Search Results (255)

Plastic waste presents a significant environmental and public health concern in Malawi, where rapid urban growth, limited waste collection services, and informal disposal practices contribute to persistent plastic waste hotspots. In Lilongwe City, the waste collection rate has been reported ranges from 10% to 30%. This means that out of the 500 to 600 tons of municipal solid waste produced each day, only about 50 to 150 tons are collected daily. These hotspots occur in settings such as drains, markets, settlement edges, riverbanks, and lakeshore environments. They intensify health-relevant exposure pathways by encouraging stagnant water, increasing flood risk, facilitating open burning, and supporting the formation of plastisphere biofilms that can contain pathogenic and antimicrobial resistant organisms. This research synthesises evidence on the main sources of plastic waste in Malawi, the mechanisms of leakage across different environments, and the associated health implications. It uses a scoping approach aligned with PRISMA-ScR guidance and is informed by the UK Research and Innovation (UKRI) funded Sustainable Plastic Attitudes to benefit Communities and their Environments (SPACES project), which highlights the influence of behavioural, governance, and environmental factors on plastic pollution. A two phase, risk-based decision framework to support targeted management of plastic waste hotspots is described. Phase 1 focuses on rapid harm reduction through the identification and ranking of hotspots according to risk severity, spatial extent, and feasibility, guiding timely interventions such as drain clearance, waste capture, and temporary stabilisation. Phase 2 addresses longer term prevention by tackling upstream drivers through policy measures, improved services, reuse and reduction schemes, and community engagement. The framework has been developed using evidence from Malawi; however, its methodology could be applied to other low- and middle-income countries that experience similar constraints and exposure pathways. The framework offers a transparent and practical tool for decision makers seeking to allocate limited resources effectively while reducing environmental and health risks associated with plastic waste. Full article

To clarify the oil–gas multiphase flow behavior of natural gas/CO₂ composite flooding in the dual-medium system of the BZ26-6 fractured reservoir, systematic oil–gas relative permeability experiments were conducted under reservoir temperature and pressure conditions. Using the steady-state method, the effects of core type, gas composition, and reservoir pressure on relative permeability behavior were investigated. The results show that the relative permeability curves are characterized by relatively high oil-phase permeability and low gas-phase permeability. Increasing the CO₂ fraction generally enhances oil mobilization and displacement efficiency, whereas the two-phase co-flow zone may reach an optimum at an intermediate CO₂ fraction, depending on the core structure. Specifically, with increasing CO₂ fraction, displacement efficiency increased from 37.05% to 43.70% in fractured metamorphic cores and from 60.74% to 64.63% in fractured carbonate cores. In contrast, decreasing reservoir pressure may induce stress-sensitive fracture compression, narrow the co-flow zone, and reduce flow capacity. Oil–gas two-phase flow behavior is strongly controlled by reservoir structure, with fractured carbonate cores exhibiting higher displacement efficiency and a wider co-flow region than fractured metamorphic cores. Within the scope of this study, a CO₂ fraction of 40% appears to be a comparatively favorable composite-gas composition when both displacement performance and gas-source economics are considered. Full article

To address the lack of systematic quantitative characterization of oil bank dynamic evolution and unclear dominant controlling factors in polymer flooding, this study combines reservoir numerical simulation with Python-based quantitative analysis and a machine learning framework (random forest + SHAP). We established 1D and 2D reservoir models: the 1D model develops a precise quantitative characterization method for oil bank width (defined by front/rear edge saturation offsets Pf < 1.0% and Pb < 1.0%, fitted with a cubic polynomial, R² > 0.95) and height (derived from optimal oil saturation difference time curves and integral calculation); the 2D model investigates the regulatory mechanism of reservoir heterogeneity. Based on 15,000 sets of physically consistent simulation data, the random forest model achieves high prediction accuracy (R² = 0.98). Sensitivity analysis reveals that main flow direction permeability, reservoir temperature, and water-phase exponent (nw) of the Corey model are the dominant controlling parameters, exhibiting substantially higher sensitivity than polymer adsorption capacity and residual resistance coefficient. The oil bank height shows a negative correlation with the first two parameters, while it displays a peak-type variation with the water-phase exponent. Under heterogeneous conditions, permeability anisotropy amplifies the regulatory effect of relative permeability exponents, leading to unbalanced oil bank migration (quantified by front ratio R). This study breaks through the limitations of traditional qualitative characterization, elucidates the spatiotemporal evolution laws and heterogeneous regulatory mechanisms of the oil bank, and provides reliable theoretical and dataset support for optimizing polymer flooding schemes. Full article

Baiyangdian Lake, the largest freshwater lake in North China, plays a critical role in the ecological security of the Beijing–Tianjin–Hebei urban agglomeration. This study conducted systematic monitoring of Baiyangdian Lake from April 2023 to November 2024. Utilizing the Trophic State Index (TSI) and principal component analysis (PCA), we elucidated the impact mechanisms of extreme precipitation events on the water quality of shallow lakes. The results indicate that: (1) During the study period, Baiyangdian Lake exhibited moderate to severe eutrophication. The average total nitrogen (TN) concentration was 2.13 mg/L, exceeding the Class V threshold of the national surface water quality standard. The average total phosphorus (TP) concentration was 0.05 mg/L, far surpassing the recognized eutrophication threshold for freshwater lakes. (2) The average TSI was 49.6 ± 4.0, indicating the lake is in a transitional state from mesotrophy to eutrophy, with 64% of sampling sites classified as eutrophic. Nitrogen was identified as the primary limiting nutrient. (3) The 2023 extreme precipitation event exerted a significant three-phase impact on water quality: “dilution–legacy–restoration”. A clear dilution effect was observed from the pre-flood to the flood period (TN decreased from 1.52 to 1.04 mg/L). A pronounced legacy effect emerged post-flood, with the TN concentration sharply increasing to 4.22 mg/L in September 2023, the highest value recorded during the study. (4) PCA identified two major pollution sources: agricultural non-point source pollution (PC2, contribution: 25.4%) and domestic sewage/livestock farming (PC1, contribution: 27.6%). Correlation analysis further revealed that the flood event significantly altered the intrinsic relationships among parameters like nitrogen and phosphorus, reinforcing the dominance of agricultural non-point source pollution. (5) Source analysis suggests that external inputs are the primary contributors, while the internal loading from sediments is relatively limited. This study enhances the understanding of how shallow lakes respond to extreme climatic events and provides a scientific basis for lake management in the Beijing–Tianjin–Hebei region. Full article

Precipitation variability in the VMD is a critical determinant of agricultural productivity, freshwater availability, and flood and drought dynamics in one of Southeast Asia’s most climate-vulnerable regions. Teleconnections between PPTA and three dominant climate modes (Niño 3.4, DMI and PDO) were quantified at ten meteorological stations from 1981 to 2025 using Pearson lag-correlation and WTC. ENSO is identified as the primary interannual driver, exhibiting a peak negative correlation at a lag of two months (r = −0.304, p < 0.001; 9.2% variance explained). The IOD exerts a secondary, delayed influence, peaking at lags of 11 to 12 months (r = 0.186, p < 0.001; 3.5% variance). The PDO functions as a persistent decadal modulator: positive phases suppress annual precipitation by 4.6%, while negative phases enhance it by 14.5% relative to the long-term mean (6.4% variance). WTC analysis reveals non-stationary coherence at 2–5 year (ENSO) and 8–16 year (PDO) periodicities. Compound El Niño and positive PDO events result in the most severe precipitation deficits, with non-linear responses during strong ENSO phases. These results establish a multi-index teleconnection framework that supports seasonal drought early warning and climate-adaptive water resource management in the VMD. Full article

Polymer microsphere flooding is an effective enhanced oil recovery (EOR) technology. Its primary mechanism is characterized by a dynamic cycle of “migration, plugging, breakthrough, and remigration”, which enables effective in-depth profile control and selective plugging. However, constructing accurate mathematical models and obtaining stable numerical solutions for this process remain challenging. Based on the black-oil framework, a three-phase, five-component mathematical model is developed for water-microsphere dispersed system, including oil, gas, water phases and two microsphere components (pre-swollen and post-swollen), and accounting for swelling kinetics, adsorption, and water phase permeability reduction. The model is numerically solved using a fully implicit finite-difference scheme, and validated by numerical tests and a field-scale application. The numerical simulation results demonstrated an overall agreement rate of approximately 85% with experimental data. Mechanistic comparisons indicated that polymer microsphere flooding significantly improves sweep efficiency and oil recovery. Field-scale application further showed that polymer microsphere flooding, compared with conventional water flooding, increases the recovery factor by 3.49 percentage points, reduces the maximum water cut by about 9.34 percentage points, and raises the average daily oil production rate over the entire development period by 7.5 m³. The proposed model can provide theoretical basis for the field application of polymer microsphere flooding for in-depth profile control. Full article

Rainfall prediction is essential for the enhanced understanding of several issues related to water resources and agriculture, such as flood and drought alerts and flood management. Neural network models are frequently used due to their capability of effectively handling large datasets and addressing the non-stationarity of rainfall data series, resulting in better accuracy and affordable solutions. However, further study is necessary to comprehend the dynamic nature and extreme events of rainfall. Therefore, we implemented a novel wavelet Fourier-enhanced network (W-FENet) that included a Fourier enhancement module (FEMEX) and an improved U-Net mechanism to strengthen the predictive accuracy of daily rainfall. The adopted U-Net structure facilitated efficient multiscale feature extraction and preservation of temporal rainfall information through encoder–decoder connections and residual learning. The results of the developed models for one-day-ahead rainfall prediction were evaluated against two traditional neural network models, i.e., artificial neural networks and long short-term memory networks. Mongla, being a coastal station and having a highly non-linear rainfall pattern, operated by the Bangladesh Meteorological Department, was selected as the study area. Four preprocessing techniques were incorporated to enhance the robustness of the models: empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), variational mode decomposition (VMD), and successive variational mode decomposition (SVMD). The SVMD-enhanced W-FENet model (abbreviated as W5) demonstrated significant improvements over existing literature with RMSE = 2.226 mm, MAE = 1.131 mm, PCC = 0.988, NSE = 0.974, and WI = 0.993 at the testing phase. Full article

Drought–flood abrupt alternation (DFAA) is a typical compound hydroclimatic extreme process and has important implications for regional water resources regulation, agricultural production, and ecological stability. However, existing studies have mainly focused on event identification and frequency variation, while lacking a systematic investigation of the directional differences between drought-to-flood (DF) and flood-to-drought (FD) events in terms of process structure, cumulative effects, and spatial hazard patterns. Based on daily precipitation data from 1960 to 2024, this study identified DFAA events in the Yellow River Basin by combining the standardized weighted average precipitation (SWAP) index with run theory, and analyzed the asymmetric characteristics of DF and FD events from the perspectives of event frequency, phase duration, abrupt-transition characteristics, cumulative severity, and integrated hazard. The results show that: (1) the frequency of DFAA events in the Yellow River Basin exhibited pronounced spatial heterogeneity, with an overall pattern of being higher in the middle reaches and lower in the upper and lower reaches. The frequency of DF events was generally higher than that of FD events, and their spatial distribution was also more continuous. No significant long-term trend was detected in the annual frequency, although clear interdecadal variability was observed, characterized by a transition from relatively low-frequency periods to medium- and high-frequency periods. (2) DF and FD events exhibited stable asymmetry in process structure. The abrupt-transition duration of DF events was mainly concentrated within 1–2 days, whereas that of FD events was mainly concentrated within 3–5 days. The two event types had comparable pre-transition durations, but DF events tended to shift more rapidly and were followed by a longer-lasting flood phase. (3) The differences between the two event types in terms of instantaneous intensity were relatively limited, whereas clearer divergence was observed in cumulative severity, with DF events showing greater overall severity than FD events. This indicates that the directional difference is manifested primarily in cumulative process effects rather than in the magnitude at a single moment. (4) The comprehensive hazard index (CHI) revealed that the northern and central-eastern parts of the middle reaches of the Yellow River Basin were the main hotspots of DFAA hazard. Among them, high-hazard areas of DF events were more extensive, whereas FD hazards were characterized more by localized intensification. These findings indicate that within the identification framework adopted here, DFAA in the Yellow River Basin is characterized not only by rapid dry–wet transitions, but also by clear directional differences between DF and FD in process structure and hazard pattern. This study can provide a scientific reference for the monitoring, early warning, and zonal hazard prevention of DFAA in the basin. Full article

Low-permeability reservoirs at the high-water-cut stage commonly suffer from dominant water channel development, poor sweep of weakly connected zones, and inefficient mobilization of remaining oil. Existing profile control or oil displacement agents can improve either flow diversion or microscopic oil displacement, but their single-agent evaluation does not fully explain the coupled process of sweep expansion and remaining oil mobilization. To address this issue, this study focuses on a previously optimized HK-0417/ALT-603 composite system and investigates its synergistic behavior at pore, core, and well group scales. Microscopic visualization displacement experiments were used to identify streamline redistribution and remaining oil evolution. Natural core experiments were conducted to evaluate injectivity adaptability and plugging persistence. Under slug injection conditions, the Box–Behnken design was employed to optimize the injection parameters. Finally, the field pilot response was analyzed based on production data from test wells in the Changqing Oilfield. The results show that the combination system simultaneously achieves streamline expansion and residual oil reduction: the injected fluid is redistributed toward weakly swept zones, large continuous oil bodies are fragmented and dispersed, and both sweep efficiency and oil displacement efficiency are superior to those of individual agents. Natural core experiments indicate that the injection pressure difference is generally controllable in cores with permeabilities ranging from 1.76 to 7.02 mD, and the plugging rate during subsequent water flooding reaches 75.47–80.54%. Response surface optimization yields the following optimal parameter combination: profile control slug volume = 0.41 pore volume (PV), oil displacement slug volume = 0.61 PV, injection rate = 0.19 mL/min, with a corresponding predicted enhanced oil recovery (EOR) of 18.52%. In the field pilot, the cumulative injection volumes of the two injectors are 41,898 kg and 61,472 kg, respectively. The injection pressure in the well group increases from 5.8 MPa to 7.0 MPa, the comprehensive water cut decreases from 90.6% to 85.3%, and the monthly decline rate is reduced from 0.5% to 0.2%. The proposed system mainly acts by increasing flow resistance and redirecting flow in high-water-cut channels, while it enhances oil detachment through interfacial tension reduction in oil-bearing pores. After optimizing the slug parameters, the field pilot exhibits a clear phased response and promising application potential. Full article

Based on monthly meteorological observations from 57 stations in Jiangsu Province during 1961–2022, the Standardized Precipitation Evapotranspiration Index (SPEI) was calculated to characterize regional dry–wet variability. Empirical Orthogonal Function (EOF) analysis was applied to extract the dominant spatially coherent dry–wet modes, and cross-wavelet analysis was further employed to examine, in the time–frequency domain, the mode-specific responses to multiscale climate drivers, including the El Niño–Southern Oscillation (ENSO), Sunspot Number (SSN), Arctic Oscillation (AO), and Pacific Decadal Oscillation (PDO). The results show that dry–wet variability in Jiangsu Province is primarily organized by a regionally coherent mode (EOF1, explaining 56.3% of the total variance) and a north–south dipole mode (EOF2, explaining 17.8%), with the zero-value line of EOF2 closely aligned with the Huaihe River–Subei Irrigation Canal climatic transition zone. The temporal coefficient of EOF1 (PC1) exhibits a significant regime shift around 2013, followed by a pronounced wetting trend across the entire region. This change may reflect recent hydroclimatic adjustments in the study area, although the present study does not attempt a formal attribution of the respective thermal and precipitation contributions. In contrast, the temporal coefficient of EOF2 (PC2) undergoes an abrupt change around 1980, indicating a transition of the spatial dry–wet pattern from “southern drought–northern flood” to “southern flood–northern drought,” broadly consistent with an interdecadal climatic transition. Cross-wavelet analysis further reveals that PC1 is closely associated with ENSO at interannual timescales, with a lag of approximately 4–6 months, while its long-term variability shows time–frequency coherence with SSN. PC2 also exhibits time–frequency coherence with SSN at longer timescales, with an apparent phase transition around the 1980s; however, this low-frequency signal should be interpreted cautiously because the underlying physical mechanism remains uncertain. Overall, this study shows that dry–wet variability in Jiangsu Province is organized by two leading spatial modes with distinct temporal evolution and scale-dependent climate linkages. These findings provide new evidence for understanding hydroclimatic variability in monsoon transition zones and offer a basis for spatially differentiated drought–flood risk assessment. Full article

Global climate change continues to intensify, leading to an increase in extreme meteorological disasters characterized by high intensity, frequency, and extensive impact. Chinese cities are facing increasingly severe flood disaster risks. As the fundamental unit of the urban system, scientifically quantifying a community’s post-disaster recovery capacity provides a crucial basis for formulating disaster prevention and mitigation strategies. Existing research has largely focused on either quantitative resilience assessment of communities or the functional recovery of specific systems within communities, falling short of meeting the quantitative needs for assessing community functional recovery after flood disasters. Given this, this paper aims to construct a community functional recovery model based on different land use types to precisely quantify the recovery trajectory of community functions. First, the MIKE 21 two-dimensional hydrodynamic model is employed to simulate 100-year and 200-year flood scenarios, obtaining dynamic inundation data at the community scale. Subsequently, a semi-Markov process is adopted to model the recovery of individual buildings, with the aggregated building functions within the community summarized to derive building recovery curves. A road network topology model is constructed using the Space L method, and network global efficiency is applied to quantify community road functionality. Green space functional loss is quantified based on the percentage of inundated areas. Finally, calculation is performed based on the proposed dual-layer computational framework consisting of a connectivity layer and a functional layer, and the overall community functional recovery curve after the disaster is generated, thereby achieving precise quantification of the recovery process. The research findings indicate that increased disaster intensity significantly amplifies functional losses and recovery delays. Concurrently, distinct land use types exert markedly different impacts on community recovery. This study quantitatively reveals the phased dominant roles of various land use types throughout the community recovery process, providing a scientific basis for formulating phased, prioritized resilience enhancement strategies. Full article

Considering escalating global climate change, flood disaster risk assessment for architectural heritage must evolve from static models toward dynamic adaptive systems. This paper proposes a dynamic evaluation model based on the Full-Life-Cycle perspective, dividing disaster progression into three phases: pre-disaster, during-disaster, and post-disaster. This system constructs a dual-track indicator system encompassing Exposure and Vulnerability. By integrating the CRITIC objective weighting method with the G1 subjective ranking approach, the model enables dynamic weight adjustment according to disaster phase. A case study of 392 cultural heritage sites in Beijing reveals that during the disaster phase, 20 sites experienced a risk level increase in two or more tiers, with 13.7% directly entering high-risk status. This finding demonstrates the spatiotemporal evolution of flood risks. The weight for Road Network Density exhibited a substantial increase from 0.046 pre-disaster to 0.153 post-disaster, a 169.5% rise, underscoring its dynamic responsiveness. The findings demonstrate that the proposed model is effective in identifying high-risk heritage sites and dynamically capturing key targets experiencing rapid risk escalation within the disaster chain. These results provide quantitative evidence to support the implementation of phased targeted protection measures and emergency decision-making. Full article

Screw compressors are critical equipment in oil and gas production and transportation, where efficiency losses caused by rotor geometry, inlet pressure pulsations, and harsh climatic conditions can accumulate into substantial annual energy penalties and reliability degradation. This study provides a quantitative assessment of these coupled effects within a unified multiphysics framework that combines time-accurate transient CFD simulations based on a fixed Cartesian immersed-boundary formulation with a climate-calibrated offline physics-based digital twin—functioning as a digital shadow with one-way data flow from archival SCADA records—a reduced-order seasonal model with no real-time updating, calibrated against a full calendar year of SCADA records and validated against a held-out cold-season dataset (October–December 2022, T_amb = −15 to +8 °C); summer-period predictions rely on calibrated extrapolation beyond the validation window—an integration not previously demonstrated for oil-flooded screw compressors. Two rotor profile configurations (Type A and Type B) were analyzed to quantify geometry-driven differences in static pressure distribution, leakage tendency, and pulsation sensitivity. Transient suction conditions were modeled using harmonic and quasi-random inlet pressure disturbances to evaluate pressure amplification, phase lag, leakage intensification, and efficiency degradation. Seasonal performance was assessed by integrating temperature-dependent gas properties, oil viscosity behavior, and external heat transfer into an annual climatic load framework. The results show that inlet oscillations are amplified inside the chambers (pressure amplification factor П_p ≈ 1.95; П_p up to 2.3 under quasi-random excitation), reducing mass flow and volumetric efficiency by 8–10% and decreasing polytropic efficiency from 0.78 to 0.69–0.71, while increasing leakage by up to 27% and raising peak contact pressures to 167–171 MPa. Seasonal variability (+30 to −30 °C) increased suction density by 38% but raised drive power by ~9% due to viscosity-driven mechanical losses, producing an energy penalty up to 10.8% and an estimated annual additional consumption of approximately 186 MWh per compressor, decomposed as: cold-season contribution ~113 MWh (±10 MWh, directly field-validated against October–December 2022 SCADA data) and summer-season contribution ~51 MWh (calibrated extrapolation; additional uncertainty unquantified and not included in the ±10 MWh bound). The full annual figure of 186 MWh should be interpreted as a model-based estimate rather than a fully validated result. These findings demonstrate that rotor design optimization and mitigation of nonstationary suction effects, coupled with climate-aware offline physics-based digital shadow operation, represent high-priority levers for improving efficiency and reducing energy penalties in field conditions; reliability implications require further validation against summer-season field measurements. Full article

An extreme rainfall event that occurred from 16 to 18 December 2021 along the coastal regions of Peninsular Malaysia (PM) caused widespread flooding and substantial socioeconomic impacts. This study investigates the mechanisms leading to this event, focusing on the roles of climatic phenomena and local terrains. Two atmospheric interactions play key roles in triggering the event. Firstly, a strong cold surge (CS) associated with the East Asian winter monsoon (EAWM) interacted with the easterly surge over the southern South China Sea, leading to the formation of Borneo vortex. Secondly, a strong northeasterly and CS largely contributed to enhancing and transporting the vortex towards the PM and across the Titiwangsa mountain ranges. The phase change of the Indian Ocean Dipole (IOD) facilitated the eastward propagation of the vortex. Sumatra and PM terrains significantly modulated vortex evolution and moisture convergence over the Strait of Malacca. These findings are analyzed to shed light on interactions between large-scale climate drivers and localized terrain in generating extreme rainfall, emphasizing the necessity of multi-scale analysis for model accuracy. Full article

The boreal summer intraseasonal oscillation (BSISO) over the western North Pacific (WNP) exhibits significant phase asymmetry, but a systematic classification of its asymmetric modes and their regional climatic impacts remains insufficiently explored. This study introduces an objective index to quantify the asymmetry in BSISO wet phase evolution. Combined with event life cycle duration, we classify WNP BSISO events into three distinct types: a short-lived Symmetric Pattern that resembles the canonical northwestward-propagating high-frequency BSISO, and two long-lived asymmetric patterns—Asymmetric Pattern I (rapid development/slow decay) and Asymmetric Pattern II (slow development/rapid decay). Both asymmetric patterns are dominated by the low-frequency BSISO component and propagate northward; their contrasting asymmetries arise from differences in the coupling timing of a transient high-frequency signal. These BSISO types exert distinct impacts on summer precipitation over eastern China. The Symmetric Pattern causes brief, alternating anomalies. However, asymmetric modes lead to longer-lasting precipitation issues. Pattern I triggers sudden drought-to-flood shifts that pose high risks, while Pattern II moves through phases more gradually. Our objective classification of asymmetric BSISO modes and revelation of their distinct rainfall impacts together provide a physical framework for refining subseasonal forecasts over East Asia. Full article