How sediment dredging alters phosphorus dynamics in a lowland rural river?

China's lowland rural rivers are facing severe eutrophication problems due to excessive phosphorus (P) from anthropogenic activities. However, quantifying P dynamics in a lowland rural river is challenging due to its complex interaction with surrounding areas. A P dynamic model (River-P) was specifically designed for lowland rural rivers to address this challenge. This model was coupled with the Environmental Fluid Dynamics Code (EFDC) and the Phosphorus Dynamic Model for lowland Polder systems (PDP) to characterize P dynamics under the impact of dredging in a lowland rural river. Based on a two-year (2020-2021) dataset from a representative lowland rural river in the Lake Taihu Basin, China, the coupled model was calibrated and achieved a model performance (R2>0.59, RMSE<0.04 mg/L) for total P (TP) concentrations. Our research in the study river revealed that (1) the time scale for the effectiveness of sediment dredging for P control was ∼300 days, with an increase in P retention capacity by 74.8 kg/year and a decrease in TP concentrations of 23% after dredging. (2) Dredging significantly reduced P release from sediment by 98%, while increased P resuspension and settling capacities by 16% and 46%, respectively. (3) The sediment-water interface (SWI) plays a critical role in P transfer within the river, as resuspension accounts for 16% of TP imports, and settling accounts for 47% of TP exports. Given the large P retention capacity of lowland rural rivers, drainage ditches and ponds with macrophytes are promising approaches to enhance P retention capacity. Our study provides valuable insights for local environmental departments, allowing a comprehensive understanding of P dynamics in lowland rural rivers. This enable the evaluation of the efficacy of sediment dredging in P control and the implementation of corresponding P control measures.

Development of a coupled model to simulate and assess arsenic contamination and impact factors in the Jinsha River Basin, China.

With the increasing severity of arsenic (As) pollution, quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies. Taking the industrial-intensive Jinsha River Basin as typical area, a two-dimensional hydrodynamic water quality model coupled with Soil and Water Assessment Tool (SWAT) model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution. The effects of hydro-climate change, hydropower station construction and non-point source emissions on As were quantified based on the coupled model. The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream. Due to the enhanced rainfall, the As concentration was significantly higher during the rainy season than the dry season. Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration, but also affected the adsorption and desorption of As in sediment. Furthermore, As concentration increased with the input of non-point source pollution, with the maximum increase about 30%, resulting that non-point sources contributed important pollutant impacts to waterways. The coupled model used in pollutant behavior analysis is general with high potential application to predict and mitigate water pollution.

Deciphering environmental factors influencing phytoplankton community structure in a polluted urban river.

Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River-which is the longest river in China. As phytoplankton are sensitive indicators of trophic changes in water bodies, characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control. Here, we used direct microscopic count and environmental DNA (eDNA) metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin (Chengdu, Sichuan Province, China). The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis. Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling. At the phylum level, the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta, Chlorophyta, and Cyanophyta, in contrast with Chlorophyta, Dinophyceae, and Bacillariophyta identified by eDNA metabarcoding. In α-diversity analysis, eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method. Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios > 16:1 in all water samples. Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth. The results could be useful for implementing comprehensive management of the river basin environment. It is recommended to control the discharge of point- and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients (e.g., Jianyang-Ziyang). Algae monitoring techniques and removal strategies should be improved in 201 Hospital, Hongrihe Bridge and Colmar Town areas.

Phytoplankton dynamics in a shellfish farming lagoon in a deltaic system threatened by ongoing climate change.

Global climate change has generated an increasing number of environmental problems, especially in Mediterranean coastal areas, such as the Po Delta (PD), where shellfish production has undergone an overall decline because of strong environmental changes. The present study is centred on assessing the fundamental ecological aspects in one of the most crucial European shellfish production lagoons, Sacca degli Scardovari (SC), addressing phytoplankton community parameters directly affecting shellfish production, namely, chemotaxonomic composition, size fractions, and total biomass, in relation to the physicochemical properties of the water column and mussel filtering activity. Our findings suggest that the phytoplankton community structure, its role within the lagoon food web and its production cycles depend on two distinct allogenic inputs, which shape the community differently and exert substantial control on shellfish production. At the same time, the suspended mussel biomass strongly controls the phytoplankton size composition, as their growth is largely supported by nanophytoplankton. As the Po River collects the drainage waters of the Italian side of the entire Alpine Arch, the phytoplankton dynamics reported here represent a useful baseline for further addressing issues of climatic changes affecting lagoon ecology. We believe that our study presents an innovative tool for the planning and management of interventions aimed at enhancing national mussel production without neglecting aspects of environmental protection or the integrity of the coastal system, with significant scientific implications.

Spatial and temporal characteristic of PM2.5 and influence factors in the Yellow River Basin.

The Yellow River Basin has been instrumental in advancing ecological preservation and fostering national high-quality development. However, since the advent of China's reform and opening-up policies, the basin has faced severe environmental pollution issues. This study leverages remote sensing data from 1998 to 2019. As per the "Basin Scope and Its Historical Changes" published by the Yellow River Conservancy Commission of the Ministry of Water Resources, the Yellow River Basin is categorized into upstream, midstream, and downstream regions for analysis of their spatial and temporal distribution traits using spatial autocorrelation methods. Additionally, we employed probes to study the effects of 10 factors, including mean surface temperature and air pressure, on PM2.5. The study findings reveal that (1) the annual average concentration of PM2.5 in the Yellow River Basin exhibited a fluctuating trend from 1998 to 2019, initially increasing, then decreasing, followed by another increase before ultimately declining. (2) The air quality in the Yellow River Basin is relatively poor, making it challenging for large-scale areas with low PM2.5 levels to occur. (3) The PM2.5 concentration in the Yellow River Basin exhibits distinct high and low-value concentration areas indicative of air pollution. Low-value areas are predominantly found in the sparsely populated central and southwestern plateau regions of Inner Mongolia, characterized by a better ecological environment. In contrast, high-value areas are prevalent in the inland areas of Northwest China, with poorer natural conditions, as well as densely populated zones with high energy demand and a relatively developed economy. (4) The overall population density in the Yellow River Basin, as well as in the upstream, midstream, and downstream regions, serves as a primary driving factor. (5) The primary drivers in the middle reaches and the entire Yellow River Basin remain consistent, whereas those in the upper and lower reaches have shifted. In the upstream, air pressure emerges as a primary driver of PM2.5, while in the downstream, NDVI and precipitation become the main influencing factors.

Hg, Cd, and Pb in fish of the Moulouya River, Morocco, and human health risk.

Concentrations of toxic metals (Hg, Pb, and Cd) were determined in the muscles of Lepomis macrochirus, Barbus callensis, and Barbus nasus caught from the Moulouya River of Morocco by graphite furnace (for Pb and Cd) and cold vapour (for Hg) atomic absorption spectrometry, after acid digestion. Although the concentration of metals in some species was relatively high, no health risk has been identified in comparison to the maximum limits as set by the European Commission. The order of increasing concentrations was Cd < Hg < Pb. Calculated Target Hazard Quotients and Hazard Indices were below 1, indicating that the intake of metals via consumption of the muscles of both fish species does not represent a hazard to human health.

Spatiotemporal distribution, risk levels, and transport variations in neonicotinoids and fipronil and its metabolites cross a river-to-sea continuum.

Neonicotinoids (NEOs) and fipronil are widely used in pest control, but their spatiotemporal distribution and risk levels in the "river-estuary-bay" system remain unclear. Between 2018 and 2021, 148 water samples from rivers to inshore and offshore seawater in Laizhou Bay, China were collected to investigate the presence of eight NEOs and fipronil and its metabolites (FIPs). Significant seasonal variations in NEOs were observed under the influence of different cultivation practices and climatic conditions, with higher levels in the summer than in the spring. The average concentrations of total neonicotinoids (ΣNEOs) and ∑FIPs decreased from rivers (63.64 ng/L, 2.41 ng/L) to inshore (22.62 ng/L, 0.14 ng/L) and offshore (4.48 ng/L, 0.10 ng/L) seawater of Laizhou Bay. The average concentrations of ΣNEOs decreased by 85.3 % from 2018 to 2021. The predominant insecticides in the study area were acetamiprid, thiamethoxam, imidacloprid, and fipronil sulfone, with a gradual shift toward low-toxicity and environmentally friendly species over time. Influenced by agricultural intensity, ∑NEOs were mostly distributed in the Yellow River, Xiaoqing River, and their estuaries, where they pose chronic ecological risks. However, FIP exhibited high risk in certain rivers and sewage treatment plants owing to the use of animal repellents or landscape gardening insecticides. This study provides evidence of the transfer of NEOs and FIPs from rivers to the ocean and also clarifies their transition dynamics and changes in risk levels from rivers to oceans. Additionally, the study offers data support for identifying critical pesticide control areas.

Spatio-temporal characteristics and multi-scale risk identification of pollution load based on sensitivity analysis in small watersheds located in Tuojiang River Basin, China.

High-quality development of water resources supports high-quality socio-economic development. High-quality development connects high-quality life, and clarifying the key management contents of small watersheds plays an important role in building ecologically clean small watersheds and promoting regional production and life. Previous research on pollution loads has focused on examining the impact of various external drivers on pollution loads but still lacks research on the impact of changes in pollution sources themselves on pollution loads. In this study, sensitivity analysis was used to determine the impact of changes from different sources on the total pollution loads, which can recognize the critical pollution sources. We first employed the pollutant discharge coefficient method to quantify non-point source pollution loads in the small watershed in the upstream Tuojiang River basin from 2010 to 2021. Then, combination sensitivity analysis with Getis-Ord Gi* was used to identify the critical sources and their crucial areas at the global, districts (counties), and towns (streets) scales, respectively. The results indicate: (1) The pollution loads of COD, NH3-N, TN, and TP all show a decreasing trend, reducing by 18.3%, 16.2%, 18.6%, and 28.1% from 2010 to 2021, respectively; (2) Livestock and poultry breeding pollution source is the most critical source for majority areas across watershed; (3) High-risk areas are mainly concentrated in Jingyang district and its subordinate towns (streets). There is a trend of low-pollution risk areas transitioning to high-pollution risk areas, with high-risk areas predominantly concentrated in the southeast and exhibiting a noticeable phenomenon of pollution load spilling around. This study can promote other similar small watersheds, holding significant importance for non-point source pollution control in small watersheds.

Enhanced river suspended sediment concentration identification via multimodal video image, optical flow, and water temperature data fusion.

Monitoring suspended sediment concentration (SSC) in rivers is pivotal for water quality management and sustainable river ecosystem development. However, achieving continuous and precise SSC monitoring is fraught with challenges, including low automation, lengthy measurement processes, and high cost. This study proposes an innovative approach for SSC identification in rivers using multimodal data fusion. We developed a robust model by harnessing colour features from video images, motion characteristics from the Lucas-Kanade (LK) optical flow method, and temperature data. By integrating ResNet with a mixed density network (MDN), our method fused the image and optical flow fields, and temperature data to enhance accuracy and reliability. Validated at a hydropower station in the Xinjiang Uygur Autonomous Region, China, the results demonstrated that while the image field alone offers a baseline level of SSC identification, it experiences local errors under specific conditions. The incorporation of optical flow and water temperature information enhanced model robustness, particularly when coupling the image and optical flow fields, yielding a Nash-Sutcliffe efficiency (NSE) of 0.91. Further enhancement was observed with the combined use of all three data types, attaining an NSE of 0.93. This integrated approach offers a more accurate SSC identification solution, enabling non-contact, low-cost measurements, facilitating remote online monitoring, and supporting water resource management and river water-sediment element monitoring.

A novel nonlinear direct-mapping approach for multiple time scale driving force analysis of surface water quality variations under intense human interference.

Identifying the driving forces of surface water quality variations is crucial for urban environmental management, especially in densely populated regions. Statistic mapping is an approach that allows researchers to directly explore the response of surface water quality to potential drivers. Conventionally, these methods encounter a mixture of issues, including nonlinear relationships and information on multiple time-scale, caused by disparities in the influencing frequencies and degrees of driving factors. In this research, a nonlinear direct-mapping approach was developed to quantitatively analyze the driving force of surface water quality under multiple time scales. This approach separated the fluctuation and trend information from water quality data and then established a direct-mapping relationship, thereby achieving the visible multilayer structure containing both linear and nonlinear information from the time scale. Typical water pollutants including total nitrogen (TN) and total phosphorus (TP) in the Pearl River Delta (PRD), were used to verify the methodology and compare its ability to analyze driving forces with traditional statistic approaches. The results demonstrated that this approach could establish a visual multilayer mapping structure with strong interpretability, which effectively captured the contained nonlinear information, thus improving the fitting degree by 12.43% compared with traditional methods. Moreover, it successfully identified the dominant driving forces of TN and TP in the PRD as human activities related to NO2 and PM and natural factors. Its application in the changing environment demonstrated a potentially increased risk of TP in the PRD under multiple scenarios. Overall, this approach could serve as a reliable reference for pollution early warning in the short term and for industrial structure adjustment planning in the long term.

Spatiotemporal pattern and obstacle factors of coupling relationship between habitat quality and urbanization level in the Yellow River Basin, China.

Land use change stands as the primary factor influencing habitat quality (HQ). Clarifying the spatiotemporal change and the obstacle factors of the coupling relationship between HQ and urbanization level (UL) can provide imperative references for achieving sustainability in the Yellow River Basin (YRB). This study is based on the InVEST model, spatial autocorrelation, and obstacle factor analysis to measure the spatiotemporal dynamics and impediments of the coupling relationship between HQ and UL from 2000 to 2020 in the YRB. The findings were as follows: (1) From 2000 to 2020, the HQ showed a tendency of rise first and then fall, with the pattern of "High in the middle and west, low in the east"; (2) from 2000 to 2020, the UL had an upward trend, with the pattern of "Low in the west, high in the middle and east"; (3) the coupling and coordination level of HQ and UL in the YRB changed from extreme incoordination to verge of coordination, and it had a distribution pattern of "High in the east, low in the west", with the high-value area expanding to the east and the low-value area shrinking to the west. (4) Location condition, climate, proportion of construction land, vegetation index, and proportion of non-agricultural employment are the main obstacle factors that determined the coupling and coordination of the HQ and UL.

Profiles, drivers, and prioritization of antibiotics in China's major rivers.

Through a systematic review of literature references from 2007 to 2022, we compiled a comprehensive national dataset comprising over 67,000 records and covering information on 129 antibiotics detected in the surface water and sediments of China's major rivers. Our analysis revealed notably high antibiotic concentrations in the Liaohe and Yellow Rivers. Among the antibiotics examined, sulfonamides, quinolones, and tetracyclines exhibited relatively high median concentrations in river water. Regional distribution analysis highlighted increased antibiotic levels in Shandong and Tianjin compared to other areas. Partial least squares path modeling revealed that animal production and pollution discharge positively influenced antibiotic levels in river water, whereas natural and socioeconomic factors had negative impacts. Based on the ecological risk assessment, we formulated a prioritized national list of antibiotics, with sulfonamides having the largest number of entries, followed by quinolones. Importantly, our analysis revealed a declining trend in antibiotic concentrations and the associated risk levels across China during the study period. This study not only enhances our understanding of antibiotic distribution in China's water systems, but also contributes to the development of a scientifically sound approach for prioritizing antibiotics. Ultimately, these findings will inform targeted antibiotic management and control strategies. ENVIRONMENTAL IMPLICATION: Antibiotics, posing threats to ecosystems and human health, exhibit pseudo-persistence in the environment. we compiled a national dataset of over 67,000 records on antibiotics, our study scrutinized antibiotic distribution in China's major river water and sediment. Through this analysis, we identified key factors influencing distribution patterns and crafted a national priority ranking for antibiotics. These findings deepen our understanding of antibiotic presence and contribute to the development of targeted management strategies aimed at minimizing environmental impact.

Soil-sediment connectivity through Bayesian source tracking in an urban naturalised waterway via microbial and isotopic markers.

Riverine sediments are important habitats for microbial activity in naturalised waterways to provide potential ecosystem services that improve stormwater quality. Yet, little is known about the sources of these sediment microbes, and the factors shaping them. This study investigated the dominant source of sediments in a tropical naturalised urban waterway, using two Bayesian methods for microbial and isotopic 13C/15N markers concurrently. Additionally, key factors shaping microbial communities from the surrounding landscape were evaluated. A comprehensive two-year field survey identified source land covers of interest based on topology and soil context. Among these land covers, riverbanks were the dominant source of sediments contribution for both edaphic and microbial components. The physico-chemical environment explains most of the variation in sediment communities compared to inter-location distances and microbial source contribution. As microbes provide ecosystem services important for rewilding waterways, management strategies that establish diverse sediment microbial communities are encouraged. Since riverbanks play a disproportionately important role in material contribution to sediment beds, management practices aimed at controlling soil erosion from riverbanks can improve overall functioning of waterway systems.

Exploration of port environmental efficiency measurement and influential factors in the Yangtze River Delta Pilot Free Trade Zone.

This study focuses on the environmental efficiency of ports in China's Yangtze River Delta Pilot Free Trade Zone (YRD PFTZ), a critical factor in advancing the high-quality development of ports and facilitating Chinese-style modernization. Current research on port efficiency primarily focuses on the geographical level, with relatively few studies examining the economic regional framework. We selected the YRD PFTZ port for our study to address this gap. Covering 2013 to 2021, we employed the Super-SBM with undesirable outputs and utilized the GML index method. We conducted a spatiotemporal analysis to assess dynamic and static aspects and used the Tobit model to thoroughly investigate the factors influencing the GML Index of these ports. The study showed that: (1) the overall environmental efficiency of these ports was relatively high with a fluctuating trend of initial increase, followed by a decrease, and then an upturn. (2) From a dynamic perspective, the average Green Total Factor Productivity (GTFP) Index is 1.549, denoting an exceptional level primarily driven by technological efficiency. The technical efficiency change index is the main factor improving GTFP in Shanghai, Jiangsu, and Anhui provinces. (3) The port cargo volume and total import and export volume significantly impact the environmental efficiency.

How water stability relates with timing, size, and community successions of harmful algal blooms: A case study in the Three Gorges Reservoir.

Effective management of Harmful Algal Blooms (HABs) requires understanding factors influencing their occurrence. This study explores these dynamics in the Pengxi River, a tributary of the Three Gorges Reservoir, focusing on nutrient stratification and algal blooms. We hypothesized that nutrient levels in eutrophic waters with stable stratification correlate with HAB magnitude and that disruption of stratification triggers blooms due to nutrient shifts. A 38-day sampling campaign in Gaoyang Lake (April 16-May 23, 2022) revealed that consistent weather between April 26 and May 16 led to a surface density layer, restricting nutrient transfer and causing a bloom with 173.0 µg L-1 Chl-a on May 1. After a heavy rain on May 18, a peak bloom on May 20, dominated by Ceratium hirundinella, showed 533 µg L-1 Chl-a. There was a significant negative correlation between Cyanobacteria and C. hirundinella biomasses (r = -0.296, P < 0.01), highlighting nutrient availability and physical stability's roles in regulating HABs.

Assessing meso-, micro-, and nanoplastic pollution in Los Angeles County estuaries.

Estuaries can behave as plastic pollution hotspots, although the dynamics of accumulation in these unique habitats are not understood. We quantified the current levels of meso-, micro-, and nanoplastic pollution in four Los Angeles County estuaries for the first time, as a function of distance from the water outlet and local population density. Fourier-transform infrared spectroscopy (FTIR) and microscope imaging revealed the presence of six types of plastic; polyethylene or polypropylene dominated the meso- and microplastic, and nanoplastics were identified as mainly polyolefin fibers. The distribution was heterogeneous throughout, although the sand between the river mouth and ocean generally contained more plastic than inland control samples. Population density did not appear to affect the abundance of plastic estuarine pollution. Other factors, such as waste treatment effluent, recreation, and river geography, may contribute to plastic deposition. A positive correlation between meso- and microplastic abundance provides insight into such mechanisms for accumulation.

A review of heavy metals pollution in riverine sediment from various Asian and European countries: Distribution, sources, and environmental risk.

Riverine sediments are important reservoirs of heavy metals, representing both historical and contemporary anthropogenic activity within the watershed. This review has been conducted to examine the distribution of heavy metals in the surface sediment of 52 riverine systems from various Asian and European countries, as well as to determine their sources and environmental risks. The results revealed significant variability in heavy metal contamination in the world's riverine systems, with certain hotspots exhibiting concentrations that exceeded the permissible limits set by environmental quality standards. Among the studied countries, India has the highest levels of chromium (Cr), cobalt (Co), manganese (Mn), nickel (Ni), zinc (Zn), cadmium (Cd), copper (Cu), and lead (Pb) contamination in its riverine systems, followed by Iran > Turkey > Spain > Vietnam > Pakistan > Malaysia > Taiwan > China > Nigeria > Bangladesh > Japan. Heavy metal pollution in the world's riverine systems was quantified using pollution evaluation indices. The Contamination Factor (CF) revealed moderate contamination (1 ≤ CF < 3) throughout the geological units, with the exception of Pb, Cd, and Cu. The Contamination Degree (CD) classifies the contamination level into different categories: Low degree of contamination (CD < 6), moderate degree of contamination (6 ≤ CD < 12), considerable degree of contamination (12 ≤ CD < 24), and a very high degree of contamination (CD ≥ 24), while the Pollution Load Index (PLI) estimate the total amount of heavy metal pollution in riverine sediments, with Turkey having the highest PLI value of 6.512, followed by Spain, Vietnam, Taiwan, Pakistan, Bangladesh, China, India, Japan, Malaysia, Iran, and Nigeria. In applied multivariate statistics, correlation analysis determined the fate and distribution of heavy metals in riverine systems, while Principal Component Analysis (PCA) elucidated the potential sources, including industrial, agrochemical, mining, and domestic wastewater discharges, lubricant leakages, multiple geogenic inputs, erosion of mafic and ultramafic rocks, and minimal atmospheric deposition. As per Potential Ecological Risk Index (PERI) perspectives, Vietnam, Spain, and Turkey have the highest ecological risk, followed by Nigeria > Pakistan > Bangladesh > China > Taiwan > Japan and Iron, while the potential risks of ∑non-carcinogenic Pb, Cr, Ni, Cu, Cd, Co, Zn, and Mn for exposed human children and adults through ingestion and dermal contact were significantly influenced between acceptable to high risk, necessitating special attention from pollution control agencies.

The seasonal variation and ecological risk of microplastics in the Lower Ganges River, Bangladesh.

Microplastic (MP) pollution has gained considerable attention in various ecosystems; however, it has received relatively less attention in freshwater-riverine environments than in other ecosystems. The Ganges River Delta, one of the world's most densely populated areas, is a potential source of MP pollution in the freshwater ecosystem. MPs were identified throughout the year in the lower Ganges River water. Seasonally, the highest abundance was observed during the monsoon (14.66 ± 2.06 MPs/L), followed by the pre-monsoon (13.46 ± 1.75 MPs/L) and post-monsoon (11.50 ± 0.40 MPs/L). Throughout the year, MP discharge was estimated at 4.12 × 1012 to 2.17 × 1013 MPs/year. Fourier transformed infrared spectroscopy identified plastic polymers in the water, like ethylene vinyl acetate, polystyrene, polypropylene, polyethylene, and nylon. Moderate contamination by MPs was assessed throughout the year. Significant correlations between MP abundance and both rainfall and discharge were observed. It is essential to implement preventative measures in the Ganges River Basin to mitigate MP pollution before the situation worsens. PRACTITIONER POINTS: Throughout the year, MP concentration ranged from 10.67 to 20.33 MPs/L The highest MP occurrence was observed in the monsoon season (14.66 ± 2.06 MPs/L) The lowest abundance was detected in the post-monsoon period (11.50 ± 0.40 MPs/L) There was a moderate level of MP contamination in the lower Ganges River water It was shown that discharge and rainfall were correlated with MP abundance.

A probabilistic risk assessment of heavy metal in water and sediment: An industrially affected urban river in Bangladesh.

Human welfare and biodiversity are at risk due to the deterioration of water and sediment quality. Particularly, in last few decades, global water and sediment quality degraded due to the rapid industrialization and urbanization. This study aimed to determine the concentration of nine heavy metals and metalloid (Pb, Cr, Cd, Hg, As, Mn, Ni, Cu, and Zn) and assess the ecological risks using different pollution indices (e.g., heavy metal pollution index [HPI], Nemerow pollution index [NI], geo-accumulation index [Igeo], contamination factor [CF], degree of contamination [CD] and pollution load index [PLI], ecological risk index [ERI]) in water and sediment of the Shitalakshya River, an industrially affected urban river of Bangladesh. For the first time, 20 water and sediment samples were collected across a wider geographical area of the Shitalakshya River during both monsoon and dry seasons and analyzed using the atomic absorption spectrometer. Average concentrations of heavy metals and metalloid in water were within the Bangladesh standard except for Cr (51.69 ppb) and Mn (228.20 ppb) during monsoon season, portraying potential ecological and human health risks. Besides, average concentration of Mn (549.75 and 370.93 ppb), Ni (549.75 and 370.93 ppb), and Cu (45.34 and 36.09 ppb) in sediment during both seasons were above international standard, implying risk to aquatic sediment biota. The average HPI values indicated moderate to high contamination, whereas the NI values implied polluted water in monsoon season with severe pollution in port area of the river. Similarly, Igeo, CF, CD, and PLI elucidated different levels of contamination in the sediment, particularly during dry season. The ERI values also referred moderate ecological risk in the sediment during dry season. Overall, our findings highlight the alarming level of heavy metal pollution in the Shitalakshya River, necessitating immediate action to protect the aquatic environment, sediment biota, and human health. PRACTITIONER POINTS: This study determined the concentration of heavy metals and metalloid in water and sediment of the Shitalakshya River, Bangladesh. The study revealed that the average concentration of Cr and Mn in water exceeded national standard, whereas Mn, Ni, and Cu in sediment exceeded international limit. Potential ecological risk of heavy metals was also assessed using different pollution indices. Calculated pollution indices indicated different degree of pollution, implying critical ecological condition due to heavy metal pollution in aquatic environment and sediment biota.

Sustainable synthesis of fluorescent polymer carbon dots@PVA for sensitive chlortetracycline detection.

Antibiotic residues persist in the environment and represent serious health hazards; thus, it is important to develop sensitive and effective detection techniques. This paper presents a bio-inspired way to make water-soluble fluorescent polymer carbon dots (PCDs@PVA) by heating biomass precursors and polyvinyl alcohol (PVA) together. For example, the synthesized PCDs@PVA are very stable with enhanced emission intensity. This property was observed in a wide range of environmental conditions, including those with changing temperatures, pH levels, UV light, and ionic strength. PCDs@PVA detected the antibiotic chlortetracycline (CTCs) with great selectivity against structurally related compounds and a low detection limit of 20 nM, demonstrating outstanding sensitivity and specificity. We confirmed the sensor's practical application through real sample analysis, yielding recovery rates of 98%-99% in samples of milk, honey, and river water. The synthesized PCDs@PVA fluorescence sensor was successfully used for CTCs detection in real samples.