Earth and Environmental Sciences

The significant impacts of pressure-flow scour have emerged as a critical concern in recent decades, largely due to the severe environmental effects of climate change. Earlier research primarily concentrated on estimating the maximum pressure-flow scour depth around cylindrical bridge piers through dimensional analysis and theoretical approaches. However, the reliability of some previous equations for predicting the scour depth has been questioned. This paper introduces two new theoretical methods to enhance the predictive accuracy of pressure-flow scour depth around cylindrical piers. Using the existing equations for maximum scour depth along the vertical jet centerlines, the first method adapts these principles to develop an equation for the pressure-flow scour around cylindrical bridge piers. The second method is grounded in phenomenological turbulence theory. It employs two distinct equations for calculating the angle and velocity of the combined jet, as well as the effective depth under the bridge deck. The equations formulated in this research have been calibrated using datasets that span sufficiently long-time intervals. The results indicate that both methods can accurately predict the maximum pressure-flow scour depth at equilibrium time. Notably, statistical indicators suggest that the second method offers significantly better results compared to the first and previous equations.

Helicobacter pylori is a Gram-negative bacterium implicated in chronic gastric infections and gastric cancer, making it an important target for therapeutic intervention. Increasing antibiotic resistance of this pathogen has reduced the efficacy of conventional therapies, emphasizing the urgent need for alternative natural treatments. Mentha piperita essential oil exhibits antimicrobial and antioxidant activities, which are further enhanced when formulated as a nanoemulsion. Nanoemulsification improves solubility, stability, bioavailability, and bacterial targeting. Although essential oil-based nanoemulsions have shown antimicrobial potential, limited studies have systematically evaluated their effects on key virulence factors such as urease activity and biofilm formation in H. pylori. In this study, a Mentha piperita essential oil nanoemulsion stabilized with sodium dodecyl sulfate (MPNE-SDS) exhibited a mean particle size of 168 nm, a Polydispersity Index of 0.28, and maintained stability for up to three months. MPNE-SDS demonstrated potent antibacterial activity against H. pylori, with MIC values ranging from 6.25 to 50 µL/mL of nanoemulsion formulation, and showed enhanced efficacy compared to bulk essential oil. It also reduced whole-cell urease activity (IC₅₀ = 41.6 µL/mL) and inhibited biofilm formation (IC₅₀ = 24.5 µL/mL), while higher concentrations were required for biofilm eradication (EC₅₀ = 133 µL/mL). These findings indicate that MPNE-SDS enhances antibacterial performance and affects key H. pylori virulence-associated activities, suggesting its potential as a non-antibiotic approach and warranting further preclinical investigation.

Land-use transition (LUT), a pivotal vector for anthropogenic intervention in the carbon cycle, profoundly influences the formation and evolution of regional carbon emission patterns. This study focuses on Hainan, China's sole tropical island, and establishes a model accounting for carbon emissions associated with LUT based on related remote-sensing data, socioeconomic statistics, and energy consumption-related data between 2000 and 2025. We combine spatial autocorrelation analysis, an extended logarithmic mean Divisia index decomposition model, and the Tapio decoupling model to systematically elucidate the spatiotemporal features of LUT-associated carbon emissions, their driving factors, and their decoupling relation with economic growth. Notably, Hainan Province features an LUT involving decreasing and increasing proportions of carbon-sink land and carbon-source land, respectively, with construction land expansion being the primary transition mode driving carbon emission growth. The associated carbon emission response features a spatial differentiation pattern of high values concentrated in the north and west and low values localized in the south and east. In addition, carbon sources and sinks demonstrate considerable spatial agglomeration. Economic output is the core driver promoting carbon emission growth, with improvements in land-use efficiency and energy intensity being critical for carbon emission mitigation. During the examined period, the correlation between LUT-associated carbon emissions and economic growth evolves from weak to strong decoupling, demonstrating the remarkable efficacy of peak carbon and carbon neutrality goals in guiding emission reduction-focused LUT. Overall, this research provides a scientific basis for coordinating LUT and low-carbon development in the Hainan Free Trade Port initiative.

The relationship between socio-economic development and ecological protection is a dynamic and interactive process. How to balance and coordinate the achievement of both objectives is an eternal topic concerning the sustainable development of nations and regions. Industry is a key factor driving economic growth. The development of industry brings technological progress and the acceleration of urbanization, but also leading to excessive consumption of resources, environmental pollution and the destruction of ecosystem. The health of ecosystem is closely related to the stability of the ecosystem services (ES) required by industrial production activities. Therefore, it is a prerequisite for realizing sustainable social and economic development to scientifically understand the impact of industrial development on ES. In summary, this study systematically analyzes the bidirectional influence mechanism between industry and ecosystems, proposing a research framework to explore the complex interactions between the two. Based on this research framework, this paper constructs a quantitative analysis model of the interaction between industry and ES using spatial simultaneous equation modeling techniques, revealing the complex feedback loop relationship between the two. This research can provide scientific references for ecological protection and high-quality development strategies.

Landslide susceptibility mapping (LSM) is a critical tool for hazard mitigation in mountainous regions. However, the reliability of existing models remains uncertain due to inconsistencies in data quality, sampling strategies, and validation approaches. Although machine learning (ML) and deep learning (DL) models often report high predictive accuracy, their performance may not be robust or transferable, particularly in data-constrained tropical environments. To address this limitation, this study develops a unified, data-consistent evaluation framework to compare statistical, ML, and DL approaches for landslide susceptibility mapping in the Luang Prabang Range, northern Thailand. Five models, including Frequency Ratio (FR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), were applied using the same landslide inventory, conditioning factors, and validation strategy to ensure a fair comparison. The results indicate that RF achieved the most stable and reliable performance (AUC = 0.942), followed by XGBoost (0.930), CNN (0.914), LSTM (0.902), and FR (0.865). While DL models demonstrated strong predictive capability, their performance was more sensitive to data limitations and model configuration. In contrast, RF provided a better balance between accuracy, robustness, and data efficiency. The findings demonstrate that differences in model performance are influenced not only by algorithm selection but also by data structure and parameter settings. The main contribution of the study is the implementation of a unified evaluation framework that enables more reliable assessment of model robustness, uncertainty, and interpretability. This study provides practical guidance for model selection in landslide susceptibility mapping and highlights the importance of data consistency and model transparency, particularly in tropical mountainous regions where data limitations are common.

Maize (Zea Mays) is one of the world's most important staple crops, providing food for humans and feed for livestock. However, its production is threatened by a range of stresses, including crop diseases, which significantly reduce yields, particularly in smallholder farming systems. Traditional disease detection methods, such as visual inspection, are often labour-intensive, subjective, and prone to error, leading to delayed interventions and widespread crop losses. This study uses unmanned aerial vehicle (UAV) remote sensing and machine learning (ML) to investigate the feasibility of detecting maize leaf diseases in a smallholder farm located in the Mopani District of Limpopo Province, South Africa. UAV-derived vegetation indices including NDVI, GNDVI, and NDRE were combined with UAV multispectral bands and the three ML algorithms, namely - support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), to first distinguish healthy from diseased plants and then to classify specific maize diseases. The SVM algorithm achieved the highest accuracy in both, distinguishing healthy and diseased crops from other land cover classes (91.73%) and in distinguishing specific diseases (89.41%). Among the diseases identified, Southern Corn Leaf Blight was classified with the highest user's accuracy, while phosphorus deficiency had the lowest user's classification accuracy. The results demonstrate the potential of integrating UAV-based multispectral imaging and ML for precision agriculture by providing timely, spatially detailed disease information that enables targeted management practices, reducing crop losses and enhancing food security for smallholder farmers.

Workers in wastewater treatment plants (WWTPs) are routinely exposed to airborne bacterial and fungal bioaerosols generated during wastewater processing. Although bioaerosol exposure has been widely reported, integrated assessments that capture spatial variability across treatment units, diurnal work shifts, and combined bacterial-fungal exposure remain limited, particularly in developing-country WWTPs. This study aimed to evaluate occupational inhalation exposure to culturable bacterial and fungal bioaerosols in municipal WWTPs and to estimate potential non-carcinogenic health risks using hazard-based metrics. A cross-sectional study was conducted in August 2024 at the Sanandaj WWTP, Kurdistan Province, Iran. Airborne bioaerosols were sampled across ten operational units, including influent wastewater, screening, grit chamber, aeration tank, settling units, anaerobic digester, and office areas. Sampling was performed over four consecutive working days during morning and evening shifts using a BioStage single-stage impactor connected to a calibrated Quick Take 30 pump. A total of 320 air samples (160 bacterial and 160 fungal) were collected at breathing-zone height (1.5 m). Non-carcinogenic inhalation risks were estimated using hazard quotient (HQ) and hazard index (HI) approaches based on standard exposure assumptions. Culturable bacterial bioaerosols were dominated by Gram-positive bacilli (~ 41%), followed by Gram-negative bacilli (30-36%), Gram-positive cocci (17-23%), and Gram-negative cocci (4-8%). Mean bacterial concentrations were highest in the aeration tank (921.67 CFU m⁻³) and grit chamber (743.52 CFU m⁻³), while the activated sludge bed and office areas showed minimal concentrations (~ 20 CFU m⁻³). Nineteen fungal species were identified, with Aspergillus niger, A. flavus, Mucor, and A. fumigatus being most prevalent. Comparisons between high-exposure units (aeration tank and grit chamber) and low-exposure areas (office building and activated sludge bed) showed a very large contrast in mean bioaerosol concentrations (Cohen's d = 2.14; 95% CI: 1.61-2.66; p < 0.001). HQ values were highest in the aeration tank (0.60) and grit chamber (0.49). The cumulative HI for the facility was 1.9, indicating exceedance of the selected reference concentration. The findings revealed marked spatial and temporal variability in bacterial and fungal bioaerosol exposure within WWTPs operations. While the estimated HI suggests potential concern, results should be interpreted cautiously due to methodological uncertainties. Targeted exposure control measures, routine monitoring, and future studies incorporating molecular techniques are recommended to better characterize occupational bioaerosol risks.

Electronic waste (e-waste) poses environmental issues and risks to health, but it holds polycarbonate, epoxy, and metal oxide, which have the potential for hydrogen production via the gasification process. This research involves the proper recycling of e-waste to an effective feedstock for hydrogen production via a plasma gasification process featuring a waste heat recovery system. During the plasma gasification process, the operating temperature is varied from 1500 to 3000 °C with an interval of 500 °C without a catalyst. The optimum plasma gasification temperature involves different concentrations of calcium oxide (CaO) catalyst for enriching the hydrogen yield. Effects of plasma gasification processing with a waste heat recovery system on energy consumption reduction, syngas yield, reactor stability, and carbon conversion efficiency are studied. The system featuring higher plasma gasification temperature (3000 °C) found reduced energy consumption (48.9%) and enhanced hydrogen yield of 66.7 mol/kg while reducing CH₄ and CO₂ emissions to 9.8 mol/kg and 10.5 mol/kg, respectively. The incorporation of a heat recovery system improved energy utilization efficiency to 71.5% and increased CCE (carbon conversion efficiency) from 69.8% to 91.6%. Additionally, CaO catalyst addition (15 wt%) further optimized gasification performance, leading to a hydrogen yield of 72.6 mol/kg while reducing CH₄ and CO₂ emissions to 8.1 mol/kg and 7.8 mol/kg, respectively. These findings highlight plasma gasification as a viable and sustainable technology for hydrogen production from e-waste, offering significant environmental and energy efficiency benefits.

River systems characterized by strong groundwater-surface water interaction exhibit complex hydrodynamic responses under hydroclimatic extremes. This study investigates how infiltration-dominated river reaches modulate flow persistence during drought and floodplain activation during extreme rainfall. A two-dimensional Environmental Fluid Dynamics Code (EFDC) model was implemented for a 20.35 km reach of the Gallinas River (Mexico) using high-resolution UAV-derived bathymetry and field-based discharge measurements. The model was calibrated and independently validated prior to simulating a 25-year return period flood (peak discharge = 1231.8[Formula: see text] [Formula: see text]) and a drought scenario constrained by an environmental-flow threshold (4.1[Formula: see text] [Formula: see text]). Results reveal the emergence of hydrodynamic thresholds driven by cumulative reach-scale losses ([Formula: see text]), producing nonlinear downstream discharge decay under low-flow conditions and requiring a minimum upstream inflow of [Formula: see text] to maintain ecological continuity. Under flood forcing, inundation patterns are primarily controlled by channel geometry and longitudinal slope reduction rather than discharge magnitude alone. These findings demonstrate that infiltration-influenced rivers exhibit dual hydrodynamic controls under contrasting extremes and highlight the importance of explicitly representing cumulative exchange processes in two-dimensional modeling frameworks. The study provides transferable insights for assessing drought resilience and flood risk in permeable or groundwater-connected river systems facing increasing hydroclimatic variability.

Helicobacter pylori (H. pylori) infection remains a significant global health challenge, contributing to various gastrointestinal disorders, including peptic ulcers and gastric cancer. The bacterium’s urease enzyme plays a pivotal role in its survival by neutralizing gastric acidity, making urease inhibitors a promising therapeutic strategy. This study explores the green synthesis of silver nanoparticles (AgNPs) using Persian lime (Citrus latifolia T.) fruit extract as a reducing and stabilizing agent, optimized via the Taguchi method to achieve minimal particle size for enhanced bioactivity. Characterization techniques such as Fourier-transform infrared spectroscopy (FT-IR), dynamic light scattering (DLS), transmission electron microscopy (TEM), X-ray diffraction (XRD), and UV-Vis spectroscopy confirmed the formation of spherical AgNPs with an average size of 27.63 nm and a zeta potential of -13.8 mV, indicating good stability. The green synthesized AgNPs exhibited potent urease inhibitory activity, with an IC50 value of 15.02 ± 2.36 µg/mL, surpassing that of Persian lime (Citrus latifolia) fruit extract (IC50= 33.31 ± 1.43 µg/mL). In contrast, chemically synthesized AgNPs counterparts exhibited minimal inhibitory activity against urease. These findings highlight the potential of green synthesized AgNPs as effective urease inhibitors with possible relevance to H. pylori-associated pathogenesis. Since H. pylori urease is structurally homologous to the jack bean urease used in this study, these results warrant further investigation using direct anti-H. pylori assays and in vivo models. The integration of natural extracts in nanotechnology not only reduces environmental impact but also enhances biocompatibility, paving the way for novel antimicrobial therapies. Consistently refer to Sample 7 conditions (pH 5, 3500 µL, 5 mM, 80 °C) as the experimentally validated optimum, while noting the Taguchi-predicted conditions where appropriate.

Nanoplastics are pervasive environmental contaminants that continuously expose humans and accumulate in multiple organs. Increasing evidence associates NPs with adverse health effects, including inflammation and carcinogenesis, yet their impact on human innate and adaptive immunity remains poorly understood. This knowledge gap is particularly relevant for diseases treated with therapies that modulate immune responses. Here, we investigated the effects of NP exposure on major subsets of human peripheral lymphocytes, essential for antitumor and antiviral defense while preserving immune tolerance. Peripheral blood mononuclear cells from healthy donors were exposed to oxidized and plasma-exposed NPs, which acquired a stable protein corona. NP exposure induced a time-dependent increase in immune cell interactions and resulted in reduced activation and functionality of CD4⁺ and CD8⁺ T cells, B cells, and natural killer cells. T lymphocytes displayed impaired tumor antigen-specific responses, while natural killer cells showed decreased tumor cell-killing capacity. Notably, B cells internalized NPs, leading to reduced ability to generate antibodies against SARS-CoV-2. Overall, these findings demonstrate that NPs compromise both innate and adaptive immune functions, weakening antiviral and antitumor responses. Our results highlight potential risks associated with NP exposure for susceptibility to infections and cancer as well as immune-based therapy efficacy.

Land suitability analysis is vital for sustainable agriculture in fragile mountain ecosystems such as the Nilgiris. Earlier assessments, based on existing criteria, often rated large areas as "not suitable" and identified no "highly suitable" land for crops like potato, cauliflower, beans, wheat, and tea, despite their long history of successful cultivation in the region. This clear mismatch highlighted the need for region-specific criteria. This study refined the FAO land evaluation criteria by introducing an erosion hazard index (EHI) that jointly integrates slope gradient and active land management conditions, particularly terracing, into a single normalized parameter. To the best of the authors' knowledge, this combination has not previously been formalized for mountain agro-ecosystems of the Western Ghats. Additional adjustments to climatic and soil parameters were made to reflect the unique agro-ecological conditions of the Nilgiris. The revised assessment produced results more consistent with on-ground reality. Tea exhibited high and moderate suitability across 37.4% and 44.4% of the representative watershed (Thambatti), respectively. Potato, cole, and root vegetables were highly suitable in 6.9% and moderately suitable in 8.2% of the area, with suitability primarily limited by high erosion hazard (EHI > 0.54 for potato; EHI > 0.62 for cole and root vegetables). Field beans showed no highly suitable area but were moderately suitable in 23.4% area, constrained mainly by soil acidity, while wheat exhibited 15.1% moderately suitable area, limited by temperature, with erosion also being a significant factor for both crops. Fruit crops were moderately suitable in 12.6% and marginally suitable in 80.3% of the area, mainly constrained by low mean temperature, high soil acidity, and heavy soil texture. The refined criteria offer a more accurate and practical assessment of land suitability, addressing observed discrepancies and supporting sustainable agricultural planning in the Nilgiris.

In this study, we compared the in-site ground-based climate variables (1982-2016) with a multiyear normalized difference vegetation index (NDVI) dataset to characterize climate change and vegetation-climate interactions at Ergune, Inner Mongolia, China, using the time series analysis, the correlation analysis and the principal component analysis (PCA). To reveal the time lag effects in climate-vegetation relationship, vector auto regression (VAR) model was constructed and the impulse-response analysis, the causality analysis were conducted. We found that the regional climate change over the past decades could be summarized as climate warming and drying. And the regional climate warming was mostly contributed by summer warming, rather than the widely reported winter warming in the north hemisphere. Climate variables were highly correlated. The PCA analysis revealed that the 1st principal component represented the temperature related variables, and the 2nd principal component represented the humidity related variables. At seasonal scale, however, the humidity and temperature was the 1st principal component for summer and winter respectively. VAR analysis revealed that, the precipitation has higher impact on NDVI than the temperature. The feedback of NDVI to humidity was significant, but feedback of NDVI to Temperature was non-significant. VAR model had better performance in prediction of NDVI than the multi-linear regression approach. This study investigated the climate-vegetation relationship with full considerations on the co-linearity and the time lag effect in climate system. The cause-effect in climate-vegetation relationship indicated the feedback of NDVI to climate variability and the ecological function of vegetation in mitigating and regulating the regional climate.

The Hawaiian Islands cause significant disruption to North Pacific oceanic and atmospheric flows creating highly localized spatial variability of ocean conditions on coral reefs. This variability affects climate impacts on these corals but is unresolved in global climate models. Using a dynamically downscaled model to resolve future conditions at high temporal (daily) and spatial (4 km) resolution for the Hawaiian Islands, we investigate projected heat stress and the adaptation rate required for corals to withstand projected end of century warming for three different emission scenarios. In the region, the Island of Hawai'i is projected to experience the greatest heat stress by the end of the century; however, we find that coral adaptation is possible to allow Hawaiian coral to persist in the three emission scenarios. Robust projections of future conditions and required adaptation rates on a local scale are critical for successful management of these crucial ecosystems.

Abstract This study investigates household air pollution from biomass combustion by integrating a household survey, experimental stove testing, and data-driven analysis. A structured survey of 1200 households captured socio-economic conditions, cooking practices, and health outcomes, showing that 57.4% rely on agriculture and 14.8% report health symptoms linked to traditional stove use, while 33.1% have adopted improved stoves. Experimental testing evaluated stove performance and emissions under real operating conditions. Results indicate that thermal efficiency peaks at 37% during the simmering phase and declines during cold and hot starts. Emissions were highest during cold start, with CO reaching 123 g/MJ and PM 1172 mg/MJ, but decreased by more than 40% during stable operation, particularly when charcoal was used. Temperature was identified as an important environmental factor, reducing CO and PM concentrations while increasing NO 2 formation. Overall, the findings highlight the combined influence of technology performance, user practices, and environmental conditions on household air pollution. The study underscores the importance of promoting cleaner cooking technologies, improving stove operation, and integrating socio-economic considerations into intervention strategies to reduce health risks and support sustainable household energy transitions.

In the present study, the biodegradation of Low-Density Polyethylene microplastics was investigated using Porphyridium purpureum microalgae, with a focus on evaluating the effects of microplastic concentration, particle size, and shaking speed. The study was conducted in two phases: first, optimizing the cultivation conditions for Porphyridium purpureum, followed by assessing its ability to remove Low-Density Polyethylene. The highest microalgae yield was achieved under optimal conditions, which included a light intensity of 2500 µmol photons m⁻² s⁻¹, F/2 culture medium, and a temperature of 30 °C. These conditions were established as the baseline for the Low-Density Polyethylene removal phase. The results demonstrated that the maximum Low-Density Polyethylene removal efficiency achieved was 34.24%. Fourier Transform Infrared Spectroscopy analysis demonstrated a reduction in the intensity of the carbonyl functional group, likely due to the release of carbon from the microplastic structure, thereby indicating an effective interaction between microalgae and Low-Density Polyethylene. Furthermore, Scanning Electron Microscopy images revealed significant surface modifications, including small holes and corrosion on the Low-Density Polyethylene particles, providing strong evidence of the degradation process facilitated by Porphyridium purpureum. These findings suggest that the microalgae have the potential to degrade Low-Density Polyethylene microplastics, offering valuable insights into their use for bioremediation of microplastic pollution.

Abstract Groundwater is a vital component of the hydrological cycle, and understanding its dynamics is crucial for water resource management under climate change. This study employs GRACE-FO satellite data to assess groundwater storage (GWS) dynamics in Hunan Province during the 2024 flood season (April-September). Given the abundant surface water resources in this region, we explicitly incorporate the water storage of Dongting Lake and 28 large reservoirs when calculating surface water storage anomaly (SWSA), which is crucial for estimating the GWS anomaly (GWSA). Accordingly, GWSA is obtained by subtracting the soil moisture storage anomaly (SMSA) and SWSA from the GRACE-FO-derived terrestrial water storage anomaly (TWSA). Furthermore, correlation coefficients and contribution of each water storage component to TWSA are calculated to reveal inter-component interactions and response mechanisms to precipitation. Results show that original TWSA, SWSA, and GWSA increase markedly from March to July 2024. After detrending and deseasonalizing, SWSA and GWSA exhibit a complementary relationship (correlation coefficient: −0.20), with changes of −3.08 km 3 and −1.12 km 3 over the flood season, largely attributed to anthropogenic flood control operations. In contrast, SMSA and GWSA are weakly positively correlated (0.29), reflecting limited direct recharge efficiency. TWSA is strongly correlated with both SMSA (0.78) and GWSA (0.71), reflecting synergistic variation among water storage components. Consistently, GWSA contributes the most (44.52%) to TWSA fluctuations, followed by SMSA (31.80%) and SWSA (23.68%), highlighting the critical role of groundwater in the regional water cycle. These findings provide a valuable scientific basis for sustainable water resource management and regulation in Hunan Province.

The surf zone is a dynamic coastal area characterising the physical environment of sandy beaches. However, direct, non-disturbing field observations of the highly variable sedimentary history of surf zones have been almost impossible in the past. The lack of on-site observations has limited our understanding of the morphological behaviour and inherent dynamics. In contrast, surf-zone stratigraphy was uplifted onto land on a time scale of seconds at the Kaiso Coast, Japan, by the Noto Peninsula Earthquake on 1 January 2024. The structure of unsolidified sediments covering the bar-trough zone to the foreshore (hereafter referred to as the surf zone) has been instantaneously preserved as it was without post-event interference except for the top layer. This extraordinary natural experiment enables us to explore the present-day sedimentary architecture formed beneath the surf zone under high-wave conditions. Here, we show the results of a large-scale trenching survey of the uplifted stratigraphy that covers the surf zone, including the breaker zone. A high-resolution photogrammetric digital archive of the sedimentary structure of the ephemerally preserved stratigraphy that was instantaneously uplifted by the earthquake was constructed, which provides an ideal basis for interpreting the spatiotemporal evolutionary history of bedforms within the surf zone. The spatially continuous orthoimages, covering a total of over 500 m, identified the development and transition of various sedimentary structures that were previously estimated but not fully evidenced in the real field. The combination of multiple trench surveys, aligned in both cross-shore and alongshore directions, allows for quasi-three-dimensional observations. This pioneering archive provides a unique opportunity for anyone to freely observe in detail the recent sedimentary structures as if they were there. Together with the wave and tidal observation records prior to the uplift, the comprehensive archive provides vital information to gain essential physical insights into the evolutionary sequences.

Remediating crude oil-contaminated sites is vital for environmental recovery. Surfactant based remediation strategies have gained importance in the management of such sites. Combining biogenic surfactant flushing with conventional methods is noted to be effective than using a single approach. Plant-based surfactants, such as saponins from Sapindus mukorossi, are easier to produce than microbial biosurfactants which require stringent control of conditions. However, research on their application in crude oil contaminated site remediation is limited. This study is an exploration of Sapindus mukorossi extract (saponin extract) for flushing crude oil from contaminated sand. It was observed that the dissolution of crude oil was controlled by its diffusion from sand. A pseudo first order model was used as an empirical description of the removal process. The saponin extract demonstrated a higher solubility enhancement factor (1.32) and better removal of asphaltenes compared to water and favored synthetic surfactant sodium dodecyl sulphate (SDS). The optimal duration of flushing was 22 h, 2 h and 106 h for distilled water (DW), sodium dodecyl sulfate (SDS) and saponin extract respectively. The dominant mechanism of flushing was inferred, based on the experimental data, to be mobilization. This affirms that a low concentration of saponin extract would render satisfactory flushing. The emulsion forming ability of saponin extract was more pronounced with crude oil- water mixtures having higher proportion of water. A lab-scale setup simulated continuous soil flushing, examining the effects of aqueous phase composition, flow rate, and flushing duration. Saponin extract flushed 60% of the crude oil from contaminated sand. Given its recognized renewability, biodegradability, low toxicity and cost, and the laboratory scale effectiveness demonstrated in the current study, saponin extract may serve as a preliminary intervention to reduce initial contaminant loads and render the soil matrix amenable for subsequent synthetic surfactant action and/or natural microbial degradation. Such an approach might contribute to the reduction in consumption of synthetic surfactants in remediation. These results indicate the potential of the approach under controlled conditions and motivate further evaluation for real remediation scenarios.

Negative interactions between humans and large carnivores represent one of the main challenges for the conservation of these species due to the social conflict they can generate. In the case of brown bears (Ursus arctos), these interactions include visits of bears to human settlements, a type of event increasingly reported in recent years and often associated with conflicts. In this study, we collected 73 events of bear visits to human settlements between 2009 and 2021 in the Cantabrian population. These events were mainly caused by young individuals, occurring mostly at night and during the summer, when bears were primarily attracted by fruit trees available in human settlements. The affected settlements were located in areas of high habitat quality, close to breeding cores, and with a high intensity of bear damage. Within these areas, human settlements with bear visits differed from nearby ones by having a larger perimeter, a shorter distance to forest patches, and greater surrounding terrain ruggedness. Our study provides a basis for understanding the patterns and drivers of these particular human-large carnivore interactions and offers valuable insights to update and improve management strategies aimed at preventing such events, mitigating associated conflicts and promoting successful coexistence.

Although Streptococcus bovis/equinus complex (SBSEC) lysogens are prevalent in the rumen, studies on prophages experimentally induced from these strains are limited. Herein, we screened inducible prophages from ruminant-derived SBSEC strains, including the newly reported S. ruminicola, leading to the characterization of a representative temperate phage. We successfully induced a temperate phage (vB_SbS-proRumen) from S. ruminicola KCCM 90354, which has a broad host range, capable of lysing several SBSEC strains and other lactic acid bacteria. The vB_SbS-proRumen belongs to the Siphovirus, characterized by a short latent period, high burst size, and stability across pH and temperature conditions typical of subacute ruminal acidosis. The phage also demonstrates potent anti-biofilm activity. The vB_SbS-proRumen has a 38,092 bp double-stranded DNA genome with 58 predicted open reading frames, sharing high similarity and conserved genetic organization with other previously predicted SBSEC prophages. This study provides valuable insights into the diversity and plasticity of SBSEC phages.