Search Results (849)

This study focuses on developing a climate-flood model to investigate and interpret the relationship and impact of climate on runoff/flooding at a sub-regional scale using multiple linear regression (MLR) with 30 years of hydro-climatic data for the Cross River Basin, Nigeria. Data were obtained from Nigerian Meteorological Agency (NIMET) for the following climatic parameters: annual average rainfall, maximum and minimum temperatures, humidity, duration of sunlight (sunshine hours), evaporation, wind speed, soil temperature, cloud cover, solar radiation, and atmospheric pressure. These hydro-meteorological data were analysed and used as parameters input to the climate-flood model. Results from multiple regression analyses were used to develop climate-flood models for all the gauge stations in the basin. The findings suggest that at 95% confidence, the climate-flood model was effective in forecasting the annual runoff at all the stations. The findings also identified the climatic parameters that were responsible for 100% of the runoff variability in Calabar (R² = 1.000), 100% the runoff in Uyo (R² = 1.000), 98.8% of the runoff in Ogoja (R² = 0.988), and 99.9% of the runoff in Eket (R² = 0.999). Based on the model, rainfall depth is the only climate parameter that significantly predicts runoff at 95% confidence intervals in Calabar, while in Ogoja, rainfall depth, temperature, and evaporation significantly predict runoff. In Eket, rainfall depth, relative humidity, solar radiation, and soil temperatures are significant predictors of runoff. The model also reveals that rainfall depth and evaporation are significant predictors of runoff in Uyo. The outcome of the study suggests that climate change has impacted runoff and flooding within the Cross River Basin. Full article

Rapid socio-economic development and the impact of human activities have exerted tremendous pressure on the groundwater system of the Dawen River Basin (DRB), the largest tributary in the middle and lower reaches of the Yellow River. Hydrochemical studies on the DRB have largely centered on the upstream Muwen River catchment and downstream Dongping Lake, with some focusing solely on karst groundwater. Basin-wide evaluations suggest good overall groundwater quality, but moderate to severe contamination is confined to the lower Dongping Lake area. The hydrogeologically complex mid-reach, where the Muwen and Chaiwen rivers merge, warrants specific focus. This region, adjacent to populous areas and industrial/agricultural zones, features diverse aquifer systems, necessitating a thorough analysis of its hydrochemistry and origins. This study presents an integrated hydrochemical, isotopic investigation and EWQI evaluation of groundwater quality and formation mechanisms within the multiple groundwater types of the central DRB. Central DRB groundwater has a pH of 7.5–8.2 (avg. 7.8) and TDSs at 450–2420 mg/L (avg. 1075.4 mg/L) and is mainly brackish, with Ca²⁺ as the primary cation (68.3% of total cations) and SO₄²⁻ (33.6%) and NO₃⁻ (28.4%) as key anions. The Piper diagram reveals complex hydrochemical types, primarily HCO₃·SO₄-Ca and SO₄·Cl-Ca. Isotopic analysis (δ²H, δ¹⁸O) confirms atmospheric precipitation as the principal recharge source, with pore water showing evaporative enrichment due to shallow depths. The Gibbs diagram and ion ratios demonstrate that hydrochemistry is primarily controlled by silicate and carbonate weathering (especially calcite dissolution), active cation exchange, and anthropogenic influences. EWQI assessment (avg. 156.2) indicates generally “good” overall quality but significant spatial variability. Pore water exhibits the highest exceedance rates (50% > Class III), driven by nitrate pollution from intensive vegetable cultivation in eastern areas (Xiyangzhuang–Liangzhuang) and sulfate contamination from gypsum mining (Guojialou–Nanxiyao). Karst water (26.7% > Class III) shows localized pollution belts (Huafeng–Dongzhuang) linked to coal mining and industrial discharges. Compared to basin-wide studies suggesting good quality in mid-upper reaches, this intensive mid-reach sampling identifies critical localized pollution zones within an overall low-EWQI background. The findings highlight the necessity for aquifer-specific and land-use-targeted groundwater protection strategies in this hydrogeologically complex region. Full article

The introduction of the ”dual carbon” target has increased the need for products that can accurately measure carbon dioxide levels, reflecting the rising demand. Due to challenges in achieving the required spatiotemporal resolution, accuracy, and spatial continuity with current carbon dioxide concentration products, it is essential to explore methods for obtaining carbon dioxide concentration products with completeness in space and time. Based on the 2018 OCO-2 carbon dioxide products and environmental variables such as vegetation coverage (FVC, LAI), net primary productivity (NPP), relative humidity (RH), evapotranspiration (ET), temperature (T) and wind (U, V), this study constructed a multiple regression model to obtain the spatial continuous carbon dioxide concentration products in the provinces of Huai River Basin. Using indicators such as correlation coefficient, root mean square error (RMSE), local variance, and percentage of valid pixels, the performance of model was validated. The validation results are shown as follows: (1) Among the selected environmental variables, the primary factors affecting the spatiotemporal distribution of carbon dioxide concentration are ET, LAI, FVC, NPP, T, U, and RH. (2) Compared with the OCO-2 carbon dioxide products, the percentage of valid pixels of the reconstructed carbon dioxide concentration data increased from less than 1% to over 90%. (3) The local variance in reconstructed data was significantly larger than that of original OCO-2 ${\mathrm{C}\mathrm{O}}_2$ products. (4) The average monthly RMSE is 2.69. Therefore, according to the model developed in this study, we can obtain a carbon dioxide concentration dataset that is spatially complete, meets precision requirements, and is rich in local detail information, which can better reflect the spatial pattern of carbon dioxide concentration and can be used to examine the carbon cycle between the terrestrial environment, biosphere, and atmosphere. Full article

With the rapid progression of global industrialization and urbanization, emerging contaminants (ECs) have become pervasive in environmental media, posing considerable risks to ecosystems and human health. While multidisciplinary evidence continues to accumulate regarding their environmental persistence and bioaccumulative hazards, critical knowledge gaps persist in understanding their spatiotemporal distribution, cross-media migration mechanisms, and cascading ecotoxicological consequences. This review systematically investigates the global distribution patterns of ECs in aquatic environments over the past five years and evaluates their potential ecological risks. Furthermore, it examines the performance of various treatment technologies, focusing on economic cost, efficiency, and environmental sustainability. Methodologically aligned with PRISMA 2020 guidelines, this study implements dual independent screening protocols, stringent inclusion–exclusion criteria (n = 327 studies). Key findings reveal the following: (1) Occurrences of ECs show geographical clustering in highly industrialized river basins, particularly in Asia (37.05%), Europe (24.31%), and North America (14.01%), where agricultural pharmaceuticals and fluorinated compounds contribute disproportionately to environmental loading. (2) Complex transboundary pollutant transport through atmospheric deposition and oceanic currents, coupled with compound-specific partitioning behaviors across water–sediment–air interfaces. (3) Emerging hybrid treatment systems (e.g., catalytic membrane bioreactors, plasma-assisted advanced oxidation) achieve > 90% removal for recalcitrant ECs, though requiring 15–40% cost reductions for scalable implementation. This work provides actionable insights for developing adaptive regulatory frameworks and advancing green chemistry principles in environmental engineering practice. Full article

By utilizing daily precipitation data from 400 meteorological stations in the Yellow River Basin (YRB) of China, atmospheric and oceanic reanalysis data, this study investigates the climatological characteristics, leading modes, and relationships with atmospheric circulation and sea surface temperature (SST) of summer extreme precipitation in the YRB from 1981 to 2020 through the extreme precipitation metrics and Empirical Orthogonal Function (EOF) analysis. The results indicate that both the frequency and intensity of extreme precipitation exhibit an eastward and southward increasing pattern in terms of climate state, with regions of higher precipitation showing greater interannual variability. When precipitation in the YRB exhibits a spatially coherent enhancement pattern, high latitudes exhibits an Eurasian teleconnection wave train that facilitates the southward movement of cold air. Concurrently, the northward extension of the Western Pacific subtropical high (WPSH) enhances moisture transport from low latitudes to the YRB, against the backdrop of a transitioning SST pattern from El Niño to La Niña. When precipitation in the YRB shows a “south-increase, north-decrease” dipole pattern, the southward-shifted Ural high and westward-extended WPSH converge cold air and moist in the southern YRB region, with no dominant SST drivers identified. Full article

Groundwater in the Qingshui River Plain of southern Ningxia is one of the main water sources for local domestic and agricultural use. However, due to the geological background of the area, 33.94% of the groundwater samples had fluoride concentrations that exceeded the WHO drinking water standards. To examine the spatial patterns and formation processes of fluoride in groundwater, researchers gathered 79 rock samples, 2618 soil samples, 21 sediment samples, 138 groundwater samples, and 82 surface water samples across the southern Qingshui River Plain. The collected data were analyzed using statistical approaches and hydrogeochemical diagrams. The findings reveal that fluoride levels in groundwater exhibit a gradual increase from the eastern, western, and southern peripheral sloping plains toward the central valley plain. Vertically, higher fluoride concentrations are found within 100 m of depth. Over a ten-year period, fluoride concentrations have shown minimal variation. Fluoride-rich rocks, unconsolidated sediments, and soils are the primary sources of fluoride in groundwater. The primary mechanisms governing high-fluoride groundwater formation are rock weathering and evaporative concentration, whereas cation exchange adsorption promotes fluoride (F⁻) mobilization into the aquifer. Additional sources of fluoride ions include leaching of fluoride-rich sediments during atmospheric precipitation infiltration and recharge from fluoride-rich surface water. Full article

Sulfate as a potential pollution source in the water environment of the basin, identifying sulfate sources and migration mechanisms is essential for protecting the water environment and ensuring sustainable water management. Liuyang River is a primary tributary of the Xiangjiang River. It has experienced progressively intensifying anthropogenic influences in recent decades, manifested by sustained sulfate concentration increases. However, the sulfate sources and their contributions were not clear. This study used hydrochemistry and multi-isotopes methods combined with Simmr model to study the hydrochemical characteristics, sulfate sources, and migration–transformation processes of surface water and groundwater. The results showed that the hydrochemical types of surface water were HCO₃-Ca and HCO₃·SO₄-Ca·Mg, and groundwater were HCO₃-Ca, HCO₃-Ca·Mg, and HCO₃·SO₄-Ca. Ions in the water primarily originated from carbonate and silicate rocks dissolution and sulfide oxidation, augmented by mining operations, sewage discharge, and chemical production. The analyses of hydrochemistry, isotopes, and Simmr model revealed that surface water sulfate originated from soil sulfate (35.70%), sulfide oxidation (26.56%), sewage (16.58%), and atmospheric precipitation (12.45%). Groundwater sulfate was derived predominantly from sewage (34.96%), followed by soil sulfate (28.09%), atmospheric precipitation (17.35%), and sulfide oxidation (12.25%). Sulfate migration and transformation were controlled by the natural environment and anthropogenic impacts. When unaffected by human activities, sulfate mainly originated from soil and atmospheric precipitation, relating to topography, geological conditions, agricultural activities, and precipitation intensity. However, in regions with intense human activities, contributions from sewage and sulfide oxidation significantly increased due to the influences of mining and industrial activities. Full article

Land Surface Temperature (LST) is essential for understanding the interactions between the land surface and the atmosphere. This study presents a comprehensive evaluation of machine learning (ML)-based downscaling algorithms to enhance the spatial resolution of MODIS LST data from 960 m to 30 m, leveraging auxiliary variables including vegetation indices, terrain parameters, and land surface reflectance. By establishing non-linear relationships between LST and predictive variables through eXtreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms, the proposed framework was rigorously validated using in situ measurements across China’s Heihe River Basin. Comparative analyses demonstrated that integrating multiple vegetation indices (e.g., NDVI, SAVI) with terrain factors yielded superior accuracy compared to factors utilizing land surface reflectance or excessive variable combinations. While slope and aspect parameters marginally improved accuracy in mountainous regions, including them degraded performance in flat terrain. Notably, land surface reflectance proved to be ineffective in snow/ice-covered areas, highlighting the need for specialized treatment in cryospheric environments. This work provides a reference for LST downscaling, with significant implications for environmental monitoring and urban heat island investigations. Full article

Understanding morphological descriptions of plants documented by ancient peoples over 1000 years ago and identifying the species they described are critical for reconstructing the natural geographic distribution of plant taxa, tracking taxonomic variations, and inferring historical climate dynamics. Analyzing shifts in plant communities and climatic conditions during this period is essential to unravel the interplay among floristic composition, climate fluctuations, and anthropogenic impacts. However, research in this field remains limited, with greater emphasis placed on plant taxa from hundreds of millions of years ago. Investigations into flora and climate during the last two millennia are sparse, and pre-millennial climatic conditions remain poorly characterized. In this study, a historical text written 1475 years ago was analyzed to compile plant names and morphological features, followed by taxonomic identification. The research identified three gymnosperm species (one in Pinaceae, two in Cupressaceae), 1 Tamaricaceae species (dicotyledon), and 19 dicotyledon species. However, three plant groups could only be identified at the genus level. Using textual analysis and woody plant coexistence methods, the climate of 1475 years ago in western Henan Province, located in the middle-lower Yellow River basin in East Asia, was reconstructed. Results indicate that the mean temperature of the coldest month (MTCM) was approximately 1.3 °C higher than modern values. In comparison, the mean temperature of the warmest month (MTWM) and mean annual temperature (MAT) were lower than present-day levels. This suggests slightly cooler overall conditions with milder seasonal extremes in ancient Luoyang—a finding supported by contemporaneous studies. Furthermore, annual precipitation (AP), precipitation of the warmest quarter (PWQ), and precipitation of the coldest quarter (PCQ) in the Luoyang region 1475 years ago exceeded modern measurements, despite the area’s monsoonal climate. This suggests significantly higher atmospheric moisture content in ancient air masses compared to today. This study provides floristic and climatic baseline data for advancing our understanding of global climate variability at millennial scales. Full article

Microplastics (MPs) have emerged as a critical environmental challenge in China’s aquatic ecosystems, driven by rapid industrialization and population growth. This review synthesizes recent findings on the abundance, morphology, and polymer types of MPs in China’s freshwater systems (rivers, lakes, reservoirs) and coastal marine environments. Spatial analysis reveals significant variability in MP abundance, ranging from 0.1 items/L in Tibet’s Lalu Wetland to 30.8 items/L in Beijing’s Qinghe River, with polypropylene (PP) and polyethylene (PE) dominating polymer profiles. Coastal regions exhibit distinct contamination patterns, with the Yellow Sea (5.3 ± 2.0 items/L) and the South China Sea (180 ± 80 items/m³) showing the highest MP loads, primarily as fibers and fragments. Fluvial transport, atmospheric deposition, and coastal anthropogenic activities (e.g., fisheries, tourism) are identified as major pathways for marine MP influx. Secondary MPs from degraded plastics and primary MPs from industrial/domestic effluents pose synergistic risks through the adsorption of heavy metals and organic pollutants. Human exposure routes—ingestion, inhalation, and dermal contact—are linked to inflammatory, metabolic, and carcinogenic health outcomes. Policy interventions, including bans on microbeads and non-degradable plastics, demonstrate progress in pollution mitigation. This work underscores the urgency of integrated source control, advanced wastewater treatment, and transboundary monitoring to address MP contamination in aquatic ecosystems. Full article

The Kundulun River Basin is the most prominent branch of the Yellow River system within the jurisdiction of Baotou City. As an important water source and ecological barrier, its ecological quality is directly related to the ecological security and sustainable development of the surrounding areas. This study selected the Kundulun River Basin in Baotou City as the research area. On the basis of collecting relevant information, a field investigation was conducted on the ecological and geological conditions of the atmospheric surface subsurface Earth system, using the watershed as the survey scope and water as the carrier for the transfer and conversion of materials and energy in the watershed. This study selected the main factors that affect the ecological geological quality of the watershed and established an evaluation model using the analytic hierarchy process, the coefficient of variation method, and the comprehensive analysis method. We have established an ecological geological quality evaluation index system for the Kundulun River Basin. We conducted quantitative evaluation and comprehensive analysis of regional ecological and geological environment quality. The results indicate that ecological environment indicators contribute the most to the ecological quality of the study area, while the impact of human activities on ecological quality is relatively small. From the perspective of evaluation indicators, grassland has the highest weight, followed by precipitation, groundwater depth, forest land, and cultivated land. Approximately 30.26% of the land in the research area is in a state of high or relatively high ecological and geological–environmental quality risk. It can be seen that the overall quality of the ecological geological environment is not optimistic and needs further protection. Full article

As a legacy of historical metal mining and the processing and smelting of metalliferous ores, metal pollution is a serious environmental problem in many areas around the globe. This review summarizes the history, technical development and environmental hazards of historic metal mining and metallurgical activities in the Harz Region (Germany), one of the oldest and most productive mining landscapes in Central Europe. The release of large amounts of metal-containing waste into rivers during historic ore processing and the ongoing leaching of metals from slag heaps, tailings dumps and contaminated soils and sediments are the main sources of metal pollution in the Harz Mountains and its foreland. This pollution extends along river systems with tributaries from the Harz Mountains and can even be detected in mudflats of the North Sea. In addition to fluvial discharges, atmospheric pollution by smelter smoke has led to long-term damage to soils and vegetation in the Harz Region. Currently, the ecological hazards caused by the legacy pollution from historical metal mining and metallurgy in the Harz Region are only partially known, particularly regarding the effects of changes in river ecosystems as a consequence of climate change. This review discusses the complexity and dynamics of human–environment interactions in the Harz Mountains and its surroundings, with a focus on lead (Pb) pollution. The paper also identifies future research directions with respect to metal contamination. Full article

This study investigates the impact of desert dust on precipitation patterns using multi-model simulations. Dust-based processes of formation/removal of ice nuclei (IN) and cloud condensation nuclei (CCN) are investigated by using both the online access model WRF-CHIMERE and the online integrated model WRF-Chem. Comparisons of model predictions with rainfall measurements (GRISO: Spatial Interpolation Generator from Rainfall Observations) over the Italian peninsula show the models’ ability to reproduce heavy orographic precipitation in alpine regions. To quantify the impact of the mineral dust transport concomitant to the atmospheric river (AR) on cloud formation, a sensitivity study is performed by using the WRF-CHIMERE model (i) by setting dust concentrations to zero and (ii) by modifying the settings of the Thompson Aerosol-Aware microphysics scheme. Statistical comparisons revealed that WRF-CHIMERE outperformed WRF-Chem. It achieved a correlation coefficient of up to 0.77, mean bias (MB) between +3.56 and +5.01 mm/day, and lower RMSE and MAE values (~32 mm and ~22 mm, respectively). Conversely, WRF-Chem displayed a substantial underestimation, with an MB of −25.22 mm/day and higher RMSE and MAE values. Our findings show that, despite general agreement in spatial precipitation patterns, both models significantly underestimated the peak daily rainfall in pre-alpine regions (e.g., 216 mm observed at Malga Valine vs. 130–140 mm simulated, corresponding to a 35–40% underestimation). Although important instantaneous changes in precipitation and temperature were modeled at a local scale, no significant total changes in precipitation or air temperature averaged over the entire domain were observed. These results underline the complexity of aerosol–cloud interactions and the need for improved parameterizations in coupled meteorological models. Full article

Data-driven distributed hydrological models utilizing atmospheric assimilation are crucial for simulating hydrological processes, particularly in regions lacking historical observational data, and for managing and developing local water resources due to the impacts of climate change and human activities. The southern part of Yunnan is located at the southwestern border of China, and the small number of observation stations poses a major obstacle to local water-resource management and hydrological research. This paper carries out an evaluation of the accuracy of the China Atmospheric-Assimilation Dataset (CMADS) in southern Yunnan and uses CMADS data and measured data to drive the BTOPMC model to investigate hydrological processes in the Jinping River basin, a representative local sub-basin. The study shows that the probability density function statistic (SS) between CMADS data and the measured precipitation data is 0.941, and their probability density curves of precipitation are basically the same. The relative error of daily precipitation is −19%, with 90% of the daily precipitation error concentrated within ±10 mm/day, which increases as daily precipitation increases. This paper examines three precipitation scenarios to drive the hydrological model, resulting in Nash–Sutcliffe efficiency (NSE) coefficients of 66.8%, 81.0%, and 83.9% for calibration, and 54.5%, 70.2%, and 74.5% for validation. These results indicate that CMADS data possesses a certain degree of applicable accuracy in southern Yunnan. Furthermore, the CMADS-driven BTOPMC model is suitable for simulating hydrological processes and conducting water-resource research in the region. The integration of CMADS data with actual measurement data can enhance the accuracy of hydrological simulations. Overall, the CMADS data have good applicability in southern Yunnan, and the CMADS-driven BTOPMC model can be used for hydrological modeling studies and water-resource management applications in southern Yunnan. Full article

Ozone (O₃) and fine particulate matter (PM_2.5) are critical atmospheric pollutants whose complex chemical coupling presents significant challenges for multi-pollutant control strategies. This study investigated the spatiotemporal variations and driving mechanisms of O₃ and PM_2.5 in Jiaxing, China, during different COVID-19 lockdown periods from November 2019 to January 2024. Using high-resolution monitoring data, random forest modeling, and HYSPLIT backward trajectory analysis, we quantified the relative contributions of anthropogenic emissions, meteorological conditions, and regional transport to the formation and variation of O₃ and PM_2.5 concentrations. The results revealed a distinct inverse relationship between O₃ and PM_2.5, with meteorologically normalized PM_2.5 decreasing significantly (−5.0 μg/m³ compared to the pre-lockdown baseline of 0.6 μg/m³), while O₃ increased substantially (15.2 μg/m³ compared to the baseline of 5.3 μg/m³). Partial dependency analysis revealed that PM_2.5-O₃ relationships evolved from linear to non-linear patterns across lockdown periods, while NO₂-O₃ interactions indicated shifts from VOC-limited to NO_x-limited regimes. Regional transport patterns exhibited significant temporal variations, with source regions shifting from predominantly northern areas pre-lockdown to more diverse directional contributions afterward. Notably, the partial lockdown period demonstrated the most balanced pollution control outcomes, maintaining reduced PM_2.5 levels while avoiding O₃ increases. These findings provide critical insights for developing targeted multi-pollutant control strategies in the Yangtze River Delta region and similar urban environments. Full article