Environmental Science and Ecotechnology最新文献

The ongoing water crisis poses significant threats to the socioeconomic sustainability and ecological security of arid and semi-arid river basins. Achieving Sustainable Development Goals (SDGs) within a complex socio-ecological nexus requires effective and balanced resource management. However, due to the intricate interactions between human societies and environmental systems, the tradeoffs and synergies of different SDGs remain unclear, posing a substantial challenge for collaborative management of natural resources. Here we introduce a gray fractional multi-objective optimization (GFMOP) model to balance multi-dimensional SDGs through a novel water–energy–economy–carbon–ecology nexus perspective. The model was applied to a typical arid river basin in Northwest China, where thirty-two scenarios were explored, considering factors such as shared socioeconomic pathways, carbon removal rates, water conveyance efficiencies, and ecological requirements. The results reveal a strong tradeoff between marginal benefit and carbon emission intensity, indicating that improving the economic efficiency of water use can simultaneously reduce emissions and protect the environment. Given the immense power generation potential, wind power development should be prioritized in the future, with its share in the energy structure projected to increase to 23.3% by 2060. Furthermore, promoting carbon capture technologies and expanding grassland coverage are recommended to achieve regional carbon neutrality, contributing 39.5% and 49.1% to carbon absorption during 2021–2060, respectively. Compared with traditional single-objective models, GFMOP demonstrates a superiority in uncovering interrelationships among multiple SDGs and identifying compromised alternatives within the compound socio-ecological nexus. The model also provides detailed strategies for resource allocation and pollutant control, offering valuable guidance to policymakers and stakeholders in pursuing sustainable and harmonious watershed management.

Coastal wetlands are important blue carbon ecosystems that play a significant role in the global carbon cycle. However, there is insufficient understanding of the variations in soil organic carbon (SOC) stocks and the mechanisms driving these ecosystems. Here we analyze a comprehensive multi-source dataset of SOC in topsoil (0–20 cm) and subsoil (20–100 cm) across 31 coastal wetlands in China to identify the factors influencing their distribution. Structural equation models (SEMs) reveal that hydrology has the greatest overall effect on SOC in both soil layers, followed by vegetation, soil properties, and climate. Notably, the mechanisms driving SOC density differ between the two layers. In topsoil, vegetation type and productivity directly impact carbon density as primary sources of carbon input, while hydrology, primarily through seawater salinity, exerts the largest indirect influence. Conversely, in subsoil, hydrology has the strongest direct effect on SOC, with seawater salinity also influencing SOC indirectly through soil and vegetation mediation. Soil properties, particularly pH, negatively affect carbon accumulation, while climate influences SOC indirectly via its effects on vegetation and soil, with a diminishing impact at greater depths. Using Random Forest, we generate high-resolution maps (90 m × 90 m) of topsoil and subsoil carbon density (R² of 0.53 and 0.62, respectively), providing the most detailed spatial distribution of SOC in Chinese coastal wetlands to date. Based on these maps, we estimate that SOC storage to a depth of 1 m in Chinese coastal wetlands totals 74.58 ± 3.85 Tg C, with subsoil carbon storage being 2.5 times greater than that in topsoil. These findings provide important insights into mechanism on driving spatial pattern of blue carbon and effective ways to assess carbon status on a national scale, thus contributing to the advancement of global blue carbon monitoring and management.

Biofilm reactors, known for utilizing biofilm formation for cell immobilization, offer enhanced biomass concentration and operational stability over traditional planktonic systems. However, the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products, making mass transfer efficiency a critical issue in these systems. Recent advancements have unveiled the intricate, heterogeneous architecture of biofilms, contradicting the earlier view of them as uniform, porous structures with consistent mass transfer properties. In this review, we explore six biofilm reactor configurations and their potential combinations, emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance. Furthermore, we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance. This review highlights the role of biofilm reactors in environmental and energy sectors, paving the way for future innovations in biofilm-based technologies and their broader applications.

Environmental assessments are critical for ensuring the sustainable development of human civilization. The integration of artificial intelligence (AI) in these assessments has shown great promise, yet the "black box" nature of AI models often undermines trust due to the lack of transparency in their decision-making processes, even when these models demonstrate high accuracy. To address this challenge, we evaluated the performance of a transformer model against other AI approaches, utilizing extensive multivariate and spatiotemporal environmental datasets encompassing both natural and anthropogenic indicators. We further explored the application of saliency maps as a novel explainability tool in multi-source AI-driven environmental assessments, enabling the identification of individual indicators' contributions to the model's predictions. We find that the transformer model outperforms others, achieving an accuracy of about 98% and an area under the receiver operating characteristic curve (AUC) of 0.891. Regionally, the environmental assessment values are predominantly classified as level II or III in the central and southwestern study areas, level IV in the northern region, and level V in the western region. Through explainability analysis, we identify that water hardness, total dissolved solids, and arsenic concentrations are the most influential indicators in the model. Our AI-driven environmental assessment model is accurate and explainable, offering actionable insights for targeted environmental management. Furthermore, this study advances the application of AI in environmental science by presenting a robust, explainable model that bridges the gap between machine learning and environmental governance, enhancing both understanding and trust in AI-assisted environmental assessments.

Urbanization is modifying aquatic ecosystems, with hydrodynamic and trophic variations altering biotic assemblages in rapidly expanding cities worldwide. Despite the fundamental bioenergetic role of food webs within these assemblages, their responding mechanism to the hydrodynamic and trophic variations remains largely unknown. Here we show that hydrodynamic and trophic loss, coupled with the weakening of cascade controls by key trophic guilds, leads to a significant decline in the structure, function and stability of macroinvertebrate food webs. Utilizing the allometric diet breadth model and biomass balance model, we established representative food webs for macroinvertebrate groups under varying hydrodynamic and trophic stresses. We found that such losses have reduced ∼75% trophic guild richness, ∼85% biomass flux, and ∼80% biomass storage. These reductions promote trophic guild specialization, further destabilizing food web, eroding interactive strength asymmetry, and diminishing the control of trophic guilds. Furthermore, macroinvertebrate food webs show divergent stability responses under similar stress levels, mainly driven by differences in the cascade controls exerted by key trophic guilds. Our results underscore the critical role of hydrodynamic and trophic variations in shaping urban aquatic ecosystems and highlight the significance of both external environmental revitalization and internal food web dynamics enhancement in restoring the ecological stability in urban settings.

Ozone (O₃) pollution is usually linked to warm weather and strong solar radiation, making it uncommon in cold winters. However, an unusual occurrence of four high O₃ episode days (with maximum hourly concentrations exceeding 100 ppbv and peaking at 121 ppbv) was recorded in January 2018 in Lanzhou city, China. During these episodes, the average daytime concentration of total non-methane volatile organic compounds (TVOCs) reached 153.4 ± 19.0 ppbv, with alkenes—largely emitted from the local petrochemical industry—comprising 82.3 ± 13.1 ppbv. Here we show a photochemical box model coupled with a Master Chemical Mechanism to elucidate the mechanisms behind this unusual wintertime O₃ pollution. We find that the typically low temperatures (−1.7 ± 1.3 °C) and weak solar radiation (263.6 ± 60.7 W m^-2) of those winter episode days had a minimal effect on the reactivity of VOCs with OH radicals. Instead, the ozonolysis of alkenes generated Criegee intermediates, which rapidly decomposed into substantial RO_x radicals (OH, HO₂, and RO₂) without sunlight. This radical production led to the oxidation of VOCs, with alkene ozonolysis ultimately contributing to 89.6 ± 8.7% of the O₃ formation during these episodes. This mechanism did not activate at night due to the depletion of O₃ by the NO titration effect. Furthermore, the findings indicate that a reduction of alkenes by 28.6% or NO_x by 27.7% in the early afternoon could significantly mitigate wintertime O₃ pollution. Overall, this study unravels the unique mechanism of alkene-induced winter O₃ pollution and offers a reference for winter O₃ reduction strategies in the petrochemical industrial regions.

Sedimentary organic matter (SOM) affects the stability of the aquatic carbon pool. The degradation process of SOM is complex for its multifaceted composition. The concentration and properties of SOM affect its steady state, yet the transformation processes of SOM in lakes remain unclear. Here we show the molecular and redox perspectives of SOM stability in polluted sediments with high organic matter content and diverse vegetation. We find significant differences in carbon fractions across various sites. The origin of the organic matter, determined using excitation-emission matrix spectra, influences the consistency of organic matter composition and biochemical degradation in lacustrine sediment. We also observe that sulfur-containing substances decrease carbon chain length and reduce organic matter stability. Fourier-transform ion cyclotron resonance mass spectrometry shows that sulfur-containing substances decrease the degree of saturation and cause reduction. In contrast, nitrogen-containing compounds increase the modified aromaticity index and humin content, enhancing organic carbon complexity and stability (p < 0.05). These results complement the characteristics and transformations of SOM. In a broader perspective, this study contributes to laying the foundation for understanding SOM stability in the carbon cycle and its future effects.

Understanding how per- and polyfluoroalkyl substances (PFASs) enter aquatic ecosystems is challenging due to the complex interplay of physical, chemical, and biological processes, as well as the influence of hydraulic and hydrological factors and pollution sources at the catchment scale. The spatiotemporal dynamics of PFASs across various media remain largely unknown. Here we show the fate and transport mechanisms of PFASs by integrating monitoring data from an estuarine reservoir in Singapore into a detailed 3D model. This model incorporates hydrological, hydrodynamic, and water quality processes to quantify the distributions of total PFASs, including the major components perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS), across water, particulate matter, and sediments within the reservoir. Our results, validated against four years of field measurements with most relative average deviations below 40%, demonstrate that this integrated approach effectively characterizes the occurrence, sources, sinks, and trends of PFASs. The majority of PFASs are found in the dissolved phase (>95%), followed by fractions sorbed to organic particles like detritus (1.0–3.5%) and phytoplankton (1–2%). We also assess the potential risks in both the water column and sediments of the reservoir. The risk quotients for PFOS and PFOA are <0.32 and < 0.00016, respectively, indicating an acceptable risk level for PFASs in this water body. The reservoir also exhibits substantial buffering capacity, even with a tenfold increase in external loading, particularly in managing the risks associated with PFOA compared to PFOS. This study not only enhances our understanding of the mechanisms influencing the fate and transport of surfactant contaminants but also establishes a framework for future research to explore how dominant environmental factors and processes can mitigate emerging contaminants in aquatic ecosystems.

Improving electrification feasibility is essential for reducing emissions from non-electric energy sources, thereby enhancing air quality and public health. Concurrently, climate mitigation actions, such as carbon pricing policies, have significant potential to alleviate increasing carbon dioxide (CO₂) and other co-emitted air pollutants. However, the interactions between climate policy and the improvement of electrification feasibility at the provincial level remain unclear, collectively impacting the net-zero transition of energy-intensive sectors. Here we combine a technologically rich economic-energy-environment model with air quality modeling across China to examine the health, climate, and economic implications of large-scale upgrades in electrification feasibility and climate policies from 2017 to 2030. The results indicate that advancing electrification feasibility, coupled with adopting carbon pricing policies, is likely to facilitate a transition towards electricity-dominant energy systems. Improved electrification feasibility is projected to yield a 7–25% increase in nationwide climate benefits and a 5–14% increase in health benefits by 2030. These incremental benefits, coupled with reduced economic costs, result in a 22–68% increase in net benefits. However, regionally, improvements in electrification feasibility will lead to heightened power demand and unintended emissions from electric energy production in certain provinces (e.g., Nei Mongol) due to the coal-dominated power system. Additionally, in major coal-producing provinces like Shanxi and Shaanxi, enhanced electrification feasibility exacerbates the negative economic impacts of climate policies. This study provides quantitative insights into how improving electrification feasibility reshapes energy evolution and the benefit-cost profile of climate policy at the provincial level. The findings underscore the necessity of a well-designed compensation scheme between affected and unaffected provinces and coordinated emission mitigation across the power and other end-use sectors.

Currently, chemicals and waste are recognized as key drivers of habitat degradation and biodiversity loss in aquatic ecosystems. To ensure vibrant habitats for aquatic species and maintain a sustainable aquatic food supply system, Japan promulgated its Environmental Quality Standards for the Conservation of Aquatic Life (EQS-CAL), based on its own aquatic life water quality criteria (ALWQC) derivation method and application mechanism. Here we overview Japan's EQS-CAL framework and highlight their best practices by examining the framework systems and related policies. Key experiences from Japan's EQS-CAL system include: (1) Classifying six types of aquatic organisms according to their adaptability to habitat status; (2) Using a risk-based chemical screening system for three groups of chemical pollutants; (3) Recommending a five-step method for determining ALWQC values based on the most sensitive life stage of the most sensitive species; (4) Applying site-specific implementation mechanisms through a series of Plan-Do-Check-Act loops. This paper offers scientific references for other jurisdictions, aiding in the development of more resilient ALWQC systems that can maintain healthy environments for aquatic life and potentially mitigate ongoing threats to human societies and global aquatic biodiversity.