Search Results (1,425)

Pharmaceuticals are increasingly being detected in coastal ecosystems globally, but contamination and bioaccumulation levels are understudied in temporarily closed estuaries. In these systems, limited freshwater inputs and periodic closure may predispose them to pharmaceutical accumulation. We quantified in situ water column pharmaceutical levels at five sites in a temporarily closed model urban estuary (Zandvlei Estuary) in Cape Town, South Africa, that has been heavily anthropogenically modified. The results indicate an almost 100-fold greater concentration of pharmaceuticals in the estuary relative to False Bay, into which the estuary discharges, with acetaminophen (max: 2.531 µg/L) and sulfamethoxazole (max: 0.138 µg/L) being the primary pollutants. Acetaminophen was potentially bioaccumulative, while nevirapine, carbamazepine and sulfamethoxazole were bioaccumulated (BAF > 5000 L/kg) by sandprawns (Kraussillichirus kraussi), which are key coastal endobenthic ecosystem engineers in southern Africa. The assimilative capacity of temporarily closed estuarine environments may be adversely impacted by wastewater discharges that contain diverse pharmaceuticals, based upon the high bioaccumulation detected in key benthic engineers. Full article

Massachusetts Bay in the northeastern United States is highly vulnerable to ocean acidification (OA) due to reduced buffering capacity from significant freshwater inputs. We hypothesize that acidification varies across temporal and spatial scales, with short-term variability driven by seasonal biological respiration, precipitation–evaporation balance, and river discharge, and long-term changes linked to global warming and river flux shifts. These patterns arise from complex nonlinear interactions between physical and biogeochemical processes. To investigate OA variability, we applied the Northeast Biogeochemistry and Ecosystem Model (NeBEM), a fully coupled three-dimensional physical–biogeochemical system, to Massachusetts Bay and Boston Harbor. Numerical simulation was performed for 2016. Assimilating satellite-derived sea surface temperature and sea surface height improved NeBEM’s ability to reproduce observed seasonal and spatial variability in stratification, mixing, and circulation. The model accurately simulated seasonal changes in nutrients, chlorophyll-a, dissolved oxygen, and pH. The model results suggest that nearshore areas were consistently more susceptible to OA, especially during winter and spring. Mechanistic analysis revealed contrasting processes between shallow inner and deeper outer bay waters. In the inner bay, partial pressure of pCO₂ (pCO₂) and aragonite saturation (Ω_a) were influenced by sea temperature, dissolved inorganic carbon (DIC), and total alkalinity (TA). TA variability was driven by nitrification and denitrification, while DIC was shaped by advection and net community production (NCP). In the outer bay, pCO₂ was controlled by temperature and DIC, and Ω_a was primarily determined by DIC variability. TA changes were linked to NCP and nitrification–denitrification, with DIC also influenced by air–sea gas exchange. Full article

The high spatial resolution of radar data enables the detailed resolution of typhoon vortices and their embedded structures; the assimilation of radar data in the initialization of numerical weather prediction exerts an important influence on the forecasting of typhoon track, intensity, and structures up to at least 12 h. For the case of typhoon Morakot (2009), Taiwan radar data was assimilated to adjust the dynamic and thermodynamic structures of the vortex in the model initialization by the three-dimensional variation data assimilation system in the Advanced Region Prediction System (ARPS). The radial wind was directly assimilated to tune the original unbalanced velocity fields through a 3-dimensional variation method, and complex cloud analysis was conducted by using the reflectivity data. The influence of radar data assimilation on typhoon prediction was examined at the stages of Morakot landing on Taiwan Island and subsequently going inland. The results showed that the assimilation made some improvement in the prediction of vortex intensity, track, and structures in the initialization and subsequent forecast. For example, besides deepening the central sea level pressure and enhancing the maximum surface wind speed, the radar data assimilation corrected the typhoon center movement to the best track and adjusted the size and inner-core structure of the vortex to be close to the observations. It was also shown that the specific humidity adjustment in the cloud analysis procedure during the assimilation time window played an important role, producing more hydrometeors and tuning the unbalanced moisture and temperature fields. The neighborhood-based ETS revealed that the assimilation with the specific humidity adjustment was propitious in improving forecast skill, specifically for smaller-scale reflectivity at the stage of Morakot landing, and for larger-scale reflectivity at the stage of Morakot going inland. The calculation of the intensity-scale skill score of the hourly precipitation forecast showed the assimilation with the specific humidity adjustment performed skillful forecasting for the spatial forecast-error scales of 30–160 km. Full article

Accurate short-term rainfall forecasting, an essential component of the broader framework of nowcasting, is crucial for managing extreme weather events. Traditional forecasting approaches, whether radar-based or satellite-based, often struggle with limited spatial coverage or temporal accuracy, reducing their effectiveness. This study tackles these challenges by implementing the Local Analysis and Prediction System (LAPS) enhanced with a forward advection nowcasting module, integrating multiple remote sensing rainfall datasets. Specifically, we combine weather radar data with three different satellite-derived rainfall products (H-SAF, GPM, and TRMM) to assess their impact on nowcasting performance for a rainfall event in Attica, Greece (29–30 September 2018). The results demonstrate that combined high-resolution radar data with the broader coverage and high temporal frequency of satellite retrievals, particularly H-SAF, leads to more accurate predictions with lower uncertainty. The assimilation of H-SAF with radar rainfall retrievals (HX experiment) substantially improved forecast skill, reducing the unbiased Root Mean Square Error by almost 60% compared to the control experiment for the 60 min rainfall nowcast and 55% for the 90 min rainfall nowcast. This work validates the effectiveness of the specific LAPS/advection configuration and underscores the importance of multi-source data assimilation for weather prediction. Full article

Groundwater is a critical yet understudied resource in Peru, where surface water has traditionally dominated national assessments. This study provides the first country-scale analysis of groundwater storage (GWS) variability in Peru from 2003 to 2023 using satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We used the GRACE Data Assimilation-Data Mass Modeling (GRACE-DA-DM GLV3.0) dataset at 0.25° resolution to estimate annual GWS trends and evaluated the influence of El Niño–Southern Oscillation (ENSO) events and anthropogenic extraction, supported by in situ well data from six major aquifers. Results show a sustained GWS decline of 30–40% in coastal and Andean regions, especially in Lima, Ica, Arequipa, and Tacna, while the Amazon basin remained stable. Strong correlation (r = 0.95) between GRACE data and well records validate the findings. Annual precipitation analysis from 2003 to 2023, disaggregated by climatic zone, revealed nearly stable trends. Coastal El Niño events (2017 and 2023) triggered episodic recharge in the northern and central coastal regions, yet these were insufficient to reverse the sustained groundwater depletion. This research provides significant contributions to understanding the spatiotemporal dynamics of groundwater in Peru through the use of satellite gravimetry data with unprecedented spatial resolution. The findings reveal a sustained decline in GWS across key regions and underscore the urgent need to implement integrated water management strategies—such as artificial recharge, optimized irrigation, and satellite-based early warning systems—aimed at preserving the sustainability of the country’s groundwater resources. Full article

Various data such as power grid sensors and manual observed icing, CMA (China Meteorological Administration) Land Surface Data Assimilation System (CLDAS) products, and the Fifth Generation Atmospheric Reanalysis of the Global Climate from Europe Center of Middle Range Weather Forecast (ERA5) are adopted to diagnose an icing process under a cold surge during 16–23 December 2023 in northeastern Yunnan Province. The results show that: (1) in the early stage of the process, mainly the freezing types, such as GG (temperature > 0 °C, relative humidity ≥ 75%) and DG (temperature < 0 °C, relative humidity ≥ 75%), occur. At the end of the process, an increase in icing type as GD (temperature > 0 °C, relative humidity < 75%) appears. (2) Significant differences exist in the elements during different stages of icing, and the atmospheric thermal, dynamic, and water vapor conditions are conducive to the occurrence of freezing rain during ice accretion. The main impact weather systems of this process include a strong high ridge in the mid to high latitudes of East Asia, transverse troughs in front of the high ridge south to Lake Baikal, low altitude troughs, and ground fronts. The transverse trough in front of the high ridge can cause cold air to accumulate and then move eastward and southward. The southerly flows, surface fronts, and other low-pressure systems can provide powerful thermodynamic and moisture conditions for ice accumulation. Full article

High-resolution numerical weather prediction requires accurate cloud microphysical initial conditions to enhance forecasting capabilities for high-impact severe weather events such as convective storms. This study integrated Fengyun-2 (FY-2) geostationary satellite data (equivalent blackbody temperature and total cloud cover) and next-generation 3D weather radar reflectivity from the China Meteorological Administration (CMA) to construct cloud microphysical initial fields and evaluate their impact on the CMA-MESO 3 km regional model. An analysis of the catastrophic rainfall event in Henan on 20 July 2021, and a 92-day continuous experiment (May–July 2024) revealed that assimilating cloud microphysical variables significantly improved precipitation forecasting: the equitable threat scores (ETSs) for 1 h forecasts of light, moderate, and heavy rain increased from 0.083, 0.043, and 0.007 to 0.41, 0.36, and 0.217, respectively, with average hourly ETS improvements of 21–71% for 2–6 h forecasts and increases in ETSs for light, moderate, and heavy rain of 7.5%, 9.8%, and 24.9% at 7–12 h, with limited improvement beyond 12 h. Furthermore, the root mean square error (RMSE) of the 2 m temperature forecasts decreased across all 1–72 h lead times, with a 4.2% reduction during the 1–9 h period, while the geopotential height RMSE reductions reached 5.8%, 3.3%, and 2.0% at 24, 48, and 72 h, respectively. Additionally, synchronized enhancements were observed in 10 m wind prediction accuracy. These findings underscore the critical role of cloud microphysical initialization in advancing mesoscale numerical weather prediction systems. Full article

Numerous scientific studies have confirmed the effectiveness of seed bioactivation using electromagnetic fields (EMFs) in agriculture. This article presents the results of the remote application of an EMF TOR device in the cultivation of barley Hordeum vulgare L. Laboratory studies and field tests were conducted, showing a positive effect on the growth and development of plants both when treating dry seeds before sowing and when treating sown seeds in the field. The optimal time period for EMF treatment was determined: treating air-dried seeds with EMFs before sowing for 10–15 min increased germination by 5–18% and the growth rate of seedlings by 2–3 times. The maximum observed effect occurred during the treatment period from 7:00 to 11:00. As a result of changing the balance of phytohormones, the further stimulation of the root system and the assimilation surface of plants was noted due to a 1.5-fold increase in the content of auxins. The density of productive stems, ear length, seed set, and 1000 seed weight increased, which ultimately led to an increase in yield by more than 10% and, in some varieties, to a decrease in the protein content in grains compared to the control variant (by 3–22%), bringing them closer to brewing conditions. Full article

Traditional 4-dimensional variational data assimilation methods have limitations due to the Gaussian distribution assumption of observation errors, and the gradient of the objective functional is vulnerable to observation noise and outliers. To address these issues, this paper proposes a non-Gaussian nonlinear data assimilation method called α-4DVar, based on Rényi entropy and the α-generalized Gaussian distribution. By incorporating the heavy-tailed property of Rényi entropy, the objective function and its gradient suitable for non-Gaussian errors are derived, and numerical experiments are conducted using the Lorenz-63 model. Experiments are conducted with Gaussian and non-Gaussian errors as well as different initial guesses to compare the assimilation effects of traditional 4DVar and α-4DVar. The results show that α-4DVar performs as well as traditional method without observational errors. Its analysis field is closer to the truth, with RMSE rapidly dropping to a low level and remaining stable, particularly under non-Gaussian errors. Under different initial guesses, the RMSE of both the background and analysis fields decreases quickly and stabilizes. In conclusion, the α-4DVar method demonstrates significant advantages in handling non-Gaussian observational errors, robustness against noise, and adaptability to various observational conditions, thus offering a more reliable and effective solution for data assimilation. Full article

Groundwater at petroleum-contaminated sites typically exhibits elevated dissolved inorganic carbon (DIC) levels due to hydrocarbon biodegradation; however, our prior field investigations revealed an enigmatic DIC depletion anomaly that starkly contradicts this global pattern and points to an unrecognized carbon sink. In a breakthrough demonstration, this study provides the first experimental confirmation that sulfur-oxidizing bacteria (SOB) drive substantial carbon sequestration via a coupled sulfur oxidation autotrophic assimilation process. Through integrated hydrochemical monitoring and 16S rRNA sequencing in an enrichment culture system, we captured the complete DIC transformation trajectory: heterotrophic acetate degradation initially increased DIC to 370 mg/L, but subsequent autotrophic assimilation by SOB dramatically reduced DIC to 270 mg/L, yielding a net consumption of 85 mg/L. The distinctive pH dynamics (initial alkalization followed by acidification) further corroborated microbial regulation of carbon cycling. Critically, Pseudomonas stutzeri and P. alcaliphila were identified as the dominant carbon-fixing agents. These findings definitively establish that chemolithoautotrophic SOB convert DIC into organic carbon through a “sulfur oxidation-carbon fixation” coupling mechanism, overturning the conventional paradigm of petroleum-contaminated sites as perpetual carbon sources. The study fundamentally redefines natural attenuation frameworks by introducing microbial carbon sink potential as an essential assessment metric for environmental sustainability. Full article

Accurately monitoring terrestrial water storage (TWS) variations is essential due to global climate change and growing water demands. This study investigates TWS changes in Oregon, USA, using Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory, Gravity Recovery and Climate Experiment (GRACE) level-3 mascon data from the Jet Propulsion Laboratory (JPL), and Noah model data from the Global Land Data Assimilation System (GLDAS) data. The results show that the GNSS inversion offers superior spatial resolution, clearly capturing a water storage gradient from 300 mm in the Cascades to 20 mm in the basin and accurately distinguishing between mountainous and basin areas. However, the GRACE data exhibit blurred spatial variability, with the equivalent water height amplitude ranging from approximately 100 mm to 145 mm across the study area, making it difficult to resolve terrestrial water storage gradients. Moreover, GLDAS exhibits limitations in mountainous regions. The GNSS can provide continuous dynamic monitoring, with results aligning well with seasonal trends seen in GRACE and GLDAS data, although with a 1–2 months phase lag compared to the precipitation data, reflecting hydrological complexity. Future work may incorporate geological constraints, region-specific elastic models, and regularization strategies to improve monitoring accuracy. This study demonstrates the strong potential of GNSS technology for monitoring TWS dynamics and supporting environmental assessment, disaster warning, and water resource management. Full article

A reliable precipitation dataset with high spatial resolution is essential for climate research in the Tarim Basin. This study evaluated the performances of four models, namely a random forest (RF), a long short-term memory network (LSTM), a support vector machine (SVM), and a feedforward neural network (FNN). FNN, which was found to be superior to the other models, was used to integrate eight precipitation datasets spanning from 1990 to 2022 across the Tarim Basin, resulting in a new monthly high-resolution (0.1°) precipitation dataset named MoHiPr-TB. This dataset was subsequently bias-corrected by the China Land Data Assimilation System version 2.0 (CLDAS2.0). Validation results indicate that the corrected MoHiPr-TB not only accurately reflects the spatial distribution of precipitation but also effectively simulates its intensity and interannual and seasonal variations. Moreover, MoHiPr-TB is capable of detecting the precipitation–elevation relationship in the Pamir Plateau, where precipitation initially increases and then decreases with elevation, as well as the synchronous variation of precipitation and elevation in the Tianshan region. Collectively, this study delivers a high-accuracy precipitation dataset for the Tarim Basin, which is anticipated to have extensive applications in meteorological, hydrological, and ecological research. Full article

This study examined the effects of both nitrogen (N) rate and form on the growth, nutrient uptake, and quality parameters of hydroponically grown purslane (Portulaca oleracea L.) during a spring cultivation cycle. Purslane was cultivated in a floating hydroponic system under either adequate or limiting N conditions. More specifically, under adequate N conditions, plants were supplied with NS where ammonium nitrogen (NH₄-N) accounted for either 7% (Nr7) or 14% (Nr14) of the total-N. The limiting N conditions were achieved through the application of either an NS where 30% of N inputs were compensated with Cl (N30), or an NS where 50% of N inputs were balanced by elevating Cl and S by 30% and 20%, respectively (N50). The results demonstrated that mild N stress enhanced the quality characteristics of purslane without significant yield losses. However, further and more severe N restrictions in the NS resulted in significant yield losses without improving product quality. The highest yield reduction (20%) occurred under high NH₄-N supply (Nr14), compared to Nr7-treated plants, which was strongly associated with impaired N assimilation and reduced biomass production. Both N-limiting treatments (N30 and N50) effectively reduced nitrate accumulation in edible tissues by 10% compared to plants grown under adequate N supply (Nr7 and Nr14); however, nitrate levels remained relatively high across all treatments, even though the environmental conditions of the experiment favored nitrate reduction. All applied N regimes and compensation strategies improved the antioxidant and flavonoid content, with the highest antioxidant activity observed in plants grown under high NH₄-N application, indirectly revealing the susceptibility of purslane to NH₄-N-rich conditions. Overall, the form and rate of N supply significantly influenced both plant performance and biochemical quality. Partial replacement of N with Cl (N30) emerged as the most promising strategy, benefiting quality traits and effectively reducing nitrate content without significantly compromising yield. Full article

Nitrogen (N) critically regulates wheat growth and grain quality, yet the molecular mechanisms underlying foliar nitrogen application remain unclear. This study evaluated the effects of foliar nitrogen application (12.25 kg ha⁻¹) on the growth, grain yield, and quality of spring wheat, as well as its molecular mechanisms. The results indicated that N was absorbed within 3 h post-application, with leaf nitrogen concentration peaking at 12 h. The N treatment increased whole-plant dry matter accumulation and grain protein content by 11.34% and 6.8%, respectively. Amino acid content peaked 24 h post-application, increasing by 25.3% compared to the control. RNA-sequencing analysis identified 4559 and 3455 differentially expressed genes at 3 h and 24 h after urea treatment, respectively, these DEGs being primarily involved in nitrogen metabolism, photosynthetic carbon fixation, amino acid biosynthesis, antioxidant systems, and nucleotide biosynthesis. Notably, the plastidic glutamine synthetase gene (GS2) is crucial in the initial phase of urea application (3 h post-treatment). The pronounced downregulation of GS2 initiates a reconfiguration of nitrogen assimilation pathways. This downregulation impedes glutamine synthesis, resulting in a transient accumulation of free ammonia. In response to ammonia toxicity, the leaves promptly activate the GDH (glutamate dehydrogenase) pathway to facilitate the temporary translocation of ammonium. This compensatory mechanism suggests that GS2 downregulation may be a key switch that redirects nitrogen metabolism from the GS/GOGAT cycle to the GDH bypass. Additionally, the upregulation of the purine and pyrimidine metabolic routes channels nitrogen resources towards nucleic acid synthesis, and thereby supporting growth. Amino acids are then transported to the seeds, culminating in enhanced seed protein content. This research elucidates the molecular mechanisms underlying the foliar response to urea application, offering significant insights for further investigation. Full article

As a major agricultural center in China, Henan Province is highly dependent on groundwater resources for its socioeconomic development. However, under the triple pressure of intensive agricultural irrigation, surging industrial water demand, and accelerating urbanization, the sustainable use of groundwater resources has become a key issue for regional development. This paper utilizes GRACE satellite data and the Global Land Data Assimilation System (GLDAS) assimilation model from 2003 to 2023 to invert alterations in terrestrial water storage (TWS) and groundwater storage (GWS) in Henan Province. We examine the factors influencing these changes and compare the spherical harmonic coefficient (SH) data with Mascon data, integrating precipitation and soil moisture data. Using the GRACE Mascon data as a reference, GWS in Henan Province exhibited a stable trend from January 2003 to October 2010, with a rate of −0.060 cm/month. From October 2010 to June 2020, GWS demonstrated a declining trend, with a rate of −0.121 cm/month. Conversely, from June 2020 to December 2023, GWS revealed a significant upward trend, with a rate of 0.255 cm/month. The TWS and GWS of the inverse performances of the Centre for Space Research (CSR) SH data and the CRS Mascon data exhibited a similar trend, albeit with differing values. Additionally, the precipitation data, soil moisture, and GLDAS data demonstrated significant seasonal variations, with a lag of approximately two months between changes in precipitation and GWS. Declining GWS could be related to climatic and anthropogenic factors. The changes in groundwater in Henan Province studied in this paper can provide a reference for the sustainable utilization of groundwater resources in the region. Full article