Search Results (821)

Diffuse pollution from agricultural runoff, characterized by intermittent discharges of complex contaminant mixtures, including nutrients, pesticides, and heavy metals (HMs), poses a persistent threat to global water quality. Conventional “end-of-pipe” strategies often fail to address these decentralized, nonpoint sources. This review examines the evolution of Permeable Reactive Barriers (PRBs) from static, abiotic filters into modern Permeable Reactive Bio-Barriers (PRBBs), engineered as dynamic, fixed-bed biofilm reactors. A key advancement in PRBB efficacy is the exploitation of biofilm plasticity, particularly in response to coexistence with organic and inorganic pollutants. While heavy metals are traditionally viewed as inhibitors, this review synthesizes evidence showing that subinhibitory HM levels can act as structural and functional drivers. These metals induce the upregulation of Extracellular Polymeric Substances (EPSs), creating a “protective shield” that sequesters metals and confers functional resilience on the microbial consortia responsible for nutrient removal and pesticide biodegradation. The review analyzes contaminant removal mechanisms, highlighting the bio-chemo synergy between reactive media and biofilms, and proposes a classification framework based on target contaminants, media, and technological integration. Significant focus is placed on emerging hybrid multi-media systems designed to protect the microbial community from toxic metal shocks, alongside the integration of artificial intelligence for predictive control. While challenges in hydraulic sustainability and field validation remain, PRBBs represent a compact, low-energy, and scalable ecotechnology. PRBBs offer a strategically targeted solution within the Nature-Based Solutions toolkit for building resilient protection of aquatic ecosystems at the critical land-water interface. Full article

Lake Erhai is an important plateau freshwater lake in China. It serves not only as a crucial drinking water source for the local region but also as the core area of the Cangshan Erhai National Nature Reserve. Consequently, Lake Erhai plays an extremely significant role in the local economy, society, and ecology. Since 2000, the water quality of Lake Erhai has continuously deteriorated, showing a eutrophic trend. To identify the primary driving forces behind these water quality changes, this study employed stepwise regression analysis. Climate conditions, socio-economic development within the basin, and implementation of environmental protection measures (IEPMs) were considered influencing factors for a comprehensive and systematic analysis of Lake Erhai’s water quality. The results indicate that rising air temperature may increase total phosphorus (TP) concentration, while rainfall may elevate both TP and total nitrogen (TN) levels. In contrast, higher wind speed may reduce chemical oxygen demand (COD_Mn), TP, and TN concentrations. Socio-economic development, meanwhile, may contribute to increased COD_Mn concentration. Based on these findings, this paper proposes recommendations focusing on formulating more effective non-point source pollution control measures and strengthening water quality monitoring in Lake Erhai during summer. By identifying the key natural and anthropogenic drivers of water quality changes in Lake Erhai, this study provides a scientific basis for the development of targeted pollution control strategies and directly contributes to the protection of clean water sources. Moreover, its revelation of the coupled impacts of climate change and socio-economic activities enhances understanding of plateau lake ecosystem resilience. This insight is critical for ensuring regional ecological security and serves as a model for advancing sustainable development goals in similar lake systems worldwide. Full article

During the critical period of agricultural green transformation, clarifying the evolutionary logic of farmers’ green production behavior under a multi-stakeholder framework provides significant insights for implementing “Dual Carbon” goals, establishing long-term mechanisms for high-quality agricultural development, and resolving deep-seated contradictions in agricultural non-point source pollution. Based on the social co-governance and public participation framework, this paper constructs a tripartite evolutionary game model involving government departments, farmer groups, and the general public, grounded in cost–benefit analysis, social governance friction, and evolutionary game theory. Through simulation, the study explores the equilibrium states and the specific impacts of varying parameter values on stable points. The findings reveal that: (1) The “interest price scissors” (benefit disparity) between green and conventional production is the key determinant of farmers’ strategic equilibrium. Once this structural contradiction is resolved, green production becomes the optimal strategy. (2) Farmers are highly sensitive to marginal cost–benefit fluctuations, leading to a sequential behavioral cascade: farmers retreat first, followed by the government, and finally the public. (3) Public participation cost is the pivotal variable for activating the co-governance mechanism, and the application of digital governance tools determines the time required to reach equilibrium. (4) A “Success Paradox” exists in government regulation; incentive mechanisms must be adjusted promptly after initial success. (5) Integrated policy combinations outperform single instruments; breaking the “locked-in” state requires a policy shock of sufficient intensity. This research offers a theoretical basis and policy enlightenment for optimizing the social co-governance landscape and promoting sustainable agricultural modernization. Full article

With urbanization transforming from scale expansion to high-quality development and the increasing prominence of the ecological environment constraints of drainage basins, systematically identifying the mechanism of action of non-point source pollution from a high-quality development perspective is significant for coordinating urban development and environmental protection. Based on remote sensing data on atmospheric pollution and multi-source spatial big data such as nighttime light (NTL), LandScan population, point of interest (POI), and land use data from 2013 to 2025, this study applies methods including deposition flux analysis, deep learning fusion, bivariate spatial autocorrelation, and geographically weighted regression (GWR) to empirically analyze the spatiotemporal evolution characteristics, spatial correlation, and local impacts of high-quality urban development on non-point source pollution in the Chenghai drainage basin. We find that, firstly, non-point source pollution and high-quality urban development in the Chenghai drainage basin both present significant stage-specific and spatial heterogeneity. In other words, the two are not mutually independent spatial elements in space; instead, they are closely and significantly correlated, with their correlation types showing obvious spatial agglomeration characteristics. Secondly, the impact of high-quality urban development on non-point source pollution evolves in stages. It gradually shifts from a whole-region, homogeneous, strongly positive driving force to spatial differentiation. Specifically, from 2013 to 2017, the whole-region regression coefficients are generally greater than 0.5, meaning that urban development represents a strong, whole-region driving force promoting pollution. However, after 2017, this impact evolves into a stable spatial differentiation pattern. It mainly shows that the northern urban core area, where coefficients are greater than 0.5, maintains a continuous strong positive driving force. Meanwhile, the peripheral area, where coefficients are generally lower than 0, creates a negative inhibition effect. Based on the above rules, further analysis shows that the impact of high-quality urban development on non-point source pollution is absolutely not a simple linear relationship. Instead, it is a result of the coupling effect of multiple factors, including development stage, spatial location, and governance level. Therefore, to positively affect the ecological environment through high-quality development, model transformation and precise governance are essential. The findings of this study deepen our understanding of the transformation of urban development models and the response mechanism of non-point source pollution. They also provide a scientific basis and decision support for promoting the coordinated governance of high-quality urban development and non-point source pollution by region and stage in plateau lake drainage basins, as well as for improving the sustainable development of drainage basins. Full article

Characterizing surface runoff and the transport process of non-point source pollutants (NSPs) carried by this runoff is crucial for identifying key source areas, estimating pollution loads entering water bodies, and implementing pollution control, which is particularly important in regions dominated by smallholder farming in China. Currently, most of the commonly used NSP models originated from international countries and have shortcomings such as high data requirements, high generalization degrees, and requiring the calibration of numerous parameters in the application process. Therefore, a distributed non-point source pollution model based on the time-varying gain and stormwater runoff response was constructed, designed for application at the watershed scale. This study describes the construction of the model, introducing its principles and structure through three key modules: a rainfall–runoff module, a soil erosion module, and a pollutant migration and transformation module. The proposed model was used to simulate the rainfall–runoff, soil erosion, and nutrient migration and transformation processes at different spatiotemporal scales. Although it achieved the best performance at the monthly and annual scales, its simulation results at the daily and hourly scales still met the relevant requirements, with relative errors within 20% and Nash–Sutcliffe Efficiency (NSE) coefficients of approximately 0.7. The annual sediment delivery ratios for the Yangliu Small Watershed and the basin above the Ankang section in 2022 were determined to be 0.445 and 0.36, respectively. The pollutant processes corresponding to different runoff events in the Yangliu Small Watershed were simulated, and the average NSE for total nitrogen (TN), ammonia nitrogen (NH₃-N), nitrate nitrogen (NO₃-N), total phosphorus (TP), and soluble reactive phosphorus (SRP) were determined to be 0.69, 0.74, 0.79, 0.71, and 0.71, respectively. For the basin above the Ankang section, the NSE coefficients for the simulation of NH₃-N and TP pollutant processes were 0.78 and 0.83, respectively. The model demonstrated robust applicability across various spatial (ranging from small to large watersheds) and temporal (hourly−daily−monthly−annual) scales, and exhibited stability across different basins in a semi-humid region of China. The model is characterized by a parsimonious parameter set, ease of calibration, and strong spatiotemporal versatility, thus providing an efficient and reliable tool for non-point source pollution simulation. Full article

In the present study, we conducted three treatments with different cadmium concentrations and three different soil types selected for grape cultivation to assess the accumulation and migration characteristics of Cadmium (Cd) in the soil–grape system in different years. The change in Cd fractions in soil and the transfer and accumulation of Cd in different soil–grape systems were analyzed to evaluate the health risks of pulp cadmium accumulation to grape consumers. The results showed that after the planting of the grape, the active Cd fraction increased by 1~3 times and the stable fraction decreased by 1~3 times compared to before planting grapes. It gradually began to stabilize as the cultivation period progressed. The bioaccumulation factor (BCF) of Cd in different parts of grape was ranked as: root (0.094~2.590) > stem (0.117~2.112) > leaf (0.008~0.621) > seed (0.010~0.195) > skin (0.000~0.148) > pulp (0.000~0.156). High Cd concentration inhibited the transfer of Cd from the soil and root to the aboveground part of the grape. The Cd of grape pulp has no health risks. Cd pollution significantly altered the soil microbial community, suppressing Actinobacteria while enriching Acidobacteria. The results of this study will help to clarify migration patterns between different soil–grape systems and providing effective data and theoretical support for the management of Cd pollution in vineyard soils. Full article

Microplastics can bind with toxic metals via surface complexation and chelation, forming combined pollutants. However, research regarding the toxicological impacts of these combined pollutants on soil fauna remains limited. This study employed Folsomia candida in a 28-day incubation experiment to investigate the ecotoxicological effects of combined pollution by polylactic acid microplastics (PLA-MPs) and thallium (Tl) on the functional traits of Folsomia candida, including biology, morphology, and gut microbiota. The results showed that the combined effects of PLA-MPs and Tl on these functional traits were characterized by amplified toxicity and trait-specific responses. Morphological traits exhibited lower sensitivity to the pollution treatments compared to other indicators. Exposure to high-concentration PLA-MPs (10%) significantly affected mortality and fecundity, and reduced gut bacterial diversity. Conversely, low-concentration Tl (1 mg/kg) significantly inhibited body length and antenna length while increasing gut bacterial diversity. Structured equation modeling further revealed that the pollution treatments exerted significant negative effects on the functional traits of Folsomia candida, both directly and indirectly by altering soil properties and soil microbiota. These findings provide valuable insights into the ecotoxicological effects of combined PLA-MPs and Tl pollution on soil fauna, contributing to ecological health risk assessments of microplastics and toxic metals in terrestrial ecosystems. Full article

Increasing agricultural productivity is vital for global food security, but it poses significant risks to aquatic ecosystems through diffuse pollution. As Türkiye aims to harmonise its agricultural policies with the European Green Deal, quantifying agricultural non-point-source pollution (ANPSP) is essential for sustainable water management. This study evaluates ANPSP loads, including Total Nitrogen (TN), Total Phosphorus (TP), Chemical Oxygen Demand (COD), and Ammonia Nitrogen (NH₃-N), originating from cereal production, fertiliser application, and livestock farming across Türkiye from 2015 to 2024. By employing activity data and pollution load coefficients, the spatiotemporal dynamics of ANPSP were analysed at both national and regional levels. The results demonstrate that cereal production is the predominant source of nutrient loading (60.5% TN, 64.9% TP), whereas livestock activities account for 52.2% of the COD load. Fertiliser use contributed 23.0% and 20.6% to TN and TP loads, respectively. The Marmara, Aegean, and Central Anatolia regions were identified as high-intensity pollution hotspots. These findings provide a robust baseline for developing region-specific mitigation strategies, such as precision fertilisation and circular waste-to-energy systems, to support Türkiye’s transition toward a Zero-Pollution and sustainable agricultural future. Full article

Heavy metals in lake sediments represent typical persistent contaminants characterized by recalcitrance, bioaccumulation potential, and delayed toxic effects, thereby exerting sustained adverse impacts on lacustrine ecosystem stability and human health. Liuye Lake is a representative small-to-medium urban lake impacted by ambient domestic sewage discharge and agricultural non-point source pollution, with documented nitrogen and phosphorus enrichment. However, the contamination profile of heavy metals in its surface sediments has not been systematically investigated to date. In this work, surface sediment samples were collected from Liuye Lake, and nine heavy metal elements (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn) were determined. An integrated approach incorporating Monte Carlo simulation, the geo-accumulation index (I_geo), and the enrichment factor (EF) method was employed to assess the ecological risk and human health risk imposed by these metals. The results revealed the following: (1) Average concentrations of eight heavy metals exceeded the background values of the Dongting Lake water system, with the exception of As, and Hg displayed potential localized anomalies. (2) Surface sediments were collectively categorized as slightly contaminated, with Hg identified as the primary pollutant, followed by minor contamination of Mn, Cr, and Ni; Monte Carlo simulation further suggested a probable risk that Mn contamination could progress to moderate levels. (3) All heavy metals posed low potential ecological risk, with an overall potential ecological risk index (RI) of 62.71, where Cd, Hg, and As were the dominant contributors. (4) Both non-carcinogenic and carcinogenic risks were generally within acceptable limits, whereas children exhibited higher non-carcinogenic susceptibility relative to adults; As and Mn were the leading contributors to non-carcinogenic risk, while Cr and As dominated carcinogenic risk. This study offers a scientific foundation for the prevention and control of heavy metal pollution and the ecological management of urban lakes. Full article

To accurately manage precise feeding and water quality regulation in the rice–duck–crayfish integrated system (RDCI), the continuous monitoring of plankton and physicochemical parameters in the water was conducted from March 2022 to January 2023 in both the RDCI and the rice–crayfish continuous culture system (RCCC). The results showed that a total of 188 phytoplankton species and 92 zooplankton species were identified in the RDCI, whereas 152 phytoplankton species and 95 zooplankton species were detected in the RCCC. The phytoplankton community composition was similar between these two systems. For zooplankton, Rotifera was the dominant group. However, Chlorophyta and Bacillariophyta were the dominant phytoplankton groups. Compared with the RCCC, the RDCI exhibited lower plankton density during the crayfish-farming stage and overwintering stage, but higher plankton biomass during the crayfish-farming stage, overwintering stage, and rice maturity stage. The diversity indices, richness indices, and evenness indices of both phytoplankton and zooplankton in the RDCI were significantly higher than those in the RCCC. Correlation analysis indicated that water temperature, dissolved oxygen, total nitrogen, and ammonia nitrogen were the key environmental factors affecting plankton community structure. In summary, compared with the RCCC, the RDCI exhibits higher plankton diversity and better evenness, suggesting a more complex and stable community structure. The species composition of plankton and related indices indicate that the RDCI mitigates the degree of eutrophication in water during both the crayfish farming and the overwintering stages, while increasing nutrients levels during the rice planting stage. This approach is beneficial for reducing non-point-source pollution in agriculture and promoting green agricultural development. Full article

Field-scale nitrogen migration mechanisms in small watersheds remain poorly quantified due to insufficient representation of microtopographic heterogeneity. This study investigates nitrogen transport dynamics in a 1.27 km² agricultural watershed in China’s Jianghuai region using unmanned aerial vehicle (UAV) -derived 0.1 m digital elevation models (DEMs) and coupled hydrological–erosion modeling. The Soil Conservation Service Curve Number (SCS-CN) and Modified Universal Soil Loss Equation (MUSLE) models quantified nitrogen output loads, while the multi-flow direction algorithm simulated migration trajectories for total nitrogen (TN), ammonium, and nitrate. Results revealed strong spatial heterogeneity in nitrogen exports (watershed mean: 29.66 kg TN/km²·a), with bare land and greenhouses exhibiting the highest outputs (448.54 and 363.41 kg/km²·a) and forested areas showing minimal export (<6.1 kg/km²·a). Nitrogen migration was predominantly controlled by topographic gradients, with microtopographic features—field ridges, ditches, and buildings—physically redirecting flows and creating critical export nodes at field boundaries. DEM resolution critically affected simulation accuracy: erosion intensity displayed a non-monotonic response with an inflection point near 1 m resolution, corresponding to the median elevation difference (1.2 m) of field ridges. Structural equation modeling confirmed that high-resolution DEMs (0.1–2 m) maintained topographic control over nitrogen migration (~80% contribution), whereas 30 m DEMs reduced this influence to 30%, inducing spurious meteorological dominance. This study demonstrates that decimeter-scale DEMs are essential for accurately capturing microtopographic regulation of nitrogen transport, providing a methodological basis for precision management of agricultural non-point source pollution. Full article

Based on a bibliometric analysis of 2680 publications (1962–2024), this study elucidates the knowledge structure and intellectual evolution of research on climate change-driven nitrogen migration and transformation in inland waters, a critical issue for water security and global climate stability. The field has experienced accelerated growth since 2016, led by the United States and China. Analysis reveals a research framework centered on climate change, nitrogen, and water quality, interconnected with processes like eutrophication and denitrification. The intellectual focus has evolved from early investigations into fundamental chemical mechanisms towards a contemporary emphasis on human–climate interactions (e.g., land use), model-based predictions, and regional management solutions for nonpoint source pollution. A key finding is the bidirectional climate–nitrogen feedback, where climate alters nitrogen pathways and transformations, which in turn release greenhouse gases. The findings underscore a pivotal shift from theoretical understanding to applied, solution-oriented research. Future work must prioritize integrated multi-technique approaches, cross-ecosystem comparisons, and data-driven modeling to advance predictive capabilities and support effective nitrogen management in inland waters under a changing climate. Full article

Agricultural rivers are often silent receivers of microplastics (MPs) from diffuse, non-point sources; however, their pollution dynamics during rainfall events remain poorly understood. In this study, MP transport was investigated at three sampling points in an agricultural river catchment, where mulching films are used, and sewage sludge is not applied. Sampling was conducted in the Umeda River and its tributaries during six sampling events. MP flux exhibited a strong positive correlation with river discharge (L–Q relationship; n = 1.49–1.61, R² = 0.67–0.87). The L–Q model indicates that a tenfold increase in discharge results in approximately a 600-fold increase in MP flux and a 1000-fold increase in total suspended solid flux. MP abundance during rainfall was up to four times higher than that during baseflow, ranging from 73 ± 64 to 200 ± 111 particles/m³, while peak flux reached 6736 particles/s, with an MP mass of 811 mg/s. Regarding particle characteristics, rainfall enhanced the heterogeneity of MPs, although fragments and polyethylene/polypropylene polymers remained consistently dominant across all hydrological stages. First-flush behavior was observed at HU, with more than half of the total MP mass exported within the initial 50% of the event flow volume. These findings help to inform mitigation strategies that should prioritize a reduction in upstream plastic inputs in order to effectively manage MP transport in agricultural rivers. Full article

Bacterial pathogens secrete effector proteins that suppress plant immune responses and facilitate infection. This study focuses on Pectobacterium brasiliense NJAU180, a bacterial pathogen causing severe blackleg disease in potato plants in Inner Mongolia, China. Using exoproteomic analysis, plant-induced extracellular proteins were identified by comparing culture supernatants from P. brasiliense NJAU180 grown in minimal medium (MM) alone and in the presence of aseptically grown potato plantlets at an early growth stage (OD₆₀₀ ≈ 0.5). The results reveal PurK as a novel plant-induced extracellular protein, and deletion of purK markedly reduces virulence. PurK, N⁵-carboxyaminoimidazole ribonucleotide synthetase, is a key enzyme in de novo purine biosynthesis. Its impact on virulence is distinct from the conventional production of plant cell wall–degrading enzymes: PurK promotes motility by modulating transcription of flagellar genes, acting through its three domains as an integrated unit to infect successfully. Extracellularly detected PurK suppresses callose deposition, a PAMP-triggered immunity (PTI)-like defense, while it also triggers a strong hypersensitive response and upregulates expression of PTI marker genes such as PR2 and WRKY7 when secreted into the host plant. Although PurK interacts specifically with PurE, our data indicate that PurK’s pathogenic effects operate independently of purine biosynthesis. This study reveals a reliable experimental model for more accurate assessment of microbe–plant interactions and highlights new functional roles for PurK in P. brasiliense NJAU180 pathogenesis and identifies potential targets for disease control strategies. Full article

With rapid industrialization and urbanization, water pollution in urban rivers has become increasingly severe, posing significant threats to regional ecological environments and water security. The Puning section of the Lianjiang River in Guangdong Province, China, suffers from complex pollution originating from multiple sources, including domestic sewage, industrial wastewater, and agricultural non-point source pollution. This underscores an urgent need for integrated river pollution control in the region. In this study, a coupled hydrodynamic-water quality model was established to systematically analyze and simulate water quality conditions in the Puning section. A total of 22 pollution control scenarios were proposed and evaluated. The results indicated that most monitoring sections in the Puning segment failed to meet the Class V surface water quality standards, with notably high concentrations of chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), and total phosphorus (TP). Numerical simulations revealed that the multi-source interception scenario—simultaneously intercepting inflows at Tiande Bridge (Baikeng Lake), Dayangmei (Liusha Zhonghe), and Liudoupu (Liusha Zhonghe)—performed best in reducing pollutant concentrations. Specifically, this scenario achieved reductions exceeding 90% in NH₃-N and TP concentrations. Furthermore, the study demonstrates that for basins with complex pollution sources, integrated management strategies—including the construction of wastewater treatment facilities, control of point and non-point sources, and ecological restoration measures—can effectively improve water quality and optimize the water environmental capacity. These findings provide theoretical and technical support for water environment management in the Lianjiang River Basin and offer valuable insights for water quality management in similar regions. Full article