Search Results (761)

Because dust-emission processes driven by local, small-scale winds (e.g., terrain-induced winds) are difficult to accurately capture with mesoscale or larger-scale predictive models, this study employed a CFD-Lagrangian particle-tracking approach to numerically simulate near-surface dust release and transport under different atmospheric stability conditions in the same local flow field. The novelty of this work was the integration of MOST-based stable/neutral/unstable inflow construction with Lagrangian particle tracking, enabling a consistent comparison of stability effects within one framework. This framework is useful for assessing local blowing-sand impacts on short-range receptors. A near-surface source term was specified for PM10-class mineral dust, and particles were emitted using a vertically exponential allocation. Simulations were conducted over a kilometer-scale flow domain containing an idealized cosine hill, and the low-level concentration patterns and dispersion-height variations in the resulting dust cloud were analyzed. Compared with neutral conditions, stable stratification produced higher near-surface concentrations and a lower dispersion height, whereas unstable stratification yielded lower near-surface concentrations and a higher dispersion height; as the $\left|L\right|$ increased, the unstable cases gradually approached the neutral state. The influence of reference wind speed exhibited clear stability dependence: under stable conditions, stronger winds intensified the buoyancy-related suppression of dust dispersion, while under unstable conditions, stronger winds inhibited the vertical spreading of the dust cloud. In addition, reduced air density representative of plateau environments resulted in lower dust-cloud concentrations and higher dispersion heights. These findings highlight the coupled effects of stratification and wind speed on near-field dust dispersion and provide a reference for assessing local dust emissions over complex terrain. Full article

This study investigates how geopolitical risk shaped the green economic efficiency (GEE) of 19 countries in the G20 group from 2000 to 2022. Using the Super-SBM model, we construct a cross-country measure of GEE and empirically examine both its determinants and underlying mechanisms. The results show that rising geopolitical risk significantly undermines GEE, indicating that external uncertainty disrupts countries’ ability to balance economic growth with environmental performance. Mechanism analysis reveals that geopolitical tensions heighten energy security concerns, leading to increased fossil fuel consumption, and trigger exchange rate depreciation to decrease green economic efficiency. Moreover, foreign direct investment mitigates the adverse effects of geopolitical risk by facilitating technology spillovers and capital inflows. Moreover, geopolitical risks have different impacts on the efficiency of a country’s green economy, varying across levels such as the country’s economic development level, resource endowment, and trade openness. The findings highlight geopolitical risk as a constraint on global green transition. Policymakers should strengthen energy source diversity, stabilize exchange rate environments, and promote FDI to enhance national resilience. Building institutional capacity is essential in sustaining green economic efficiency under rising geopolitical uncertainty. Full article

Regulatory bodies have observed an increase in environmental issues due to firms’ interactions with the environment. Nonetheless, reconciliation actions are emerging, driven by the pursuit of sustainable development goals. This study investigated the impact of financial development and foreign direct investment on ecological footprints in sub-Saharan African nations, while examining the mediating role of regulatory quality and control for corruption. The research was motivated by the growing environmental degradation in the region amid growing capital inflows and financial market expansion. Using panel data of 18 sub-Saharan African countries between 1996 and 2023, sourced from the World Bank database and World Governance Indicators, we employed an Autoregressive Distributed Lag model to assess the short- and long-run relationships among ecological footprint, financial development, foreign direct investment, and key institutional factors. Results from the baseline model show that financial development significantly increases ecological footprints, while the effect of foreign direct investments is insignificant in the absence of institutional factors. However, when mediating variables are introduced, foreign direct investment significantly worsens ecological footprint, and regulatory quality and control for corruption show strong moderating effects, confirming the pollution haven hypothesis. Also, all control variables (trade openness, gross domestic product per capita, government expenditure, and population density) show significant outcomes with environmental sustainability. The findings underscore the importance of institutional factors in shaping sustainable foreign direct investment flows and financial systems. These research findings offer policy pathways for aligning investment strategies with sustainability goals in sub-Saharan Africa. Recommendations include strengthening the nation’s institutional framework, linking foreign direct investment to environmental compliance and promoting green finance policies across the region. Full article

Water resources management in arid and semi-arid regions has become increasingly challenging due to climate change impacts and upstream water policies, particularly for strategic reservoirs. This study evaluates the applicability of the HEC-HMS model for simulating inflow hydrographs and supporting reservoir operation in data-scarce arid environments, focusing on Haditha Reservoir, the only major dam on the Euphrates River within Iraqi territory. An integrated hydro-meteorological and GIS-based framework was developed using 20 years of data (2004–2024), incorporating basin characteristics and reservoir operation records into the HEC-HMS model. Rainfall–runoff processes were simulated using SCS-based methods and routing techniques, followed by calibration and validation against observed inflows. The results demonstrated satisfactory model performance, with an accurate reproduction of inflow hydrographs during both calibration and validation periods. Subsequently, three reservoir operation scenarios were developed and compared with the actual operating policy (outflow curve operation, outflow structure routing operation and rule-based operation scenarios). The rule-based operation scenario showed superior performance by maintaining higher reservoir storage and water levels during dry periods compared to the existing operation, despite higher supply deficits. Overall, the findings confirm that the HEC-HMS model can be reliably applied as a decision-support tool for evaluating reservoir operation in arid and semi-arid regions under water scarcity conditions. Full article

Agricultural transboundary water pollution induced by inter-regional trade poses a complex and pressing challenge for environmental governance. This study integrates an agricultural water pollutant emission inventory, multi-regional input–output model, responsibility-sharing framework, and ecological compensation scheme to establish the collaborative control of agriculture water pollution embodied in China’s inter-provincial trade. The findings reveal, firstly, that inter-provincial agricultural trade led to significant transfers of agricultural water pollution, predominantly flowing from economically developed provinces to less developed provinces, reflecting a mismatch between economic gains and environmental costs. Specifically, Gansu and Qinghai bear the largest agricultural water pollution impact (2.15 Kt and 3.25 Kt, respectively), while it is still a loss in terms of economic net benefits (0.21 trillion and 0.06 trillion yuan, respectively). Secondly, the economic benefit responsibility-sharing shows that for most provinces, responsibility lies between production- and consumption-based accounting and provides a feasible pathway for responsibility sharing. Third, economically developed provinces like Beijing, Jiangsu, and Zhejiang bear the largest compensation liabilities to others, with 1.60 Kt, 0.73 Kt, and 0.54 Kt, respectively. Conversely, provinces including Qinghai, Gansu, and Jiangxi require the greatest compensation inflows, at 2.55 Kt, 0.62 Kt, and 0.34 Kt, respectively. Finally, the maximum acceptable payment value for compensating provinces and the minimum acceptable compensation value for recipient provinces are identified. Our study elucidates the inter-provincial disparities in agricultural water pollution burdens and economic benefits, establishing a quantitative foundation for optimizing responsibility-sharing and compensation strategies in China, which is crucial for fostering regional cooperation in water pollution control. Full article

This paper investigates the determinants of tourism in selected Asian economies over the period 1995–2024, employing the Augmented Mean Group (AMG) estimator to account for cross-sectional dependence, unobserved common factors, and heterogeneous country-specific dynamics. As a robustness check, method of moments quantile regressions (MMQRs) are applied to examine how the effects of GDP, consumer prices, foreign direct investment (FDI), trade openness, and institutional quality vary across the distribution of tourism inflows. The results indicate that GDP consistently promotes tourist arrivals, particularly in countries with lower to median tourism inflows, while higher consumer prices reduce tourism demand across all quantiles. FDI and trade openness positively influence tourism, with FDI’s impact amplified in countries with stronger institutional quality. The MMQR analysis further highlights substantial heterogeneity: emerging economies benefit more from FDI and institutional reforms, whereas advanced economies rely primarily on GDP growth, trade integration, and high-quality tourism services. Overall, the findings underscore the complementary roles of macroeconomic fundamentals, foreign investment, trade, and governance in supporting sustainable long-run tourism growth in Asia, while demonstrating the value of distributional analysis for capturing heterogeneous effects. Full article

Tunnel construction in karst aquifers can substantially alter groundwater flow systems. In this study, a three-dimensional groundwater flow model based on MODFLOW-CFP was developed to simulate the Pingyanggai synclinal karst system in Chongqing, China, incorporating dynamic tunnel excavation and lining processes. Under natural conditions, groundwater recharge is approximately 4.8 × 10⁴ m³/d and is primarily balanced by discharge to the Yanmenkou and Miaolongtang underground rivers. Tunnel excavation introduced a new drainage outlet, generating an inflow of about 5.6 × 10⁴ m³/d. The two underground rivers exhibited contrasting responses to excavation. Discharge from the Yanmenkou underground river decreased by approximately 6 × 10³ m³/d (about 30%), indicating strong hydraulic connectivity with the tunnel, whereas the Miaolongtang underground river showed only minor changes. The simulated responses were qualitatively consistent with field observations during key excavation stages. These results demonstrate that tunnel excavation modifies not only the overall groundwater balance but also the internal redistribution of discharge pathways within the karst system, providing a quantitative basis for evaluating tunnel-induced hydrogeological impacts in complex karst environments. Full article

Particulate matter (PM) emissions are common in technological processes, and effective mitigation requires gas pre-treatment before high-efficiency filtration to reduce fine and ultrafine PM that are particularly dangerous to the human health. This study evaluates a multichannel electric field manipulator (agglomerator) as a flow pre-treatment stage and investigates the aerodynamic conditions that govern particle–gas flow distribution and variation in trajectories and dynamics at different flow rates. These factors provide meaningful assumptions about the possible behavior of particles in the flow, and they are critical for optimizing an agglomeration and its intensity. Such phenomena can have an impact on the probability of agglomeration in the manipulator channels, i.e., the adherence of small particles into larger ones, and this allows for improving the design and operating conditions of the apparatus. Gas flow velocities and pressure were analyzed experimentally at various cross-sectional points in the inlet and outlet ducts at inflow rates of 3.4 L/s and 50 L/s. The static inlet pressure of the manipulator ranged from 8 Pa to 178 Pa. This study provides new insights into flow pre-treatment using the electric field mechanism in a multichannel modular apparatus and provides a reasonable understanding of the necessary characteristics of gas flow distribution to support subsequent improvements targeting higher agglomeration. Full article

The Three Gorges Reservoir (TGR) in China is one of the world’s largest hydropower projects. Interval inflow, originating from ungauged areas between the upstream gauging control stations (Zhutuo, Beibei, Wulong) and the TGR dam site, is a critical component of total reservoir inflow, but its hydrological characteristics have not been fully clarified. The accurate estimation and prediction of interval inflow are essential for reservoir safety and flood control operations. Using daily hydrological data from 2009 to 2017, we propose an integrated analytical framework combining (i) flow travel time estimation using cross-correlation analysis, (ii) multi-scale statistical characterization, and (iii) K-means clustering with bootstrap validation and algorithm comparison. This framework systematically identified hydrological regimes of interval inflow and their associated flood control risks. The key findings are as follows. (1) The optimal flow travel time from the upstream gauging stations to the dam site is 1 day (correlation coefficient $\rho =0.9809,p<0.001$), and it remains stable across different flow regimes. (2) The interval inflow exhibited a highly right-skewed distribution (mean 1279 m³/s, standard deviation 1651 m³/s) and contributed on average 10.1% to the total inflow. The contribution ratio exhibited an inverted U-shaped relationship with increasing total inflow, peaking at 11.4% when the total inflow ($Q$) was 13,014 m³/s. The quartile thresholds were 5788 m³/s, 9575 m³/s, and 16,869 m³/s (corresponding to Q1, Q2, and Q3, respectively), and the 10th and 90th percentiles (P10 and P90) were 4865 m³/s and 24,625 m³/s, respectively. (3) Five distinct hydrological patterns (C1–C5) were successfully identified, among which Cluster C4 (5.7% of days) was defined as the high-impact pattern based on reservoir operational criteria, with a mean $I$ of 6425 m³/s, a mean $R$ of 27.8% (up to 44% in extreme events), a mean flood duration of 5.8 days, a mean flood volume of 36.1 × 10⁸ m³, and a flashiness index of 1.48. (4) C4 is predominantly triggered by localized heavy rainfall, and its flashy nature implies a substantially shorter forecast lead time compared with mainstream-dominated floods, posing major challenges to real-time reservoir operations. This study demonstrates that interval inflow risk is pattern-dependent and that the proposed framework provides a scientific basis for developing pattern-specific reservoir operation strategies. The proposed framework is transferable to other large river-type reservoirs facing similar ungauged interval inflow challenges. Full article

The Prespa Lakes system, shared between Greece, the Republic of North Macedonia, and Albania, forms a significant transboundary, large-scale integrated freshwater ecosystem subject to multiple anthropogenic and natural pressures. This study focuses on the Greek part of the Prespa Lakes system with particular emphasis on the identification of the ecological and hydrological impacts of the contributing stream inflows on the lakes by examining the spatial variability in physicochemical and biological conditions and conducting water balance and isotopic analyses. Based on our results, streams draining into Lesser Prespa Lake exhibited more pronounced hydrological and physicochemical fluctuations than the Agios Germanos River connected to Great Prespa Lake, while ecological status classifications of all studied streams ranged from high to moderate. Furthermore, moderate ecological status conditions (mainly observed at the downstream stations) were closely associated with adjacent anthropogenic pressures, including agricultural drainage, livestock activities, irrigated croplands, and wastewater discharges. In addition, although both lakes were classified as mesotrophic, field data indicated greater transparency loss in Lesser Prespa than in Great Prespa Lake. Regarding the stream influences on Lesser Prespa Lake’s water quality, nutrient loads induced changes in lake concentrations by roughly one month. Total nitrogen showed moderate stream–lake correlations (R = 0.61) and a strong negative correlation for total phosphorus (R = −0.94), suggesting substantial nutrient retention and processes within the lake. Water balance analysis revealed an annual water deficit for both Lesser and Great Prespa, with the latter exhibiting a markedly stronger and systematic long-term decline in water level. In the Lesser Prespa, seasonal fluctuations in water volume were primarily driven by excess rainfall, while stream inflows contributed minimally. Conversely, correlation analysis for Great Prespa identified surface inflow from the Ag. Germanos catchment as the dominant driver of water storage variability, surpassing direct rainfall, with strong correlations in both wet (R = 0.79) and dry (R = 0.88) periods. Isotopic compositions (δ¹⁸O, δ²H) did not differ significantly between the two lakes, indicating common recharge sources and strong evaporative imprints, while stream isotopic signatures highlighted spatial and seasonal variability in hydrological inputs. Seasonal and spatial variations were proved to be strongly influenced by both natural hydrological dynamics and anthropogenic pressures within the basin, while these findings reinforce the importance and the necessity of adopting holistic, cross-border management strategies that maintain the ecological integrity and the long-term sustainability of the Prespa Lakes ecosystem. Full article

Background: In 2016, Charles McMonnies advanced a theory positing that the use of scleral lenses might result in an elevation of intraocular pressure (IOP) due to the compression of the episcleral veins, consequently diminishing the eye’s capacity for draining aqueous humor. Alternative drainage pathways are capable of compensating only for 10–30% of the aqueous humor that requires drainage. Then it remains a quantity of fluid trapped in the anterior chamber. Recent data has demonstrated that the scleral lenses wear results indeed in an augmentation of the anterior chamber volume and a reduction of the iridocorneal angle, concomitant with a compression of Schlemm’s canal. Assuming that aqueous humor production remains constant, this imbalance between inflow and outflow can only lead to an increase in intraocular pressure. Methods: Several studies have attempted to answer this question over the past 10 years. Most authors have encountered the inherent difficulty of measuring IOP while the lens is still in place. Others were performed without waiting for the required time (>4 h of wear) for the lens to exert its maximum compression, thus minimizing their impact. Some attempted to assess IOP via the sclera (pneumotonometry), a technique known to give variable results and hard to reproduce. Ultimately, there are few reliable ways to assess IOP. One of them is by directly observing changes in the optic nerve structure over time. Results: These works indicate that there is indeed a moderate increase (<5 mmHg) in IOP. Could this be causing neuropathy and long-term negative impacts for patients who may be at risk? Based on the clinical experience of those involved in the field for many years, it is unlikely that IOP variations may have an impact on a healthy optic nerve. However, glaucoma patients or those at risk could be adversely affected in the long term. Conclusions: It is still too early to determine, without a doubt, the actual impact of the likely increase in IOP resulting from the structural changes caused by wearing scleral lenses Further work is therefore urgently needed to document these longitudinal changes. Full article

Wakes generated by upstream turbines in an offshore wind farm severely reduce the efficiency and power output of downstream turbines. Wind farm layout optimization offers a way to alleviate these negative impacts, where the main challenge lies in accurate and efficient evaluation across a vast number of potential configurations. Analytical wake models are crucial tools for this optimization, owing to their superb ability to efficiently predict wake distributions. This paper evaluates and discusses recent advances and persistent challenges in analytical wake modelling for layout optimization of wind farms. While the Jensen model remains efficient for discrete searches, the models capturing radial velocity gradients have become a preferred choice for high-fidelity optimization designs. Advanced models show the transition to full wakes to cover near-wake characteristics and complex inflow conditions. Motion corrections and physically based superposition methods improve the performance evaluation of floating offshore wind farms. Multi-objective optimization frameworks balance energy production and fatigue life by the integration of turbulence modelling. However, the increasing scale of modern wind turbines, the dynamic complexity of floating offshore wind farms, the clustering, and the model validation of large-scale wind farms present significant challenges to the applicability of these models. This paper highlights these emerging limitations in optimization problems, clarifying that addressing the gaps in these specific areas is essential for the development of high-fidelity optimizations and the design of future large-scale offshore wind turbine clusters. Full article

Clouds are essential for regulating the hydrological cycle and Earth’s radiation budget, and their fluctuations over the Tibetan Plateau (TP) have a significant effect on both regional climate dynamics and global atmospheric circulation. Using ground-based Vaisala CL51 ceilometer data and Fengyun-4A (FY-4A) satellite observations from October 2020 to June 2022, this study examines cloud occurrence frequency (COF), cloud vertical structure (including cloud base height (CBH), cloud top height (CTH), and cloud layer stratification), and related macroscopic properties over the Large High Altitude Air Shower Observatory (LHAASO). CL51 and FY-4A had cloud occurrence rates of 43.7% and 37.7%, respectively, over the observation period, with a strong correlation coefficient of 0.82. Given the impact of clouds on Cherenkov light observations by the LHAASO Wide Field of view Cherenkov Telescope Array (WFCTA), we specifically evaluated the cloud occurrence during the operational periods of the LHAASO-WFCTA, finding rates of 34.2% (CL51) and 28.0% (FY-4A), with the lowest rates occurring in the early morning. Due to monsoonal moisture inflow and dry northeasterly winds, seasonal COF changes showed clear peaks in summer (78.8%) and minima in winter (24.8%). Seasonal differences existed in the diurnal COF patterns, with nocturnal prominence in summer/autumn and daytime dominance in spring/winter. The CBH showed daily oscillations, peaking at 18:00 (local solar time) and troughing at 08:00 (local solar time), with seasonal CBH minima in summer/autumn and maxima in spring/winter. Low- and mid-level clouds predominated, with clear diurnal cycles: low- and mid-level clouds rose from morning until midday, while high-level clouds appeared after dusk. Vertical cloud structures were predominantly single-layered (81%), with multi-layered complexity peaking in the summer due to convective activity. The CTH distributions showed unimodal patterns in the fall and winter (1.5–3 km), while in the summer, they showed multimodal extents (up to 12 km). These results improve LHAASO-WFCTA observational scheduling, enhance climate model parameterizations, and deepen our understanding of the dynamics of the TP cloud. Full article

Phosphorus enrichment remains a major driver of eutrophication in lake-feeding rivers, yet effective regulation is hindered by insufficient understanding of the spatiotemporal variability and dominant sources of total phosphorus (TP) at the basin scale. The Xiangjiang River, a major inflow to Dongting Lake, provides a representative system for examining TP dynamics in a human-impacted watershed. An interpretable association rule mining framework was applied to multi-source water quality, hydrological, agricultural, and socio-economic data (2020–2024) to characterize TP variation and quantify source contributions. TP concentrations exhibit pronounced seasonal and hydrological variability, with higher levels during spring and the flood season and lower levels during autumn and low-flow periods, together with a longitudinal increasing pattern from upstream to downstream. Quantitative source apportionment indicates that agricultural non-point sources dominate TP contributions at the basin scale, domestic sources provide a stable secondary contribution, and industrial sources exert localized influences. The spatial organization of source contributions closely corresponds to land-use patterns, with relatively consistent source structures among sites despite local heterogeneity. These results demonstrate the utility of an interpretable association rule mining framework for resolving TP source structures in heterogeneous river basins. The proposed framework offers a transferable approach for phosphorus source identification and supports basin-scale nutrient management and targeted control of agricultural non-point source pollution. Full article

Tidal inundation plays a critical role in maintaining the ecosystem services of the Sundarbans mangrove forest. In this study, we configured and calibrated a coupled one-dimensional (1D) river network and two-dimensional (2D) floodplain hydrodynamic model for the Sundarbans in Bangladesh. Model calibration was performed using gauged water levels, inundation maps, and Google Earth (Version 7.3.6) imagery. Using the calibrated model, we assessed potential changes in inundation extent, depth, and duration across the Sundarbans for varying freshwater inflow and tidal height scenarios. Results show variation in inundation extent, depth, and duration spatially and temporarily across the Sundarbans. Inundation is relatively less during February-March (end of the dry season) and high in July-August (mid-wet season). Approximately 3158 km² (85.1%) of the Sundarbans experiences at least one inundation in March, increasing to about 3658 km² (98.6%) in July. Although a large proportion of the Sundarbans inundate during daily tidal cycles, the mean inundation depth remains shallow (0.24 to 0.33 m) due to flat topography. The influence of freshwater inflow on inundations is small (<2%). In contrast, the impacts of tidal magnitude are substantial on both inundation extent and depth. These findings provide valuable insights on inundation dynamics for understanding the hydrological and ecological functioning of the Sundarbans. Full article