Numerous genetic markers for microbial source tracking (MST) have been evaluated by testing a panel of target and nontarget faecal samples. However, the performance of MST markers may vary between faecal and water samples, thereby resulting in inaccurate water quality assessment. In this study, a 30-day sampling study was conducted in an urban river impacted by human- and sewage-associated pollution to evaluate the performance of different human-associated markers in environmental water. Additionally, marker decay was assessed via a microcosms approach. Overall, Bacteroidales 16sRNA and crAssphage markers exhibited higher prevalence in the study area, and their detection frequencies exceeded 90%. In contrast, Bacteroidales protein markers exhibited poor detection frequencies compared to other markers, with the prevalence of Hum2 and Hum163 reaching only 63% and 84%, respectively. Regarding marker abundance, there was no significant difference in the detection concentrations between Bacteroidales 16sRNA and crAssphage markers (p > 0.05); however, the concentrations of Bacteroidales protein markers were nearly 1 order of magnitude lower than those of other MST markers. The microcosm experiments indicated that the decay rate of crAssphage markers was significantly lower than that of other bacterial target markers, which may improve their detectability when the pollution source is located far from the sampling site. Due to the observed differences in performance and decay patterns among Bacteroidales 16sRNA, crAssphage, and Bacteroidales protein markers, we recommend the simultaneous use of multiple markers from different target microorganisms to obtain a more comprehensive understanding of the pollution sources. This approach would also provide an accurate assessment of pollution levels and health risks.

Nitrogen in urban stormwater has been widely studied, and effective management of nitrogen pollution is critical for improving urban stormwater and receiving water quality. This requires an in-depth understanding of the transport process and source contribution to both dissolved and particulate nitrogen in stormwater from urban catchments. In this study, 123 stormwater runoff samples were collected from an urban catchment during different rainfall events. Dissolved and particulate nitrogen concentrations in roof runoff, road runoff, and sewer flow were analyzed. The concentration of dissolved nitrogen was higher in roof runoff than in road runoff and sewer flow. However, the concentration of particulate nitrogen was lower in roof runoff than in road runoff and sewer flow. Isotopic analysis and Bayesian mixing models showed that road runoff was the largest source contributor of both nitrate and particulate organic nitrogen (PON) in sewer flow discharged from the study catchment. In addition, road runoff contributed the majority of PON associated with coarse particles (>105 μm), whereas PON associated with fine particles (<105 μm) was primarily washed-off of sewer sediments. The results provided several suggestions for the management of nitrogen pollution in urban catchments. This study could help to fully understand the transport and sources of nitrogen pollution in urban stormwater and provide recommendations to the government for implementing appropriate stormwater management strategies to minimize stormwater pollution.

Biomonitoring of aquatic environments requires new tools to characterize the effects of pollutants on living organisms. Zebra mussels (Dreissena polymorpha) from the same site in north-eastern France were caged for two months, upstream and downstream of three wastewater treatment plants (WWTPs) in the international watershed of the Meuse (Charleville-Mézières “CM” in France, Namur “Nam” and Charleroi “Cr” in Belgium). The aim was to test ¹H-NMR metabolomics for the assessment of water bodies’ quality. The metabolomic approach was combined with a more “classical” one, i.e., the measurement of a range of energy biomarkers: lactate dehydrogenase (LDH), lipase, acid phosphatase (ACP) and amylase activities, condition index (CI), total reserves, electron transport system (ETS) activity and cellular energy allocation (CEA). Five of the eight energy biomarkers were significantly impacted (LDH, ACP, lipase, total reserves and ETS), without a clear pattern between sites (Up and Down) and stations (CM, Nam and Cr). The metabolomic approach revealed variations among the three stations, and also between the upstream and downstream of Nam and CM WWTPs. A total of 28 known metabolites was detected, among which four (lactate, glycine, maltose and glutamate) explained the observed metabolome variations between sites and stations, in accordance with chemical exposure levels. Metabolome changes suggest that zebra mussel exposure to field contamination could alter their osmoregulation and anaerobic metabolism capacities. This study reveals that lactate is a potential biomarker of interest, and ¹H-NMR metabolomics can be an efficient approach to assess the health status of zebra mussels in the biomonitoring of aquatic environments.

A monitoring network was established in streams within a catchment near the Costa Rican Pacific coast (2008–2011) to estimate the impact of pesticides in surface water (84 samples) and sediments (84 samples) in areas under the influence of melon and watermelon production. A total of 66 (water) and 47 (sediment) pesticides were analyzed, and an environmental risk assessment (ERA) was performed for four taxa (algae, Daphnia magna, fish and Chironomus riparius). One fungicide and seven insecticides were detected in water and/or sediment; the fungicide azoxystrobin (water) and the insecticide cypermethrin (sediments) were the most frequently detected pesticides. The insecticides endosulfan (5.76 μg/L) and cypermethrin (301 μg/kg) presented the highest concentrations in water and sediment, respectively. The ERA revealed acute risk in half of the sampling points of the melon-influenced area and in every sampling point from the watermelon-influenced area. Safety levels were exceeded within and around the crop fields, suggesting that agrochemical contamination was distributed along the catchment, with potential influence of nearby crops. Acute risk was caused by the insecticides chlorpyrifos, cypermethrin and endosulfan to D. magna, fish and C. riparius; the latter was the organism with the overall highest/continuous risk. High chronic risk was determined in all but one sampling point, and revealed a higher number of pesticides of concern. Cypermethrin was the only pesticide to pose chronic risk for all benchmark organisms. The results provide new information on the risk that tropical crops pose to aquatic ecosystems, and highlight the importance of including the analysis of sediment concentrations and chronic exposure in ERA.

Pollution of riverine ecosystems through the multidimensional impact of human footprints around the world poses a serious challenge. Research studies that communicate potential repercussions of landscape structure metrics on snowmelt riverine water quality particularly, in climatically fragile Himalayan watersheds are very scarce. Though, worldwide, grasping the influence of land-use practices on water quality (WQ) has received renewed attention yet, the relevance of spatial scale linked to landscape pattern is still elusive due to its heterogenic nature across diverse geomorphic regions. In this work, therefore, we tried to capture the insights on landscape-aquascape interface by juxtapositioning the impacts of landscape structure pattern on snowmelt stream WQ of the whole Jhelum River Basin (JRB) under three varying spatial scales viz., watershed scale, riparian corridor (1000 m wide) and reach buffer (500 m wide). The percentage of landscape pattern composition and configuration metrics in the JRB were computed in GIS utilizing Landsat-8 OLI/TIRS satellite image having 30 m resolution. To better explicate the influence of land-use metrics on riverine WQ with space and time, we used Redundancy analysis (RDA) and multilinear regression (MLR) modeling. MLR selected land-use structure metrics revealed the varied response of WQ parameters to multi-scale factors except for total faecal coliform bacteria (TC) which showed perpetual presence. The reach-scale explained slightly better (76%) variations in WQ than riparian (75%) and watershed (70%) scales. Likewise, across seasonal scale, autumn (75%), winter (83%), and summer (77%) captured the most WQ variation at catchment, riparian, and reach scales respectively. We observed impairing WQ linkages with agriculture, built-up and barren rocky areas across watersheds, besides, pastures in riparian buffer areas, and fragmentation of landscape patches at the reach scale. Due to little appearance of spatial scale differences, a multi scale perspective landscape planning is emphasized to ensure future sustainability of Kashmir Himalayan water resources.

Management of water-quality in a river ecosystem needs to be focused on susceptible regions to eutrophication based on proper measurements. The stress–response relationships between nutrients and primary productivity of phytoplankton allow the derivation of ecologically acceptable thresholds of stressors under field conditions. However, spatio-temporal variations in heterogeneous environmental conditions have hindered the development of locally applicable criteria. To address these issues, we utilized a combination of a geographically specialized artificial neural network (Geo-SOM, geo-self-organizing map) and linear mixed-effect models (LMMs). The model was applied to a 24-month dataset of 54 stations that spanned a wide spatial gradient in the Nakdong River basin. The Geo-SOM classified 1286 observations in the basin into 13 clusters that were regionally and seasonally distinct. Inclusion of the random effects of Geo-SOM clustering improved the performance of each LMM, which suggests that there were significant spatio-temporal variations in the Chla–stressor relationships. These variations arise owing to differences in background seasonality and the effects of local pollutant variables and land-use patterns. Among the 16 environmental variables, the major stressors for Chla were total phosphate (TP) as a nutrient and biological oxygen demand (BOD) as a non-nutrient according to the results of both Geo-SOM and LMM analyses. Based on LMMs with the random effect of the Geo-SOM clusters on the intercept and the slope, we can propose recommended thresholds for TP (18.5 μg L⁻¹) and BOD (1.6 mg L⁻¹) in the Nakdong River. The combined method of LMM and Geo-SOM will be useful in guiding appropriate local water-quality-management strategies and in the global development of large-scale nutrient criteria.

Forest soils are among the world’s largest repositories for long-term accumulation of atmospherically deposited mercury (Hg), and understanding the potential for remobilization through gaseous emissions, aqueous dissolution and runoff, or erosive particulate transport to down-gradient aquatic ecosystems is critically important for projecting ecosystem recovery. Forestry operations, especially clear-cut logging where most of the vegetaiton is removed, can influence Hg mobility/fluxes, foodweb dynamics, and bioaccumulation processes. This paper measured surface-air Hg fluxes from catchments in the Pacific Northwest, USA, to determine if there is a difference between forested and logged catchments. These measurements were conducted as part of a larger project on the impact of forestry operations on Hg cycling which include measurements of water fluxes as well as impacts on biota. Surface-air Hg fluxes were measured using a commonly applied dynamic flux chamber (DFC) method that incorporated diel and seasonal variability in elemental Hg (Hg⁰) fluxes at multiple forested and harvested catchments. The results showed that the forested ecosystem had depositional Hg⁰ fluxes throughout most of the year (annual mean: −0.26 ng/m²/h). In contrast, the harvested catchments showed mostly emission of Hg⁰ (annual mean: 0.63 ng/m²/h). Differences in solar radiation reaching the soil was the primary driver resulting in a shift from net deposition to emission in harvested catchments. The surface-air Hg fluxes were larger than the fluxes to water as runoff and accounted for 97% of the differences in Hg sequestered in forested versus harvested catchments.

Microplastic pollution in the Yangtze River Basin has become a major concern; however, the variations in different environmental compartments are unknown. Here, we compiled published information including detection methods, occurrence, and characterization of microplastics from 624 sampling sites in river water, river sediment, lake and reservoir water, and lake and reservoir sediment in the Yangtze River Basin. The spatial distribution of sampling sites shows fractal pattern and was uniformly concentrated around the main stream of the Yangtze River and the lake geographical zone. Collection, pretreatment, identification, and quantification processes varied among different studies. Non-parametric tests were performed to compare the different microplastic indices. A Pearson correlation analysis was used to study the relationship between microplastic pollution and local socioeconomic conditions. We found that the microplastic size and abundance distribution in river water and lake and reservoir water showed different patterns for different sampling methods, indicating that different methods influenced the results. Population density and urbanization rate are suggested to be important factors influencing the spatial heterogeneity of microplastic abundances in water, rather than in sediment. The microplastic abundances in lake and reservoir water were higher than that in river water in bulk samples. However, microplastic abundances among different sediment environments shows no significant difference. For bulk water samples and sediment samples overall, the proportion of small microplastics (<1 mm, i.e. SMP), fibers, transparent debris, and polypropylene (PP) were 65.1%, 67.8%, 31.8%, and 29.7%, respectively. The microplastic characteristics of lake and reservoir water and sediment were similar, differing from those of river water and sediment. This study provides the first basin scale insight into microplastic occurrence and characteristics in different environments in the Yangtze River Basin.

Heavy metal pollution is an issue of wide concern owing to the toxic and bioaccumulative properties of many heavy metals and their tendencies to persist in the environment. The Haihe River is an important river in the Beijing–Tianjin–Hebei region, and heavy metal pollution of the basin has attracted considerable attention. This study determined the concentrations of 14 heavy metals (As, Ba, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, and Zn) in water, sediments, and fish samples from the Haihe River basin. The results showed that the concentrations ranged from 0.08 μg L⁻¹ to 60.49 μg L⁻¹ in water, 0.11 mg kg⁻¹ to 229.20 mg kg⁻¹ in sediments, and 0.01 mg kg⁻¹ to 11.72 mg kg⁻¹ in fish. We derived the ambient water quality criteria (AWQC) value of each heavy metal with respect to human health, and then performed a comprehensive risk assessment according to the native parameters. The human health AWQC values for the assessed 14 heavy metals ranged from 0.16 μg L⁻¹ to 726.53 μg L⁻¹. The health risks posed by As, Cr, Hg, and Sb and the ecological risks associated with Ni, Cu, Cr, Zn, Cd, Co, Hg, and Sn were found to be issues of concern. The results of a sensitivity analysis revealed that the highest contributing parameter was i) the concentration in water (Cw) for Cd, Co, Mn, Sb, and Sn; ii) the intake rate of water (IRw) for As, Ba, Cr, Hg, Ni, Pb, and Se; and iii) the concentration in fish (Cf) for Cu and Zn. The results of this research could contribute to the information required for water quality assessments and the development of water quality standards.

Forest-stream ecosystems are widespread and biodiverse terrestrial landscapes with physical and social connections to downstream human activities. After radiocesium is introduced into these ecosystems, various material flows cause its accumulation or dispersal. We review studies conducted in the decade after the Fukushima nuclear accident to clarify the mechanisms of radiocesium transfer within ecosystems and to downstream areas through biological, hydrological, and geomorphological processes. After its introduction, radiocesium is heavily deposited in the organic soil layer, leading to persistent circulation due to biological activities in soils. Some radiocesium in soils, litter, and organisms is transported to stream ecosystems, forming contamination spots in depositional habitats. While reservoir dams function as effective traps, radiocesium leaching from sediments is a continual phenomenon causing re-contamination downstream. Integration of data regarding radiocesium dynamics and contamination sites, as proposed here, is essential for contamination management in societies depending on nuclear power to address the climate crisis.