Prevention Of Heavy Metal Pollution Research Articles

Effects of Heavy Metal Pollution on the Element Distribution in Hydrobios.

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.

Characterization of heavy metal contamination in groundwater of typical mining area in Hunan Province

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.

Pollution Characteristics and Risk Assessment of Heavy Metals in the Sediments of the Inflow Rivers of Dianchi Lake, China.

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.

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.

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

Accurate prediction of heavy metal accumulation in soil ecosystems is crucial for maintaining healthy soil environments and ensuring high-quality agricultural products, as well as a challenging scientific task. In this study, we constructed a dataset containing 490 sets of multidimensional environmental covariate data and proposed prediction models for heavy metal concentrations (HMC) in a soil–rice system, EL-HMC (including RF-HMC and GBM-HMC), based on Random Forest (RF) and Gradient Boosting Machine (GBM) ensemble learning (EL) techniques. To reasonably evaluate the effectiveness of each model, Multiple linear and Bayesian regressions were selected as benchmark models (BM), and mean absolute error (MAE), root mean square error (RMSE), and determination coefficient R2 were selected as evaluation indicators. In addition, sensitivity and spatial autocorrelation (SAC) analyses were used to examine the robustness of the model. The results showed that the R2 values of RF-HMC and GBM-HMC for modeling available cadmium (Cd) concentrations in soil were 0.654 and 0.690, respectively, with an average increase of 48.0 % compared to the BMs. The R2 values of RF-HMC and GBM-HMC for predicting Cd, lead (Pb), chromium (Cr), and mercury (Hg) concentrations in rice ranged from 0.618 to 0.824 and 0.645 to 0.850, respectively, with an average increase of 58.2 % compared with the BMs. The corresponding MAEs and RMSEs of RF-HMC and GBM-HMC had low error levels. Sensitivity analysis of the input features and the SAC of the prediction bias showed that the EL-HMC models have excellent robustness. Therefore, the EL technology-based prediction models for HMCs proposed herein are practical and feasible, demonstrating better accuracy and stability than the traditional model. This study verifies the application potential of EL technology in pollution ecology and provides a new perspective and solution for sustainable management and precise prevention of heavy metal pollution in farmland soil at the regional scale.

Spatial variability and hotspot prediction of heavy metal pollution in soil-rice system: based on a new geostatistical method

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.

Enrichments, Migrations, and Conversions of Heavy Metal in the Soil/Sediment-Plant System Towards the Lake in Typical Poyang Lake Wetland

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.

Characteristics and Risk Assessment of Heavy Metals in the Soil Around Copper Smelting Sites

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

Direct discharge of chromium-containing waste water and improper disposal of waste residues in industrial sites may lead to the vertical migration of metals into aquifers, posing serious threat to soil-groundwater system. The heterogeneity in soil profile further aggravates the complexity and unpredictability of this transport process. However, topsoil was the main focus of most studies. Herein, the vertical transport and transformation of Cr in soils at different depths in three industrial sites (i.e., Shijiazhuang, Zhuzhou, and Guangzhou) were investigated to delineate Cr transport and retention characteristics under complex conditions. Regional and vertical differences in soil properties led to the specificity in Cr migration behaviors among these three sites. Correlation analysis showed that soil pH (r = −0.909, p < 0.05) and Fe content (r = 0.949, p < 0.01) were the major controlling factors of Cr(VI) migration and transformation in aquifers. Furthermore, the soil of Zhuzhou site showed the maximum adsorption capacity for Cr(VI) (0.225 mol/kg), and the strongest reduction ability of Cr(VI) was observed in the Guangzhou soil. Results of model-based long-term forecast indicated that the Cr(III) concentration in the liquid phase of Guangzhou subsoil could reach 0.08 mol/m3 within 20 years. Heavier rainfall condition exacerbated the contamination due to an increased pollutant flux and enhanced convection. Specially, Cr was fixed in the topsoil of Zhuzhou site with the formation of PbCrO4 and presented least vertical migration risk. The conclusions above can provide scientific theoretical guidance for heavy metal pollution prevention and control in industrial contaminated regions.

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

Heavy metals are highly toxic elements which are persistent in the natural environment, resulting in magnification throughout the food chain, adversely affecting both human and environmental health. Consequently, heavy metal pollution has received widespread research attention. This review assesses the current progress in heavy metal pollution monitoring, management and mitigations, which show a lack of systematic criteria for risk evaluation. Risk assessment and multivariate analysis methods are also discussed. Assessment of risk evaluation and multivariate statistical analysis are the basic step for the treatment technologies choosing. The technique used is always site-specific, and it often combines different strategies. Only by comprehensively considering the contaminated time, the concentration and nature of the contaminant, the soil/water and site characteristics, the contaminant's availability, and the existence of specific regulations can appropriate restoration and treatment plans be formulated. Combinations of GIS and modeling appear to be most effective for analysis of heavy metal pollution risk. In recent years, many physico, chemical and bio technologies have been used to remove heavy metal pollution from water and soil, each having inherent advantages and limitations. So far, no single method is universally effective for the removal of all heavy metals. Combining different technologies can lead to greater efficiency and may provide a reasonable method to conduct inter-governmental, cross-border heavy-metal prevention and monitoring, for the control of anthropogenic pollution sources. Efficient and commercially viable scaled-up heavy metal treatment technologies will yield large benefits to human and environmental health, as well as economic output. This review provides an overview of the currently available methods, to inform researchers and other stakeholders in the prevention of heavy metal pollution of water and soil.

Bi-Directional Pollution Characteristics and Ecological Health Risk Assessment of Heavy Metals in Soil and Crops in Wanjiang Economic Zone, Anhui Province, China.

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.

A High-Detection-Efficiency Optoelectronic Device for Trace Cadmium Detection.

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).

Research on the traceability method of heavy metal pollution in typical wetlands

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.

Seasonal Variation and Contamination Risk Assessment of Heavy Metals in Surface Sediment of an Estuary Alluvial Island in Eastern China.

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.

Distribution, source, water quality and health risk assessment of dissolved heavy metals in major rivers in Wuhan, China.

Heavy metals are released into the water system through various natural processes and anthropogenic activities, thus indirectly or directly endangering human health. The distribution, source, water quality and health risk assessment of dissolved heavy metals (V, Mn, Fe, Co, Ni, Zn, As, Mo, Sb) in major rivers in Wuhan were analyzed by correlation analysis (CA), principal component analysis (PCA), heavy metal pollution index (HPI), hazard index (HI) and carcinogenic risk (CR). The results showed that the spatial variability of heavy metal contents was pronounced. PCA and CA results indicated that natural sources controlled Mn, Fe, Co, Ni and Mo, and industrial emissions were the dominant factor for V, Zn and Sb, while As was mainly from the mixed input of urban and agricultural activities. According to the heavy metal pollution index (HPI, ranging from 23.74 to 184.0) analysis, it should be noted that As and Sb contribute most of the HPI values. The health risk assessment using HI and CR showed that V and Sb might have a potential non-carcinogenic risk and As might have a potential carcinogenic risk to adults and children in the study area (CR value exceeded target risk 10−4). At the same time, it was worth noting that As might have a potential non-carcinogenic risk for children around QLR (HI value exceeded the threshold value 1). The secular variation of As and Sb should be monitor in high-risk areas. The results of this study can provide important data for improving water resources management efficiency and heavy metal pollution prevention in Wuhan.

Environmental sustainability and prevention of heavy metal pollution of some geo-materials within a city in southwestern Nigeria

Increased anthropogenic activities may cause the release of potentially hazardous metals into the environment. This is a major public health concern. The study was aimed at accessing ways by which pollution can be prevented with enhanced environmental sustainability in Ibadan, Southwestern, Nigeria. Geo-materials (groundwater, soil and stream sediment) were collected, analyzed for heavy metals using inductively coupled plasma-mass spectrometry. Results of acidity (pH), electrical conductivity (EC), total dissolved solid (TDS) and heavy metals (Zn, As, and Cd) obtained in water were compared with WHO permissible limits. All parameters were found within WHO permissible limits except TDS (624.35 mg/L). Risk index showed dangerous to extremely dangerous. High TDS can be attributed to weathering while high Cd, Zn and Pb in stream sediment and soil are due to anthropogenic effect. Provision of adequate disposal facilities should be created by private and government agencies and the use of it must be enforced.

Spatial Distribution and Risk Assessment of Heavy Metal Pollution in Farmland Soils Surrounding a Typical Industrial Area of Henan Province

In order to fully explore the spatial distribution of soil heavy metal contaminants in farmland soil surrounding a typical industrial area in Dakuai town, Xinxiang city, Henan Province, the concentrations of As, Cd, Cr, Cu, Ni, Pb, and Zn in the surface soil and within the soil profile were determined and assessed. The principal components were also analyzed for source apportionment to provide a theoretical basis for the control and prevention of heavy metal pollution. According to the results, the soils in the study area are severely contaminated by Cd and Cu and moderated contaminated by As due to the battery manufacture and Cu (e.g., pipe and wire) processing. The concentrations of Cd, Cu, and As in soils were (2.56±1.23) mg·kg-1, (205.58±157.49) mg·kg-1, and (15.27±4.14) mg·kg-1, respectively, which exceeds standards by 100%, 89.44%, and 3.40%, respectively. Accounting for the influence of pollution sources, terrain, runoff erosion, and prevailing wind direction, all heavy metal concentrations were higher in the south direction, lower in the north direction. The concentrations of Cd and Cu in soil profile samples decreased with depth, with highest concentrations at the surface, indicating the strong effect of industrial activities. Arsenic concentrations varied little with soil depth due to its strong migration ability in alkaline soil, again suggesting an industrial source. Among them, the soil of study area was severely contaminated by Cd and Cu (Level 5). Cd poses a severe potential ecological risk (Level 5) and Cu poses a medium risk (Level 2) in the study soils, while other heavy metals show low potential ecological risk (Level 1). The order of the risk identified was Cd > Cu > Ni > As > Pb > Cr > Zn. In addition, the combined potential ecological risk of heavy metals in the target area is severe. The principal component analysis showed that the high As, Cd, and Cu contents are mainly derived from industrial areas. Therefore, it is urgent to remediate Cd and Cu soil contamination in this area and implement precautions to limit As contamination.

Assessment and sources of heavy metals in suspended particulate matter in a tropical catchment, northeast Thailand

Since the suspended particulate matter (SPM) is a vital heavy metal transporter of the river systems, assessment of heavy metals contamination in SPM is significant as the first step of the high-efficiency surface water environment management and further foundation of water resources sustainability. However, this assessment is rare in developing countries (e.g., Thailand, agriculture is the main economic pillar). Fluvial heavy metal pollution prevention strategy is urgently required in these areas for reducing human exposure to metal contamination. For this purpose, the assessment of eight selected heavy metals of 52 SPM samples in a Thailand tropical river (Mun River) was conducted. The findings suggest that the contents of heavy metals in SPM are Mn (4616.7 mg kg−1) > Zn (223.9 mg kg−1) > V (109.1 mg kg−1) > Cr (100.1 mg kg−1) > Ni (51.0 mg kg−1) > Cu (27.6 mg kg−1) > Pb (14.3 mg kg−1) > Cd (10.7 mg kg−1). A relatively large proportion of heavy metals (e.g., Mn, 89.5%; Zn, 54.2%) are transported in suspended loads in Mun River. Heavy metals accumulation assessment suggests that Cd (EF = 17.5, Igeo = 3.7) and Mn (EF = 14.3, Igeo = 2.1) are extremely enriched in SPM, while the other metals are slightly enriched or not enriched. Principal component (PC) analysis extracted three PCs. PC 1 with a high loading of Mn, Zn, Cd, Pb reflecting these metals mainly from anthropogenic emissions, PC 2 (V and Cu) is primarily characterized by the natural sources (e.g., rock weathering), while PC 3 (Cr and Ni) can be defined as the result of combined action of natural and anthropogenic inputs. Risk assessment denotes that Cd is the major toxicity of SPM with a high toxic risk index (TRICd = 9.4, 54% of the total TRI) and the V, Cr, Mn, and Cd in SPM are the major exposure health risk, particularly for children (hazard index, HI > 0.1), more focus is required for these metals. In total, this study provides powerful support for the prevention of heavy metal pollution and the sustainability of water resources in the Mun River in such a developing country (Thailand).

Cd contamination status and cost-benefits analysis in agriculture soils of Yangtze River basin

Soil is a fundamental carrier to support for human living and development and has been polluted seriously by heavy metals. This fact highlights the urgency to realize soil heavy metal pollution prevention through soil heavy metals contamination status assessment and root cause analysis. The previous research tends to focus status assessment and source identification without consideration of economic aspect. This study realized the systematic analysis from status assessment, sources identification and economic-environmental cost-benefits analysis in the Yangtze River basin. Through the spatial difference comparison among the provinces of upper, middle and lower in the Yangtze River basin, it revealed that anthropogenic influence is the main reason caused the current Cd contamination in Yangtze River basin. An interesting finding is that the human caused Cd concentration contribution amount is nearly the same between upstream and downstream which is all about 0.1 mg/kg, while they have quite different economic scale. It indicated that due to the difference of the scale and structure of local economy, and the level of cleaner production and pollution treatment, some regions could own high economic-benefits and low environmental cost, which it is opposite in other regions. The geographic location and natural resources is the root cause to form the environmental cost-economic benefits difference among regions. The convenient traffic promoted downstream to develop large amount and high quality of economy. The natural mineral resources promoted midstream to develop resources based economy. The poor condition of traffic and natural resources has restricted the development of Qinghai province, and made it has the highest Cd pollution intensity. The results would provide effective economic management measures for better soil quality and sustainable development goals achievement.

Heavy metal pollution assessment, source identification, and health risk evaluation in Aibi Lake of northwest China.

This study sought to analyze heavy metal (Pb, Zn, Cu, Ni, Mn, and Fe) pollution status in the waters of Aibi Lake in northwest China through the use of an applied comprehensive pollution index, health risk model, and multivariate statistical analyses in combination with the lake's land use types. Results showed that (1) the maximum (average) values of the heavy metals Pb, Zn, Cu, Ni, Mn, and Fe were 0.0644 (0.0123), 0.0006 (0.0002), 0.0009 (0.0032), 0.1235 (0.0242), 0.0061 (0.0025), and 0.0222 (0.0080)μg/L, respectively. Among these, in all the samples, Pb and Ni exceeded the standard and acceptable values put forth by the World Health Organization by 21.13 and 25.67%, respectively. Ni also exceeded (30.16%) the third grade of the Environmental Quality Standards for Surface Water of China. The levels of the six heavy metals were all within the fishery and irrigation water quality standard ranges in China. (2) The average values for single pollution index of heavy metals Pb, Zn, Cu, Ni, Mn, and Fe were 1.000, 0.0006, 0.0009, 3.000, 0.060, and 0.070, respectively, among which Ni levels indicated moderate to significant pollution, while others indicated healthy levels. (3) Health risk evaluation showed that the Rn values for Pb, Zn, Cu, Mn, and Fe were 1.8 × 10-4, 5.33 × 10-9, 4.80 × 10-7, 1.08 × 10-6, and 2.51 × 10-7a-1, respectively, of which, in all samples, Pb and Ni contents all exceeded the maximum acceptable risk levels according to the International Commission on Radiological Protection (ICRP) as well as the U.S. Environment Protection Agency. (4) Combining with multivariate statistical analyses along with the land use distribution within the lake basin, Pb, Zn, Cu, Ni, and Mn were mainly influenced by the agriculture production and emission from urban lives and traffics, and Fe mainly originated from the natural environment. The results of this research can provide reference values for heavy metal pollution prevention in Aibi Lake as well as for environmental protection of rump lakes in the arid regions of northwest China and Central Asia.