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Water quality monitoring is imperative in providing the objective evidence required to make sound decisions about water quality management. This study aimed to examine the water quality status of the Migori River by determining spatio-seasonal variations in water quality parameters, along with associated influencing factors and potential health risks. Therefore, eighteen physico-chemical and bacteriological variables were sampled and analyzed monthly for six months covering the wet and dry seasons from the upstream, midstream, and downstream stations, and a health risk survey was conducted with 90 watershed households. ANOVA and T-test were used to test for the significant spatial and seasonal variations (p < 0.05), respectively; whereas Pearson's correlation was used to identify relationships between parameters. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) were used to find various spatial patterns in the river water quality datasets, while the Canadian Council of Ministries of the Environment Water Quality Index (CCME-WQI) showed the suitability status of the river water quality. The assessed variables showed significant seasonal variability but no significant spatial differences in the river. HCA generated 3 clusters suggesting that water quality deteriorated downstream from the upstream of the watershed. The PCA extracted four PCs explaining 80.5% of the total variance, which suggested that the variations in water quality are attributed to point and nonpoint sources of pollution. While most of the physico-chemical variables were within maximum permissible limits, the bacteriological levels exceeded the prescribed standards. The index ranked the river's water condition between 'poor' to 'marginal'; upstream has better water condition that gradually decreases toward the downstream, and water quality is better in the wet season than the dry season. The study revealed that the water of the Migori River is polluted and potentially hazardous for human usage, and thus suitable pollution control measures are urgently needed to safeguard public health. [ABSTRACT FROM AUTHOR]

Methane, with a global warming potential roughly 86 times greater than carbon dioxide over a 20‐year timeframe, plays a crucial role in global warming. Remote sensing retrieval is a pivotal methodology for identifying methane emission sources, with accuracy influenced largely by surface and atmospheric properties, including aerosols. In this study, we propose an Aerosol‐Calibrated Matched Filter (ACMF) algorithm to improve the traditional Matched Filter (MF) method. Our new approach incorporates an aerosol scattering correction factor to reduce the aerosol‐induced bias on methane retrievals. Validating our algorithm through simulated spectra, we demonstrate that considering the aerosol scattering effect significantly reduces retrieval errors compared to MF methods by an average of approximately 90%. We apply our newly developed algorithm to hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer—Next Generation in the Los Angeles Basin and focus on 11 plumes identified through case studies. Our results reveal that ACMF estimates of emission rates and inversion uncertainties exhibit an average reduction of approximately 4% compared to corresponding MF results, with deviation increasing with aerosol optical depth (AOD). Plain Language Summary: Emissions from facilities like oil and gas plants, coal mines, and waste management sites are a major contributor to atmospheric methane, which is a greenhouse gas that significantly impacts global warming. We can remotely measure these emissions using hyperspectral instruments. However, atmospheric particulates (aerosols) can skew these measurements by affecting how sunlight travels through the atmosphere. In our study, we have developed a new, computationally efficient approach to adjust for aerosol effects when analyzing data from these instruments. Tests with simulated data show that our method reduces errors caused by aerosols by about 90% compared with existing schemes. Investigations over 11 different methane emission plumes in the Los Angeles area indicate that traditional methods overestimate methane releases, especially when aerosols are present. Key Points: The Aerosol‐Calibrated Matched Filter (ACMF) is proposed for correction of aerosol‐induced bias in methane point source emission retrievalsThe ACMF method decreased the bias in methane concentration retrieval, demonstrating a clear improvement over the Matched Filter (MF) methodThe ACMF method, implemented in 11 cases over the LA Basin, yielded lower flux rate estimates and uncertainties compared to the MF method [ABSTRACT FROM AUTHOR]

The Danube River is, at 2857 km, the second longest river in Europe and the most international river in the world with 19 countries in its catchment. Along the entire river, faecal pollution levels are mainly influenced by point-source emissions from treated and untreated sewage of municipal origin under base-flow conditions. In the past 2 decades, large investments in wastewater collection and treatment infrastructure were made in the European Union (EU) Member States located in the Danube River Basin (DRB). Overall, the share of population equivalents with appropriately biologically treated wastewater (without disinfection) has increased from 69% to more than 85%. The proportion of tertiary treatment has risen from 46 to 73%. In contrast, no comparable improvements of wastewater infrastructure took place in non-EU Member States in the middle and lower DRB, where a substantial amount of untreated wastewater is still directly discharged into the Danube River. Faecal pollution levels along the whole Danube River and the confluence sites of the most important tributaries were monitored during four Danube River expeditions, the Joint Danube Surveys (JDS). During all four surveys, the longitudinal patterns of faecal pollution were highly consistent, with generally lower levels in the upper section and elevated levels and major hotspots in the middle and lower sections of the Danube River. From 2001 to 2019, a significant decrease in faecal pollution levels could be observed in all three sections with average reduction rates between 72 and 86%. Despite this general improvement in microbiological water quality, no such decreases were observed for the highly polluted stretch in Central Serbia. Further improvements in microbiological water quality can be expected for the next decades on the basis of further investments in wastewater infrastructure in the EU Member States, in the middle and lower DRB. In the upper DRB, and due to the high compliance level as regards collection and treatment, improvements can further be achieved by upgrading sewage treatment plants with quaternary treatment steps as well as by preventing combined sewer overflows. The accession of the Western Balkan countries to the EU would also significantly boost investments in wastewater infrastructure and water quality improvements in the middle section of the Danube. Continuing whole-river expeditions such as the Joint Danube Surveys is highly recommended to monitor the developments in water quality in the future. [ABSTRACT FROM AUTHOR]

This document discusses the issue of groundwater pollution, which poses a threat to ecosystems and human health. Groundwater pollution can come from natural sources or human activities such as agriculture and industry. Identifying the sources and mechanisms of pollution is crucial for prevention and mitigation efforts. The document highlights various studies from around the world that focus on groundwater contamination, including the evaluation of groundwater quality, assessment of health risks, and the development of remediation strategies. The research utilizes tools such as simulation models, remote sensing, and monitoring instruments to better understand and manage groundwater pollution. The goal is to protect and restore groundwater resources through effective prevention and remediation measures. [Extracted from the article]

For the first time, the AGRUM model consortium—consisting of the agro-economic model RAUMIS, the water balance model mGROWA, the hydrological nutrient transport models DENUZ, WeKu and MEPhos, and the urban emission model MONERIS—was jointly set up throughout Germany (357,000 km2). This provided a nationwide consistent nutrient model to capture the current status of N and P inputs to surface waters from diffuse sources and urban areas. Diffuse nutrient emissions were quantified in high spatial resolution for the input pathways' groundwater, drainage runoff, and natural interflow (100 m × 100 m), as well as for water erosion and wash-off (25 m × 25 m). The sum of diffuse nutrient inputs to surface waters is about 385,000 metric tons N/yr and ca. 11,530 metric tons P/yr. Urban emissions were quantified either as point source inputs (wastewater treatment plants, industrial direct dischargers) or at municipality scale for different collection and treatment systems, e.g., rainwater sewers or decentralized treatment plants, and sum up to ca. 95,000 t N/yr and 7500 t P/yr. As modelled, total N and P inputs into surface waters correspond well with observed N and P loads in rivers. The model results represent valuable information for water managers, being responsible for the preparation of management plans for the third management cycle of the EC Water Framework Directive spanning from 2021 to 2027. [ABSTRACT FROM AUTHOR]

The Garuda River is one of the tributaries of Bengawan Solo in Sragen Regency which is suspected of experiencing a decline in water quality. This study aims to determine the quality and pollution load carrying capacity (PLCC) of the Garuda River to the source of pollutants, especially those caused by tofu industrial liquid waste. The research method used in this study is a quantitative method to analyze the status of river water quality using the pollution index (PI) method and the calculation of river PLCC using the QUAL2Kw model with 3 modeling scenarios. The analysis showed that the Garuda River was proven not to meet the class III quality standards because several parameters such as temperature, TSS, nitrite (NO2-N), and total Coliform were above the set quality standards. Based on the calculation of the pollution index, it was found that the Garuda River was proven to be polluted with a lightly polluted quality status with a pollution score ranging from 1.49 to 2.91. Based on QUAL2Kw modeling, it was found that the PLCC of Garuda River for TSS parameters was 233.28-259.20 kg/day, BOD was 12.96-15.55 kg/day, and COD was 51.84-103.68 kg/day. One of the control efforts that can be carried out is reducing the pollutant burden on each source of pollution, especially point source pollutants from tofu industrial liquid waste. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: Cinangka Village in Bogor Regency is a traditional used battery recycling center in West Java, Indonesia. The smelting process was operated in open space, but because of adverse impacts, it has ceased since 2010. This activity generated a large amount of solid waste, categorized as hazardous and toxic materials, thereby polluting the air, land, and water. Because an area of Cinangka Village has been converted into a fishing pond, it is necessary to investigate whether the fish that live in this pond are accumulating heavy metals, thereby threatening and harming humans as consumers. This research is important for the innovative remediation of land contaminated with used battery smelting waste. METHODS: Analysis of lead, zinc, arsenic, and iron levels in water, sediment, fish, and aquatic plants, as well as histomorphology analysis of several fish organs, was performed. The safety aspect of consuming fish originating from this location was also calculated. For the used battery recycling area, lead and iron contaminate the environment in the highest concentrations, while arsenic and zinc are always detected but in low concentrations. FINDINGS: The results showed that sediment and water around the pond, previously a burning area of used battery smelting but 12 years after cessation, are polluted by heavy metals, not only lead, zinc, arsenic, and iron. Other metals are present because lead and lead oxide plates are impure and associated with other minerals. According to the lead concentration, the soil/sediment is still categorized as hazardous and toxic material and becomes a pollutant for the ecosystem. Water hyacinth plants that live in ponds are densely cultivated and contaminated with heavy metals. They can become heavy metal phytoremediators on the land where traditional used battery burning was performed. Goldfish from this area are contaminated with high levels of heavy metals and are unfortunately unsafe for consumption because zinc is perilous. Adults are only allowed 3 gram per week, while children may not consume goldfish from this fishing pond. Contaminating heavy metals also cause various damage to fish organs, namely, edema in the kidneys, melano-macrophage centers in the spleen and liver, edema and hyperplasia in the epithelial gills, and fatty degeneration in the liver and its lysed ovary cells. CONCLUSION: Consequently, land in Cinangka Village is still categorized as hazardous, and toxic waste and should not be converted into a fishing pond because the soil is a point source of pollution that contaminates fish with high concentrations of heavy metals and damages their organs. Consuming these goldfish will harm health and thus is prohibited for children. Cleaning and remediation of the environment is necessary and must cover the entire area. Meanwhile, water hyacinth plants can be used as phytoremediators in freshwater ponds to reduce heavy metals. [ABSTRACT FROM AUTHOR]

Monitoring water quality in urban rivers is crucial for water resource management since point and non-point source pollution remain a major challenge. However, traditional water quality monitoring methods are costly and limited in frequency and spatial coverage. To optimize the monitoring, techniques such as modeling have been proposed. These methods rely on networks of low-cost multiprobes integrated with IoT networks to offer continuous real-time monitoring, with sufficient spatial coverage. But challenges persist in terms of data quality. Here, we propose a framework to verify the reliability and stability of low-cost sensors, focusing on the implementation of multiparameter probes embedding six sensors. Various tests have been developed to validate these sensors. First of all, a calibration check was carried out, indicating good accuracy. We then analyzed the influence of temperature. This revealed that for the conductivity and the oxygen sensors, a temperature compensation was required, and correction coefficients were identified. Temporal stability was verified in the laboratory and in the field (from 3 h to 3 months), which helped identify the frequency of maintenance procedures. To compensate for the sensor drift, weekly calibration and cleaning were required. This paper also explores the feasibility of LoRa technology for real-time data retrieval. However, with the LoRa gateways tested, the communication distance with the sensing device did not exceed 200 m. Based on these results, we propose a validation method to verify and to assure the performance of the low-cost sensors for water quality monitoring. [ABSTRACT FROM AUTHOR]

Various forms of pollution carry a substantial burden with respect to increasing the risk of causing and exacerbating noncommunicable diseases, especially cardiovascular disease. The first part of this 2-part series on pollution and cardiovascular disease provided an overview of the impact of global warming and air pollution. This second paper provides an overview of the impact of water, soil, noise, and light pollution on the cardiovascular system. This review discusses the biological mechanisms underlying these effects and potential environmental biometrics of exposure. What is clear from both these pollution papers is that significant efforts and redoubled urgency are needed to reduce the sources of pollution in our environment, to incorporate environmental risk factors into medical education, to provide resources for research, and, ultimately, to protect those who are particularly vulnerable and susceptible. [Display omitted] • Increasing evidence suggests that water, soil, noise, and light pollution increase cardiovascular morbidity and mortality. • The mechanisms linking these sources of pollution to cardiovascular disease are diverse, making mitigation efforts challenging, but evolving methods to track these sources of pollution may point to new strategies. • Collectively, these data underscore the urgent need to address pollution in all its forms at a global level. [ABSTRACT FROM AUTHOR]

Current source apportionment models have successfully identified emission sources and quantified their contributions. However, when being utilized for heavy metal source apportion in soil, their accuracy needs to be improved, regarding migration patterns. Therefore, this work intended to improve the pre-existing principal component analysis and multiple linear regression with distance (PCA-MLRD) model to effectively locate pollution pathways (traffic emissions, irrigation water, atmospheric depositions, etc.) and achieve a more precise quantification. The dataset of soil heavy metals was collected from a typical area in the Chang-Zhu-Tan region, Hunan, China in 2021. The identification of the contribution of soil parent material was accomplished through enrichment factors and crustal reference elements. Meanwhile, the anthropogenic emission was identified with principal component analysis and GeoDetector. GeoDetector was used to accurately point to the pollution source from a spatial differentiation perspective. Subsequently, the pollution pathways linked to the identified sources were determined. Non-metal manufacturing factories were found to be significant anthropogenic sources of local soil contamination, mainly through rivers and atmospheric deposition. Furthermore, the influence of irrigation water on heavy metals showed a more pronounced effect within a distance of 1000 m, became weaker after that, and then gradually disappeared. This model may offer improved technical guidance for practical production and the management of soil heavy metal contamination. [ABSTRACT FROM AUTHOR]

Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4 , a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, which is an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced Hyperspectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in centre wavelength and change in full width at half-maximum (FWHM) from the nominal design values are estimated for all spectral channels, which are used as inputs for retrieving the enhancement of the column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter-based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of the emission flux rate by up to 5.0 %. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 761.78 ± 185.00 to 12 729.12 ± 4658.13 kgh-1. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84 % to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing them with a ground-based meteorological station. We found a large discrepancy, especially in wind direction, suggesting that incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi. [ABSTRACT FROM AUTHOR]

The topic of riverine microplastics is of great interest to the general public, yet the univocal scientific knowledge on this topic is limited. This review investigated the occurrence of microplastics in 6 major European rivers and their tributaries based on the results from 29 studies. We examined the reviewed studies in regard to data quality and reproducibility and assessed the abundance of microplastics in different sections of the water column. Furthermore, we investigated the chemical composition and potential origin of the reported riverine microplastics. We found that polystyrene, polypropylene, and polyethylene were the most abundant polymer types. The majority of primary microplastics arose from the industry sector as well as from personal care and cleaning products, whereas secondary microplastics constituted fibers from synthetic textiles and fragments of diverse origins. We highlighted the diversity of experimental and analytical approaches that could lead to high uncertainties in the measurements of microplastics abundance. Furthermore, the presence of microplastics in rivers was found to vary spatially likely due to point and nonpoint pollution sources of anthropogenic activities. Heterogenous environmental processes impacted the fate of microplastics characterized by various forms, sizes, and densities, in different ways. This impeded the identification of representative quantitative measurements of microplastics across different time frames. We advocate for the development of standardized protocols by the research community to ensure higher reproducibility of sampling, processing, and analysis of microplastics in aquatic environments. We recommend long‐term and site‐specific monitoring on microplastics with high data comparability to better inform policy making. This article is categorized under:Science of Water > Water QualityWater and Life > Conservation, Management, and Awareness [ABSTRACT FROM AUTHOR]

Per‐ and polyfluoroalkyl substances (PFAS) are persistent, bioaccumulative, and toxic synthetic chemicals of concern, which have been detected in nearly all environmental compartments. The present study provides a data analysis on PFAS concentrations in the Dutch inland and coastal national waters and fish sampled from 2008 to 2022 and 2015 to 2022, respectively. Although the fish database is relatively small, the water database is unique because of its temporal dimension. It appears that PFAS are omnipresent in Dutch water and fish, with relatively small spatial differences in absolute and relative concentrations (fingerprints) and few obvious temporal trends. Only perfluorooctanoic acid and perfluorooctanesulfonic acid (PFOS) aqueous concentrations in the rivers Rhine and Scheldt have substantially decreased since 2012. Still, PFOS concentrations exceed the European water quality standards at all and fish standards at many locations. Masses of PFAS entering the country and the North Sea are roughly 3.5 tonnes/year. Generally, the data suggest that most PFAS enter the Dutch aquatic environment predominantly through diffuse sources, yet several major point sources of specific PFAS were identified using fingerprints and monthly concentration profiles as identification tools. Finally, combining concentrations in fish and water, 265 bioaccumulation factors were derived, showing no statistically significant differences between freshwater and marine fish. Overall, the analysis provides new insights into PFAS bioaccumulation and spatiotemporal trends, mass discharges, and sources in The Netherlands. Environ Toxicol Chem 2024;43:965–975. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Lotic ecosystems are sources of greenhouse gases (GHGs) to the atmosphere, but their emissions are uncertain due to longitudinal GHG heterogeneities associated with point source pollution from anthropogenic activities. In this study, we quantified summer concentrations and fluxes of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and dinitrogen (N2), as well as several water quality parameters along the Rhine River and the Mittelland Canal, two critical inland waterways in Germany. Our main objectives were to compare GHG concentrations and fluxes along the two ecosystems and to determine the main driving factors responsible for their longitudinal GHG heterogeneities. The results indicated that the two ecosystems were sources of GHG fluxes to the atmosphere, with the Mittelland Canal being a hotspot for CH4 and N2O fluxes. We also found significant longitudinal GHG flux discontinuities along the mainstems of both ecosystems, which were mainly driven by divergent drivers. Along the Mittelland Canal, peak CO2 and CH4 fluxes coincided with point pollution sources such as a joining river tributary or the presence of harbors, while harbors and in-situ biogeochemical processes such as methanogenesis and respiration mainly explained CH4 and CO2 hotspots along the Rhine River. In contrast to CO2 and CH4 fluxes, N2O longitudinal trends along the two lotic ecosystems were better predicted by in-situ parameters such as chlorophyll-a concentrations and N2 fluxes. Based on a positive relationship with N2 fluxes, we hypothesized that in-situ denitrification was driving N2O hotspots in the Canal, while a negative relationship with N2 in the Rhine River suggested that coupled biological N2 fixation and nitrification accounted for N2O hotspots. These findings stress the need to include N2 flux estimates in GHG studies, as it can potentially improve our understanding of whether nitrogen is fixed through N2 fixation or lost through denitrification. [ABSTRACT FROM AUTHOR]

Rapid industrial development is one of the leading causes of environmental degradation. The textile industries and the domestic activities in Majalaya District produce wastewater directly discharged into the Cikakembang River. As a result, the Cikakembang River's water quality has decreased to the point that the water quality cannot be used for daily needs. This study modeled three main parameters in water quality modelling, namely Dissolved Oxygen (DO), Biological Oxygen Demand (BOD), and Chemical Oxygen Demand (COD). Using MATLAB, the three-water quality governing equations originating from the Advection-Dispersion Equation were solved using the Runge Kutte-4 discretization scheme. The numerical modelling was carried out along 2.36 km of the Cikakembang River. All water quality coefficients, such as the DO Saturation (DOsat), the Reaeration Rate (ka), the Dispersion Coefficient (D), the Deoxygenation Rate (kd), and the Decomposition Rate (kc), for the Cikakembang River were estimated using equations developed by existing studies. The estimation of ka and D coefficients requires hydraulic parameters, which in this study were estimated using the HEC-RAS simulation. Meanwhile, kd and kc values were obtained from the calibration and verification process. The Relative Root Mean Square Error (RRMSE) objective function was used to evaluate the results of water quality modelling at three sampling points. In the calibration process, the results of water quality modelling produced RRMSE values for the DO, BOD, and COD parameters of 1.99%, 0.36% and 0.92%, respectively. Meanwhile, for the verification process, the RRMSE values for the DO, BOD, and COD parameters are 1.95%, 1.02% and 1.86%. All water quality parameters produce small RRMSE values in the calibration and verification processes. Hence, the water quality model created has good accuracy and stability. [ABSTRACT FROM AUTHOR]

Given the widespread use as flame retardants, plasticizers, and organophosphate esters (OPEs) received increasing scientific interests on their occurrence and ecotoxicological research progress. This review comprehensively conducted bibliometric analysis and surveyed the OPEs occurrence in aquatic ecosystem (water, sediment, and aquatic organisms) and human-related (drinking water and sewage) over the past decade to unraveling knowledge gaps. The OPEs concentrations in water, sediment were at the range of not detected (n.d.) or several to hundreds ng/g or ng/L and exhibited landuses-specific characteristics. The electronic waste (e-waste) processing activities and sewage discharge were identified as point sources of OPEs in aquatic environment. Emission source intensity, water chemistry, and content of organic carbon were important for the partition and transfer processes of OPEs in the water, as well as hydrophobicity of OPEs dominating the absorption on the organic matter. Degradation, especially photodegradation and reductive degradation, has application potential in improving removal efficiencies of chlorinated-OPEs (Cl-OPEs) being reluctant to degrade. Generally, most surveyed OPEs have negligible ecological and health risks, whereas those OPEs with moderate threats or chronic effects on aquatic ecosystem should gain more attention. This review elucidates the status of OPEs pollution in water and highlights the need for more transport and degradation studies on traditional and emerging OPEs and metabolites to further identify potential threats on aquatic ecosystem. [ABSTRACT FROM AUTHOR]

Both human populations and marine biodiversity are concentrated along coastlines, with growing conservation interest in how these ecosystems can survive intense anthropogenic impacts. Tropical urban centres provide valuable research opportunities because these megacities are often adjacent to mega‐diverse coral reef systems. The Pearl River Delta is a prime exemplar, as it encompasses one of the most densely populated and impacted regions in the world and is located just northwest of the Coral Triangle. However, the spatial and taxonomic complexity of this biodiversity, most of which is small, cryptic in habitat and poorly known, make comparative analyses challenging. We deployed standardized settlement structures at seven sites differing in the intensity of human impacts and used COI metabarcoding to characterize benthic biodiversity, with a focus on metazoans. We found a total of 7184 OTUs, with an average of 665 OTUs per sampling unit; these numbers exceed those observed in many previous studies using comparable methods, despite the location of our study in an urbanized environment. Beta diversity was also high, with 52% of the OTUs found at just one site. As expected, we found that the sites close to point sources of pollution had substantially lower diversity (44% less) relative to sites bathed in less polluted oceanic waters. However, the polluted sites contributed substantially to the total animal diversity of the region, with 25% of all OTUs occurring only within polluted sites. Further analysis of Arthropoda, Annelida and Mollusca showed that phylogenetic clustering within a site was common, suggesting that environmental filtering reduced biodiversity to a subset of lineages present within the region, a pattern that was most pronounced in polluted sites and for the Arthropoda. The water quality gradients surrounding the PRD highlight the unique role of in situ studies for understanding the impacts of complex urbanization pressures on biodiversity. [ABSTRACT FROM AUTHOR]

Water quality deterioration and eutrophication have become a global concern, while reservoir pollution caused by multiple factors has led to frequent algal blooms, posing a serious threat to rural drinking water security and urban water supply. The purpose of this paper is to analyze the current water quality of Waihu Reservoir and use the single index method, the weighted comprehensive scoring method, and the nutrient level index method (TLI) to evaluate eutrophication. On this basis, the pollution sources of the reservoir are comprehensively analyzed and discussed, and effective control strategies are proposed. The evaluation results indicate that the reservoir is of moderate eutrophication type. Therefore, reducing the input of nutrients such as nitrogen and phosphorus in water is the main goal of alleviating exogenous pollution. The combination of engineering intervention and ecological restoration strategies to remove nutrients from the aquatic environment is an effective strategy to manage endogenous pollution. From the point of view of the source of pollution, this study provides an in-depth analysis of exogenous and endogenous pollution, respectively, and the proposed treatment is instructive for the control and routine management of eutrophication in the Waihu Reservoir, as well as for the management of similar problems in different reservoirs. [ABSTRACT FROM AUTHOR]

The Betwa River Basin (BRB), a sub-basin of the River Yamuna, is the oldest flowing water system in Central India. The water quality of the rivers are under stress, hence regular monitoring and appraisal is required to know the health of the rivers. Factor analysis and principal component analysis (FA/PCA) multivariate statistical techniques were used to extract three and four varimax factors that explained 96.408 and 100.00 percent of the total variance in water quality, respectively. Cluster analysis (CA) categorizes observed items into distinct quality categories based on correlations between stations and years. Point industrial/sewage effluents, diffuse pollution as runoff from arable land, erosion, and natural source pollution contribute to the pollution of the BRB. As a result, water quality is threatened or impaired, and conditions often departed from natural or desirable levels at Rajghat, Garrauli, Mohana, and Shahijina stations. According to the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), the surface water quality at the Rajghat and Mohana stations corresponds to fair ecological status. However, the surface water quality of the Garrauli and Shahijina stations has a marginal water quality as per CCME-WQI. From 1985 to 2018, the Shahijina had the most considerable load of nutrients and organic matter, as determined by the CCME-WQI and by comparing the water quality data. A thorough examination had revealed a fluctuating trend in the BRB pollution, particularly at all stations. Results indicate that between 1985 and 2018, the only defense mechanism of the river was the auto purification mechanism, which is strongly influenced by the drought, point pollution source, and extreme meteorological events that probably cause these fluctuations. [ABSTRACT FROM AUTHOR]

Although phytoplankton is well known as robust bioindicators to aquatic environments, their indicating functions based on different community parameters remain to be understood. In order to filter effective bioindicators in aquatic ecosystems, four phytoplankton community parameters including species richness (SR), total biomass (SBP), functional groups (FGBP), and size-fractionated chlorophyll-a (SC) were demonstrated in a subtropical artificial lake with ecological restoration in South China. Our results indicated that all the above four parameters exhibited high sensitivity to environmental variations and illustrated distinct aspects of indicating functions to aquatic environments due to their individual biological characteristics. Based on FGBP, both spatial and temporal differences in phytoplankton community could be identified. SR and SBP only classified the spatial and temporal distributions, respectively, while SC could distinguish the sewage outfalls from other sites. In terms of ecological management, two parameters (SR and FGBP) could distinguish the restored waters from untreated environments as non-point source pollution, and another parameter SC could indicate the sewage outfalls as point source pollution. Therefore, the combination of the above two categories of phytoplankton community parameters could make the strongest indicating functions. Our study provided greater insight into indicating functions of phytoplankton community parameters in an ecological restored lake and enabled better managements in such artificial lakes. [ABSTRACT FROM AUTHOR]

Groundwater vulnerability has gained widespread attention, particularly in Chiang Mai Province, one of Thailand's fastest-growing cities, which is experiencing rapid development in both economic and social sectors. The expansion of urban communities and the industrial, tourism, and agriculture sectors has resulted in the overutilization of available resources, notably water resources. This overuse, coupled with the adoption of modern technology to boost productivity and meet market demands, has led to an increased reliance on groundwater to supplement surface water sources, providing benefits across all sectors. However, the economic and social growth plays a pivotal role in shaping the diversity of land use, encompassing residential, commercial, industrial, and agricultural activities. These activities, in turn, directly contribute to environmental pollution, particularly in terms of the risk of groundwater contamination in Chiang Mai Province. This study aims to predict the future vulnerabilities of groundwater resources under an ensemble of climate change scenarios and changes in land-use patterns. Chiang Mai Province in northern Thailand is one of the fastest-growing cities and therefore is experiencing rapid urbanization, as well as land-use pattern changes, which was important for the case study. The new DRASTIC model, namely the DRASTIC-LP model, combined with GIS-based techniques and overlay techniques, was used to generate the map of groundwater resource vulnerabilities. A point pollution source (P)-related land-use pattern (L) that represents contamination impacts was considered an additional new DRASTIC parameter. The study's findings reveal the high reliability and maximum effectiveness of the new DRASTIC-LP model in assessing groundwater vulnerability and contamination-risk areas under a climate change scenario (by MIROC-ESM-CHEM model under RCP.8.5 scenario) and land-use pattern changes (by CA_Markov Chian Model) for both the current year (2020) and the next 50-year period (2021–2070). Furthermore, the new DRASTIC-LP model is employed to trace the movement of pollutants from high- to very high-risk areas based on the groundwater vulnerability and contamination-risk maps. The results highlight that waste disposal dumping sites pose a more critical distribution and movement of pollutants when compared to industrial sites. Additionally, unconsolidated aquifers and cracked consolidated rock aquifers show a potentially higher occurrence of pollutant distribution and movement when compared to consolidated aquifers. Consequently, the study's outcomes are applied to formulate guidelines for the management and control of groundwater resource contamination. These guidelines serve as valuable tools for decision makers, aiding in pollution prevention and the effective management of contamination risks in groundwater resources. [ABSTRACT FROM AUTHOR]

In situ monitoring is fundamental to manage eutrophication in rivers and streams. However, in recent decades, the frequency and spatial coverage of regulatory monitoring have often been reduced due to funding and infrastructure limitations. This reduction has made it impossible to provide adequate coverage for most water bodies. In this study, trained citizen scientists filled spatial and temporal gaps in agency monitoring across a major catchment in rural England. By integrating data from citizen scientists, regulatory agencies, and the local water company, it was possible to demonstrate the opportunities for hypothesis-based citizen scientist monitoring to identify continuous and event-driven sources of phosphate pollution. Local citizen scientists effectively covered important spatial gaps, investigating river conditions both upstream and downstream of suspected pollution point sources, improving the identification of their temporal dynamics. When combined with long-term monitoring data from regulatory agencies, it became possible to identify areas within the catchment that exhibited increased phosphate concentrations during periods of low river discharge (summer). Inter-annual trends and anomaly detection suggested that continuous pollution sources dominated over event-driven sources in many sub-basins, allowing for the prioritisation of mitigation actions. This study highlights the opportunity for citizen scientists to fill gaps in regulatory monitoring efforts and contribute to the improved management of eutrophication in rural catchments. [ABSTRACT FROM AUTHOR]

Knowledge about the long history of the anthropogenic inputs of Nitrogen (N) and Phosphorus (P) is crucial to capture long-term N and P processes (legacies) and to investigate water quality and ecosystem health. These inputs include N and P point sources, that originate mainly from wastewater, and that are directly discharged into surface waters, thus having an immediate impact on ecosystem functioning. However, N and P point sources are challenging to estimate, due to the scarcity and uncertainty in observational data. Here, we contribute towards improved characterisation of N and P point sources from wastewater, by providing a long-term (1950--2019), high resolution (0.015625°~ 1.4 km on average) dataset for Germany. The dataset includes both the domestic and industrial emissions treated in wastewater treatment plants and untreated domestic emissions that are collected in the sewer system. We adopt a modelling approach that relies on a large range of data collected from different sources. Importantly, we account for the uncertainties arising from different modelling choices (i.e., coefficients and downscaling approach). We provide 200 gridded N and P point sources realisations, which are constrained and evaluated using available (recent) observations of wastewater treatment plants outgoing loads. We discuss the uncertainties in our reconstructed dataset over a large sample of river basins in Germany, and provide guidance for future uses. Overall, by capturing the long-term spatial and temporal variations in N and P point sources and accounting for uncertainties, our dataset can facilitate long-term and large-scale robust water quality studies. The dataset is available at https://doi.org/10.5281/zenodo.10500535 (Sarrazin et al., 2024). [ABSTRACT FROM AUTHOR]

Atmospheric environmental issues have evolved from point source pollution to regional pollution, leading to controlling specific air pollutant emissions. A-value method has been found suitable for estimating large-scale atmospheric environmental capacity rather than small-scale, resulting in the inaccuracy of developing air pollution control strategy. This study proposed a grid computing method based on the CALPUFF modelling system and GIS spatial analysis tool. The meteorological data from the MM5 model were used to simulate the spatial distribution of air pollutants. The meteorological flow field data was used to simulate the ventilation coefficient. The A value was revised with the simulated to achieve accurate results of atmospheric environment capacity. The credibility was verified by applying this method to Fengtai District, Beijing, China. The research area was divided into small partitions via the ArcGIS spatial analysis tool. The simulation results agreed well with the observation data from actual monitoring stations, even for the PM10 concentration with the most significant error (MRE: 7.05%−13.28%, RMSE: 11.62–17.89, R2: 0.84–0.90). The GIS spatial analysis tools were applied to match the underlying surface types and overcome the restrictions of administrative boundary management. The study proposed four schemes to achieve differentiated air pollutant emission reduction and develop suitable control strategies. Furthermore, this method can be applied on different scales of natural geographic boundaries and realize the precise spatial management of atmospheric environmental capacity. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) are deemed major conveyors and point sources of per‐ and polyfluoroalkyl substances (PFAS) to the environment. This statistical meta‐analysis of existing literature from the past 15 years focused on the significance of treatment type for PFAS removal efficiencies and the influence of PFAS sources (domestic vs. industrial) on their removal. Different sampling events, WWTPs across the world, different treatment technologies, configurations, and processes, as well as different PFAS classes and compounds were considered. This study evaluated 13 PFAS analyzed predominantly in 161 WWTPs across the world. The statistical test results revealed that these 13 frequently detected and reported PFAS can be divided into four groups based on their behavior during wastewater treatment, namely (1) C6–10 perfluorocarboxylic acids (PFCAs), (2) C4,5,11,12 PFCAs, (3) C4,6,8 perfluoroalkane sulfonic acids (PFSAs), and (4) C10 PFSA. In this study, biological treatments such as (1) membrane bioreactors, (2) combination of two or more biological treatments, and (3) biofilm processes revealed the highest PFAS removals, although the addition of a tertiary treatment actually had a nonbeneficial effect on PFAS removal. Moreover, a strong statistical correlation was observed between industrial wastewater sources and the presence of high influent PFAS concentrations in the receiving WWTPs. This indicates that industrial sources were the main contributors of the PFAS load in the analyzed WWTPs. Integr Environ Assess Manag 2024;20:59–69. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: Per‐ and polyfluoroalkyl substances (PFAS) from the same group behave differently based on their chain length.Biological treatment affects PFAS removals to the greatest extent.Precursor degradation affects the removal efficiencies.High PFAS influent concentrations correlate with industrial contribution. [ABSTRACT FROM AUTHOR]

Analyzing 165 data from five national control sites in Baiyangdian Lake, this study unveils its spatiotemporal pattern of water quality. Utilizing machine learning and multivariate statistical techniques, this study elucidates the effects of rainfall and human activities on the lake's water quality. The results show that the main pollutants in Baiyangdian Lake are TN, TP, and IMN. Spatially, human activities are the main drivers of water quality, with the poorest quality observed in the surrounding village area. The temporal dynamics of water quality parameters exhibit three distinct patterns: Firstly, parameters predominantly influenced by point source pollution, like TN and NH4+-N, show lower concentrations during flood periods. Secondly, parameters affected by non-point source pollution, such as TP, show higher concentrations during flood periods. Thirdly, irregular variations were observed in pH, DO, and IMN. The evaluation of Baiyangdian Lake's water quality based on the grey relationship analysis method indicates that its water quality is good, falling within Classes I and II. Time series analysis found that the dilution effect of rainfall and the scouring action of runoff dominate the temporal variation in water quality in Baiyangdian Lake. The major pollution sources were identified as domestic sewage, followed by agricultural non-point source pollution and the release of internal pollutants. Additionally, aquaculture emerged as a significant contributor to the Lake's pollution. This research provides a scientific basis for controlling the continuous deterioration of Baiyangdian Lake's water quality and restoring its ecological function. [ABSTRACT FROM AUTHOR]

A portable toilet manufacturer in northwest Indiana (USA) released polyethylene microplastic (MP) pollution into a protected wetland for at least three years. To assess the loads, movement, and fate of the MPs in the wetland from this point source, water and sediment samples were collected in the fall and spring of 2021–2023. Additional samples, including sediment cores and atmospheric particulates, were collected during the summer of 2023 from select areas of the wetland. The MPs were isolated from the field samples using density separation, filtration, and chemical oxidation. Infrared and Raman spectroscopy analyses identified the MPs as polyethylene, which were quantified visually using a stereomicroscope. The numbers of MPs in 100 mL of the marsh water closest to the source ranged from several hundred to over 400,000, while the open water samples contained few microplastics. Marsh surface sediments were highly contaminated with MPs, up to 18,800 per 30.0 g dry mass (dm), compared to core samples in the lower depths (>15 cm) that contained only smaller MPs (<200 µm), numbering 0–480 per 30.0 g (dm). The wide variations in loads of MP contaminants indicate the influence of numerous factors, such as proximity to the point source pollution, weather conditions, natural matter, and pollution sinks, namely sediment deposition. As proof of concept, we demonstrated a novel remediation method using these real-world samples to effectively agglomerate and remove MPs from contaminated waters. [ABSTRACT FROM AUTHOR]

Nothing can replace water as the most vital natural resource we utilize on a daily basis. It is the most critical component of the earth's life support system, and life would not be possible without it. The world's population is growing at an alarming rate, making freshwater availability a significant problem for emerging nations like India. The environment is becoming out of balance due to pollution from point and non-point sources. To be fit for human consumption, water must be clear of all pollutants. High dangers to human health are increased by contaminated water systems. Gomati Taal, Madho, Tanda, Pilibhit, Uttar Pradesh is the source of the Gomti River (25°30'N; 83°10' E). A bacterial evaluation of the Gomti River's several Ghats has been conducted in light of the pollution levels and how they affect human health. It has been explored how the existence of indicator bacteria affects other microorganisms. [ABSTRACT FROM AUTHOR]

Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4, a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced HyperSpectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in center wavelength and change in full-width-half-maximum (FWHM) are estimated for all spectra channels, which are used as inputs for retrieving the enhancement of column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of emission flux rate by up to 5.0%. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 857.67 ± 207.34 kg·h-1 to 14333.02 ± 5249.32 kg·h-1. The total emission flux rate reaches 13.26 t·h-1 in Shanxi, assuming all point sources emit simultaneously. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84% to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing with ground-based meteorological station. We found large discrepancy, especially in wind direction, suggesting incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi. [ABSTRACT FROM AUTHOR]

Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4, a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced HyperSpectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in center wavelength and change in full-width-half-maximum (FWHM) are estimated for all spectra channels, which are used as inputs for retrieving the enhancement of column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of emission flux rate by up to 5.0 %. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 857.67 ± 207.34 kg·h-1 to 14333.02 ± 5249.32 kg·h-1. The total emission flux rate reaches 13.26 t·h-1 in Shanxi, assuming all point sources emit simultaneously. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84 % to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing with ground-based meteorological station. We found large discrepancy, especially in wind direction, suggesting incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi. [ABSTRACT FROM AUTHOR]

Effective management of nitrate loading in complex river systems requires quantitative estimation to trace different nitrogen sources. This study aims to validate an integrated framework using soluble nitrogen isotope ratios (δ15N–NH4 and δ15N–NO3) and hydrological modeling (hydrological simulation program SPARROW) of the main stream and tributaries in the Yeongsan River to determine anthropogenic nitrogen fluxes among different land-use types in the complex river watershed. The δ15N–NH4 and δ15N–NO3 isotopic compositions varied across different land-use types (4.9 to 15.5‰ for δ15N–NH4 and −4.9 to 12.1‰ for δ15N–NO3), reflecting the different sources of nitrogen in the watershed (soil N including synthetic fertilizer N, manure N, and sewage treatment plant effluent N). We compared the soluble nitrogen isotopic compositions (δ15N–NH4 and δ15N–NO3) of the river water with various nitrogen sources (soil N, manure N, and sewage N) to assess their contribution, revealing that N from sewage treatment plant effluent as a point source was dominant during the dry season and N from forest- and soil-derived non-point sources was dominant due to intensive rainfall during the wet season. The coefficient of determination (R2) between the measured pollution load and the predicted pollution load calculated by the SPARROW model was 0.95, indicating a high correlation. In addition, the EMMA-based nitrogen contributions compared to the SPARROW-based nitrogen fluxes were similar to each other, indicating that large amounts of forest- and soil-derived N may be transported to the Yeongsan River watershed as non-point sources, along with the effect of sewage treatment plant effluent N as a point source. This study provides valuable insights for the formulation of management policies to control nitrogen inputs from point and non-point sources across different land-use types for the restoration of water quality and aquatic ecosystems in complex river systems. Given the recent escalation in human activity near aquatic environments, this framework is effective in estimating the quantitative contribution of individual anthropogenic nitrogen sources transported along riverine systems. [ABSTRACT FROM AUTHOR]

Hydrological drought has wide‐ranging impacts on water quality, nutrient and carbon metrics, and given the uncertainty of climate change and the predicted increased frequency and intensity of drought in the future, investigations into changes induced by drought become increasingly important. This study compared physicochemical parameters (temperature, conductivity, pH and DO), nutrients (TN, NOX [NO2 + NO3], NH3 and TP) and carbon (TOC and DOC) between hydrological drought conditions (2006–2008) and hydrological normal conditions (2016–2019) at five sites along the lower Savannah River (Georgia, USA). Although we had predicted that water temperatures would increase from drought, we instead found temperature was significantly lower during drought conditions. Levels of pH and DO were significantly higher during drought. Further, TN, TOC and DOC concentrations were significantly lower during drought, but NOX concentrations were significantly higher during drought. Conductivity varied at the lower river sites, being significantly higher during drought at sites located below the city of Augusta, GA. These complex changes could be attributed to volume reductions coupled with an increase in the percentage of total flow originating from groundwater as well as limnetic reservoir inputs, persistent point source pollution, reduced natural catchment inputs and/or reduced floodplain interactions. The changes that occurred during drought may be disruptive to aquatic life, not only from reduced water quantity but also due to a scarcity of some biologically essential materials and lower food resources, combined with artificially high levels of some other potentially stressful materials. [ABSTRACT FROM AUTHOR]

The localization of pollution sources is one of the main tasks in environmental engineering. For this paper, models of spatial distribution of nitrate concentration in groundwater were created, and the point of highest concentration was determined. This point represents the assumed location of the pollution source and differs from the actual location, so there is a certain distance between the measured and assumed location. This paper puts forward a new hypothesis that the distance between the measured and the assumed location is a function of the variance of the estimation error. The scientific contribution of this paper is based on the fact that the interaction of statistical and geostatistical methods can locate the dominant point source of pollution or narrow down the search area. The above hypothesis is confirmed by the example of the Varaždin wellfield, which was closed due to an excessively high groundwater nitrate concentration. Seven different interpolation methods were used to create spatial distribution models. Each method provides a different model, a different variance of the estimation error, and estimates of the location of the pollution source. The smallest value of variance of the estimation error of 1.65 was obtained for the minimum curvature interpolation method and the largest value of variance (24.49) was obtained for the kriging with logarithmic variogram. Our results show a nonlinear and monotonic relationship between the distance and the variance of the estimation error, so logarithmic and rational quadratic models were fitted to the scatter point data. The models were linearized, a t-test was performed, and the results show that the models can be considered reliable, which is confirmed by the values of the coefficients of determination of the linearized models, which are around 0.50. The obtained results can be used in planning additional research work to determine the measured location of the pollution source. The research methodology we used is universal and can be applied to other locations where high concentrations of certain contaminants have been detected in groundwater in alluvial aquifers. [ABSTRACT FROM AUTHOR]

Landfill leachate is regarded as a significant point source of pollutants that may pose a hazard to the environment, particularly to surface and ground waters. Leachates are highly variable and heterogeneous. Our study was focused on the characterization of landfill leachates derived from young (YDS) and matured (MDS) dumpsites in terms of the abundance of micropollutants, antimicrobial resistance genes (ARG), and microbial community structure. The concentrations of poly- and perfluoroalkyl substances (PFASs) were found to be higher in MDS compared to YDS, i.e., 13.19 and 7.16 μg/L, respectively. Among pharmaceutical compounds, ibuprofen was detected at the highest concentrations, i.e., 12.54, 12.81, and 13.13 μg/L, in the leachates derived from MDS, YDS, and ponds. The distribution of bacteria, archaea, eukaryotes, and viruses in the three leachate samples was as follows: 85.15 ÷ 88.04%, 9.13 ÷ 12.29%, 2.20 ÷ 2.68%, and 0.12 ÷ 0.15%, respectively. In total, 31 distinct families of ARGs were identified, comprising a total of 80 ARGs. Incubation of P. putida MSCL650 in sterile leachate from the pond resulted in decreasing the minimum inhibitory concentrations for six antibiotics as compared to cells incubated in nutrient broth. Hydrological processes, i.e., runoff and infiltration, can increase the dissemination of ARGs. [ABSTRACT FROM AUTHOR]

Although the Clean Water Act's regulation of point source pollution has had a significant effect on water quality, nonpoint sources of pollution, especially animal agriculture, remain a leading unevenly regulated source of water pollution in the United States. This work studies the effectiveness of local manure management regulations on dairy farms in Wisconsin. Wisconsin represents a unique policy experiment in the delegation of nonpoint agricultural pollution policy in a state with economically important small, nonpoint, dairy farms. Using hand collected regulatory data from Wisconsin counties we estimate the effects of changes in local regulations on water quality outcomes. The results demonstrate that a few easily implemented and verifiable regulations such as nutrient management plans have significant short‐term effects on water quality, whereas other less observable and difficult to implement regulations have no discernible effects in the short term. The work points to a number of potential policy levers to improve the Management of nonpoint pollution, as well as the challenges of nonpoint source regulatory policies on slow‐moving hydrologic processes. [ABSTRACT FROM AUTHOR]

In numerous environmental compartments around the world, the existence of micro- and nanoplastics (MNPs) in the environment has been verified. A growing number of studies have looked at the interaction between MNPs and human activities due to the risks they may pose to humans. Exposure pathways are key factors in measuring MNPs risks. However, current research largely ignores the contribution of mechanical fragmentation pathways to MNPs exposure during the daily use of plastic products. Our critical review demonstrated the research gap between MNP fragmentation and risk assessments via a network analysis. The release of fragmented MNPs and their properties were also described at various scales, with emphasis on environmental stressors and mechanical fragmentation. In the scenarios of daily use, plastic products such as food packaging and clothing provide acute pathways of MNPs exposure. The release tendency of those products (up to 102 mg MNPs) are several orders of magnitude higher than MNPs abundances in natural compartments. Despite the limited evidence available, waste recycling, landfill and municipal activities represented long-term pathways for MNPs fragmentation and point sources of MNPs pollution in environmental media. Assessing the health effects of the fragmentation process, unfortunately, is further hampered by the current absence of human exposure impact assessments for secondary MNPs. We proposed that future studies should integrate aging evaluation into risk assessment frameworks and establish early warning signs of MNPs released from plastic products. [ABSTRACT FROM AUTHOR]

This study aims to identify sources of pollution and determine the magnitude of the potential pollution load from pollutant sources in the Wai Batu Merah watershed, Sirimau District, Ambon City. The method for identifying sources of pollution is carried out by using saturated or census sampling methods, calculating pollutant loads using direct methods for point source pollutant sources and indirect methods for non-point sources . The direct calculation method uses wastewater discharge data and the results of wastewater quality analysis results from measurements directly at the point source pollutant wastewater treatment plant (WWTP). The wastewater sampling technique uses the grab sampling method. While the indirect method uses effluent factors and supporting data from non-point source pollution sources that have been identified in the Wai Batu Merah watershed. The results showed that the pollutant sources found in the Wai Batu Merah watershed were point sources originating from hotel and health facility activities and non-point sources originating from domestic activities from residential areas, agricultural and livestock businesses, nonpoint source land (forest and open land), micro, small and medium enterprises (MSMEs), small scale industries and waste. The dominant pollutant source in the Wai Batu Merah watershed comes from domestic non-point sources. The highest point source pollution loads for BOD, COD and TSS parameters in the Wai Batu Merah watershed came from hotel activities in segment 6 with the contribution of each parameter of 17.82 kg/day, 23.82 kg/day and 0.029 kg/day. Meanwhile, the highest non-point source pollution load for BOD, COD and TSS parameters came from non-point source waste in segment 6 with the contribution of each parameter of 2825.3 kg/day, 3884.8 kg/day and 2684.03 kg/day. [ABSTRACT FROM AUTHOR]

Faisalabad industrial units discharge effluents and associated toxic chemicals into the environment, deteriorating ecological conditions and ecosystem health. Morphoanatomical changes in some medicinally important native species (Calotropis procera, Eclipta alba, Phyla nodiflora, and Ranunculus sceleratus) exposed to heavy industrial pollution gained evaluation. These species of choice were due to their widespread distribution in the area. Ten sites selected in the River Chenab, Chiniot, had three near point source pollution of Faisalabad industries within the 500-m radius (polluted) at three drains and two sites inside the river after each drain point source with the control site at 14 km after from the first industrial drain point source. The general response of all plants to effluents was growth retardation. Plant height increased significantly in all species from river sites. An increase in tallness was more prominent in species like C. procera and P. nodiflora. An increase in stem sclerification in C. procera and E. alba from polluted sites occurred, which indicated a better ability to tolerate industrial pollution. Remarkable increases in stem and leaf epidermis, intensive stem sclerenchyma, and closely packed stem vascular bundles in C. procera appeared, which could increase resistance to industrial pollution. Most of the morphoanatomical parameters notably attained a decrease in E. alba, the most vulnerable species. Plant survival depends on particular structural changes in dermal, mechanical, parenchymatous, and vascular tissues. Overall, industrial pollution adversely impacts plant morphological and micromorphological features, although the reaction of specific species to industrial contamination varies. The study determined that stem and leaf anatomical features, such as, epidermis size and storage tissue thickness, are suitable morphoanatomical markers for industrial pollution biomonitoring. Internal modifications of plants vegetating different industrial contaminated sites played a significant role in high tolerance levels. [ABSTRACT FROM AUTHOR]

Soil heavy metal pollution and complex sources have posed the serious risks on the ecological system in recent years. In this study, the positive matrix factorization (PMF) model was established to explore the spatial distribution and sources of heavy metals in soil. The composite polluted soil was taken from the Yuanyang floodplain of the lower Yellow River. 81 surface soil (0-20 cm) samples were collected to identify the soil heavy metal, such as Pb, Cu, Cd, Hg Cr, Ni, Zn and As. A systematic analysis was then made to determine the pollution content and spatial distribution of heavy metals. The geographical accumulation index and potential ecological risk index were used to assess the pollution degree of heavy metals and their ecology risk. The contents of Pb, Cu, Cd, Hg, Cr, Ni, Zn, and As in the soil of the study area were 27.77, 27.05, 0.31, 0.24, 73.55, 25.38, 88.25, and 29.00 mg/kg, respectively. Among them, Hg pollution was the most severe with an average content nearly 7 times of the soil background value, indicating a strong ecological risk, followed by Cd pollution with a strong ecological risk. An island -like pattern was observed in the spatial distribution of heavy metal concentration in the Yuanyang Beach District. The Cu, Ni, Pb, and Cd pollution were widely polluted with the high value in the central Jiangzhuang Township of the study area. An overlapping space was found on the high value distribution of Zn, Cr, As, and Hg in the surface soil, indicating the point source pollution. The geographical accumulation index also showed that the Hg pollution was the most serious, followed by As and Cd. The intensity of potential ecological risk was ranked in the descending order of Hg>Cd>As>Pb>Cu>Ni>Cr>Zn. The heavy metal of Hg presented the very strong ecological hazards, while Cd was the strong ecological hazards, and the rest were belonged to the slight ecological hazards. The potential ecological risk index (RI) was 459.31 on average among the eight heavy metals, indicating the level of strong ecological hazards. The contribution rates of Hg and Cd were 61.66% and 27.71%, respectively. The spatial interpolation was performed on the comprehensive potential ecological risk index of heavy metals. The most severe pollution of heavy metals was distributed in Xibianqiao North Township and middle Jiangzhuang Township, indicating a strong ecological risk level. The Hg and Cd pollution were relatively sereve and posed the greatest ecological harm to the environment. The cluster and source analysis showed that the heavy metal pollution was attributed to the industrial, transportation, natural, coal-burning, and agricultural sources. Agricultural sources were dominated in the soil heavy metal pollution, with the relative contribution rate of 23.5%. By contrast, the relative contribution rate of industrial, transportation, natural and coal-burning sources were 16.2%, 22.1%, 19.4% and 18.9%, respectively. The finding can provide a strong reference to identify the pollution sources of polymetallic composite polluted soil. The scientific basis and data support can greatly contribute to the "scientific pollution control" and "precise pollution control" of the soil for the better Ecological protection and high-quality development in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) represent major point sources of pollution in coastal systems, affecting benthic ecosystems. In the present study, we assessed the potential role that WWTPs have in shaping nematode communities and established baseline knowledge of free-living nematode community structures in St. Andrew Bay, Florida. Sediment samples were collected from four sites representing areas of WWTP outflow and areas with no apparent outflow, during the winter and summer. Nematode communities across sites were significantly different, and the differences were strongly associated with the distance to the nearest WWTP. While the communities were not different along transects at each site, nor across seasons, community dissimilarity across sites was high, implying strong contrasts throughout the bay system. Dominance of tolerant, opportunistic genera and Ecological Quality Status assessments suggest that the system is stressed by organic enrichment, possibly linked to the WWTPs. Our results suggest that knowledge on the life-history of dominant genera is imperative to assess the ecological quality of a benthic system, in addition to taxonomic and functional metrics. Considering the value of marine nematodes as bioindicators, more work should be done to monitor temporal variability in nematode communities in this system as future infrastructure changes alter its dynamics. [ABSTRACT FROM AUTHOR]

Accurate identification of nitrate (NO3−) sources is critical to addressing groundwater pollution, especially in highly vulnerable karst aquifers. The groundwater hydrochemistry and δ15NNO3 and δ18ONO3 isotopes were analyzed in samples taken from the Jinan Spring Catchment, which has been affected by urbanization and agricultural activities. The study highlighted the use of hydrochemistry, environmental isotopes, and a multisource linear mixed model for NO3− source identification and apportionment. The results showed that, controlled by carbonate rocks, the hydrochemical types in both rainy and dry seasons were highly consistent, and HCO3·SO4−Ca was the dominant type, accounting for 60%. Except for Ca2+, Mg2+ and HCO3−, the coefficients of variation of other ions were all greater than 0.5 in rainy and dry seasons. The chemical composition of groundwater was mainly controlled by water–rock interaction. Ca2+ and HCO3− were mainly derived from carbonate rock dissolution; K+, Na+, SO42−, NO3− and Cl− were partially derived from atmospheric precipitation. The IsoSource model quantitatively revealed that the majority of the groundwater and surface water was influenced by manure and sewage (M&S) contributing 39.3% and 52.3% in the rainy season, and 37.1% and 56.9% in the dry season, respectively. The NO3− source fraction rates were in the order M&S > SON > AF > CF > AD. In addition, nitrate pollution control measures and suggestions for different areas are put forward. In rural residential areas, the free discharge of livestock manure and sewage should be strictly controlled. In agricultural planting areas, chemical fertilizers and pesticides should be used rationally to prevent non-point source pollution. In urban areas, the centralized treatment of industrial and residential sewage should be strengthened to prevent point source pollution. [ABSTRACT FROM AUTHOR]

The Danube navigation is geographically limited and subject to the effects of environmental change. On the other hand, the Danube commercial navigation is the point source of pollution with emissions of the Danube vessels and harbours, directly polluting the environment. The focus of this paper is the annual evaluation and calculation of air polluting emissions from fossil fuel consumption from the following types of the Danube fleet: push boats, pull boats, freight motor vessels and cruise passenger ships. Emissions from the Danube transport vessels are estimated by EMEP/EEA (European Monitoring and Evaluation Programme/European Environment Agency) air pollutant emission inventory guidebook within Serbian-Croatian, Serbian and Serbian-Romanian sections of the Danube fairway on an average level. Emissions costs for all types of the Danube fleet (euro per vessel-kilometre) are estimated by the Practical guideline for realistic transport pricing depending on the population density close to the waterway: rural or urban area. [ABSTRACT FROM AUTHOR]

Excessive and unplanned growth of urbanization caused severe environmental degradation. Lakes are important ecosystems because of the variety of uses for their water, including industrial, recreational, agricultural, and water retention. Hatirjheel Lake became one of the famous recreational destinations in Dhaka, Bangladesh and due to this reason, the water quality has deteriorated; therefore, it is necessary to monitor the water quality regularly. This paper aims to assess the water quality of Hatirjheel Lake to find out its present state. Water samples were collected from five different sampling points based on sources of pollution by the purposive sampling method. The water sample has been analyzed for various physiochemical parameters, including Color, Odor, Temperature, pH, Dissolved Oxygen (DO), Electrical Conductivity (EC), Total Dissolved Solid (TDS), and Total Suspended Solid (TSS) and also calculated the correlation between parameters. From the overall analysis, it is evident that six types of color and strong odor were found, and water temperature varied from 30°C to 31°C, pH varied from 6.35 to 7.16, DO varied from 2.80 to 4.42 mg/L, EC from 0.6 to 0.7 dS/m, TDS varied from 577 to 680 mg/L, and TSS varied from 2.41 to 5.61 mg/L. Moreover, interpreting the findings in the context of comparison with previous studies, the results collectively suggest a decline in water quality, highlighting the need for immediate attention and intervention. Therefore, inclusive public consciousness, and government monitoring must be adopted to save the quality of water in Hatirjheel Lake. [ABSTRACT FROM AUTHOR]

A better understanding of diffuse pollution processes distressing surface water bodies is relevant to develop actions focused on the sustainable management of water resources. This research aims to identify relevant watershed variables that explain the spatial variability patterns of surface water quality in lotic mountain water bodies. Twenty-eight candidate variables (10 land cover and land use (LCLU), 6 pedo-topographic (PT), and 12 hydrometeorological (HM)) were defined to explain the concentration of six water quality parameters temperature (T), pH, dissolved oxygen (DO), chemical oxygen demand (COD), electrical conductivity (EC), and nitrates (NO3-)) in 76 surface water streams of the Andina region, Colombia. The selection of the explanatory variables was carried out by applying an iterative input selection (IIS) algorithm based on highly randomized tree models. The results show that the variability in the concentration of each water quality parameter is explained by a combination of LCLU, HM, and PT variables. LCLU was the most important group of explanatory variables in the selection, followed by HM variables group. This is not the case for DO, where the HM variables show the highest importance. In all the implemented models, the PT variables showed the lowest incidence. This research developed a success approach for identifying basin variables able to contribute to understand non-point sources of pollution, and thus it was not oriented to create a predictive model of water quality, but rather to use machine learning modeling to expose probable relationships between watershed attributes and the quality of surface water. These results can support other water quality studies and territorial planning instruments on the role of watershed-scale variables in diffuse pollution processes in surface water bodies. The implemented algorithm provided modeling flexibility, computational efficiency, and minimum redundancy, allowing a reasonable representation of the observational data set. [ABSTRACT FROM AUTHOR]

Point source pollution by pesticide use poses serious challenges for soil and water quality, especially in developing countries, where heavy pesticide use is often noted. However, data on farmers' practices of waste disposal and factors affecting actual behavior are scarce. The current study dealt with farmers' practices and safety behavior in proper disposal of empty pesticide containers (EPC) in Ardabil Province, Iran, based on a survey with structured questionnaires. Almost 30% of the farmers mentioned that they were leaving EPC in the farm or throwing EPC in water canals, while the remaining farmers reported that they were burning EPC or throwing them in the common trash. Concerning information on proper disposal of EPC, almost one-third of the respondents (34.3%) had no information, while above half (56.3%) had very low or low information. On a scale from 1 to 5, farmers' showed relatively negative attitudes towards proper disposal of EPC. Moreover, farmers showed low levels of subjective norms and perceived behavioral control, i.e. they were not influenced by people around them in the proper management of EPC and had fair control of proper management of EPC. Therefore, farmers showed slightly negative intention and rather weak behavior to proper disposal of EPC. Attitudes and subjective norms showed a positive effect (P < 0.05) on farmers' intention towards disposal of EPC and farmers' intention showed a positive effect (P < 0.05) on actual behavior towards disposal of EPC. Findings provide novel fundamental information for more effective disposal schemes of EPC in the study area, where disposal of pesticide waste is insufficient. Promoting attitudes towards proper disposal of EPC through information from peers or important individuals to farmers can be targeted for promoting environmentally friendly behavior of farmers with proper practices of EPC disposal after use. [ABSTRACT FROM AUTHOR]

Municipal wastewater has been considered as one of the largest contributors and carriers of microplastics to the aquatic environment. However, the various residential activities that generate municipal wastewater are equally significant whenever the source of microplastics in aquatic system is accounted. However, so far, only municipal wastewater has received wide attention in previous review articles. Hence, this review article is written to address this gap by highlighting, firstly, the chances of microplastics arising from the usage of personal care products (PCPs), laundry washing, face masks, and other potential sources. Thereafter, the various factors influencing the generation and intensity of indoor microplastic pollution and the evidence available on the possibility of microplastic inhalation by humans and pet animals are explained. Followed by that, the removal efficiency of microplastics observed in wastewater treatment plants, the fate of microplastics present in the effluent and biosolids, and their impact on aquatic and soil environment are explored. Furthermore, the impact of aging on the characteristics of microsized plastics has been explored. Finally, the influence of age and size of microplastics on the toxicity effects and the factors impacting the retention and accumulation of microplastics in aquatic species are reviewed. Furthermore, the prominent pathway of microplastics into the human body and the studies available on the toxicity effects observed in human cells upon exposure to microplastics of different characteristics are explored. [ABSTRACT FROM AUTHOR]