Seasonal variation of heavy metals in water and Cyprinus carpio L. from Umiam Lake reservoir of Meghalaya, India: Potential health risk assessment for human consumption.

The purpose of this study is to assess the seasonal variation of heavy metal concentration in water and fish tissues of common carp (Cyprinus carpio L.) from the Umiam Lake reservoir located in the Ri bhoi district of Meghalaya, India, and to elucidate the possible human health risk of ingesting fish captured from the contaminated lake. Results show significant (p < 0.05) seasonal differences of heavy metal concentrations in the water and different tissues of fish Cyprinus carpio L.. The total concentration of heavy metals in the water exceeds the WHO and BIS standards and thus poses a significant threat to the aquatic flora and fauna of the reservoir. The heavy metal concentrations in fish tissues were tissue-dependent, where the average concentration of heavy metals in all the tissues of Cyprinus carpio L. was in the order of Cr > Pb > Cu > Cd. In addition, the health risk assessment suggests that the heavy metals in the fish muscle from the Umiam Lake reservoir might have adverse effects on human. Therefore, the overall results of the study provide an understanding on the seasonal distribution of heavy metals in water, provide insight on their bioaccumulation in the fish tissues, and highlights the potential health risk for the local population of long-term fish consumption from Umiam Lake reservoir.

Sustaining ex-mining lake-converted constructed wetlands as nature-based solutions: A comprehensive assessment of the carbon-water nexus in Paya Indah Wetlands, Malaysia.

Water and carbon, essential for Earth's well-being, face imminent threats from human activities that fuel climate change. This study investigates nature-based solutions, focusing on the carbon-water nexus of ex-mining lake-converted constructed wetlands, specifically in Malaysia's Paya Indah Wetlands (PIW). Addressing research gaps, it assesses the ecosystem services of these wetlands, emphasising integrated evaluations for informed land management and employing a top-down conservation approach. Methodologically, spatial assessments, soil and water sampling, carbon quantification, water quality index calculations, land cover classification and stakeholder surveys were conducted. Results underscore the significant carbon sequestration and water quality improvement potential of constructed wetlands, with soil and sediment carbon accumulation reaching 1553.11 Mg C ha-1 (equivalent to 5700 Mg CO2 ha-1), translating to an annual sequestration capacity of 67.5 Mg C ha-1 year-1. Water quality index values ranged from 58 to 81 (Classes II to III). PIW's establishment led to a reduction of over 90% in barren land, with increases in water bodies (36%) and vegetation-covered land (38%), boosting wildlife populations by 30%. Spatial variations in organic carbon density and water quality underscore the complexity of the carbon-water nexus and its impacts on ecosystem health and water security. Despite land use changes, PIW demonstrates resilience, contributing to climate change mitigation. Stakeholder perceptions vary, emphasising the need for adaptive strategies. The study proposes transdisciplinary conservation initiatives and adaptive plans, stressing the pivotal role of ex-mining lake-converted constructed wetlands in enhancing climate resilience.

Functional trait-based phytoplankton biomass and assemblage analyses in the pre-growing season for comprehensive algal bloom risk assessment.

Algal bloom (AB) risk assessment is critical for maintaining ecosystem health and human sustainability. Previous AB risk assessments have focused on the potential occurrence of ABs and related factors in the growing season, whereas their hazards, especially in the pre-growing season, have attracted less attention. Here, we performed a comprehensive AB risk assessment, including water trophic levels, phytoplankton biomass, functional trait-based assemblages, and related environmental factors, in the pre-growing season in Dongting Lake, China. Although mesotrophic water and low phytoplankton biomass suggested low AB potential, toxic taxa, which constituted 13.28% of the phytoplankton biomass, indicated non-negligible AB hazards. NH4+ and water temperature were key factors affecting phytoplankton motility and toxicity. Our study establishes a new paradigm for quantitative AB risk assessment, including both potential AB occurrence and hazards. We emphasize the importance of phytoplankton functional traits for early AB warning and NH4+ reduction for AB control in the pre-growing season.

Examining inequality in aquatic ecosystem services: Evidence from large-scale monitoring programs.

We hypothesize that aquatic ecosystem services are likely to be inequitably accessible and addressing this hypothesis requires systematic assessment at regional and national scales. We used existing data from large-scale aquatic monitoring programs (National Coastal Condition Assessment, National Lakes Assessment) to examine relationships between ecosystem condition, approximating a subset of cultural and provisioning services, and inequality (population below poverty level, minority population). We also assessed whether monitoring sites equitably represented the gradient of socioeconomic backgrounds. Several water quality indicators were associated with significantly different minority and low-income percentages; however, the effect size was generally small, with the exception of nitrogen condition status. Minority communities were somewhat under-represented when comparing the distribution of all census blocks to those in proximity to monitoring sites. Analyses were sensitive to the skewed distribution of monitoring sites with a low frequency of observations at the more socially vulnerable part of the gradient. We discuss implications of these findings for improving the representation of vulnerable communities in large-scale monitoring programs.

Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems.

Water quality index (WQI) is a well-established tool for assessing the overall quality of fresh inland-waters. However, the effectiveness of real-time assessment of aquatic ecosystems using the WQI is usually impacted by the absence of some water quality parameters in which their accurately in-situ measurements are impossible and face difficulties. Using a rich water quality dataset spanned from 1980 to 2023, we employed four machine learning-based models to estimate the British Colombia WQI (BCWQI) in the Lake Päijänne, Finland, without parameters like chemical oxygen demand (COD) and total phosphorus (TP). Measurement of both COD and TP is time-consuming, needs laboratory equipment and labor costs, and faces sampling-related difficulties. Our results suggest the machine learning-based models successfully estimate the BCWQI in Lake Päijänne when TP and COD are omitted from the dataset. The long-short term memory model is the least sensitive model to exclusion of COD and TP from inputs. This model with the coefficient of determination and root-mean squared error of 0.91 and 0.11, respectively, outperforms the support vector regression, random forest, and neural network models in real-time estimation of the BCWQI in Lake Päijänne. Incorporation of BCWQI with the machine learning-based models could enhance assessment of overall quality of inland-waters with a limited database in a more economical and time-saving way. Our proposed method is an effort to replace the traditional offline water quality assessment tools with a real-time model and improve understanding of decision-makers on the effectiveness of management practices on the changes in lake water quality.

Heavy metal analysis of water and sediments of the Kaptai Lake in Bangladesh: Contamination and concomitant health risk assessment.

In this study, concentrations of 9 heavy metals (Cr, Fe, Co, Ni, Cu, Zn, As, Cd, and Pb) in water and sediments of the Kaptai Lake were determined by neutron activation analysis and atomic absorption spectrometry techniques to study their distribution and contamination in the lake. Average concentrations of Cr and Co in sediments, and Fe and Pb in water were higher than those of some international guideline values. Different environmental pollution indexes (individual and synergistic) suggested that the sediments of Kaptai Lake are minorly enriched by As and Zn, and have low severity of contamination at most of the sampling sites. For residential receptors exposed to the heavy metals in lake water, both non-carcinogenic and carcinogenic hazards were assessed which indicated that there is no carcinogenic risk for As while Cr shows a slightly carcinogenic risk. Moreover, estimated potential ecological risks and different SQGs suggested low ecotoxicological risks in the sediments of Kaptai Lake. Multivariate statistical analyses revealed the correlation among the studied heavy metals and indicated that the origin of most of the metals is mainly lithogenic and a small number of metals (Cu and Pb) from anthropogenic sources. The results of this study will be helpful in developing a pollution control strategy for the lake.

Water quality assessment of Bheemasandra Lake, South India: A blend of water quality indices, multivariate data mining techniques, and GIS.

An integrated approach combining water quality indices (WQIs), multivariate data mining, and geographic information system (GIS) was employed to examine the water quality of Bheemasandra Lake, located adjacent to a sewage treatment plant (STP) in Tumakuru city, India. The analysis of 22 lake water samples, examined before and after the monsoons, revealed that the physicochemical parameters namely - electrical conductivity, biochemical oxygen demand, turbidity, total dissolved solids, ammoniacal nitrogen, nitrates, phosphates, magnesium, total hardness, total alkalinity, and calcium - exceeded the acceptable limits stipulated by national and international standards. The Canadian Council of Ministers of the Environment WQI (pre-monsoon: 25.3; post-monsoon: 33.9) and weighted arithmetic WQI (pre-monsoon: 3398; post-monsoon: 2093) designated the water as unsafe for drinking. Irrigation WQIs (sodium adsorption ratio, sodium percentage, residual sodium carbonate, magnesium hazard, permeability index, and potential salinity) implied water's suitability for irrigation. However, electrical conductivity indicated otherwise. Industrial WQIs (Larson-Skold Index, Langelier Index, Aggressive Index, and Puckorius Scaling Index) illustrated scaling propensity and the chloride sulfate mass ratio alluded galvanic corrosion potential. Hierarchical cluster analysis gathered 22 sampling points into two clusters (cluster 1: relatively lower polluted regions; cluster 2: highly polluted regions) for each season based on similarities in water features. Principal component analysis extracted four (79.07% cumulative variance) and six (87.14% cumulative variance) principal components before and after the monsoons, respectively. These components identified the primary pollution sources as urban sewage and natural lithological processes. WQI maps, created using the inverse distance weighted interpolation technique, enhanced the visualization of spatial-temporal variations. This study highlights the dire consequences of urbanization, STP pollution, and sewage management failures, necessitating that concerned authorities should implement policies and measures to curb the negative impacts on the environment and public health.

Spatiotemporal and multi-isotope assessment of metal sedimentation in the Great Lakes.

This study investigates spatiotemporal dynamics in metal sedimentation in the North American Great Lakes and their underlying biogeochemical controls. Bulk geochemical and isotope analyses of n = 72 surface and core sediment samples show that metal (Cu, Zn, Pb) concentrations and their isotopic compositions vary spatially across oligotrophic to mesotrophic settings, with intra-lake heterogeneity being similar or higher than inter-lake (basin-scale) variability. Concentrations of Cu, Zn, and Pb in sediments from Lake Huron and Lake Erie vary from 5 to 73 mg/kg, 18-580 mg/kg, and 5-168 mg/kg, respectively, but metal enrichment factors were small (<2) across the surface- and core sediments. The isotopic signatures of surface sediment Cu (δ65Cu between -1.19‰ and +0.96‰), Zn (δ66Zn between -0.09‰ and +0.41‰) and Pb (206/207Pb from 1.200 to 1.263) indicate predominantly lithogenic metal sourcing. In addition, temporal trends in sediment cores from Lake Huron and Lake Erie show uniform metal concentrations, minor enrichment, and Zn and Pb isotopic signatures suggestive of negligible in-lake biogeochemical fractionation. In contrast, Cu isotopic signatures and correlation to chlorophyll and macronutrient levels suggest more differentiation from source variability and/or redox-dependent fractionation, likely related to biological scavenging. Our results are used to derive baseline metal sedimentation fluxes and will help optimize water quality management and strategies for reducing metal loads and enrichment in the Great Lakes and beyond.

Appraisal of metallic accumulation in the surface sediment of a fish breeding dam in Türkiye: A stochastical approach to ecotoxicological risk assessment.

This study examines the levels and patterns of potentially toxic elements (PTEs) in surface sediment of Almus Dam Lake (ADL), a key fish breeding site in Türkiye. PTE concentrations in sediment were ranked: Hg (0.05 ± 0.01) < Cd (0.16 ± 0.01) < Pb (9.34 ± 1.42) < As (18.75 ± 15.65) < Cu (63.30 ± 15.17) < Ni (72.64 ± 20.54) < Zn (86.66 ± 11.95) < Cr (108.35 ± 36.40) < Mn (1008 ± 151) < Fe (53,998 ± 6468), with no significant seasonal or spatial differences. Ecological risk indices (mHQ, EF, Igeo, CF, PLI, Eri, mCd, NPI, PERI, MPI, and TRI) showed low contamination levels. Health risk assessments, including LCR, HQ, and THI, indicated minimal risks to humans from sediment PTEs. Statistical analyses (PCA, HCA, SCC) identified natural, transportation, and anthropogenic PTE sources, with slight impacts from agriculture and fish farming. This research underlines contamination status of ADL and emphasizes the need for targeted management strategies, offering critical insights for environmental safeguarding.

Community Structure and Water Quality Assessment of Benthic Macroinvertebrates in Hongze Lake.

This study investigated the species, density, biomass and physicochemical factors of benthic macroinvertebrates in Hongze Lake from 2016 to 2020. Redundancy analysis (RDA) was used to analyze the relationship between physicochemical parameters and the community structure of macroinvertebrates. Macroinvertebrate-based indices were used to evaluate the water quality conditions in Hongze Lake. The results showed that a total of 50 benthic species (10 annelids, 21 arthropods and 19 mollusks) were collected. The community structure of benthic macroinvertebrates varied in time and space. The dominant species were Limnodrilus hoffmeisteri (L.hoffmeisteri), Corbicula fluminea (C.fluminea), Nephtys oligobranchia (N.oligobranchia). In 2016, arthropods such as Grandidierella sp. were the dominant species of benthos in Hongze Lake while annelids and mollusks dominated from 2017 to 2020, such as L.hoffmeisteri, N.oligobranchia, C.fluminea. The benthic fauna of Chengzi Lake and Lihewa District were relatively abundant and showed slight variation, while the benthic macroinvertebrates of the Crossing the water area were few and varied greatly. RDA showed that changes in benthic macroinvertebrate structure were significantly correlated with dissolved oxygen (DO), Pondus Hydrogenii (pH) and transparency (SD). The Shannon Wiener, Pielou, and Margalef indices indicate that Hongze Lake is currently in a moderately polluted state. Future studies should focus on the combined effects of various physicochemical indicators and other environmental factors on benthic communities.

[Effects of Pesticides Use on Pesticides Residues and Its Environmental Risk Assessment in Xingkai Lake（China）].

Xingkai Lake, located in Heilongjiang Province, is an important fishery and agricultural base and is seriously polluted by agricultural non-point sources. To clarify the residual status of many pesticides in the surface water of Xingkai Lake, 27 types of pesticides, herbicides, and their degradation products were analyzed in rice paddy, drainage, and surface water around Xingkai Lake (China) during the rice heading and maturity periods. The results showed that all 27 types of pesticides, herbicides, and their degradation products were detected during the rice heading period, and the total concentration ranged from 247.97 to 6 094.49 ng·L-1. Additionally, 25 species were detected during the rice maturity period, and the total concentration ranged from 485.36 to 796.23 ng·L-1. In comparison, more pesticides, herbicides, and derived degradation products were detected during the heading period, and their total concentration was higher as well. During the rice heading period, atrazine, simetryn, and paclobutrazol were the main detected pesticides, atrazine and isoprothiolane were the main pesticides detected during the maturity period. The distribution characteristics of pesticides and herbicides in the surface water around Xingkai Lake (China) was similar to that in drainage, so they were probably imported from the drainage and rice paddy. The average risk quotient (RQ) values of atrazine, simetryn, prometryn, butachlor, isoprothiolane, and oxadiazon were higher than 0.1 in drainage and Xingkai Lake (China), which showed a potential risk to aquatic organisms.

A water quality assessment model involving novel fluorescence technology.

The reasonable utilization of water resources and real-time monitoring of water pollution are the core tasks of current world hydrological and water conservancy work. Novel technologies and methods for monitoring water pollution are important means to ensure water health. However, the absence of intuitive and simple analysis methods for the assessment of regional pollution in large-scale water bodies has prevented scientists from quickly grasping the overall situation of water pollution. In this study, we propose a strategy based on the unique combination of fluorescence technology and simple kriging (SK) interpolation (FL-SK) for the first time. This strategy could present the relative magnitude and distribution of the physicochemical indicators of a whole natural lake intuitively and accurately. The unique FL-SK model firstly offers a simple and effective water quality method that provides the pollution index of different sampling points in lakes. The macroscopic evaluation of large-scale water bodies by the FL-SK model primarily relies on the fluorescence response of the RDM-TPE to the comprehensive indicators of the water body, as experimental results have revealed a good correlation between fluorescent responses and six normalized physicochemical indicators. Multiple linear regression and fluorescence response experiments on RDM-TPE indicate that to some extent, the fluorescence signals of the FL-SK model may originate from a certain type of sulfide in the water body. Pattern discovery could enable the analysis of pollution levels in other ecosystems and promote early pollution assessment in the future.

An innovative method based on Gaussian cloud distribution and sample information richness for eutrophication assessment of Yangtze's lakes and reservoirs under uncertainty.

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33-50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment.

Seasonal impact of constructed wetlands on nitrogen and phosphorus in sediments of flood control lakes with pollution assessment.

The primary drivers of eutrophication in lakes following the reduction of external nutrient inputs are the release of N and P from sediments. Constructed wetlands play a pivotal role in ameliorating N, P, and other biogenic element levels. However, the presence of large vegetation in these wetlands also substantially contributes to nutrient accumulation in sediments, a phenomenon influenced by seasonal variations. In this study, a typical constructed wetland was selected as the research site. The research aimed to analyze the forms of N and P in sediments during both summer and winter. Simultaneously, a comprehensive pollution assessment and analysis were conducted within the study area. The findings indicate that elevated summer temperatures, together with the presence of wetland vegetation, promote the release of N through the nitrification process. Additionally, seasonal variations exert a significant impact on the distribution of P storage. Furthermore, the role of constructed wetlands in the absorption and release of N and P is primarily controlled by the influence of organic matter on nitrate-nitrogen, nitrite-nitrogen, and available phosphorus, and is also subject to seasonal fluctuations. In summary, under the comprehensive influence of constructed wetlands, vegetation types, and seasons, sediments within the lake generally exhibit a state of mild or moderate pollution. Therefore, targeted measures should be adopted to optimally adjust vegetation types, and human intervention is necessary, involving timely sediment harvesting during the summer to reduce N and P loads, and enhancing sediment adsorption and retention capacity for N and P during the winter.

Assessment of two non-invasive techniques for measuring turbulent benthic fluxes in a shallow lake.

Benthic fluxes refer to the exchange rates of nutrients and other compounds between the water column and the sediment bed in aquatic ecosystems. Their quantification contributes to our understanding of aquatic ecosystem functioning. Near-bed hydrodynamics plays an important role at the sediment-water interface, especially in shallow lakes, but it is poorly considered by traditional measuring techniques of flux quantification, such as sediment incubations. Thus, alternative sampling techniques are needed to characterize key benthic fluxes under in-situ hydrodynamic conditions. This study aimed to evaluate the performance of two promising methods: relaxed eddy accumulation (REA) and mass transfer coefficient (MTC). We applied them in a hyper-eutrophic shallow lake to measure the fluxes of ammonium, phosphate, iron, and manganese ions. For the first time, REA revealed hourly nutrient flux variations, indicating a strong lake biogeochemical dynamics at short time-scales. Daily average fluxes are of similar orders of magnitude for REA and MTC for ammonium (24 and 42 mmol m2 d-1), manganese (1.0 and 0.8), and iron (0.8 and 0.7) ions. They are one order of magnitude higher than fluxes estimated from sediment incubations, due to the difficulty in reproducing in-situ oxygen and hydrodynamic conditions in the laboratory. Although the accuracy of both techniques needs to be improved, the results revealed their potential: REA follows the short-term biogeochemical dynamics of sediments, while MTC could be widely used for lake monitoring because of its simpler implementation.

Eco-environmental changes due to human activities in the Erhai Lake Basin from 1990 to 2020.

Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit-based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995-2000, 2000-2005, 2005-2009 and 2015-2020, and the improvement was most significant in 1995-2000, covering an area of 823.95 km2 and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.

Evaluation of a financial incentive intervention on malaria prevalence among the residents in Lake Victoria basin, Kenya: study protocol for a cluster-randomized controlled trial.

BACKGROUND: In the Lake Victoria basin of western Kenya, malaria remains highly endemic despite high coverage of interventions such as mass distribution of long-lasting insecticidal nets (LLIN), indoor residual spraying (IRS) programs, and improvement of availability and accessibility of rapid diagnostic tests (RDT) and artemisinin-based combination therapy (ACT) at community healthcare facilities. We hypothesize that one major cause of the residual transmission is the lack of motivation among residents for malaria prevention and early treatment. METHODS: This study will aim to develop a demand-side policy tool to encourage local residents' active malaria prevention and early treatment-seeking behaviors. We examine the causal impact of a financial incentive intervention complemented with malaria education to residents in malaria-prone areas. A cluster-randomized controlled trial is designed to assess the effect of the financial incentive intervention on reducing malaria prevalence in residents of Suba South in Homa Bay County, Kenya. The intervention includes two components. The first component is the introduction of a financial incentive scheme tied to negative RDT results for malaria infection among the target population. This study is an attempt to promote behavioral changes in the residents by providing them with monetary incentives. The project has two different forms of incentive schemes. One is a conditional cash transfer (CCT) that offers a small reward (200 Ksh) for non-infected subjects during the follow-up survey, and the other is a lottery incentive scheme (LIS) that gives a lottery with a 10% chance of winning a large reward (2000 Ksh) instead of the small reward. The second component is a knowledge enhancement with animated tablet-based malaria educational material (EDU) developed by the research team. It complements the incentive scheme by providing the appropriate knowledge to the residents for malaria elimination. We evaluate the intervention's impact on the residents' malaria prevalence using a cluster-randomized control trial. DISCUSSION: A policy tool to encourage active malaria prevention and early treatment to residents in Suba South, examined in this trial, may benefit other malaria-endemic counties and be incorporated as part of Kenya's national malaria elimination strategy. TRIAL REGISTRATION: UMIN000047728. Registered on 29th July 2022.

An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013-2018).

Defining the environmental occurrence and distribution of chemicals of emerging concern (CECs), including pharmaceuticals and personal care products (PPCPs) in coastal aquatic systems, is often difficult and complex. In this study, 70 compounds representing several classes of pharmaceuticals, including antibiotics, anti-inflammatories, insect repellant, antibacterial, antidepressants, chemotherapy drugs, and X-ray contrast media compounds, were found in dreissenid mussel (zebra/quagga; Dreissena spp.) tissue samples. Overall concentration and detection frequencies varied significantly among sampling locations, site land-use categories, and sites sampled proximate and downstream of point source discharge. Verapamil, triclocarban, etoposide, citalopram, diphenhydramine, sertraline, amitriptyline, and DEET (N,N-diethyl-meta-toluamide) comprised the most ubiquitous PPCPs (> 50%) detected in dreissenid mussels. Among those compounds quantified in mussel tissue, sertraline, metformin, methylprednisolone, hydrocortisone, 1,7-dimethylxanthine, theophylline, zidovudine, prednisone, clonidine, 2-hydroxy-ibuprofen, iopamidol, and melphalan were detected at concentrations up to 475 ng/g (wet weight). Antihypertensives, antibiotics, and antidepressants accounted for the majority of the compounds quantified in mussel tissue. The results showed that PPCPs quantified in dreissenid mussels are occurring as complex mixtures, with 4 to 28 compounds detected at one or more sampling locations. The magnitude and composition of PPCPs detected were highest for sites not influenced by either WWTP or CSO discharge (i.e., non-WWTPs), strongly supporting non-point sources as important drivers and pathways for PPCPs detected in this study. As these compounds are detected at inshore and offshore locations, the findings of this study indicate that their persistence and potential risks are largely unknown, thus warranting further assessment and prioritization of these emerging contaminants in the Great Lakes Basin.

Anthropogenic-induced environmental and ecological changes in the Nile Delta over the past half-century.

Anthropogenic activities over the past half-century have had a negative impact on the wetland ecosystem in the Nile Delta, which provides essential provisioning and regulating services. Therefore, it is crucial to systematically investigate pollution levels and their ecological consequences at both spatial and temporal scales in order to promote sustainable development. In this study, data on metal pollution in the Manzala Lake were compiled through a systematic review of all published literature from 1968 to 2020. Additionally, agricultural data (including land use, pesticide and fertilizer usage, and discharge) and economic data for the same time period were collected to identify the main drivers of pollution. The results indicated an overall increasing trend in heavy metal concentrations during the study period. The average concentrations of metals, arranged in descending order, were as follows: Fe (15,115.5 µg/g) > Mn (722 µg/g) > Zn (115.4 µg/g) > Cu (65.9 µg/g) > Ni (62.5 µg/g) > Cr (58.1 µg/g) > Pb (54.1 µg/g) > Cd (4.7 µg/g) > Hg (0.1 µg/g). A linear regression model revealed that wastewater discharge, water reuse, and the use of pesticides and fertilizers are the main sources of heavy metal pollution in the Manzala Lake. Consequently, there has been a dramatic decrease in the biodiversity of fish and molluscan communities. The study also found a correlation between heavy metal pollution and socio-economic development, highlighting the urgent need for attention to the conservation, management, and sustainable development of the lake.

Assessment of occurrence, partitioning and ecological risk for 144 steroid hormones in Taihu Lake using UPLC-MS/MS with machine learning model.

Steroid hormones (SHs) have attracted mounting attention due to their endocrine-disrupting effects on humans and aquatic organisms. However, the lack of analytical methods and toxicity data for a large number of SHs has limited the effective management of SH contamination in the water-sediment systems. In this study, we developed a highly sensitive analytical method for the simultaneous quantification of 144 SHs to investigate their occurrence, spatial distribution and partitioning in the water and sediment in Taihu Lake. The results showed that the total concentrations of SHs in water and sediment were 366.88-998.23 ng/L (mean: 612.84 ng/L) and 17.46-150.20 ng/g (mean: 63.41 ng/g), respectively. The spatial distribution of SHs in Taihu Lake might be simultaneously influenced by the pollution sources, lake hydrodynamics, and sediment properties. The sediment-water partitioning result implied that 28 SHs were in dynamic equilibrium at the water-water interface. In addition, 22 and 12 SHs tended to spread to water and settle into sediment, respectively. To assess the ecological risk of all SHs, a robust random forest model (R2 = 0.801) was developed to predict the acute toxicity of SHs for which toxicity data were not available from publications. Risk assessment showed that SHs posed a high ecological risk throughout Taihu Lake, with the highest risk in the northwestern areas. Estrone, 17ß-estradiol and 17α-ethynylestradiol were the dominant risk contributors and were therefore recommended as the priority SHs in Taihu Lake. This work provided a valuable dataset for Taihu Lake, which would help to provide guidance and suggestions for future studies and be useful for the government to develop the mitigation and management measures.