Suspended Particulate Matter Research Articles

Distribution of heavy metals in the sediments of Ganga River basin: source identification and risk assessment.

Sediment serves as a heavy metal store in the riverine system and provides information about the river's health. To understand the distribution of heavy metal content in the Ganga River basin (GRB), a total of 25-bed sediment and suspended particulate matter (SPM) samples were collected from 25 locations in December 2019. Bed sediment samples were analyzed for different physio-chemical parameters, along with heavy metals. Due to insufficient quantity of SPM, the samples were not analyzed for any physio-chemical parameter. The metal concentrations in bed sediments were found to be as follows: Co (6-20mg/kg), Cr (34-108mg/kg), Ni (6-46mg/kg), Cu (14-210mg/kg), and Zn (30-264mg/kg) and in SPM, the concentrations were Co (BDL-50mg/kg), Cr (10-168mg/kg), Ni (BDL-88mg/kg), Cu (26-80mg/kg), and Zn (44-1186mg/kg). In bed sediment, a strong correlation of 0.86 and 0.93 was found between Ni and Cr, and Cu and Zn respectively and no significant correlation exists between organic carbon and metals except Co. In SPM, a low to moderate correlation was found between all the metals except Zn. The risk indices show adverse effects at Pragayraj, Fulhar, and Banshberia. Two major clusters were formed in Hierarchal Cluster Analysis (HCA) among the sample points in SPM and bed sediment. This study concludes that the Ganga River at Prayagraj, Banshberia, and Fulhar River is predominately polluted with Cu and Zn, possibly posing an ecological risk. These results can help policymakers in implementing measures to control metal pollution in the Ganga River and its tributaries.

Remote sensing inversion of suspended particulate matter in the estuary of the Pinglu Canal in China based on machine learning algorithms

Remote sensing inversion of suspended particulate matter in the estuary of the Pinglu Canal in China based on machine learning algorithms

Modelling of Carbon Monoxide and Suspended Particulate Matter Concentrations in a Rural Area Using Artificial Neural Networks

Air pollution is a growing concern in rural areas where agricultural production can be reduced by it. This article analyses data obtained as part of a research project. The aim of this study is to understand the influence of atmospheric pressure, air temperature, air relative humidity, longitude and latitude of the location, and indoor and outdoor environment on local rural workplace diversity of air pollutants such as carbon monoxide (CO) and suspended particulate matter (SPM), as well as the contribution of these variables to changes in such air pollutants. The focus is on four topics: motivation, innovation and creativity, leadership, and social responsibility. Furthermore, this study developed an artificial neural network (ANN) model to predict CO and SPM concentrations in the air based on data collected from the mentioned inputs. The related sensors were assembled on an Arduino Mega 2560 board to form a field-portable device to detect air pollutants and meteorological parameters. The sensors included an MQ7 sensor for CO concentration measurement, a Sharp GP2Y1010AU0F dust sensor for SPM concentration measurement, a DHT11 sensor for air temperature and air relative humidity measurement, and a BMP180 sensor for air pressure measurements. The longitude and latitude of the location were measured using a smartphone. Measurements were conducted from 20 December 2021 to 16 July 2022. Results showed that the overall average outdoor CO and SPM concentrations were 10.97 ppm and 231.14 μg/m3 air, respectively. The overall average indoor concentrations were 12.21 ppm and 233.91 μg/m3 air for CO and SPM, respectively. Results showed that the ANN model demonstrated acceptable performance in predicting CO and SPM in both the training and testing phases, exhibiting a coefficient of determination (R2) of 0.575, a root mean square error (RMSE) of 1.490 ppm, and a mean absolute error (MAE) of 0.994 ppm for CO concentrations when applying the testing dataset. For SPM concentrations, the R2, RMSE, and MAE using the test dataset were 0.497, 30.301 μg/m3 air, and 23.889 μg/m3 air, respectively. The most influential input variable was air pressure, with contribution rates of 22.88% and 22.82% in predicting CO and SPM concentrations, respectively. The acceptable performance of the developed ANN model provides potential advances in air quality management and agricultural planning, enabling a more accurate and informed decision-making process regarding air pollution. The results of short-term estimation of CO and SPM concentrations suggest that the accuracy of the ANN model needs to be improved through more comprehensive data collection or advanced machine learning algorithms to improve the prediction results of these two air pollutants. Moreover, as even lower cost devices can predict CO and SPM concentrations, this study could lead to the development some kind of virtual sensor, as other air pollutants can be estimated from measurements of particulate matters.

Assessment of PM2.5 pollution features and health advantages in Northwest China.

The elevated concentration of suspended particulate matter in the atmosphere is closely associated with the morbidity and mortality of human diseases. In northwest China, fine particulate matter pollution has persistently affected local health, production, and daily life due to climatic factors and economic development. This paper first examines the distribution and variation of PM2.5 concentrations in northwest China from 2013 to 2022 to understand changes in PM2.5 exposure levels, as well as their associated health and economic benefits since the implementation of the "Air Pollution Prevention and Control Action Plan." Second, we estimated the number of premature deaths in the research region under various control scenarios based on PM2.5 concentrations recorded in 2013 and 2021, utilizing existing epidemiological studies for reference. Finally, we calculated the financial benefits resulting from variations in PM2.5 concentrations within this region. Results indicated that (1) from 2013 to 2022, the Tarim Basin exhibited the highest PM2.5 concentration among all studied areas, while northern Xinjiang and Qinghai Province had notably lower levels. Additionally, wintertime concentrations were consistently higher than those observed during summer months; however, there has been a general trend toward reduced PM2.5 content over the past decade. (2) A significant inverse relationship was found between premature mortality rates and PM2.5 concentrations; specifically, fluctuations in PM2.5 levels exerted a more pronounced impact on premature deaths attributable to cardiovascular diseases compared to respiratory conditions within this northwest region. (3) Males were disproportionately affected by increases in PM2.5 concentration relative to females-experiencing two to three times more early fatalities than their female counterparts did. (4) Over a 9-year period within this research area, fiscal benefits derived from interventions targeting PM2.5 treatment increased by approximately 891 million yuan.

Prenatal exposure to air pollutants and the second to fourth digit ratio in adult women

The study aimed to analyse the association between the digit ratio in adult women and the degree of air pollution (suspended particulate matter, sulphur dioxide, nitric dioxide, benzene levels) in the place of residence of their mothers during pregnancy. The data was collected from female students in several Polish cities. Measurements were taken, and questionnaire data were collected. 2D:4D ratios were calculated for the left and the right hand. The ratio was analysed as a continuous variables. Air quality information was retrieved from reports by the Chief Inspectorate for Environmental Protection. Statistically significant differences both in right- and left-hand 2D:4D ratio were found for PM10 and benzene. In addition, the right-hand 2D:4D differed significantly depending on PM2.5. The association between digit ratio and the complex air pollution index was also found. Poor air quality was associated with higher values of the ratio. Our results indicate that a high airborne pollutant level, especially suspended particulate matter, is associated with a higher digit ratio.

Flocs as vectors for microplastics in the aquatic environment

AbstractMicroplastics (MPs) are an important component of suspended particulate matter in aquatic environments with two main transport modes, that is, as individual entities or in flocs. Despite its importance to MP pollution management, understanding and predicting MP flocculation remains a challenge. In this Article, we combined a meta-analysis of published data (>2,000 measurements) with new experimental data (>4,000 measurements) to investigate which size fraction of MPs can be incorporated into and transported by flocs in the aquatic environment. The size relationship between MPs and flocs can be used to predict the flocculation of MPs in various aquatic environments, and we have proposed a mathematical model to show that small MPs (<162 µm) are predominantly transported as flocs, regardless of the physicochemical characteristics of the MPs or water body. This provides valuable information to predict the transport modes of MPs, presenting a critical insight for multiple environmental settings and future pollution control strategies.

Risk assessment and sources associated with potentially toxic elements in suspended particulate matter: A karst river perspective in active mining area

Study regionDaiyang River Basin, a typical karst river basin impacted by mining activities in Guizhou, Southwest China. Study focusRivers are fundamental components of regional water security, but they are facing potentially toxic elements (PTEs) pollution caused by mining activities. This study investigated the concentration, behavior, risks and sources of nine PTEs in suspended particulate matter (SPM) from mining-impacted karst rivers, which are essential for the safety and management of karst water environments. New hydrological insights for the regionThe contents of Cr, Ni, Cu, Zn, As, Cd, Sb and Hg exceeded the corresponding local soil background values, with Zn and Cu being the most important pollutants. These elements caused a very high potential toxicity risk to the basin and unacceptable carcinogenic and non-carcinogenic risks to the local residents. Correlation analysis and the positive matrix factorization (PMF) model indicated that Ni, Cd, Zn and Cu were mainly derived from mixed sources of geological background and anthropogenic activities (30.95 %), Hg, Sb, and As were related to coal mining and combustion sources (28.91 %), while Pb, As, Cr and Sb were mainly contributed by natural sources (40.15 %). Furthermore, mixed sources, mining-related sources and As were identified as priority control factors in the study area. These insights can provide powerful support for decision-makers to develop control policies and reduce PTEs pollution in karst areas.

Variations of phosphorus in sediments and suspended particulate matter of a typical mesotrophic plateau lake and their contribution to eutrophication

Internal phosphorus loading (IPL), as an important part of lake phosphorus cycle and the key to solve the eutrophication problem, is still an important cause of regional and seasonal algal blooms for some mesotrophic lakes located in plateau areas. We investigated the composition, distribution of P fractions in sediments and suspended particulate matter (SPM) of Erhai Lake, southwest China, and explored the relationships between environmental variables and spatial-temporal variations of P fractions. The total P (TP) in surface sediments ranged from 817 to 1216 mg/kg, with inert Ca-P (32%) and Res-P (24%) predominating, at a moderate level. The comparison of short-term release fluxes (0.08 mg/(m2·d)) and long-term release fluxes (0.09 mg/(m2·d)) reflected that the northern region was recovering slowly from the previous P pollution. Mobile-P (the sum of loosely adsorbed P, iron bound P, and organic P) accounted for 52.3% of the TP in SPM and showed high spatial-temporal variations, which were closely related to the growth of algae throughout the investigation. The results suggested that sediments could make a sustained contribution to IPL, and that the P in SPM was highly active and significantly contributed to eutrophication in Erhai Lake especially at the time of seasonal alternations. Our data provided important theoretical bases for the relationship between internal phosphorus loading and eutrophication in plateau lakes.

Distribution, sorption patterns, and outflows of riverine microplastics-affiliated linear alkylbenzenes and polycyclic aromatic hydrocarbons in a dynamic coastal zone.

Microplastics (MPs) pollution has emerged as a global concern. To mitigate the potential threats by MPs, particularly to coastal regions, it is crucial to comprehend the environmental behavior of MPs and their affiliated chemicals. In the present study, we collected floating MPs using a Manta net (0.33 mm mesh size) in a one-year sampling event in 2022 from the eight major estuaries in the Pearl River Delta, China, and also from five coastal sites in August and December in the same year. Nineteen linear alkylbenzenes (∑19LAB) and 16 polycyclic aromatic hydrocarbons (∑16PAH) affiliated with MPs were measured. The mean concentrations of MPs-affiliated ∑19LAB and ∑16PAH were 6710 (range: 3400-12300) and 5310 (range: 817-19,600) ng g-1, respectively, at the estuarine sites, and were 4920 (range: 2400-7600) and 2610 (range: 911-7890) ng g-1, respectively, at the coastal sites. Significant correlations were found between logarithmic MPs-water partition coefficients (log Kpw) and logarithmic suspended particulate matter-water partition coefficients (log Kd) values for LABs and PAHs, indicating analogous partitioning dynamics for MPs and suspended particulate matter with water. The annual riverine outflows were 1170 and 414 g for ∑19LAB and ∑16PAH, respectively. Although the riverine outflows of LABs and PAHs carried by MPs remain negligible compared to those by suspended particulate matter, an upward trend was identified between 2018 and 2022. Notably, the riverine input of LABs and PAHs carried by suspended particulate matter to the coastal ocean decreased from 2005/2006 to 2022, due to a combination of improved technological processes and energy structures.

Variability of inherent optical properties of seawater in relation to the concentration and composition of suspended particulate matter in the coastal Arctic waters of western Spitsbergen

Inherent optical properties (IOPs) and characteristics of suspended particles in surface seawater samples were measured in summer months of 2021 and 2022 in Arctic fjords and coastal waters of western Spitsbergen in the Svalbard archipelago. The measured IOPs included the spectral backscattering and scattering coefficients of suspended particulate matter, as well as the spectral absorption coefficients of suspended particulate matter and its non-algal particulate and phytoplankton components. The particulate assemblages were characterized by measuring the mass concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate inorganic matter (PIM), and phytoplankton pigments including chlorophyll-a (Chla). The investigated coastal waters exhibit high variability of particulate characteristics and associated IOPs. We observed more than two orders of magnitude variation in SPM and particulate IOPs, and Chla varied from below the detection limit to more than 3 mg m−3. The contribution of organic fraction to SPM (POM/SPM ratio) varied from 0.05 to 0.6, and the Chla/SPM ratio spanned more than three orders of magnitude with a maximum value of the order of 10−3. As a result, the mass-specific optical coefficients, especially the mass-specific backscattering and scattering coefficients of particles and mass-specific absorption coefficient of non-algal particulate matter, exhibit large variations. In addition, our study demonstrates the influences of changes in composition of suspended particulate matter parameterized in terms of POM/SPM and Chla/SPM ratios on IOPs. Various variants of spectral parametrizations of optical coefficients in terms of univariate or multivariable relationships with particulate characteristics are provided. These parameterizations are representative of the investigated coastal Arctic waters in Svalbard region and can be used for better interpretation of optical measurements, both in-situ and remote, in this Arctic environment.

Gaussian process regression as a powerful tool for analysing time series in environmental geochemistry

Monitoring programs require more advanced data management for the registered time series. Classical temporal series decomposition cannot fulfil current needs regarding adequate data representation, optimization of the spatial-temporal sampling resolution and predictive power. In the manuscript at hand, we will demonstrate that Gaussian process regression (GPR) models are a vital machine-learning tool to interpret temporal series, improving understanding of geochemical cycles, providing input data for geochemical models and acting as a guide for future decisions in environmental monitoring. Firstly, we explore the impacts of sampling frequency in the GPR performance for temporal series with variable lengths and sampled frequencies of water discharges. On a second approach, we present the strengths and weaknesses between classical decomposition of temporal series and GPR results for a case study: a 14-year record of water discharge, suspended particulate matter and antimony concentrations in the Garonne River. Our results suggest that (i) even short temporal series with low sampling resolution can be accurately characterized by GPR when presenting well defined seasonal patterns, and (ii) GPR provides more detailed and robust support than classical statistics to identify processes responsible for multi-scale geochemical signals. This work provides a reference for researchers, engineers, and stakeholders for more reliable monitoring, understanding, and managing aquatic ecosystems.

Air Quality Near Middle East's Large Dried Lake: Heavy Metal Emissions, Machine learning Analysis, and Health Risks

The present study aimed to measure the concentrations and chemical compositions of suspended particulate matters smaller than 10 μm (PM10) in the ambient air of Bakhtegan Lake and to assess the health risks associated with exposure to metal elements through inhalation. Ambient air samples were collected from a rural area close to the lake. The levels of metal elements bonded to PM10 were measured by the Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The mean ambient PM10 concentration around the studied lake (78.12 μg/m3) was higher than the 24 hours guidelines PM10 standards proposed by World Health Organization (WHO) (50 μg/m3). The highest and lowest concentrations were related to Fe and V, respectively. Lifetime Cancer Risk (LCR) was higher for adults than for children. Additionally, the LCR value was higher for As compared to other metals, indicating that the cancer risk in the adults group was mainly due to As. Besides, health risk assessments indicated that adults suffered from higher cancer risks compared to children, while both adults and children did not suffer from non-carcinogenic risks. Through Principal component analysis (PCA) and random forest (RF) analysis, it was determined that metallic concentrations in the air samples are influenced by both natural and anthropogenic sources, with copper and lead identified as pivotal predictors for nickel levels. Therefore, monitoring and addressing such metal-induced pollution is essential for regional public health.

An Empirical Algorithm for Estimating the Absorption of Colored Dissolved Organic Matter from Sentinel-2 (MSI) and Landsat-8 (OLI) Observations of Coastal Waters

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, acdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating acdom at the wavelength 412 nm (acdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, Rrs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite Rrs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate acdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m−1 from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived acdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of acdom (412) is provided for a coastal transect in the south of Vietnam.

Simulation study on the clogging process of suspended matter in recharge of anti-filtration recharge well

ABSTRACT Anti-filtration recharge wells are a class of recharge facilities in groundwater reservoirs with their own anti-filtration function, and aquifer clogging is a key issue in recharge. In this paper, the process of recharging groundwater by rainfall flood water recharge from an anti-filtration recharge well was simulated by indoor sand column test, and the change of permeability coefficient, turbidity at the outlet, and the distribution of suspended particulate matter at the end of the experiment were measured and computed, so as to analyze and study the effect of filtration in anti-filtration recharge wells and carry out the contrast test with ordinary recharge wells without a recharge pool. Compared with ordinary recharge wells, the anti-filter layer in the recharge pool of anti-filtration recharge wells can largely remove suspended matter in recharge water and intercept suspended matter at the surface, thus preventing aquifer clogging, and it is recommended that the anti-filter layer should be cleaned up and replaced regularly according to the experimental results, and this study provides a reference for the practical application of anti-filtration recharge wells.

The Effects of Montmorillonite–Humic Acid Composite Particles on the Photolysis of Tetracycline in Water

Suspended particulate matter (SPM) is an important component of natural water bodies and can significantly influence the photolytic behavior of water pollutants. A comprehensive understanding of the photochemical behavior of water pollutants in natural waters requires consideration of the presence of SPM. In this study, montmorillonite–humic acid (MMT-HA) composite particles were synthesized to simulate SPM in natural waters and their effects on the photolysis of tetracycline (TC) were investigated. The results demonstrated that the presence of MMT-HA composite particles in water significantly enhanced the photolysis of TC, with the photolytic kinetics following a pseudo-first-order model. Electron spin resonance spectra and free radical quenching experiments indicated that the photoactive components (MMT and humic acids) in the composite particles induced the generation of reactive oxygen species under light exposure, further contributing to the enhanced photolysis of TC. Comparative analysis of the free radical signals and adsorption experiments revealed that the accelerated photolysis of TC was also related to the interfacial interaction between the MMT in the composite particles and the TC molecules. The formation of surface complexes between TC molecules and the negatively charged sites on the MMT surface facilitated light absorption and electron transfer, thereby accelerating the photolysis of TC. Photoproduct analysis indicated that the primary degradation pathways of TC in the composite particle systems included the addition of hydroxyl radicals to the aromatic ring, as well as demethylation, deamination and dehydration in the side chains. This study shows that SPM in water bodies can affect the photochemical behavior of pollutants and should be taken into account when assessing the phototransformation of pollutants in natural waters.

Numerical Investigation of the Sediment Load Exchange between a Coastal Mud Bank and Its Neighbouring Estuary

Muddy coastlines cover much of the world’s shores, yet studies on the interaction between mud-affected coasts and estuaries are limited. This study focuses on the Mahury River estuary and its interaction with the muddy coast of the Guianas, primarily fed by the Amazon. A coupled wave–current–sediment transport model is developed to analyze the sediment exchange in an environment with strong interactions between the waves and the fluid mud. Simulations explore how seasonal changes in waves, mud availability, and tides affect sediment fluxes. The main processes influencing suspended particulate matter (SPM) and sediment transport are well emulated, notwithstanding the complexity of the ambient muddy environment. The results show that during the rainy season, strong wave damping and wave refraction zones cause high SPM resuspension in shallow waters (<5 m). In contrast, during the dry season, wave influence shifts to the estuary mouth. Erosion and sedimentation patterns indicate that ebb currents associated with neap tides during the rainy season represent the most favourable conditions for the alongshore migration of mud banks. Neaptide ebb currents also contribute to sedimentation during the dry season but only in the estuary mouth and the nearby coastal area. The abundance of mud leads to an extension of the estuary’s intertidal area during the dry season.

Attention-Enhanced Urban Fugitive Dust Source Segmentation in High-Resolution Remote Sensing Images

Fugitive dust is an important source of total suspended particulate matter in urban ambient air. The existing segmentation methods for dust sources face challenges in distinguishing key and secondary features, and they exhibit poor segmentation at the image edge. To address these issues, this paper proposes the Dust Source U-Net (DSU-Net), enhancing the U-Net model by incorporating VGG16 for feature extraction, and integrating the shuffle attention module into the jump connection branch to enhance feature acquisition. Furthermore, we combine Dice Loss, Focal Loss, and Activate Boundary Loss to improve the boundary extraction accuracy and reduce the loss oscillation. To evaluate the effectiveness of our model, we selected Jingmen City, Jingzhou City, and Yichang City in Hubei Province as the experimental area and established two dust source datasets from 0.5 m high-resolution remote sensing imagery acquired by the Jilin-1 satellite. Our created datasets include dataset HDSD-A for dust source segmentation and dataset HDSD-B for distinguishing the dust control measures. Comparative analyses of our proposed model with other typical segmentation models demonstrated that our proposed DSU-Net has the best detection performance, achieving a mIoU of 93% on dataset HDSD-A and 92% on dataset HDSD-B. In addition, we verified that it can be successfully applied to detect dust sources in urban areas.

Organic carbon burial dynamics at the Chukchi Shelf margin: Implications for the Arctic Ocean carbon sink

Organic carbon (OC) burial plays a crucial role in regulating the Arctic Ocean's capacity to uptake atmospheric CO₂. In this study, we demonstrate the transport, deposition, and degradation patterns of different sources of OC to reveal burial dynamics at the Chukchi Shelf margin, a region with the highest primary production in the Arctic Ocean currently affected by dramatic sea ice retreat. Observations of suspended particulate material show a pronounced separation of terrestrial and marine OC in the water column, which subsequently influences OC lateral transport and differential deposition. Easily suspendable terrestrial OC is concentrated in the upper 10 m of water or sea ice and transported to the Canada Basin, where it undergoes severe degradation of fresh carbon in the water column and uppermost sediments. In contrast, faster-settling marine OC is more likely to be buried in the canyons and at the Chukchi Shelf margin, with ice algae contributing about 14 % and 55 % of OC burial in areas south and north of 73°N, respectively, leading to higher initial burial efficiency. Increasing Arctic marine primary production could thus enhance the region's role as a carbon sink over millennial timescales, although the burial efficiency of terrestrial OC will eventually exceed that of marine OC with prolonged burial time. Our findings highlight the importance of lateral transport, differential deposition, and selective degradation in Arctic carbon burial, providing a basis for objectively assessing the future capacity of the Arctic carbon sink and its feedback to climate change.

Downstream Effects of the Pandemic? Spatiotemporal Trends of Quaternary Ammonium Compounds in Suspended Particulate Matter of German Rivers

During the SARS-CoV-2 pandemic, the preventive use of antimicrobials such as quaternary ammonium compounds (QACs) surged worldwide. As cationic and surface-active biocides, QACs are only partly removed during wastewater treatment and may cause adverse ecological effects in the downstream environment. To understand the environmental consequences of increased disinfectant use during the pandemic, we investigated spatiotemporal QAC concentration trends in the suspended particulate matter (SPM) of three diverse German rivers. Covering pooled annual SPM samples from 2006-2021 and monthly samples from 2018-2021 collected by the German Environmental Specimen Bank, 31 QACs were quantified by high performance liquid chromatography–mass spectrometry.∑QAC concentrations in annual samples differed by more than tenfold between rivers in the order Saar (average 6.7µg/g) > Rhine (0.9µg/g) > Mulde (0.3µg/g). The strongest potential pandemic imprint was however observed in the Mulde (+67%) and Rhine (+22%). Besides pandemic dynamics, also seasonal variation and mineral content of SPM tentatively affected QAC concentrations. Exceedance of predicted no-effect concentrations for sediment suggest ecotoxicological risks for long-chained QACs already before the pandemic. Our study thus highlights the importance of monitoring the environmental effects of antimicrobial use during pandemics and calls for an urgent minimization of non-essential applications. Environmental implicationThe SARS-CoV-2 pandemic caused a global surge in disinfectant use, including quaternary ammonium compounds (QACs). This raises concerns about their environmental residues, aquatic toxicity and contribution to the (co)selection of antimicrobial resistance in pathogens. To assess these ecotoxicological risks, we investigated spatiotemporal QAC concentration trends in suspended particulate matter of German rivers. While seasonal and spatial fluctuations exceed a potential pandemic “imprint” by a factor of 10, concentrations of some QACs reach ecotoxicological effect levels. This highlights the need to consider particle-associated QAC concentrations, the widespread use of QAC, as well as the environmental implications of chemical public health interventions.

Study on the diffusion and blocking behavior of bubble plumes in Cross-Flow

Abstract With the deepening of the concept of environmental protection, environmental problems in dredging engineering have attracted more and more attention. The diffusion of suspended particulate matter is inevitable in the process of dredging. A bubble plume, as a multiphase linear plume, has been widely studied because it can block the diffusion of suspended particulate matter in water. To explore the formation characteristics of the bubble plume, we evaluate the formation quality of the bubble plume qualitatively and quantitatively, analyze the effect of the bubble plume on blocking the diffusion of suspended particulates under different operating conditions (the type of bubble plume generation device, the number of bubble plume rows, and the ventilation flow rate) and environmental conditions (water flow velocity), and study the movement trajectory of blocked particles and blocked failed particles. A series of experiments on bubble plume characteristics and bubble plume blocking the diffusion of suspended particles were conducted to analyze the particle distribution characteristics and bubble plume blocking effect under the interaction of transverse flow and bubble plume. The results show that the better the quality of the bubble plume is, the lower the transverse flow intensity is, and the better the barrier effect of the bubble plume is.