Search Results (36)

It is essential to emphasize the significant impacts of climate change, which are evident in the form of severe and prolonged droughts, hurricanes, snowstorms, and other climatic disturbances. These challenges are particularly pronounced in urban environments and among human populations. The situation is further aggravated by the increasing utilization of available open spaces for residential and industrial development, leading to heightened energy consumption, elevated pollution levels, and increased carbon emissions, all of which negatively affect public health. The primary objective of this review article is to provide a comprehensive evaluation of current research, with a particular focus on the innovative use of residual biomass from urban vegetation for biochar production in the United States. This research entails an exhaustive review of existing literature to assess the implementation of a carbon-negative wood biomass biochar system as a strategic approach to sustainable urban management. By transforming urban wood waste—including tree trimmings, construction debris, and storm-damaged timber—into biochar through pyrolysis, a thermochemical process that sequesters carbon while generating renewable energy, we can leverage this valuable resource. The resulting biochar offers a range of co-benefits: it enhances soil health, improves water retention, reduces stormwater runoff, and lowers greenhouse gas emissions when applied in urban green spaces, agriculture, and land restoration projects. This review highlights the advantages and potential of converting urban wood waste into biochar while exploring how municipalities can strengthen their green ecosystems. Furthermore, it aims to provide a thorough understanding of how the utilization of woody biomass biochar can contribute to mitigating urban carbon emissions across the United States. Full article

Wildfires cause substantial ecological disturbances, altering vegetation dynamics and soil properties over extended periods. This study investigated the influence of vegetation burn severity on post-fire vegetation recovery rates using multi-temporal Landsat 8 surface reflectance imagery from 2014 to 2023. Two major fire events in Nevada, the Snowstorm Fire (2017) and the South Sugar Loaf Fire (2018), were examined through four spectral indices: the Normalized Difference Vegetation Index (NDVI), Moisture Stress Index (MSI), Modified Chlorophyll Absorption Ratio Index 2 (MCARI2), and Land Surface Temperature (LST). Statistical techniques, including the Mann–Kendall trend test and Linear Mixed Effects models, were applied to assess pre- and post-fire trends across burn severity classes. Results showed that vegetation recovery was primarily driven by temporal factors rather than burn severity, especially in the Snowstorm Fire. In the South Sugar Loaf Fire, significant changes were observed in LST and NDVI scores in low-severity areas, while MSI and MCARI2 scores exhibited significant recovery differences in high-severity zones. These findings suggest that post-fire vegetation dynamics vary spatially and temporally, with severity effects more pronounced in certain conditions. The study underscores the effectiveness of spectral indices in capturing post-disturbance recovery and supports their application in guiding site-specific restoration and long-term ecosystem management. Full article

The accuracy of ERA5 reanalysis datasets and their applicability in the coastal area of Bohai Bay are crucial for weather forecasting and environmental protection research. However, synthesis evaluation of ERA5 in this region remains lacking. In this study, using a tropospheric wind profile radar (CFL-06L) placed in coastal Huanghua city, the deviations of ERA5 reanalysis data are assessed from the ground to an altitude of 5 km. The results indicate that the wind speed of ERA5 reanalysis data exhibits good consistency from the surface to the tropospheric level of about 5 km, with R² values ranging from 0.5 to 0.85. The lowest mean wind speed error, less than 3 m/s, occurs in the middle layer, while larger errors are observed at the surface and upper layers. Specifically, at 150 m, the R² is as low as 0.5, with numerous outliers around 5000 m. Seasonal analysis shows that the ERA5 wind field performs best in summer and worst in autumn and winter, especially at lower levels affected by circulation systems, high stratus clouds, and aerosols, with errors reaching up to 10 m/s. Further analysis of extreme weather events, such as heavy rain; hot, dry winds; and snowstorms, reveals that the effects of sea-land winds and strong convective systems significantly impact the observation of wind profiles and the assimilation of reanalysis data, particularly under the constrain of boundary layer height. Additionally, we also find that the transition of sea-land breeze is capable of triggering the nighttime low-level jet, thereby downward transporting the aloft ozone to the ground and resulting in an abnormal increase in the surface ozone concentration. The study provides a scientific basis for improving meteorological forecasting, optimizing wind energy resource utilization, and formulating environmental protection policies, highlighting its significant scientific and practical application value. Full article

This study introduces an innovative analytical methodology for examining the interconnections among the atmosphere, ocean, and society. The primary area of interest pertains to the North Atlantic Oscillation (NAO), a notable phenomenon characterised by daily to decadal fluctuations in atmospheric conditions over the Northern Hemisphere. The NAO has a prominent impact on winter weather patterns in North America, Europe, and to some extent, Asia. This impact has significant ramifications for civilization, as well as for marine, freshwater, and terrestrial ecosystems, and food chains. Accurate predictions of the surface NAO hold significant importance for society in terms of energy consumption planning and adaptation to severe winter conditions, such as winter wind and snowstorms, which can result in property damage and disruptions to transportation networks. Moreover, it is crucial to improve climate forecasts in order to bolster the resilience of food systems. This would enable producers to quickly respond to expected changes and make the required modifications, such as adjusting their food output or expanding their product range, in order to reduce potential hazards. The forecast centres prioritise and actively research the predictability and variability of the NAO. Nevertheless, it is increasingly evident that conventional analytical methods and prediction models that rely solely on scientific methodologies are inadequate in comprehensively addressing the transdisciplinary dimension of NAO variability. This includes a comprehensive view of research, forecasting, and social ramifications. This study introduces a new framework that combines sophisticated Big Data analytic techniques and forecasting tools using a generalised additive model to investigate the fluctuations of the NAO and the interplay between the ocean and atmosphere. Additionally, it explores innovative approaches to analyze the socio-economic response associated with these phenomena using text mining tools, specifically modern deep learning techniques. The analysis is conducted on an extensive corpora of free text information sourced from media outlets, public companies, government reports, and newspapers. Overall, the result shows that the NAO index has been reproduced well by the Deep-NAO model with a correlation coefficient of 0.74. Full article

A thorough understanding of the development process of grazing activities and an elucidation of their complex mechanisms are crucial for the formulation and adjustment of livestock management policies. In the Selinco region of the Qinghai–Tibet Plateau, we conducted a comprehensive analysis of year-end livestock numbers and densities over the past 30 years. The results indicate a gradual decline in overall livestock numbers in the Selinco region during this period, with a notable decrease between 2004 and 2014, followed by stabilization. Notably, the number of yaks has significantly increased, whereas the numbers of sheep, goats, and horses have markedly decreased. Regarding livestock density, there is a spatial pattern of decrease from northwest to southeast, with the density order being Seni District > Bange County > Anduo County > Shenzha County > Nima County > Shuanghu County. Between 2004 and 2014, most counties experienced a significant decline in livestock density, exhibiting a trough–peak pattern. However, after 2014, a complex spatiotemporal dynamic emerged. Concerning driving factors, from 1990 to 2004, rural population and economic development were the primary influences on livestock density. After 2004, forage–livestock balance management policies, snowstorms, and fluctuations in livestock prices likely became the main influencing factors. Further detailed analysis of these factors is essential for developing more effective management strategies. Full article

The accurate diagnosis of gout frequently constitutes a challenge in clinical practice, as it bears a close resemblance to other rheumatologic conditions. An undelayed diagnosis and an early therapeutic intervention using uric acid lowering therapy (ULT) is of the utmost importance for preventing bone destruction, the main point of managing gout patients. Advanced and less invasive imaging techniques are employed to diagnose the pathology and ultrasonography (US) stands out as a non-invasive, widely accessible and easily reproducible method with high patient acceptability, enabling the evaluation of the full clinical spectrum in gout. The 2023 EULAR recommendations for imaging in diagnosis and management of crystal-induced arthropathies in clinical practice state that US is a fundamental imagistic modality. The guidelines underline its effectiveness in detecting crystal deposition, particularly for identifying tophi and the double contour sign (DCS). Its utility also arises in the early stages, consequent to synovitis detection. US measures of monosodium urate (MSU) deposits are valuable indicators, sensitive to change consequent to even short-term administration of ULT treatment, and can be feasibly used both in current daily practice and clinical trials. This paper aimed to provide an overview of the main US features observed in gout patients with reference to standardized imaging guidelines, as well as the clinical applicability both for diagnosis accuracy and treatment follow-up. Our research focused on summarizing the current knowledge on the topic, highlighting key data that emphasize gout as one of the few rheumatological conditions where US is recognized as a fundamental diagnostic and monitoring tool, as reflected in the most recent classification criteria. Full article

In order to provide insights into how various page views are influenced by public engagement with weather information and to shed light on the patterns of warning issuance across different seasons and regions, this study analyzes the multi-dimensional characteristics of city weather forecast page views and the spatiotemporal characteristics of early warning information in China, from 1 March 2020 to 31 August 2023. This is achieved by utilizing the daily page views of city weather forecasts and meteorological warning data, comparing the public’s attention to weather during holidays versus regular days, assessing the public’s attention to weather under different meteorological warning levels, and performing statistical analysis of the spatiotemporal scale of meteorological disasters. Our analysis shows that compared to weekends and holidays, the public pays more attention to the weather on weekdays, and the difference between weekdays and national statutory holidays is more significant. Due to the widespread impact of heat waves, typhoons, severe convective weather, and geological disasters caused by heavy rainfall, public awareness and participation in flood season weather forecasting have significantly increased. Under red alerts, flash floods, typhoons, and geological risks are the primary concerns. Orange alerts predominantly feature flash floods, rainstorms, typhoons, snowstorms, and cold waves, while sandstorms attract the most attention during yellow alerts. Droughts, however, receive relatively less attention regardless of the warning level. Seasonal patterns in the issuance of meteorological warnings reveal a peak in summer, particularly with typhoons and rainstorms being the main concerns in July, followed by high temperatures and additional typhoon warnings in August. Heavy sea surface wind warnings exhibit a strong seasonal trend, with the majority issued during the winter months. Regionally, southern China experiences the highest frequency of severe convection weather warnings, with provinces such as Jiangxi, Guangxi, and Hunan being the most affected. Full article

Based on ground observed data, S-band dual-polarization radar data, and ERA-5 reanalysis data, the statistical characteristics of polarimetric parameters and the application of melting layer (ML) and hydrometeor classification (HCL) products during eight snowstorm events in Jiangsu Province from 2020 to 2022 were investigated. A heavy snowstorm that went through different phases of rain, sleet, and pure snow and that occurred on 29 December 2020 was also analyzed as a typical example. The results showed the following: During the phase transition between rain and snow in the Jiangsu region, the basic reflectivity factor Z_H ≥ 27 dBZ, the zero-order lag correlation coefficient CC ≤ 0.93, and the differential reflectivity Z_DR ≥ 1.0 dB were important indicators for judging the melting layer while the specific differential phase K_DP changed slightly. The snowstorm event was well observed and recorded by the Yancheng dual-polarimetric radar, whose low value area of CC coincided mostly with the melting layer. The ML products and HCL products based on fuzzy-logic hydrometeor classification algorithms can help identify the melting layer and the properties of precipitation particles. ML products are more reliable when the melting layer is high and can better show the trends of melting layer decline. They can certainly serve as a reference for detecting and judging precipitation phase changes in winter in Jiangsu Province. Full article

Background and Objectives: The surge in breast-related surgeries in Korea underscores the critical need for an accurate early diagnosis of silicone breast implant-related issues. Complications such as BIA-ALCL and BIA-SCC add complexity to breast health concerns, necessitating vigilant monitoring. Despite advancements, discrepancies persist between ultrasonographic and pathologic classifications of silicone implant ruptures, highlighting a need for enhanced diagnostic tools. This study explores the reliability of ultrasonography in diagnosing silicone breast implant ruptures and determining the extent of silicone migration, specifically with a focus on guiding potential capsulectomy based on pathology. Materials and Methods: A comprehensive review of medical records encompassing 5557 breast implants across 2790 patients who underwent ultrasound-assisted examinations was conducted. Among the screened implants, 8.9% (249 cases) were diagnosed with silicone breast implant rupture through ultrasonography. Subsequently, 89 women underwent revisional surgery, involving capsulectomy. The pathological analysis of 111 periprosthetic capsules from these cases aimed to assess the extent of silicone migration, and the findings were juxtaposed with the existing ultrasonographic rupture classification. Results: The diagnostic agreement between preoperative sonography and postoperative findings reached 100% for silicone breast implant ruptures. All eighty prosthetic capsules exhibiting a snowstorm sign in ultrasonography demonstrated silicone migration to capsules upon pathologic findings. Conclusions: High-resolution ultrasonography emerged as a valuable and reliable imaging modality for diagnosing silicone breast implant ruptures, with a notable ability to ascertain the extent of free silicone migration to capsules. This diagnostic precision is pivotal in informing decisions about potential capsulectomy during revisional surgery. The study advocates for an update to the current binary ultrasonographic classification, suggesting a more nuanced categorization into three types (subcapsular, intracapsular, and extracapsular) based on pathology. Full article

The development of integrated public transportation networks has received widespread attention in recent years. Especially in global northern cities, improving the substitution of subways for buses could meet population travel demand during snowstorms, which minimizes the impact of snowstorms on the public transportation network. Furthermore, the development of rail transit is conducive to the intensive and efficient use of land resources. Therefore, in this study, we selected a northern Chinese city, Shenyang, as a case study. For obtaining the population travel demand, we collected the actual population flow data in the morning and evening peaks during snowstorms. The network analysis was used to identify the loopholes and key stations in the subway and bus networks, respectively. A coupling model was built to measure the coupling value of each station in the subway and bus networks, according to its population travel demand and supply capacity, which was further used to measure the substitution of subways for buses in the morning and evening peaks during snowstorms. The results indicate that some subway stations were in a coupling state, while their surrounding bus stations were in a decoupling state. These subway stations could replace the bus stations to reduce the impact and damage of snowstorms on public transportation network. However, some subway stations and the surrounding bus stations were all in a decoupling state, which were under great pressure to meet the population commuting demand during snowstorms. This study can provide insight into optimizing public transportation network planning and design in many northern regions and help to coordinate land and transportation utilization. Full article

Anthropogenic salt inputs have impacted many streams in the U.S. for over a century. Urban stream salinity is often chronically elevated and punctuated by episodic salinization events, which can last hours to days after snowstorms and the application of road salt. Here, we investigated the impacts of freshwater salinization on total dissolved nitrogen (TDN) and NO₃⁻/NO₂⁻ concentrations and fluxes across time in urban watersheds in the Baltimore-Washington D.C. metropolitan area of the Chesapeake Bay region. Episodic salinization from road salt applications and snowmelt quickly mobilized TDN in streams likely through soil ion exchange, hydrologic flushing, and other biogeochemical processes. Previous experimental work from other studies has shown that salinization can mobilize nitrogen from sediments, but less work has investigated this phenomenon with high-frequency sensors and targeted monitoring during road salt events. We found that urban streams exhibited elevated concentrations and fluxes of TDN, NO₃⁻/NO₂⁻, and specific conductance that rapidly peaked during and after winter road salt events, and then rapidly declined afterwards. We observed plateaus in TDN concentrations in the ranges of the highest specific conductance values (between 1000 and 2000 μS/cm) caused by road salt events. Plateaus in TDN concentrations beyond a certain threshold of specific conductance values suggested source limitation of TDN in watersheds (at the highest ranges in chloride concentrations and ranges); salts were likely extracting nitrogen from soils and streams through ion exchange in soils and sediments, ion pairing in soils and waters, and sodium dispersion of soils to a certain threshold level. When watershed transport was compared across land use, including a forested reference watershed, there was a positive relationship between Cl⁻ loads and NO₃⁻/NO₂⁻ loads. This relationship occurred across all sites regardless of land use, which suggests that the mass transport of Cl⁻ and NO₃⁻/NO₂⁻ are likely influenced by similar factors such as soil ion exchange, ion pairing, sodium dispersion of soils, hydrologic flushing, and biogeochemical processes. Freshwater salinization has the potential to alter the magnitude and timing of total dissolved nitrogen delivery to receiving waters during winter months following road salt applications, and further work should investigate the seasonal relationships of N transport with salinization in urban watersheds. Full article

Forest water dynamics and hydro-chemical characteristics are essential for understanding forest hydrology and ecological processes. Yet, such understanding is limited by a lack of long-term monitoring data and observations from specialized forest ecosystems such as those from high elevation. Here, we analyze the precipitation redistribution including interception, stemflow, and throughfall and hydro-chemical characteristics by using a 15 year (2005–2019) precipitation dataset in a high elevation, evergreen broad-leaved forest in Southwest China. The forest experienced an obvious seasonal variation in precipitation with a monthly average of 117.31 ± 91.21 mm. The precipitation redistribution was influenced by precipitation intensity and leaf area index and differed inter-annually and intra-annually, with a general pattern: throughfall > canopy interception > stemflow. Throughfall rate increased significantly from 2015 to 2019 after experiencing the January 2015 snowstorm. The majority of water within the study site was retained in the soil and apoplastic materials. The primary means of water output was evapotranspiration, with minimal surface runoff. Quality of surface water was affected by the weathering of rocks, resulting in a lower pH than that of atmospheric precipitation. During the rainy season, elemental Ca and Mg showed negative correlation with precipitation due to plant mediation. The other elements, pH, total dissolved solids, precipitation, air temperature, and water temperature showed different degrees of correlation with each other. Overall, while the water balance fluctuated over the past 15 years, the water-holding capacity remained relatively stable. Alkali cations such as Ca²⁺, Mg²⁺, and K⁺ in the water body showed a decreasing trend during 2005–2019, which is a potential threat to ecological stability. Full article

Differentiating between snow and clouds presents a formidable challenge in the context of mapping snow cover over the Qinghai–Tibetan Plateau (QTP). The frequent presence of cloudy conditions severely complicates the discrimination of snow cover from satellite imagery. To accurately monitor the spatiotemporal evolution of snow cover, it is imperative to address these challenges and enhance the segmentation schemes employed for snow cover assessment. In this study, we devised a pixel-wise classification algorithm based on Support Vector Machine (SVM) called the 3-D Orientation Gradient algorithm (3-D OG), which captures the variations of the gradient direction of snow and clouds in spatiotemporal dimensions based on geostationary satellite “Fengyun-4A” (FY-4A) multi-spectral and multi-temporal optical imagery. This algorithm assumes that the speed and direction of clouds and snow are different in the process of movement leading to their discrepancy of gradient characteristics in time and space. Therefore, in this algorithm, the gradient of the images in the spatiotemporal dimensions is calculated first, and then the movement angle and trend are obtained based on that. Finally, the feature space is composed of the multi-spectral image, gradient image, and movement feature maps, which are used as the input of the SVM. Our results demonstrate that the proposed algorithm can identify snow and clouds more accurately during snowfall by utilizing the FY-4A’s high temporal resolution image. Weather station data, which was collected during snowstorms in the QTP, were used for evaluating the accuracy of our algorithm. It is demonstrated that the overall accuracy of snow cover segmentation by using the 3-D OG algorithm is improved by at least 12% and 10% as compared to snow products of Fengyun-2 and MODIS, respectively. Overall, the proposed algorithm has overcome the axial swing errors existing in Geostationary satellites and is successfully applied to cloud and snow segmentation in QTP. Furthermore, our study underscores that the visible and near-infrared bands of Fengyun-4A can be used for near real-time snow cover monitoring with high performance using the 3-D OG algorithm. Full article

As the primary greenhouse gas, CO₂ emission has noticeably increased over the past decades resulting in global warming and climate change. Surprisingly, anthropogenic activities have increased atmospheric CO₂ by 50% in less than 200 years, causing more frequent and severe rainfall, snowstorms, flash floods, droughts, heat waves, and rising sea levels in recent times. Hence, reducing the excess CO₂ in the atmosphere is imperative to keep the global average temperature rise below 2 °C. Among many CO₂ mitigation approaches, CO₂ capture using porous materials is considered one of the most promising technologies. Porous solid materials such as carbons, silica, zeolites, hollow fibers, and alumina have been widely investigated in CO₂ capture technologies. Interestingly, porous silica-based materials have recently emerged as excellent candidates for CO₂ capture technologies due to their unique properties, including high surface area, pore volume, easy surface functionalization, excellent thermal, and mechanical stability, and low cost. Therefore, this review comprehensively covers major CO₂ capture processes and their pros and cons, selecting a suitable sorbent, use of liquid amines, and highlights the recent progress of various porous silica materials, including amine-functionalized silica, their reaction mechanisms and synthesis processes. Moreover, CO₂ adsorption capacities, gas selectivity, reusability, current challenges, and future directions of porous silica materials have also been discussed. Full article

Winter cropping can be used to achieve a double benefit for producers: as soil cover and an additional economic crop cycle. Flax (Linum usitatissimum L.) is a spring crop growing in the northern region of the US and used as a fall cover crop in some southern states. In this study, eight seed-type flax varieties were evaluated for production as a fall/winter crop for the Commonwealth of Virginia, a mid-latitude region. Mixed results were obtained; however, the crop showed winter tolerance and potential productivity, especially when the frequency of sub-zero winter temperatures was low. Planting too early in the fall allows for significant stem development that increases susceptibility to physical damage by snowstorms and winter frost. Seed yield was low compared to spring-planted crops; however, it reached up to 400 kg ha⁻¹ in some varieties. Seed weights were comparable to those found elsewhere for the same or other varieties, and seed protein and crude fat content ranged from 228–270 and 189–234 g kg⁻¹, respectively. Across years and varieties, P, K, Mg, Ca, and S averaged 7.74, 9.88, 3.88, 2.86, and 2.35 g kg⁻¹, respectively. Mineral elements Fe, Zn, Mn, Cu, and B averaged 95, 62, 21, and 10 mg kg⁻¹, respectively. However, early maturity in spring ahead of other grains subjected it to significant losses to wild birds. Fall-planted flax has potential as a cover crop and may be harvested for seed, which in addition to a summer crop, provides a producer with economic returns from two crop cycles per year. Full article