Spatiotemporal characterization of dissolved trace elements in the Gandaki River, Central Himalaya Nepal

Metals and phosphorus in the sediments of streams emptying into the Çanakkale strait (Dardanelles): Spatial distribution, pollution status, risk assessment and source identification

The Çanakkale Strait is exposed to various pollutants due to its strategic location. It is thought that stream inputs may contribute significantly to metal and phosphorus (P) accumulation in the strait. In this study, the spatial distribution, pollution status, ecological risks and possible sources of twelve metals and P in the sediments of seven important streams emptying into the strait were analyzed. The results showed that Zn (226 mg/kg), Ba (67.2 mg/kg) and Pb (10.4 mg/kg) concentrations were higher in the Umurbey Stream due to mining activities, while P concentration (295 mg/kg) was higher in the Çanakkale Stream due to both agricultural activities and domestic wastewater discharges. Modified hazard quotient (mHQ), enrichment factor (EF) and contamination factor (Cf) values revealed that Zn and Pb showed high and moderate contamination in the US3 and US4 sampling sites of the Umurbey Stream, respectively. Similarly, P showed moderate contamination in the ÇS3 site of the Çanakkale Stream. Nemerow pollution index (NPI) showed that the US3 (2.41) and US4 (4.28) sites of the Umurbey Stream were slightly and moderately polluted, respectively. Toxic risk index (TRI) values demonstrated that the sediments in only the US4 site (5.17) of the Umurbey Stream may pose a low toxic risk due to high Zn content. Similarly, based on comparison results with sediment quality guidelines (SQGs), it was found that high Zn content may lead to adverse effects on sediment-dwelling organisms in the US4 site. In addition, the PEC-quotient value in the US4 site exceeded 0.5, confirming the finding that the sediments in this site could be toxic to benthic organisms. Finally, correlation, cluster and factor analyzes were used to determine possible sources of elements. Mining activities, natural sources and mixed sources (agricultural activities and natural sources) were identified as the main sources of elements in the sediments of the streams. This study can provide an important reference for evaluating stream sediment pollution and managing marine pollution.

Distribution, source identification, water quality, and risk assessment of trace elements in the surface-groundwater-sediments multifunctional system in Guohe River Basin

Within the Huaihe River Basin, Guohe River, as its second-largest tributary, serves as a critical water supply source. Recent industrial and agricultural advancements have led to increased trace element contamination, adversely impacting the water quality within Guohe River Basin. Therefore, this study aimed to investigate the distribution characteristics, sources, water quality and risk assessment of trace elements in the surface water, groundwater, and sediments across the basin. The results showed that the spatial distribution of trace elements in the surface water and groundwater of Guohe River Basin was that most of the high concentrations appeared in Qiaocheng District of Bozhou City, the mean concentration of Fe in Guohe River sediments was the highest, the mean concentration of Sb was the lowest. The PMF source analysis results showed that the main source of trace elements in Guohe River Basin was natural geological processes, followed by human activities. The sodium adsorption ratio (SAR) indicated that the surface water samples of Guohe River in two seasons had high sodium and salinity hazards. The water quality index (WQI) showed that surface water and groundwater samples in the northwestern of Guohe River Basin had poor water quality. The results of the risk assessment showed that As and Mn posed great ecological risks to surface water and groundwater, respectively, and that F- was the pollutant with the most potential health risk hazard in the basin. The Geo-accumulation index (Igeo) results showed that Cd, Se and As should be taken seriously as the main contaminants of the sediments in Guohe River Basin. KEYWARDS: Trace elements; Source analysis; Sodium adsorption ratio; Water quality index; Risk assessment; Geo-accumulation index.

Spatiotemporal variations, sources, pollution status and health risk assessment of dissolved trace elements in a major Arabian Sea draining river: insights from multivariate statistical and machine learning approaches

River Mahi drains through semi-arid regions (Western India) and is a major Arabian Sea draining river. As the principal surface water source, its water quality is important to the regional population. Therefore, the river water was sampled extensively (n = 64, 16 locations, 4 seasons and 2 years) and analyzed for 11 trace elements (TEs; Sr, V, Cu, Ni, Zn, Cd, Ba, Cr, Mn, Fe, and Co). Machine learning (ML) and multivariate statistical analysis (MVSA) were applied to investigate their possible sources, spatial-temporal-annual variations, evaluate multiple water quality parameters [heavy metal pollution index (HPI), heavy metal evaluation index (HEI)], and health indices [hazard quotient (HQ), and hazard index (THI)] associated with TEs. TE levels were higher than their corresponding world average values in 100% (Sr, V and Zn), 78%(Cu), 41%(Ni), 27%(Cr), 9%(Cd), 8%(Ba), 8%(Co), 6%(Fe), and 0%(Mn), of the samples. Three principal components (PCs) accounted for 74.5% of the TE variance: PC-1 (Fe, Co, Mn and Cu) and PC-2 (Sr and Ba) are contributed from geogenic sources, while PC-3 (Cr, Ni and Zn) are derived from geogenic and anthropogenic sources. HPI, HEI, HQ and THI all indicate that water quality is good for domestic purposes and poses little hazard. ML identified Random forest as the most suitable model for predicting HEI class (accuracy: 92%, recall: 92% and precision: 94%). Even with a limited dataset, the study underscores the potential application of ML to predictive classification modeling.

Using numerical methods for map the spatiotemporal geogenic and anthropogenic influences on the groundwater in a detrital aquifer in south Spain

The presence of trace elements in water for domestic supply or irrigation could pose a significant toxic risk for health, due to direct consumption or bioaccumulation through the ingestion of vegetables irrigated with this water. This paper studies the presence of 41 trace elements plus nitrate and bromate in groundwater, using a multivariate statistical tool based on Principal Component Analysis and a geostatistical Kriging method to map the results. Principal Component Analysis revealed 11 significant principal components, which account for 82% and 81% of the total variance (information) respectively for the two dates analysed. Ordinary Kriging was applied to draw maps of the trace elements and PC scores. This research breaks new ground in terms of the large number of parameters used and in terms of the analysis of spatiotemporal variations in these parameters. The results obtained indicate that PC1 represents the natural quality of the aquifer (geogenic) and that there is little change in the average PC1 value between the two dates studied (June near the peak recharge point and November at the end of summer). Agriculture is the human activity that causes the greatest variations in the quality of the groundwater due to the use of fertilizers and due to watering crops with wastewater (PC7_J and PC5_N, June and November, respectively). Other elements of industrial origin, which are dangerous for human health, such as Pb, Cu and Cd, are grouped together in other principal components. The results show that the decline, or even complete absence, of natural recharge during the summer months leads to an increase in the TEs produced by human activity. This indicates that a temporary reduction in the natural recharge could worsen the quality of water resources. Based on the interpretation of the estimated maps, a synthetic map was created to show the spatial distribution of the areas affected by geogenic and anthropogenic factors. Studies with a global approach like this one are necessary in that the possible sources of pollution that could alter the quality of the groundwater and the amount of trace elements and other potentially harmful substances could increase as time goes by. The main advantage of the methodology proposed here is that it reduces the number of parameters, so simplifying the results. This makes it easier to interpret the results and manage the quality of the water.

Geochemical evolution of dissolved trace elements in space and time in the Ramganga River, India

Understanding the spatiotemporal dynamics of river water chemistry from its source to sinks is critical for constraining the origin, transformation, and "hotspots" of contaminants in a river basin. To provide new spatiotemporal constraints on river chemistry, dissolved trace element concentrations were measured at 17 targeted locations across the Ramganga River catchment. River water samples were collected across three seasons: pre-monsoon, monsoon, and post-monsoon between 2019 and 2021. To remove the dependency of trace element concentrations on discharge, we used molar ratios, as discharge data on Indian transboundary rivers are not publicly available. The dataset reveals significant spatiotemporal variability in dissolved trace element concentrations of the Ramganga River. Samples collected upstream of Moradabad, a major industrial city in western Uttar Pradesh, are characterized by ~ 1.2-2.5 times higher average concentrations of most of the trace elements except Sc, V, Cr, Rb, and Pb, likely due to intense water-rock interactions in the headwaters. Such kind of enrichment in trace metal concentrations was also observed at sites downstream of large cities and industrial centers. However, such enrichment was not enough to bring a major change in the River Ganga chemistry, as the signals got diluted downstream of the Ramganga-Ganga confluence. The average river water composition of the Ramganga River was comparable to worldwide river water composition, albeit a few sites were characterized by very high concentrations of dissolved trace elements. Finally, we provide an outlook that calls for an assessment of stable non-traditional isotopes that are ideally suited to track the origin and transformation of elements such as Li, Mg, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn, Sr, Ag, Cd, Sn, Pt, and Hg in Indian rivers.

Exploring the trend effects of diffuse anthropogenic pollution in a large river passing through a densely populated area

The detection of non-point pollution in large rivers requires high-frequency sampling over a longer period of time, which, however presumably provides data with large spatial and temporal variance. Variability may mean that data sets recorded upstream and downstream from a densely populated area overlap, suggesting at first glance that the urban area did not affect water quality. This study presents a simple way to explore trend-like effects of non-point pollution in the Danube based on data that varied strongly in space and time. For one year, biweekly sampling was carried out upstream and downstream from a large city with negligible emission of untreated wastewater and the surrounding settlements, industrial and agricultural areas. Although most of the values of the 34 examined physicochemical characteristics fell within the range of data previously published for the Danube, and the mean values of all parameters indicated unpolluted surface water, different water quality was revealed upstream and downstream from the metropolitan area at each sampling time. Since the physicochemical characteristics causing the separation also differed from time to time, univariate tests and consensus ordination were used to determine which variables changed similarly during most of the examined period. With this evaluation method, several diffuse pollutants of anthropogenic origin contaminating the Danube in the long term were identified, such as nitrogen, phosphorus, sulphate, chloride, potassium and vanadium. The results demonstrated that trend-like effects of non-point pollution can be detected even in a large river, where physicochemical measurements can vary strongly in space and time.

Water quality and hydrochemical assessments of thermal springs, Gandaki Province, Nepal

Thermal springs are the sites where the water temperature lies above ambient temperature. They are widely used for power generation, hot water spas, balneotherapy, agriculture, laundering, and aquaculture. In Nepal, many thermal springs are reported but scientific understanding on water quality and hydrogeochemistry of the springs is very limited. In this study, a total of 28 physico-chemical parameters were measured in water samples collected from 12 thermal springs from Gandaki Province, Nepal. Correlation matrix and multivariate statistical analysis such as principal component analysis (PCA) and cluster analysis were used to understand the water quality and hydrogeochemistry of the hot water springs. The pH, temperature, electrical conductivity, total dissolved solids, and turbidity in the hot water springs ranged from 7.3 to 8.8, 31.6-64.3 °C, 206-16270 μS/cm, 115-6637 mg/L, and 0.21-63.7 NTU; respectively. The dominance order of major anions and cations were: Cl^- > HCO₃^- > SO₄^2- > NO₃^- > F^- and Na⁺ > Ca²⁺ > K⁺ > Mg²⁺; respectively. Comparison of the water quality parameters with the WHO and National Water Quality Standards suggested that the majority of the parameters were within the safe limit. Out of 9 heavy metals and trace elements analyzed Zn²⁺, Ni²⁺, Cr³⁺, Cd⁺², Hg (total), and Pb²⁺ were found below the safe limit but Fe (total), As (total) and Cu (total) were found higher than the WHO safe limit in total of 3, 5 and 1 sampling sites; respectively. The water quality index (WQI), sodium absorption ratio (SAR), and magnesium hazard (MH) ratio in the hot water springs ranged from 40.9 to 573, 2.2-49.3, 7.1-70.8; respectively. The result of PCA analysis showed that four principal components are required to explain hydrogeochemistry. Cluster analysis suggested that the sampling sites can be grouped into three distinct clusters based on total dissolved solids. Interestingly, the classification of hydrochemical facies using a Piper diagram suggested that 7 out of 12 thermal springs have Na-Cl type water. Finally, a perspective on the suitability of the hot springs for hot water spas and balneotherapy and policy recommendation is provided.

Spatial-temporal distribution, source identification, risk assessment and water quality assessment of trace elements in the surface water of typical tributary in Yangtze River delta, China

As China's first cross-province ecological compensation mechanism pilot area in the hinterland of the Yangtze River Delta, Xin'an River has been hotspot in the study of rational utilization of ecological resources, and the functional value of its ecosystem services has been widely concerned. As an important tributary of the upper reaches of Xin'an River, Fengle River may affect the whole basin. The spatial-temporal distributions, occurrence, water quality and risk assessment of trace elements were studied in Fengle River in three seasons. High element concentrations were found in the downstream. Traceability models results showed that the major sources of trace elements were related to different human activities. The water quality was worse downstream in the wet season, and was more suitable for irrigation in the dry season. Risk assessment results showed that Zn, Cu, Mn, Co, and As were able to pose the risk to the ecological environment and human.

Spatiotemporal analysis and prediction of water quality in Pearl River, China, using multivariate statistical techniques and data-driven model

Identifying spatiotemporal variation patterns and predicting future water quality are critical for rational and effective surface water management. In this study, an exploratory analysis and forecast workflow for water quality in Pearl River, Guangzhou, China, was established based on the 4-h interval dataset selected from 10 stations for water quality monitoring from 2019 to 2021. The multiple statistical techniques, such as cluster analysis (CA), principal component analysis (PCA), correlation analysis (CoA), and redundancy analysis (RDA), as well as data-driven model (i.e., gated recurrent unit (GRU)), were applied for assessing and predicting the water quality in the basin. The investigated sampling stations were classified into 3 categories based on differences in water quality, i.e., low, moderate, and high pollution regions. The average water quality indexes (WQI) values ranged from 38.43 to 92.63. Nitrogen was the most dominant pollutant, with high TN concentrations of 0.81-7.67 mg/L. Surface runoff, atmospheric deposition, and anthropogenic activities were the major contributors affecting the spatiotemporal variations in water quality. The decline in river water quality during the wet season was mainly attributed to increased surface runoff and extensive human activities. Furthermore, the short-term prediction of river water quality was achieved using the GRU model. The result indicated that for both DLCK and DTJ stations, the WQI for the 5-day lead time were predicted with accuracies of 0.82; for the LXH station, the WQI for the 3-day lead time was forecasted with an accuracy of 0.83. The finding of this study will shed a light on an effective reference and systematic support for spatio-seasonal variation and prediction patterns of water quality.

Ecological and health risk assessment and quantitative source apportionment of dissolved metals in ponds used for drinking and irrigation purposes

In this study, dissolved metal levels of 10 different ponds used as irrigation and drinking water sources in the north of Saros Bay (Türkiye) were evaluated using multivariate statistical methods, contamination and ecological risk indices, and absolute principal component score-multiple linear regression (APCS-MLR). The mean levels of metals in the ponds ranged from 0.045 µg/L (Cd) to 127 µg/L (Mn). Pond 7 used for drinking water source had the lowest total metal level. Only Mn levels in two ponds (P1 and P2) slightly exceeded the critical value set by EU Drinking Water Directive. However, the levels of all metals in all ponds were lower than the critical values set for irrigation water and aquatic life. According to the heavy metal pollution index (HPI), five ponds showed low metal pollution in terms of drinking water quality, four ponds showed moderate metal pollution, and one pond (P1) showed moderate to heavy pollution. According to the Nemerow pollution index (NPI) values (0.26-1.82), ponds P1 and P2 showed slight metal pollution, while other ponds showed insignificant metal pollution. Contamination degree (CD) values of ponds varied between 0.95 and 3.33, indicating that all ponds showed low pollution. In terms of irrigation water quality, all ponds showed low or insignificant metal pollution according to the HPI, NPI, and CD values. According to the ecological risk index (ERI) values, metals in all ponds posed low ecological risks for both drinking and irrigation purposes. Factor analysis identified two potential sources: mixed sources and natural sources. The APCS-MLR model results revealed that mixed sources and natural sources contributed 78.99% and 21.01% to dissolved metals in the ponds, respectively. Health risk assessment results indicated that both individual and combined metals in the ponds would not cause non-carcinogenic risks to both adults and children. Similarly, it was found that Cr and As would not cause carcinogenic risks to the residents of the region.

Spatiotemporal variations, health risks, pollution status and possible sources of dissolved trace metal(loid)s in the Karasu River, Turkey

The Karasu River is the main tributary of the Euphrates River, which is the longest river in Southwest Asia. Domestic and industrial wastewater discharges, agricultural practices and mining activities in the basin can cause potential toxic metal pollution in the Karasu River. However, very little is known about the levels of dissolved trace metal(loid)s (TMs) in the river. In this study, levels of ten TMs (Fe, Al, Cd, Ni, Cu, Zn, Pb, As, Mn and Cr) in water samples taken monthly from 8 stations along the Karasu River between January 2019 and December 2019 were measured and compared with water quality guidelines. In addition, spatial and seasonal variations, health risks, pollution status and possible sources of the TMs were assessed. The 90th percentile levels of the TMs were below the drinking water standards. The highest total concentration was recorded at the most upstream station due to weathering processes, and rain and snowmelt runoff. The total metal concentration showed an increasing trend from winter to summer due to the combined effect of natural and anthropogenic sources. Metal pollution indices indicated that river water quality is suitable for potable uses. The results of factor and cluster analyses revealed that Ni, Fe, Mn and Cr are controlled by both lithogenic sources and anthropogenic activities, while other TMs are controlled by lithogenic sources. The hazard quotient (HQ) of each TM for both water ingestion and dermal contact pathways for residents was below the risk level. However, the hazard index (sum of HQs of all TMs) for water ingestion for children was higher than the risk level, indicated that the ingestion of ten TMs in the Karasu River may pose non-carcinogenic health risks to children. The carcinogenic risk results of As and Cr for both water ingestion and dermal absorption were within or below the acceptable carcinogenic risk range.

Hydrochemical appraisal and solute acquisitions in Seti River Basin, Central Himalaya, Nepal

The chemical characterization and assessment of the water quality in the headwater areas of the Himalaya are necessary for securing the water in the future. This study aims to assess the hydrochemistry and water quality concerning drinking and irrigational uses in the Seti River Basin (SRB), Nepal. A total of 45 water samples were collected in 2016 from the SRB during pre-monsoon, monsoon, and post-monsoon seasons, and pH, EC, TDS, and DO were measured on-site, whereas Ca²⁺, Mg²⁺, K⁺, Na⁺, Cl^-, SO₄^2-, NO₃^-, and dissolved Si were analyzed in the laboratory. The results revealed mildly alkaline pH (8.40 ± 0.43) with the pattern of average ionic dominancy: Ca²⁺  > Mg²⁺  > Na⁺  > K⁺ and HCO₃^- > SO₄^2- > Cl^- > NO₃^- for cations and anions, respectively. Gibbs diagram implied that the lithogenic weathering mainly controlled the solute acquisition process, which was further confirmed by the Piper diagram, exhibiting Ca-HCO₃ as the governing hydrochemical facies (91%). The average molar ratios were 0.88, 8.33, and 6.86 of (Ca²⁺ + Mg²⁺)/TZ⁺, (Ca²⁺ + Mg²⁺)/(Na⁺ + K⁺), and HCO₃^-/(Na⁺ + K⁺), respectively, which specified that the carbonate weathering largely controlled the solute acquisition processes with a minor contribution of silicates. The mass budget calculation also confirmed the dominance of carbonate weathering (72.0%, 78.9%, and 62.0% in Pre-Monsoon, Monsoon, and Post-Monsoon, respectively) and the high monsoon rainfall's dilution effect to anthropogenic input of cations. Principal component analysis and correlation matrix exhibited that the major sources of ions in the basin were geogenic with minor anthropic signatures. Furthermore, water quality in connection to drinking and irrigation uses revealed that the basin has mostly retained its natural water quality. This investigation suggests that regular monitoring and assessment are essential for maintaining the water quality and ecological integrity in the Himalayan river basins.

Seasonal Variations and Health Risk Assessment of Trace Elements in Seti River Basin, Gandaki Province, Nepal

To explore the seasonal variability and associated health risks of dissolved trace elements (TEs), a total of 45 water samples (15 samples in each season) were collected from the Seti River Basin during pre-monsoon, monsoon, and post-monsoon seasons. A total of 15 TEs were analysed and the results revealed that Arsenic (As), Chromium (Cr), and Nickel (Ni) were primarily controlled by lithogenic sources, whereas, Cadmium (Cd), Cobalt (Co), Cesium (Cs), Cupper (Cu), Manganese (Mn), Lead (Pb), and Zinc (Zn) were derived from both anthropic and geogenic sources. Additionally, the concentration of Zn was markedly high, especially during the post-monsoon season nearby the landfill site, indicating the anthropic signatures. The hazard index and cancer index were found to be < 1.00 and 10^-6-10^-4, respectively indicating minimum health impacts. The water quality index was < 50 throughout the sampling periods, with better water quality during the monsoon. This study could help to formulate the necessary policies for the sustainability of the Himalayan River Basins.

Forest restoration and support for sustainable ecosystems in the Gandaki Basin, Nepal

Restoring degraded forest is essential if we are to reduce human pressure on natural ecosystems and their biodiversity. Forests were nationalized in 1957 in Nepal and as a consequence, forest cover declined from 45% in 1964 to just 29% in 1994. However, as its response, sectoral plans and policies, particularly introduction of community-based forest management programs since the 1980s and conservation activities resulted in large scale forest cover restoration. Here, we examined the forest cover change in the Gandaki River Basin (GRB), the catchment with the largest altitudinal variation (ranging from ± 93 to 8167 m) and environmental and ecological significance. To see how forests have changed since then, we analyzed snapshots of spatiotemporal, ecological and physiographic changes in forest cover, and forest type at decadal intervals from 1996 to 2016 using Landsat 5 and 8 satellite images. We observed an overall gain in forest cover of 207 km², from 7571 km² (34.4% of the total area) in 1996 to 7778 km² (35.3%) in 2016. Of the 21 forest cover types identified, the greatest forest coverage during 2016 was of Schima-Castanopsis forest (25.9%) and hill sal forests (16.4%). In terms of physiographic zones, land below 500 m (Tarai) where most people live, witnessed gradual declines in forest cover, in contrast to large increases in forests above 500 m. Historical examination of forest cover at ecological and physiographic scales helps to identify the elevation-wise distribution of forest resources, vegetation composition, ecosystem characteristics, anthropogenic pressure upon vegetation, and hence the overall influence of LULC upon the environment. These outputs will assist planners, policy makers, and researchers in their formulation of effective basin wide plans and policies to ensure the protection of basin level biodiversity and ecosystem function.

Distribution and risk appraisal of dissolved trace elements in Begnas Lake and Rupa Lake, Gandaki Province, Nepal

Contamination of the trace elements (TEs) in the freshwater ecosystems is becoming a worldwide problem. This study was carried out to investigate the TEs contamination, and their associated health risk in Begnas Lake and Rupa Lake, Gandaki Province, Nepal. A total of 30 water samples were collected from both lakes during the pre-monsoon season in 2016. The samples were analyzed for the TEs including copper (Cu), lead (Pb), zinc (Zn), nickel (Ni), cobalt (Co), chromium (Cr), cadmium (Cd), manganese (Mn), cesium (Cs), and arsenic (As) using inductively coupled plasma mass spectrometry. The results exhibited that the mean concentrations of all the TEs were higher in Rupa Lake as compared to Begnas Lake except Pb. Principal component analysis and cluster analysis revealed that both the geogenic and anthropic sources were the major contributors of TEs in the lake water. Anthropic activities were considered to contribute the TEs like Zn and Mn in lake water mainly via agricultural runoff, while evaluating the risk of TEs on human health all the elements showed HQ < 1 and CR < 10−4 indicating currently very low health risk concerns. In good agreement with above, the water quality index (WQI) of the Begnas Lake and Rupa Lake was 2.67 and 5.66, respectively, specifying the lake water was safe for drinking and public health concern. This appraisal would help the policymakers and concerned stakeholders for the sustainable management of Ramsar listed freshwater lakes in the Himalayas.

Spatiotemporal variations, sources, water quality and health risk assessment of trace elements in the Fen River

As the largest river in Shanxi Province, the Fen River is the main water source for regional economic and ecological development. Water deficiency and industrialization have led to serious water pollution in the Fen River. The major and trace elements of seasonal river waters were measured to determine the spatiotemporal variations and assess the water quality as well as its controlling factors in the Fen River. Trace elements are divided into high abundance elements (B, Ba, Li, and Mn) and low abundance elements (As, Cu, Fe, Ni, Rb, Se, U, and V). The spatial variation of trace elements is obvious, with low values upstream, intermediate values downstream, and very high values midstream. The average values of the trace elements showed different seasonal variations, with high values of As, B, Ba, Mn, and Rb in the wet season, high Cu, V, and Li values in the dry season, and minor seasonal variations of Fe, Ni, Se, and U concentrations. Principal component analysis (PCA) and correlation analysis (CA) showed natural origins of Ba, Mn, Ni, and U, anthropogenic input of As, B, Cu, Li, Rb, Se, and V. According to the results of absolute principal component sore-multivariate linear regression (APCS-MLR), the major pollution sources in the Fen River basin were related to human activities. The land use type significantly influenced the concentrations of trace elements, with high values in the cropland and low values in the forest. The water quality index (WQI) values were higher in the midstream and wet season. In comparison with other rivers in the world, the pollution of the Fen River is at a moderate level. Health risk assessment showed that As, Ba, Mn, Ni, V, and Se were the potential pollutants damaging in the Fen River, especially for children. This study highlights the importance of seasonal sample analysis and can provide vital data for water quality conservation in the Fen River basin.

New insights into trace elements in the water cycle of a karst-dominated glacierized region, southeast Tibetan Plateau

Trace elements (TEs) in water are crucial parameters for assessing water quality. However, detailed studies are limited on TEs in the hydrological system of the Tibetan plateau (TP). Here, we sampled snow, river water, and groundwater in Yulong Snow Mountain (Mt. Yulong) region, southeast TP, in 2016 and analyzed the concentrations of nine TEs (namely Al, Mn, Fe, Cr, Ni, Cu, Zn, As, and Pb). In snow, the average concentrations of Fe, Zn, and Al were >10 μg/L, whereas other elements, including Cr, Ni, Cu, As, Hg, and Pb, exhibited average concentrations <1 μg/L. The concentrations of Al, Mn, Fe, Zn, and As were higher in rivers than in snow. According to enrichment factors (EFs), Zn concentration in snow was highly influenced by anthropogenic activities, whereas Mn, Fe, Cr, and As were uninfluenced. River and lake/reservoir water near human settlements were affected by anthropogenic activities. However, groundwater around Mt. Yulong is not contaminated yet. The increasing EFs in Mt. Yulong snowpit are consistent with those of southern TP snowpits, suggesting that the area has been affected by anthropogenic activities both from local emissions and long-distance transport of pollutants from South Asia. A conceptual model was proposed to show TEs in the water cycle. Although water quality is good overall in Mt. Yulong region, threats to the water environment still exit due to increasing anthropogenic activities and climate warming. The accelerated ablation of cryosphere due to climate warming could be a source of TEs in rivers and groundwater, which should be paid attention to in the future.

Quantifying Source Apportionment, Co-occurrence, and Ecotoxicological Risk of Metals from Upstream, Lower Midstream, and Downstream River Segments, Bangladesh

The positive matrix factorization (PMF) receptor model was used for the first time to quantify the source contributions to heavy metal pollution of sediment on a national basin scale in the upstream, midstream, and downstream rivers (Teesta and Kortoya-Shitalakkah and Meghna-Rupsha and Pasur) of Bangladesh. The metal contamination status, co-occurrence, and ecotoxicological risk were also investigated. Sediment samples were collected from 30 sites at a depth range of 0 to 20 cm for analysis of 9 metals using inductively coupled plasma-mass spectrometry. The mean concentrations of metals varied for upstream, lower midstream, and downstream river segments. The results showed that chromium (Cr) exhibited a strong significant co-occurrence network with other metals (e.g., manganese [Mn], iron [Fe], and nickel [Ni]). Monte Carlo simulation results of the geo-accumulation index (Igeo; 63.3%) and risk indices (48.5%) showed that cadmium (Cd) was the main contributor to sediment pollution. However, the cumulative probabilities of sediments being polluted by metals were ranked as "moderate to heavily polluted" (Igeo 46.6%; risk index 16.7%). Toxicity unit results revealed that zinc (Zn) and Cd were the key toxic contributors to sediments. The PMF model predicted metal concentrations and identified 4 potential sources. The agricultural source (factor 1) mostly contributed to copper (Cu; 78.9%) and arsenic (As; 62.8%); Ni (96.9%) and Mn (83.5%) exhibited industrial point sources (factor 2), with 2 hot spots in northwestern and southwestern regions. Cadmium (93.5%) had anthropogenic point sources (factor 3), and Fe (64.3%) and Cr (53.5%) had a mixed source (factor 4). Spatially, similar patterns between PMF apportioning factors and predicted metal sources were identified, showing the efficiency of the model for river systems analysis. The degree of metal contamination in the river segments suggests an alarming condition for biotic components of the ecosystem. Environ Toxicol Chem 2020;39:2041-2054. © 2020 SETAC.