Search Results (1,675)

Atmospheric sulfur (S) deposition, a key component of acid deposition, poses risks to ecosystems, human health, and sustainable development. In China, decades of coal-dominated energy use caused severe S pollution, but recent emission-control policies and energy restructuring have sought to reverse this trend. However, the effectiveness and regional differences in these measures remain insufficiently quantified. Here, we combined continuous observations from 43 monitoring sites (2013–2023), satellite-derived SO₂ vertical column density, and multi-source environmental datasets to construct a high-resolution record of wet S deposition. A random forest model, validated with R² = 0.52 and RMSE = 1.2 kg ha⁻¹ yr⁻¹, was used to estimate fluxes and spatial patterns, while ridge regression and SHAP analysis quantified the relative contributions of emissions, precipitation, and socioeconomic factors. This framework allows us to assess both the environmental and health-related sustainability implications of sulfur deposition. Results show a nationwide decline of more than 50% in wet S deposition during 2013–2023, with two-thirds of sites and 95% of grids showing significant decreases. Historical hotspots such as the North China Plain and Sichuan Basin improved markedly, while some southern provinces (e.g., Guizhou, Hunan, Jiangxi) still exhibited high deposition (>20 kg ha⁻¹ yr⁻¹). Over 90% of the reduction was attributable to emission declines, confirming the dominant effect of sustained policy-driven measures. This study extends sulfur deposition records to 2023, demonstrates the value of integrating ground monitoring with remote sensing and machine learning, and provides robust evidence that China’s emission reduction policies have delivered significant environmental and sustainability benefits. The findings offer insights for region-specific governance and for developing countries balancing economic growth with ecological protection. Full article

The lack of research on the slip behavior of the NW-trending faults in the central Tibetan Plateau constrains our understanding of the deformation models for this region. The Ba Co Fault, located in the central Tibetan Plateau, is a NW–SE-trending right-lateral strike-slip fault. Its eastern section has been active in the Holocene and plays an important accommodating role in the northward compression and east–west extension of the Tibetan Plateau. This study presents a detailed analysis of the geomorphic features of the eastern section of the Ba Co Fault in the Ngari Prefecture of Tibet, precisely measuring the newly discovered surface rupture zone on its eastern side and preliminarily discussing the activity of the fault based on the optically stimulated luminescence (OSL) dating results. The results reveal that the eastern segment of the Ba Co Fault displays geomorphic evidence of offset, including displaced Holocene alluvial–fluvial fans at the mountain front and partially offset ridges. A series of pressure ridges, trenches, counter-slope scarps, and shutter ridge ponds have developed along the fault trace. Some gullies exhibit a cumulative dextral displacement of approximately 16–52 m. The newly discovered co-seismic surface rupture zone extends for a total length of ~21 km, with a width ranging from 30 to 102 m. Pressure ridges within the rupture zone reach heights of 0.3–5.5 m, while trenches exhibit depths of 0.6–15 m. Optically stimulated luminescence (OSL) dating constrains the timing of the surface-rupturing earthquake to after 5.73 ± 0.17 ka. The eastern segment of the Ba Co Fault experienced a NW-trending compressional deformation regime during the Holocene, manifesting as a transpressional dextral strike-slip fault. Magnitude estimation indicates that this segment possesses the potential to generate earthquakes of M ≥ 6. The regional tectonic analysis indicates that the activity of the eastern section of the Ba Co Fault is related to the shear model of the conjugate strike-slip fault zone in the central Tibetan Plateau and may play a boundary role between different shear zones. Full article

This study proposes a novel causality-structured matrix long short-term memory (C-mLSTM) model for significant wave height (SWH) forecasting. The framework incorporates a two-stage causal feature selection methodology using cointegration testing and Granger causality testing to identify long-term stable causal relationships among variables. These relationships are embedded within the C-mLSTM architecture, enabling the model to effectively capture both temporal dependencies and causal information within the data. Furthermore, the model integrates Bayesian optimization (BO) and twin delayed deep deterministic policy gradient (TD3) algorithms for synergistic optimization. This combined TD3-BO approach achieves an 11.11% improvement in the mean absolute percentage error (MAPE) on average compared to the base model without optimization. For 1–24 h SWH forecasts, the proposed TD3-BO-C-mLSTM outperforms the benchmark models TD3-BO-LSTM and TD3-BO-mLSTM in prediction accuracy. Finally, a Shapley additive explanations (SHAP) analysis was conducted on the input features of the BO-C-mLSTM model, which reveals interpretability patterns consistent with the two-stage causal feature selection methodology. This research demonstrates that integrating causal modeling with optimization strategies significantly enhances time-series forecasting performance. Full article

The hydrology of the transboundary region encompassing the western Red River Basin headwaters, such as Devils Lake Basin (DLB) in North America, is complex and highly sensitive to climate variability, impacting water resources, agriculture, and flood risk. Understanding hydrological shifts in this region is critical, particularly given recent hydroclimatic changes. This study aimed to simulate and analyze key hydrological processes and their evolution from 1981 to 2020 using an integrated modeling approach. We employed the NASA Land Information System (LIS) framework configured with the Noah-MP land surface model and the HyMAP routing model, driven by a combination of reanalysis and observational datasets. Simulations revealed a significant increase in precipitation inputs and consequential positive net water storage trends post-1990, indicating increased water retention within the system. Snow dynamics showed high interannual variability and decadal shifts in average Snow Water Equivalent (SWE). Simulated streamflow exhibited corresponding multi-decadal trends, including increasing flows within a major DLB headwater basin (Mauvais Coulee Basin) during the period of Devils Lake expansion (mid-1990s to ~2011). Furthermore, analysis of decadal average seasonal hydrographs indicated significant shifts post-2000, characterized by earlier and often higher spring peaks and increased baseflows compared to previous decades. While the model captured these trends, validation against observed streamflow highlighted significant challenges in accurately simulating peak flow magnitudes (Nash–Sutcliffe Efficiency = 0.33 at Mauvais Coulee River near Cando). Overall, the results depict a non-stationary hydrological system responding dynamically to hydroclimatic forcing over the past four decades. While the integrated modeling approach provided valuable insights into these changes and their potential drivers, the findings also underscore the need for targeted model improvements, particularly concerning the representation of peak runoff generation processes, to enhance predictive capabilities for water resource management in this vital region. Full article

The Necrópolis de Wari Kayan, at the Paracas site in the coastal desert of south–central Peru, is a large archeologically excavated mortuary complex with fine textile preservation, dated approximately to 2000 BP. This study investigates loose yarns associated with textiles from Wari Kayan tomb 12 (bundle 382), collected by the late Dr. Anne Paul in 1985 at what is now the Museo Nacional de Arqueología Antropología e Historia del Perú (MNAAHP). Sequencing multiple state-of-the-art analyses, including direct analysis in real time mass spectrometry (DART-MS), high performance liquid chromatography (HPLC) with diode array detection, and accelerator mass spectrometry, on the same small sample, seeks to “squeeze out every drop” of information. Six mantles from the outer layer include different sets of color hues and values, representing either different time periods or different producer groups. Plasma oxidation at low temperature (<100 °C) prepared carbon dioxide for AMS radiocarbon analysis. Fibers remaining after oxidation were combusted for light-stable isotope analysis. The sequential analysis results in fiber and dye composition, radiocarbon age, and stable isotope fractionation values may suggest fiber origin, continuing and updating a project started over 40 years ago. Full article

Phosphorus, a crucial yet nonrenewable resource, is essential for agriculture, life processes, and various industries. In this study, we employed co-pyrolysis of eggshells and peanut shells to prepare calcium-based biochar (EPB) with a high adsorption capacity and ecological non-toxicity, enabling effective phosphorus recovery from wastewater. EPB was characterized via X-ray diffraction, scanning electron microscopy, electron probe microanalysis, and Brunauer–Emmett–Teller analysis. Additionally, its phosphate adsorption characteristics were investigated under varying temperature, pH, and coexisting ion conditions. Phosphate adsorption followed the Langmuir isotherm with a maximum adsorption capacity of 178.08 mg/g, and the kinetics aligned with those of the quasi-second-order kinetic model. Phosphate adsorption by EPB was driven by electrostatic attraction and chemical precipitation. Moreover, we investigated the effects of phosphorus-enriched biochar on the growth and development of tobacco and soil microbial communities. Phosphorus-enriched biochar increased organic and inorganic phosphorus levels and promoted tobacco growth compared with conventional fertilizers. Phosphorus-enriched biochar reshaped tobacco rhizosphere microbial communities, promoting beneficial taxa, such as Nitrospira. Structural equation analysis showed that EPB enhanced microbial alpha diversity and key microbial communities, improving phosphorus availability and tobacco growth and development. Conclusively, this study provides a theoretical reference for phosphorus-containing wastewater treatment and reuse. Full article

This study investigates the impact of long-term memory stochastic forcing on the ensemble mean dynamics of the El Niño–Southern Oscillation (ENSO) by incorporating a fractional Ornstein-Uhlenbeck (FOU) process as external forcing into an ENSO spatiotemporal oscillator (STO) conceptual model. Unlike the classic Ornstein-Uhlenbeck (OU) process, the FOU process exhibits a slow power-law decay in auto-correlation and can trigger an anomalous growth rate that persistently influences the divergence/dissipation of the ensemble mean system. Furthermore, theoretical and quantitative analyses verify that the anomalous growth rate is determined by the ensemble mean of the FOU process, reflecting the cumulative nature of long-memory forcing. Crucially, the anomalous growth rate is positive and thus induces system divergence when the FOU process exhibits a positive ensemble mean, whereas it is negative and induces dissipation when the ensemble mean is negative. Also, the anomalous growth rate intensifies with decreasing fractional order. On the other hand, FOU forcing can also modulate the phase of the ensemble mean oscillation for ENSO. When the phases of the natural and forced oscillations are in phase alignment, the phase of the ensemble mean oscillation leads relative to the natural oscillation. Conversely, when the phases of the natural and forced oscillations are in anti-phase alignment, the phase of the ensemble mean oscillation lags behind relative to the natural oscillation. Future work would address the case when the external forcing has a spatial structure and seek observational validation of the identified growth rate signatures and phase shifts. Full article

The North Atlantic Ocean is vital to Earth’s climate system. Scientific investigations have identified the Atlantic Meridional Overturning Circulation (AMOC) as a significant factor influencing global climate change. This circulation involves ocean currents that carry relatively warm, salty water northward in the upper layers, while transporting colder, less salty water southward in the deeper layers. The AMOC relies on descending water at deep convection sites in the high-latitude North Atlantic (NA), where warmer water cools, becomes denser, and sinks. A concern regarding the AMOC is that the freshening of the sea surface at these convection sites can slow it by inhibiting deep convection. Researchers have used oceanographic observations and models of Earth’s climate and ocean circulation to investigate decadal shifts in the AMOC and NA. We examined these findings to provide insights into these models, observational analyses, and palaeoceanographic reconstructions, aiming to deepen our understanding of AMOC variability and offer potential predictions for future climate change in the North Atlantic. While the influence of high-latitude freshwater is crucial and may slow the AMOC, evidence also shows a complex feedback mechanism. In this mechanism, the negative feedback from wind stress can stabilize the AMOC, partially counteracting the positive feedback effects of freshwater at high latitudes. Although some models predict significant shifts in AMOC dynamics, suggesting imminent and possibly severe deceleration, recent observational research presents a more cautious view. These data analysis studies acknowledge changes, but highlight the robustness of the AMOC, particularly in its upper arm within the Gulf Stream system. While it cannot be entirely dismissed that the AMOC may reach its tipping point within this century, an analysis of data concerning the decadal variability in the AMOC’s upper arm indicates that a collapse is unlikely within this timeframe, although significant weakening remains quite possible. Furthermore, deceleration of the AMOC’s upper arm could lead to less stable and more vulnerable North Atlantic Ocean climate patterns over extended periods. Full article

Intensive greenhouse agriculture significantly alters dissolved organic matter (DOM) dynamics in aquatic ecosystems, but related research remains scarce. To address this knowledge gap, this study employed an integrated approach combining Excitation–Emission Matrix Parallel Factor Analysis (EEM-PARAFAC), Two-Dimensional Correlation Spectroscopy (2D-COS), and Self-Organizing Map (SOM) analyses with hydrochemical and stable water isotopes (δ¹⁸O and δD) to investigate the dynamic characteristics of DOM in surface water and groundwater in an intensive greenhouse agriculture catchment (XER) in northern China. Water chemistry and isotope results consistently demonstrated mixing between surface water and groundwater, which was attributed to irrigation pumping. Four fluorescent components were identified via EEM-PARAFAC (C1 and C4 are humic components, while C2 and C3 are tryptophan components), with microbial decomposition of organic fertilizers and domestic wastewater discharge being important sources. Compared with tryptophan components, terrestrial humic substances in groundwater preferentially change in the parallel river direction, while microbial humic substances are more sensitive in the vertical direction, as confirmed by 2D-COS. SOM analysis validated the EEM-PARAFAC results through component plane visualization, demonstrating both DOM inter-component relationships and their correlations with inorganic ions. These results provide critical scientific support for developing sustainable water resource management strategies and optimizing organic fertilizer use in greenhouse agricultural systems, with important practical implications for protecting groundwater quality in intensively cultivated catchments. Full article

Nonpoint Source (NPS) pollution refers to water pollution that does not originate from a single identifiable source. In this study, we conducted water-quality monitoring during the snowmelt period from February to March of 2024 and 2025 in Jaun, a highland agricultural area. We analyzed changes in nonpoint source pollutant concentration and evaluated Best Management Practice (BMPs) effectiveness. A year-to-year comparison showed that in 2024, a single intense snowmelt event led to a sharp increase in particulate pollutants, such as TP and SS. In 2025, repeated and gradual thawing resulted in the accumulation and release of dissolved pollutants, including TN and TOC. BMPs such as straw mulching were partially effective in reducing pollutant concentrations. However, in 2025, a lack of proper maintenance led to increased concentration at certain sites. The water quality during the snowmelt period was comparable to that during the summer monsoon season, indicating that snowmelt has a similar potential for generating nonpoint source pollution. The findings provide area-based insights into snowmelt-induced nonpoint source pollution and can form a foundation for developing seasonal water quality management policies. Full article

Seasonal dynamics of dissolved organic matter (DOM) in agricultural ditches significantly impact carbon cycling and water quality in connected rivers. This study aimed to characterize seasonal variations in DOM composition and dynamics within hierarchical agricultural ditch systems in Tianjin, northern China. Surface water samples were collected from river channels, main ditches, branch ditches, lateral ditches, and field ditches during wet (June 2021) and dry (December 2021) seasons. DOM characteristics were analyzed using dissolved organic carbon (DOC) quantification, ultraviolet-visible (UV-Vis) absorption spectroscopy, and three-dimensional excitation–emission matrix spectroscopy (3D-EEMs) coupled with parallel factor analysis (PARAFAC). The concentration of DOC in ditch surface water exhibited significant seasonal variations, with significantly higher levels observed during the wet season (Huangzhuang: 6.72 ± 0.7 mg/L; Weixing: 13.15 ± 3.1 mg/L) compared to the dry season (Huangzhuang: 5.93 ± 0.3 mg/L; Weixing: 9.35 ± 2.6 mg/L). Both UV-Vis spectral and EEM-PARAFAC analysis revealed that DOM in ditch systems was predominantly composed of fulvic-like and tryptophan-like components, representing the portion of organic matter in water bodies that is highly biologically active, highly mobile, relatively “fresh”, or “not fully humified”. PARAFAC identified microbial humic-like (C1: wet season 40.36%, dry season 34.42%) and protein-like (C3: wet season 40.3%, dry season 49.87%) components as dominant. DOM sources were influenced by dual inputs from terrestrial and autochthonous origins during the wet season, while primarily deriving from autochthonous sources in the dry season. This study elucidates the advances of spectroscopic techniques in deciphering the composition, sources, and influencing factors of DOM in aquatic systems. The findings support implementing riparian buffer strips and optimized fertilizer management to mitigate seasonal peaks of bioavailable DOM in agricultural ditch systems. Full article

This essay proposes a transdisciplinary framework that positions cooperation as a foundational principle for ecosystem stewardship in the Anthropocene. Drawing from microbial ecology, evolutionary theory, and sustainability science, we argue that cooperation, rather than competition, is a robust and scalable strategy for resilience across biological and institutional systems. In particular, microbial behaviors such as biofilm formation, quorum sensing, and horizontal gene transfer are especially pronounced in extreme environments, where cooperation becomes essential for survival. These strategies serve as functional analogues that illuminate the structural logics of resilience: interdependence, redundancy, distributed coordination, and adaptation. As the Anthropocene progresses toward increasingly extreme conditions, including potential “Hothouse Earth” scenarios driven by climate disruption, such ecological heuristics offer concrete insights into how human institutions can adapt to stress and uncertainty. Rather than reiterating familiar calls for hybrid governance, we use microbial cooperation as a heuristic to reveal the functional architecture already present in many resilient governance practices. These microbial strategies emerging from life in extreme environments demonstrate how interdependence, redundancy, and distributed coordination can create system resilience and sustainability in the long run. By translating microbial survival strategies into institutional design principles, this framework reframes ecosystem stewardship not as a normative ideal, but as an ecological imperative grounded in the evolutionary logic of cooperation. Full article

Exposure to extreme temperature events (ETEs) and ambient fine particulate matter (PM_2.5) has been linked to an increased risk of pneumonia mortality, but their interactive effects remain largely unknown. We investigated 50,196 pneumonia deaths from 2015 to 2022 in Jiangsu province, China, with a time-stratified case-crossover design. An individual-level exposure to heat wave, cold spell, and PM_2.5 was assessed at each subject’s residential address using validated grid datasets. Conditional logistic regression models integrated with a distributed lag nonlinear model were used to quantitatively estimate both independent and interactive effects. With different ETE definitions, the cumulative odds ratio (OR) of pneumonia mortality associated with heat wave and cold spell ranged from 1.22 (95% confidence interval [CI]: 1.14, 1.31) to 1.60 (1.40, 1.81), and from 1.08 (1.002, 1.17) to 1.18 (1.01, 1.38), respectively, while the OR for PM_2.5 ranged from 1.013 (1.006, 1.021) to 1.016 (1.009, 1.024). We observed a synergistic effect (relative excess risk due to interaction [RERI] ranging from 0.40 [0.06, 0.76] to 1.16 [0.41, 2.09]) of co-exposure to heat wave and PM_2.5, as well as an antagonistic effect (RERI ranging from −0.20 [−0.40, −0.03] to −1.02 [−1.78, −0.38]) of co-exposure to cold spell and PM_2.5 on pneumonia mortality. It was estimated that up to 6.49% of pneumonia deaths were attributable to heat wave and PM_2.5 exposures. We found that heat wave and cold spell interacted oppositely with PM_2.5 to increase the odds of pneumonia mortality, highlighting the needs to reduce co-exposures to heat wave and PM_2.5. Full article

The integration of low Earth orbit (LEO) satellite constellations into the Global Navigation Satellite System (GNSS) has emerged as a prominent research focus, as LEO satellites can significantly enhance the precision of GNSS positioning, navigation, and timing (PNT) services. In the design of LEO navigation constellations, the development of an efficient broadcast ephemeris model is critical for delivering high-accuracy navigation solutions. This study extends the conventional 16-parameter Keplerian broadcast ephemeris model by proposing enhanced 18-, 20-, 22-, and 24-parameter models, ensuring compatibility with existing GNSS ephemeris standards. The performance of these models was evaluated using precise science orbit from five satellites at varying altitudes, ranging from 320 km to 1336 km. By analyzing fitting errors, Signal-in-Space Range Error (SISRE), and Message Size Bits (MSB) across different fitting arc durations and parameter counts, the optimal model configuration was identified. The results demonstrate that the 22-parameter model, which was constructed by augmenting the standard 16-parameter ephemeris with $(\dot{a}$, $\dot{n}$, $Crs3$, $Crc3$, $Crs1$, $Crc1$) delivers the best balance of accuracy and efficiency. With a fitting arc length of 20 min, the SISRE for the GRACE-A (320 km), GRACE-C (475 km), Sentinel-2A (786 km), HY-2A (966 km), and Sentinel-6A (1336 km) satellites were measured at 8.88 cm, 6.21 cm, 2.87 cm, 2.11 cm, and 0.75 cm, respectively. Meanwhile, the corresponding MSB remained compact at 501, 490, 491, 487, and 476 bits. These findings confirm that the proposed 22-parameter broadcast ephemeris model meets the stringent accuracy requirements for next-generation LEO-augmented GNSSs, paving the way for enhanced global navigation services. Full article