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The present study was conducted on the river Yamuna, which passes through Delhi-NCR from Baghpat to Chhainssa, a distance of about 125 km, at six sampling locations to evaluate the concentrations of heavy metals in surface water using heavy metal pollution index (HPI) approach. The river serves both urban-industrial and rural areas in the study area; hence, domestic, industrial, and agricultural wastes are being contributed greatly in the contamination of river water. The Yamuna River is one of the major tributaries of the river Ganga originated in the Himalayas and is flowing through a varied geological terrain. Metals such as iron (Fe), copper (Cu), cobalt (Co), zinc (Zn), lead (Pb), cyanide (CN), nickel (Ni), and chromium (Cr) in selected sites of Yamuna River water were determined by using atomic absorption spectrophotometer. The concentrations of Fe, Cu, Co, Zn, Pb, CN, Ni, and Cr in the river water were found to be in the range of 40–190, 50–120, 4–66, 840–1800, 2–40, 100–600, 88–253, and 35–52 μg/L, respectively. The results show that the maximum heavy metal content was found at sampling site S3 (Nizamuddin) followed by S6 (Chhainssa), S4 (Okhla), S1 (Baghpat), S5 (Manjhawali), and S2 (Pachahira). The heavy metal data was integrated in GIS environment for preparing spatial distribution maps of sampling sites. A scatter plot matrix was created to assess the pattern and interrelationships between heavy metals. The average concentration of heavy metals was recorded high, often exceeding the permissible limits for drinking of surface water prescribed by the Bureau of Indian Standards (BIS) and World Health Organization (WHO). Based on HPI (varies from 98.2 to 555.1), about 85% of the river water was classified as highly polluted; hence, it is not recommended for drinking. Overall, significant variations were observed in concentrations of heavy metals from one location to the other which may be because of toxic industrial effluents and domestic sewage wastes being added to the river water by various anthropogenic activities in the study area. The present work highlights the pollution load of heavy metals in the river Yamuna and also advocates an urgent attention towards minimizing the health risk of people residing not only along the river banks and surrounding regions but also for city population.

Wetlands are recognized as one of the most important natural environments for humans. At the same time, heavy metal pollution has an important impact on wetlands. China's Raoyanghe Wetland is one of the most important natural wild species gene banks in China. Eight heavy metal elements (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in surface layer and deep layer soils were analyzed using statistical-, pollution index-, and Nemerow index-based methods, the Hakanson potential ecological risk index method, and principal component and cluster analyses. The results showed that the maximum concentrations of heavy metals exceeded the background values in the core area and buffer zone of the wetland, but the heavy metal content of the soils was generally low and did not exceed 30%. With the exception of Hg, heavy metal concentrations showed strong spatial differentiation. The differences between the surface layer and deep layer soils of the core area were smaller than in the buffer zone. With the exception of Cd, a clear vertical zonation in the buffer zone soils was observed, showing greater evidence of external influences in this zone than the core. With the exception of partial surface soils, which indicated a safe level of pollution in the core area, all other soils were classified as having a 'mild' level of pollution. Thus, the wetland is moderately polluted, with both the core area and the buffer zone presenting a low level of potential ecological risk. According to the results of the present study, heavy metal contaminants in the wetland soils were found to be derived mainly from the natural sources.

The investigation of chemical composition in hailstones offers valuable insights into cloud physics. Unique characteristics of heavy metals and water‐soluble ions have been detected to provide a comprehensive perspective on their presence and behavior within hailstones. 34 hailstone samples were collected from 12 cities in China between 2016 and 2021. Regional differences in heavy metal concentrations between northern and southern China are influenced by anthropogenic pollution sources. Water‐soluble ions are dominated by distant marine aerosol sources. The most notable distinction is that heavy metals display negligible correlation with PM10, whereas water‐soluble ions exhibit a statistically significant relationship. This suggests that chemical components contribute to hailstone formation through diverse pathways. Water‐soluble ions with hygroscopicity primarily act as cloud condensation nuclei (CCN) to promote the formation of cloud droplets. Heavy metals are barely noticeable when attached to aerosol particles due to random collisions with various hydrometeors. Plain Language Summary The study examines the chemical composition of hailstones to further understand cloud microphysical processes during convective activities. We collected 34 hailstone samples from 12 cities in China between 2016 and 2021 to investigate the presence and behavior of heavy metals and water‐soluble ions. Our findings reveal that the heavy metal content in hailstones is significantly higher in northern China than in the south, primarily owing to local anthropogenic pollution. Water‐soluble ions are predominantly sourced from faraway marine aerosols. These two chemical components contribute to hail formation through different pathways. This distinction is evident from the lack of correlation between heavy metals and PM10, while water‐soluble ions show a significant correlation. Water‐soluble ions with high hygroscopicity promote the formation of cloud droplets by acting as CCN during the nucleation process. Trace heavy metals absorbed onto aerosol particles are transported into hailstones through the impaction scavenging processes. Key Points Significant regional differences in the concentrations of heavy metals in hailstones are observed between northern and southern China Heavy metals found in hailstones originate from local traffic emissions, whereas water‐soluble ions are dominated by distant marine aerosols Heavy metals and water‐soluble ions in hailstones follow distinct transmission paths during cloud formation processes

In India, the rice paddy is cultivated as one or two crops per year using synthetic fertilizers and organic manures. Although the application of agrochemicals enhances the soil's heavy metals, the influence of cultivation patterns on the metal accumulation in rice paddy soil is not documented. Such information could provide a basis for controlling heavy metals in rice paddy soil. Therefore, the investigation was carried out to assess the influence of cultivation patterns on heavy metal accumulation. The study was made during the cultivation and noncultivation periods of single and double cropping patterns. The heavy metals viz . Zn, Cu, Mn, Fe, Ni, Cr, and Pb were analyzed in soil after acid extraction using AAS. The result revealed that, in both cropping patterns, the heavy metals content was high during the noncultivation period compared to cultivation period, and only Cu and Pb showed significant differences between the periods (Single cropping F 1,25  = 7.291, p = 0.012 and F 1,25  = 7.820, p = 0.010; double cropping F 1,25  = 9.242, p = 0.005 and F 1,25  = 7.746, p = 0.010 respectively). Compared to single cropping, Zn, Cu, Mn, and Pb contents were high in double cropping. The Mn, Ni, and Cr content showed significant differences between the cropping pattern (Mn: F 1,55  = 18.20, p = 0.0001; Ni: F 1,55  = 5.764, p = 0.020; Cr: F 1,55  = 4.283, p = 0.043). The study indicates that the difference in the heavy metal content of the rice paddy soils is attributed to managerial and cultivation practices.

With the development of hyperspectral imaging technology, the potential for utilizing hyperspectral images to accurately estimate heavy metal concentrations in regional soil has emerged. Currently, soil heavy metal inversion based on laboratory hyperspectral data has demonstrated a commendable level of accuracy. However, satellite images are susceptible to environmental factors such as atmospheric and soil background, presenting a significant challenge in the accurate estimation of soil heavy metal concentrations. In this study, typical chromium (Cr)-contaminated agricultural land in Shaoguan City, Guangdong Province, China, was taken as the study area. Soil sample collection, Cr content determination, laboratory spectral measurements, and hyperspectral satellite image collection were carried out simultaneously. The Zhuhai-1 hyperspectral satellite image spectra were corrected to match laboratory spectra using the direct standardization (DS) algorithm. Then, the corrected spectra were integrated into an optimal model based on laboratory spectral data and sample Cr content data for regional inversion of soil heavy metal Cr content in agricultural land. The results indicated that the combination of standard normal variate (SNV)+ uninformative variable elimination (UVE)+ support vector regression (SVR) model performed best with laboratory spectral data, achieving a high accuracy with an R2 of 0.97, RMSE of 5.87, MAE of 4.72, and RPD of 4.04. The DS algorithm effectively transformed satellite hyperspectral image data into spectra resembling laboratory measurements, mitigating the impact of environmental factors. Therefore, it can be applied for regional inversion of soil heavy metal content. Overall, the study area exhibited a low-risk level of Cr content in the soil, with the majority of Cr content values falling within the range of 36.21–76.23 mg/kg. Higher concentrations were primarily observed in the southeastern part of the study area. This study can provide useful exploration for the promotion and application of Zhuhai-1 image data in the regional inversion of soil heavy metals.

In order to clarify the effects of long-term coal gangue(CG) dump on the surrounding soil bacterial community structure, we selected the CG dump formed during the mining of Tunlan coal mine in Gujiao city, Shanxi province in China as the study area to conduct a comprehensive study, the experimental design included six distinct zones: control soil area with no impaction (NC), undisturbed control sediment area (NL), atmospheric dry and wet deposition area (MC), upstream (MLS), midstream (MLZ) and downstream (MLX) in the leachate flow area (LFA), Using high-throughput sequencing technology and related software analysis, we obtained the following key findings: The heavy metal contents of Cr and Cd were different significantly in MC and NC (p < 0.05),Cr (90.18 mg·kg-1) in MC was higher than that in NC (65.29 mg·kg-1) (p < 0.05), while Cd (0.09 mg·kg-1) was lower than that in NC (0.14 mg·kg-1) (p < 0.05), and there was no significant differences in Cu, Zn, As and Pb between MC and NC (p > 0.05). All the heavy metal contents in MLS were highest significantly except Cd among NL and LFA. Shannon and Chao1 indices in NC were significantly higher than those in MC (p < 0.05), In LFA, Shannon and Chao1 indices of MLX were the highest, while MLS was significantly lower than NL (p < 0.05). The relative abundance of bacteria more than 40% in MC and NC was Actinomycetes (42.06%−42.38%), and while was Proteobacteria (40.66%−50.77%) in NL and LFA. Bacterial communities in different disturbed areas were significantly correlated with As, Pb, Cu, Cd, TP, SOC and EC in the soil, among which SOC contributed most about 40.1%. Molecular ecological network showed that the interactions among bacterial taxa in MC and LFA were mainly in a positive synergistic development, the bacteria with higher relative abundance may not be the key node in the bacterial molecular ecological network, while bacteria with the lower relative abundance might have been. The bacterial community structure of MC was more complex than NC because of fewer nodes and modules but more connections. The positive connection proportion and modules of bacteria in LFA was higher than that in NL, while the aggregation coefficient decreased. The average path distance (5.09) in MLS was the shortest, indicating the bacteria in MLS were most environmental sensitive to the external environment with rapid community response to disturbances. Our results revealed the changes in the bacterial community and the main environmental driving factors under disturbance of CG dump, this information provides a theoretical basis for ecological environment management.

Heavy-metal pollution has been established to affect ginseng quality. However, this effect is still unknown in ginseng of different ages, emphasizing the need to investigate the effects of heavy metals in soils on ginseng growth. Herein, we determined the content of heavy metals (Cu, Cd, Pb, Hg, and As) in ginseng of different ages (2 to 6-year-old) and the corresponding soil samples. Then, the total ginsenosides content of ginseng and rate-limiting enzyme (HMGR, SQE, CYP450) activity in the synthesis of ginsenosides were assessed. Results from 200 differently-aged Chinese ginseng showed that increased ginsenoside content in 3 to 5-year-old ginseng was paralleled by increased heavy metal element content in ginseng and its soil. The activity of rate-limiting enzymes increased in the first four years of ginseng growth and then exhibited a steady or downward trend. Further analysis suggested that heavy metal elements in soils could directly affect ginsenoside content. Moreover, we found that Cu significantly affected the rate-limiting enzyme CYP450 activity. Further principal component analysis and correlation analysis found that heavy metals could obviously inhibit ginseng growth during the 5th and 6th years. Heavy metal content in soils has huge prospects for predicting ginsenoside, Cu and As content in ginseng. This study provided support for ginseng cultivation, quality research and quality assessment.

Heavy metal pollution in soil and groundwater is difficult to detect in time because of its long-term accumulation. This poses a severe hazard to the ecosystem security in polluted areas. Considering the Tongyang River Basin of the Chaohu Lake water system as the research object, various pollution evaluation methods, Geographic Information System (GIS) source analysis models, adsorption and desorption experiments, and mathematical models were used. Based on the data of the heavy metal content in the soil and river sediments in the study area, regional heavy metal pollution evaluation, spatial distribution characteristics, source identification, and lake loss analysis were conducted to evaluate the current situation of environmental pollution, pollution sources, and migration and transformation of heavy metals in the basin. The results show that the heavy metals in the soil of the basin are mainly distributed from the southwest to the northeast and the island distribution to the east of Tongyang Town. The Cd, Cu, Zn, and Pb concentrations are higher in the sediment than in the soil. The Unmix analytical model was established. The natural source of heavy metals in the Tongyang River Basin and the composite pollution source of traffic-production and life showed a high correlation. According to the one-dimensional steady-state model, the concentrations of the heavy metals are in the following descending order: Zn, Cr, Pb, Cu, Ni, and Cd. The amounts of these elements entering the lake annually are 1993.04, 1028.1, 372.47, 301.72, 308.80, and 19.46 kg, respectively (a total of 4023.6 kg).

Coastal lagoons are important but sensitive environments, being transitional zones between land and sea. The Khnifiss lagoon is the most important desert wetland in Morocco, but little data have been produced concerning heavy metal geochemistry and enrichments in the sediments. Therefore, 26 surface sediments (15 intertidal and 11 subtidal) and 2 sediment cores were collected in 2016 and analyzed for a selection of heavy metals. The data were processed to assess the degree of contamination and the corresponding potential ecological risk, using several accumulation/enrichment indices, and the singular and multi-metal risk indices. Mean concentrations in the bottom layers of the two cores, dating from a pre-industrial age according to geochronological analysis, were used as the local geochemical background. The resulting values were on the whole lower than those reported for other areas of the northeastern coast of Morocco. Multivariate statistics were also applied to better understand relationships among variables (metals and other geochemical parameters) and to reveal similarities among sample groups. The results showed that, although the lagoon is not yet affected by significant anthropogenic influences, small enrichments can be recognized, especially for Ni and Cd. The cause may be related to the proximity to the main national highway, the vehicles and machinery used in the saltworks located in the area, and the small harbors used principally for fishing. In addition, industrial emissions from the Atlantic coast of Morocco and adjacent countries can be reasonably attributed as additional contributors to the enrichments. In terms of potential ecological risk, Cd shows the greatest impact compared to the other metals investigated.

The disordered mining of Dabaoshan lead-zinc mineral resources in Shaoguan has brought serious harm to the regional ecological environment. In order to investigate the heavy metal pollution status and microbial characteristics of soil plant system in mining area, The distribution of heavy metals in the soil, the activity of soil microorganisms and the accumulation characteristics of heavy metals in the dominant plant Miscanthus floridulus were studied. The results indicated that metal element contents of Miscanthus floridulus in sequence were: Zn>Pb>Cu> Cd. This study demonstrated that the elemental content of the Miscanthus floridulus plant showed Zn>Pb>Cu>Cd, with Zn being the most significantly correlated with soil elements, followed by Pb. Compared with the control group, the Miscanthus floridulus -soil system possessed obviously different soil microbial features: intensiver in microbial basal respiration strength, and higher microbial eco-physiological parameters Cmic/Corg and qCO 2 , but lower in soil microbial biomass. The results showed the soil enzymatic activities decreased significantly with increase of contamination of heavy metals, especially dehydrogenase and urease activities. With the increase of the content of heavy metals in the mining area soil, the intensity of soil biochemical action in the mining area (Q1, Q2) soil decreased significantly, and the biochemical action showed a significant negative correlation with the content of heavy metals in the soil. Compared with the non mining area (Q8) soil, the intensity of soil ammonification, nitrification, N fixation and cellulose decomposition decreased by 43.2%~71.1%, 70.1%~92.1%, 58.7%~87.8% and 55.3%~79.8% respectively. The decrease of soil microbial activity weakened the circulation rate and energy flow of C and N nutrients in the soil of the mining area.