Pharmaceutical analysis is vital for assessing drug quality and identifying impurities. The recent emergence of carcinogenic nitrosamine contaminants has escalated scrutiny, resulting in the withdrawal of multiple medications. This study focuses on developing robust analytical techniques to detect specific nitrosamine impurities in anticoagulant drugs (Apixaban, Rivaroxaban) and antidepressant drugs (Duloxetine HCl) while enhancing the eco-friendliness of the method. Nitrosamines were separated on a microbore liquid chromatographic column, and their concentrations were determined using a liquid chromatography system coupled to a triple quadrupole tandem mass spectrometer in positive/negative mode with atmospheric pressure chemical ionisation. The results showed good separation of analytes with sensitivities reaching the required standards. The method was validated as per ICH Q2(R2) guidelines. The linearity of the method was performed from 0.1 ng/g to 5 μg/g quantity of the nitrosamines. The obtained calibration curves showed excellent linearity with the square of regression coefficient ranging from 0.994 to 0.998. The determination accuracy ranged from 85.53% to 119.55%, with a relative standard deviation of 2.3% to 8.1%. The interday and intraday precisions were less than 10%. The findings illuminate intricate relative uncertainties ranging from 18.2% to 29.5% across three drug products. Regarding sustainability, the method scored 69 on the GAPI assessment and 0.67 on the AGREE assessment, indicating moderately green. This validated method provides sensitivity and precision in detecting nitrosamine impurities in the selected pharmaceutical products in the limits specified by various pharmacopeias and compliant with ICH Q2 (R2) standards. The solvent consumption is relatively very low compared with that of the reported standard methods; hence, the method becomes environmentally friendly and economical.
The atmospheric oxidation of biogenic volatile organic compounds is a key driver of secondary organic aerosol formation. In this study, a quantum chemical and molecular dynamics investigation of 1,3-dipolar cycloadditions between linalool-derived Criegee intermediates and dimethylketone, both co-products of ozonolysis, is presented. Density functional theory, conceptual DFT descriptors, and transition state theory show that O1-oriented anti-CI pathways proceed with submerged barriers and competitive rate constants up to 10-10 cm3 molecule-1 s-1, while O2 channels are kinetically inaccessible. Classical dynamics reveal rapid nucleation and stable clustering, with water molecules enhancing cohesion through cooperative hydrogen bonding. These results identify cycloadditions with carbonyls as competitive tropospheric sinks for Criegee intermediates and emphasize how emissions from Southern Hemisphere forests may contribute to secondary organic aerosol growth and cloud condensation nuclei formation, with implications for regional climate models.
Although desert dust aerosols affect more than half of the world's countries, the mechanisms of their oxidative toxicity have long been underrecognized. To break through this limitation, we conducted a comprehensive investigation of the oxidative potential (OP) and generation mechanisms of dust aerosols through multievent sampling across desert source regions (Taklamakan and Tengger deserts) and downwind areas, combined with independent laboratory simulations of surface sand emissions from these source regions. We reveal that desert dust exhibits OP comparable to that of urban aerosols, challenging the notion of low toxicity of desert dust. Typical OP drivers (organic components and metal ions) are insufficient to explain this elevated OP. We propose that mechanical processes such as saltation and sandblasting, which occur during dust entrainment, induce the formation of mineral free radicals on the PM surface─serving as an important source of reactive species that enhance OP. Furthermore, chemical processes such as photoaging contribute to enhanced OP in dust aerosols, explaining the contradiction that the dust aerosols observed in urban areas are essentially higher than those observed in desert areas and urban aerosols. This study fundamentally revises our understanding of desert dust toxicity, establishing its significant health risk as a major natural aerosol source.
More than a quarter of anthropogenic global warming has been attributed to methane growth in the atmosphere. Landfills account for 17% of estimated methane emissions in the United States of America (USA), according to the Environmental Protection Agency (EPA), but studies show that many landfills emit more than reported. We developed a novel method to calculate monthly methane emissions from an active landfill using atmospheric methane mixing ratios observed from a single tower in New Jersey, USA. The tower method provides two and a half years of semicontinuous measurements and therefore observes more of the variability of methane emissions and lacks the sampling bias present in other methods. Time-specific comparison of tower-based methane emissions against those observed from summertime aircraft sampling and year-round mobile ground-based platforms showed good agreement. Estimated methane emissions for 2023 were five times greater than those reported to the EPA. We observed a strong seasonality in methane emissions, with a peak in the winter and a minimum in the summer. This seasonal cycle was driven by a strong negative dependence on air temperature and the change in atmospheric pressure. Our results highlight the importance of observations in nonideal weather conditions (such as declining pressure and near-freezing temperatures) when methane emissions are largest. We suggest that this methodology could be applied to other suitable landfills to improve estimates of methane emissions.
Radioactive cesium-rich microparticles (CsMPs) released from the Fukushima Daiichi Nuclear Power Plant (FDNPP) in 2011 pose a persistent environmental concern, yet their initial atmospheric dispersion has remained poorly constrained. Here we quantify CsMP abundance and radioactive fraction (RF) in 100 surface soil samples collected across Fukushima Prefecture in July 2011 and integrate the results with WSPEEDI atmospheric simulations. CsMP abundance ranged from 0 to 52.3 particles g⁻¹ (dry weight), with RF values of 0-61.85%. The combined analysis identifies a major CsMP formation and release event at ∼03:00 JST on 15th March 2011, producing a plume strongly enriched in CsMPs. Plumes released after 00:00 JST on 16th March contained no detectable CsMPs, indicating that particle formation had ceased by that time. The widespread distribution of CsMPs across Fukushima is therefore attributed primarily to this single plume. Directional variations in CsMP abundance reflect temporal changes in plume composition, with peak concentrations of ∼2070 particles m⁻³ toward the southwest and ∼4700 particles m⁻³ toward the northwest. These findings constrain CsMP formation mechanisms and improve reconstruction of radiological dispersion relevant to the long-term environmental risk assessment of nuclear power plants.
Tree recruitment is one of the most critical processes in forest dynamics. However, prediction of forest dynamics is largely limited by a lack of understanding on how climate variability drives tree recruitment. Modes of large-scale atmospheric variability, such as the Atlantic Multi-decadal Oscillation (AMO), exert a strong influence on climate and forest ecosystems worldwide. Yet, the linkages between forest dynamics and AMO at large spatial scales, particularly in climatically marginal tree populations such as treelines, remain unknown. Using field survey data from 68,011 trees at 120 treeline sites across the Northern Hemisphere, we investigated tree recruitment dynamics and their relationships with climate and the AMO during 1951-2010. We identified increasing tree recruitment on the Tibetan Plateau and Central China at mid-latitudes, whereas a decreasing trend was observed in Scandinavia-Kola and Ural-Siberia at high latitudes. An inverse recruitment pattern was documented between mid-latitude Western North America and high-latitude Alaska-Northern Canada. Regional warming and changes in precipitation were linked to spring and summer AMO variability. In general, tree recruitment increased with warming and suitable moisture conditions and snow cover. Conversely, low precipitation in the non-growing season and warming-induced drought stress reduced recruitment. We provide evidence on how large-scale atmospheric circulation patterns influence treeline dynamics by modulating regional climatic limitations on tree recruitment at hemispheric scales. Our results have notable implications to forecast future forest shifts in climatically harsh environments.
This study investigates the sources of heavy metal contamination in surface and core sediments from the semi-enclosed Pohang Old Port (POP), South Korea, using an integrated approach combining positive matrix factorization (PMF) and Zn-Cu-Pb stable isotope analyses. Geochemical profiling showed that although heavy metals were primarily derived from anthropogenic sources, sediment grain size controlled the spatial variability of their concentrations through hydrodynamic sorting. PMF resolved four major factors: (1) urban and seafood market discharges enriched in Cd and Zn; (2) Hg-dominated inputs likely associated with riverine transport of landfill-derived sediments; (3) As, Ni, and Pb linked to atmospheric deposition and industrial runoff; and (4) Cu and Zn contamination related to antifouling paint (AFP) use in shipyards. Isotopic analysis of δ66Zn, δ65Cu, and 207Pb/206Pb-208Pb/206Pb provided complementary source constraints. Zn isotopic compositions exhibited limited variability among sediments and potential sources, restricting their discriminatory power. In contrast, Cu isotopes effectively distinguished AFP-related shipyard inputs from urban-industrial contributions, while Pb isotopic ratios indicated mixing between marine background sediments and atmospheric fallout from road dust and cement-related emissions. Isotope-based mixing models were consistent with PMF results and refined the distinction between diffuse and point sources. These findings demonstrate the value of integrating receptor modeling with isotopic fingerprinting to resolve complex multi-source contamination in estuarine sediments.
Deep-derived carbon dioxide (CO2) degassing is a globally important process linking crust-mantle fluid transport with atmospheric carbon budgets. Matched Field Processing-Bartlett Beamformer (MFP-BB) method offers a seismic approach for detecting tremor signals generated by these degassing centers (mofette). Its principle relies on comparing recorded wavefields with modeled replicas to identify the most likely source locations. This study applies the MFP-BB technique to dense-array seismic noise data from three key mofette areas in the Cheb Basin, western Eger Rift-Bublák, Hartoušov, and Soos. We combine field observations with numerical simulations to evaluate the method's performance. Synthetic tests with interfering noise-embedded sources (SNR = 5 dB) demonstrate that accurate localization is achievable with appropriate frequency selection, and that even 20% perturbations in the velocity model introduce only minor degradation. Field data were processed through segmentation, noise filtering, and spectral analysis to determine persistent frequency bands used in the algorithm. Across all sites, MFP-BB energy concentrates near the surface, coinciding with known mofette fields and CO2 discharge zones. These shallow anomalies reflect microtremors generated as ascending CO2 interacts with groundwater and unconsolidated sediments; additional, weaker anomalies at depths < 200 m may also represent active gas migration.
Nitrous oxide (N2O) is a strong greenhouse gas that contributes significantly to global warming and causes depletion of ozone in the stratosphere. Recent observational records show an unprecedented acceleration in atmospheric N₂O growth, reaching 1.15 ppb yr- 1 in 2019-2023, a significant increase compared to 0.68 ppb yr- 1 in 2001-2005. This surge in growth rate is particularly pronounced over tropical regions, and has been measured most prominently at the southern-most island of Japan (Hateruma). In this study, we use N2O observations from globally distributed multi-institutional networks and the MIROC4-ACTM inversion framework to quantify N2O emissions and identify key regions that are driving the recent acceleration. Our results suggest that the major Asian countries, Brazil, Central and Northern Africa, and the Contiguous United States have increased emission sources in the recent 2.5 decades (1998-2023). Further, there has been an increase in land N2O emissions, at a rate of 106 GgN yr- 1 per year during 1998-2002 to 2019-2023 (1Gg = 109g). The inversion inferred trends are consistent with increased fertiliser use and manure production to support extensive agriculture, and terrestrial ecosystem model results. The emissions from oceanic regions did not show significant increases in N2O (rate: 7 ± 2 GgN yr- 1 per year) in our inverse model setup. Our results underscore the importance for improved climate mitigation strategies and emissions reduction policies by increasing nitrogen-fertiliser use efficiency in agricultural land. The online version contains supplementary material available at 10.1186/s40562-026-00476-z.
This study examines the long-term variations in the water-level time series of Lake Uluabat, located in western Türkiye, over the past six decades. Despite the decline in lake water level in recent years, the scarcity of reliable information remains a major problem in understanding this phenomenon. To overcome this limitation, monthly water-level observations spanning from October 1960 to September 2019 (708 months) were analyzed to explore temporal dynamics in trend, homogeneity, stationarity, frequency, persistence, entropy, and the reconstructed phase-space geometry. The analyses were conducted for the entire period (1960-2019) and six decadal intervals (i.e., 1960-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2009, and 2010-2019) to identify regime shifts and decade-scale variability. The so-called autocorrelation function, mutual information, probability distributions, return period, and dimensional analysis were performed. Also, the teleconnections between lake-level fluctuations and 19 large-scale atmospheric-oceanic oscillation indices were investigated. Results indicated a persistent but gradually descending downward trend, accompanied by a rise in system entropy and short-term dependencies. This indicates increased complexity and dependence on external factors. So in a nutshell, the recent lake water-level properties indicate reduced degree of functionality and self-dependency of the hydrological regime. Yet, the temporal teleconnection between lake water level and the climatic oscillations showed stability. This indicates that the climate and the anthropogenic factors have a direct effect on the lake water level states, although in this case, the latter seems to have the upper hand.
The thermal decomposition of nickel hydroxide (Ni(OH)2) was investigated using thermoanalytical techniques with a specific focus on the multistep kinetic behavior and the effect of the partial pressure of water vapor (p(H2O)). The thermal decomposition process was modeled as a four-step kinetic process, comprising the dehydration of absorbed or included water, a two-step primary reaction process yielding nickel oxide (NiO), and the evolution of the trapped water molecules as the crystal growth of NiO progressed. The kinetic characteristics of the individual reaction steps in the primary reaction process were revealed using advanced kinetic analysis methodologies for multistep reactions. A distinctive retardation effect of atmospheric water vapor pressure (p(H2O)ATM) was evidenced by systematically tracing the reaction process at varying p(H2O)ATM values. Combining the kinetic analysis methodologies for multistep reactions and universal kinetic description across different p(H2O) values, the individual reaction steps in the primary reaction process were described as a function of temperature, degree of reaction, and p(H2O)ATM. This approach was further extended to incorporate the effect of the self-generated water vapor pressure, thereby enabling the universal kinetic description covering all kinetic data in a stream of dry and wet N2 gases. The kinetic results indicated the initial reaction step in the primary reaction process as being regulative of the primary reaction process in the context of the physico-geometrical kinetic behavior and the effect of p(H2O). The novel kinetic findings are expected to provide the necessary information to refine the thermal processing of Ni(OH)2, yielding NiO with the desired properties and morphologies.
Air pollution is currently one of the major environmental problems related to human health, affecting many diseases. In this regard, while studies have established an association between air quality and Type 2 Diabetes Mellitus (T2DM), there is still a need to refine exposure-response functions. Therefore, this study aims to establish the exposure-response function that relates the concentration of two air pollutants (NO2 and PM2.5) to the hazard ratio associated with acquiring T2DM, based on various cohort studies conducted worldwide. To achieve this, a methodology using nonlinear function adjustments will be employed. This function is then applied to determine the number of T2DM cases attributable to air pollution across Europe for different age groups, using atmospheric concentrations from 1991 to 2020. Results indicate a significant nonlinear relationship between pollutant exposure and T2DM cases, with higher risks observed in areas with elevated levels of NO2 and PM2.5 (specifically, in large European cities and in central Europe, mainly related to traffic and industrial activities). NO2 relates to 3754000 [3428000 - 3957000; 95% CI] annual T2DM cases, which represent 0.51% [0.46%-0.54%; 95% CI]; while PM2.5, annual cases increase to 5109000 [4036000 - 6581000; 95% CI], corresponding to a 0.69% [0.55%-0.89%; 95% CI] of cases of T2DM attributable to this pollutant. The analysis revealed that, despite lower concentrations, PM2.5 shows a higher impact on T2DM incidence compared to NO2, especially at lower exposure levels. Findings underscore the need for stringent air quality regulations, particularly in urban and industrial regions, to mitigate air pollution's health impacts.
Air pollution is a major environmental and public health challenge in Greater Cairo due to rapid urbanization, intense traffic activity, and recurrent regional dust intrusions. This study presents a data driven analytical framework for identifying and interpreting recurring air pollution regimes in the city. The framework combines unsupervised K-means clustering with supervised Decision Tree (DT) and Random Forest (RF) models using atmospheric reanalysis data derived from the Copernicus Atmosphere Monitoring Service (CAMS) for the period 2023-2024. The optimized K-means model identified four distinct pollution regimes. Low pollution conditions accounted for approximately 75.1% of the analyzed period, whereas higher pollution regimes were mainly associated with traffic related emissions and episodic dust events. To assess the separability of the identified regimes, DT and RF classifiers were trained to predict cluster membership. The optimized Decision Tree achieved an accuracy of 93.10%, while the Random Forest model showed better classification performance, reaching a maximum accuracy of 97.49%, with a practical optimum of 97.43% obtained using 300 trees. Feature importance analysis showed that NO₂ was the dominant variable for distinguishing traffic related pollution regimes, whereas PM₁₀ played a key role in identifying dust related events. Overall, the findings indicate that integrating clustering with tree based classification provides an interpretable and effective approach for characterizing urban air pollution patterns. The resulting framework may support regime based air quality interpretation and targeted management strategies in Greater Cairo.
The levels, profiles, sources, and health risks of polycyclic aromatic hydrocarbons (PAHs), nitrated PAHs (NPAHs), and oxygenated PAHs (OPAHs) were investigated in Pohang, a major iron and steel industrial city in South Korea. Passive air samplers (PASs) were deployed at 26 sites across port, industrial, and urban areas during winter for a 72-day sampling period. The mean concentrations of 21 PAHs, 17 NPAHs, and 9 OPAHs were 54.6 ng/m3, 530 pg/m3, and 4.8 ng/m3, respectively. The mean PAH concentration at the port area was 3.9 times higher than that in other areas, primarily due to emissions from steel production processes (e.g., sintering and blast furnaces) and ship and truck activities related to cargo handling. Among NPAHs, 1-nitropyrene, a marker of diesel exhaust, was predominant at the port sites, highlighting the contribution of traffic emissions. OPAHs showed a spatial distribution similar to that of PAHs, with 9-fluorenone being the most abundant compound. Correlation analysis, diagnostic ratios, and principal component analysis revealed the influence of primary emission sources, including iron and steel manufacturing, diesel exhaust, and coal combustion, as well as contributions from secondary formation. Cancer risk assessments indicated elevated health risks in the port area, with PAHs being the major contributors. Overall, PAH and N/OPAH levels were largely driven by primary emissions in the port area, while secondary formation played a more significant role in the urban areas. This study is the first in South Korea to report atmospheric levels of both NPAHs and OPAHs using PASs.
With the intensifying effects of global warming and the growing demand for cooling, passive daytime radiative cooling (PDRC) has emerged as a promising and sustainable solution, in which PDRC reflects solar radiation and dissipates heat through the 8-13 µm atmospheric window without energy consumption, offering a viable approach to reducing electricity usage for cooling. A key factor in enhancing PDRC performance is the use of bioinspired light-scattering structures, which effectively regulate solar reflection and long-wave infrared emission. This review systematically outlines the design principles and regulation strategies of scattering structures in radiative cooling materials, focusing on two primary systems: scattering particles and porous architecture. It examines their individual contributions and synergistic effects in improving both solar reflectivity and infrared emissivity. Special emphasis is placed on bioinspired structural designs, exploring how nature-inspired patterns can enhance spectral selectivity and scattering efficiency. The review also summarizes representative applications in building energy conservation, photovoltaic thermal management, wearable electronics, and agricultural environments regulation. Finally, it discusses current technical challenges and offers perspectives on future developments in structural design and scalable fabrication methods, aiming to provide both theoretical insights and practical guidance for the advancement of radiative cooling technologies.
Carbohydrates play essential roles in biological, atmospheric, and food-related systems, where their hydration characteristics regulate stability, reactivity, and macroscopic behavior. In this work, ATR-FTIR difference spectroscopy combined with spectral deconvolution was employed to elucidate how arabinose, galactose, and fructose modulate the hydrogen-bond network of water. Analysis of the integrated peak areas shows that sugar addition perturbs the ordered water structure and redistributes the populations of different hydrogen-bonded environments within the OH-stretch region, with fructose inducing the highest effect, followed by galactose and arabinose. As solute concentration increases, the progressive depletion of available water molecules enhances sugar-sugar interactions, further shaping the overall hydrogen-bonding landscape in bulk water. Moreover, fructose forms stronger hydrogen bonds with water relative to arabinose and galactose. These findings indicate that the hydration behavior of carbohydrates is governed predominantly by the number and spatial arrangement of hydroxyl groups rather than by the carbohydrate backbone, while the present approach enables a comparative and concentration-resolved analysis of hydrogen-bond environments across different sugars, providing molecular-level insights relevant to aqueous solution structure, biophysical hydration, and liquid-phase carbohydrate chemistry.
Dissolved atmospheric gases are typically neglected in models of aqueous electrolytes, yet several past examples in the literature reveal physicochemical property anomalies (e.g., changes in electrical conductivity) upon degassing. Here, we use classical molecular dynamics simulations to investigate whether dissolved nitrogen can reorganize the microscopic structure of 0.5 M potassium salt solutions (KX). These simulations closely mimic previous experimental work by Ninham and Lo Nostro, which reported unusual conductivity changes depending on whether dissolved gas was present. By comparing systems with and without N2 for a series of halide and molecular anions, radial distribution functions, coordination numbers, and spatial distribution functions reveal that N2 perturbs electrolyte structure through collective, hydrotropy-like solvent organization. Molecular anions with diffuse hydration shells display anisotropic gas-anion interactions and support weak spatial correlations of N2 molecules, whereas halides remain structurally rigid and largely insensitive to N2. Viewed in terms of hydrotrope-like aggregation between gas and anions, these results explain the conductivity anomalies reported in earlier experiments. Altogether, the effects on the conductivity due to the dissolved gas arise not from local kinetic changes but from mesoscale solvent structuring driven by gas-ion-water cooperativity, providing a molecular-level explanation for gas-mediated ion-specific phenomena in aqueous electrolytes.
This study presents a comprehensive simulation-based assessment of potential transboundary radiological transport to Ireland from six nuclear facilities in the United Kingdom and France, utilising weather data over a fourteen-year period (2011-2024). Systematic screening of 2.2 million HYSPLIT atmospheric dispersion simulations identified eighteen worst-case scenarios representing maximum ground deposition, maximum air concentration, and minimum warning time. Independent verification using FLEXPART and HYSPLIT demonstrated expected inter-model variability (factor of 1-10), with both Lagrangian models providing consistent risk assessment brackets. Heysham, despite its complex 19-isotope AGR source term, produced negligible radiological doses to Ireland (<0.01 mSv), substantially below intervention thresholds. More distant continental facilities (Flamanville, Paluel, Sizewell B) showed low but measurable doses (0.1-4.6 mSv), remaining well below the 50 mSv sheltering threshold. This study addresses urgent-phase protective actions only; transitional-phase food chain countermeasures are beyond scope. Hinkley Point C (under construction) showed elevated but sub-threshold doses (0.3-8.5 mSv). However, the cancelled Wylfa Newydd gigawatt-scale project (the site is now proposed for small modular reactors), owing to its extreme proximity to Ireland, exhibited concerning dose predictions: FLEXPART calculated 19.6 mSv under maximum deposition conditions (May 2024 scenario), approaching the 50 mSv sheltering threshold, whilst HYSPLIT predicted 4.5 mSv. This inter-model variability (factor of ∼5) highlights genuine uncertainty for near-source impacts but converges on a critical finding: were a gigawatt-scale reactor constructed at the Wylfa site, severe accidents during specific meteorological patterns could require protective actions in Ireland. Machine learning models (XGBoost) achieved validation accuracies of 85-93% for rapid impact prediction, whilst global sensitivity analysis revealed that meteorological conditions, rather than release parameters, dominate consequence severity. These findings provide quantitative assurance that existing nuclear infrastructure poses low transboundary risk to Ireland well below urgent-phase intervention thresholds (sheltering and evacuation), whilst demonstrating that facility proximity constitutes the dominant factor determining potential radiological impact.
Daihai Lake, a typical closed inland lake in the arid and semi-arid region of Inner Mongolia, has been subject to two consecutive years of ecological water replenishment to mitigate its severe ecological degradation. While the lake water level has risen and wetland ecosystems have been gradually restored, existing studies have predominantly focused on changes in lake water quality, leaving a critical research gap regarding the hydrochemical evolution, formation mechanisms, and drinking water safety risks of groundwater in the plain area of the Daihai Lake Basin under the dynamic conditions of ongoing water replenishment. To fill this gap, this study systematically analyzed the hydrochemical characteristics and formation mechanisms of groundwater in the study area, and conducted a comprehensive groundwater quality assessment. A suite of representative groundwater samples were collected from the study area after two years of ecological water replenishment, and analyzed using an integrated set of methods including Self-Organizing Map (SOM) clustering, hydrochemical graphical analysis, ion ratio analysis, multivariate statistical analysis, and the Entropy-weighted Water Quality Index (EWQI) method. The results show that: (1) Groundwater is divided into three clusters via SOM, with distinct ion sources from carbonate/silicate weathering and halite dissolution across clusters; some samples have excess SO₄2- and HCO₃-, requiring additional cations for charge balance. (2) Groundwater evolution is jointly controlled by water-rock interaction and evaporative concentration, with limited influence from atmospheric precipitation. (3) Three high-fluoride enrichment mechanisms are identified: mineral dissolution under weakly alkaline conditions, evaporative concentration-driven F⁻ enrichment, and accelerated dissolution of fluorine-bearing minerals induced by acidic mining wastewater. (4) 89% of Cluster-3 groundwater meets drinking standards (EWQI < 50), while 70% of groundwater samples from Cluster 1 and Cluster 2 are of poor quality, mainly distributed in the southwestern lakeshore. This study systematically elucidates the hydrochemical characteristics and formation mechanisms of groundwater in the Daihai Lake Basin under continuous ecological water replenishment, identifies key risk zones for groundwater quality, and provides a solid scientific basis for the protection and sustainable utilization of regional groundwater resources, as well as the optimization of ecological water replenishment strategies in similar arid and semi-arid inland lake basins.
Hyperosmolar-hypernatremic dehydration (HHND) is a life-threatening yet preventable neonatal condition, often due to inadequate breastfeeding. The recent North Indian heat wave heightened dehydration risks, necessitating an evaluation of extreme temperatures' impact on neonatal hydration. This retrospective study analysed neonates admitted to a tertiary care level 3 neonatal intensive care unit (NICU) at AIIMS Jodhpur between April and June 2024. Case records were reviewed, and details on maternal age, feeding practices, presenting complaints, biochemical profile, and outcome were studied. The 2024 (April-May) heat wave led to a threefold increase in NICU admissions for HND compared to the previous 2 years, with cases rising from 2 to 3 per year to 10. Primigravida mothers accounted for 70% of the cases. The mean age of presentation was 6.7 days. Affected neonates experienced weight loss ranging from 11% to 33%, with serum sodium levels between 149 and 185 mEq/l and plasma osmolarity reaching 370-450 mOsm/l. Six neonates required peritoneal dialysis (PD) due to encephalopathy/anuria. One developed aortic thrombosis with lower limb gangrene, necessitating thrombolytic therapy. MRI abnormalities were observed in one case. Despite intensive management, one neonate succumbed to sepsis. Extreme environmental heat significantly heightens the risk of hyperosmolar-hypernatremic dehydration (HND) in neonates. Proactive neonatal monitoring, early breastfeeding support, and parental education are critical to preventing dehydration and its complications, especially in tropical and resource-limited settings, where extreme heat, early discharge, and limited lactation support increase neonatal vulnerability. Judicious fluid management targeting plasma osmolarity and timely intervention with PD in severe cases can optimize survival and neurological outcomes, underscoring the need for heightened vigilance during heat waves.