Search Results (6,058)

Low-permeability reservoirs have poor reservoir properties and are difficult to develop by conventional water flooding. CO₂ flooding can significantly improve oil recovery while achieving carbon storage, and is widely recognized as an effective solution for the development of low-permeability oil reservoirs. In order to address the lack of a comparative quantitative analysis of the tradeoff between oil recovery factor, CO₂ storage rate, and total CO₂ storage volume for the main injection modes in low-permeability reservoirs, this study systematically evaluated the performance of CO₂-enhanced oil recovery (EOR) and geological storage under different pressures and injection modes through core flooding experiments. The results indicate that displacement pressure and injection strategy significantly influence the CO₂ flooding performance. Continuous miscible flooding (30 MPa) substantially reduced the displacement pressure differential (maximum 6.1 MPa) and achieved the highest oil recovery (78.96%) and the greatest CO₂ storage capacity (5916 cm³). Miscible WAG flooding effectively delayed gas breakthrough (extended to 1.90 pore volumes), homogenized the displacement front, and yielded the best overall outcome: the highest ultimate oil recovery (83.8%) coupled with the optimal CO₂ storage rate (89.1%). The study further reveals that the pre-breakthrough stage is critical for contributing to oil recovery and achieving efficient storage, regardless of the injection modes. These findings clarify the technical characteristics and applicable conditions of different injection modes, providing crucial theoretical insights and practical guidance for optimizing CO₂ EOR and storage projects in low-permeability reservoirs. Full article

The fish liver, as the main detoxification organ, is highly susceptible to xenobiotic exposure, often resulting in various hepatopathies. The cytochrome P450 system plays a central role in xenobiotic metabolism, with cytochrome P450 reductase (CYPOR) supplying the electrons required for CYP enzyme activity. This study aimed to evaluate the relationship between the ecological state of a reservoir and fish health, including CYPOR levels, through hematological, bacteriological, and histological analyses. Samples of water and fish were collected from 12 littoral sites of Lake Ladoga. A total of 1360 specimens of fish from carp (Cyprinidae) and perch (Percidae) families were examined. For histological examination and CYPOR level determination, we selected 40 specimens using a blind randomization method. This sample size was sufficient for statistical analyses. Hematological smears were stained with azure eosin; bacteriological cultures were grown on multiple media; liver samples were stained with hematoxylin and eosin and Sudan III. CYPOR levels in liver homogenates were measured by ELISA-test. Physical and hydrochemical analyses indicated a high pollution level in the littoral zones. Isolated bacterial species were non-pathogenic but exhibited broad antibiotic resistance. Hematological evaluation revealed erythrocyte vacuolization and anisocytosis. Histological analysis showed marked fatty degeneration in hepatocytes, indicating toxic damage. CYPOR concentrations ranged from 0.3–0.4 ng/mL in healthy fish to 5–6 ng/mL in exposed specimens, showing strong correlation between environmental influence and enzyme activity. These findings demonstrate the potential of CYPOR as a sensitive biomarker for biomonitoring programs. The integrated methodological approach provides a model for assessing aquatic ecosystem health and identifying zones requiring priority remediation. Full article

This study provides a practice-oriented sensitivity analysis of DeePC for pressure management in water distribution systems. Two public benchmark systems were used, Fossolo (simpler) and Modena (more complex). Each run fixed a monitored node and pressure reference, applied the same randomized identification phase followed by closed-loop control, and quantified performance by the mean absolute error (MAE) of the node pressure relative to the reference value. To better characterize closed-loop behavior beyond MAE, we additionally report (i) the maximum deviation from the reference over the control window and (ii) a valve actuation effort metric, normalized to enable fair comparison across different numbers of valves and, where relevant, different control update rates. Motivated by the need for practical guidance on how hydraulic boundary conditions and algorithmic choices shape DeePC performance in complex water networks, we examined four factors: (1) placement of an additional internal PRV, supplementing the reservoir-outlet PRVs; (2) the control time step $(\Delta t)$; (3) a uniform reservoir-head offset $(\Delta h)$; and (4) DeePC regularization weights ${(\lambda }_g,{\lambda }_u,{\lambda }_y)$. Results show strong location sensitivity, in Fossolo, topologically closer placements tended to lower MAE, with exceptions; the baseline MAE with only the inlet PRV was 3.35 [m], defined as a DeePC run with no additions, no extra valve, and no changes to reservoir head, time step, or regularization weights. Several added-valve locations improved the MAE (i.e., reduced it) below this level, whereas poor choices increased the error up to ~8.5 [m]. In Modena, 54 candidate pipes were tested, the baseline MAE was 2.19 [m], and the best candidate (Pipe 312) achieved 2.02 [m], while pipes adjacent to the monitored node did not outperform the baseline. Decreasing $\Delta t$ across nine tested values consistently reduced MAE, with an approximately linear trend over the tested range, maximum deviation was unchanged (7.8 [m]) across all $\Delta t$ cases, and actuation effort decreased with shorter steps after normalization. Changing reservoir head had a pronounced effect: positive offsets improved tracking toward a floor of ≈0.49 [m] around $\Delta h$ ≈ +30 [m], whereas negative offsets (below the reference) degraded performance. Tuning of regularization weights produced a modest spread (≈0.1 [m]) relative to other factors, and the best tested combination (λy, λg, λu) = (10², 10⁻³, 10⁻²) yielded MAE ≈ 2.11 [m], while actuation effort was more sensitive to the regularization choice than MAE/max deviation. We conclude that baseline system calibration, especially reservoir heads, is essential before running DeePC to avoid biased or artificially bounded outcomes, and that for large systems an external optimization (e.g., a genetic-algorithm search) is advisable to identify beneficial PRV locations. Full article

As a potential strategic resource of critical metals, deep-sea cobalt-rich crusts represent one of the most promising metal reservoirs within oceanic seamount systems, and their metallogenic mechanism constitutes a frontier topic in deep-sea geoscience research. This review focuses on the cobalt-rich crusts from the Magellan Seamount region in the northwestern Pacific and synthesizes existing geological, mineralogical, and geochemical studies to systematically elucidate their mineralization processes and metal enrichment mechanisms from a microstructural perspective, with particular emphasis on cobalt enrichment and its controlling factors. Based on published observations and experimental evidence, the formation of cobalt-rich crusts is divided into three stages: (1) Mn/Fe colloid formation—At the chemical interface between oxygen-rich bottom water and the oxygen minimum zone (OMZ), Mn²⁺ and Fe²⁺ are oxidized to form hydrated oxide colloids such as δ-MnO₂ and Fe(OH)₃. (2) Key metal adsorption—Colloidal particles adsorb metal ions such as Co²⁺, Ni²⁺, and Cu²⁺ through surface complexation and oxidation–substitution reactions, among which Co²⁺ is further oxidized to Co³⁺ and stably incorporated into MnO₆ octahedral vacancies. (3) Colloid deposition and mineralization—Mn–Fe colloids aggregate, dehydrate, and cement on the exposed seamount bedrock surface to form layered cobalt-rich crusts. This process is dominated by the Fe/Mn redox cycle, representing a continuous evolution from colloidal reactions to solid-phase mineral formation. Biological processes play a crucial catalytic role in the microstructural evolution of the crusts. Mn-oxidizing bacteria and extracellular polymeric substances (EPS) accelerate Mn oxidation, regulate mineral-oriented growth, and enhance particle cementation, thereby significantly improving the oxidation and adsorption efficiency of metal ions. Tectonic and paleoceanographic evolution, seamount topography, and the circulation of Antarctic Bottom Water jointly control the metallogenic environment and metal sources, while crystal defects, redox gradients, and biological activity collectively drive metal enrichment. This review establishes a conceptual framework of a multi-level metallogenic model linking macroscopic oceanic circulation and geological evolution with microscopic chemical and biological processes, providing a theoretical basis for the exploration, prediction, and sustainable development of potential cobalt-rich crust deposits. Full article

Landslide dams, typically composed of newly deposited, loose, and heterogeneous materials, are highly susceptible to failure induced by overtopping and seepage, particularly under extreme hydrological conditions. Accurate prediction of such breaching processes is essential for flood risk management and emergency response, yet existing models generally consider only a single failure mechanism. This study develops a mathematical model to simulate landslide dam breaching under the coupled action of overtopping and seepage erosion. The model integrates surface erosion and internal erosion processes within a unified framework and employs a stable time-stepping numerical scheme. Application to three real-world landslide dam cases demonstrates that the model successfully reproduces key breaching characteristics across overtopping-only, seepage-only, and coupled erosion scenarios. The simulated breach hydrographs, reservoir water levels, and breach geometries show good agreement with field observations, with peak outflow and breach timing predicted with errors generally within approximately 5%. Sensitivity analysis further indicates that the model is robust to geometric uncertainties, as variations in breach outcomes remain smaller than the imposed parameter perturbations. These results confirm that explicitly accounting for the coupled interaction between overtopping and seepage significantly improves the representation of complex breaching processes. The proposed model therefore provides a reliable computational tool for analyzing landslide dam failures and supports more accurate hazard assessment under multi-mechanism erosion conditions. Full article

Antibiotic feeding in shrimp farming is an optional practice conducted with the aim of preventing and controlling bacterial diseases. However, the administration of antibiotics can disrupt the microbiota of both shrimp and surrounding environment, potentially compromising host health. Given the limited effective antibiotic options in aquaculture, it is crucial to evaluate the effects of florfenicol (FF) on the intestinal health of shrimp and the associated microbial communities. This study first investigated the impact of FF on the intestinal structure of Penaeus vannamei over two feeding durations (5 and 10 days), each followed by a 10-day basal diet recovery period. Simultaneously, variations in microbial communities and antibiotic resistance genes (ARGs) in both the intestine and rearing water were explored. The results showed that intestinal damage was aggravated with the extension of FF duration and gradually recovered after FF withdrawal. Significant changes in microbial composition and β-diversity were observed in both the rearing water and intestine following FF feeding. Extending the FF treatment to 10 days led to a reduced abundance of Rhodobacteraceae and an increased abundance of Flavobacteriaceae and Vibrionaceae in the intestine after 10 days of feeding the basic diet, which may pose a potential risk to shrimp health. Based on correlation analysis of ARGs, microbial communities and pathogenic bacteria, we speculated that rearing water may serve as a reservoir for ARGs dissemination compared to the shrimp intestine. These findings are of great importance for assessing the impact of administration duration under the FF therapeutic dose and highlight the potential risks associated with its overuse in shrimp farming. Full article

This study investigates the application of nanofluid (iNanoW)–polymer binary flooding system to enhance oil recovery efficiency in medium-to-high permeability reservoirs. Traditional polymer flooding technologies still have the potential for further improvement in these types of reservoirs. Therefore, this study combines iNanoW with the polymer flooding system to examine its effects on the rheological properties, injectability, interfacial performance, sweep volume, and recovery factor of the polymer solution. Experimental results show that iNanoW significantly improves the injectability of the polymer solution. The introduction of iNanoW reduces the size of polymer aggregates, as demonstrated by aggregate size and rheological performance experiments. Power-law model analysis reveals that the flow behavior of the polymer solution is further improved with the introduction of iNanoW, manifested by weakened shear-thinning behavior, reduced viscosity, and optimized flowability, which in turn helps to improve oil recovery efficiency. Moreover, iNanoW interacts with polymer molecules, lowering the surface tension and enhancing wettability, thereby improving oil–water separation efficiency. Core flooding experiments show that the introduction of iNanoW significantly increases sweep volume, particularly in medium- and small-pore spaces, where oil recovery efficiencies reached 57.97% and 61.54%, respectively. These results indicate that iNanoW not only optimizes the rheological properties of the polymer solution but also improves fluid distribution during the flooding process, significantly enhancing the overall oil recovery performance. This study provides a new approach to optimizing polymer flooding technology and highlights the potential of iNanoW in improving oil recovery efficiency. Full article

An explicit coupled two-dimensional (2D) hydromechanical model (HMM) that can simulate discontinuous features in the foundation, as well as the effects of grout curtains and drainage systems, is employed to evaluate the influence of key parameters such as dam height, foundation behaviour, joint patterns, joint stiffness and strength, hydraulic apertures, and grout curtain permeability. A parametric sensitive study using four gravity dams, and a real case study of an operating dam are presented. The results presented show that dam height influences the relationship between water level in the reservoir and drain discharges, with higher dams showing more pronounced curved nonlinearity. The strength properties of the concrete–rock interface are also shown to have a meaningful influence on the HM response, especially for an elastic foundation and for higher dams, showing the need to properly characterize this interface through in situ testing. The joint aperture at nominal zero stress is shown to be the parameter with the most significant effect on the HM response. The results also show that a progressive degradation scenario of the concrete–rock interface or of the grout curtain permeability is easier to identify through the hydraulic measurements than in the mechanical displacement field. Full article

Cool roof and green roof have been acknowledged as effective heat mitigation strategies for fighting against the urban heat island (UHI). However, empirical data in hot–humid climate are still insufficient. Experimental conventional, cool and green roofs (three types) were established to comprehensively investigate the thermal performances in Hong Kong under typical summer conditions, as retrofitting strategies for an office building. The holistic vertical thermal behavior was investigated. The comparative cooling potentials were assessed. The results reveal a “vertical thermal sequence” in peak temperatures of each substrate layer for the conventional, cool and green roofs on a sunny day. However, local reversion in the thermal sequence may occur on a rainy day. Green roof-plot C (GR_C) demonstrates the highest thermal damping effect, followed by plot B (GR_B), A (GR_A) and the cool roof (CR) in summer. On a sunny day, the thermal dampening effectiveness of the substrates in the three green roofs is consistent: drainage > soil > water reservoir > root barrier. The holistic vertical thermal profiling was constructed in a high-rise office context in Hong Kong. The diurnal temperature profiles indicate all roof systems could effectively attenuate the temperature fluctuations. The daily maximum surface temperature reduction (SDMR) was introduced for cooling potential characterization of the cool roof and green roofs with multiple vegetation types. On a sunny day, the cool roof and green roofs all showed significant cooling potential. SDMR on the concrete tile of the best performing system was GR_C (26 °C), followed by GR_B (22.4 °C), GR_A (20.7 °C) and CR (13.3 °C), respectively. The SDMR on the ceiling ranked as GR_C, GR_B, GR_A and CR, with 2.9 °C, 2.4 °C, 2.1 °C and 2.1 °C, separately. On a rainy day, the cooling effect was still present but greatly diminished. A critical insight of a “warming effect at the ceiling” of the green roof was revealed. This research offers critical insights for unlocking rooftop cooling potential, endorsing cool roof and green roof as pivotal solutions for sustainable urban environments. Full article

In soils, it is key to not simply determine the behavior of the major elements but also understand the fate of trace and ultra-trace elements that can often have disproportionate effects on these complex systems. Soils, including agricultural soils, constitute a reservoir of nanoparticles and natural colloids of multiple origins. Nonetheless, only limited information is available on the concentrations and fate of nanoparticles in soils, due largely to the difficulty of distinguishing anthropogenically generated particles from the complex soil matrices in which they are found. Bulk measurements are often unable to quantify the key contributions of trace pollutants (i.e., needle in a haystack); however, single particle techniques have recently become available for studying complex agricultural systems, including soils. For example, the characterization of engineered nanoparticles or incidentally generated particulate pollutants within a natural soil or sediment is now possible using techniques such as single particle inductively coupled plasma mass spectrometry (SP-ICP-MS). Nonetheless, in order to exploit the single particle techniques, it is first necessary to representatively sample the soils. The approach presented here has been designed to help better understand the impact of incidental and engineered nanoparticles on agricultural soils. In this study, we examine two approaches for extracting colloidal particles (CP) from soils in order to facilitate their characterization by single particle inductively coupled plasma mass spectrometry using a sector field- (SP-ICP-SF-MS) and time-of-flight- (SP-ICP-ToF-MS) based instruments. A novel sampling methodology consisting of an ultrasound-assisted continuous-flow extraction (USCFE) was developed and compared to a commonly used batch extraction procedure. Metal containing colloidal particles (M–CP) were quantified and characterized following their extraction in ultrapure water and tetrasodium pyrophosphate (TSPP). At least five successive extraction cycles of 18 h each were required to optimally extract Si–CP (ca. 6 × 10¹⁵ kg⁻¹) using the batch extraction approach, whereas similarly high numbers of CP could be extracted by USCFE in about 3 h. The combined use of continuous flow, ultrasound and TSPP improved the sampling of colloidal particles and nanoparticles from an agricultural soil. Due to its higher sensitivity, SP-ICP-SF-MS was used to measure the smallest detectable M–CP in the soil extracts. SP-ICP-ToF-MS was used to determine the multi-elemental composition of the extracted colloidal particles. Full article

This analysis examines long-term changes in water levels of the Mead and Glen Canyon reservoirs on the Colorado River. Both reservoirs display clear declining trends in water levels, particularly after 2003. The causes include a combination of climate change, megadrought, increased water consumption, and alterations in the hydrological regime. Lake Mead exhibits a stronger and more concerning decline than Lake Powell, including extreme drought conditions over the past three years. The Rescaled Adjusted Partial Sums (RAPS) analysis identifies three statistically distinct subperiods, with an unambiguous decline in the most recent period. The day-to-day (DTD) method indicates reduced day-to-day water level variability in Lake Mead following the commissioning of the Powell reservoir, confirming its regulating influence. The Standardized Hydrological Index (SHI) indicates an accelerating intensification of drought conditions over the past 20 years. Regression analysis confirms a strong relationship between the water levels of the two reservoirs, along with significantly increased water losses in the more recent period. The literature suggests that climate projections are highly unfavorable, with further reductions in Colorado River discharge expected. The study underscores the urgent need to adapt water-management policies and align consumption with the new hydrological realities. Full article

This study examines the hydroclimatic controls on reservoir storage dynamics in the Sinni River basin (southern Italy), with a specific focus on the Monte Cotugno dam—the largest earth-fill reservoir in Europe. Using monthly precipitation data (2000–2024) from eight gauges and standardized indicators (SPI at multiple timescales and SRI for storage), we apply robust trend, correlation, autocorrelation, and causality analyses, supported by advanced preprocessing (TFPW), to disentangle climatic influences from anthropogenic pressures. Results show a statistically significant and persistent decline in the SRI series, indicating progressive storage depletion, despite stationary or slightly positive trends in precipitation at annual and hydrologically relevant timescales. These findings highlight the dominant role of cumulative operational losses and systemic inefficiencies—rather than sustained climatic drying—as primary drivers of reservoir decline. Granger causality and lagged-correlation analyses reveal that multi-month to annual precipitation anomalies (SPI-3, SPI-6, SPI-12) exert the strongest influence on storage variations, yet the basin’s ability to convert rainfall into effective reservoir supply is severely constrained by infrastructural and management limitations. The study underscores the urgent need to integrate climate-based monitoring with infrastructural modernization and governance reforms to address the combined climatic and anthropogenic pressures increasingly affecting Mediterranean water systems. Full article

The Wenchang Oilfield’s high-porosity and high-permeability reservoirs are planned to be developed using synthetic-based drilling fluids. However, the induced reservoir damage problems caused by existing synthetic-based drilling fluids in high-porosity and high-permeability reservoirs are still unclear. Currently, through the analysis of reservoir core porosity and permeability characteristics, physical and chemical property analysis, reservoir sensitivity evaluation, and solid-phase and filtrate invasion experiments, the mechanism of reservoir damage is systematically explored, and a synthetic-based drilling fluid specifically for high-porosity and high-permeability reservoirs is developed to reduce reservoir damage. The results show that the average pore radius of this reservoir is 29.4 μm, with well-developed pores and strong permeability; the mineral composition is mainly quartz (with an average content of 55.6%), and the clay mineral content is 21.5%. It has water-sensitive, salt-sensitive, and stress-sensitive damage characteristics. Filter fluid invasion and solid-phase blockage are the core factors causing reservoir damage. Based on its damage mechanism, through the optimization of the plug-forming agent formula and the selection of a sealing agent, a low-harm synthetic-based drilling fluid (hereinafter referred to as KS-9) was developed. Performance evaluation shows that the KS-9 drilling fluid maintains stable rheology after 110 °C/16 h thermal rolling, with an upper temperature limit of 150 °C, and can resist 10% NaCl, 1% CaCl₂, and 8% inferior soil pollution; in the core contamination experiment, its static permeability recovery value exceeds 88%, and it has good reservoir protection performance, which can provide technical support for the safe drilling and completion of high-porosity and high-permeability reservoirs in the Wenchang Oilfield. Full article

Campylobacter is a leading foodborne bacterial pathogen, and poultry production is a major reservoir contributing to human exposure. Reducing Campylobacter at farm level is therefore critical to limit downstream contamination. This systematic review and meta-analysis aimed to identify and quantitively summarise the current interventions and control measures applied in poultry farms to control the contamination and bird colonisation by Campylobacter. The Scopus electronic database was accessed to collect primary research articles that focused on observational studies and in vivo experiments, reporting results on Campylobacter concentrations or prevalence in both non-intervened and intervened groups. A total of 4080 studies were reviewed, from which 112 were selected and included in the meta-analysis according to predefined criteria, yielding 1467 observations. Meta-regression models were adjusted to the full data set and by intervention strategy based on the type of outcome measure (i.e., concentration and prevalence). In general terms, the results reveal that the effectiveness to reduce Campylobacter colonisation vary among interventions. A highly significant effect (p < 0.001) was observed in interventions such as organic acids, bacteriophages, plant extracts, probiotics, and organic iron complexes added to feed or drinking water; although drinking water was proven to be a more effective means of administration than feed for extracts and organic acids. In contrast, interventions such as chemical treatments, routine cleaning and disinfection, and vaccination showed both lower and more heterogeneous effects on Campylobacter loads. Vaccination effects were demonstrated to be driven by route and schedule, with intramuscular administration, longer vaccination periods and sufficient time before slaughter linked to greater reduction in Campylobacter colonisation. Probiotics, plant extracts and routine cleaning and disinfection were associated with lower Campylobacter prevalence in flocks. Meta-regression models consistently showed that the interventions were proven more effective when the sample analysed was caecal contents in comparison to faeces (p < 0.001). Overall, the findings of this meta-analysis study emphasise the application of a multi-barrier approach that combines targeted interventions with robust biosecurity and hygiene measures in order to reduce Campylobacter levels in poultry farms. Full article

The aim of this study was to determine the factors that influence eutrophication. The factors causing eutrophication are widely known, but identifying the primary threat for a specific water body remains challenging. The study objects were the warm monomictic urban Dal Lake in Kashmir, India, and the artificial dam reservoir Dobczyce in Poland. Data analysis methods, including multiple regression and artificial neural networks (NNET and NeuralNet) from the R package [ver. 4.5.2], were used. Regarding Dal Lake, the factor most influencing the trophic change was total nitrogen. In contrast, for the Dobczyce dam reservoir, water temperature was the dominant factor. Although the regression method did not provide clear results, neural networks enabled the identification of the limiting factors; therefore, the proposed approach may be useful for determining the factors limiting the eutrophication process. The core novelty of this research lies in demonstrating the potential of artificial neural networks to identify key factors causing eutrophication, particularly under conditions of limited data. Full article