Source apportionment and source-oriented risk assessment of heavy metals in the sediments of an urban river-lake system

Spatial distribution, sediment‒water partitioning, risk assessment and source apportionment of heavy metals in the Golmud River-Dabson Salt Lake ecosystem

The occurrence of heavy metals is important for understanding their behavior in the sediments of river-salt lake ecosystems due to dramatically changes in salinity and flow velocity at the confluence area. Sediments and surface water samples were collected from the Golmud River-Dabson Salt Lake ecosystem, northwest China, to investigate the spatial distribution, sediment-water partitioning, risk assessment and source apportionment of heavy metals. Higher concentrations of heavy metals were observed in surface water from Dabson Salt Lake than in other regions. Additionally, a lower partition coefficient (Kd) for heavy metals was observed in Dabson Salt Lake, indicating their pronounced release from the sediments into the surface water. Elevated levels of heavy metals were detected at the confluence area between the Golmud River and southeast Dabson Salt Lake because of industrial activities. The assessment indices indicated that almost all heavy metals in the sediments of the Golmud River and Dabson Lake posed no pollution or low potential ecological risk. Notably, Pb in some samples from the Freshwater Zone reached heavy pollution levels. The results of APCS-MLR revealed that except Pb, other heavy metals were grouped into the first principal component, which originated primarily from rock parent materials. The second principal components (industrial source), explaining 46.97% of the variance, only included Pb. The natural, industrial and unidentified sources explained 76.56%, 14.95% and 8.49%, respectively, of the heavy metal sources. These findings can significantly contribute to the management of heavy metal pollution and enhance our understanding of heavy metal behavior in river-salt lake ecosystems.

Metals in sediments of the Great Lakes of North America determined by factor analysis

Metal data from eight sediment cores including 178 segments from Lakes Superior, Michigan, Huron, Erie, and Ontario were subjected to positive matrix factorization to extract characteristic loading and score plots for Pb, Cd, As, Zn, Cu, Ni, Co, and Cr. Lake Superior has significant concentrations of Cu, max 205 ppm, with notable contributions of Pb, Ni, and Cr from the Precambrian bedrock in the northern part. Lake Michigan shows distinct Pb input in the southern core and likely automotive input with max during 1966-1971 in both cores. Recent input of As since 2009 is reflected in Lake Huron, max 31.4 ppm, and both the western and eastern Lake Ontario, max 81 ppm, which may originate in part from Lakes in the Sudbury, area and from Lake Moira both in Ontario, Canada. Highway input of metals is shown in cores from Lakes Huron, Erie, and Ontario with maxima during 1970-1973. This is supported by Zn/Pb and Zn/Cu ratios which match literature values of 6.3 and 4.7, respectively, for highway runoff. Lake Ontario has large inputs of Ni and Zn, likely from local industries. Plots of Ag vs. time for Lake Ontario point to a maximum in the eastern part in 1971, which along with literature values for Ag in Ponar Grabs of eastern Lake Ontario suggest an Ag source near Rochester, NY.

Tracing sources-oriented ecological risks of metal(loid)s in sediments of anthropogenically-affected coastal ecosystem from northeast bay of Bengal

The current study focused on thirty-nine locations in the four islands (i.e., St. Martin, Moheskhali, Kutubdia, and Sonadia) and beach (Innani Beach) along the northeast Bay of Bengal to quantify sources-orientated ecological risks of metal(loid)s. The mean concentrations of As, Mn, Cr, Cd, and Pb are 4.8, 8.7, 1.6, 1.1, and 2 times higher than average shale volume (ASV) values. Key findings revealed that Mn, Cr, Cd, Pb, and As exceed safe levels, particularly on St. Martin and Moheshkhali islands, where tourism and coal mining intensify contamination. Ecological indexes showed moderate to considerable contamination levels, suggesting diverse impacts on aquatic life. Positive matrix factorization (PMF) model-based Nemerow integrated risk index (NIRI) indicated that mixed and coal mining sources posed a moderate risk for 10.26 % and 5.13 % of sediment samples, respectively. This paper serves as a model-based plan for mitigating pollution risks of metal(oid)s in coastal sediments on the northeast coast.

Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodetector

Identifying and quantifying the dominant factors influencing heavy metal (HM) pollution sources are essential for maintaining soil ecological health and implementing effective pollution control measures. This study analyzed soil HM samples from 53 different land use types in Jiaozuo City, Henan Province, China. Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation. Geodetector and a genetic algorithm optimized random forest model (GA-RF) were employed to quantify the dominant factors and precisely identify pollution sources. A Monte Carlo model was further applied to assess source-oriented health risk probabilities across age groups in the study area. The results revealed three principal components representing pollution sources, with contribution rates of 47.2 %, 33.3 %, and 19.5 %, respectively. For pollution source 1, industrial activities were dominant, with factory density (27.7 %) and distance from the factory (36.3 %) identified as the main factors. Cr, Cu, Mn, and Ni had high loads in this source. Pollution source 2, a combination of natural and transportation influences, was primarily affected by the normalized difference vegetation index (NDVI, 37.8 %), road network density (16.8 %), and proximity to roads (15.3 %). Pollution source 3 was linked to agricultural activities, with cultivated land density (CLD) contributing 39.1 %. As exhibited a high load (91.1 %) in this source, with an exceedance rate of 93 % in cultivated soil, a moderate enrichment factor of 2.33, and a strong ecological risk index of 615.72, making it the most polluted metal in the area. The source-oriented Health Risk Assessment (HRA) showed that agricultural activities contributed 88.7 % to the carcinogenic risk from As in cultivated land. Overall, 99.3 % of the population faced an acceptable cancer risk level. Unlike traditional source apportionment methods, the GA-RF model effectively quantified the contributions of specific influencing factors (e.g., factory density) to pollution sources, rather than merely estimating the percentage contributions of the sources themselves. This approach provides a novel perspective for HM source apportionment under complex environmental conditions.

Microbial community structure and causal analysis in sediments of shallow eutrophic freshwater lakes under heavy metal compound pollution

Heavy metals, due to their toxicity, persistence, and non-biodegradability, have become some of the most severe environmental pollutants globally. Their accumulation in lake sediments can significantly impact aquatic ecosystems' biogeochemical cycles by altering the ecological dynamics of microbial communities. To further elucidate the mechanisms underlying microbial responses to complex heavy metal pollution in lake sediments, sediment samples were collected from Nan Yi Lake, and their physicochemical properties and microbial composition were systematically analyzed. The results demonstrated that the sediments of Nan Yi Lake were significantly contaminated with heavy metals, which were identified as the predominant factors shaping microbial community structure. Heavy metals influenced microbial richness and distribution patterns along sediment depth gradients, driving the establishment of optimal ecological niches. Meanwhile, other physicochemical factors indirectly affected microbial communities by modulating the concentration of heavy metals. Furthermore, the microbial co-occurrence network was closely associated with the concentrations of Fe and As, with sediment particle size also playing a contributing role. This study highlights the intricate interactions between physicochemical factors and microorganisms, offering critical insights into the multifaceted impacts of heavy metal compound pollution on lake ecosystems. It provides a scientific foundation for effective management of lake environmental pollution and ecological restoration efforts.

Soil and Sediment Organisms as Bioindicators of Pollution

This review examines the role of soil and sediment organisms as bioindicators in environmental pollution assessment. As fundamental elements of terrestrial ecosystems, soils harbour a rich and diverse biodiversity that plays a key role in regulating ecological processes. The use of bioindicators provides a sensitive and specific approach to detecting the effects of chemical, biological, and physical pollutants on soil health. The review presents a detailed analysis of the types of contaminants commonly encountered, the soil organisms used as bioindicators, and the criteria for selecting the most appropriate bioindicators. It also discusses assessment methods, including soil sampling and analysis techniques, and the biological and ecological indices used to measure contamination. Regional case studies illustrate the practical application of bioindicators for assessing soil quality in different geographical contexts. The review also highlights current challenges to the use of bioindicators, such as technical limitations and the variability of organism responses, and suggests perspectives for future research, including technological innovation and the integration of bioindicators into environmental policy.

Source-risk and uncertainty assessment of trace metals in surface sediments of a human-dominated seaward catchment in eastern China

Current total concentration-based methods for source attribution and risk assessment often overestimate metal risks, thereby impeding the formulation of effective risk management strategies. This study aims to develop a framework for source-specific risk assessment based on metal bioavailability in surface river sediments from a human-dominated seaward catchment in eastern China. Metal bioavailability was quantified using chemical fractionation results, and source apportionment was conducted using the positive matrix factorization (PMF) model. Risk assessment integrated these findings using two indices: the Potential Ecological Risk Index (PERI) and the Mean Probable Effect Concentration Quotient (mPEC-Q), with uncertainty addressed via Monte Carlo simulations. Results indicated that average total concentrations of Cu, Pb, Zn, Cr, Hg, Cd, and As exceeded their respective background levels by 1.63 to 15.00 times. The residual fraction constituted the majority, accounting for 53.84 % to 77.79 % of total concentrations, suggesting significant natural origins. However, source apportionment revealed a predominant contribution from anthropogenic activities, including industrial smelting, agricultural practices, and atmospheric deposition. The contributions were found to vary between 5.35 % and 40.03 % when the total concentration was adjusted to bioavailable content. Total concentration-based PERI/mPEC-Q assessments indicated high/moderate risk levels, decreasing to considerable/low risk levels with bioavailability adjustment. Hg and Cd were identified as priority metals. Further incorporating source appointment parameters into the risk assessment, industrial smelting was identified as the primary contributor, accounting for 66.06 % of total risk by total concentration and 65.63 % by bioavailability. This underscores the role of bioavailability in mitigating risk overestimation. Monte Carlo simulations validated industrial smelting as a major risk contributor. This study emphasizes the importance of considering bioavailability in the source-risk assessment of sediment-metals, crucial for targeted risk management in urbanized catchment areas.

Trends and risk assessment of heavy metals in the surface sediments of river-connected lakes: A case study of Dongting Lake

This study analyzed the spatiotemporal distribution characteristics, ecological risks, biological toxicity, and sources of Cu, Zn, Pb, Cd, Hg, and As in the surface sediments of Dongting Lake, as well as the response of benthic macroinvertebrates to these pollutants. Among the three lake regions, the concentration of Cu, Zn, Pb, Cd, and As fell in the order of South Dongting Lake (SD) > East Dongting Lake (ED) > West Dongting Lake (WD), whereas the concentration of Hg fell in the order of WD > SD > ED. The concentrations of Cu, Zn, Pb, and As were 1.69-2.02 times the background values recorded in 1986, whereas the concentrations of Cd and Hg were 8.97 and 5.32 times the background values, respectively. The ecological risk was low for Cu, Zn, Pb, As but high for Hg and Cd. For Dongting Lake in aggregate, the heavy metals caused considerable ecological risk and high biotoxicity, although the situation was improving in recent years. Cd, As, Cu, Pb, Hg were mainly from agricultural sources, mining sources, tire wear and agricultural sources, industrial smelting and mining sources, industrial processing and smelting sources, respectively, and Zn was from mixed sources. A total of 66 species of benthic macroinvertebrates were identified from the sediments. From 2018 to 2022, the dominant benthic macroinvertebrates gradually shifted from the pollution-resistant in Tubificidae to those in Gammarus, Bellamya, Valvatidae, etc. Oligochaetes and Stictochironomus spp. exhibited extremely high response to heavy metals and could serve as indicator organisms of heavy metal pollution.

Potentially toxic elements in surface sediments of the Beibu Gulf, South Sea, China: Occurrence, bioavailability and probabilistic risk assessment

At present, pollution of gulf sediments with potentially toxic elements (PTEs) has become a prominent marine environmental problem. This study thoroughly investigated the occurrence, bioavailability, and probabilistic risk of PTEs in the surface sediments of the Beibu Gulf. The average total concentrations (mg/kg) were 8.03 for As, 0.06 for Cd, 52.73 for Cr, 9.86 for Cu, 0.04 for Hg, 18.70 for Ni, 27.77 for Pb and 59.80 for Zn, respectively. The positive matrix factorization model revealed that the PTE enrichment was primarily due to composite sources from aquaculture and fisheries activities, industrial and agricultural sources. Risk assessment code and correlation analysis indicated that Cd had the highest bioavailability, influenced by TOC and TP. The probabilistic risk assessment model estimated a 60.83 % probability that the mixed PTEs in the Beibu Gulf's surface sediments could have toxic effects on aquatic life. These findings underscore the impact of intensive human activities on PTE pollution and highlight the need for further research on PTE ecotoxicology and pollution control strategies.

Contamination, fraction, and source apportionment of heavy metals in sediment of an industrialized urban river in China

In this study, we conducted an analysis of the heavy metal concentrations, health risk assessment, fraction and source interpretation in surface and core sediments from main stream of the Pearl River and Pearl River Estuary (RRE) area. Results showed that the higher deposited heavy metal concentrations in sediments occur at the Pearl River. The concentrations of heavy metals in surface sediments from the studied locations are in a descending order: Zn > Cr > Cu > Ni > Pb > Cd. Regarding chemical fractions, Cd showed the highest proportion of acid soluble fraction (F1) among all studied heavy metals. The high mobility of Cd poses a significant threat to water bodies and the surrounding environment. The potential ecological risk index (RI) showed the Pearl River sediments exhibited significantly higher values than the estuary sediments. Cd was found to be the primary contributor to potential ecological risk, accounting for 74% of RI. The health risk assessment showed the total hazard index (HI) for child was exceeded 1 mainly driven by Zn, indicating that the child population was at risk of non-carcinogenic effects. Besides, unacceptable carcinogenic risk in both Pearl River and estuary area were observed for children. The positive matrix factorization (PMF) model was used to ascertain sources of six heavy metals and apportion their contributions in sediments. The results showed that the source contributions of natural, industrial, and mixed sources from coal combustion and traffic emissions accounted for 39.81%, 34.10%, 26.10%.

Spatial distribution of heavy metal contamination and risk indices of surface sediments in high-altitude lakes

Lake ecosystems in northern Pakistan are the most critical resources that maintain and regulate water flow for downstream agricultural, domestic, industrial, and ecological processes. One consequence of these processes is that ecosystems deposit heavy metals (HMs), where lake stagnant conditions result in high vulnerability of water resources. For this purpose, the present study examined HMs such as cadmium (Cd), chromium (Cr), cobalt (Co), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn) concentrations in high-altitude lakes (HAL) sediments of Mansehra district, northern Pakistan. Sediment samples were collected from the five HAL. This study used HM concentrations in lake sediments for the pollution factors such as contamination factor (Cf), pollution load index (PLI), sediment pollution index (SPI), ecological risk assessment (ERA), and risk index (RI). Among HMs, Fe showed the uppermost levels of 1410 mg/kg in lake sediment, while Cd with lowermost levels of 1.05 mg/kg. Results revealed that most HM concentrations in HAL sediments were within the threshold of sediments quality guidelines (SQGs), except for Cd. Among lakes, the sediments of Siri Lake showed higher contamination of HMs than others. Siri Lake sediments also showed higher Cf, PLI, ERA, and RI values than others. The majority of HMs in HAL sediments showed no contamination, except for Cd (considerable) and Pb (moderate) levels to the exposed aquatic ecosystem. This study revealed that 95% of sediment samples in HAL were noted low to medium-level risks to the exposed aquatic communities. Statistical and geospatial analyses revealed that geogenic sources of contamination are a significant contributor to HM contamination of HAL sediments compared to others.

Deciphering the pollution risks, sources and their links of heavy metals in soils

Heavy metals in soils pose serious ecological and health risks. To make efficient strategies for mitigating the underlying hazards, it is critical to reveal the pollution sources and their links with the risks. Researchers have investigated source identification and risk evaluation of heavy metals in soils, yet few have systematically deciphered the source-sink relationship of soil metals and the links between source apportionment and risk assessment. In the study, an integrated technological framework has been proposed to address the gaps, and applied to characterize the pollution risks, sources and their links of soil metals in a typical coal resource city in China. The assessment using geochemical tool and ecological risk index shows the soils in study area are polluted by Cd, Hg, Cr, As and Pb in varied degrees, and particularly, Cd and Hg present significant ecological risk. Two advanced receptor models (multivariate curve resolution-weighted alternating least-squares and multilinear engine 2) are comparatively applied for apportioning the potential sources of soil metals, and the results suggest the two models have identified similar sources (r2 > 0.90), including agricultural activities, atmospheric depositions and industrial discharges with contributions of 35.5 %-38.3 %, 30.3 %-35.1 %, and 26.6 %-34.1 %, respectively. Then, apportionment results of the two models are jointly employed for evaluating the source-specific health risks of metals in the environment using a probabilistic risk assessment model. The risk levels within the area are overall acceptable or tolerable, and relatively, the industrial discharges present higher contribution on the non-carcinogenic and carcinogenic risks of soil metals to public. Findings will help the managers to design targeted policies for reducing the risks of soil metals, and the framework proposed provides a useful guideline to better understand the source-risk relationship of soil metals in other environments worldwide.

Multimodel-based quantitative source apportionment and risk assessment of soil heavy metals: A reliable method to achieve regional pollution traceability and management

To strengthen the control of pollution sources and promote soil pollution management of agricultural land, this study constructed a comprehensive source apportionment framework, which significantly improved the reliability of potential source analysis compared with the traditional single model. The spatial distribution pattern of agricultural soil heavy metals (SHMs) content in Lintong, a typical river valley city in China, was determined and the degree of contamination was evaluated. A scientific source apportionment methodological framework was constructed through correlation analysis methods together with multiple source apportionment receptor models. Finally, the Monte Carlo simulation method was used to derive the results of the human health risk assessment (HHRA). The results revealed the following: (1) Agricultural soils were moderately and mildly polluted, accounting for 28.8 % and 71.2 % of the total number of sampling points, respectively. (2) The overall correlation of heavy metals (HMs) was strong according to the coupling analysis of the SHMs, in which a strong correlation (0.8-1) was reached among Cu, Ni, Pb, Cr and Zn, indicating that these HMs were most likely homologous or composite. (3) Multimodel analysis of the SHMs sources revealed that the first and second principal components were agricultural (41.36 %) and industrial (19.69 %) sources, respectively, and the remaining principal components were road traffic, natural factors, and atmospheric deposition or surface runoff, respectively. (4) The average comprehensive noncarcinogenic health risk indices for adults and children were 4.2259E-02 and 1.4194E-01, respectively, which were within the slight risk range, indicating that the risk caused by SHMs to the human body can be almost negligible. This study adopted a mixed method to reveal the risk of SHMs pollution and its sources, which provides some reference and technical support for traceability analysis, zoning control, and health risk studies of regional pollutants and is helpful for formulating scientific management measures and targeting control policies.

Spatial heterogeneity: Necessary and feasible for revealing soil trace elements pollution, sources, risks, and their links

The source diversity and health risk of trace elements (TEs) in soil make it necessary to reveal the relationship between pollution, source, and risk. However, neglect of spatial heterogeneity restricts the reliability of existing identification methods. In this study, spatial heterogeneity is proposed as a necessary and feasible factor for accurately dissecting the pollution-source-risk link of soil TEs. A comprehensive framework is developed by integrating positive matrix factorization, Geodetector, and risk evaluation tools, and successfully applied in a mining-intensive city in northern China. Overall, the TEs are derived from natural background (28.5 %), atmospheric deposition (25.6 %), coal mining (21.8 %), and metal industry (24.1 %). The formation mechanism of heterogeneity for high-variance TEs (Se, Hg, Cd) is first systematically deciphered by revealing the heterogeneous source-sink relationship. Specifically, Se is dominated (76.5 %) by heterogeneous coal mining (q=0.187), Hg is determined (92.6 %) by the heterogeneity of metal mining (q=0.183) and smelting (q=0.363), and Cd is caused (50.9 %) by heterogeneous atmospheric deposition (q>0.254) co-influenced by the terrains and soil properties. Highly heterogeneous sources are also noteworthy for their potential to pose extreme risks (THI=1.122) in local areas. This study highlights the necessity of integrating spatial heterogeneity in pollution and risk assessment of soil TEs.

Application of time series and multivariate statistical models for water quality assessment and pollution source apportionment in an Urban River, New Jersey, USA

Water quality monitoring reveals changing trends in the environmental condition of aquatic systems, elucidates the prevailing factors impacting a water body, and facilitates science-backed policymaking. A 2020 hiatus in water quality data tracking in the Lower Passaic River (LPR), New Jersey, has created a 5-year information gap. To gain insight into the LPR water quality status during this lag period and ahead, water quality indices computed with 16-year historical data available for 12 physical, chemical, nutrient, and microbiological parameters were used to predict water quality between 2020 and 2025 using seasonal autoregressive moving average (ARIMA) models. Average water quality ranged from good to very poor (34 ≤ µWQI ≤ 95), with noticeable spatial and seasonal variations detected in the historical and predicted data. Pollution source tracking with the positive matrix factorization (PMF) model yielded significant R2 values (0.9 < R2 ≤ 1) for the input parameters and revealed four major LPR pollution factors, i.e., combined sewer systems, surface runoff, tide-influenced sediment resuspension, and industrial wastewater with pollution contribution rates of 23-30.2% in the upstream and downstream study areas. Significant correlation of toxic metals, nutrients, and sewage indicators suggest similarities in their sources.

Appraisal of contamination, hydrogeochemistry, and Monte Carlo simulation of health risks of groundwater in a lithium-rich ore area

This study incorporated hydrogeochemical facies, the entropy-weighted water quality index (EWQI), multivariate statistics, and probabilistic human exposure assessment to investigate hydrogeochemistry, analyze groundwater quality, and estimate potential risks to human health in a lithium-rich ore area (Jadar River basin, Serbia). The findings designated the Ca·Mg-HCO3 hydrogeochemical type as the predominant type of groundwater, in which rock weathering and evaporation control the major ion chemistry. Due to the weathering of a lithium-rich mineral (Jadarite), the lithium content in the groundwater was very high, up to 567 mg/L, with a median value of 4.3 mg/L. According to the calculated EWQI, 86.4% of the samples belong to poor and extremely poor quality water for drinking. Geospatial mapping of the studied area uncovered several hotspots of severely contaminated groundwater. The risk assessment results show that groundwater contaminants pose significant non-carcinogenic and carcinogenic human health risks to residents, with most samples exceeding the allowable limits for the hazard index (HI) and the incremental lifetime cancer risk (ILCR). The ingestion exposure pathway has been identified as a critical contaminant route. Monte Carlo risk simulation made apparent that the likelihood of developing cancerous diseases is very high for both age groups. Sensitivity analysis highlighted ingestion rate and human body weight as the two most influential exposure factors on the variability of health risk assessment outcomes.

Source-specific ecological and human health risk analysis of topsoil heavy metals in urban greenspace: a case study from Tianshui City, northwest China

Soil contamination of heavy metals in urban greenspaces can exert detrimental impacts on ecological biodiversity and the health of inhabitants through cross-media migration-induced risks. Here, a total of 72 topsoil samples were collected from greenspaces in the popular tourist city of Tianshui, ranging from areas with parks, residential, road, industrial and educational soils. The study aimed to evaluate an integrated source-specific ecological and human health risk assessment of heavy metals. Among the analyzed heavy metals, except Cr (mean), all exceeded the local background values by 1.30-5.67-fold, and Hg, Cd, Pb and As were the metals with large CV values. The Igeo and CF results showed Hg, Cd, As and Pb exhibited significantly high pollution levels and were the primary pollution factors. The mean PLI values indicated moderate pollution in educational (2.21), industrial (2.07), and road (2.02) soils but slight pollution in park (1.84) and residential (1.39) greenspaces. The Igeo, CF, and PLI results also revealing that these heavy metals are more likely to be affected by human activity. Four primary source factors were identified based on PMF model: coal combustion (25.57%), agricultural sources (14.49%), atmospheric deposition (20.44%) and mixed sources (39.50%). In terms of ecological risk, the mean IRI values showed considerable risks in educational soils (287.52) and moderate risks in road (215.09), park (151.27) and residential (136.71) soils. And the contribution ratio of atmospheric deposition for park, residential, road, industrial and educational greenspaces were 57.72%, 65.41%, 67.69%, 59.60% and 75.76%, respectively. In terms of human health risk, the HI (below 1) and CR (below 1.00E-04) for adults from soils of all land use types was negligible. However, children have more significant non-carcinogenic and carcinogenic hazards especially in residential soils, the HI (above 1) and CR (above 1.00E-04) revealed the significance of regarding legacy As contamination from coal combustion when formulating risk mitigation strategies in this area. The proposed method for source and risk identification makes the multifaceted concerns of pollution and the different relevant risks into a concrete decision-making process, providing robust support for soil contamination control.

Development of an integrated framework for dissecting source-oriented ecological and health risks of heavy metals in soils

Heavy metals (HMs) in soils pose significant risks on ecosystem and human health. To design targeted regulatory measures for mitigating and controlling the risk, it is necessary to accurately identify the pollution sources and environmental risks of soil HMs, as well as to reveal the linkages between them. To date, yet systematic investigation aimed at deciphering the links between source apportionment of soil HMs and their associated environmental risks is still lacking. To fill the gap, an integrated framework has been developed in this study and applied for dissecting the source-sink relationship and source-oriented ecological and health risks of soil HMs in Shanxi, a province with rich coal resource, in which long-term coal mining activities in history has resulted in soil HMs pollution and unavoidably posed environmental risks. Two advanced receptor models, multivariate curve resolution alternating least squares based on maximum likelihood principal component analysis (MCR-ALS/MLPCA) and multilinear engine 2 (ME2), have been employed for apportioning the potential sources, and their apportionment results are jointly incorporated into a modified ecological risk index and a probabilistic health risk assessment model for identifying the source-oriented ecological and health risks posed by soil metals. The results show that the soils in study area have been polluted by HMs (i.e., Cd, Cr, Hg and As) to varying degrees. Industrial activities (35%-35.8%), agricultural activities (11.1%-20.5%), atmospheric deposition (10.5%-13%) and mix source (31.5%-42.6%) are apportioned as the main contributors of soil HMs in the area. The source-oriented ecological risk assessment suggests Hg has presented significant ecological risk and largely contributed by the sources from atmospheric deposition and industrial activities. The source-oriented health risk assessment shows the non-carcinogenic hazard level and carcinogenic risk posed by soil HMs in the study area are acceptable. Relatively, industrial activities and mix source have contributed more on the health risks.

Vertical Distribution Characteristics and Ecological Risk Assessment of Mercury and Arsenic in Ice, Water, and Sediment at a Cold-Arid Lake

Mercury and arsenic are two highly toxic pollutants, and many researchers have explored the effects of the two substances on the environment. However, the research content of toxic substances in frozen periods is relatively small. To explore the spatial and vertical distribution of mercury and arsenic in the ice, water, and sediments of Wuliangsuhai Lake under ice conditions, and to assess the harm degree of the two toxic substances to human beings. We collected the ice, water, and sediments of the lake in December 2020, and tested the contents of Hg and As. The single-factor pollution index method, the local cumulative index method, and the ecological risk coding method were used to assess the pollution status in these three environmental media, and the Monte Carlo simulation combined with the quantitative model recommended by USEPA was used to assess the population health risk. The results showed that (1) The average single-factor pollution values of Hg and As in water were 0.367 and 0.114, both pollutants were at clean levels during the frozen period. (2) The mean Igeo values of Hg and As were 0.657 and -0.948. The bioavailability of Hg in the sediments of Wuliangsuhai Lake during the frozen period was high, and its average value was 7.8%, which belonged to the low-risk grade. The bioavailability of As ranged from 0.2% to 3.7%, with an average value of 1.3%. (3) Monte Carlo simulation results indicate acceptable levels of health risks in both water and ice. This study preliminarily investigated the distribution characteristics of toxic substances and their potential effects on human health in lakes in cold and arid regions during the frozen period. It not only clarified the pollution characteristics of lakes in cold and arid regions during the frozen period, but also provided beneficial supplements for the ecological protection of lake basins. This study lays a foundation for further environmental science research in the region in the future.

Coupling sedimentary records of anthropogenic metal(loid)s in urban waterscape parks with the "Coal to Gas" transition

Energy consumption structure has been adjusted worldwide as a measure to reduce CO2 emission and mitigate air pollution. The "Coal to Gas" transition in mainland China has successfully controlled air pollution in recent decades, but its impacts on the environment beyond air quality improvement remain unknown. With 210Pb dating, this study chronicled profiles of eight anthropogenic metal(loid)s in sediment core from 14 waterscape parks across the Ring Road Network of Beijing, China. Six sediment cores were dated showing a timing coupling of metal(loid) loadings with annual coal consumption during the increasing period before 2000. Two downwind sediment cores in downtown Beijing presented such couplings in both increasing and descending periods for coal consumption before and after 2000, respectively, close to the tipping point observed in 2002 for primary energy consumption efficiency. Evidence from stable Pb isotope composition and exceedances of Cu loadings against sediment quality guidelines of China and the USA suggest that vehicular sources have been dominating metal(loid) loadings in sedimentation in these waterscape parks after the "Coal to Gas" transition. These findings would be helpful in identifying environmental impact patterns resulting from shifts in energy consumption structure and dominance of emission sources thereafter.

Rare earth elements reveal the human health and environmental concerns in the largest tributary of the Mekong river, Northeastern Thailand

The widespread application of rare earth elements (REEs) in contemporary industries and agriculture, has caused emerging contaminant accumulation in aquatic environments. However, there is a limited scope of risk assessments, particularly in relation to human health associated with REEs. This study investigated the provenance, and contamination levels of REEs, further evaluating their environmental and human health risks in river sediments from an agricultural basin. The concentrations of REEs ranged from 30.5 to 347.7 mg/kg, with showing an upward trend from headwater to downstream. The positive matrix factorization (PMF) model identified natural and anthropogenic input, especially from agricultural activities, as the primary source of REEs in Mun River sediments. The contamination assessment by the geoaccumulation index (I-geo) and pollution load index (PLI) confirmed that almost individual REEs in the samples were slightly to moderately polluted. The potential ecological risk index (PERI) showed mild to moderate risks in Mun River sediment. Regular fertilization poses pollution and ecological risks to agricultural areas, manifesting as an enrichment of light REEs in river sediments. Nevertheless, Monte Carlo simulations estimated the average daily doses of total REEs from sediments to be 0.24 μg/kg/day for adults and 0.95 μg/kg/day for children, comfortably below established human health thresholds. However, the risk of REE exposure appears to be higher in children, and sensitivity analyses suggested that REE concentration contributed more to health risks, whether the adults or children. Thus, concerns regarding REE contamination and risks should be raised considering the wide distribution of agricultural regions, and further attention is warranted to assess the health risks associated with other routes of REE exposure.

Identification of toxic metal contamination in surface sediments of the Xiaoqing River under a long-term perspective (1996-2020): Risks, sources and driving factors

The contamination of sediments by toxic metals poses a significant threat to both river ecosystems and human health. In this study, the geo-accumulation index (Igeo), biotoxicity evaluation method, and potential ecological risk index (RI) were employed to analyze the contamination level, biotoxicity risk, and potential ecological risk of toxic metals in surface sediments of the Xiaoqing River. To identify toxic metal sources, Spearman correlation and principal component analysis with multiple linear regression analysis (PCA-MLR) were employed. Additionally, redundancy analysis (RDA) was utilized to investigate potential driving factors affecting toxic metal accumulation in sediments. The results revealed that the levels of the five investigated metals (Cr, Pb, As, Hg, and Cd) showed constant fluctuations during the period 1996-2020. The midstream was found to be more polluted than the upstream and downstream. In the research area, Hg was identified as the primary contaminant with high levels of contamination, posing a biotoxicity risk and potential ecological risk. Pollution sources were identified for two periods: A (1996-2010) and B (2011-2020), with industrial, agricultural, traffic, and natural sources being the main contributors. During period A, industrial sources accounted for the highest proportion (40.8%), followed by agricultural sources (36.6%), and geological natural sources (22.6%). During period B, agricultural sources accounted for the highest proportion (42%), followed by industrial and traffic sources (32.4%), and geological natural sources (25.6%). The distribution of toxic metals in the basin was significantly influenced by water pH, sediment organic matter, population density, and per capita GDP. The study results provide fundamental data for preventing pollution and managing water resources contaminated with toxic metals in the sediments of the Xiaoqing River in Jinan. Additionally, it serves as a reference for analyzing related ecological and environmental issues in the basin.

Source apportionment and source-specific risk assessment of bioavailable metals in river sediments of an anthropogenically influenced watershed in China

Integrated source analysis and risk assessment of metals facilitate the development of targeted risk management strategies. However, previous studies usually addressed total concentration rather than bioavailability, and consequently overestimated metal risk, especially natural source-related risk. In this study, a source-specific risk assessment was conducted by integrating the source analysis of bioavailable metals in surface sediments. Moreover, risk assessment was performed using two bioavailability-based indices: the total availability risk index (TARI) and a modified index of mean probable effect concentration quotients (mPEC-Q). A representative river watershed in eastern China was selected as the study area. Findings revealed that the total concentrations of Pb, Cu, Zn, Cr, and Ni in the sediments were 1.4-2.2 times higher than the local soil background values. Using a modified community bureau of reference (BCR) sequential extraction procedure, the dominant fraction for Pb, Cu, Zn, and Cr in the studied area was found to be the residual fraction, constituting 53.63-62.44% of the total concentrations. This suggested that a significant portion of the metals potentially originated from natural sources. Nevertheless, the concentration enrichment ratio (CER) indicated that anthropogenic sources contributed significantly, accounting for 67.84-87.68% of bioavailable metals. The positive matrix factorization (PMF) model further identified three different sources of bioavailable metals, with a descending concentration contribution sequence of industrial sources (37.61%), mixed traffic and natural sources (33.17%), and agricultural sources (29.22%). Both the TARI and mPEC-Q index values indicated that the bioavailable metals generally posed a moderate risk, and Ni was the priority pollutant. Industrial sources contributed the most to the total risk, although the contribution from TARI-based assessment (37.27%) was lower than that from the mPEC-Q assessment (46.43%). This study provides an example of the consideration of metal bioavailability in the context of source-specific risk assessments to develop more reasonable management strategies.

Source-specific ecological and health risks of polycyclic aromatic hydrocarbons in the adjacent coastal area of the Yellow River Estuary, China

Industrialization and urbanization have led to increasing levels of PAH pollution in highly urbanized estuaries and their adjacent coastal areas globally. This study focused on the adjacent coastal area of the Yellow River Estuary (YRE) and collected surface seawater, surface sediment, and clams Ruditapes philippinarum and Mactra veneriformis at four sites (S1 to S4) in May, August, and October 2021 to analyze the source-specific ecological and health risks and bioeffects. The findings revealed that the main sources of PAHs were traffic emission (25.2% to 28.5%), petroleum sources (23.3% to 29.5%), coal combustion (24.7% to 27.5%), and biomass combustion (19.8% to 20.7%). Further, the PMF-RQ and PMF-ILCR analyses indicated that traffic emission was the primary contributor to ecological risks in seawater and health risks in both clam species, while coal combustion was the major contributor in sediment. Taken together, it is recommended to implement control strategies for PAH pollution following the priority order: traffic > coal > petroleum > biomass, to reduce the content and risk of PAHs in the YRE.

Potentially toxic metals in seawater, sediment and seaweeds: bioaccumulation, ecological and human health risk assessment

This study assesses the bioaccumulation, ecological, and health risks associated with potentially toxic metals (PTMs), including Pb, Hg, Cd, As, and Cr in Hare Island, Thoothukudi. The results revealed that the concentration of PTMs in sediment, seawater, and S. wightii ranged from 0.095 to 2.81 mg kg-1, 0.017 to 1.515 mg L-1, and 0.076 to 5.713 mg kg-1, respectively. The highest concentrations of PTMs were found in the S. wightii compared to seawater and sediment. The high bioaccumulation of Hg and As in S. wightii suggests that it can be used as a bioindicator for these elements in this region. The ecological risk indices, which include individual, complex, biological, and ecological pollution indices, suggest that Hare Island had moderate contamination with Hg and Cd. However, there are no human health risks associated with PTMs. This study examines the current ecological and health risks associated with PTMs and emphasizes the importance of regular monitoring.

Source-based health risk assessment of heavy metal contamination in soil: a case study from a polymetallic mining region in Southeastern Hubei, Central China

To conduct a precise health risk assessment of heavy metals (HMs) in soil, it is imperative to ascertain the primary sources of potential health risks. In this study, we conducted comprehensive measurements of HMs, specifically focusing on the accumulation of Cu, Cd, Sb, Zn, and Pb in local soil, which may pose threats to environmental quality. To achieve our objective, we employed a method that combines positive matrix factorization with a health risk assessment model to quantify the health risks associated with specific sources. The results obtained from the geo-accumulation index indicate that the majority of HMs found in the local soil are influenced by anthropogenic activities. Among these sources, local industrial-related activities contributed the largest proportion of HMs to the soil at 34.7%, followed by natural sources at 28.7%, mining and metallurgy-related activities at 28.2%, and traffic-related activities at 8.40%. Although the non-carcinogenic and carcinogenic risks associated with individual HMs were found to be below safety thresholds, the cumulative health risks stemming from total HMs exceeded safety limits for children. Moreover, the unacceptable health risks for children originating from industrial-related activities, natural sources, and mining and metallurgy-related activities were primarily concentrated in proximity to mining sites and industrial areas within the local region. This investigation furnishes valuable insights that can aid governmental authorities in formulating precise control policies to mitigate health threats posed by soils in polymetallic mining areas.

Source apportionment and source specific health risk assessment of HMs and PAHs in soils with an integrated framework in a typical cold agricultural region in China

A new innovative methodology system framework for source apportionment and source-specific risk assessment has been proposed and actively applied to identify the contamination characteristics, oriented sources and health risks associated with contamination levels of Heavy metals (HMs) and Polycyclic Aromatic Hydrocarbons (PAHs) in soils, a typical cold agricultural region in Northeastern China. To achieve this meaningful goal, a large-scale dataset including 1780 top soil samples, 10 HMs and 16 priority PAHs has been organized and collected from a typical study area in China. The total concentrations of the 10 selected HMs in study area range from 0.05 to 2147.40 mg/kg, with an average of 549.25 ± 541.37 mg/kg. The average concentrations of PAHs for (3-6)-rings are 16.60 ± 18.90, 26.40 ± 28.20, 9.51 ± 13.00 and 1.99 ± 5.30 ng/g, respectively. On the base of optimized literature source fingerprints for HM and PAH, a widely used receptor model, positive matrix factorization (PMF) has been applied to apportion the contamination sources HMs and PAHs in soils. Then source-specific health risk of soil HMs and PAHs have been assessed using the probabilistic incremental lifetime cancer risk model incorporated with source apportionment results data. Fertilizer residues/coke oven comprise the primary contamination source contributors of HMs and PAHs with corresponding contributions of 32.23 % and 27.93 % for HMs and 37.94 % for PAHs. Fertilizer/pesticide residues contributes most to the risks of soil HMs (28.8 %), followed by fossil fuel combustion (24.6 %), mining activities (20.2 %), traffic and vehicle emission (16.3 %) and electroplating/dyeing (14.1 %). Meanwhile, the ranking of health risks from the five identified contamination sources of soil PAHs are resident discharge, coal-fired boilers, coke oven emission, gasoline combustion and power plant, with the contribution of 27.1 %, 25.3 %, 17.3 %, 15.5 % and 14.8 %. And relatively, source-specific risk assessment demonstrates fossil fuel and coal combustion contribute the greatest impact to the total risk of HMs and PAHs (61.7 % and 56.1 %), respectively. This study provides a good example of how the source specific health risk assessment can be utilized to reduce the contamination in soils.

Traditional and new proposals for environmental microbial indicators-a review

The continuous increment in world population coupled with the greatest natural resource consumption and waste generation has an enormous impact on the environment. To date, using biological indicators (bioindicators) to evaluate the biological quality of natural environments is very common. Nonetheless, selecting those suitable for each ecosystem or contaminant is one of the most important issues for environmental sciences. Bacteria and helminths are mainly related to fecal contamination, while antibiotic-resistant bacteria, fungi, viruses, and microalgae are organisms used to determine deteriorated ecosystems by diverse contaminants. Nowadays, each bioindicator is used as a specific agent of different contaminant types, but detecting and quantifying these bioindicator microorganisms can be performed from simple microscopy and culture methods up to a complex procedure based on omic sciences. Developing new techniques based on the metabolism and physiological responses of traditional bioindicators is shown in a fast environmental sensitivity analysis. Therefore, the present review focuses on analyzing different bioindicators to facilitate developing suitable monitoring environmental systems according to different pollutant agents. The traditional and new methods proposed to detect and quantify different bioindicators are also discussed. Their vital role is considered in implementing efficient ecosystem bioprospection, restoration, and conservation strategies directed to natural resource management.

Distribution, sources, and risk analysis of heavy metals in sediments of Xiaoqing River basin, Shandong province, China

The accumulation of heavy metals in river sediment poses a major threat to ecological safety. The Xiaoqing River originates in western Jinan, with higher population density and per capita gross domestic product (GDP) in its basin compared to the Shandong province average. This study analyzed the spatial characteristics, ecological risk, human health risk, and contamination sources of heavy metals by collecting sediment samples from Xiaoqing River. We use the methods such as geo-accumulation index (Igeo), ecological risk assessment based on the interval number sorting method, and health risk assessment to evaluate the risk of heavy metals in sediments. The research finding suggests heavy metals including Pb, As, Ni, and Cr are low ecological risks, while Hg and Cd have reached high and extreme ecological risks. Correlation analysis and principal component analysis were used to analyze the correlation and sources of different heavy metals. The six heavy metals were categorized into three groups. Factor 1, comprising Hg, Cr, and Pb, was identified as a mixed source with a contribution rate of 37.76%. Factor 2 is an agricultural source and comprises Ni, Cd, and As with a contribution rate of 27.05%. Factor 3 includes Pb and Ni contributing to 15.30% as a natural source. This study offers valuable insights for the prevention of heavy metal pollution, as well as promoting sustainable urban development.

Spatial and temporal distribution of heavy metals pollution and risk indices in surface sediments of Gomal Zam Dam Basin, Pakistan

Sediments were considered a sink and potential source of heavy metals in the aquatic system. For this purpose, the present study examined surface sediments for spatial and temporal variation of heavy metals pollution and risk indices in the Gomal Zam Dam Basin (GZDB), Pakistan. Sediment samples (n = 20) were collected from the GZDB, i.e., Gomal Zam Dam, its inlets, and outlets in the winter and summer seasons of 2020, and examined for heavy metals such as zinc (Zn), nickel (Ni), manganese (Mn), lead (Pb), chromium (Cr), copper (Cu), iron (Fe), and cobalt (Co) concentrations. Among GZDB, results showed that the Zhob River Inlet had a higher levels of heavy metals in both seasons. The results revealed that pollution load index values were < 1, observing no pollution in the aquatic system. The risk indices values revealed that sampling sites showed no or very low risk during the summer, 84% of samples showed no or very low risk during the winter, and the rest noted with reasonable risks. Winter season showed higher average values of contamination and risk indices than summer. Statistical analyses revealed that the heavy metals contaminations were mainly due to geogenic sources of rock weathering and ore deposits, with minor contributions from anthropic activities. This study recommends regular monitoring of temporal studies on heavy metals contamination in the water of the GZDB.

Source-oriented ecological and resistome risks associated with geochemical enrichment of heavy metals in river sediments

Heavy metals (HMs) pose ecological and resistome risks to aquatic systems. To efficiently develop targeted risk mitigation strategies, apportioning HM sources and assessing their source-oriented risks are essential. Although many studies have reported risk assessment and source apportionment of HMs, yet few have explored source-specific ecological and resistome risks associated with geochemical enrichment of HMs in aquatic environments. Therefore, this study proposes an integrated technological framework to characterize source-oriented ecological and resistome risks in the sediments of a plain river in China. Several geochemical tools quantitatively showed Cd and Hg had the highest pollution levels in the environment, with 19.7 and 7.5 times higher than their background values, respectively. Positive matrix factorization (PMF) and Unmix were comparatively used to apportion sources of HMs. Essentially, the two models were complementary and identified similar sources including industrial discharges, agricultural activities, atmospheric deposition and natural background, with contributions of 32.3-37.0%, 8.0-9.0%, 12.1-15.9% and 42.8-43.0%, respectively. To analyze source-specific ecological risks, the apportionment results were integratively incorporated into a modified ecological risk index. The results showed anthropogenic sources were the most significant contributors to the ecological risks. Particularly, industrial discharges majorly contributed high- (44%) and extremely high (52%) ecological risk for Cd, while agricultural activities posed a greater percentage of considerable-(36%) and high- (46%) ecological risk for Hg. Furthermore, the high-throughput sequencing metagenomic analysis identified abundant and diverse antibiotic resistance genes (ARGs), including some carbapenem-resistance genes and emerging genes such as mcr-type in the river sediments. Network and statistical analyses displayed significant correlations between ARGs and geochemical enrichment of HMs (ρ > 0.8; P-value <0.01), indicating their important impacts on resistome risks in the environment. This study provides useful insights into risk prevention and pollution control of HMs, and the framework can be made applicable to other rivers facing environmental challenges worldwide.

A review on toxic metal pollution and source-oriented risk apportionment in road dust of a highly polluted megacity in Bangladesh

Heavy metal enrichment in road dust has resulted from intensive anthropogenic activity, particularly urbanization, industrial activities and traffic emission, posing a hazard to urban ecosystems and human health. To promote optimal road dust management in urban environments, it is necessary to assess the possible ecological and health impact of toxic elements in road dust. In a heavily populated megacity like Dhaka, Bangladesh, large-scale risk assessments of contamination in road dust with heavy metals are limited. The present study aims at presenting a concentration of twenty-five metals in road dust (Na, K, Cs, Rb, Mg, Ca, Sr, Ba, Al, Zn, Cd, Pb, As, Sb, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zr and W) in Dhaka megacity. We used a critical source-based positive matrix factorization model, source-oriented potential ecological risks and health risks. Out of the studied metals, Na, Ca, Zn, Cd, Cu, Zr and W exceeded the shale value. About 73%, 48%, 29% and 32% of sampling sites showed a higher level of pollution based on PLI, NIPI, PER and NIRI, respectively. PMF model identified that Cd (85.3%), Cr (62.4%), Ni (58.2%), Zn (81.8%) and Mn (65.9%) in road dust were primarily attributed to traffic emission, fuel combustion, metal processing, transport sources and natural sources, respectively. Fuel combustion and metal processing posed considerable and high risks based on modified potential ecological risk and NIRI. Based on health hazards, traffic emission posed a high cancer risk in adult males (29%), whereas transport sources contributed to females (21%) and children (23%).

Occurrence, sources and risk of heavy metals in soil from a typical antimony mining area in Guizhou Province, China

Antimony mining activities can result in serious contamination of soil by heavy metals, which represents a risk to human health. In this study, the contamination and sources of 14 heavy metals, and their risks to both ecosystem and public health from these metals at an antimony mining site in Guizhou Province in China were explored. The results showed that the mean concentrations of Hg, Cu, As, Se, Cd, Sn, Sb and Pb were 3.73, 2.49, 13.99, 38.32, 1.11, 1.61, 305.33, 1.59 times than their local background levels. Sb, Se, As and Hg presented the relatively heavy pollution, wherein Sb (EI = 2137.34 > 320), Hg (EI = 150.26 > 80) and As (EI = 139.92 > 80) also posed the strong ecological risk. The sources identification illustrated Hg, Pb, As, Bi, Cr, Sb, Cd and Zn were attributed to industrial activities, Ni, Co, Au and Cu (p < 0.01) were derived from a combination of a lithogeny origin and anthropogenic source, whereas Se was of natural origin. Health risk assessment demonstrated that Ni, Cr and As presented both the unacceptable noncarcinogenic and carcinogenic risk, and Sb (HI = 1.44E+03) and Cd (HI = 2.91E+00) posed unacceptable noncarcinogenic risk to the local resident. Furthermore, children in the 1-6 age group (HI = 7.83E+02) were more sensitive to noncarcinogenic risk, and the 6-18 age group (CRI = 2.39E-02) as more prone to carcinogenic risk. The dermal contact was the predominant exposure pathway of noncarcinogenic and carcinogenic risks with a contribution rate of over 97% for all age groups. Overall, this research provided the comprehensive information on heavy metals in an antimony mining sites, and the related heavy metals should be paid attention for ensuring soil safety and protecting local people's health.

Application of Monte Carlo simulation for carcinogenic and non-carcinogenic risks assessment through multi-exposure pathways of heavy metals of river water and sediment, India

Heavy metal contamination has severe detrimental impacts on the entire river ecosystem's quality and causes potential risks to human health. An integrated approach comprising deterministic and probabilistic (Monte Carlo simulation) models with sensitivity analysis was adopted to determine heavy metals' chronic daily intake (CDI) and their associated health risks from the riverine ecosystem. Both carcinogenic and non-carcinogenic risks of water and sediment were estimated through multi-exposure pathways. The analytical results indicated that the concentration patterns of heavy metals in sediment (Fe > Mn > Sr > Zn > Cr > Cu > Cd) were slightly different and higher than in water (Fe > Zn > Cr > Sr > Mn > Cu > Cd). The potential carcinogenic risks of Cr and Cd in sediment (5.06E-02, 5.98E-04) were significantly (p < 0.05) higher than in water (9.08E-04, 8.97E-05). Moreover, 95th percentile values of total cancer risk (TCR) for sediment (1.80E-02, 3.37E-02) were about 22 and 143 times higher than those of water (8.10E-04, 2.36E-04) for adults and children, respectively. The analysis of non-carcinogenic risk revealed a significantly higher overall hazard index (OHI) for both sediment (adults: 1.26E+02, children: 1.11E+03) and water (adults: 3.26E+00, children: 9.85E+00) than the USEPA guidelines (OHI ≤ 1). The sensitivity analysis identified that the concentration of heavy metals was the most influencing input factor in health risk assessment. Based on the reasonable maximum exposure estimate (RME), the study will be advantageous for researchers, scientists, policymakers, and regulatory authorities to predict and manage human health risks.

New insight into the geochemical mechanism and behavior of heavy metals in soil and dust fall of a typical copper smelter

The desorption mechanism of heavy metals (HMs) in soil around the mining region are complex and affected by multiple pollution sources, including sewage discharge and atmospheric deposition. Meanwhile, pollution sources would change soil physical and chemical properties (mineralogy and organic matter), thus affecting the bioavailability of HMs. This study aimed to investigate the pollution source of HMs (Cd, Co, Cu, Cr, Mn, Ni, Pb, and Zn) in soil near mining, and further evaluate influence mechanism of dust fall on HMs pollution in soil by desorption dynamics processes and pH-dependence leaching test. Result presented that dust fall is the primary pollution source to HMs accumulation in soil. Additionally, the result of mineralogical analysis in dust fall revealed that quartz, kaolinite, calcite, chalcopyrite, and magnetite are the major mineralogical phases by XRD and SEM-EDS. Meanwhile, the abundance of kaolinite and calcite in dust fall is higher than in soil, which is the primary reason of higher acid-base buffer capacity of dust fall. Correspondingly, the weakened or disappeared of hydroxyl after the adding acid extraction (0-0.4 mmol· g-1) demonstrated that hydroxyl is the main participants of HMs absorption in soil and dust fall. These combined findings suggested that atmospheric deposition not only increases the pollution loading of HMs in soil, but also changes the mineral phase composition of soil, which would increase the adsorption capacity and bioavailability of HMs in soil. This is very remarkable that heavy metals in soil influenced by dust fall pollution could be released preferentially when soil pH is changed. The present results of this study would provide efficient and scientific targeted strategies for pollution control of HMs in soil near mining areas.

Metal-mining-induced sediment pollution presents a potential ecological risk and threat to human health across China: A meta-analysis

Aquatic sediment polluted by potentially toxic elements (PTEs) from mining activities represents a potential health "time bomb" for humans and the local ecology, but the integrated analysis of pollution and hazards of PTEs in sediment around typical metal mines in China is limited. Presently, the associated pollution status, spatial distribution, and ecological and health hazards of Cd, Cu, Zn, Pb, Cr, and As were investigated through index evaluation, spatial analysis, health risk assessment models, and Monte Carlo simulation. Overall, the sediment exhibited varying degrees of PTE contamination; notably, the level of Cd was 104.85 times higher than its background value, and it became the most enriched element in the surveyed sediment, followed in descending order by Cu, As, Zn, Pb, and Cr. Nationally, over 64.5% of metal-mining-affected sediment presented a very high ecological risk, contributed mostly by Cd (43.2%-98.7%) followed by As, Pb, and Cu; the risk contributed by both Cr and Zn was found to be negligible. The adverse health risk posed to children by most sediment was 1.72 and 6.46 times higher than that posed to adults for cancerous and noncancerous risks, respectively. The potential noncarcinogenic risks were mainly caused by As, which contributed over 78.9% of the Hazard Index values, then followed by Pb (>9.3%). For both children and adults, the carcinogenic risk of PTEs decreased in the following order: As > Cd > Cr > Pb. The investigated sediment was found seriously affected by nearby metal mines, especially those in regions with long-term and large-scale nonferrous-metal-mining activities. This study could provide a reference for policymakers to develop control strategies for PTE pollution in sediment around mining areas.

Diagnostic strategy for the combined effects of microplastics and potentially toxic elements on microbial communities in catchment scale

Combined effects of potentially toxic materials (PTMs) released from production activities on microbial communities in environmental flimsy area are poorly recognised. Microplastics (MPs) and potentially toxic elements (PTEs) were investigated in soils and river sediments in a headwater catchment from the Qinghai-Tibet Plateau. Their co-effects on microbial communities and the controlling factors affecting communities were further explored. Results showed that MPs and PTEs significantly accumulated in soils and sediments. Among which fragment-shaped MPs and copper (Cu) dominated, with mean contents of 1.11 × 10⁴ and 1.81 × 10⁴ items kg^-1 and 13.80 and 7.33 mg kg^-1 in soils and sediments, respectively. Distribution index (0.54) suggested that fiber-shaped MPs preferred to transport into rivers and deposited in sediments. The film mulching contributed significantly to the occurrence of fragment-shaped MPs, while Cu may be derived from industrial wastewater. The antagonistic effect between fiber-shaped MPs and zinc (Zn) on soil microbial structure was found based on their obtuse angle in canonical correlation analysis. While the synergistic effect between total phosphorus (TP) and Cu on diversity was detected by interaction detector model (q(TP ∩ Cu) >q(TP) >q(Cu), p < 0.05). Soil TP and Cu were identified as controlling factors influencing diversity through random forest model and factor detector (q(TP) = 0.49, q(Cu) = 0.36, p < 0.05), which may be related to direct nutrient supply and microbial resistance, respectively. The negative effects of MPs on structure might be counteracted by increasing Zn content, while the co-existence of TP and Cu further increased diversity. A diagnostic framework, which involves background data collection, sampling analysis, characterisation and relationship investigation, was proposed to explore the co-effects of complex pollution and factors on communities. This study may provide strategies to mitigate the negative effects on microorganisms in the environment.

A PMF-SSD based approach for the source apportionment and source-specific ecological risk assessment of Le'an river in Jiangxi Province, China

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated.

Evaluation of heavy metals in water and sediments, pollution, and risk indices of Naltar Lakes, Pakistan

This study examined the physicochemical parameters of water and sediments in the Naltar Lakes, northern Pakistan. Water and sediments were sampled and analyzed for physicochemical parameters. Heavy metals such as iron (Fe, 11% and 12%), nickel (Ni, 100% and 88%), chromium (Cr, 22% and 12%), and arsenic (As, 0% and 12%) of sampling sites had surpassed the threshold of drinking water set by world health organization (WHO) in the Naltar Lake I (Naltar I) and Naltar Lake II (Naltar II), respectively. Water quality parameters were evaluated for the drinking and irrigation water quality indices (WQI). Drinking WQI values were found within the excellent category for Naltar I and Naltar II, except for the 6% of sampling sites observed in the good category. Toxic parameter concentrations were used for the risk indices, which revealed the highest average daily dose (ADD) values of 138 µg/kg-day and hazard quotient (HQ) 1.8 for children through nitrate (NO₃) and As consumption in drinking water from the Naltar I and Naltar II, respectively. Water of the Naltar Lakes were characterized by rock weathering dominance. Heavy metal concentrations of sediments showed a moderate level of contamination that poses a low risk to the Naltar Lake ecosystem.

Source-oriented ecological risk assessment of heavy metals in sediments of West Taihu Lake, China

The geographical location of West Taihu Lake determines that it is the entrance of the whole Taihu Lake, and the intensive industries around it pose a great threat to the ecology of Taihu Lake. We innovatively combined Pb isotope ratio analysis with ecological risk assessment index to quantify the source-oriented ecological risk of heavy metals (HMs) in the sediments of West Taihu Lake. In this study, the representative HMs Zn, Pb, Cr, and Cd in the surface (0-2 cm) sediments of West Tai Lake were determined, and the ecological risk assessment of HM sources was carried out based on the Pb isotope ratio and ecological risk index. The results showed that HMs were significantly enriched in the south and the west of the study area. The average geo-accumulation index (I_geo) of Pb was unpolluted, Cr and Zn were between unpolluted and moderately polluted, and Cd was moderately polluted. The average ecological risk index (E_i) of Pb, Cr, and Zn was low, and only Cd reached a considerable risk (E_Cd = 120.7), which accounted for 89.8% of the comprehensive ecological risk index (RI). However, the RI in the whole study area (RI = 134.4) still indicated low risk. There was a significant correlation between Pb and other HMs (P < 0.05). The IsoSource analysis showed that the order of contribution rate was fossil fuels (48.0%) > industrial sources (35.8%) > natural sources (14.9%) > agricultural sources (1.3%). The HM pollution caused by fossil fuel combustion and industrial activities reaches a moderate ecological risk, whereas natural sources and agricultural sources pose a low risk. Overall, the main sources of HM pollution are anthropogenic, which pose moderate ecological risk to the study area and should be paid more attention to.

Bayesian-Based Approaches to Exploring the Long-Term Alteration in Trace Metals of Surface Water and Its Driving Forces

Trace metal pollution poses a serious threat to the aquatic ecosystem. Therefore, characterizing the long-term environmental behavior of trace metals and their driving forces is essential for guiding water quality management. Based on a long-term data set from 1990 to 2019, this study systematically conducted the spatiotemporal trend assessment, influential factor analysis, and source apportionment of trace elements in the rivers of the German Elbe River basin. Results show that the mean concentrations of the given elements in the last 30 years were found in the order of Fe (1179.5 ± 1221 μg·L^-1) ≫ Mn (209.6 ± 181.7 μg·L^-1) ≫ Zn (52.5 ± 166.2 μg·L^-1) ≫ Cu (5.3 ± 5.5 μg·L^-1) > Ni (4.4 ± 8.3 μg·L^-1) > Pb (3.3 ± 4.4 μg·L^-1) > As (2.9 ± 2.3 μg·L^-1) > Cr (1.8 ± 2.4 μg·L^-1) ≫ Cd (0.3 ± 1.1 μg·L^-1) > Hg (0.05 ± 0.12 μg·L^-1). Wavelet analyses show that river flow regimes and flooding dominated the periodic variations in metal pollution. Bayesian network suggests that the hydrochemical factors (i.e., TOC, TP, TN, pH, and EC) chemically influenced the metal mobility between water and sediments. Furthermore, the source apportionment computed by the Bayesian multivariate receptor model shows that the given element contamination was typically attributed to the geogenic sources (17.5, 95% confidence interval: 13.1-17.6%), urban and industrial sources (22.1, 18.0-27.2%), arable soil erosion (24.2, 16.4-31.5%), and historical anthropogenic activities (35.2, 32.8-43.3%). The results provided herein reveal that both the hydrochemical influence on metal mobility and the chronic disturbance from anthropogenic activities caused the long-term variation in trace metal pollution.

Impacts of the Residual Trace Metals of Aquaculture in Net Cages on the Quality of Sediment

Anthropogenic pollution by trace metals in aquatic environments in semiarid zones is a critical area of investigation. The objective of this study was to investigate the concentration and spatial distribution of trace metals in surface sediments in the Rosário reservoir, which is affected by the intensive aquaculture of Tilápia-do-Nilo (Oreochromis niloticus). Sediment samples were collected in three different areas, postculture (PCTV), cultivation (CTV) and control (CTRL) in the dry season in 2019. The granulometric composition, organic matter and concentrations of Fe, Mn, Zn, Cu, Cr, Cd, Pb and Ni metals were determined. Multivariate statistics were used. Geochemical and ecotoxicological indices and a comparison with sediment quality guidelines (SQG) were used. The sediment was characterized by silty clay loam with an average organic matter of 18.76 ± 4.27. The analytical merit figures demonstrated accuracy (metal recoveries in certified standards) between 89 to 99% and high precision (RSD < 5%). The concentration ranges for the metals were Fe: 0.11-0.85 (%), Mn: 14.46-86.91, Zn: 2.6-220.56, Cu: 26.89-98.75, Cr: 60.18-76.06, Cd: 0.38-0.59, Pb: 18.13-43.13, and Ni: 34.4-46.75, all in (mg/kg^-1). The highest concentration values were found in the CTV areas (Fe: 40 ± 0.22, Mn: 66.48 ± 19.11, Zn: 114.83 ± 59.75 and Cr: 70.85 ± 2.62) and PCTV (Cd: 0.53 ± 0.04, Cu: 71.83 ± 21.20, Pb: 33.71 ± 4.34 and Ni: 44.60 ± 1.79). Pearson's correlation, hierarchical cluster analysis and principal component analysis confirmed the influence of fish farming on metals. Only Ni presented concentration values higher than the reference value established in the SQG. Thus, considering the probable geochemical and ecotoxicological effects, they comprise the two lowest levels of impact.

Multi-element features and trace metal sources of road sediment from a mega heavy industrial city in North China

As the primary carrier of harmful elements, road sediment poses severe hazards to human health and ecological environment, especially in megacities. Based on the industrial cities in North China, this research focused on the multi-element features and the pollution levels, sources, and spatial distributions of trace metals in road sediment of Shijiazhuang. The mean levels of P (928.4 mg kg^-1), S (1446.2 mg kg^-1), Cl (783.9 mg kg^-1), Br (5.3 mg kg^-1), Na₂O (2.0%), CaO (9.9%), Co (36.0 mg kg^-1), Pb (38.0 mg kg^-1), Cu (34.7 mg g^-1), Zn (149.1 mg kg^-1), Ba (518.1 mg kg^-1), and Sr (224.9 mg kg^-1) in road sediment were greater than their soil background values. Trace metals in most samples was moderately (75%) and heavily contaminated (15.6%). The industrial areas, congested roads, and residential areas in the northeast, middle and south of Shijiazhuang are the hotspots of trace metals pollution. A comprehensive analysis of trace metals sources indicated that Ni, V, Ga, Rb, Y, Sc, La, Ce, Zr, and Hf were mainly from natural source, which contributed to 34.2% of the total trace metals concentrations. Cu, Pb, Zn, Cr, Ba, Sr, and Mn primarily originated from mixed source, which accounted for 46.5%. Co principally came from building source, which accounted for 19.3%. This study shows that industrial discharges, construction dust and traffic emissions are the primary anthropogenic sources of trace metals in road sediment in the study area.

Understanding the Heavy Metal Pollution Pattern in Sediments of a Typical Small- and Medium-Sized Reservoir in China

Heavy metal pollution in sediments is a common environmental issue in small- and medium-sized reservoirs not only in China but also worldwide; however, few interpretations of the pollution pattern exist. Based on the analyses of accumulation characteristics, ecological risks, and source apportionments of eight heavy metals (As, Cd, Cr, Cu, Hg, Pb, Ni, and Zn) in sediments, we derived a paradigm to describe the pollution pattern of heavy metals in sediments of a typical small- and medium-sized Tongjiqiao Reservoir. The results showed high levels of Cd, Hg, and As pollutants in the surface and upper sediment layers of the pre-dam area. Additionally, As, Cd, Hg, and Pb pollutants peaked in the middle layers of the inflow area, indicating a high ecological risk in these areas. The positive matrix factorization results implied that industrial, agricultural, and transportation activities were the main sources of heavy metals. The heavy metal pollution pattern exhibited three distinct stages: low contamination, rapid pollution, and pollution control. This pattern explains the heavy metal pollution process in the sediments and will provide scientific guidance for realizing the green and sustainable operation and development of the reservoir.

Source apportionment of soil heavy metals: A new quantitative framework coupling receptor model and stable isotopic ratios

Tracing the source of heavy metals in soils is crucial for reversing the worrisome situation of heavy metal contamination. In this study, the origins of heavy metal pollution in soil were examined in a primary electronic waste treatment and disposal hub in China, using a synergistic source apportionment framework consisting of the positive matrix factorization (PMF) model and the Bayesian stable-isotope analysis mixing model (MixSIAR). Industrial activity is significant to heavy metal contamination in both industrial park and farmland soils, however, the contribution varied through PMF model (industrial park, 64.2%; farmland, 35.6%). In the industrial park, Pb was identified as the major pollutant in the soils, and the local children suffered from noncarcinogenic risks. Moreover, the contribution of Pb contamination sources were allocated more accurately (electronic waste dismantling, 25.1%; industrial production, 23.7%; vehicle exhaust from leaded gasoline, 9.1%; vehicle exhaust from unleaded gasoline, 20.2%; natural process, 21.9%) using MixSIAR for the first time. The main soil contaminants in surrounding farmland were Cd, Cu, and Zn. The variations in heavy metal pollution sources in soils were found to be associated with local policies and regulations, such as the phasing out of leaded gasoline and the conversion of industrial park from electronic waste demolition switched to production and storage. The identification of the source of heavy metals in soil will support targeted reduction of the associated emissions, which can immediately help alleviating soil contamination and control human health risks.

Assessing the effects of nickel on, e.g., Medicago sativa L. nodules using multidisciplinary approach

Industrial wastes and fertilizers can introduce excessive levels of nickel (Ni) into the environment, potentially causing threats to plants, animals, as well as human beings. However, the number of studies on the effects of Ni toxicity on nodules is fairly limited. To address this issue, the effects of increasing Ni concentration on alfalfa nodules were assessed at chemical, biochemical, and transcriptomic levels. For this purpose, plants were grown in soils supplied with Ni (control, 0 mg/kg; C1, 50 mg/kg; C2, 150 mg/kg; C3, 250 mg/kg; and C4, 500 mg/kg) for 90 days. Ni loads in leaves, roots, and nodules were monitored after the exposure period. A set of biochemical biomarkers of oxidative stress was determined in nodules including antioxidants and metal homeostasis as well as lipid peroxidation. Gene expression levels of the main targets involved in oxidative stress and metal homeostasis were assessed. Our data indicated a high concentration of Ni in leaves, roots, and nodules where values reached 25.64 ± 3.04 mg/kg, 83.23 ± 5.16 mg/kg, and 125.71 ± 4.53 mg/kg in dry weight, respectively. Moreover, a significant increase in nodule biomass was observed in plants exposed to C4 in comparison to control treatment and percentage increased by 63%. Then, lipid peroxidation increased with a rate of 95% in nodules exposed to C4. Enzymatic activities were enhanced remarkably, suggesting the occurrence of oxidative stress, with increased superoxide dismutase (SOD), glutathione reductase (GR), and ascorbate peroxidase (APX). Our results showed also a significant upregulation of SOD, GR and APX genes in nodules. Nodule homoglutathione (HGSH) levels increased with the different Ni concentrations, with a remarkable decrease of glutathione S-transferase (GST) activity and glutathione (GSH) content for the highest Ni concentration with 43% and 52% reduction, respectively. The phytochelatin (PC) and metallothionein (MT) concentrations increased in nodules, which implied the triggering of a cellular protection mechanism for coping with Ni toxicity. The results suggested that Ni promotes a drastic oxidative stress in alfalfa nodules, yet the expression of MT and PC to reduce Ni toxicity could be used as Ni stress bioindicators. Our findings provide new insights into the central role of alfalfa nodules in limiting the harmful effects of soil pollution. Therefore, nodules co-expressing antioxidant enzymes may have high phytoremediation potential.

Source apportionment and risk assessment of metal pollution in natural biofilms and surface water along the Lancang River, China

Herein, surface water and periphytic biofilm samples were collected from 16 sites along the Lancang River, China, to assess the spatial distribution, enrichment factor (EF), potential ecological risk index (RI), and associated source-oriented health risks of heavy metal elements (As, Cd, Co, Cr, Cu, Ni, Pb, V, and Zn) in the samples. Results showed that the levels of heavy metals were significantly lower in the surface water samples than in the biofilm samples (one-way analysis of variance, p < 0.001). Moreover, 37.50 % of the biofilm samples were significantly polluted by these heavy metals with a mean EF of >5. As and V were the highest polluting metals, and the enrichment of Co and Ni were attributed to natural sources. RI assessment results showed a consistent ecological risk of As. Based on principal component analysis with multiple linear regression (PCA-MLR) and positive matrix factorization (PMF) models, the presence of heavy metal ions in the biofilm samples was largely attributed to industrial activities (PCA-MLR: 68.89 %; PMF: 76.39 %), followed by a mixed source of natural and agricultural activities (PCA-MLR: 18.12 %; PMF: 13.56 %), and traffic emissions (PCA-MLR: 12.99 %; PMF: 10.05 %). Both carcinogenic and noncarcinogenic risks for adults were negligible even though adults tended to be exposed to greater risk through ingestion. Source-specific risk evaluations indicated that industrial pollution was the most important source of health risks. Our findings highlight the potential threat of biofilms to the ecological and human health.

Receptor model-oriented sources and risks evaluation of metals in sediments of an industrial affected riverine system in Bangladesh

Toxic metals in river sediments may represent significant ecological concerns, although there has been limited research on the source-oriented ecological hazards of metals in sediments. Surface sediments from an industrial affected Rupsa River were utilized in this study to conduct a complete investigation of toxic metals with source-specific ecological risk assessment. The findings indicated that the average concentration of Ni, Cr, Cd, Zn, As, Cu, Mn and Pb were 50.60 ± 10.97, 53.41 ± 7.76, 3.25 ± 1.73, 147.76 ± 36.78, 6.41 ± 1.85, 59.78 ± 17.77, 832.43 ± 71.56 and 25.64 ± 7.98 mg/kg, respectively and Cd, Ni, Cu, Pb and Zn concentration were higher than average shale value. Based on sediment quality guidelines, the mean effective range median (ERM) quotient (1.29) and Mean probable effect level (PEL) quotient (2.18) showed medium-high contamination in sediment. Ecological indexes like toxic risk index (20.73), Nemerow integrated risk index (427.59) and potential ecological risk index (610.66) posed very high sediment pollution. The absolute principle component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) model indicated that Zn (64.21%), Cd (51.58%), Cu (67.32%) and Ni (58.49%) in APCS-MLR model whereas Zn (49.5%), Cd (52.7%), Cu (57.4%) and Ni (44.6%) in PMF model were derived from traffic emission, agricultural activities, industrial source and mixed sources. PMF model-based Nemerow integrated risk index (NIRI) reported that industrial emission posed considerable and high risks for 87.27% and 12.72% of sediment samples. This work will provide a model-based guidelines for identifying and assessing metal sources which would be suitable for mitigating future pollution hazards in Riverine sediments in Bangladesh.