Campylobacter, non-typhoidal Salmonella, Shigella, Cryptosporidium, and Giardia are responsible for ~1 million domestically acquired waterborne illnesses annually in the United States. The contribution of private well water and underlying geology to these infections has been underexplored. The objectives of this research were to (1) determine whether enteric disease cases in Pennsylvania cluster in time and space; and (2) determine whether enteric disease cases are associated with private well water and karst geology. Confirmed cases of Campylobacter, non-typhoidal Salmonella, Cryptosporidium, and Giardia from 2010 to 2019 in Pennsylvania were analyzed. Spatial clusters were identified using a Poisson-based spatial scan statistic (SaTScan), and temporal patterns were examined using the R package Model Temporal Trends. Zero-inflated negative binomial model regression with county-level random intercepts examined associations between disease incidence, private well usage, and karst geology. All four pathogens had significant clusters of illness in time and space. Cryptosporidium, Giardia, and Campylobacter cases were significantly associated with areas served by private wells (P < 0.05; P < 0.001), and cases of Cryptosporidium and Campylobacter were associated with karst geology (P < 0.01). This novel investigation adds to a growing body of evidence that private well water is a risk factor for enteric disease. Public health interventions should target the management of private well water to reduce the burden of disease globally, particularly in communities not serviced by public water supplies.
Radon is a naturally occurring radioactive gas that poses environmental and health concerns, particularly in regions characterized by uranium-rich geological formations and active fault systems that facilitate its migration from the subsurface into soil gas and near-surface environments. In the Eastern Cordillera of the Central Andes, southern Peru, uranium-bearing deposits intersected by geological faults create favorable conditions for elevated radon concentrations in the soil gas and near-surface environment, due to increased permeability that enhances upward transport. However, lack of systematic data on radon concentrations in these areas has limited development of a national radon framework and constrained regional assessments. This study establishes baseline concentrations of soil gas radon (Rn-222) in faulted and uranium-bearing zones of the Eastern Cordillera. Sixteen measurement sites were surveyed across key geological units, integrating lithogeochemical analyses of uranium in rock samples with in-situ radon measurements. Results reveal spatial variability, with soil gas radon concentrations reaching up to 567 kBq/m3, including high values in structurally controlled zones despite relatively low uranium content (23 ppm). These findings demonstrate that, while uranium-rich lithologies act as primary radon sources, fault-controlled permeability and fracture networks exert dominant control on radon migration. By integrating geological, geochemical, and radon data, this study provides a framework for radon mapping in Peru. Results highlight role of structural geology in radon distribution and support soil gas radon as indicator of uranium mineralization and fault-related permeability. These insights contribute to improved radon assessment strategies and provide scientific basis for future development of a national radon potential map.
Contamination by potentially toxic elements (PTEs) in soil-rice systems poses serious threats to food safety and human health. A total of 225 soil samples and 90 rice samples were collected from typical rice-growing areas in Chongqing, Southwestern China, to investigate PTE sources and transfer in the soil-rice system. The concentrations of 11 PTEs (As, Cd, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Se, and Zn) were determined, and their sources and migration behaviors were investigated using a Positive Matrix Factorization (PMF) model combined with enrichment and transfer indices. Results showed that Zn and Mn dominated in soils, while As, Cd, and Hg exhibited pronounced spatial heterogeneity and signals of exogenous disturbance. PMF identified five pollution sources in soils: geological background (39.5%), agricultural sources (34.8%), light industrial activities & sewage irrigation (17.8%), arsenic-enriched urban disturbance mixed source (5.7%), and industrial emissions & atmospheric deposition (2.2%). Within rice plants, Cd, As, and Se were notably enriched in roots (BCF > 2.6), while grain translocation was limited, indicating a protective barrier. PMF source analysis for rice identified industrial activities & traffic (40.8%), agriculture & irrigation water (34.5%), and coal combustion & waste disposal (24.7%) as major contributors. Transfer coefficient patterns suggested element-specific translocation within rice plants, with Cd showing relatively stronger upward movement, Zn preferentially enriched in stems, and grain accumulation remaining low for most elements. This study provides insights into PTE source-associated patterns and transfer dynamics in soil-rice systems, providing a theoretical basis for paddy soil remediation and agricultural product safety management.
Gadolinium (Gd) has emerged as a trace contaminant in aquatic environments due to the widespread use of gadolinium-based contrast agents (GBCAs) in magnetic resonance imaging (MRI) diagnostics. This study evaluates how preservation conditions, including temperature, acidification, and filtration, affect the stability of Gd chelates in three water matrices (deionized water, tap water, and river water) using inductively coupled plasma mass spectrometry (ICP-MS) for total Gd quantification and ion chromatography coupled with ICP-MS (IC-ICP-MS) for individual GBCA quantification. Across all experiments, the linear GBCA was the most susceptible to degradation, with acidification and ion-rich waters accelerating their dissociation, while macrocyclic agents remained more stable. Freezing provided no preservation benefit and sometimes introduced artifacts possibly related to freeze-concentration effects. Filtration improved recoveries in river water by reducing interactions with particulates and microbial activity, and refrigeration slowed degradation but did not fully prevent it in complex matrices. These patterns show that certain preservation choices can alter apparent speciation and lead to underestimation of linear chelates and misinterpretation of GBCA sources. The results provide standardized preservation protocols for sample handling, including avoiding acidification, minimizing storage time, and refrigerating samples when immediate analysis is not possible.
Injecting CO2 into ultradeep shale gas reservoirs for carbon capture, utilization, and storage (CCUS) can deliver two benefits at the same time: long-term geological storage of CO2 and enhanced gas recovery (EGR). In this study, molecular dynamics simulations were used to examine the competitive adsorption and transport behavior of CH4 and CO2 in representative kerogen-Illite composite nanopores under ultradeep reservoir conditions. Composite pore models containing Illite clay and type I, II, or III kerogen at high thermal maturity were built to represent the matrix pore system of deep shale. CO2 was then injected into kerogen/Illite pores that had already adsorbed CH4, so that the dynamic CH4 displacement process could be observed at the molecular scale. The results show that CO2 adsorbs much more strongly than CH4 and has clear adsorption selectivity. CH4 displacement efficiency is strongly controlled by kerogen type. Type III kerogen shows the strongest affinity for CO2 and the highest CH4 displacement ratio, followed by type II kerogen, while type I kerogen has the lowest CO2/CH4 selectivity and releases the least CH4. The diffusion results further show that CH4 always moves faster than CO2 in these nanopores. These findings confirm that, under ultradeep reservoir conditions, injected CO2 can efficiently compete for adsorption sites on kerogen surfaces and release a large amount of bound CH4. This provides molecular-level support for the feasibility of CO2-EGR in deep shale reservoirs and offers a theoretical basis for optimizing CCUS strategies in ultradeep unconventional formations.
The Viking missions hosted identical payloads on each of two orbiters and landers. All four missions far exceeded their pre-planned operating times and science objectives, with all but one of the 40 science experiments operating fully successfully. Six experiments on each lander were potentially able to detect evidence of life on the mysterious red planet. Only one such experiment obtained significant positive results, and these were not unequivocal because they could possibly be due to nonbiological chemical reactants in the soil. However, Mars science was greatly advanced by other measurements. These established contemporaneous environmental conditions as well as evidence for conditions in the geologic past that would have been far more favorable for life than conditions today. Mars remains the most likely place for life to have originated and evolved other than Earth itself, and it remains the prime target for future exploration. Further, Mars is the only other body in our solar system (and hence, in the universe) potentially inhabitable by the human species.
The standard addition method (SAM) determines sample isotope compositions from mixtures of samples and standards with known isotope ratios, which has been widely applicated for low-mass or low-concentration samples. However, conventional off-line SAM is labor-intensive and can suffer from substantial uncertainty (≥2.5%) in the sample proportion (f value) within the mixture, which compromises isotopic accuracy. Here we present a novel online SAM specifically designed to address these challenges. The reference gas routinely used in conventional analyses is innovatively repurposed as a standard and introduced online directly into the sample stream via the ConFlo IV interface. The isotope ratios of samples are subsequently calculated using an isotope mass balance model. The method is evaluated and validated by measuring the sulfur (S) isotope compositions of standard materials and natural samples using elemental analyzer isotope ratio mass spectrometry (EA-IRMS). The uncertainty in the f value is less than 0.148%, ensuring the accuracy of calculated results. The approach eliminates the need for manual standard addition, significantly enhancing measurement efficiency. The method achieves accuracy and reproducibility comparable to conventional techniques while reducing the sample mass by 75%. Based on the developed approach, coarse to ultrafine atmospheric particulate matter was successfully measured in a haze event, revealing size-dependent S isotope variations. Importantly, this methodology is highly practical and easy to be widely adopted for current standard equipped EA-IRMS laboratories, as it requires no additional labor and financial investments for hardware upgrading proposed in previous publications.
Groundwater quality is often affected by anthropogenic activities in urban settings. This study examines groundwater quality in and around the Santa Fe Springs Oil Field in Los Angeles County, California, where oil and gas production commonly intersects with high density industrial, commercial and residential land uses. Utilizing a combination of new and historical data, we evaluated potential pathways that would allow for oil field formation fluids to migrate into groundwater and whether mixing may have occurred based on the distribution of groundwater and oil field formation fluid tracers in samples. Samples were analyzed for a wide array of constituents including volatile organic compounds, light hydrocarbons, major ions, and various isotopic compositions. Despite evidence of oil field infrastructure providing potential pathways of migration via uncemented annular spaces, casing breaches and historical disposal of oil field formation water in surface ponds, the distribution and occurrence of stable isotopes of water, chloride, boron, and total dissolved solids do not indicate mixing of oil field formation water and groundwater. However, methane isotopic signatures and the presence of heavier alkanes suggest gas from oil-bearing formations have migrated from depth via oil field well infrastructure. Volatile organic compound detections were mainly from manufactured compounds unrelated to oil and gas production, with a relatively limited number of petroleum hydrocarbons also detected. Volatile organic compounds were generally found in wells tapping shallow, modern aged groundwater, indicating anthropogenic activities occurring at or near land surface as the source. Study results suggest that while oil field infrastructure provides migration pathways for oil field formation fluids to be introduced into groundwater, urban land uses not related to oil and gas production are the primary drivers of groundwater quality degradation.
Bacteriophage Shea, which infects the opportunistic pathogen Pseudomonas aeruginosa, likely has a non-canonical pseudolysogenic lifestyle. Here, we present its complete 43,333 bp genome sequence. This announcement will contribute to investigations of this underappreciated phage lifestyle.
Persistent biodiversity data shortfalls undermine our capacity to detect species, map their distributions and characterize their spatial genetic structure, limiting robust biogeographic analyses and the development of effective conservation strategies. This particularly affects hyperdiverse invertebrate groups where hidden diversity remains largely undocumented. This study develops and demonstrates the potential of an integrated high-throughput sequencing (HTS) framework to improve the representation of hidden diversity in regional species inventories and to help close critical gaps in our understanding of species distributions and genetic diversity from a conservation biogeography perspective. Focusing on the Canary Islands (Spain), the workflow combines megabarcoding of more than 4000 mesofauna specimens to generate a curated species-level molecular reference library with community DNA metabarcoding of 168 soil samples. This approach enables consistent taxonomic assignment across insular landscapes and increases the spatial and genetic resolution of occurrence data. We identified 145 species of mites and springtails, including 49 species newly recorded for the archipelago and numerous genetically distinct lineages likely representing undescribed taxa, highlighting all the biodiversity that remains to be described. Integration of the barcode library with metabarcoding data produced 1440 species occurrences, revealing extensive distributional gaps, multiple range expansions and strong within-island phylogeographic structuring, indicating prevalent diversification at fine spatial scales. These results highlight a deep, taxonomically broad underestimation of soil biodiversity and demonstrate that this integrative approach provides a transferable model for advancing the biogeography, evolutionary understanding and conservation of dark and cryptic taxa across broad taxonomic and conservation-relevant contexts.
Photocatalysis is a promising technology for the removal of microplastics from aquatic environments. A current research focus lies in developing photocatalytic materials capable of efficiently degrading microplastics under visible or ultraviolet (UV) light irradiation. In this study, a TiO2@UiO-66 heterostructured nanocomposite was synthesized and employed for the photocatalytic degradation of polystyrene (PS) microplastics under UV illumination at room temperature. The synthesized materials were characterized by XRD, SEM, UV-Vis/DRS, PL spectroscopy, XPS, and EDX mapping. The TiO2@UiO-66 composite exhibited significantly higher photocatalytic activity toward PS microplastic degradation compared with pristine TiO2 and UiO-66 under UV light irradiation. Approximately 63% of PS microplastics (150 ppm) were degraded after 30 h of irradiation at an intensity of 4 mW·cm-2 under natural pH conditions. The analysis of total organic carbon indicated a decline in the removal efficiency of PS microplastics with increasing concentration. Liquid chromatography-mass spectrometry and Fourier transform infrared analyses revealed the formation of soluble organic intermediates such as aldehydes and carboxylic acids during the degradation process. These results demonstrate that the TiO2@UiO-66 photocatalyst is a promising material for the removal of PS microplastics in aqueous environments, where the •OH, O2• - play a dominant role in the degradation mechanism.
Every fall season, Sudan experiences devastating floods that result in significant fatalities, displacement of populations, and severe disruptions to agricultural and economic activities. The 2020 floods were particularly catastrophic, reaching the highest Nile River levels in over a century and affecting more than 800,000 people. To the best of the authors' knowledge, this study represents one of the first large-scale, data-driven flood susceptibility assessments for Sudan using deep Convolutional Neural Network (CNN) model. Twelve conditioning factors spanning topographical, hydrological, geological, and anthropogenic parameters were systematically analyzed. The flood inventory dataset was obtained from the Humanitarian Data Exchange (HDX), comprising geospatially verified flood polygons compiled from remote sensing and field observations. A five-fold cross-validation strategy was implemented to ensure model robustness, yielding a classification accuracy of 97% and demonstrating reliable generalizability across spatial partitions. The analysis generated probability maps with susceptibility values ranging from zero to 1, delineating three discrete risk zones: High, Medium, and Low susceptibility. Results reveal that very high susceptibility zones are concentrated along immediate river corridors, the Khartoum metropolitan confluence area, and low-lying Quaternary alluvial plains in Jazirah and Sennar states, where Sudan's most critical agricultural production occurs. The susceptibility maps provide essential decision-support tools for evidence-based urban planning, agricultural management, and water resources development, enabling targeted risk reduction strategies that can protect lives, livelihoods, and development investments.
Riverine inputs and sedimentary processes jointly regulate nutrient cycling in semi-enclosed coastal seas, yet their combined influence on phosphorus (P) dynamics remains insufficiently understood. This study evaluates the chemical forms, spatial gradients, burial, and long-term evolution of sedimentary P from the Yellow River Estuary Wetland to the Bohai Sea based on observations from 2011 to 2020. A pronounced regional pattern was identified, with detrital P dominating and a clear land-sea gradient reflecting the influence of major riverine inputs. Spatial heterogeneity was further expressed through contrasting sedimentary environments: high-sedimentation areas accumulated substantial detrital P, whereas regions with stronger biological activity exhibited elevated reactive P. At the sediment-water interface, burial exceeded benthic release, enhancing deposition of reactive P and contributing to a 22.7% increase in total sedimentary P from 1998 to 1999 to 2018-2020, indicative of efficient downward transport. Despite this, porewater data showed that benthic efflux remained sufficient to influence nutrient stoichiometry in the overlying water. Elevated nitrogen-to-phosphorus ratios, amplified by terrestrial loading and imbalanced benthic fluxes, reinforce persistent P limitation and highlight the vulnerability of the Bohai Sea to nutrient imbalance. These results highlight the central role of river-sea coupling in regulating coastal P pool and guiding eutrophication management.
Water source and quality is the most important factor for region sustainable development, especially in the water-scarce arid agricultural regions. In the agricultural area of arid Qaidam Basin, water quality remains inadequately studied. Focusing on the Xiangride River Watershed in the southeastern Qaidam Basin, this research explores the recharge sources, hydrogeochemical evolution, and quality of river water and groundwater integrating correlation analysis, principal component analysis (PCA), and inverse geochemical modeling. Stable isotopic analysis indicates that river water and groundwater are derived from mountainous precipitation, and groundwater is recharged by lateral runoff and river seepage in the plain area. Most river water and groundwater samples exhibit relatively low TDS values of < 1000 mg/L, and groundwater exhibits more complex hydrochemistry compared with river water. Along the flow path, the hydrochemical types are marked by the HCO3·Cl·SO4-Na·Mg type for river water, which groundwater shows an evolution from Cl·HCO3-Na·Mg to Cl·HCO3·SO4-Na·Ca·Mg and ultimately to HCO3·Cl·SO4-Na·Ca·Mg. The comprehensive analysis by PCA, major ions relationships and inverse geochemical modeling identifies that water-rock interactions including dissolution and precipitation of evaporites, carbonates, and silicates, together with cation exchange and mixing control the hydrochemical compositions. Water quality assessment based on EQWI, SAR, and Na% values classifies most river water and groundwater as "good" without obvious spatial variation, indicating that the overall water quality is adequate for domestic and agricultural uses. The attention needs to be made in certain area with relatively elevated groundwater NO3 -. These findings provide a basis for the sustainable management of water resource in arid agricultural zones.
Dendrogeomorphology provides valuable insights into the dating of geomorphic events but requires complex analyses of tree-ring records from highly disturbed trees. While deep learning algorithms have been successfully applied to detect boundaries in normally developed growth rings, their performance under severely disturbed growth conditions remains largely unexplored. This study evaluates whether deep learning can effectively segment tree rings exhibiting abnormal growth patterns commonly observed in dendrogeomorphological contexts. Increment cores were collected from a debris-flow-affected area. High-resolution images were subsequently acquired and manually annotated to identify tree rings boundaries and growth disturbances. A series of experiments was conducted using different neural network architectures, image resolutions, and filtering techniques to examine the relationship between convolutional neural network (CNN)-based models and the level of cellular detail represented in the images. Our results indicate that segmentation performance declines in growth disturbances characterised by pronounced changes in colour and texture relative to normal growth patterns. Nevertheless, the proposed framework successfully identified sets of narrow ring boundaries spaced more than 200 μm apart when colour remained consistent, correctly segmenting most rings associated with the most severe growth suppressions in our dataset. Notably, models relying primarily on simple features such as colour variation performed comparably to those incorporating finer cellular details. We also found that, within a patch-based processing framework, performance decreased when growth direction was not specified in advance. Overall, this study provides a systematic evaluation of CNN-based methods under highly disturbed growth conditions, highlighting both their potential and current limitations in dendrogeomorphological applications.
An analytical method combining sample pretreatment with ion chromatography (IC) was established for the determination of fluorine content in lithium cobalt oxide (LiCoO2) samples. The samples were treated using a sulfuric acid-hydrogen peroxide system, and volatile fluorine-containing species were transferred by nitrogen purging, absorbed in alkaline solution, and finally determined as F- by IC. Preliminary spike experiments and condition screening were conducted to evaluate the feasibility of the pretreatment procedure and to investigate the effects of sulfuric acid solution volume, sulfuric acid volume fraction, reaction time, and reaction temperature. The results showed that selection of pretreatment conditions should not be based solely on the F- response in the absorption solution, but should also take the sample decomposition state into account. The final pretreatment conditions were determined as follows: sulfuric acid solution volume, 20.0 mL; sulfuric acid volume fraction, 60%; reaction time, 120 min; and reaction temperature, 190 °C. Under these conditions, the fluorine contents in five batches of LiCoO2 samples were 0.25, 0.32, 0.26, 0.19, and 0.39 mg g-1, respectively. These results indicate that the proposed method is preliminarily applicable to fluorine determination in LiCoO2 samples.
In matrix acid stimulation of carbonate rocks, understanding acid-rock interaction is essential to optimize wormhole formation and overall treatment efficiency, since heterogeneity can lead to distinct dissolution patterns. Mineralogical heterogeneity significantly affects this process due to the different dissolution kinetics of calcite and dolomite; however, it remains unclear how grain size, crystal defects, and mineral distribution influence this interaction. To investigate these factors, five highly dolomitized carbonate samples from the Piauí Formation (Parnaíba Basin) were characterized by petrography, X-ray diffraction, X-ray fluorescence, scanning electron microscopy, and porosity measurements, and subjected to static dissolution in 1 M HCl with evaluation of mass loss and quantification of calcium and magnesium ions. The results showed that texture and mineralogical composition play a fundamental role in dissolution: larger crystals generated wider cavities due to detachment during acid attack; samples with higher Ca and Mg contents relative to Si exhibited higher dissolution rates, whereas increasing quartz content reduced reactivity. Most samples showed an early predominance of Ca2+ release followed by increasing Mg2+ concentrations, reflecting preferential calcite dissolution and progressive dolomite contribution. Well-developed crystals with fewer structural defects exhibited lower reactivity. Postdissolution peak broadening in XRD patterns suggests structural modification of the minerals. Overall, mineralogical heterogeneity controls acid-rock reactivity across multiple scales, highlighting the importance of integrated mineralogical and textural characterization to improve prediction and optimization of acid stimulation in heterogeneous carbonate reservoirs.
Soil nitrogen (N) turnover regulates plant nutrient availability and potential N loss, yet how microbial communities, anthropogenic activities, and climate-change factors are associated with its global patterns remains poorly synthesized. Here, we quantified soil N turnover using the N mineralization efficiency index (NMEI), defined as gross N mineralization normalized by soil N content, together with recalcitrant and labile NMEIs. Using 2444 observations from 373 15N-based studies, we combined global pattern analysis with meta-analysis to evaluate climatic, edaphic, microbial, land-use, fertilization, and global-change associations with NMEI. We found that NMEI was higher in croplands and alkaline soils than in natural ecosystems and acidic or neutral soils. Recalcitrant NMEI exceeded labile NMEI in croplands and alkaline soils, suggesting greater contribution of less labile organic N pools to mineral N production under these conditions. Bacterial abundance was the strongest positive predictor of NMEI, whereas fungal abundance, fungal-to-bacterial ratio, and microbial biomass were negatively associated with NMEI. Higher temperatures and soil pH, combined with lower soil organic carbon, were associated with higher NMEI, partly through shifts in microbial community towards bacterial dominance. Meta-analysis showed that land-use change and fertilization increased NMEI by 11.7% and 21.4%, respectively, whereas direct climate-change factors showed no significant overall effect. Conversion of natural forests to croplands or managed plantations increased NMEI by 17.4% and 19.8%, respectively. Balanced N-phosphorus-potassium, organic-only, and combined organic-balanced fertilization increased NMEI by 62.7%, 49.2%, and 47.7%, respectively, whereas inorganic N-only fertilization had no significant effect. These findings suggest that bacterial dominance and anthropogenic changes in land use and fertilization are key predictors of global soil N turnover. Nitrogen management should therefore interpret and optimize mineral N supply by jointly considering microbial regulation, land-use effects, and balanced or organic nutrient inputs.
Carbon dioxide is a fundamental atmospheric component that regulates Earth's climate. However, atmospheric CO2 levels (pCO2) during the Cambrian Explosion remain poorly constrained. Here we report pCO2 variations reconstructed via carbon isotope signatures of algal fossils from eight fossil deposits across the Ediacaran-Cambrian transition (~553 to ~508 Ma). Results reveal an increase in pCO2 (±1σ) from ~3-9 to ~9-21 PAL during ~553-529 Ma, followed by a progressive decline to ~5-17 PAL and ~3-8 PAL at ~517 Ma and ~508 Ma, respectively. These temporal pCO2 changes coincide with shifts in marine strontium isotope values, which, together, are most consistent with tectonically driven changes in the carbon and strontium cycles, as supported by the results of Earth system biogeochemical box modelling. Tectonic modulation over a three-stage greenhouse-hypergreenhouse-greenhouse climate could have profoundly influenced marine environments in ways that impacted the early diversification of animals.