Search Results (27,619)

The Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) mission provides valuable three-dimensional precipitation structure data on a global scale and has been widely used in hydrometeorological research. However, due to its spatial resolution limitations and inherent algorithmic assumptions, the accuracy of GPM precipitation estimates can exhibit systematic biases, especially under complex terrain conditions or in the presence of variable precipitation structures, such as light stratiform rain or intense convective storms. In this study, we evaluated the near-surface precipitation rate estimates from the GPM-DPR Level 2A product using over 1440 min of disdrometer observations collected across China from 2021 to 2023. Based on three years of stable stratiform precipitation data from the Jinghe station, we developed a least squares linear correction model for radar reflectivity. Independent validation using national disdrometer data from 2023 demonstrated that the corrected reflectivity significantly improved rainfall estimates under light precipitation conditions, although improvements were limited for convective events or in complex terrain. To further enhance retrieval accuracy, we introduced a regionally adaptive R–Z relationship scheme stratified by precipitation type and terrain category. Applying these localized relationships to the corrected reflectivity yielded more consistent rainfall estimates across diverse conditions, highlighting the importance of incorporating regional microphysical characteristics into satellite retrieval algorithms. The results indicate that the accuracy of GPM precipitation retrievals is more significantly influenced by precipitation type than by terrain complexity. Under stratiform precipitation conditions, the GPM-estimated precipitation data demonstrate the highest reliability. The correction framework proposed in this study is grounded on ground-based observations and integrates regional precipitation types with terrain characteristics. It effectively enhances the applicability of GPM-DPR products across diverse environmental conditions in China and offers a methodological reference for correcting satellite precipitation biases in other regions. Full article

The precipitation of minerals, in particular carbonates, is a widespread phenomenon in all ecosystems, where it assumes a high relevance both from a geological and biogeochemical standpoint. Most carbonate rocks are of biological origin and made in an aquatic environment. In particular, bioprecipitation of carbonates is believed to have started in the Mesoproterozoic Era, thanks to a process often driven by photosynthetic microorganisms. Nevertheless, an important contribution to carbonate precipitation is also due to the metabolic activity of heterotrophic bacteria, which is not restricted to specific taxonomic groups or to specific environments, making this process a ubiquitous phenomenon. In this framework, the relationship between carbonatogenic microorganisms and other living organisms assumes a particular interest. This study aims to isolate and identify the culturable heterotrophic bacterial component associated with the coenosarc of Corallium rubrum in order to evaluate the occurrence of strains able to precipitate carbonates. In particular, the study was focused on the identification and characterisation of bacterial strains isolated from a coral coenosarc showing a high carbonatogenic capacity under laboratory conditions. Samples of C. rubrum were taken in the coastal waters of three Italian regions. The concentration of the aerobic heterotrophic microflora colonising C. rubrum coenosarc samples spanned from 3 to 6∙10⁶ CFU/cm². This variation in microbial populations colonising the C. rubrum coenosarc, spanning over 6 orders of magnitude, is not mirrored by a corresponding variability in the colony morphotypes recorded, with the mean being 5.1 (±2.1 sd). Among these bacteria, the carbonatogenic predominant species was Staphylococcus equorum (93% of the isolates), whereas Staphylococcus xylosus and Shewanella sp. accounted only for 3% of isolates each. All these strains showed a remarkable capacity of precipitating calcium carbonate, in the form of calcite crystals organised radially as well crystalised spherulites (S. equorum) or coalescing spherulites (Shewanella sp.). S. xylosus only produced amorphous precipitates of calcium carbonate. All bacterial strains identified were positive both for the production of urease and carbon anhydrase in vitro at 30 °C. It seems that they potentially possess the major biochemical abilities conducive to Ca²⁺ precipitation, as they showed in vitro. In addition, all our carbonatogenic isolates were able to hydrolyse the phytic acid calcium salt and then were potentially able to induce precipitation of calcium phosphates also through such a mechanism. Full article

Concrete cracks and sulfate degradation severely compromise structural durability, highlighting the need for sustainable solutions to enhance longevity and minimize environmental impact. This study assesses the efficacy of bacterial self-healing technology utilizing Bacillus megaterium (BM) and Bacillus sphaericus (BS) in enhancing the resistance of concrete to sulfate attacks and improving its mechanical properties. Bacterial suspensions (1% and 2.5% of cement weight) were mixed with concrete containing silica fume or fly ash (10% of cement weight) and cured in freshwater or sulfate solutions (2%, 5%, and 10% concentrations). Specimens were tested for compressive strength, flexural strength, and microstructure using a Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectroscopy (EDS), and X-ray diffraction (XRD) at various ages. The results indicate that a 2.5% bacterial content yielded the best performance, with BM surpassing BS, enhancing compressive strength by up to 41.3% and flexural strength by 52.3% in freshwater-cured samples. Although sulfate exposure initially improved early-age strength by 1.97% at 7 days, it led to an 8.5% loss at 120 days. Bacterial inclusion mitigated sulfate damage through microbially induced calcium carbonate precipitation (MICP), sealing cracks, and bolstering durability. Cracked specimens treated with BM recovered up to 93.1% of their original compressive strength, promoting sustainable, sulfate-resistant, self-healing concrete for more resilient infrastructure. Full article

The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available hydrometeorological observation data and satellite remote sensing monitoring data from 2001 to 2020, a machine learning model of the Lancang–Mekong Basin was developed to reconstruct the basin’s hydrological processes, and identify the occurrence patterns and influencing mechanisms of water-related hazards. The results show that, against the background of climate change, the Lancang–Mekong Basin is affected by the increasing frequency and intensity of extreme precipitation events. In particular, Rx1day, Rx5day, R10mm, and R95p (extreme precipitation indicators determined by the World Meteorological Organization’s Expert Group on Climate Change Monitoring and Extreme Climate Events) in the northwestern part of the Mekong River Basin show upward trends, with the average maximum daily rainfall increasing by 1.8 mm/year and the total extreme precipitation increasing by 18 mm/year on average. The risks of flood and drought disasters will continue to rise. The flood peak period is mainly concentrated in August and September, with the annual maximum flood peak ranging from 5600 to 8500 m³/s. The Stung Treng Station exhibits longer drought duration, greater severity, and higher peak intensity than the Chiang Saen and Pakse Stations. At the Pakse Station, climate change and hydropower development have altered the non-drought proportion by −12.50% and +15.90%, respectively. For the Chiang Saen Station, the fragmentation degree of the drought index time series under the baseline, naturalized, and hydropower development scenarios is 0.901, 1.16, and 0.775, respectively. These results indicate that hydropower development has effectively reduced the frequency of rapid drought–flood transitions within the basin, thereby alleviating pressure on drought management efforts. The regulatory role of the cascade reservoirs in the Lancang River can mitigate risks posed by climate change, weaken adverse effects, reduce flood peak flows, alleviate hydrological droughts in the dry season, and decrease flash drought–flood transitions in the basin. The research findings can enable basin managers to proactively address climate change, develop science-based technical pathways for hydropower dispatch, and formulate adaptive disaster prevention and mitigation strategies. Full article

The Amazon Basin plays a crucial role in the global hydrological cycle, where seasonal and interannual variations in terrestrial water storage (TWS) are essential for understanding climate–hydrology coupling mechanisms. This study utilizes data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its follow-on mission (GRACE-FO, collectively referred to as GRACE) to investigate the spatiotemporal dynamics of hydrological mass changes in the Amazon Basin from 2002 to 2021. Results reveal pronounced spatial heterogeneity in the annual amplitude of TWS, exceeding 65 cm near the Amazon River and decreasing to less than 25 cm in peripheral mountainous regions. This distribution likely reflects the interplay between precipitation and topography. Vertical displacement measurements from the Global Navigation Satellite System (GNSS) show strong correlations with GRACE-derived hydrological load deformation (mean Pearson correlation coefficient = 0.72) and reduce its root mean square (RMS) by 35%. Furthermore, the study demonstrates that existing hydrological models, which neglect groundwater dynamics, underestimate hydrological load deformation. Principal component analysis (PCA) of the Amazon GNSS network demonstrates that the first principal component (PC) of GNSS vertical displacement aligns with abrupt interannual TWS fluctuations identified by GRACE during 2010–2011, 2011–2012, 2013–2014, 2015–2016, and 2020–2021. These fluctuations coincide with extreme precipitation events associated with the El Niño–Southern Oscillation (ENSO), confirming that ENSO modulates basin-scale interannual hydrological variability primarily through precipitation anomalies. This study provides new insights for predicting extreme hydrological events under climate warming and offers a methodological framework applicable to other critical global hydrological regions. Full article

One of the main challenges in hydroxyapatite research is to develop cost-effective synthesis methods that consistently produce materials closely resembling natural bone, while maintaining high biocompatibility, phase purity, and mechanical stability for biomedical applications. Traditional synthetic techniques frequently fail to provide desirable mechanical characteristics and antibacterial activity, necessitating the development of novel strategies based on natural precursors and selective ion doping. The present study aims to explore the possibility of synthesizing hydroxyapatite through the co-precipitation method, followed by a microwave-assisted hydrothermal maturation process. The main CaO sources selected for this study are eggshells and mussel shells. Cu²⁺ and Sr²⁺ ions were added into the hydroxyapatite structure at concentrations of 1% and 5% to investigate their potential for biomedical applications. Furthermore, the morpho-structural and biological properties have been investigated. Results demonstrated the success of hydroxyapatite synthesis and ion incorporation into its chemical structure. Moreover, HAp samples exhibited significant antimicrobial properties, especially the samples doped with 5% Cu and Sr. Additionally, all samples presented good biological activity on MC3T3-E1 osteoblast cells, demonstrating good cellular viability of all samples. Therefore, by correlating the results, it could be concluded that the undoped and doped hydroxyapatite samples are suitable biomaterials to be further applied in orthopedic applications. Full article

Glaciers and glacierets of the Kuznetsky Alatau Mountains are distributed at altitudes of 1200–1500 m above sea level, which is not typical for continental areas. The main factor contributing to the persistence of glaciation here is abundant winter precipitation. According to ground surface temperature measurements, the negative annual values are typical for upper glacier boundaries only. Since intensive study during the compilation of the USSR Glacier Inventory (1965–1980), the glaciation of the region has undergone notable changes. To assess the current state of glaciation, Sentinel-2 satellite images were used; contours of the glaciers were traced on the basis of images from 2021 to 2023. In total, 78 glaciers and 57 glacierets were identified. UAV imagery and field inspection were used for validation. The total glaciated area has reduced from 8.5 to 3.1 km², which is 50–75% for selected river basins, with slope morphological types decreasing the most. According to our opinion, the morphological classification requires clarification due to absence of hanging glaciers, described previously. Full article

Precipitation concentration reflects the uneven temporal distribution of rainfall. It plays a critical role in water resource management and flood–drought risk under climate change. However, its long-term trends, associations with atmospheric teleconnections as potential drivers, and links to extreme heavy precipitation events remain poorly understood in complex basins like the Yangtze River Basin. This study analyzes these aspects using ground station data from 1960 to 2019 and conducts a comparison using the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM (GPM IMERG) satellite product. We calculated three indices—Daily Precipitation Concentration Index (PCID), Monthly Precipitation Concentration Index (PCIM), and Seasonal Precipitation Concentration Index (SPCI)—to quantify rainfall unevenness, selected for their ability to capture multi-scale variability and associations with extremes. Key methods include Mann–Kendall trend tests for detecting changes, Hurst exponents for persistence, Pettitt detection for abrupt shifts, random forest modeling to assess atmospheric teleconnections, and hot spot analysis for spatial clustering. Results show a significant basin-wide decrease in PCID, driven by increased frequency of small-to-moderate rainfall events, with strong spatial synchrony to extreme heavy precipitation indices. PCIM is most strongly associated with El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). GPM IMERG captures PCIM patterns well but underestimates PCID trends and magnitudes, highlighting limitations in daily-scale resolution. These findings provide a benchmark for satellite product improvement and support adaptive strategies for extreme precipitation risks in changing climates. Full article

Heavy rainfall events, characterized by extreme downpours that exceed 100 mm per day, pose an intensifying hazard to the densely settled valleys of the western Himalaya; however, their coupling with expanding urban land cover remains under-quantified. This study mapped the spatiotemporal exposure of built-up areas to heavy-day rainfall (HDR) across Jammu, Kashmir, and Ladakh and the adjoining areas by integrating daily Climate Hazards Group InfraRed Precipitation with Stations product (CHIRPS) precipitation (0.05°) with Global Human Settlement Layer (GHSL) built-up fractions within the Google Earth Engine (GEE). Given the limited sub-hourly observations, a daily threshold of ≥100 mm was adopted as a proxy for HDR, with sensitivity evaluated at alternative thresholds. The results showed that HDR is strongly clustered along the Kashmir Valley and the Pir Panjal flank, as demonstrated by the mean annual count of threshold-exceeding pixels increasing from 12 yr⁻¹ (2000–2010) to 18 yr⁻¹ (2011–2020), with two pixel-scale hotspots recurring southwest of Srinagar and near Baramulla regions. The cumulative high-intensity areas covered 31,555.26 km², whereas 37,897.04 km² of adjacent terrain registered no HDR events. Within this hazard belt, the exposed built-up area increased from 45 km² in 2000 to 72 km² in 2020, totaling 828 km². The years with the most expansive rainfall footprints, 344 km² (2010), 520 km² (2012), and 650 km² (2014), coincided with heavy Western Disturbances (WDs) and locally vigorous convection, producing the largest exposure increments. We also performed a forecast using a univariate long short-term memory (LSTM), outperforming Autoregressive Integrated Moving Average (ARIMA) and linear baselines on a 2017–2020 holdout (Root Mean Square Error, RMSE 0.82 km²; measure of errors, MAE 0.65 km²; R² 0.89), projecting the annual built-up area intersecting HDR to increase from ~320 km² (2021) to ~420 km² (2030); 95% prediction intervals widened from ±6 to ±11 km² and remained above the historical median (~70 km²). In the absence of a long-term increase in total annual precipitation, the projected rise most likely reflects continued urban encroachment into recurrent high-intensity zones. The resulting spatial masks and exposure trajectories provide operational evidence to guide zoning, drainage design, and early warning protocols in the region. Full article

Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, and Google Earth Engine (GEE) were used to assess flood-prone zones across North Macedonia’s watersheds. The presented GEE-based assessment was accomplished by a custom script that automates the FFPI calculation process by integrating key factors derived from publicly available sources. These factors, which define susceptibility to torrential floods, include slope (Copernicus GLO-30 DEM), land cover (Copernicus GLO-30 DEM), soil type (SoilGrids), vegetation (ESA World Cover), and erodibility (CHIRPS). The spatial distribution of average FFPI values across 1396 small catchments (10–100 km²) revealed that a total of 45.4% of the area exhibited high to very high susceptibility, with notable spatial variability. The CHIRPS rainfall data (2000–2024) that combines satellite imagery and in situ measurements was used to estimate peak 24 h runoff and discharge. To improve the accuracy of CHIRPS, the data were adjusted by 30–50% to align with meteorological station records, along with normalized FFPI values as runoff coefficients. Validation against 328 historical river flood and flash flood records confirmed that 73.2% of events aligned with moderate to very high flash flood susceptibility catchments, underscoring the model’s reliability. Thus, the presented cloud-based scenario highlights the potential of the GEE’s efficacy in scalability and robustness for flash flood modeling and regional risk management at national scale. Full article

Precipitable water vapor (PWV) is a critical component of the Earth’s atmosphere, playing a pivotal role in weather systems, climate dynamics, and hydrological cycles. Accurate estimation of PWV is essential for numerical weather prediction, climate modeling, and atmospheric correction in remote sensing. Ground-based observation stations can only provide PWV measurements at discrete points, whereas spaceborne infrared remote sensing enables spatially continuous coverage, but its retrieval algorithm is restricted to clear-sky conditions. This study proposes an innovative approach that uses ensemble learning models to integrate infrared and microwave satellite data and other geographic features to achieve all-weather PWV retrieval. The proposed product shows strong consistency with IGRA radiosonde data, with correlation coefficients (R) of 0.96 for the ascending orbit and 0.95 for the descending orbit, and corresponding RMSE values of 5.65 and 5.68, respectively. Spatiotemporal analysis revealed that the retrieved PWV product exhibits a clear latitudinal gradient and seasonal variability, consistent with physical expectations. Unlike MODIS PWV products, which suffer from cloud-induced data gaps, the proposed method provides seamless spatial coverage, particularly in regions with frequent cloud cover, such as southern China. Temporal consistency was further validated across four east Asian climate zones, with correlation coefficients exceeding 0.88 and low error metrics. This algorithm establishes a novel all-weather approach for atmospheric water vapor retrieval that does not rely on ground-based PWV measurements for model training, thereby offering a new solution for estimating water vapor in regions lacking ground observation stations. Full article

This study aims to investigate the differences in the effects of spraying and immersing methods on edible coatings for halved and pitted plums. Earlier studies have shown that these biodegradable packaging materials can preserve the quality and safety of fruits for an extended shelf life. Halved and pitted plums (variety Stanley) were treated with chitosan and rosehip oil edible coating emulsions by spraying and immersing methods. The treated series were analyzed by physical, physicochemical, microbiological, and sensorial methods during refrigerated storage for nine days, until the onset of microbiological spoilage. At the beginning of the storage, there was a visible difference between the differently treated samples. The untreated series showed the fastest browning. The emulsion-sprayed samples presented the least changes in color, shape, and volume. A weaker effect of the immersion technique can be explained by a deep standing of the fruits in a treating solution or emulsion. Some of the immersed samples have an aqueous texture and received a smaller sensory rating. The advantages and disadvantages of the methods need further investigation, but on a production scale, spraying can guarantee uniform batches. In laboratory circumstances, immersion is an easier method that does not need expensive and difficult-to-use equipment and gives good results. Full article

Electrostatic precipitators (ESPs) are widely applied to reduce particle concentrations. However, the performance of ESPs is impaired in the nanosized diameter range due to the difficulty in electrically charging these particles. The present work evaluated the inclusion of a wire screen, perpendicular to the airflow, as an additional collecting electrode of a single-stage wire-plate ESP containing two collecting plates and a single discharge wire. ESP performance was evaluated in terms of voltage, air velocity and electrode positioning in relation to the beginning of the collecting plate (inlet spacings of 1.5, 10 and 23 cm). When compared to theoretical prediction, the penetration results presented a decay for larger particles not predicted by the diffusion battery model. It was observed that the inclusion of the wire screen increased the removal of ultrafine particles and that the overall collection efficiencies increased up to 70% in the operating conditions evaluated. Moreover, the central positioning of the electrodes (inlet spacing of 10 cm) achieved the highest collection efficiencies at high voltages, but the final positioning (inlet spacing of 23 cm) presented a better performance at higher air velocities. Therefore, the wire screen can be an alternative to enhance nanoparticle collection. Full article

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

2,5-bis(hydroxymethy)lfuran (BHMF), a renewable compound with extensive industrial applications, can be obtained by selective hydrogenation of the C=O group of 5-hydroxymethylfurfural (HMF), a platform molecule derived from lignocellulosic biomass. In this work, we perform kinetic modeling of the selective liquid-phase hydrogenation of HMF to BHMF over a Cu/SiO₂ catalyst prepared by precipitation–deposition (PD) at a constant pH. Physicochemical characterization, using different techniques, confirms that the Cu/SiO₂–PD catalyst is formed by copper metallic nanoparticles of 3–5 nm in size highly dispersed on the SiO₂ surface. Before the kinetic study, the Cu/SiO₂-PD catalyst was evaluated in three solvents: tetrahydrofuran (THF), 2-propanol (2-POH), and water. The pattern of catalytic activity and BHMF yield for the different solvents was THF > 2-POH > H₂O. In addition, selectivity to BHF was the highest in THF. Thus, THF was chosen for further kinetic study. Several experiments were carried out by varying the initial HMF concentration (C⁰_HMF) between 0.02 and 0.26 M and the hydrogen pressure (P_H2) between 200 and 1500 kPa. In all experiments, BHMF selectivity was 97–99%. By pseudo-homogeneous modeling, an apparent reaction order with respect to HFM close to 1 was estimated for a C⁰_HMF between 0.02 M and 0.065 M, while when higher than 0.065 M, the apparent reaction order changed to 0. The apparent reaction order with respect to H₂ was nearly 0 when C⁰_HMF = 0.13 M, while for C⁰_HMF = 0.04 M, it was close to 1. The reaction orders estimated suggest that HMF is strongly absorbed on the catalyst surface, and thus total active site coverage is reached when the C⁰_HMF is higher than 0.065 M. Several Langmuir–Hinshelwood–Hougen–Watson (LHHW) kinetic models were proposed, tested against experimental data, and statistically compared. The best fitting of the experimental data was obtained with an LHHW model that considered non-competitive H₂ and HMF chemisorption and strong chemisorption of reactant and product molecules on copper metallic active sites. This model predicts both the catalytic performance of Cu/SiO₂-PD and its deactivation during liquid-phase HMF hydrogenation. Full article