Search Results (599)

Fibrate pharmaceuticals (fibrates), as a widespread class of emerging contaminants, pose potential risks to both ecological systems and human health. The photocatalytic system based on nitrogen (N) and fluorine (F) co-doped TiO₂ nanotube arrays (NF-TNAs) provides a renewable solution for fibrate pharmaceutical removal from water, powered by inexhaustible sunlight. In this study, the degradation of two typical fibrates, i.e., bezafibrate (BZF) and ciprofibrate (CPF), under simulated sunlight irradiation through NF-TNAs were investigated. The photocatalytic degradation of BZF/CPF was achieved through combined radical and non-radical oxidation processes, while the generation and reaction mechanisms of associated reactive oxygen species (ROS) were examined. Electron paramagnetic resonance detection and quenching tests confirmed the existence of h⁺, •OH, O₂^•−, and ¹O₂, with O₂^•− playing the predominant role. The transformation products (TPs) of BZF/CPF were identified through high-resolution mass spectrometry analysis combined with quantum chemical calculations to elucidate the degradation pathways. The influence of co-existing ions and typical natural organic matters (NOM) on BZF/CPF degradation were also tested. Eventually, the ecological risk of BZF/CPF transformation products was assessed through quantitative structure–activity relationship (QSAR) modeling, and the results showed that the proposed photocatalytic system can largely alleviate fibrate toxicity. Full article

The Three Gorges Reservoir Area (TGRA) is an important ecological barrier and cultural intermingling zone in the upper reaches of the Yangtze River, and its traditional villages carry unique information about natural changes and civilisational development, but face the challenges of conservation and development under the impact of modernisation and ecological pressure. This study takes 112 traditional villages in the TGRA that have been included in the protection list as the research objects, aiming to construct a cultural landscape identification framework for the traditional villages in the TGRA. Through field surveys, landscape feature assessments, GIS spatial analysis, and multi-source data analysis, we systematically analyse their cultural landscape type systems and spatial differentiation characteristics, and then reveal their cultural landscape types and spatial differentiation patterns. (1) The results of the study show that the spatial distribution of traditional villages exhibits significant altitude gradient differentiation—the low-altitude area is dominated by traffic and trade villages, the middle-altitude area is dominated by patriarchal manor villages and mountain farming villages, and the high-altitude area is dominated by ethno-cultural and ecologically dependent villages. (2) Slope and direction analyses further reveal that the gently sloping areas are conducive to the development of commercial and agricultural settlements, while the steeply sloping areas strengthen the function of ethnic and cultural defence. The results indicate that topographic conditions drive the synergistic evolution of the human–land system in traditional villages through the mechanisms of agricultural optimisation, trade networks, cultural defence, and ecological adaptation. The study provides a paradigm of “nature–humanities” interaction analysis for the conservation and development of traditional villages in mountainous areas, which is of practical value in coordinating the construction of ecological barriers and the revitalisation of villages in the reservoir area. Full article

The ongoing genetic erosion of natural Prunus armeniaca populations in their native habitats underscores the urgent need for targeted conservation and restoration strategies. This study provides the first comprehensive characterization of P. armeniaca populations in the Almaty region of Kazakhstan, integrating morphological descriptors (46 parameters), molecular markers, geobotanical, and remote sensing analyses. Geobotanical and remote sensing analyses enhanced understanding of accession distribution, geological features, and ecosystem health across sites, while also revealing their vulnerability to various biotic and abiotic threats. Of 111 morphologically classified accessions, 54 were analyzed with 13 simple sequence repeat (SSR) markers and four DNA barcoding regions. Our findings demonstrate the necessity of integrated morphological and molecular analyses to differentiate closely related accessions. Genetic analysis identified 11 distinct populations with high heterozygosity and substantial genetic variability. Eight populations exhibited 100% polymorphism, indicating their potential as sources of adaptive genetic diversity. Cluster analysis grouped populations into three geographic clusters, suggesting limited gene flow across Gorges (features of a mountainous landscape) and greater connectivity within them. These findings underscore the need for site-specific conservation strategies, especially for genetically distinct, isolated populations with unique allelic profiles. This study provides a valuable foundation for prioritizing conservation targets, confirming genetic redundancies, and preserving genetic uniqueness to enhance the efficiency and effectiveness of the future conservation and use of P. armeniaca genetic resources in the region. Full article

Asynchrony between the movement of water and sediment in a reservoir will affect long-term maintenance of the reservoir’s capacity to a certain extent. Based on water and sediment data on the Three Gorges Reservoir (TGR) measured over the years and a river network model, optimization of the dispatching mode of the reservoir’s sand peak process was studied, and the corresponding water and sediment dispatching indicators were provided. The results show that (1) sand peak discharge dispatching of the TGR can be divided roughly into three stages, namely the flood detention period, the sediment transport period, and the sediment discharge period. (2) According to the process of the flood peak and the sand peak, a division method for each period is proposed. (3) A corresponding scheduling index is proposed according to the characteristics of the sand peak process and the needs of flood control scheduling. This research can provide operational indicators for the operation and management of the sediment load in the TGR and also provide technical support for sustainable reservoirs similar to TGR. Full article

Waterborne transportation serves as a critical pillar of trunk-line freight systems, offering unparalleled advantages in transport capacity, energy efficiency, and cost-effectiveness. As cargo throughput demands escalate, optimizing lock capacity becomes imperative. This study investigates ship sinkage dynamics through computational fluid dynamics (CFD) simulations for a representative inland cargo vessel navigating the Three Gorges on the Yangtze River. We develop a predictive sinkage model that integrates four key hydrodynamic parameters: ship velocity, draft, water depth, and bank clearance, applicable to both open shallow water and lockage conditions. The model enables determination of maximum safe drafts for lock transit by analyzing upstream/downstream water levels and corresponding chamber depths. Our results demonstrate the technical feasibility of enhancing single-lock cargo capacity while maintaining safety margins. These findings provide (1) a scientifically grounded framework for draft control optimization, and (2) actionable insights for lock operation management. The study establishes a methodological foundation for balancing navigational safety with growing throughput requirements in constrained waterways. Full article

In the landslide chain from pre-disaster conditions to landslide mitigation and recovery, time is an important factor in understanding the geological hazards process and managing landsides. Static knowledge graphs are unable to capture the temporal dynamics of landslide events. To address this limitation, we propose a systematic framework for constructing a multi-temporal knowledge graph of landslides that integrates multi-source temporal data, enabling the dynamic tracking of landslide processes. Our approach comprises three key steps. First, we summarize domain knowledge and develop a temporal ontology model based on the disaster chain management system. Second, we map heterogeneous datasets (both tabular and textual data) into triples/quadruples and represent them based on the RDF (Resource Description Framework) and quadruple approaches. Finally, we validate the utility of multi-temporal knowledge graphs through multidimensional queries and develop a web interface that allows users to input landslide names to retrieve location and time-axis information. A case study of the Zhangjiawan landslide in the Three Gorges Reservoir Area demonstrates the multi-temporal knowledge graph’s capability to track temporal updates effectively. The query results show that multi-temporal knowledge graphs effectively support multi-temporal queries. This study advances landslide research by combining static knowledge representation with the dynamic evolution of landslides, laying the foundation for hazard forecasting and intelligent early-warning systems. Full article

Early warning systems depend heavily on the accuracy of landslide displacement forecasts. This study focuses on the Bazimen landslide located in the Three Gorges Reservoir region and proposes a hybrid prediction approach combining support vector regression (SVR) and long short-term memory (LSTM) networks. These models are optimized via the K-Nearest Neighbor (KNN) algorithm. Initially, cumulative displacement data were separated into trend and cyclic elements using a smoothing approach. SVR and LSTM were then used to predict the components, and KNN was introduced to optimize input factors and classify the results, improving accuracy. The final KNN-optimized SVR-LSTM model effectively integrates static and dynamic features, addressing limitations of traditional models. The results show that LSTM performs better than SVR, with an RMSE and MAPE of 24.73 mm and 1.87% at monitoring point ZG111, compared to 30.71 mm and 2.15% for SVR. The sequential hybrid model based on KNN-optimized SVR and LSTM achieved the best performance, with an RMSE and MAPE of 23.11 mm and 1.68%, respectively. This integrated model, which combines multiple algorithms, offers improved prediction of landslide displacement and practical value for disaster forecasting in the Three Gorges area. Full article

To investigate the remediation efficiency of different plant species on cadmium (Cd)-contaminated soil, this study conducted a pot experiment with two woody species (Populu adenopoda and Salix babylonica) and two herbaceous species (Artemisia argyi and Amaranthus hypochondriacus). Soils were collected from an abandoned coal mine and adjacent pristine natural areas within the dam-adjacent section of the Three Gorges Reservoir Area to establish three soil treatment groups: unpolluted soil (T1, 0.18 mg·kg⁻¹ Cd), a 1:1 mixture of contaminated and unpolluted soil (T2, 0.35 mg·kg⁻¹ Cd), and contaminated coal mine soil (T3, 0.54 mg·kg⁻¹ Cd). This study aimed to investigate the growth status of plants, Cd accumulation and translocation characteristics, and the relationship between them and soil environmental factors. Woody plants exhibited significant advantages in aboveground biomass accumulation. Under T3 treatment, the Cd extraction amount of S. babylonica (224.93 mg) increased by about 36 times compared to T1, and the extraction efficiency (6.42%) was significantly higher than other species. Among the herbaceous species, A. argyi showed the maximum Cd extraction amount (66.26 mg) and extraction efficiency (3.11%) during T2 treatment. While A. hypochondriacus exhibited a trend of increasing extraction amount but decreasing extraction efficiency with increasing concentration. With the exception of S. babylonica under T1 treatment (BCF = 0.78), the bioconcentration factor was greater than 1 in both woody (BCF = 1.39–6.42) and herbaceous species (BCF = 1.39–3.11). However, herbaceous plants demonstrated significantly higher translocation factors (TF = 1.58–3.43) compared to woody species (TF = 0.31–0.87). There was a significant negative correlation between aboveground phosphorus (P) content and root Cd (p < 0.05), while underground nitrogen (N) content was positively correlated to aboveground Cd content (p < 0.05). Soil total N and available P were significantly positively correlated with plant Cd absorption, whereas total potassium (K) showed a negative correlation. This study demonstrated that woody plants can achieve long-term remediation through biomass advantages, while herbaceous plants, with their high transfer efficiency, are suitable for short-term rotation. In the future, it is suggested to conduct a mixed planting model of woody and herbaceous plants to remediate Cd-contaminated soils in the tailing areas of reservoir areas. This would synergistically leverage the dual advantages of root retention and aboveground removal, enhancing remediation efficiency. Concurrent optimization of soil nutrient management would further improve the Cd remediation efficiency of plants. Full article

This study investigates the dynamic response mechanisms of discharge capacity in the Han River Estuary to hydrological process changes at the Yangtze–Han River confluence. By constructing a one-dimensional hydrodynamic model for the 265 km Xinglong–Hankou reach, we quantitatively decouple the synergistic effects of riverbed scouring (mean annual incision rate: 0.12 m) and Three Gorges Dam (TGD) operation through four orthogonal scenarios. Key findings reveal: (1) Riverbed incision dominates discharge variation (annual mean contribution >84%), enhancing flood conveyance efficiency with a peak flow increase of 21.3 m³/s during July–September; (2) TGD regulation exhibits spatiotemporal intermittency, contributing 25–36% during impoundment periods (September–October) by reducing Yangtze backwater effects; (3) Nonlinear interactions between drivers reconfigure flow paths—antagonism occurs at low confluence ratios (R < 0.15, e.g., Cd increases to 45 under TGD but decreases to 8 under incision), while synergy at high ratios (R > 0.25) reduces Hanchuan Station flow by 13.84 m³/s; (4) The 180–265 km confluence-proximal zone is identified as a sensitive area, where coupled drivers amplify water surface gradients to −1.41 × 10⁻³ m/km (2.3× upstream) and velocity increments to 0.0027 m/s. The proposed “Natural/Anthropogenic Dual-Stressor Framework” elucidates estuary discharge mechanisms under intensive human interference, providing critical insights for flood control and trans-basin water resource management in tide-free estuaries globally. Full article

Clubroot, caused by Plasmodiophora brassicae Woronin, poses a major threat to Chinese cabbage (Brassica rapa subsp. pekinensis) production worldwide, significantly impacting crop yield, quality, and economic value. Biological control represents a promising approach since it is non-toxic and eco-friendly, and it reduces the risk of pathogen resistance development. In this study, our objective was to screen for actinomycetes that can effectively inhibit clubroot. We screened 13 actinomycete strains, identifying 2, XDS3-6 and CD1-1, with substantial in vivo inhibitory effects, achieving infection suppression rates above 64% against P. brassicae. Phylogenetic analysis classified XDS3-6 and CD1-1 as Streptomyces virginiae and Streptomyces cinnamonensis, respectively. Both strains exhibited protease and glucanase production capabilities, essential for pathogenic suppression. Additionally, these strains induced host defense responses, as evidenced by increased jasmonic acid (JA) and salicylic acid (SA) accumulation and elevated activities of defense-related enzymes. Colonization studies of XDS3-6 and CD1-1 mutant strains in cabbage roots indicated sustained root colonization, with peak colony-forming units (CFUs) at 20 days post-inoculation, reaching 11.0 × 10⁴ CFU/g and 8.5 × 10⁴ CFU/g, respectively, and persisting for at least 30 days. Overall, these findings underscore the potential of Streptomyces strains XDS3-6 and CD1-1 as effective biocontrol agents, providing a theoretical foundation for their application in managing clubroot in Chinese cabbage. Full article

The Three Gorges Reservoir Area in China presents a critical conflict between industrial development and ecological conservation. It functions as a key hub for water management, energy production, and shipping, while also serving as a vital zone for ecological and environmental protection. Focusing on Zigui County, this study developed a 16-indicator evaluation system integrating geological, ecological, and socioeconomic factors. It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. The findings indicate the following: (1) The RAGA-PP model outperforms conventional AHP-CV methods in assessing Zigui County’s eco-geological environment, showing superior accuracy (higher Moran’s I) and spatial consistency. (2) Hotspot analysis confirms these results, revealing distinct spatial patterns. (3) From 2000 to 2020, “bad” quality areas decreased from 17.31% to 12.33%, while “moderate” or “better” zones expanded. (4) This improvement reflects favorable natural conditions and reduced human impacts. These trends underscore the effectiveness of China’s ecological civilization policies, which have prioritized sustainable development through targeted environmental governance, afforestation initiatives, and stringent regulations on industrial activities. Full article

Limited research has been conducted on the potential and mechanisms of irrigating Suaeda salsa with wastewater and microalgae to improve saline–alkali land. This study used three irrigation treatments (freshwater, saline wastewater, and saline wastewater with microalgae) to irrigate S. salsa, and microalgae promoted the growth of S. salsa and increased soil nutrient content, increasing available nitrogen (4.85%), available phosphorus (44.51%), and organic carbon (24.05%) while alleviating salt stress through reduced soil salinity (13.52%) and electrical conductivity (21.62%). These changes promoted eutrophic bacteria while inhibiting oligotrophic bacteria. Bacterial community composition exhibited significant variations, primarily driven by soil pH, total nitrogen, and organic carbon content. Notably, rhizosphere bacteria showed enhanced functional capabilities, with increased abundance of salt stress resistance and nitrogen metabolism-related genes compared to original soil, particularly under saline irrigation conditions. Furthermore, microalgae addition enriched nitrogen metabolism-related gene abundance. These findings revealed the potential role of key bacteria in enhancing plant growth and the soil environment and highlighted the potential of applying S. salsa, wastewater, and microalgae for the synergistic improvement of saline–alkali land. Full article

Waterway tunnels, a novel type of infrastructure designed for inland waterways in mountainous gorge regions, have seen rapid development in recent years. However, their unique structural characteristics and specific shipping activities pose significant risks in the event of an accident. To enhance the scientific rigor and efficiency of emergency responses to vessel incidents in tunnels, this study focuses on fire accidents in waterway tunnels. Considering the unique challenges of emergency response in such scenarios, we propose an emergency response framework using Business Process Modeling Notation (BPMN). The framework is mapped into a Petri net model encompassing three key stages: detection and early warning, emergency response actions, and recovery. A Colored Hierarchical Timed Petri Net (CHTPN) emergency response model is then developed based on fire incident data and emergency response time functions. Furthermore, a homomorphic Markov chain is employed to assess the network’s validity and performance. Finally, optimization strategies are proposed to improve the emergency response process. The results indicate that the emergency response network demonstrates strong accessibility, effectively mitigating information bottlenecks in critical stages of the response process. The network provides accurate and rapid decision support for different tunnel ship fire scenarios, efficiently and reasonably allocating emergency resources and response teams, and monitoring the operation of key emergency response stages. This enhances the efficiency of emergency operations and provides robust support for decision-making in waterway tunnel fire emergencies. Full article

With the continuous improvement of reservoir projects and the advancement of digital twin basin initiatives in China, rapidly and accurately generating long-term practical reservoir operation schedules has become a key priority for stakeholders. This study proposes a Theory-guided Long Short-Term Memory (TgLSTM) model to extract optimal reservoir operation rules accurately and reliably. Concretely, TgLSTM integrates data-fitting accuracy with the physical constraints of an operation, e.g., water level constraints and minimal discharge constraints, to address the low credibility often observed in conventional LSTM networks. Using the Three Gorges Reservoir during the dry season as a case study, a multi-year hydrological series optimized by particle swarm optimization (PSO) was used to train the TgLSTM network and derive optimized operation rules. Results show that TgLSTM efficiently generates operation schemes close to the theoretical optimum, achieving power generations of 4.27 × 10¹⁰ kW·h and 4.19 × 10¹⁰ kW·h in two test years, with deviations of only 4.20% and 2.33%, respectively. Compared to traditional LSTM models, TgLSTM is more reliable as it captures key operational characteristics such as terminal water levels and water level fluctuations, maintaining an average ten-day drawdown depth below 1.5 m—significantly lower than the 7 m fluctuations observed with conventional LSTM. Furthermore, comparative analyses against SwR, BP–ANN, and SVM confirm that TgLSTM offers a moderate performance in absolute metrics but is the best to simulate the constrained reservoir operation. Full article

Globally, ecosystems are affected by climate change, human activities, and natural disasters, which impact ecosystem quality and stability. Vegetation plays a crucial role in ecosystem material cycle and energy transformation, making it important to monitor its resilience under disturbance stress. The Critical Slowing Down (CSD) indicates that as ecosystems near collapse, the autocorrelation of lag temporal increases and resilience decreases. We used the lag Temporal Autocorrelation (TAC) of long-term remote sensing Leaf Area Index (LAI) to monitor vegetation resilience in the Three Gorges Reservoir Area (TGRA). The Disturbance Event Model (DEM) was used to validate the CSD. The results showed the following: (1) The eastern TGRA exhibited high and increasing vegetation resilience, while most areas showed a decline. (2) Among the various vegetation types, forests demonstrated higher resilience than other vegetation types. (3) Precipitation, temperature, and soil moisture significantly influenced vegetation resilience dynamics within the TGRA. (4) For model accuracy, the CSD’s results were consistent with the DEM, confirming its applicability in the TGRA. Overall, the CSD when applied to long-term remote sensing data, provided valuable quantitative indicators for vegetation resilience. Furthermore, more CSD-based indicators are needed to analyze vegetation resilience dynamics and better understand the biological processes determining vegetation degradation and restoration. Full article