Search Results (1,043)

There are many types of probes available on the market for measuring ambient dose equivalent rates (ADERs), which makes intercomparison exercises essential to ensure data comparability and reliability. This study evaluated the performance of four widely used and similarly priced probes—the Reuter-Stokes ionization chamber, the RX04L from BITT, the MIRA from ENVINET, and the LB9360 from Berthold. The Reuter-Stokes ionization chamber was also taken as reference. Measurements were continuously conducted in Bilbao, northern Spain, during the period 2017–2021 under background conditions as well as during episodes of heavy rainfall and extreme temperatures. Results show that the BITT proportional counter exhibited the highest consistency with the Reuter-Stokes chamber under all meteorological conditions, and excellent stability even during extreme conditions. The Berthold probe displayed similar trends, but systematically overestimated dose rates, while the Geiger–Müller-based detector showed acceptable agreement under rainfall, but clear instability during temperature extremes. These findings highlight the importance of probe selection in environmental radioactivity networks as well as the use of reliable instruments for integration into modernized radiological surveillance systems. Full article

Under global warming, the frequency and intensity of extreme climate events have markedly increased. As one of the most climate-sensitive and ecologically fragile regions in the world, the Tibetan Plateau faces mounting environmental and demographic challenges. This study integrates multi-model ensemble simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) with population projection data from the Shared Socioeconomic Pathways (SSPs) under the high-emission scenario (SSP5-8.5). Three extreme climate indices—very wet days precipitation (R95p), warm days (TX90p), and consecutive dry days (CDDs)—were analyzed to assess future changes in climate extremes (2021–2100) and their relationships with demographic dynamics across Tibetan ethnic areas. The results indicate that, under high-emission conditions, both R95p and TX90p increase significantly, while CDDs slightly decreases, though drought risks remain pronounced in central regions. Over the same period, the total population is projected to decline by nearly 60%, with substantial differences in climate risk exposure across groups: working-age adults and less-educated individuals experience the highest exposure before mid-century, followed by a decline, whereas the elderly and highly educated populations will show continuously increasing exposure, stabilizing by the end of the century. The transformation of population patterns is reshaping socio-cultural structures, highlighting the need for culturally adaptive governance to ensure the sustainability of Tibetan ethnic communities. These findings enhance our understanding of the coupled interactions among climate change, population dynamics, and cultural transitions, providing a scientific basis for integrated adaptation strategies to promote sustainable development across the Tibetan Plateau. Full article

The validation of climate models is important for ensuring accurate climate variability over a given region. This study evaluates the performance of multiple global climate model simulations from the Coupled Model Intercomparison Project Phases 5 and 6 and the downscaled regional climate model simulations from the Coordinated Regional Climate Downscaling Experiment against gridded observational data from the Climatic Research Unit gridded data during the historic period 1981–2000. Spatial analysis using monthly bias maps and statistical metrics (i.e., correlation coefficient, standard deviation, and centred root-mean-squared error) were employed to assess the model outputs’ ability to reproduce monthly temperature and precipitation patterns over South Africa. The results indicate an improvement in CMIP6 and CORDEX model simulation outputs compared to their CMIP5 predecessors, with reduced biases and enhanced correlation. The study underscores the importance of model selection for regional climate analysis and highlights a need for further model development to capture complex physical processes. Full article

Wind is an important renewable energy source, and even minor variations in wind speed will significantly impact wind power generation. The objective of this study was to systematically assess the impacts of climate change on wind energy resources in the South China Sea (SCS) under future climate projections. To achieve this, we employed a multi-model ensemble approach based on Coupled Model Intercomparison Project Phase 6 (CMIP6) data under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results demonstrated that, in comparison with scatterometer wind data, the CMIP6 historical results (1995–2014) showed good performance in capturing the spatiotemporal distribution of wind power density (WPD) in the SCS. There were regional discrepancies in the central SCS due to the complex monsoon-driven wind dynamics. Future projections revealed an overall increase in annual mean wind power density (WPD) across the entire SCS by the mid-21st century (2046–2065) and late 21st century (2080–2099). The seasonal analyses indicated significant WPD increases in summer, especially in the northern SCS and the region adjacent to the Kalimantan strait. The increase in summer (>40 × 10⁻⁴ m/s/year under SSP5-8.5) is about triple that in winter. In the late 21st century, an increase in WPD exceeding 10% can be generally anticipated under the SSP2-4.5 and SSP5-8.5 scenarios in all seasons. The extreme wind in the northern and central SCS will further increase by 5% under the three scenarios, which will add an extra extreme load to wind turbines and related marine facilities. These assessments are essential for wind farm planning and long-term energy production evaluations in the SCS. Based on the findings in this study, specific areas of concern can be targeted to conduct localized downscaling analyses and risk assessments. Full article

Previous studies have suggested that Earth’s annual cycle of modern climate provides information relevant to orbital-scale climate variability, since both are driven by solar insolation changes determined by orbital geometry. However, there has been no systematic assessment of the climate response to annual-scale insolation changes in climate models, leading to large uncertainty in orbital-scale simulation. In this study, we evaluate the Northern Hemisphere land surface air temperature response to the annual insolation cycle in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. A polynomial transfer framework reveals that CMIP6 models broadly capture the observed 20–30-day lag between insolation and temperature, indicating realistic land thermal inertia. However, CMIP6 models consistently overestimate temperature sensitivities to insolation, with particularly strong biases over mid-latitude and high-latitude regions in summer and winter, respectively. Applying the annual-scale polynomial transfer framework to the middle Holocene (~6000 years ago) shows that models with the highest sensitivity simulate significantly larger seasonal temperature anomalies than the lowest-sensitivity models, underscoring the impact of modern biases on orbital-scale paleoclimate simulations. The results highlight systematic overestimation of temperature–insolation sensitivity in CMIP6 models, emphasizing the importance of constraining seasonal sensitivity for robust orbital-scale climate modeling. Full article

Background: Patients with adolescent idiopathic scoliosis (AIS) require effective bracing to control curve progression. However, most traditional spinal braces commonly pose challenges in terms of undesired bulkiness and restricted mobility. Recent advancements have focused on innovative brace designs, utilizing novel materials and structural configurations to improve wearability and functionality. However, it remains unclear how effective these next-generation braces are biomechanically compared to traditional braces. Objectives: This review aimed to analyze the design features of next-generation AIS braces and assess their biomechanical effectiveness via reviewing contemporary studies. Methods: Studies on newly designed scoliosis braces over the past decade were searched in databases, including Web of Science, PubMed, ScienceDirect, Wiley, EBCOHost and SpringerLink. The Joanna Briggs Institute Critical Appraisal Checklist for Cohort Studies was adopted to evaluate the quality of the included studies. The data extracted for biomechanical effect analysis included brace components/materials, design principle, interfacial pressure, morphological changes, and intercomparison parameters. Results: A total of 19 studies encompassing 12 different kinds of braces met the inclusion/exclusion criteria. Clinical effectiveness was reported in 14 studies, with an average short-term Cobb angle correction of 25.4% (range: 12.41–34.3%) and long-term correction of 18.22% (range: 15.79–19.3%). This result aligned broadly with the previously reported efficacy of the traditional braces in short-term cases (range: 12.36–31.33%), but was lower than the long-term ones (range: 23.02–33.6%). Two included studies reported an interface pressure range between 6.0 kPa and 24.4 kPa for novel braces, which was comparable to that of the traditional braces (4.8–30.0 kPa). Additionally, five of six studies reported the trunk asymmetric parameters and demonstrated improvement in trunk alignment. Conclusions: This study demonstrates that most newly designed scoliosis braces could achieve comparable biomechanical efficacy to the conventional designs, particularly in interface pressure management and Cobb angle correction. However, future clinical adoption of these novel braces requires further improvements of ergonomic design and three-dimensional correction, as well as more investigation and rigorous evidence on the long-term treatment outcomes and cost-effectiveness. Full article

The increasing frequency of extreme climate events (ECEs) is expected to significantly affect crop yields in the future, threatening regional and global food security. However, uncertainties in yield projections persist due to regional variability, model differences, and scenario assumptions. Leveraging historical agricultural disaster and meteorological data from China (1995–2014), this study employs the vulnerability curve assessment to determine the most appropriate models for assessing crop yields affected by different ECEs (drought, extreme precipitation, extreme low temperature, and extreme wind) across six regions. By integrating multi-model and multi-scenario (SSP1-2.6, SSP3-7.0, SSP5-8.5) future climate data from Coupled Model Intercomparison Project Phase 6 (CMIP6), we conducted pooled prediction of the individual and combined impacts of different ECEs on crop yields for the near-term (2020–2040) and mid-term (2041–2060). The median of multi-model prediction of crop yield reductions in China was −16.0% (range: −32.5% to −2.6%), with more severe losses in Northeast, Northwest, and North China, particularly under higher radiative forcing scenarios. Drought is the most destructive of the four types of ECEs. These results will aid decision-makers in identifying high-risk zones for crop yields affected by ECEs and provide a scientific basis for the developing targeted adaptation strategies in various regions. Full article

Global warming has been altering the East Asian climate at an unprecedented rate since the 20th century. In order to evaluate the changes in the East Asian winter climate (EAWC) and support policy-making for climate mitigation and adaptation strategies, this paper utilizes the multimodel ensemble from the Couple Model Intercomparison Project 6 and a temperature threshold method to investigate the EAWC changes during the period 1979–2100. The results show that the EAWC has been undergoing widespread and robust changes in response to global warming. The winter length in East Asia has shortened and will continue shortening owing to later onsets and earlier withdrawals, leading to a drastic contraction in length from 100 days in 1979 to 43 days (27 days) in 2100 under SSP2-4.5 (SSP5-8.5). While most regions of the East Asian continent are projected to become warmer in winter, the Japan and marginal seas of northeastern Asia will face the risks from colder winters with more frequent extreme cold events, accompanied by less precipitation. Meanwhile, the Tibetan Plateau is very likely to have colder winters in the future, though its surface snow amounts will significantly decline. Greenhouse gas (GHG) emissions are found to be responsible for the EAWC changes. GHG traps heat inside the Earth’s atmosphere and notably increases the air temperature; moreover, its force modulates large-scale atmospheric circulation, facilitating an enhanced and northward-positioned Aleutian low together with a weakened Siberian high, East Asian trough, and East Asian jet stream. These two effects work together, resulting in a contracted winter with robust and uneven regional changes in the EAWC. This finding highlights the urgency of curbing GHG emissions and improving forecasts of the EAWC, which are crucial for mitigating their major ecological and social impacts. Full article

This research evaluates three wind data sources, the Sentinel-1 wind product, the global reanalysis ERA5, and the regional reanalysis CARRA, across Iceland’s North, South, West, and East coastal regions. The analysis mainly focuses on validating Sentinel-1 high-resolution capabilities for capturing fine-scale wind patterns in coastal zones, where traditional reanalyses may have tangible limitations. Performance is evaluated through intercomparison of datasets and analysis of regional wind speed variability, with in situ coastal meteorological observations providing ground-truth validation. The results highlight the relative strengths and limitations of each source, offering guidance for improving wind-driven and wind-dependent applications in Iceland’s coastal regions, such as hazard assessment, marine operations, and renewable energy planning. Full article

Fluctuations in precipitation usually affect the ecological environment and human socioeconomics through events such as floods and droughts, resulting in substantial economic losses. The high-resolution models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) are vital for simulating precipitation patterns in China; however, significant uncertainties still exist. This study utilized the quantile mapping (QM) method to correct biases in nine high-resolution Earth System Models (ESMs) and then comprehensively evaluated their precipitation simulation capabilities over the Chinese mainland from 1985 to 2014. Based on the selected models, the Bayesian Model Averaging (BMA) method was used to integrate them to obtain the spatial–temporal variation in precipitation over the Chinese mainland. The results showed that the simulation performance of nine models for precipitation from 1985 to 2014 was significantly improved after the bias correction. Six out of the nine high-resolution ESMs were selected to generate the BMA ensemble model. For the BMA model, the precipitation trend and the locations of significant points were more closely aligned with the observational data in the summer than in other seasons. It overestimated precipitation in the spring and winter, while it underestimated it in the summer and autumn. Additionally, both the BMA model and the worst multi-model ensemble (WMME) model exhibited a negative mean bias in the summer, while they displayed a positive mean bias in the winter. And the BMA model outperformed the WMME model in terms of mean bias and bias range in both the summer and winter. Moreover, high-resolution models delivered precipitation simulations that more closely aligned with observational data compared to low-resolution models. Full article

The climatic variability of near-surface air temperature (NSAT) over the Caspian region (35–60° N; 40–65° E) was analyzed in this study. The analysis was based on a comparison of data from various sources: weather stations, NOAA OISSTv2 satellite-based data, atmospheric reanalyses ECMWF ERA5, NASA MERRA-2, and NCEP/NCAR, and the outputs from 33 Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). CMIP6 models results from the historical and Shared Socioeconomic Pathways (SSPs) experiments were utilized. Over the period 1940–2023, NSAT exhibited variable changes across the Caspian region. Weather stations in the northwestern part of the region indicated NSAT increases of 0.9 ± 0.2 °C for 1985–2023. In the central-western part of the Caspian region, the increase in average NSAT between 1940–1969 and 1994–2023 was 1.4 °C with a spatial standard deviation of 0.3 °C. In the southern part of the Caspian region, the increase in average NSAT between 1986–2004 and 2005–2023 was 0.8 ± 0.1 °C. Importantly, all 33 CMIP6 models, as well as the ERA5 reanalysis, captured an average NSAT increase of approximately 1.3 ± 0.5 °C for the whole Caspian region between 1940–1969 and 1994–2023. From the ERA5 data, the increase in NSAT was more pronounced in the north (~1.6 °C) than in the central Caspian region, with the most significant warming observed in the mountainous regions of Iran (up to 3.0 °C). Under various CMIP6 SSPs scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), projections indicate an increase in average NSAT across the study region. Comparing the periods 1994–2023 and 2070–2099, the projected NSAT increases are 1.7 ± 0.7 °C, 2.8 ± 0.8 °C, 4.0 ± 0.9 °C, and 5.2 ± 1.2 °C, respectively. For the earlier period of 2024–2053 relative to 1994–2023, the projected NSAT increases are 1.2 ± 0.4 °C, 1.3 ± 0.4 °C, 1.4 ± 0.4 °C, and 1.7 ± 0.5 °C. Notably, the projected increase in NSAT is slower over the Caspian Sea compared to the surrounding land areas. Full article

Oil content is a critical component of yield production in Mediterranean olive orchards, but it has received limited attention in modeling olive cultivation under extreme weather conditions. To address this gap, statistical and regression models based on multiple oil content measurements from field trials conducted with representative olive cultivars in the Guadalquivir basin (southern Iberian Peninsula), together with the latest future climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for the Iberian Peninsula, were integrated to improve the modeling of its behavior under future climate conditions. Temperature was the most influential factor affecting the olive oil accumulation pattern. Summer temperature was negatively correlated with the onset of oil accumulation, the accumulation rate, and the maximum oil content (MOC), while it was positively correlated with the date at which MOC was reached. When these relationships were combined with CMIP6 climate projections, inland southern Spain emerge as one of the most affected areas in the Iberian Peninsula. In the near future period (2040–2069), projected climate warning is expected to result in an earlier onset of oil accumulation, delays of up to 33 days in reaching MOC, and reductions in MOC of up to 17.5 percentage points, corresponding to an average olive oil yield loss of up to 30.3%, considering only the olive oil yield loss associated with the reduction in MOC. These changes vary in intensity depending on the location, cultivar, climate period and the greenhouse gas emission scenario considered. This study confirms the critical importance of temperature in olive oil production, highlights the need to incorporate functions that account for the effects of rising temperature on MOC, and emphasizes the identification of adaptation measures to cope with increasing temperatures and more frequent heat waves. Full article

This study investigates the future temperature changes in the climate-vulnerable region of the Eastern Mediterranean. The results from seventeen (17) CMIP6 (6th Phase of Coupled Model Intercomparison Project) model simulations are analyzed. The analysis is focused on the SSP2-4.5 and SSP5-8.5 scenarios. The ERA5 reanalysis is used as a reference dataset to investigate the performance of CMIP6 simulations to accurately reproduce the mean temperature in the Eastern Mediterranean region. The results show that CMIP6 model simulations vary regarding their efficiency for capturing the mean temperature. Future projections show that significant warming is shown during the last period of the 21st century. The continental Balkan and Turkish regions are recognized as the most affected areas regarding future warming. The increase in temperature spatially ranges (in local scale) from 1.5 °C to 4.5 °C for the SSP2-4.5 scenario and from 3.0 °C to 8.0 °C for the SSP5-8.5 scenario. Finally, the seasonal analysis indicates that summer (JJA) shows the maximum temperature increase compared with the other seasons. Full article

Smart meters (SMs) are essential components of modern smart grids, enabling real-time and accurate monitoring of electricity consumption. However, their evaluation is often hindered by proprietary communication protocols and the high cost of commercial testing tools. This study presents a low-cost, open-source experimental platform for smart meter validation, using a microcontroller and light sensor to detect optical pulses emitted by standard SMs. This non-intrusive approach circumvents proprietary restrictions while enabling transparent and reproducible comparisons. A case study was conducted comparing the static meter GAMA 300 model, manufactured by Elgama-Elektronika Ltd. (Vilnius, Lithuania), which is a closed-source commercial meter, with theTexas Instruments EVM430-F67641 evaluation module, manufactured by Texas Instruments Inc. (Dallas, TX, USA), which serves as an open-source reference design. Statistical analyses—based on confidence intervals and ANOVA—revealed a mean deviation of less than 1.5% between the devices, confirming the platform’s reliability. The system supports indirect power monitoring without hardware modification or access to internal data, making it suitable for both educational and applied contexts. Compared to existing tools, it offers enhanced accessibility, modularity, and open-source compatibility. Its scalable design supports IoT and environmental sensor integration, aligning with Internet of Energy (IoE) principles. The platform facilitates transparent, reproducible, and cost-effective smart meter evaluations, supporting the advancement of intelligent energy systems. Full article

This study investigates the impacts of near-term climate forcers (NTCFs) and ozone precursor emissions on particulate matter (PM_2.5) concentrations in East Asia (EA). Our analysis used the Coupled Model Intercomparison Project Phase 6 Aerosols and Chemistry Model Intercomparison Project (AerChemMIP) dataset to assess the potential changes in air quality under varying emission scenarios for the present day (1995–2014) and near-term future (2015–2054). Present-day PM_2.5 concentrations in EA averaged 14.3 ± 2.6 μg/m³, with significant regional variation: East China (32.43 μg/m³), Korea (13.71 μg/m³), and Japan (7.51 μg/m³). A reduction in historical NTCF emissions would lower PM_2.5 concentrations by approximately 43% across EA, whereas reducing O₃ precursors would yield an approximately 10% decrease. Under the SSP370 scenario, PM_2.5 concentrations are projected to increase by 16% in the near-term future (2045–2054). However, robust NTCF mitigation could reduce PM_2.5 levels by approximately 40%, primarily by decreasing sulfate and organic aerosols, which are the dominant contributors of historical PM_2.5 variability. Despite substantial projected improvements, achieving the World Health Organization’s stringent air quality guidelines remains challenging, highlighting the necessity for enhanced emissions control targeting key pollutant sources. These insights are crucial to East Asian policymakers aiming to implement effective air quality management strategies. Full article