The risk assessment of soil-rice system at the cross-provincial and national scales is of great significance for the prevention of heavy metal pollution and corresponding hazards. In this study, based on 183 studies, the concentrations of heavy metals in soil-rice systems, and the associated ecological and health risks in three main rice cultivated regions in China were determined. The species sensitivity distribution (SSD) curves were used to evaluate the predicted no effect concentrations (PNEC), hazardous concentration for 5 % of species (HC5) and the percentages of local species affected. The average Cd content in paddy soils in YRB (0.50 mg/kg) and SCR (0.64 mg/kg) exceeded the standards (0.4 mg/kg for YRB, 0.3 mg/kg for SCR). The ecological risks caused by Cadmium (Cd) and Mercury (Hg) were unneglectable. Chromium (Cr) and Arsenic (As) had the greatest effects on all local species, and the affected ratios in YRB, NP, and SCR were 46.4 % and 21.3 %, 45.7 % and 18.0 %, 42.1 % and 21.9 %, respectively. Arsenic (As) was the main contributor of non-carcinogenic health risks and influenced 41.9 %, 38.1 % and 86.6 % of men, women, and child, respectively. The estimated blood lead (Pb) concentration of child was approximately 8 times higher than adult groups, which was mainly caused by higher Pb gastrointestinal absorption rate due to long-term high demand for iron. This study provides a reference for the large-scale and long-term management of heavy metal pollution in soil-rice systems in China. In the future, in-field experiments should be conducted to further validate the outcomes based on literatures.

Deciphering the signal of metal ions: the principle, design and multi-field application of DNAzyme fluorescence sensor.

Abstract Heavy metal pollution is currently a major problem globally, threatening public and environmental health, and ecosystem functioning, requiring urgent solutions and mitigation strategies. Thus, the determination and monitoring of heavy metals in diverse environmental samples is of high critical importance, considering the significant risks posed by these elements. Many potentiometric sensors have been developed in the past for the determination of different heavy metal ions present in environmental samples using various sensor materials including poly(vinly chloride) membranes, carbon nanotubes composite membranes, metal‐organic frameworks, ionic liquids, and nanoparticles. In this review, we covered these electrochemical devices, focusing comparatively on their certain potentiometric performance parameters such as linear working range, stability, response time and limit of detection, and also highlighted their potential applicability areas in diverse fields, with the ultimate aim of contributing to the limitation and prevention of heavy metal pollution in the environment.

Heavy metals were discharged into the agricultural soil through coal mining, transportation, etc., posing a threat to human health through the food chain. In order to investigate the sources of heavy metals and potential risk to the population, we collected 298 surface soil samples in the black soil area of Sanjiang Plain in Heilongjiang province and tested the concentrations of seven heavy metals. Toxic element contamination in the soil was evaluated by combining the potential ecological risk index and environmental capacity, and pollution sources are identified through positive matrix factorization. The results indicate that the concentrations of Cd and As exceed background values by 1.74 and 1.51 times, respectively, and the ecological risk of Cd is significantly higher than those of other toxic elements. The comprehensive ecological risk level is a moderate comprehensive ecological risk level at 78.5% and a low comprehensive ecological risk level at 21.5%. The sources of heavy metal elements include pesticide spraying (36.5%), input fertilizer and transport activities (20.5%), and mining and metallurgy-related activities (43.1%). When linking the PMF to the Human Health Risk Assessment model, it was found that about 56% of the samples pose a carcinogenic risk to children. Knowledge of soil pollution can certainly help to understand the sources of toxic elements and the health risks to people in the black soil area and provide a scientific basis for the prevention of heavy metal pollution.

Abstract Environmental pollution with heavy metals is a problem for most developing or emerging countries. The study investigated the concentrations of arsenic (As), nickel (Ni), chromium (Cr), nickel (Ni), zinc (Zn), cobalt (Co), copper (Cu), and lead (Pb) in 10 samples of reclaimed soil for environmental risk assessment and spatial distribution following The Municipal Solid Waste Depot in Central Northern Bulgaria. According to Bulgarian legislation, the measured average concentrations of arsenic are below the maximum permissible concentration. Using the obtained heavy metal data, pollution indices such as geoaccumulation index (Igeo), pollution factor (CF), ecological risk factor (Er), pollution degree (Cdeg), and pollution index (PLI) were calculated and the results obtained categorized the site as uncontaminated. This suggests that the studied area is well-reclaimed and does not pose an ecological risk. The findings presented in this work support data on heavy metal contamination and risk assessment in Bulgaria. This research may have benefits for trace heavy metal pollution prevention and future monitoring studies of the region.

Sustainable potable groundwater supply is crucial for human development and the preservation of natural habitats. The largest endorheic inland lake in Kazakhstan, Balkhash Lake, is the main water resource for the arid southeastern part of the country. Several ore enrichment plants that are located along its shore have heavy metal pollution potential. The study area is located around a plant that has an evident anthropogenic impact on the Balkhash Lake aquatic ecological system, with ten known heavy metal toxic hotspots endangering fragile habitats, including some indigenous human communities. This study assessed the risk of heavy metal contamination from tailing dump operations, storage ponds, and related facilities and suggested management practices for preventing this risk. The coastal zone risk assessment analysis used an innovative integrated groundwater numerical flow and transport model that predicted the spread of groundwater contamination from tailing dump operations under several mitigation strategies. Heavy metal pollution prevention models included a no-action scenario, a filtration barrier construction scenario, and two scenarios involving the drilling of drainage wells between the pollution sources and the lake. The scenario assessment indicates that drilling ten drainage wells down to the bedrock between the existing drainage channel and the lake is the optimal engineering solution for confining pollution. Under these conditions, pollution from tailings will not reach Lake Balkhash during the forecast period. The methods and tools used in this study to enable mining activity without environmental implications for the region can be applied to sites with similar anthropogenic influences worldwide.

At a time when heavy metal pollution is increasing, assessing the levels of contamination and associated health risks is crucial. Samples of water, aquatic plants, and fish were collected from four key areas of heavy metal pollution prevention and control in Zhejiang Province. The levels of elements were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES). A human health risk model was also developed. The study revealed that heavy metal pollution in the five industrial zones exceeded the national standard for Class V water. Elements like arsenic (As), cadmium (Cd), and chromium (Cr) exceeded permissible levels in aquatic plants across all industrial zones; the exception was lead (Pb). Moreover, the heavy metal concentrations in subject fish tissues collected from each industrial area exceeded safe limits, especially in the gut. According to the human health risk evaluation model, the health risk (1.12 × 10-3) and children's health risk (1.10 × 10-3) in these prevention and control zones surpassed the maximum acceptable human risk values. In conclusion, heavy metal elements, along with other pollutants, accumulate and become concentrated in the examined aquatic plants and fish. These pollutants move through the food chain, impacting the entire aquatic ecosystem and posing a health risk to nearby populations.

Heavy metal pollution in mining areas is a major cause of groundwater contamination, characterized by high toxicity, difficult degradability, and easy accumulation, and the source of pollution is not easily identified. Relying on the results of groundwater quality analysis tests in a typical mining area, this paper uses the SPSS 18.0 statistical analysis model to analyze the statistical characteristics of different indicator factors in the antimony mining area. The conclusions play a crucial role in implementing health and safety measures for the mining area and its surrounding residents. The statistical study results show that Mn, Se, As, and Sb are closely related to human mining activities and are polluted to varying degrees; the principal component analysis model indicates that the upstream monitoring points 26#, 22#, and 25# in the mining area groundwater are less polluted. The five monitoring points with a comprehensive principal component F > 1 are all located within the range of the metal mine cluster, indicating that the groundwater in the mining area is particularly sensitive to the impact of anthropogenic mineral extraction. This research summarizes the hydrogeological and geochemical statistical characteristics of the groundwater in the mining area, providing a reference for groundwater pollution risk diagnosis, ecological restoration, and heavy metal pollution prevention and control in this and similar mining areas.

To explore the contamination status and identify the source of the heavy metals in the sediments in the major inflow rivers of Dianchi Lake in China, sediment samples were collected and analyzed. Specifically, the distribution, source, water quality, and health risk assessment of the heavy metals were analyzed using correlation analysis (CA), principal component analysis (PCA), the heavy metal contamination factor (Cf), the pollution load index (PLI), and the potential ecological risk index (PERI). Additionally, the chemical fractions were analyzed for mobility characteristics. The results indicate that the average concentration of the heavy metals in the sediment ranked in the descending order of Zn > Cr > Cu > Pb > As > Ni > Cd > Hg, and most of the elements existed in less-mobile forms. The Cfwas in the order of Hg > Zn > Cd > As > Pb > Cr > Ni; the accumulation of Hg, Zn, Cd, and As was obvious. Although the spatial variability of the heavy metal contents was pronounced, the synthetical evaluation index of the PLI and PERI both reached a high pollution level. The PCA and CA results indicate that industrial, transportation, and agricultural emissions were the dominant factors causing heavy metal pollution. These results provide important data for improving water resource management efficiency and heavy metal pollution prevention in Dianchi Lake.

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.

Ensemble learning-based applied research on heavy metals prediction in a soil-rice system

ABSTRACT The goal of this research was to better understand the spatial characteristics and hot areas of heavy metal concentrations in the soil-rice system, which was critical for implementing heavy metal pollution prevention and control strategies. The amounts of heavy metals in soil-rice were determined using high-precision testing methods such as XRF, ICP-MS, and AFS based on the systematic collection of 285 pairs of soil-rice samples from Wanjiang Economic Zone, China. The Getis-Ord index, Kriging method, and geostatistical method were used to reveal the spatial distribution of heavy metal contamination hot spots in the soil-rice system. The results revealed that the average concentration of heavy metals in soil was Zn>Cr>Cu>Pb>Ni>As>Cd>Hg, whereas it was Zn>Cu>Ni>Cr>Cd>As>Pb>Hg in rice. The average concentrations of heavy metals in the soil were all well below the maximum allowable limit, except for Cd, which was slightly above the allowable limit. Only Cd and Ni concentrations in rice exceeded the maximum permitted limits. In soil, Cd, Hg, Pb, and Zn pollution hotspots were mostly found in the southeast, while Cr and Ni were mostly found in the northeast. An intriguing discovery was that there was a weak relationship between heavy metal concentrations in soil and rice and the spatial pattern of their distribution. The study’s findings offer a scientific foundation for establishing a long-term agricultural development strategy for the soil-rice system in the Wanjiang Economic Zone.

A large area of periodic water-level-fluctuating zone (WLFZ) in the Poyang Lake, regulated by a special hydrologic rhythm, was deposited with significant amounts of nutrients and pollutants. In this study, the WLFZ located in a typical estuarine wetland was chosen and sampling transects were arranged according to different vegetation types towards the lake. Soil/sediment and dominant plant (different tissues) samples were collected, and contents and enrichment levels of heavy metals (Cr, Ni, Cu, Zn, As, Cd, Sb, and Pb) in these samples were analyzed. The migrations and conversions of heavy metal in the soil/sediment-plant system were evaluated, and driving environmental factors were explored. The results indicated that the contents of heavy metal in the soil/sediment presented an obvious single-peak distribution towards the lake, that is, the seasonally flooded zone was identified as the main deposited zone of heavy metals. There was a high enrichment level of Cu, Pb, and Sb in the soil/sediment from the WLFZ, and significant Cu and Sb pollution was identified (EF>5). The results from the potential ecological risk evaluation (RI) indicated that the ecological risk of the seasonally flooded zone was significantly higher than that in the flooded and unflooded zones, being at a low ecological risk (70 ≤ RI<140). There was no obvious spatial distribution of heavy metal contents in the dominant plant towards the lake, whereas significant seasonal differences were detected. The levels of heavy metals in plants at the growth phase (April) were higher compared to those at the other sampling times. The tissue distributions of heavy metal content basically followed the sequence of soil/sediment>root ≥ above-ground part, except for in Cd and Sb. The Cd content in the roots was significantly higher than that in the sediment/soil, and the Sb concentration was not significantly different among the three tissues. The bio-enrichment coefficient (BAF) and transfer factor (TF) of heavy metal in the dominant plant towards the lake did not show an obvious spatial pattern, and BAF and TF of heavy metals in the Artemisia capillaris Thunb. was higher than those in other dominant plants. The RDA revealed that pH, organic matter, plant height, and Fe-Mn oxides were the key environmental factors driving the migrations of heavy metals in the soil/sediment-plant system. These results will provide scientific basis and theoretical support for the biodiversity conservation and heavy metal pollution prevention and management in wetlands of the Poyang Lake.

Copper smelting can cause heavy metal pollution in surrounding soil and threaten human health. This study examined the characteristics, distribution, and health risk of heavy metals in soil with different land uses around 40 copper smelting sites at home and abroad by collecting published literature data. The results showed that the mean values of ω(As), ω(Cd), ω(Cu), ω(Pb), and ω(Zn) in the soil around the copper smelting sites were 196, 10.5, 1948, 604, and 853 mg·kg-1, respectively. The order of Igeo was Cd(5.63)>Cu(3.88)>As(2.96)>Pb(2.30)>Zn(1.27), and the accumulation of Cd and Cu was the most serious. High Nemero index (NIPI) values were found in the soil around smelting sites with a long history of smelting, outdated process, and insufficient environmental protection measures. Significant correlations were found between the concentrations of heavy metals in the soil, which decreased with the sampling distance. The heavy metals mainly accumulated within 2-3 km from the smelting sites. Compared with the smelting history, scale, and process, land use type had a lower effect on soil heavy metal concentrations. The heavy metals in the soil around copper smelters may pose carcinogenic and non-carcinogenic risks on residents. The high health risks were mainly caused by As and Pb in smelting production areas, and Pb in woodland. These results may guide the risk prevention of heavy metal pollution in the soil around smelting sites.

Fate and transport of chromium in industrial sites: Dynamic simulation on soil profile

Overview assessment of risk evaluation and treatment technologies for heavy metal pollution of water and soil

Understanding the extent of contamination, sources and various carcinogenic and non-carcinogenic risks associated with different heavy metals in soil-crop systems is crucial for the prevention of heavy metal pollution. A survey was undertaken to determine heavy metal concentrations and degree of pollution in soil-crop systems (rice, wheat, and corn) using various indices such as pollution factor (CF), geo-accumulation index (Igeo), enrichment coefficients and transfer coefficient, and to determine the source of heavy metals pollution in the Wanjiang Economic Zone, Anhui Province, China. A total of 308 pairs of soil-crop samples were collected in this study, comprising 245 pairs of soil-rice samples, 53 pairs of soil-wheat samples, and 10 pairs of soil-corn samples. The concentrations of cadmium (Cd) and nickel (Ni) in the soil of the study area exceeded the national limitation of heavy metals in the soil of China (GB 15618-2018, Soil Environmental Quality: Risk Control Standard for Soil Contamination of Agricultural Land. Ministry of Environmental Protection of China. Beijing. China). The concentrations of copper (Cu), zinc (Zn) and lead (Pb) were also above the national limits to a lesser extent. All eight heavy metals (Cd, Cu, Ni, Pb Zn, arsenic (As), chromium (Cr), and mercury (Hg)) exceeded the background values in the study area. The enrichment coefficients of rice, wheat and maize to Cd, Cu and Zn were higher than those to other elements. On the basis of Igeo, it can be indicated that the rhizosphere soil of rice was slightly polluted by Cd and Hg, while the concentrations of the other heavy metals were below the safety limits. The CF and pollution load index (PLI) indicated that the soil in the study area was heavily contaminated with heavy metals. A principal component analysis identified different sources of soil heavy metal pollution, that is, Cu, Pb, Zn and Cd from industrial sources, Cr and Ni from natural sources, and As and Hg from agricultural sources. The carcinogenic risk of heavy metals was related to the intake of crops. Residents in the study area ingest rice, wheat, and corn on a daily basis. On the basis this study, it is suggested that local governments should pay attention to the carcinogenic risk of heavy metals in rice.

Cadmium (Cd) pollution in soil is a serious threat to food security and human health, while, currently, the most widely used detection methods cannot accurately reflect the content of heavy metals in soil. Soil heavy metal detection combined with microelectronic sensors has become an important means of environmental heavy metal pollution prevention and control. X-ray Fluorescence spectrometry (XRF) can capture the excitation spectrum of metal elements, which is often used to detect Cd (II). However, due to the lack of high-performance optoelectronic devices, the analysis accuracy of the system cannot meet the requirements. Therefore, this study proposes a high-detection-efficiency photodiode (HDEPD) which can effectively improve the detection accuracy of the analyzer. The HDEPD is manufactured based on a 0.18 μm standard complementary metal-oxide-semiconductor (CMOS) process. The volt-ampere curve, spectral response and noise characteristics of the device are obtained by constructing a test circuit combined with a spectral detection system. The test results show that the threshold voltage of HDEPD is 12.15 V. When the excess bias voltage increases from 1 V to 3 V, the spectral response peak of the device appears at 500 nm, and the photon detection probability (PDP) increases from 41.7% to 52.8%. The dark count rate (DCR) is 31.9 Hz/μm2 at a 3 V excess bias voltage. Since the excitation spectrum peak of Cd (II) is between 500 nm and 600 nm, the wavelength response range of HDEPD fully meets the detection requirements of Cd (II).

In order to study the source of heavy metal pollution in Baiyangdian Lake, laser-induced breakdown spectroscopy technology was used to analyze Fe, Cu, Cd, Pb, Zn, Cr, Ni, and As elements in the wetland bottom mud and fish gills of the lake. The methods of correlation analysis, principal component analysis, and cluster analysis are combined to analyze the characteristic spectra of heavy metal elements in the wetland bottom mud and fish gills. Research results show that the pollution sources of Longwangdian, Maidian, Wangjiazhai, and fish gills can be classified into three types. The first pollution source of Longwangdian is Fe, Cd, Pb, and As. The second is Ni, Zn, and Cu. The third is Cr. The first pollution source of Maidian is Fe, Cd, Zn, and Cr. The second is Cu, Pb, and As. The third is Ni. The first pollution source of Wangjiazhai is Fe, Cd, As, Cr, and Cu. The second is Ni and Zn. The third is Pb. The first pollution source of fish gills is Fe, Cd, Zn, Cr, Ni, and As. The second is Pb. The third is Cu. The similarity of heavy metal sources between fish gills and Maidian is higher than that of the other two wetlands. It is determined that the heavy metals in fish gills come from the bottom mud of Maidian. The research results can provide a basis for ecological protection and heavy metal pollution prevention and control in Baiyangdian Lake.

The heavy metal pollution of estuary wetlands caused by industrial and agricultural production activities has aroused widespread concern. The Hakanson Pollution index, Geo-accumulation index (Igeo) and Redundancy analysis were used to explore the seasonal variation and contamination risk of heavy metals in surface sediments. Results showed that the heavy metal concentrations were ranked in descending order: Cd > Cu > Zn > Pb > Cr. The analysis result of HPI and Igeo showed that there was a low level of heavy metal contamination both in summer and winter. Redundancy analysis showed that the correlation between heavy metals and physicochemical properties of sediment was significantly different in winter and summer. Our findings provide scientific support for the prevention of heavy metal pollution in estuary wetlands.