Search Results (481)

Accurate estimation of ship emissions is essential for the effective enforcement of emission control policies in inland waterways. However, existing “bottom-up” models face significant challenges owing to severe data scarcity for inland ships, particularly regarding ship static parameters. This study proposes a novel data fusion and machine learning framework to address this issue. The methodology integrates real-time SO₂ and CO₂ pollutant concentrations on the Nanjing Dashengguan Yangtze River Bridge, Automatic Identification System (AIS) data, and meteorological information. To address the scarcity of design data for inland ships, web scraping was used to extract basic parameters, which were then used to train five machine learning models. Among them, the XGBoost model demonstrated superior performance in predicting the main engine rated power. A refined activity-based emission model combines these predicted parameters, ship operational profiles, and specific emission factors to calculate real-time emission source strengths. Furthermore, the model was validated against field measurements by comparing the calculated and measured emission source strengths from ships, demonstrating high predictive accuracy with R² values of 0.980 for SO₂ and 0.977 for CO₂, and MAPE below 13%. This framework provides a reliable and scalable approach for real-time emission monitoring and supports regulatory enforcement in inland waterways. Full article

Heavy metal (HM) pollution in the southern Tibetan Plateau has attracted global attention. Prior studies have noted HM enrichment and water issues in Tibetan rivers, but seasonal variation, sources, and controlling factors remain unclear. This study measured HM levels in high-frequency river water and suspended particulate matter (SPM) at the Lhaze on the Yarlung Tsangpo River (YTR), assessing pollution and ecological risks. The results showed that the overall surface water quality was excellent. The SPM overall showed a low potential ecological risk. Nevertheless, pollution risks were observed for As and B in river water samples during the dry season. Additionally, As and B were found to be in moderate-to-heavy pollution levels for SPM samples, and there was a moderate potential ecological risk for As during the dry season. The source identification results revealed geothermal spring input as the primary factor contributing to the ecological risks of As and B in the YTR water. While rock weathering dominates the origins of Al, Mn, and Fe in river water, with contributions ranging from 64% to 90% of their total amounts, water availability during weathering reactions in the dry and wet seasons serves as the primary control factor for their release, mobility in the YTR basin, and concentration in the river water. As an erosion product, SPM exhibited no significant seasonal changes in metal element concentrations and showed a moderate correlation with water discharge, indicating a stable HM ecological impact from the erosion process in the YTR basin. Full article

Hydrogen energy has been recognized as the most promising secondary energy source due to high energy density, abundance, and environmental friendliness. Among hydrogen production techniques, water electrolysis has emerged as a key research focus, owing to its high efficiency, operational simplicity, controllability, and pollution-free nature. However, the anodic oxygen evolution reaction (OER) involves a high overpotential and sluggish kinetics, which severely constrain the overall efficiency of water electrolysis. Transition metal oxide (TMO) catalysts are regarded as promising substitutes for noble-metal-based catalysts, given their advantages of low cost, elemental abundance, tunable electronic structures, and favorable stability. This review systematically elaborates on the reaction mechanisms of TMO catalysts, including the adsorbate evolution mechanism (AEM) and lattice oxygen mechanism (LOM), and summarizes various performance-enhancement strategies, such as morphology control, doping engineering, support engineering, and heterostructure construction. Furthermore, it outlines current challenges and future research directions, covering precise synthesis and structural control, identification of active sites and mechanistic elucidation, and stability and degradation issues, as well as multifunctional applications and broad-pH-range adaptability. The aim is to offer theoretical guidance and technical insights for designing and developing high-performance TMO electrocatalysts. Full article

Microplastics in lake waters are a global problem that is gaining increasing attention from researchers. However, most studies to date have focused on the water column. Much less attention has been paid to the problem of sediment pollution at the shoreline, the zone where water and land meet, and microplastics accumulate and degrade. This study assessed microplastic pollution in shoreline sediments in six urban lakes, which are exposed to varying degrees of recreational pressure. Fourier transform infrared spectroscopy (FTIR) was used in the qualitative analysis. The concentration of microplastics in the studied lakes was not high, ranging from 5.2 to 42 particles per kg dw⁻¹. More than half of the plastics detected were filaments. Nine different types of synthetic polymers were identified in the material collected from the shorelines of the studied urban lakes. Polypropylene (PP) was the most frequently found polymer. The characteristics of the collected material allowed for the identification of potential sources of pollution, most of which can be linked to various forms of recreation. The lake most heavily used for recreation was characterized by the highest concentration of microplastics in shoreline sediments, the greatest morphological diversity, and the greatest variety of polymer types. The results of this study indicated that recreation could be a significant source of microplastic pollution and highlighted the need for sustainable recreational use of lakes. Full article

Rural and agricultural runoff continues to pose a threat to water quality and human health despite a plethora of research identifying likely causes. Large livestock operations and leaking septic systems have proven to be significant sources of both nutrients and bacteria in the form of algal blooms and antibiotic-resistant Escherichia coli. These impacts are often witnessed on a watershed scale. Implementing remedies is complicated, as livestock operations are defined as point-source facilities under the USA Clean Water Act (CWA) but regulated as non-point-source entities under a NPDES CAFO general permit. Non-point-source pollutant assessment of watersheds involves a wide array of sampling parameters that focus primarily on impacts after-the-fact and lack regulatory teeth. This watershed management approach is not sustainable, as evidenced by the continual degradation of our rural watersheds. This study lays out streamlined methods and techniques incorporating focused parameters that can infer point-source pollutant pathways even in already impaired waterways. We applied this methodology to the Pine River Watershed in central Lower Michigan after the appearance of an algal bloom downstream from several potential nutrient inputs. Findings show that the application of these unique methods and techniques results in the successful identification of point-source inputs. These methods are inexpensive and demand few resources, and hence they are easily reproduced and replicated. Therefore, by regulating large livestock operations as point-source discharge entities, it is possible for local communities, educational institutions, and regulatory agencies to identify likely pollutant sources in a way that promotes higher water quality and long-term sustainability. Full article

To address the challenges in simulating nonpoint source pollution inflow, pollutant source distribution, and migration pathways in plain river network regions, this study innovatively proposes an optimized technical framework based on the NDR module of the InVEST model. Through land use data reconstruction, DEM negative value correction, and flow accumulation threshold optimization, the framework effectively resolves key issues including pollutant receiving water identification, runoff path simulation, and pollutant migration termination determination, significantly enhancing the model’s applicability to complex river systems. Using the Taipu River as a case study, this research investigates the spatial distribution characteristics of nonpoint source pollution load inflow and its sources in major rivers within plain river network regions. Results show that in 2023, total nitrogen and total phosphorus inflows into the Taipu River were 1004.11 t/a and 83.80 t/a, respectively, with pollution loads primarily originating from the Wangning Polders in the midstream, Chengnan New District Small Watersheds and Chang Yang River Small Watersheds, mainly entering the Taipu River through tributaries such as the Beijing-Hangzhou Grand Canal and Nanzha Port. Calculations based on measured data indicate total nitrogen and total phosphorus inflows into the Taipu River were approximately 1300 t/a and 90 t/a, respectively, consistent with model predictions. Building on environmental capacity assessment results, this study proposes targeted recommendations for precision-based nonpoint source pollution control in the Taipu River basin. The findings provide scientific evidence and technical paradigms for nonpoint source pollution management and sustainable management in plain river network regions. Full article

This study focuses on a rapidly urbanizing coastal plain where river networks serve as critical pathways for pollutant transport to nearshore waters. Under frequent sluice control and sluggish hydrodynamics, pollutants accumulate in channels and are subsequently flushed during intense rainfall or sluice-opening events, increasing pollutant loads in downstream estuaries. Based on 2017–2024 water quality monitoring data, integrated multi-source environmental factor analysis and unmanned patrol boat technology, systematic water quality assessment and pollution source identification were conducted. Significant spatial heterogeneity was observed: phosphorus and nitrogen pollution dominated in the eastern region, whereas the permanganate index was more prominent in the western part of the network. Identification of abrupt water quality change sections revealed industrial wastewater as the primary contributor to phosphorus and nitrogen, whereas permanganate index pollution originated widely from aquaculture, agriculture, and industrial discharges. Atmospheric deposition likely provides a non-negligible contribution to phosphorus and nitrogen input, with fluxes strongly correlated to rainfall. Sediment release posed internal risks of carbon and phosphorus, with intensity positively linked to pollution levels. This study elucidates the water quality characteristics and multi-source pollution mechanisms in typical coastal river networks under rapid economic development. Therefore, it provides a scientific basis for precise regional water environment management and coastal water quality protection. Full article

A major goal of fecal pollution monitoring in the environment is to identify point sources of fecal contamination that may pose potential health risks due to animal- and human-specific pathogens. Ideal source tracking markers should have high host specificity and can be employed for the unambiguous identification of the host/fecal point sources. Conserved signature proteins (CSPs) are a class of unique, phylogenetically coherent indicators that are specific to a given taxon (e.g., genus or species). In this study, we report the identification and characterization of a new CSP, whose gene (designated as CSP-DV) is present in a single copy, and for whom homologs showing a high degree of sequence similarity are found only in genomes of Phocaeicola dorei and Phocaeicola vulgatus, two commensal species commonly found in the human gut and feces. We developed a qPCR method targeting this CSP gene to explore its usefulness as a human source tracking marker. We confirmed that the CSP-DV marker showed an absolute human sensitivity (100%) but some cross-reactivities in chicken, cats, dogs, rabbits, and rodents. In recreational water, the CSP-DV marker gene levels were well correlated with those of HF183, a well-validated human marker that predominantly targets the 16S rRNA gene of P. dorei, suggesting that it can be a new potential source tracking tool for human fecal contamination in specific environmental waters. In summary, our CSP-DV marker targets Phocaeicola clade-specific microbes and can provide an additional approach independent of the 16S rRNA gene to detect human sources of fecal pollution. Full article

Lead and zinc pollution is a prevalent issue in agricultural soils surrounding lead and zinc mines, posing a serious risk to crop growth and soil health. Heavy metal-resistant, plant growth-promoting bacteria (PGPB) capable of supporting plant development under high metal exposure have significant potential for mitigating these deleterious effects. Here we isolated and identified the Pb- and Zn-resistant and plant growth-promoting bacterial strain Serratia ureilytica T6 based on 16S rRNA and average nucleotide identity (ANI) analysis. Furthermore, 14 strains (T1–T14) from a rice paddy soil irrigated by Pb-Zn mine effluent were isolated and identified, and their phytopromoting characteristics were determined. Genome analysis of S. ureilytica T6 showed a genome size of 5,102,941 bp, with G + C content of 59.74%. A total of 4822 genes were annotated by RAST, among which 15 genes were putatively associated with Pb-Zn resistance. The genome of S. ureilytica T6 was found to possess multiple genes associated with probiotic properties by a comparative analysis of KEGG, GO, and COG databases. Several taxonomic identifications of S. ureilytica T6 revealed that strain T6 is Gram-negative, facultative anaerobic and motile. The pH growth range of S. ureilytica T6 was between 4.00 and 9.50; temperature growth range was 4–37 °C; NaCl tolerance was 0–9%. S. ureilytica T6 displayed a high tolerance to a variety of heavy metals, with minimum inhibitory concentrations of 1.5 and 9 mmol·L⁻¹ for Pb and Zn. S. ureilytica T6 can utilize a variety of carbon sources and nitrogen sources. T6 has the ability to produce indole-3-acetic acid (IAA), siderophore, and phosphorus and potassium solubilization, and it was initially judged that strain T6 has the potential for plant growth-promoting ability. Different plant growth-promoting effects of T6 inoculations were observed in improving rice biomass, plant height, etc. We observed that with increasing Pb and Zn stress, SOD activity first increased and then decreased, while POD and CAT activities gradually decreased. The addition of S. ureilytica T6 significantly enhanced the activities of SOD, POD, and CAT in rice seedlings under low to moderate Pb and Zn stress but had no significant effect under high concentrations (150 mg·L⁻¹) of Pb or Zn. In addition, S. ureilytica T6 has the potential to be used as a phytoremediation tool. Full article

In recent years, the public environmental protection consciousness has improved regarding the source of drinking water. However, the risk status and sources of heavy metals (HMs) in the soil around drinking water sources remain unclear. The typical Drawdown Zone (DZ) of Danjiangkou Reservoir is taken as an example in this study. Pollution levels of HMs and associated ecological and human health risks were evaluated under four land-use types during the low-water-level period. The sources of 10 HMs were determined using the positive matrix factorization (PMF) model and correlation analysis. Quantitative source-oriented risk identification was then conducted by integrating risk characteristics with source apportionment. The results indicate that soils in the study area are generally slightly polluted, with comprehensive potential ecological risks at a medium level. Farmland soils exhibit the highest pollution and ecological risk levels, particularly for Hg and Cd. Our Monte Carlo simulation-based human health risk assessment shows that, compared with non-carcinogenic risks, carcinogenic risks should be given further attention. Farmland poses higher health risks than other land-use types, and children are more vulnerable than adults. Four main sources were identified: transportation sources (29.5%), agricultural activities (32%), natural sources (19.3%), and atmospheric deposition (19.2%). The source-oriented risk assessment indicates that agricultural activities are the priority control source for ecological risks (64.7%), with Hg as the primary control element. Transportation and agricultural sources are the primary contributors to carcinogenic risks in children (57.1%) and adults (57.1%), with Ni as the primary control element. Full article

In recent decades, significant efforts have been devoted to constructing energy-efficient buildings, providing comfortable indoor environments. However, measures such as enhanced airtightness, while reducing infiltration through the building envelope, might consequently reduce natural ventilation. This reduction is a critical concern because natural ventilation is an essential factor in controlling indoor air quality (IAQ), and its diminution could therefore worsen IAQ. Sick building syndrome has emerged as a term used to describe health hazards linked to the time spent indoors but with no particular cause. Since people spend most of their time indoors, the demand for continuous and real-time IAQ management to reduce human exposure to pollutants has increased considerably. In this context, low-cost sensors (LCS) for IAQ monitoring have become popular, driven by recent technological advancements and increased awareness regarding indoor air pollution and its negative health impacts. Although LCS do not meet the performance requirements of reference and regulatory equipment, they provide informative measurements, offering high-resolution monitoring, emission source identification, exposure mitigation, real-time IAQ assessment, and energy efficiency management. This perspective article proposes a general model for LCS systems (and subsystems) implementation and presents a prospective analysis of their strengths and limitations for IAQ management, reviews the literature regarding sensor system technologies, and offers design recommendations. It provides valuable insights for researchers and practitioners in the field of IAQ and discusses future trends. Full article

Microplastic pollution in riverine ecosystems poses critical environmental challenges, yet current modeling approaches inadequately capture the spatial heterogeneity and topological complexity of fluvial systems. This study develops an innovative spatiotemporal graph convolutional network (ST-GCN) framework that integrates hydrological connectivity, flow parameters, and microplastic characteristics for simultaneous migration pathway identification and pollution source tracing. This model constructs multi-scale graph representations encoding system structure and transport dynamics, implements spatial-temporal convolution layers with adaptive attention mechanisms, and employs a backpropagation-based algorithm for inverse source identification. Validation using 18 months of field observations from 45 monitoring nodes across a 127 km river reach demonstrates 87.3% pathway prediction accuracy and 94.3% source localization accuracy (R² = 0.841, p < 0.001), representing substantial improvements over conventional advection–diffusion models. The framework successfully identified three pollution sources during a real contamination incident within 6 h of detection, enabling rapid regulatory intervention. This research advances environmental modeling by demonstrating that graph neural networks effectively capture transport processes in networked hydrological systems, providing practical tools for watershed management and evidence-based pollution control decision-making. Full article

Air pollution, particularly fine particulate matter (PM_2.5) and ozone (O₃) pollution, poses serious challenges to environmental quality and sustainable development. The Tibetan Plateau, often described as the “Third Pole,” functions as a key ecological shield for China and exerts wide-reaching influence on global climate systems, hydrological cycles, and cross-regional pollution transport. To better clarify the driving mechanisms of air pollution in this sensitive region, we propose an integrated MRG–HSW framework, which, for the first time, systematically couples statistical modeling and trajectory analysis by combining multivariate regression, residual-based screening, and HYSPLIT–WCWT trajectory analyses. Taking Qinghai Province as a case study, ERA5 and GDAS1 reanalysis products were coupled with in situ monitoring to identify the relative contributions of local emissions and long-range atmospheric transport. The results show that, in low-elevation zones, PM_2.5 levels are largely governed by local anthropogenic activities (R² = 0.631–0.803), whereas O₃ concentrations respond more strongly to meteorological variability (R² = 0.529–0.779). At higher elevations, however, local explanatory factors weaken, and long-range transport from the Hexi Corridor, Qaidam Basin, and even South Asia becomes the dominant influence for both pollutants. Additional sensitivity tests confirm that the framework performs robustly under diverse meteorological and seasonal conditions. Collectively, this work not only establishes a transferable methodology for source attribution in plateau environments but also underscores the pivotal role of the Tibetan Plateau in sustaining regional air quality and global environmental stability. Full article

Exploring the spatiotemporal pattern of water quality and identifying pollution sources is crucial for achieving precise management of reservoir watersheds. This study is based on monthly water quality data from 9 monitoring stations in the upstream watershed of Guanting Reservoir in 2024, combined with an improved water quality index method (WQI) and multivariate statistical analysis (clustering, discrimination, principal component and factor analysis), to reveal the spatiotemporal variation characteristics of water quality and pollution sources. The results show (1) significant spatiotemporal heterogeneity. In terms of time, the water quality is worst during the summer rainy season (June August), indicating that the pollution load input from surface runoff exceeds the dilution effect of rainfall. In terms of space, the water quality deteriorates significantly downstream along the river network, with the most prominent pollution occurring in the entrance area. (2) The results also show clear identification of key indicators and dominant pollution sources. Discriminant analysis shows that BOD₅ and DO are key indicators for distinguishing rainy and dry seasons, while TN, TP, COD, COD_Mn, and F can effectively distinguish spatial clusters. Factor analysis further revealed that organic pollution (originating from domestic and industrial wastewater) and nutrient pollution (mainly from agricultural non-point sources) are the dominant factors. This study confirms that pollution input during rainfall is the primary driving factor for water quality deterioration, and human activities have led to the cumulative effect of pollutants along the river network. Based on this suggestion, differentiated and precise governance strategies should be implemented according to the spatiotemporal differentiation characteristics to improve the water environment quality of the upstream watershed of Guanting Reservoir. Full article

This study is based on data obtained as part of continuous monitoring of small gas impurities (SO₂, NO₂, NO), mass concentration of aerosol particles PM_2.5 and meteorological parameters, which was first implemented at the Tankhoi observation point (southeastern coast of Lake Baikal, Russia) from October 2023 to May 2025. Statistical methods and the non-parametric wind regression receptor model (NWR) were used to analyze temporal variability and identify sources of pollution. It was found that the concentrations of gas impurities have a clearly pronounced winter maximum: the median values for sulfur dioxide and nitrogen in winter reached 9.2 μg/m³ and 13.8 μg/m³, respectively, which is associated with emissions from coal-fired thermal power plants and unfavorable meteorological conditions (inversions, low boundary layer height). In contrast to gases, PM_2.5 demonstrated a summer peak up to 43.5 μg/m³ in July–August 2024 due to abnormally hot weather and forest fires. The daily course of sulfur dioxide was characterized by an atypical daily maximum caused by the convective transport of polluted air masses from the upper layers of the boundary layer. During this period, higher concentrations of sulfur dioxide caused by long-range high-altitude transport of emissions from regional thermal power plants can reach the ground surface, leading to an increase in their concentration in the near-surface layer. Using the NWR model, the influence of regional thermal power plants located 100–150 km northwest of the station on the levels of SO₂ and NO₂ was confirmed. The results also highlight the contribution of local sources, such as vehicles, stoves, and shipping, to the formation of NO and PM_2.5. Full article