A comprehensive exploration on distribution, risk assessment, and source quantification of heavy metals in the multi-media environment from Shaying River Basin, China

Occurrence, transport and sources of metals and metalloids in the Bangpakong River in the eastern economic corridor area of Thailand

The occurrence of elements in river water is affected by various factors, including mobility, weathering and transport processes and anthropogenic contributions. A total of six water sampling campaigns were conducted from 2021 to 2022 to study the factors affecting the occurrence of twelve elements (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn and Se) in the Bangpakong River. The total concentrations of all the elements were within the levels set by the national surface water quality standard. Comparisons of dissolved elemental concentrations in the study area with the global average for dissolved elemental concentrations in pristine rivers indicated contamination with Al, As, Co, Mn, Zn and Se in the river water. Based on the percentage of each element in particulates to the total concentration, Al (80.6 %), Cr (71.9 %), Cu (69.9 %), Fe (95.6 %), Mn (76.6 %), Pb (74.7 %), and Zn (70.6 %) were mainly transported in the particulate phase in both the dry and wet seasons. However, As (65.5 %), Co (60.3 %), and Se (77.6 %) were mainly transported in the dissolved phase in both seasons. The ratios of the dissolved Se concentration in river water to the Se concentration in the Earth's crust indicated significant and high mobility, especially in downstream sites, likely due to Se leaching from alluvial sediments. Seawater intrusion is likely the cause of As and Zn contamination in the dry season. Weathering of rocks and soils likely causes Al, Co, and Mn contamination in the wet season. The anthropogenic sources of contamination include the discharge of Mn and Zn from fertilizers in agriculture and the use of formulated feed in aquaculture. Approximately 52.98, 25.23, 5.68 and 0.63 tons of Fe, Al, Mn and Zn, respectively, are estimated to be transported from the river into the Gulf of Thailand each year.

Hydrochemical characterization and assessment of health risks of trace elements in the Huai River Basin of China

Basin water pollution is a global problem, especially in the densely populated areas. The Huai River Basin (abbreviated as HRB), including the Huai River system and the Yishu River system, is the sixth-largest and most densely populated watershed in China. However, there is a lack of comprehensive studies of river and well water throughout the Huai River basin, including hydrochemistry characterization and assessment of health risks. This study investigated water quality and pollution sources of river and well water in the HRB based on the hydrochemistry analysis and different water quality indices. The water body in the HRB showed weak alkalinity (pH = 8.4 ± 0.7) and had high TDS values (TDS = 339 ± 186 mg/L) with water types of HCO3-Ca-Mg and SO4-Cl-Ca-Mg in the Huai River system, and SO4-Cl-Ca-Mg in the Yishu River system. Atmospheric input and evaporation had less impact on hydrochemistry. Evaporite dissolution and carbonate weathering had a greater impact on hydrochemistry. Carbonate precipitation and cation exchange also influenced the dissolved solutes, especially Ca2+ and Na+. Samples had low to medium salinity hazards and sodium absorption ratios and were suitable for irrigation. For drinking purposes, samples were fresh water and have good or excellent according to the Water Quality Index (WQI). Land use types influenced water quality with the worst river water quality from cropland. Combining different assessment indices, the water quality of the Yishu River system performed better than the Huai River system. Absolute principal component analysis-multiple linear regression and the positive matrix factorization models identified the main pollutants as As, Ba, Cr, Ni, and Mn, with natural sources of As, Ba, and Ni and anthropogenic inputs of Cr, and Mn. Although the water quality of the HRB has improved in recent years, high potential risk from As, Cr, Mn, Ba, and Ni should be noted. This study provided vital information for basin hydrochemistry analysis and water quality assessment.

Health risk assessment and potential sources of metals in riparian soils of the Wujiang River, China

In order to understand the pollution status of metals in the riparian soils along the Wujiang River, 26 sampling sites in the mainstream and tributary streams were selected for investigation. The geo-accumulation index (Igeo), Nemerow integrated pollution index, and potential ecological risk index were applied to evaluate the contamination status and ecological risks of metals. Results revealed that the average concentrations of As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn were 12.20, 0.51, 84.01, 57.42, 922.57, 38.37, 38.06, and 127.82 mg/kg, respectively. The metal contamination degree and ecological risks in the upper reaches were significantly higher than those in the middle and lower reaches of the Wujiang River. Cd was the dominant contamination metal. Significant non-carcinogenic and carcinogenic risks of metals were found in children based on the hazard index and carcinogenic risk. As was the main non-carcinogenic and carcinogenic pollutant metal in both adults and children. According to principal component analysis, hierarchical clustering analysis, and absolute principal component scores-multiple linear regression, anthropogenic sources (mining and agricultural activities) contributed most to Zn, Pb, Cr, Cd, Cu, and Ni, with contribution rates of 89.14, 82.32, 74.46, 72.12, 68.52, and 61.02%, respectively. Natural sources contributed most to Mn, with a contribution rate of 83.07%. Unidentified sources contributed most to As, with a contribution rate of 47.27%.

Assessment of metal pollution and effects of physicochemical factors on soil microbial communities around a landfill

The physicochemical properties, chemical fractions of six metals (Cu, Zn, Pb, Cd, Cr, and Mn), and microbial communities of soil around a typical sanitary landfill were analyzed. The results indicate that soils around the landfill were from neutral to weak alkalinity. The contents of organic matter (OM), total nitrogen (TN), total phosphorous (TP), and activities of catalase, cellulase, and urease were significantly higher in landfill soils than those in background soils. Negative correlations were found between pH and metals. Cr was the dominant metal. Cu, Pb, Cr, and Mn were accumulated in the nearby farmland soils. Cd had the highest percentage of exchangeable fraction (33.7%-51.8%) in landfill and farmland soils, suggesting a high bioavailability to the soil environment affected by the landfill. Pb, Cr, and Mn existed mostly in oxidable fraction, and Cu and Zn were dominant in residual fraction. There was a low risk of soil metals around the landfill based on the RI values, while according to RAC classification, Cd had high to very high environmental risk. The MisSeq sequencing results showed that Actinobacteria, Proteobacteria, Chloroflexi, and Acidobacteria were the dominant phyla of bacteria, and the most abundant phylum of fungi was Ascomycota. The NMDS analysis revealed that the landfill could influence soil fungal communities more intensely than bacterial communities. TN, cellulase, and bioavailable metals (Pb-Bio and Cr-Bio) were identified to have main influences on microbial communities. Pb-Bio was the most dominant driving factor for bacterial community structures. For fungi, Pb-Bio was significantly negatively related to Olpidiomycota and Cr-Bio had a significantly negative correlation with Ascomycota. It manifests that bioavailable metals play important roles in assessing environmental risks and microbial community structures of soil around landfill.

Quantitative risk analysis of sediment heavy metals using the positive matrix factorization-based ecological risk index method: a case of the Kuye River, China

Identifying the sources of heavy metals (HMs) in river sediments is crucial to effectively mitigate sediment HM pollution and control its associated ecological risks in coal-mining areas. In this study, ecological risks resulting from different pollution sources were evaluated using an integrated method combining the positive matrix factorization (PMF) and the potential ecological risk index (RI) model. A total of 59 sediment samples were collected from the Kuye River and analyzed for eight HMs (Zn, Cr, Ni, Cu, Pb, As, Cd, and Hg). The obtained results showed that the sediment HM contents were higher than the corresponding soil background values in Shaanxi Province. The average sediment Hg content was 3.42 times higher than the corresponding background value. The PMF results indicated that HMs in the sediments were mainly derived from industrial, traffic, agricultural, and coal-mining sources. The RI values ranged from 26.15 to 483.70. Hg was the major contributor (75%) to the ecological risk in the vicinity of the Yanjiata Industrial Park. According to the PMF-based RI model, coal-mining activities exhibited the strongest impact on the river ecosystem (48.79%), followed, respectively, by traffic (34.41%), industrial (12.70%), and agricultural (4.10%) activities. These results indicated that the major anthropogenic sources contributing to the HM contents in the sediments are not necessarily those posing the greatest ecological risks. The proposed integrated approach in this study was useful in evaluating the ecological risks associated with different anthropogenic sources in the Kuye River, providing valuable suggestions for reducing sediment HM pollution and effectively protecting river ecosystems.

A novel mixture sampling strategy combining latin hypercube sampling with optimized one factor at a time method: A case study on mixtures of antibiotics and pesticides

Global sensitivity analysis in conjunction with quantitative high-throughput screening presents a novel technique for identifying the key components that induce the toxicities of mixtures. However, the mixtures currently designed with this method suffer from unequal frequency sampling, repeated mixtures, and only odd factor levels being considered. Accordingly, we use latin hypercube sampling to generate the starting points of the trajectories to achieve equal frequency sampling and non-repeated mixtures, as well as apply different one factor at a time methods for factors with odd and even levels to achieve suitability for factors with both odd and even levels. This method is called LHS-OAT. LHS-OAT was successfully applied to design 110 equal-frequency and non-repeated mixtures consisting of six antibiotics and four pesticides. It was found that four factors, roxithromycin (A5), tetracycline (A6), dichlorvos (P1), and demeton-S (P3), induce the toxicities of mixtures, and A5 and P1 in the Shaying River Basin have risk quotients ≥ 1. Additionally, we developed the toxicity deviation ratio to correct the risk quotients of interacting mixtures for effective risk assessments. This study provides a rational and effective method for mixture design that accurately identifies the important factors that induce the toxicities of mixtures.

Bacterial heavy metal resistance related to environmental conditions

Contaminated water bodies such as rivers provide reservoirs for bacterial resistance. This field study tested the water quality and the bacterial resistance to heavy metals of Qishan River water pollution. Wastewater discharged to environmental surface waters is a major pathway of heavy metals and heavy metal-resistant bacteria. Contaminated water bodies such as rivers provide reservoirs for bacterial resistance. This field study tested the water quality and bacterial resistance to heavy metals of Qishan River water pollution. Guided by our research hypothesis that an overall increase in downstream heavy metal resistance levels was following an increase in human settlements were eight sites sampled along the Qishan River. These were situated upstream and downstream to the confluence of the Qishan River with the Kaoping River. In the laboratory bacterial heavy metal resistance was bio-assayed by disk diffusion and micro-dilution with six widely used heavy metals. The comparison of bacterial resistance was among Qishan River upstream sites (sites 1-6) and downstream sites (sites 7-9). Multi-drug-resistant bacteria and co-resistance against heavy metals and antibacterials appeared at site 8. This research discusses the correlation between environmental factors, and antibacterial and heavy metal resistance. The results provide stakeholders and authorities responsible for environmental pollution with a reference for risk assessment and management of bacterial resistance.

Source apportionment of heavy metal(loid)s in sediments of a typical karst mountain drinking-water reservoir and the associated risk assessment based on chemical speciations

As important place for water storage and supply, drinking-water reservoirs in karst mountain areas play a key role in ensuring human well-being, and its water quality safety has attracted much attention. Source apportionment and ecological risks of heavy metal(loid)s in sediments of drinking-water reservoir are important for water security, public health, and regional water resources management, especially in karst mountain areas where water resources are scarce. To expound the accumulation, potential ecological risks, and sources of heavy metal(loid)s in a drinking-water reservoir in Northwest Guizhou, China, the surface sediments were collected and analyzed based on the combined use of the geo-accumulation index (Igeo), sequential extraction (BCR), ratios of secondary phase and primary phase (RSP), risk assessment code (RAC), modified potential ecological risk index (MRI), as well as the positive matrix factorization methods. The results indicated that the accumulation of Cd in sediments was obvious, with approximately 61.9% of the samples showing moderate to high accumulation levels, followed by Pb, Cu, Ni, and Zn, whereas the As and Cr were at low levels. A large proportion of BCR-extracted acid extractable and reducible fraction were found in Cd (72.5%) and Pb (40.3%), suggesting high bioavailability. The combined results of RSP, RAC, and MRI showed that Cd was the major pollutant in sediments with high potential ecological risk, while the risk of other elements was low. Source apportionment results of heavy metal(loid)s indicated that Cd (75.76%) and Zn (23.1%) mainly originated from agricultural activities; As (69.82%), Cr (50.05%), Cu (33.47%), and Ni (31.87%) were associated with domestic sources related to residents' lives; Cu (52.36%), Ni (44.57%), Cr (34.33%), As (26.51%), Pb (24.77%), and Zn (23.80%) primarily came from natural geological sources; and Pb (47.56%), Zn (22.46%) and Cr (13.92%) might be introduced by mixed sources of traffic and domestic. The contribution ratios of the four sources were 18.41%, 36.67%, 29.48%, and 15.44%, respectively. Overall, priority control factors for pollution in relation to agricultural sources included Cd, while domestic sources are primarily associated with As. It is crucial to place special emphasis on the impacts of human activities when formulating pollution prevention and control measures. The results of this study can provide valuable reference and insights for water resources management and pollution prevention and control strategies in karst mountainous areas.

High-resolution risk mapping of heavy metals in soil with an integrated static-dynamic interaction model: A case study in an industrial agglomeration area in China

Heavy metal pollution of soils in industrial agglomeration areas is an increasing concern worldwide. In this study, we traced the sources of heavy metal emissions using a positive matrix factorization (PMF) model. Accordingly, we proposed a novel static-dynamic risk interaction model incorporating multiple risk-related factors to quantify the spatial interaction of emission sources and the probability of accumulation of heavy metals on a large scale. This model was further classified using the Jenks optimization technique to predict the spatial distribution of high-risk hotspots. Our results determined four primary emission sources of heavy metals: industrial (35.01 %), natural (28.61 %), agricultural (26.07 %), and traffic (10.31 %) sources. Five levels were classified by the integrated risk coefficient (IRC), namely, from extremely high to extremely low risk. The extremely high- and high-risk hotspots constituting 41.52 % of the total area of the Zhenhai District, with IRC values ranging from 0.221 to 0.413, were mainly generated by multiple sources linked to PMF-based factors. This quantitative evaluation framework can generate a high-resolution spatially distributed pollution risk map at the grid scale (1 km), which can provide a relatively precise basis for policymaking for point-to-point soil pollution management.

Destabilizing Effects of Environmental Stressors on Aquatic Communities and Interaction Networks across a Major River Basin

Human-driven environmental stressors are increasingly threatening species survival and diversity of river systems worldwide. However, it remains unclear how the stressors affect the stability changes across aquatic multiple communities. Here, we used environmental DNA (eDNA) data sets from a human-dominated river in China over 3 years and analyzed the stability changes in multiple communities under persistent anthropogenic stressors, including land use and pollutants. First, we found that persistent stressors significantly reduced multifaceted species diversity (e.g., species richness, Shannon's diversity, and Simpson's diversity) and species stability but increased species synchrony across multiple communities. Second, the structures of interaction networks inferred from an empirical meta-food web were significantly changed under persistent stressors, for example, resulting in decreased network modularity and negative/positive cohesion. Third, piecewise structural equation modeling proved that the persistent stress-induced decline in the stability of multiple communities mainly depended upon diversity-mediated pathways rather than the direct effects of stress per se; specifically, the increase of species synchrony and the decline of interaction network modularity were the main biotic drivers of stability variation. Overall, our study highlights the destabilizing effects of persistent stressors on multiple communities as well as the mechanistic dependencies, mainly through reducing species diversity, increasing species synchrony, and changing interaction networks.

Heavy metal(loid)s contaminations in soils of Pakistan: a review for the evaluation of human and ecological risks assessment and spatial distribution

Heavy metal(loid)s (HM) contaminations in the soil poses threats to the human and ecological community due to their bioaccumulation, toxicity, and persistent nature in the ecosystem. This review was designed to know about the HM contamination in soils, ecological risk, distribution, and potential health risks. Soil HM concentrations published in the last 30 years were collected from Springer, Science Direct, Willey, Mendeley, ResearchGate, Google Scholar, etc. HM concentrations were used for the geo-accumulation index (Igeo), contamination factor, as well as integrated indices such as spatial distribution of ecological risk index. Similarly, the Igeo pattern was observed in Sindh > Baluchistan > Punjab > Khyber Pakhtunkhwa > Gilgit-Baltistan > Islamabad. Moreover, the high ecological risk mean values ranged (160 < ERI < 320) due to cadmium (Cd) was exhibited in the Punjab and Khyber Pakhtunkhwa provinces and Islamabad. Non-carcinogenic risk like hazard quotient was found higher for children (1.59) of Punjab due to arsenic (As) ingestion, whereas the lower risk was observed due to Zn (2.5E-08) for adults of Punjab province via inhalation pathway. Similarly, the health index (HI) from exposure to As (1.61) in soil was higher than the rest of the HM. Moreover, cancerous risk was determined and found in the tolerable range (10^-4-10^-6). This study recommended that HM contaminants in the soil need to be monitored on regular basis, especially in Baluchistan, Gilgit-Baltistan, and Sindh provinces.