/2024. This approach made it possible to more precisely reproduce real operating conditions. The study was conducted for various configurations of the central heating system: surface and radiator. The following parameters were also taken into account: (1) variable heat pump parameters, such as supply temperature LWT and coefficient of performance COP; (2) current tariffs for electricity and natural gas; and (3) forecasted tariffs for electricity and natural gas in the conditions of market liberalization and phasing out of protective mechanisms. A comparison of the two heating seasons revealed lower costs with a heat pump. In some cases, the cost of heat generated by a gas boiler was over 100% higher than with a heat pump. This applies to both heating seasons. Under the current tariffs, the calculated gas cost for the first season was PLN 6856 (EUR 1605) (1 EUR = 4.27 PLN) compared to heat pump heating costs ranging from PLN 3191 to PLN 4576 (EUR 747 to 1072). For future gas and electricity tariffs, the costs were PLN 8227 (EUR 1926) for gas and PLN 3841 to PLN 5304 (EUR 899 to 1242) for a heat pump. Similarly, for the second heating season, these values were PLN 6055 (EUR 1418) for gas heating and PLN 2741–3917 (EUR 642–917) for a heat pump under the current tariffs, and PLN 7267 (EUR 1702) and PLN 3307–4540 (EUR 774–1064) under future tariffs. This means percentage savings of between approximately 33% and 55%, depending on the heating type and tariff. Therefore, the obtained results indicate the higher profitability of using an air heat pump compared to a gas boiler. This advantage was maintained in all the discussed scenarios, and its scale depended on the type of installation, supply temperature, and the selected electricity tariff. The highest economic profitability was noted for low-temperature systems. These results can provide a basis for making rational investment and design decisions in the context of the energy transformation of single-family housing. Full article

This paper presents the development of a high-resolution composite index to monitor and quantify climate-related risks across Italy. The country’s complex climatic variability, extensive coastline, and low insurance penetration highlight the urgent need for robust, locally calibrated tools to bridge the climate protection gap. Building on the methodological framework of existing actuarial climate indices, previously adapted for France and the Iberian Peninsula, the index integrates six standardised indicators capturing warm and cool temperature extremes, heavy precipitation intensity, dry spell duration, high wind frequency, and sea level change. It leverages hourly ERA5-Land reanalysis data and monthly sea level observations from tide gauges. Results show a clear upward trend in climate anomalies, with regional and seasonal differentiation. Among all components, sea level is most strongly correlated with the composite index, underscoring Italy’s vulnerability to marine-related risks. Comparative analysis with European indices confirms both the robustness and specificity of the Italian exposure profile, reinforcing the need for tailored risk metrics. The index can support innovative risk transfer mechanisms, including climate-related insurance, regulatory stress testing, and resilience planning. Combining scientific rigour with operational relevance, it offers a consistent, transparent, and policy-relevant tool for managing climate risk in Italy and contributing to harmonised European frameworks. Full article

Norway spruce (Picea abies (L.) H. Karst.) is a primary forest-forming species in the European part of Russia, both in terms of its distribution and economic importance. A number of studies indicate that one of the reasons for the disturbance of spruce forests is linked to rising temperatures, particularly the detrimental effects of extreme droughts. The aim of our research is to identify changes in the structural and functional organization of mature spruce forests at the center of the East European Plain. The study was conducted in intact spruce forests using resurveyed vegetation relevés within the Smolensk–Moscow Upland, with relevés repeated after 40 years (in 1985 and 2025). Changes in structural and functional parameters of spruce communities were analyzed. The results showed that significant disturbances of the tree layer led to changes in the vegetation of subordinate layers, as well as the successional dynamics of spruce forests. It was found that following the collapse of old-growth spruce stands, two types of secondary succession developed: (1) with the renewal of spruce and (2) with active development of shrubs (hazel and rowan) and undergrowth of broadleaved species. It was also demonstrated that the typological diversity of the studied communities changed over 40 years not only due to the loss of the tree layer and the formation of new “non-forest” types but also because several mixed spruce-broadleaved communities transitioned into broadleaved ones, and pine–spruce communities of boreal origin shifted to nemoral types. An analysis of the complete species composition of spruce forests based on Ellenberg’s scales scoring revealed changes in habitat conditions over the 40-year period. A noticeable trend was an increase in the proportion of thermophilic and alkaliphilic species, indicating a shift toward a nemoral vegetation spectrum. It is expected that under the current forest management regime, the next 40 to 60 years will see a decline in the proportion of spruce within mixed stands, potentially culminating in the complete collapse of monospecific spruce forests in the center of the East European Plain. Full article

Air pollution critically impacts global health, climate change, and ecosystem balance. In Türkiye, rapid population growth, urban expansion, and industrial activities lead to significant land use and cover changes, negatively affecting air quality. This study examined the relationship between land use and land cover changes and six key pollutants (sulfur dioxide, ozone, aerosol index, carbon dioxide, nitrogen dioxide, and formaldehyde) using TROPOMI/Sentinel-5P and European Space Agency Climate Change Initiative data between 2018 and 2024. Satellite-based remote sensing techniques, MODIS data, land surface temperature, and Normalized Vegetation Index analyses were employed. The findings revealed that nitrogen dioxide and carbon dioxide emissions increase with urban expansion and traffic density in metropolitan areas (Istanbul, Ankara, Izmir), while agriculture and deforestation increase aerosol index levels in inland areas. Additionally, photochemical reactions increased surface ozone in the Mediterranean and Aegean regions. At the same time, sulfur dioxide and formaldehyde concentrations reached high levels in highly industrialized and metropolitan cities such as Istanbul, Ankara, and Izmir. This study highlights the role of green infrastructure in improving air quality and provides data-based recommendations for sustainable land management and urban planning policies. Full article