A Monte Carlo simulation-based health risk assessment of heavy metals in soils of an oasis agricultural region in northwest China

Metals and polycyclic aromatic hydrocarbons pollutants in industrial parks under valley landforms in Tibetan Plateau: Spatial pattern, ecological risk and interaction with soil microorganisms

The spatial patterns of pollutants produced by industrial parks are affected by many factors, but the interactions among polycyclic aromatic hydrocarbons (PAHs), metals, and soil microorganisms in the valley landforms of the Tibetan Plateau are poorly understood. Thus, this study systematically investigated the distribution and pollution of metals and PAHs in soil around an industrial park in the typical valley landform of the Tibetan Plateau and analyzed and clarified the interaction among metals, PAHs, and microorganisms. The results were as follows: metal and PAH concentrations were affected by wind direction, especially WN-ES and S-N winds; Cd (2.86-54.64 mg·kg-1) had the highest soil concentrations of the metals screened, followed by variable concentrations of Cu, Pb, and Zn; the pollution levels of metals and PAHs in the S-N wind direction were lower than those in the WN-ES wind direction; the Cd content of Avena sativa in the agricultural soil around the factory exceeded its enrichment ability and food safety standards; the closer to the center of the park, the higher the ecological risk of PAHs; and the TEQ and MEQ values of the PAHs were consistent with their concentration distributions. The results of the soil microbial diversity and co-occurrence network in the dominant wind direction showed that metal and PAH pollution weakened the robustness of soil microbial communities. Additionally, the diversity and robustness of soil microbial communities at the S wind site were higher than those at the ES wind site, which might be attributed to the lower metal content of the former than the latter, which plays a negative role in the biodegradation of PAHs. The results of this study provide insights into the site selection, pollutant supervision, and environmental remediation of industrial parks in typical landforms.

Do the residual metals in multiple environmental media surrounding mines pose ecological and health risks? A case of an abandoned mining area in central south China

Despite effective mining environmental regulations, residual metal pollution persists, leading to significant ecological harm and posing substantial risks to human well-being. This study employed multiple-criteria methods to investigate the ecological and health risks caused by metals in multiple environmental media (e.g., arable soil, indoor dust, PM10, homegrown vegetables, and rice) around abandoned mine areas (MA) in central south China. The study also aimed to identify predominant risk factors and the main exposure pathway. The findings revealed that metal levels and risks in the environmental media surrounding the MA were significantly higher than those in the control areas (away from abandoned mines, CA). This indicates that the accumulation of metals in the environmental media surrounding the MA was attributed to the previous mining activities. Variations in metal content were observed among different environmental media in MA, with Cd from mining source being the primary pollutant in arable soil, indoor dust, PM10, and vegetables, while As from agricultural source was the main pollutant in rice. Additionally, the consumption of Cd-contaminated vegetables and As-contaminated rice emerged as the primary routes of health hazards for the local population, leading to significant non-carcinogenic and carcinogenic risks. Consequently, it is imperative for the government and mining companies to promptly establish risk control and remedial strategies for mitigating residual metal levels in multiple environmental media surrounding the MA.

Heavy metal immobilization and radish growth improvement using Ca(OH)2-treated cypress biochar in contaminated soil

Heavy metal contamination poses a significant threat to soil quality, plant growth, and food safety, and directly affects multiple UN SDGs. Addressing this issue and offering a remediation solution are vital for human health. One effective approach for immobilizing heavy metals involves impregnating cypress chips with calcium hydroxide (Ca(OH)2) to enhance the chemical adsorption capacity of the resulting woody charcoal. In the present study, un-treated cypress biochar (UCBC) and calcium-treated cypress biochar (TCBC), were introduced into pristine and contaminated soil, at rates of 3, 6, and 9% (w/w). Both BCs were alkaline (UCBC pH: 8.9, TCBC pH: 9.7) with high specific surface area, which improved the soil properties (pH, EC, and OM). Radish (Raphanus sativus) cultivated in pots revealed that both UCBC and TCBC demonstrated significant improvements in growth attributes and heavy metal immobilization compared to the control, with TCBC exhibiting superior effects. The TCBC surface showed highly active nanosized precipitated calcium carbonate particles that were active in immobilizing heavy metals. The application of TCBC at a rate of 9% resulted in a substantial reduction in Zn and Cu uptake by radish roots and shoots. In contaminated soil, Zn uptake by radish roots decreased by 55% (68.3-31.0 mg kg-1), and shoots by 37% (49.3-31.0 mg kg-1); Cu uptake decreased by 40% (38.6-23.2 mg kg-1) in roots and 39% (58.2-35.2 mg kg-1) in shoots. Uptake of Pb was undetectable after TCBC application. Principal component analysis (PCA) highlighted the potential of TCBC over UCBC in reducing heavy metal concentrations and promoting radish growth. Future research should consider the long-term effects and microbial interactions of TCBC application.

Source-oriented health risk assessment of groundwater nitrate by using EMMTE coupled with HHRA model

Conventional concentration-oriented approaches for nitrate risk diagnosis only provide overall risk levels without identifying risk values of individual sources or sources accountable for potential health risks. Therefore, a hybrid model combining the end-member mixing model tool on Excel™ (EMMTE) with human health risk assessment (HHRA) was developed to assess the source-oriented health risks for groundwater nitrate, particularly in the Poyang Lake Plain (PLP) region. The results indicated that the EMMTE and the Bayesian stable isotope mixing model (MixSIAR) exhibited remarkable consistency in source apportionment of groundwater nitrate. The source contribution of groundwater nitrate in PLP was related to land use types, hydrogeological conditions, and soil properties. Notably, manure and sewage sources, contributing up to 53.4 %, represented the largest nitrate pollution sources, with a significant contribution of soil nitrogen and nitrogen fertilizers. The non-carcinogenic risk for four potential sources was below the acceptable threshold of 1. Given the factors including rainfall dilution and economic development, attention should be directed towards mitigating the health risks posed by manure and sewage. This study can verify the efficacy of EMMTE in source apportionment and offer valuable insights for decision-makers to regulate the largest sources of nitrate contamination and enhance groundwater management efficiency.

Cadmium biosorption and mechanism investigation using two cadmium-tolerant microorganisms isolated from rhizosphere soil of rice

Microbial remediation of cadmium-contaminated soil offers advantages like environmental friendliness, cost-effectiveness, and simple operation. However, the efficacy of this remediation process relies on obtaining dominant strains and a comprehensive understanding of their Cd adsorption mechanisms. This study identified two Cd-resistant bacteria, Burkholderia sp. 1-22 and Bacillus sp. 6-6, with significant growth-promoting effects from rice rhizosphere soil. The strains showed remarkable Cd resistance up to ∼200 mg/L and alleviated Cd toxicity by regulating pH and facilitating bacterial adsorption of Cd. FTIR analysis showed crucial surface functional groups, like carboxyl and amino groups, on bacteria played significant roles in Cd adsorption. The strains could induce CdCO3 formation via a microbially induced calcium precipitation (MICP) mechanism, confirmed by SEM-EDS, X-ray analysis, and elemental mapping. Pot experiments showed these strains significantly increased organic matter and enzyme activity (e.g., urease, sucrase, peroxidase) in the rhizosphere soil versus the control group. These changes are crucial for restricting Cd mobility. Furthermore, strains 6-6 and 1-22 significantly enhance plant root detoxification of Cd, alleviating toxicity. Notably, increased pH likely plays a vital role in enhancing Cd precipitation and adsorption by strains, converting free Cd into non-bioavailable forms.

Relationship between nitrate, heavy metal, and sterols contents in Japanese agricultural soils with risk of groundwater pollution

In Japanese agricultural lands, nitrate-nitrogen contamination of soil and groundwater often occurs due to the application of livestock excrements and compost. Therefore, rural soils in Japan were sampled and analyzed for nitrate-nitrogen leaching, heavy metal content, and sterols associated with livestock excrement and compost to calculate contamination risk indicators. The results were analyzed using self-organizing maps and cluster analysis. Nitrate-nitrogen content using water extraction was detected in most of the sampled soils. In addition, many samples from areas that were already severely contaminated with nitrate-nitrogen showed particularly high concentrations. Coprostanol, an indicator of fecal contamination, was detected in more than half of the samples. The main source of nitrate-nitrogen contamination in these areas is livestock excrement and compost. Self-organization maps showed that areas with high nitrate-nitrogen contamination also corresponded to areas with high copper and zinc soil contents. The self-organization maps and cluster analysis resulted in five clusters: a nitrate-contaminated group mainly originating from livestock excrement and compost, a heavy metal-contaminated group, a general group, a nitrate-contaminated group mainly originating from chemical fertilizers, and a contaminated group with potentially hazardous substances requiring attention. Authorities and decision-makers can use the results to prioritize areas requiring remediation.

Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater

Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.

Health risk assessment of heavy metals based on source analysis and Monte Carlo in the downstream basin of the Zishui

In this study, stone coal mines in the lower reaches of the Zijiang River were adopted as the research object. To analyze the spatial distribution, sources, and health risks of heavy metals in the surrounding soil of stone coal mines, 82 topsoil samples were collected in the study area, and the contents of 8 heavy metals including Cd, Hg, As, Cr, Pb, Cu, Ni, and Zn were determined. The spatial distribution of heavy metals was analyzed using ArcGIS, and the pollution sources of heavy metals were identified using Positive matrix factorization (PMF). Then, Monte Carlo and health risk assessment models were used to evaluate the health risks of different populations. The results showed that the average content of heavy metals followed the order of Zn > Cr > Pb > Cu > Ni > As > Cd > Hg, and the contents of all heavy metals were higher than the soil background values of Hunan Province. The high-value areas of heavy metals content were mostly concentrated in the central region close to areas with a notable concentration of stone coal mines. PMF identified four pollution sources, namely, mining activities (26.9%), atmospheric deposition (18.8%), natural sources (32.8%) and agricultural sources (21.5%). The carcinogenic and non-carcinogenic risks for children were higher than those for adults, with As and Cd posing higher carcinogenic risks to children. Based on the source of health risks, it was determined that the health risks could be primarily attributed to agricultural sources, and As was the main heavy metal causing health risks. This study provides theoretical support for treating heavy metal pollution in mining basins.

Health risk assessment of heavy metals in wild fish and seasonal variation and source identification of heavy metals in sediments: a case study of typical urban river in Xi'an, China

In order to determine the status of heavy metal pollution in river sediments and wild fish in Xi'an, concentrations of heavy metals (Cr, Ni, Cu, Zn, As, and Pb) were collected and analyzed in sediments and wild fish during dry season (October-November 2020) and wet season (June-July 2021). This study aimed to investigate the spatial and temporal variations of heavy metals in urban rivers of Xi'an, China. Their distribution characteristics and sources as well their pollution levels and health risks were assessed. The findings revealed that influenced by human activities, the heavy metal content in sediments (mg·kg-1 dry weight) in wet season was ranked as follows: Cr (73.09) > Zn (63.73) > Pb (40.31) > Ni (31.52) > Cu (24.86) > As (6.83); in the dry season: Zn (94.07) > Cr (69.59) > Cu (34.24) > Ni (33.60) > Pb (32.87) > As (7.60). Moreover, 32 fish samples from six species indicated an average metal content trend (mg·kg-1 wet weight) of Zn (8.70) > Cr (0.57) > Pb (0.28) > Ni (0.27) > Cu (0.24) > As (0.05). The potential ecological risk indices for sediment heavy metal concentrations in both seasons were well below the thresholds, which indicates that the aquatic environment is in safe level. The analysis of the potential ecological risk of sediment heavy metal concentrations indicates that the aquatic environment is safe for the time being. Based on the estimated daily intake (EDI), target risk quotient (THQ), total target risk quotient (TTHQ), cancer risk (CR), total cancer risk (TCR), and the permissible safety limits set by the agencies, the consumption of the fish examined is safe for human health. However, the presence of Cr and As in wild fish should still be a concern for human health, especially for children. The cumulative effect of heavy metals and the bioconcentration factor (BCF) suggest that sediment and heavy metals in fish are closely related, with higher concentrations in fish living in the bottom layer of the water column than in other water layers, and increasing with increasing predator levels. Correlation analysis and PMF modeling identified and determined four comparable categories of potential sources, namely, (1) atmospheric deposition and traffic sources, (2) agricultural sources, (3) industrial sources, and (4) natural sources.

Source-oriented risk assessment of heavy metal(loid)s in agricultural soils around a multimetal smelting area near the Yellow River, China

Heavy metal(loid) (HM) contamination in agricultural soils, particularly in areas severely impacted by smelting industries, has attracted worldwide attention. In this study, agricultural soils were collected in a flourishing multimetal smelting area near the Yellow River in central China. By an integrated approach encompassing the positive matrix factorization model, ordinary kriging interpolation and hierarchical clustering analysis (PMF-OK-HC), a total of four major sources and their mass contributions were identified, namely, soil parent material (56.6%), industrial waste and Mo smelting (24.0%), metal smelting and traffic emissions (12.8%), and coal combustion (6.7%). On this basis, the health risk of HMs was evaluated by Monte Carlo simulations and showed that a higher risk, with a higher proportion of exceeding-thresholds risk, was observed for children than for adults in terms of both noncarcinogenic and carcinogenic risks. Exposure pathways of oral ingestion in children could result in a higher attributed risk than other pathways. Furthermore, source-oriented risk assessment (SORA) revealed that the sources of coal combustion, industrial waste and Mo smelting had the highest contributions to noncarcinogenic and carcinogenic risks. Overall, for effective environmental management in agricultural soil, the framework of SORA was verified as an effective tool in the identification of the priority control of HMs and their sources.

Geochemical characteristics and health risks of heavy metals in agricultural soils and crops from a coal mining area in Anhui province, China

Soil contamination by heavy metals (HMs) in mining areas is a major issue because of its significant impact on the environmental quality and physical health of residents. Mining of minerals used in energy production, particularly coal, has led to HMs entering the surrounding soil through geochemical pathways. In this study, a total of 166 surface soil and 100 wheat grain samples around the Guobei coal mine in southeast China were collected, and trace metal levels were determined via inductively coupled plasma mass spectrometry (ICP-MS). The average HMs (Ni, As, Cr, Cu, Pb, Cd, and Zn) concentrations were lower than the screening values in China (GB 15618-2018) but higher than the soil background values in the Huaibei Bozhou area of Anhui Province (except Zn), indicating HMs enrichment. Based on the geoaccumulation index (Igeo) and ecological risk index (IER), Cd pollution levels were low, while for the other metals the samples were pollution-free, and therefore no ecological risk warning was issued for the mining area. Both Cr and Pb had a higher noncarcinogenic health risks for adults and children. The lifetime carcinogenic risks (LCR) of Cr, Pb, and Cd were within acceptable levels. A positive matrix factorization (PMF) model identified two factors that could explain the HMs sources: factor 1 for Zn, Cd, and Pb, factor 2 for Ni, As, Cr, and Cu. Furthermore, HMs enrichment was observed in surface soil and the Carboniferous-Permian coal seams in the Guobei coal mine, which may suggest that coal mining is an important source for HMs enrichment in surface soil. Overall, this study provides a theoretical basis for undertaking the management and assessment of soil HMs pollution around a coal mine.

The spatial distribution of potentially toxic elements in the mountain forest topsoils (the Silesian Beskids, southern Poland)

Progressive industrialisation and urbanisation in recent decades have dramatically affected the soil cover and led to significant changes in its properties, which inevitably affect the functioning of other components of the forest ecosystems. The total content of Pb, Cd, Zn, Fe, Cr, Cu, Ni, As, and Hg was studied in twenty-five plots at different heights in the topsoil (organic and humus horizons) formed from the Carpathian flysch in the area of the Silesian Beskids (Western Carpathians). The aim of this article is to analyse the spatial distribution of potentially toxic elements in the mountain forest topsoil in different types of plant communities and to determine the relationship between altitude and potentially toxic elements contamination. The soils studied are acidic or very acidic, with an average range of 3.8 (H2O) and 2.9 (KCl). Concentrations of the metals Cd, Zn, Fe, Cr, Cu, Ni, and Hg on the plots that were analysed are within the range of permissible standards for forest ecosystems in Poland, while Pb and As exceed the permissible standards for this type of ecosystem. Spearman's rank correlation coefficient showed a high correlation between Fe-Cr (r(32) = 0.879, Pb-Hg r(32) = 0.772, Ni-Cr r(32) = 0.738, Zn-Cd r(32) = 0.734, and Cu-Hg r(32) = 0.743, and a moderate statistically significant positive correlation between Cu-Pb r(32) = 0.667 and As-Pb r(32) = 0.557. No correlation was found between altitude and the occurrence of potentially toxic elements. The geo-accumulation index (Igeo) index, on the other hand, indicates that Pb, As, and Cd have the highest impact on soil contamination in all study plots: it classifies soils from moderately to strongly polluted. The enrichment factor (EF) obtained for As and Hg indicates significant-to-very high enrichment in all areas studied. The potential ecological risk index (PLI) calculated for the sites indicates the existence of pollution in all areas examined. The highest risk categories (considerable to very high) are associated with cadmium and mercury.

Source-specific probabilistic contamination risk and health risk assessment of soil heavy metals in a typical ancient mining area

Heavy metal pollution (HMP) from mining operations severely threatens soil ecosystems and human health. Identifying the sources of soil heavy metals (HMs) and assessing source-specific risks are critical for developing effective risk mitigation strategies. In this study, a combination of methodologies including PMF, Monte Carlo analysis, soil pollution risk index, and a human health risk assessment model were utilized to investigate soil HM risks in a typical ancient mining area in Daye City, China, considering both environmental pollution and human health impacts. Cu emerged as the most significant soil pollution risk, whereas As posing the highest health risk. About 48.44 % of the multi-element integrated soil pollution risk has escalated to the heavy level. Furthermore, around 22.42 % of the non-carcinogenic risk (NCR) and 9.53 % of the carcinogenic risk (CR) exceeded unacceptable thresholds (THI > 1 for NCR and TCR > 1E-4 for CR). The PMF model identified four distinct sources: the smelting industry, traffic emissions, a combination of agricultural and natural factors, and mining activities. The mixed agricultural and natural source significantly impacted health risks, contributing 42.17 % to NCR and 53.88 % to CR, followed by the mining source, contributing 31.67 % to NCR and 24.07 % to CR. Interestingly, the mining source contributed the highest soil pollution risk at 42.45 %, while the mixed agricultural and natural source exhibited the lowest at 16.33 %. Furthermore, the study explored source-specific risk components by evaluating the contributions of different sources to specific elements. The mining source was identified as the focus for soil HMP control, followed by the mixed agricultural and natural source. Overall, this study provided an in-depth analysis of soil heavy metal risks in mining areas from the source apportionment perspective, which broadened the research framework of soil heavy metal source analysis and risk assessment, potentially providing scientific guidance for managing regional soil HMP.

Uncertainty Evaluation of Soil Heavy Metal(loid) Pollution and Health Risk in Hunan Province: A Geographic Detector with Monte Carlo Simulation

Research on soil heavy metal(loid) pollution and health risk assessment is extensive, but a notable gap exists in systematically examining uncertainty in this process. We employ the Nemerow index, the health risk assessment model, and the geographic detector model (GDM) to analyze soil heavy metal(loid) pollution, assess health risks, and identify driving factors in Hunan Province, China. Furthermore, the Monte Carlo simulation (MCS) method is utilized to quantitatively evaluate the uncertainties associated with the sampling point positions, model parameters, and classification boundaries of the driving factors in these processes. The experimental findings reveal the following key insights: (1) Regions with high levels of heavy metal(loid) pollution, accompanied by low uncertainty, are identified in Chenzhou and Hengyang Cities in Hunan Province. (2) Arsenic (As) and chromium (Cr) are identified as the primary contributors to health risks. (3) The GDM results highlight strong nonlinear enhanced interactions among lithology and other factors. (4) The input GDM factors, such as temperature, river distance, and gross domestic product (GDP), show high uncertainty on the influencing degree of soil heavy metal(loid) pollution. This study thoroughly assesses high heavy metal(loid) pollution in Hunan Province, China, emphasizing uncertainty and offering a scientific foundation for land management and pollution remediation.

Spatial distribution, source identification, and risk assessment of heavy metals in riparian soils of the Tibetan plateau

Riparian soils in the lower sections of the Lhasa River were chosen as the research focus, to examine the characteristics and sources of heavy metals in riparian soils of high-cold regions. To investigate the influence of various factors on the geographical distribution of heavy metals, three horizontal and one vertical profiles were considered. The geoaccumulation index, prospective ecological risk index, and enrichment factor were used to evaluate the extent of soil contamination. Correlation analysis and the positive-matrix-analysis receptor model were used to quantitatively examine the sources of the elements. According to the soil-evaluation, the topsoil was more polluted than the deep soil. Overall, the soil was slightly degraded and posed minor ecological concern. Cd was the primary contributor to the overall contamination, with moderate and considerable risk levels at certain locations. Five sources were identified for the six heavy metals. Transportation and agricultural production were the principal sources of Cd. Ni and Cr were mostly connected to agricultural practices and weathering of parent-soil materials. Pb and Zn were mostly related to geological history, geothermal development, and traffic pollution. Mineral resource development has had a major impact on Cu. Non-carcinogenic risk index of each heavy metal and their total value were <1, indicating they are not harmful to human health. The riparian soil of the Lhasa River Basin contains heavy metals from various sources; therefore, it is important to monitor these heavy metals. This study provides a scientific foundation for the safe utilization and classification of soils in high cold regions.

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.

Connection between health risk and heavy metals in agricultural soils of China: a study based on current field investigations

Heavy metal pollution in agricultural soil is a threat to people's health and sustainable development. However, there is currently no nationwide health risk assessment in China. In this study, we performed a preliminary assessment of heavy metals in agricultural soils of the Chinese mainland, and found obvious carcinogenic risks (total lifetime carcinogenic risk (TLCR) > 1 × 10-5). A similar spatial distribution pattern was found in soil heavy metal and the mortality of esophagus and stomach cancers. Combining the potential carcinogenic risk assessed by LCR for individual heavy metal with Pearson correlation, Geographical Detector (q statistic > 0.75 for TLCR, p < 0.05), and redundancy analysis (RDA), it was found that long-term exposure and intake route of heavy metals exceeding the maximum safety threshold (Health Canada standard) may induce digestive system (esophagus, stomach, liver, and colorectum) cancers in rural populations. Through Partial Least Squares Path Model (PLS-PM), it was also revealed that the LCR of heavy metals was closely related to the soil environmental background (path coefficients = 0.82), which in turn was affected by factors such as economic development and pollution discharge. The current research results highlight the potential carcinogenic risk to the digestive system associated with low-dose and long-term exposure to heavy metals in agricultural soils, and policymakers should propose countermeasures and solutions according to the local conditions.

Health risk assessment of trace metal(loid)s in agricultural soil using an integrated model combining soil-related and plants-accumulation exposures: A case study on Hainan Island, South China

Traditional health risk assessment of trace metal(loid)s (TMs) in agricultural soil exclusively considers direct soil-related exposure and may underestimate the health risks they pose. In this study, the health risks of TMs were evaluated using an integrated model that combined soil-related and plant-accumulating exposures. A detailed investigation of common TMs (Cr, Pb, Cd, As, and Hg) coupled with probability risk analysis based on a Monte Carlo simulation was conducted on Hainan Island. Our results showed that, except for As, the non-carcinogenic risk (HI) and carcinogenic risk (CR) of the TMs were all within the acceptable ranges (HI < 1.0, and CR < 1E-06) for direct soil-related exposure to bio-accessible fractions and indirect exposure via plant accumulation (CR substantially lower than the warning threshold 1E-04). We identified crop food ingestion as the essential pathway for TM exposure and As as the critical toxic element in terms of risk control. Moreover, we determined that RfDo and SFo are the most suitable parameters for assessing As health risk severity. Our study demonstrated that the proposed integrated model combining soil-related and plant-accumulating exposures can avoid major health risk assessment deviations. The results obtained and the integrated model proposed in this study can facilitate future multi-pathway exposure research and could be the basis for determining agricultural soil quality criteria in tropical areas.

Estimating human health risks associated with heavy metal exposure from bottled water using Monte Carlo simulation

Water is the most important non-organic compound for living cells, and the life of all living organisms depends on it. Water is not found purely in nature, but it always contains some solutes, suspended matters and soluble gases. In this study, 11 bottled water brands (500 mL) were sampled across the Kashan city market to determine the concentration of selected heavy metals (Cr, Cd, Pb, Ni and As) and evaluated their potential risks following consumption. The concentration range of Cr, Cd, Pb, Ni and As were 5-34 μg/L, 1.5-7 μg/L, 1-7 μg/L, 2-29 μg/L, Collapse

Key Words

• Bottled water
• Heavy metals
• Human risk assessment
• Kashan

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Affiliation(s)

Nezam Mirzaei Department of Environmental Health Engineering, Social Determinants of Health (SDH) Research Center, Kashan University of Medical Sciences, Kashan, Iran
Safa Kalteh Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Hakime Zamani-Badi Department of Health, Safety and Environment Management, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran
Heshmatallah Moradpour Department of Environmental Health Engineering, Social Determinants of Health (SDH) Research Center, Kashan University of Medical Sciences, Kashan, Iran
Zeinab Parmoozeh Department of Environmental Health Engineering, Social Determinants of Health (SDH) Research Center, Kashan University of Medical Sciences, Kashan, Iran
Mansour Baziar Department of Environmental Health Engineering, Ferdows Faculty of Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran

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Toxic Elements in Beans from Zhejiang, Southeast China: Distribution and Probabilistic Health Risk Assessment

This study described the distribution of As, Cd, Cr, Hg, and Pb in 692 bean samples from Zhejiang province, southeast China, and estimated the health risk using Monte Carlo simulation. The average levels of As, Cd, Cr, Hg, and Pb were 0.0349, 0.0379, 0.246, 0.0019, and 0.0246 mg kg-1. Correlation analyses showed very strong positive correlations for Cd-Pb in kidney beans and mung beans, Cd-As in black beans, and Pb-As in red beans. The target hazard quotients (THQs) were adopted for non-carcinogenic risk assessment, and THQs at the 50th percentile were all less than 1, indicating that there are no deleterious effects from rice exposure to these elements. When evaluating THQ for multiple elements, the certainty with a hazard index (HI) greater than 1 for children was 12.64%, for teens 11.54%, and for adults 1.01%. The sensitivity analysis reveals that the concentration of Cd in beans and ED (exposure duration) are the main principal factors that contributed to the total risk. The mean carcinogenic risks for children, teens, and adults were all less than 1 × 10-4, indicating no potential carcinogenic risk. Despite that, the routine monitoring of these elements, especially for Cd should be continued.

In Vitro Bioaccessibility and Health Risk Assessment of Arsenic and Zinc Contaminated Soil Stabilized by Ferrous Sulfate: Effect of Different Dietary Components

Iron-based materials have good stability in reducing the mobility and toxicity of heavy metals, but the behavior and human health risks of heavy metals could be affected by dietary components. This study investigated the effect of typical diets (lettuce, cooked rice and apples) on the bioaccessibility and morphological changes of arsenic (As) and zinc (Zn) in contaminated site after stabilization by ferrous sulfate (FeSO4). The results showed that the bioaccessibility of As and Zn were increased in a co-digestion system of food. The augmented effect on As bioaccessibility mainly occurred in the gastric phase: apple > lettuce > cooked rice (p < 0.05), while the augmented effect on Zn bioaccessibility mainly occurred in the intestinal phase: lettuce > apple > cooked rice (p < 0.05). FeSO4 weakened the dissolution effect of dietary components on As bioaccessibility, and reduced As bioaccessibility in the gastric and intestinal phases by 34.0% and 37.9% (p < 0.05), respectively. Dietary components and Fe fractions influenced the speciation and distribution of As and Zn. FeSO4 reduced the hazard quotient (HQ) and carcinogenic risk (CR) values of the contaminated soil by 33.97% and 33.59%, respectively. This study provides a reference for a better understanding of more realistic strategies to modulate exposure risks of heavy metal-contaminated sites.