Abstract: Per- and polyfluoroalkyl substances (PFAS) represent a diverse group of chemicals widely used in industrial and consumer products due to their unique physicochemical properties. This review critically examines the ecotoxicological profiles of six key PFAS—PFOA, PFOS, PFBA, PFBS, GenX, and ADONA—focusing on their effects on standard aquatic model organisms (Daphnia magna, Raphidocelis subcapitata, and Aliivibrio fischeri). The data highlight that legacy compounds such as PFOA and PFOS generally show greater toxicity, particularly with reproductive and growth endpoints in D. magna and growth inhibition in R. subcapitata, at lower concentrations compared to their short-chain analogues (PFBA, PFBS). GenX and ADONA, introduced as replacements for long-chain PFAS, have been the subject of far fewer studies. Available data, mainly from regulatory sources, suggest lower acute and chronic toxicity for these alternatives under standard test conditions. However, the lack of comprehensive data—especially regarding sub-lethal, chronic, and mixture effects—precludes firm conclusions about their environmental safety. The findings underscore the need for further ecotoxicological research on emerging PFAS and call for integrating bioassays with chemical analyses to better assess risks associated with PFAS mixtures in aquatic ecosystems.

Abstract: This study aimed to evaluate the impact of vineyard cultivation time and the use of metal-based fungicides on the chemical fractions of soil organic matter (SOM), as well as their interactions with Cu, Zn, and Mn in vineyard soils from Southern Brazil with varying histories of fungicide application. Soil samples were collected from vineyards aged 35, 37, and 39 years in the Serra Gaúcha region, and 13, 19, and 36 years in the Campanha Gaúcha. In each region, samples were also collected from a non-anthropized reference area. In the oldest vineyards, sampling was conducted both within and between the planting rows. From the collected soil samples, chemical fractionation of SOM was performed, yielding the following fractions: non-humic substances (nHS), particulate organic matter (POM), fulvic acid (FA), humic acid (HA), and humin (Hu). After this step, Fourier-transform infrared (FTIR) spectra were obtained for the humic acids, from which the aromaticity index (AI) and relative intensities (RI) were calculated. In each SOM fraction, total organic carbon and the concentrations of Cu, Zn, and Mn were determined. Changes in land use influenced the distribution and chemical nature of SOC and its interaction with metals. HA from vineyard soils showed greater humification and aromaticity, while Cu was mainly associated with HA and FA, and Zn and Mn accumulated in the Hu. Over time, vineyard cultivation, especially with cover crop management, contributed to increased SOC stocks, reaching levels comparable to those in native areas.

Abstract: Underground hydrogen storage (UHS) in carbonate and siliceous formations presents a promising solution for managing intermittent renewable energy. However, experimental data on hydrogen-rock interactions under representative subsurface conditions remains limited. This study systematically investigates mineralogical and petrophysical altera-tions in dolomite, calcite-rich limestone, and quartz-dominant siliceous cores subjected to high-pressure hydrogen (100 bar, 70°C, 100 days). Distinct from prior research focused on diffraction peak shifts, our analysis prioritizes quantitative changes in mineral concentra-tion (%) as a direct metric of reactivity and structural integrity, offering more robust in-sights into long-term storage viability. Hydrogen exposure induced significant dolomite dissolution, evidenced by reduced crys-talline content (from 12.20% to 10.53%) and accessory phase loss, indicative of partial de-carbonation and ankerite-like formation via cation exchange. Conversely, limestone ex-hibited more pronounced carbonate reduction (vaterite from 6.05% to 4.82% and calcite from 2.35% to 0%), signaling high reactivity, mineral instability, and potential pore clog-ging from secondary precipitation. In contrast, quartz-rich cores demonstrated exceptional chemical inertness, maintaining consistent mineral concentrations. Furthermore, BET and BJH analyses revealed enhanced porosity and permeability in do-lomite (pore volume increased >10x), while calcite showed declining properties and quartz negligible changes. SEM-EDS supported these trends, detailing Fe migration and textural evolution in dolomite, microfissuring in calcite, and structural preservation in quartz. This research establishes a unique experimental framework for understanding hydrogen–rock interactions under reservoir-relevant conditions. It provides crucial insights into mineralogical compatibility and structural resilience for UHS, identifying dolomite as a highly promising host and highlighting calcitic rocks limitations for long-term hydrogen containment.

Abstract: Mozambique soils are known for an unbalanced agronomic and environmental composition that results in poor agricultural production yields. However, agriculture is the main economic activity of Mozambique, and soils must be characterised for their elemental deficiencies and/or excesses. This paper sampled nine farms from the Manica and Sussundenga districts (Manica province) in three campaigns in 2021/2022, 2022/2023 and 2023/2024 (before and after the rainy seasons). They were subjected to an agronomical and environmental chemical analysis to assess their quality, from the fertility and environmental contamination point of view. A multivariate data analysis methodology was used based on cluster and discriminant analysis. The analysis of 23 agronomical soil variables suggested four clusters of soils characterised by deficiencies and excess elements that must be corrected to improve the yield and quality of agricultural production. Moreover, the multivariate analysis of the metal composition (Ba, Cr, Co, Cu, Pb, Ni, V and Zn) of soil samples from the second campaign and the third campaign, before and after the rainy season, suggested five clusters with pristine composition and with different metal pollutants composition and concentrations. The information obtained in this study allows scientific comprehension of agricultural soil quality, which is crucial for designing agronomic and environmental corrective measures to improve food quality and quantity in the Manica and Sussundenga districts and ensure environmental, social, and economic sustainability.

Abstract: The rich Eocene larger benthic foraminiferal (LBF) assemblages from the vicinity of Verona are well-known long since. However, they are described in detail only from the Ypresian to Bartonian interval. Here, we present the results of our morphometrically based study of Priabonian LBF. The lowermost part of the succession, just above the uppermost occurrence of giant Nummulites (N. biedai) is outcropping on Monte Cavro and contains Heterostegina reticulata multifida and Nummulites hormoensis as major constituents. These taxa clearly determine the earliest Priabonian SBZ 18C shallow benthic zone. Slightly younger strata could be studied in the three studied exposures on the northern side of Castel San Felice. These beds already represent the early Priabonian SBZ 19A Zone based on the first appearing Spiroclypeus sirottii and on the presence of Heterostegina reticulata mossanensis and Nummulites fabianii (replacing H. r. multifida and N. hormoensis, respectively). The most abundant LBF in these beds are the very diverse and well-preserved orthophragmines represented both by family Discocyclinidae (genus Discocyclina and Nemkovella) and Orbitoclypeidae (genus Orbitoclypeus and Asterocyclina). They determine the OZ 14 orthophragminid zone. The distinction of six species of the genus Discocyclina (especially that of D. euaensis from D. dispansa) is discussed in detail. The exposures around Castel San Felice are considered as key localities for the SBZ 19A and OZ 14 Zones containing their key LBF assemblages. Late Lutetian–Priabonian range charts for LBF and separately also for orthophragminid taxa are updated.

Abstract: Detecting surface water beneath vegetation canopies remains a major challenge for widely used water indices, which often underestimate water obscured by vegetation. This limitation is further compounded by the scarcity of reliable in-situ data needed for robust index development and validation. To address this, we introduce a Vegetation-Adjusted Water Index using a logarithmic transformation of the ratio between the Land Surface Water Index (LSWI) and the Enhanced Vegetation Index (EVI), referred to as VAWIlog. This transformation compresses high vegetation values while expanding the range typical of water surfaces, enhancing contrast in mixed land cover areas and improving class separability. The index was developed and validated using in-situ water level measurements, providing a strong empirical basis for detecting surface water under variable vegetation conditions. VAWIlog consistently outperformed established indices for detecting open water, wetlands, and flooded vegetation, demonstrating superior accuracy and overall detection performance. Evaluation against the Dynamic World V1 dataset confirmed its enhanced ability to identify water under vegetation, though some limitations remain in dense forest and open water contexts. Overall, VAWIlog offers a simple yet effective solution for improved surface water mapping in vegetated landscapes. Its compatibility with open-source optical satellite data supports broader applications in irrigation monitoring, and greenhouse gas assessments.

Abstract: Due to the increasingly complicated urban building structure and the rising occurrence of emergent events, the on-duty-to-road processing for an urban fire movement has come up against severe challenges for time response and road intelligence. To achieve this, the paper puts forward a new adaptive diffusion spatiotemporal graph neural network framework based on the NFIRS-PDR (National Fire Event Reporting System-Vehicle Scheduling Record) data, to achieve dynamic optimization of vehicle allocation plans of urban fire incidents. Based on the traditional ST-GCN and DCRNN, the model makes the following key contributions: (1) The dual-channel diffusion module is proposed to simultaneously model the directed traffic flow and regional risk in urban roads. (2) The timing attention gating mechanism is used to dynamically capture the law of the time dependence of sudden fire and the law of high-risk period; (3) The scheduling perception reinforcement feedback mechanism is introduced, a dynamic resource constraint learning path based on the Q-learning constraint is learnt in the training process to enhance the model of the accessibility and coverage of firefighting vehicles. The global graph structure is generated dynamically as a function of road connectivity and fire station arrangement and each node contains local history information of events as well as the regional risk obtained in advance from the NFIRS statistical model. The proposed AD-STGNN model has prominent advantages compared with the existing methods including the ASTGCN, ST-MetaNet and GraphSARL, its reduction rate on average scheduling time is up to 14% ), which can greatly improve the efficiency of emergency response.

Abstract: White rot fungi and soil microbial communities at the hyphosphere influence phosphorus availability through their interactions. However, the mechanisms underlying the effects of different phosphorus forms on polycyclic aromatic hydrocarbons (PAHs) during plant-white rot fungus remediation remain unclear. Thus, this study aimed to investigate the effects of different phosphorus addition forms on soil microbial community diversity during plant-white rot fungus remediation and their correlation with PAH biodegradation through amplicon high-throughput sequencing. Pot experiments were conducted in a greenhouse. Salix viminalis was cultivated under two fungal levels (inoculated and non-inoculated with Crucibulum laeve) and three phosphorus levels (no phosphorus addition, potassium dihydrogen phosphate addition, and calcium phytate addition) to remediate phenanthrene (PHE)-contaminated soil. Among the treatments, two potassium dihydrogen phosphate addition treatments exhibited the highest PHE removal rates (74.0% and 79.4%) on day 60. Inoculation with C. laeve significantly increased the relative abundance of Pseudomonas but antagonized other putative indigenous PAH-degrading taxa. Potassium dihydrogen phosphate addition alleviated the antagonistic effect of C. laeve and indigenous microorganisms and synergistically promoted PHE degradation in soil with C. laeve, whereas calcium phytate addition did not significantly improve soil PHE removal rates. Additionally, the simultaneous phosphorus addition and C. laeve inoculation created a unique microbial community structure that facilitated organic phosphorus activation and accelerated phosphorus turnover. However, PHE degradation varied depending on the phosphorus form. Therefore, the addition of soluble phosphorus should be prioritized over insoluble phosphorus to optimize plant-white rot fungus remediation.

Abstract: Background: Antimicrobial resistance (AMR) is a growing global public health threat, and effective treatment of microbiological waste is essential in preventing the spread of resistance genes into the environment. Autoclaving is commonly used in healthcare and laboratory settings to sterilize microbiological waste, ensuring the destruction of viable bacteria. However, the fate of antimicrobial resistance genes (ARGs), such as blaCTX-M and blaTEM, following autoclaving is not well understood. To fill this critical gap, this study determined the PCR stability of AMR encoding genes from autoclaved microbiological waste in Mwanza, Tanzania. Methods: A laboratory-based experimental study was conducted between May and August 2024 at the Catholic University of Health and Allied Sciences (CUHAS). Standard and resistant E. coli strains carrying blaCTX-M and blaTEM genes were subjected to autoclaving at 121°C and 0.1 MPa for varying duration. Bacterial viability was assessed through sub-culturing on MacConkey agar, while the presence of ARGs was evaluated using multiplex PCR.

Abstract: Some herbicides, such as saflufenacil, can persist as residues in sprayer tanks even after cleaning, causing phytotoxicity in sensitive crops. This study aimed to simulate potential injury caused by saflufenacil residues, applied alone or combined with glyphosate, on soybean. The field experiment was conducted using a randomized complete block design with four replicates. Treatments included glyphosate (1440 g ha-1), eight saflufenacil doses (1.09, 2.17, 4.38, 8.75, 17.50, 35.00, 52.50, and 70.00 g ha-1), each of these saflufenacil doses combined with glyphosate, and a weed-free control, totalling 18 treatments. Phytotoxicity was assessed at 7, 14, 21, 28, and 35 days after treatment (DAT). Physiological parameters were measured at 21 DAT, and grain yield components were evaluated at harvest. Increasing saflufenacil doses caused progressively greater phytotoxicity, both alone (above 4.38 g ha-1) and combined with glyphosate (above 2.17 g ha-1). The highest doses negatively affected soybean physiology and grain yield components. Soybean tolerated up to 2.17 g ha-1 saflufenacil alone and up to 1.09 g ha⁻¹ combined with glyphosate without significant yield loss.

Abstract: The materials typically used for radiation shielding include lead, concrete, and polymers. However, some of these materials can be toxic or very expensive to produce. This raises interest in using more readily available natural materials, such as rocks, as an alternative. In this study, we analyze the radiation shielding efficiency of sandstones. We evaluated different layers of rock and obtained shielding parameters based on the composition of various oxides. The analysis revealed that these layers showed a predominance of silicon and aluminum oxides. Notably, the lowest photon energies (0.015 MeV and 0.1 MeV) displayed significant differences in photon attenuation, as indicated by linear and mass attenuation coefficients. This suggests that the chemical composition of the samples had a considerable impact on their shielding performance. Samples containing higher amounts of heavier elements proved to be more effective at attenuating radiation, efficiently reducing 50% (half-value layer) and 90% (tenth-value layer) of the photons. Additionally, the presence of these heavier elements decreased the production of secondary photons (buildup factor), further enhancing the samples' efficiency in shielding against radiation. Our results indicate that sandstones hold potential for radiation shielding, particularly when they contain higher quantities of heavier elements.

Abstract: Satellite imagery is crucial for monitoring global economic and ecological changes. However, integrating diverse datasets from different satellites is challenging due to differences in sensing technologies, lack of standardized calibration, and instrument hardware drift over time. Converting images from one sensor to another, like from WorldView-3 (WV) to SuperDove (SD), involves spectral band resampling and radiometric intensity scaling. A parametrized convolutional network approach has shown promise in non-linear conversion tasks across sensor domains, but it introduces artefacts when objects are in motion, due to temporal delays between multispectral band acquisitions. This results in spuriously blurred images of moving objects in the converted imagery. To resolve this, we propose an enhanced model, the Physics-Informed Gaussian-Enforced Separated-Band Convolutional Conversion Network (PIGESBCCN), which better accounts for spatial, spectral, and temporal correlations between bands.

Abstract: With an increase in methane quantification requirements and recent developments in technology, quantification of methane emissions from offshore oil and gas production infrastructure has become more important, and studies reporting emissions more numerous. While reported emissions range from those below method quantification limits to thousands of tons of methane per hour, there is currently no clear understanding on what expected emission from offshore facilities should be. To investigate if current methods generate realistic emission estimates, we will create bottom-up models that simulate two prototypical facilities operating in the Gulf of Mexico and compare the calculated emissions to actual emissions reported by published studies. Prototypical facility type 1 are those fixed platforms operating closer to shore in shallower water and comprise typically older, lower-producing platforms with less processing equipment, no compressor, the oil is piped to shore and usually unmanned 24 hours per day. Using the bottom-up model, total emissions from a prototypical facility type 1 are estimated at 9.2 kg CH4 h-1, largest emissions from fugitive emissions, pneumatic controllers and chemical injection pumps, and correspond to a loss of 1.9 % of the average facility production of 480 kg CH4 h-1. Prototypical facility type 2 platforms operate in deeper water, farther from shore, are newer, have higher production rates from more well heads, have more processing equipment, oil storage tanks, compressors and power generation, and are usually manned 24 hours per day. Total emissions from prototypical type 2 facilities are estimated at 42.2 kg CH4 h-1 (loss of 1.2 % of the average facility production) with the largest emissions from the liquid storage tanks, water storage tanks, and compressors. Fugitive emissions are estimated at 23.4 kg CH4 h-1 with 13 fugitive emissions per facility with an average emission rate of 1.8 kg CH4 h-1. The measured average emission from 13 type 1 facilities was 17.6 kg CH4 h-1 with a median production loss estimated at 8 %, 76 % higher than this study’s bottom-up estimate. As there are few moving parts and no storage tanks on type 1 facilities, the largest unknown emission source are fugitives and we therefore suggest that 6 % of production is currently lost as fugitive emissions from type 1 facilities. The measured average emission from 20 type 2 facilities was 35.5 kg CH4 h-1 with a median production loss estimated at 2.4 %, 50% higher than the bottom-up estimate. Using emission factors that consider the long-tail emission distribution in part reconciles the difference between modelled and measured emission estimates but we suggest the current the fugitive emission estimate may be an underestimate and more data on the number and size of fugitive emissions would help to reconcile the modelled and measured emission estimate. We suggest a bottom-up approach that uses production data coupled with facility equipment could be used to identify facilities that have unusually large measured emissions, caused by methodological failure or larger than expected fugitive emissions, which should be targeted for further evaluation resulting in remeasurement or identification of source type (maintenance event or fugitive) so that a more accurate estimates can be made on the absolute emission.

Abstract: Arsenic contamination in groundwater is a significant public health concern, with As(III) posing a greater and more challenging risk than As(V), due to its higher toxicity, mobility, and weaker adsorption affinity. Fe-Mn-based adsorbents offer a promising solution, simultaneously oxidizing As(III) to As(V), enhancing its adsorption. This study evaluates an Fe-Mn nanocomposite across typical batch (20 mg of adsorbent), fixed-bed column (28 g) and pilot-scale (2.5 kg) studies, bridging the gap between laboratory and real-world applications. Batch experiments yielded maximum adsorption capacities of 6.25 mg/g and 4.71 mg/g in synthetic and real groundwater respectively, demonstrating the impact of water matrix on adsorption. Operational constraints and competing anions lead to a lower capacity at the pilot (0.551 mg/g). Good agreement was obtained by the breakthrough curves at the pilot (breakthrough at 475 Bed Volumes) and the fixed-bed column studies (365–587 Bed Volumes) under similar empty bed contact times (EBCT). The Thomas, Adams-Bohart, and Yoon-Nelson models demonstrated that lower flow rates and extended EBCT significantly enhance arsenic removal efficiency, prolonging operational lifespan. Our findings demonstrate the necessity of continuous-flow experiments using real contaminated water sources, and the importance of optimising flow conditions, EBCT and pre-treatment, in order to successfully scale up Fe-Mn-based adsorbents for sustainable arsenic removal.

Abstract: Grassland ecosystems are fundamentally shaped by the complex behaviours of livestock. While most previous studies have monitored grassland health using vegetation indices such as NDVI and LAI, fewer have investigated livestock behaviours as direct drivers of grassland degradation. In particular, the spatial clustering and temporal concentration patterns of livestock behaviours are critical yet underexplored factors that significantly influence grassland ecosystems. This study investigated the spatiotemporal patterns of livestock behaviours under different grazing management systems and grazing-intensity gradients (GIGs) in Wenchang, China, using high-resolution GPS tracking data and machine learning classification. the K-Nearest Neighbours (KNN) model combined with SMOTE-ENN resampling achieved the highest accuracy, with F1-scores of 0.960 and 0.956 for continuous and rotational grazing datasets. Results showed that continuous grazing system failed to mitigate grazing pressure when reduced grazing intensity, as the spatial clustering of livestock behaviours did not decrease accordingly, and the frequency of temporal peaks in grazing behaviour even showed an increasing trend. Conversely, rotational grazing system responded more effectively, as reduced GIGs led to more evenly distributed temporal activity patterns and lower spatial clustering. These findings highlight the importance of incorporating livestock behavioural patterns into grassland monitoring and offer data-driven insights for sustainable grazing management.

Abstract: Although the implementation of the European Union's policies has contributed substan-tially to reducing air pollution in recent years, PM2.5 remains a pollutant that poses sig-nificant risks to the environment and public health. The present study examines the ap-plication of a novel method for assessing the environmental impact and risk associated with this pollutant. The new integrated approach for air quality evaluation and predic-tion of the effects and risk of certain pollutants is based on AOD analysis, considering the AERONET database. For its validation, the new approach was applied based on moni-toring air quality data for two cities in Romania, considering 13 years (from 2011 to 2023) in one case and 12 years (from 2012 to 2023) in the other. The results demonstrated that an AOD risk index can be developed and utilised for air quality evaluation and prediction, enabling the estimation of impacts and risks. In this case, the aerosols measured by AERONET over Cluj-Napoca for 13 years (2011 – 2023) were dominated by the occurrence of a 46% elemental carbon (EC) and organic carbon (OC) mixture, while the measure-ments over Iasi city for 12 years (2012 – 2023) were dominated by the occurrence of 55% EC and OC mixture. The impacts and risks, as calculated by the AOD index for EC, show few significant ones, with an AOD range of 0.88 to 1.05 for Iasi city and 0.73 to 0.88 for Cluj-Napoca.

Abstract: Air pollution and climate change are a growing threat to terrestrial woodland ecosystems. Extensive research in China has focused on single environmental factors, such as ozone, carbon dioxide, and climate change, but the multifactor interactions are poorly known. Here, we coupled the interactions of climate change, elevated CO2 concentration, and increasing O3 into the BEPS_O3 model. The GPP simulated by the BEPS_O3 is verified at site scale by using the eddy covariance (EC) derived GPP data in China. We then investigated the impact of ozone and CO2 fertilization on woodland ecosystem gross primary production（GPP） in the context of climate change during 2001-2020 over China. The results of multi-scenario simulations indicate that the GPP of woodland ecosystems will increase by 1-5% due to elevated CO2. However, increased ozone pollution will result in a GPP loss of approximately 8-9%. In the historical climate, under the combined effects of CO2 and O3, the effect of ozone on GPP will be mitigated by CO2 to 4-7%. In most areas, the effect of ozone on woodland ecosystems is higher than that of CO2 on vegetation photosynthesis, but CO2 gradually counteracts the effect of ozone on the ecosystem. Our simulation study provides a new way of thinking about assessing the interactive responses to climate change, and advances our understanding of the interactions of global change agents over time. In addition, the comparison of individual and combined models will provide an important basis for national emission reduction strategies as well as O3 regulation and climate adaptation in different regions.

Abstract: Honey processing is closely linked to water pollution due to the lack of a specific wastewater treatment. This work presents a sustainable and innovative solution based on two sequential bioprocesses using a real effluent from an Argentine honey-exporting facility. In the first stage, the honey wastewater was enriched with a non-Saccharomyces yeast (Candida ethanolica), isolated and identified from the same effluent. Yeast treatment was carried out in a bioreactor, achieving nearly double the efficiency in total sugar removal compared to the control (native flora). Subsequent clarification with diatomaceous earth reduced optical density (91.6%) and COD (30.9%). In the second stage, secondary sewage effluent, was added to the clarified effluent and inoculated with Chlorella vulgaris under different culture conditions. The best microalgae performance was observed under high light intensity and high inoculum concentration, reaching a fivefold increase in cell density, a specific growth rate of 0.752 d⁻¹, and a doubling time of 0.921 d. Total sugar removal in this stage was under 28%, while cumulative COD removal reached 90% in nine days under both lighting conditions. The synergistic use of complementary microorganisms and different effluents enhances microalgal growth and supports to the overall sustainability of an integrated approach to managing all wastewater streams from honey production.

Abstract: Calcium (Ca²⁺) is an essential nutrient for plants and enhances their resistance to heavy metal stress. This study employed hydroponic experiments to investigate how varying Ca²⁺ levels (0, 0.5, 2, and 5 mM) regulate maize seedling growth, physiological-biochemical traits, and cellular antioxidant defense systems under cadmium (Cd) stress, thereby alleviating Cd toxicity. The results showed that Ca²⁺ supplementation mitigated the inhibitory effects of Cd stress on root length, dry weight, and photosynthetic pigment content. Additionally, Ca²⁺ application increased the activities of superoxide dismutase (SOD) and catalase (CAT), as well as the contents of glutathione (GSH) and ascorbic acid (ASA) in leaves, with maximum increases of 14.9%, 65.39%, 146%, and 135%, respectively, compared to the control (CK). Under Ca²⁺ treatment, peroxidase (POD) activity significantly decreased, with a maximum reduction of 34.38% compared to CK, while malondialdehyde (MDA) content markedly increased, reaching 19.84% higher than CK. Principal component analysis (PCA) revealed that the 5 mM Ca²⁺ treatment achieved the highest composite score, indicating optimal antioxidant capacity in maize seedlings and reduced membrane lipid peroxidation caused by excessive Cd accumulation. This study enhances the understanding of calcium’s role in plant stress responses and provides insights for safe maize production in Cd-contaminated environments.

Abstract: Geological hazards severely constrain urban construction planning and economic development, particularly for large and medium-sized cities. Xi'an City is located in the transitional zone between the Guanzhong Plain and the Qinling Mountains, characterized by complex geological conditions and frequent occurrence of various geological hazards, posing serious threats to regional economic development and the safety of residents' lives and property. Currently, diverse methods and models exist for geological hazard susceptibility assessment. Selecting appropriate evaluation models and assessment factors to conduct geological hazard susceptibility evaluation plays a crucial role in geological hazard risk management and economic development promotion in Xi'an City. Taking geological hazards throughout Xi'an City as the research object, this study analyzed the formation conditions and influencing factors of geological hazards. Via Spearman correlation analysis, appropriate evaluation indicators were selected, and a geological hazard susceptibility assessment system was constructed through the comprehensive application of the combined weighting method and information value model. The main research findings are as follows: (1) A total of 787 geological hazards (hidden danger points) have developed in Xi'an City, predominantly landslides (435 occurrences) and collapses (304 occurrences), distributed in loess landform areas and the Qinling mountainous region, while ground subsidence and ground fissures are mainly distributed in alluvial plain areas; (2) Twelve factors including slope gradient, slope aspect, and surface relief were selected as susceptibility evaluation indicators. The analytic hierarchy process was employed to determine subjective weights, the entropy weight method was used to calculate objective weights, and the distance function method was utilized to combine the two types of weights; (3) Four information value models were established: unweighted, subjective weighted, objective weighted, and combined weighted models. Through verification via hazard point density and ROC curves, the combined weighting information value model demonstrated the highest evaluation accuracy (AUC value of 0.872); (4) The combined weighting information value model was employed to assess geological hazard susceptibility in Xi'an City, resulting in classification into high susceptibility areas (1,305.36 km², accounting for 12.31%), moderate susceptibility areas (1,980.96 km², accounting for 18.68%), low susceptibility areas (835.48 km², accounting for 7.88%), and non-susceptible areas (6,485.72 km², accounting for 61.14%). The study demonstrates that the combined weighting method can overcome the limitations of single weighting approaches, and the evaluation results better conform to the distribution patterns of geological hazards in the study area, providing a scientific basis for geological hazard prevention and control in Xi'an City.