Environmental Science and Ecotechnology最新文献

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018–2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH₃–N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (COD_Mn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Ecological water replenishment (EWR) is an important strategy for river restoration globally, but timely evaluation of its ecological effects at a large spatiotemporal scale to further adjust the EWR schemes is of great challenge. Here, we examine the impact of EWR on microeukaryotic plankton communities in three distinct river ecosystems through environmental DNA (eDNA) metabarcoding. The three ecosystems include a long-term cut-off river, a short-term connected river after EWR, and long-term connected rivers. We analyzed community stability by investigating species composition, stochastic and deterministic dynamics interplay, and ecological network robustness. We found that EWR markedly reduced the diversity and complexity of microeukaryotic plankton, altered their community dynamics, and lessened the variation within the community. Moreover, EWR disrupted the deterministic patterns of community organization, favoring dispersal constraints, and aligning with trends observed in naturally connected rivers. The shift from an isolated to a temporarily connected river appeared to transition community structuring mechanisms from deterministic to stochastic dominance, whereas, in permanently connected rivers, both forces concurrently influenced community assembly. The ecological network in temporarily connected rivers post-EWR demonstrated significantly greater stability and intricacy compared to other river systems. This shift markedly bolstered the resilience of the ecological network. The eDNA metabarcoding insights offer a novel understanding of ecosystem resilience under EWR interventions, which could be critical in assessing the effects of river restoration projects throughout their life cycle.

Green-blue spaces (GBS) are pivotal in mitigating thermal discomfort. However, their management lacks guidelines rooted in epidemiological evidence for specific planning and design. Here we show how various GBS types modify the link between non-optimal temperatures and cardiovascular mortality across different thermal extremes. We merged fine-scale population density and GBS data to create novel GBS exposure index. A case time series approach was employed to analyse temperature-cardiovascular mortality association and the effect modifications of type-specific GBSs across 1085 subdistricts in south-eastern China. Our findings indicate that both green and blue spaces may significantly reduce high-temperature-related cardiovascular mortality risks (e.g., for low (5%) vs. high (95%) level of overall green spaces at 99th vs. minimum mortality temperature (MMT), Ratio of relative risk (RRR) = 1.14 (95% CI: 1.07, 1.21); for overall blue spaces, RRR = 1.20 (95% CI: 1.12, 1.29)), while specific blue space types offer protection against cold temperatures (e.g., for the rivers at 1st vs MMT, RRR = 1.17 (95% CI: 1.07, 1.28)). Notably, forests, parks, nature reserves, street greenery, and lakes are linked with lower heat-related cardiovascular mortality, whereas rivers and coasts mitigate cold-related cardiovascular mortality. Blue spaces provide greater benefits than green spaces. The severity of temperature extremes further amplifies GBS's protective effects. This study enhances our understanding of how type-specific GBS influences health risks associated with non-optimal temperatures, offering valuable insights for integrating GBS into climate adaptation strategies for maximal health benefits.

Mismanaged plastics, upon entering the environment, undergo degradation through physicochemical and/or biological processes. This process often results in the formation of microplastics (MPs), the most prevalent form of plastic debris (<1 mm). MPs pose severe threats to aquatic and terrestrial ecosystems, necessitating innovative strategies for effective remediation. Some photosynthetic microorganisms can degrade MPs but there lacks a comprehensive review. Here we examine the specific role of photoautotrophic microorganisms in water and soil environments for the biodegradation of plastics, focussing on their unique ability to grow persistently on diverse polymers under sunlight. Notably, these cells utilise light and CO₂ to produce valuable compounds such as carbohydrates, lipids, and proteins, showcasing their multifaceted environmental benefits. We address key scientific questions surrounding the utilisation of photosynthetic microorganisms for MPs and nanoplastics (NPs) bioremediation, discussing potential engineering strategies for enhanced efficacy. Our review highlights the significance of alternative biomaterials and the exploration of strains expressing enzymes, such as polyethylene terephthalate (PET) hydrolases, in conjunction with microalgal and/or cyanobacterial metabolisms. Furthermore, we delve into the promising potential of photo-biocatalytic approaches, emphasising the coupling of plastic debris degradation with sunlight exposure. The integration of microalgal-bacterial consortia is explored for biotechnological applications against MPs and NPs pollution, showcasing the synergistic effects in wastewater treatment through the absorption of nitrogen, heavy metals, phosphorous, and carbon. In conclusion, this review provides a comprehensive overview of the current state of research on the use of photoautotrophic cells for plastic bioremediation. It underscores the need for continued investigation into the engineering of these microorganisms and the development of innovative approaches to tackle the global issue of plastic pollution in aquatic and terrestrial ecosystems.

High salinity inhibits microbial activity in the bioremediation of saline wastewater. To alleviate osmotic stress, glycine betaine (GB), an osmoprotectant, is added to enhance the secretion of extracellular polymeric substances (EPS). These EPS are pivotal in withstanding environmental stressors, yet the intricate interplay between GB supplementation and microbial responses through EPS modifications—encompassing composition, molecular architecture, and electrochemical features—remains elusive in hypersaline conditions. Here we show microbial strategies for salinity endurance by investigating the impact of GB on the dynamic alterations of EPS properties. Our findings reveal that GB supplementation at 3.5% salinity elevates the total EPS (T-EPS) content from 12.50 ± 0.05 to 24.58 ± 0.96 mg per g dry cell weight. The observed shift in zeta potential from −28.95 to −6.25 mV at 0% and 3.5% salinity, respectively, with GB treatment, indicates a reduction in electrostatic repulsion and compaction. Notably, the EPS protein secondary structure transition from β-sheet to α-helix, with GB addition, signifies a more compact protein configuration, less susceptible to salinity fluctuations. Electrochemical analyses, including cyclic voltammetry (CV) and differential pulse voltammetry (DPV), reveal GB's role in promoting the release of exogenous electron shuttles, such as flavins and c-type cytochromes (c-Cyts). The enhancement in DPV peak areas (Q_DPV) with GB addition implies an increase in available extracellular electron transfer sites. This investigation advances our comprehension of microbial adaptation mechanisms to salinity through EPS modifications facilitated by GB in saline habitats.

Water quality in surface bodies remains a pressing issue worldwide. While some regions have rich water quality data, less attention is given to areas that lack sufficient data. Therefore, it is crucial to explore novel ways of managing source-oriented surface water pollution in scenarios with infrequent data collection such as weekly or monthly. Here we showed sparse-dataset-based prediction of water pollution using machine learning. We investigated the efficacy of a traditional Recurrent Neural Network alongside three Long Short-Term Memory (LSTM) models, integrated with the Load Estimator (LOADEST). The research was conducted at a river-lake confluence, an area with intricate hydrological patterns. We found that the Self-Attentive LSTM (SA-LSTM) model outperformed the other three machine learning models in predicting water quality, achieving Nash-Sutcliffe Efficiency (NSE) scores of 0.71 for COD_Mn and 0.57 for NH₃N when utilizing LOADEST-augmented water quality data (referred to as the SA-LSTM-LOADEST model). The SA-LSTM-LOADEST model improved upon the standalone SA-LSTM model by reducing the Root Mean Square Error (RMSE) by 24.6% for COD_Mn and 21.3% for NH₃N. Furthermore, the model maintained its predictive accuracy when data collection intervals were extended from weekly to monthly. Additionally, the SA-LSTM-LOADEST model demonstrated the capability to forecast pollution loads up to ten days in advance. This study shows promise for improving water quality modeling in regions with limited monitoring capabilities.

Climate change and anthropogenic activities are reshaping dryland ecosystems globally at an unprecedented pace, jeopardizing their stability. The stability of these ecosystems is crucial for maintaining ecological balance and supporting local communities. Yet, the mechanisms governing their stability are poorly understood, largely due to the scarcity of comprehensive field data. Here we show the patterns of community temporal stability and its determinants across an aridity spectrum by integrating a transect survey across China's drylands with remote sensing. Our results revealed a U-shaped relationship between community temporal stability and aridity, with a pivotal shift occurring around an aridity level of 0.88. In less arid areas (aridity level below 0.88), enhanced precipitation and biodiversity were associated with increased community productivity and stability. Conversely, in more arid zones (aridity level above 0.88), elevated soil organic carbon and biodiversity were linked to greater fluctuations in community productivity and reduced stability. Our study identifies a critical aridity threshold that precipitates significant changes in community stability in China's drylands, underscoring the importance of distinct mechanisms driving ecosystem stability in varying aridity contexts. These insights are pivotal for developing informed ecosystem management and policy strategies tailored to the unique challenges of dryland conservation.

The ubiquity of refractory organic matter in aquatic environments necessitates innovative removal strategies. Sulfate radical-based advanced oxidation has emerged as an attractive solution, offering high selectivity, enduring efficacy, and anti-interference ability. Among many technologies, sulfite activation, leveraging its cost-effectiveness and lower toxicity compared to conventional persulfates, stands out. Yet, the activation process often relies on transition metals, suffering from low atom utilization. Here we introduce a series of single-atom catalysts (SACs) employing transition metals on g-C₃N₄ substrates, effectively activating sulfite for acetaminophen degradation. We highlight the superior performance of Fe/CN, which demonstrates a degradation rate constant significantly surpassing those of Ni/CN and Cu/CN. Our investigation into the electronic and spin polarization characteristics of these catalysts reveals their critical role in catalytic efficiency, with oxysulfur radical-mediated reactions predominating. Notably, under visible light, the catalytic activity is enhanced, attributed to an increased generation of oxysulfur radicals and a strengthened electron donation-back donation dynamic. The proximity of Fe/CN's d-band center to the Fermi level, alongside its high spin polarization, is shown to improve sulfite adsorption and reduce the HOMO-LUMO gap, thereby accelerating photo-assisted sulfite activation. This work advances the understanding of SACs in environmental applications and lays the groundwork for future water treatment technologies.

Evaluating environmental flow (EF) is pivotal for conserving and restoring riverine ecosystems. Yet, prevalent EF evaluations presume that a river reach's hydraulic conditions are exclusively governed by inflow discharge, presupposing a state of equilibrium in the river channel. This presumption narrows the scope of EF evaluations in expansive alluvial rivers like the Middle Yangtze River (MYR), characterized by marked channel alterations. Here we show the profound channel erosion process and its impact on EF requirements for riparian habitats within the MYR. Our research unveils that: (i) pronounced erosion has led to a mean reduction of 1.0–2.7 m in the riverbed across four sub-reaches of the MYR; (ii) notwithstanding a 37–107% increase in minimal discharges post the Three Gorges Project, the lowest river stages at some hydrometric stations diminished owing to bed erosion, signifying a notable transformation in MYR's hydraulic dynamics; (iii) a discernible rightward shift in the correlation curve between the weighted useable area and discharge from 2002 to 2020 in a specific sub-reach of the MYR, instigated by alterations in hydraulic conditions, necessitated an increase of 1500–2600 m³ s⁻¹ in the required EF for the sub-reach; (iv) it is deduced that macroinvertebrate biomass rapidly decreases as the flow entrains the riverbed substrate, with the maximum survivable velocity for macroinvertebrates being contingent on their entrainment threshold. These findings highlight the importance of incorporating channel morphological changes in devising conservation strategies for the MYR ecosystem.

Organophosphate esters (OPEs) are increasingly recognized as pervasive environmental contaminants, primarily from their extensive application in flame retardants and plasticizers. Despite their widespread presence, the intricacies of OPE bioaccumulation within aquatic ecosystems remain poorly understood, particularly the environmental determinants influencing their distribution and the bioaccumulation dynamics across aquatic food chains. Here we show that water temperature plays a crucial role in modulating the dispersion of OPE in the aquatic environment of Poyang Lake. We quantified OPE concentrations across various matrices, uncovering levels ranging from 0.198 to 912.622 ng L⁻¹ in water, 0.013–493.36 ng per g dry weight (dw) in sediment, 0.026–41.92 ng per g wet weight (ww) in plankton, 0.13–2100.72 ng per g dw in benthic invertebrates, and 0.31–3956.49 ng per g dw in wild fish, highlighting a pronounced bioaccumulation gradient. Notably, the intestines emerged as the principal site for OPE absorption, displaying the highest concentrations among the seven tissues examined. Among the various OPEs, tris(chloroethyl) phosphate was distinguished by its significant bioaccumulation potential within the aquatic food web, suggesting a need for heightened scrutiny. The propensity for OPE accumulation was markedly higher in benthic invertebrates than wild fish, indicating a differential vulnerability within aquatic biota. This study lays a foundational basis for the risk assessment of OPEs as emerging contaminants and underscores the imperative to prioritize the examination of bioaccumulation effects, particularly in benthic invertebrates, to inform future environmental safeguarding strategies.