Probabilistic Health Risk Assessment Research Articles

Multiple pathway exposure risks and driving factors of heavy metals in soil-crop system in a Pb/Zn smelting city, China

Heavy metals (HMs) in soil near metal smelting areas have attracted great interest due to their crucial threat to agricultural product safety and human health. We investigated HMs in agricultural soils and crops (wheat and maize) in a Pb/Zn smelting city, central China; analysed the exposure risk of HMs through multiple pathways in a soil-crop system through Monte Carlo simulations; and identified the key driving factors using random forest (RF) model. The results showed that most soil HMs exceeded their background level. Cd had the highest exceeding rate compared with the screening values and the highest exceeding rate (40%, in wheat) compared with the food safety limit. Additionally, Cd had the highest bioaccumulation capacity in both maize and wheat. In identifying the key driving factors of soil HMs, RF had a satisfactory prediction performance for As, Cd, and Pb, with corresponding R2 values of 0.47, 0.51, and 0.60, respectively, with the dominant factors being distance to the Pb/Zn smelter, coal washery, and road area, respectively. However, Cr and Hg exhibited lower R2 values which may be due to their limited influence from the selected anthropogenic, traffic, and industrial variables. Probabilistic health risk assessments through Monte Carlo simulations revealed that the non-carcinogenic risk was around the risk limit (HI=1), while the carcinogenic risk for both children and adults exceeded the risk limit (TCR=1E-04), and adults had higher carcinogenic risk than children, which was due to a longer duration of exposure and higher ingestion rate of crop grains in adults. Cd had the highest carcinogenic risk and the highest probability of exceeding the limiting risk. Briefly, levels of Cd in both soil and crops should be controlled, especially for the source of smelting emissions. The results of this study could be treated as valuable references for policymakers to formulate control strategies for soil HM pollution in agricultural areas near Pb/Zn smelting activities.

Analyzing heavy metal contamination for one of the high-rate consumption fruits in Iran: A probabilistic health risk assessment

Good health and well-being is one of the sustainable development goals (SDGs) that can be achieved through fruit consumption. This study measured cucumber (Cucumis sativus L.) heavy metal concentrations. Inductively coupled plasma-mass spectrometry (ICP-OES) was used to analyze the samples for heavy metal content. The uncertainty and sensitivity analyses of carcinogenic and non-carcinogenic heavy metal intake via cucumber (Cucumis sativus L.) consumption were assessed by Monte Carlo simulation. The mean ± SD levels of Cu, Pb, Zn, Cd, and As were determined to be 157.87 ± 128.54, 33.81 ± 6.27, 288.46 ± 114.59, 35.22 ± 18.67, and 33.6 ± 18.1 μg/kg, respectively. The 95th percentile of HI related to heavy metal intake via cucumber (Cucumis sativus L.) among children and adults were 2.64 and 1.75, respectively. Also, the 95th percentile of ELCR related to heavy metal were 8.26E-4 and 4.14E-3 among children and adults, respectively. The 95th percentile of LTCR of As among adults and As, Cd, and Pb among children were in the WHO target range (1E-04 to 1E-06) so reducing the concentration of them can help to reduce overall LTCR. When HQ and LTCR are below the cut limits, reducing heavy metals in high-consumption meals is a good way to lower them. In general, due to the wide consumption of various fruits, such as cucumber (Cucumis sativus L.), the concentration of environmental pollutants in their edible tissues should be monitored regularly, and the concentration of pollutants in these tissues should be minimized by proper planning.

Presence of heavy metals in pulses and cereals ploughed adjacent to the Rampal power plant: a probabilistic health risk assessment

ABSTRACT In a recent study, we examined the concentrations of heavy metals, namely lead (Pb), arsenic (As), nickel (Ni), cadmium (Cd), chromium (Cr) and copper (Cu), in seven categories of food, specifically rice, wheat, maize, lentil, black gram, mung bean and pea (B-22). The ranges of Ni, Cu, As, Cd, Cr and Pb in the food items were 0–4.7, 1.1–8.5, 0.01–8, 0.001–0.2, 0–4.7 and 0–0.8 mg per kg fresh weight (fw), respectively. The estimated daily intakes (EDIs) of As, Ni and Cr exceeded the maximum tolerable daily intake (MTDI), stipulating that these elements potentially originated from dietary consumption. The cumulative risk {target hazard quotient (∑THQ)} associated with food consumption was found to exceed in rice and maize, indicating that non-carcinogenic risks from heavy metals in these two dietary items may offer possible health problems for the population. The hazard index (HI) value was 1.4 × 101, indicating that the food items may encounter detrimental health consequences. However, the carcinogenic risk (CR) linked with total As from most of the food items (rice, wheat and maize) exceeded the acceptable level. From a human health perspective, our analysis revealed that the studied food items were declared safe for residents living near the Rampal power plant area in Bagerhat, Bangladesh. However, the present results suggest that regular monitoring of these essential and toxic elements in food items as well as in soil and irrigation water around the study area is necessary to prevent excessive build-up of these elements in the food chain.

Source-specific probabilistic health risk assessment of heavy metals in surface water of the Yangtze River Basin

The detrimental effects of heavy metal accumulation on both ecosystems and public health have raised widespread concern. Source-specific risk assessment is crucial for developing effective strategies to prevent and control heavy metal contamination in surface water. This study aims to investigate the contamination characteristics of heavy metals in the Yangtze River Basin, identifying the pollution sources, assessing the risk levels, and further evaluating the health risks to humans. The results indicated that the average concentrations of heavy metals were ranked as follows: zinc (Zn) > arsenic (As) > copper (Cu) > chromium (Cr) > cadmium (Cd) > nickel (Ni) > lead (Pb), with average concentrations of 38.02 μg/L, 4.34 μg/L, 2.53 μg/L, 2.10 μg/L, 1.17 μg/L, 0.84 μg/L, and 0.32 μg/L, respectively, all below the WHO 2017 standards for safe drinking water. The distribution trend indicates higher concentrations in the upper and lower reaches and lower concentrations in the mid-reaches of the river. By integrating the Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) receptor model and Positive Matrix Factorization (PMF) model, the main sources of heavy metals were identified as industrial activities (APCS-MLR: 41.3 %; PMF: 42.1 %), agricultural activities (APCS-MLR: 30.1 %; PMF: 27.4 %), and unknown mix sources (APCS-MLR: 29.1 %; PMF: 30.4 %). The calculation of the hazard index (HI) for both children and adults was <1, indicating no non-carcinogenic or carcinogenic risks. Based on the source-specific risk assessment, agricultural activities contribute the most to non-carcinogenic risks, while industrial activities pose the greatest contribution to carcinogenic risks. This study offers a reference for monitoring heavy metals and controlling health risks to residents, and provides crucial evidence for the utilization and protection of surface water in the Yangtze River Basin.

Health risk assessment of soil heavy metals in a typical mining town in north China based on Monte Carlo simulation coupled with Positive matrix factorization model

The accumulation of heavy metals (HMs) in soil caused by mineral resource exploitation and its ancillary industrial processes poses a threat to ecology and public health. Effective risk control measures require a quantification of the impacts and contributions to health risks from individual sources of soil HMs. Based on high-density sampling, soil contamination risk indexes, positive matrix factorization (PMF) model, Monte Carlo simulation and human health risk analysis model were applied to investigate the risk of HMs in a typical mining town in North China. The results showed that As was the most dominant soil pollutant factor, Cd and Hg were the most dominant soil ecological risk factors, and Cr and Ni were the most dominant health risk factors in the study area. Overall, both pollution and ecological risks were at low levels, while there were still some higher hazard areas located in the central and south-central part of the region. According to the probabilistic health risk assessment (HRA), children suffered greater health risks than adults, with 21.63% of non-carcinogenic risks and 53.24% of carcinogenic risks exceeding the prescribed thresholds (HI > 1 and TCR>1E-4). The PMF model identified five potential sources: fuel combustion (FC), processing of building materials with limestone as raw materials (PBML), industry source (IS), iron ore mining combined with garbage (IOG), and agriculture source (AS). PBML is the primary source of soil HM contamination, as well as the major anthropogenic source of carcinogenic risk for all populations. Agricultural inputs associated with As are the major source of non-carcinogenic risk. This study offers a good example of probabilistic HRA using specific sources, which can provide a valuable reference for strategy establishment of pollution remediation and risk prevention and control.

Appraisal of non-carcinogenic health risks posed by fluoride and iron in groundwater of a rural semi-arid part of India

ABSTRACT The study was initiated to evaluate groundwater quality in the post-monsoon season (2021) vis a vis chemistry and hydrochemical facies, assessment of probabilistic health risks posed by F− and Fe and quality appraisal of regional groundwater for irrigation in Kumarganj community development block. As per potable water quality standards of Bureau of Indian Standards (BIS), 50% and 13.3% of water samples were found to be unsafe due to F− and Fe, respectively. Fluoride concentration ranged from 0.1 to 3.62 mg l−1 (mean, 1.22 mg l−1). The northern, north-western and south-eastern parts of the block were found to have F− concentrations above the permissible safe limit of 1.0 mg F l−1 while a small area within southern region had >1 mg l−1 Fe. Factor analysis showed that four factors contributed to 38.21%, 19.67%, 10.62%, and 8.45%, respectively, to water quality. According to the human health risk assessment by Total Hazard Index, all age groups in the study area were at risk of exposure, in the order of THIchildren > THIinfant > THIadult due to consumption of excessive F− and Fe. This assessment was consistent with the results of probabilistic health risk assessment undertaken by Monte Carlo simulation (5000 trials) wherein maximum risk of 4.14 and 0.17 at 95th percentile to children was attributable to F− and Fe, respectively.

Spatiotemporal distribution of carbon monoxide dynamics and probabilistic health risk assessment: A comprehensive sensitivity analysis across India's state capitals

Carbon monoxide (CO) is a harmful trace gas produced from the incomplete combustion of fossil fuels. Carbon monoxide (CO) poses a substantial threat to human health. The objectives of this study were to investigate carbon monoxide (CO) annual and seasonal variations with meteorological factors, study the marginal effects of weather factors on CO, analyze the impact of independent variables (meteorological factors) importance on CO distribution, time series trend analysis (Mann-Kendall and Sen's slope, additive decomposition model, and linear trend model), study the spatial distribution of CO in the capital cities and non-carcinogenic health risk in India from 2019 to 2022. The study showed that CO concentrations varied, notably across different years (from 2019 to 2022), months, and seasons. The maximum annual CO (0.91 ± 0.17 mg/m3) concentration was recorded in 2019, while the lowest was (0.67 ± 0.12 mg/m3) in 2022. Seasonally, the winter season had the highest load of CO (ranging from 0.17 to 2.17 mg/m3) in the ambient atmosphere compared to the monsoon (0.08 to 1.38 mg/m3) and summer (0.10 to 1.50 mg/m3) seasons. The analysis of the importance of the independent variables (meteorological factors) on CO indicated that temperature had the most substantial impact on CO variation, followed by wind direction, relative humidity, and wind speed. The trend analysis using different models showed a declining trend in CO concentrations over the study period. The non-carcinogenic health risk HQ values were less than 1, suggesting no notable risk. The Monte Carlo simulation revealed that the 5th and 95th percentile range of HQ risk was 0.02 to 0.07 and the sensitivity analysis of non-carcinogenic risk at the state capital level was conducted, and revealed that Delhi was at a higher risk than Chandigarh, Patna, Gandhinagar, Bengaluru, Mumbai, and others, respectively. The results of this study on CO emissions will be beneficial in creating focused plans and policies to reduce CO pollution in seasonal influences and its effects on ambient air quality and public health in the capital cities of Indian states.

Heavy metals in centralized drinking water sources of the Yangtze River: A comprehensive study from a basin-wide perspective

Water quality in the Yangtze River Basin (YRB) has received considerable attention because it supplies water to 400 million people. However, the trends, sources, and risks associated with heavy metals (HMs) in water of centralized drinking water sources (CDWSs) in the YRB region are not well understood due to the lack of high-frequency, large-scale monitoring data. Moreover, research on the factors affecting the transportation of HMs in natural water are limited, all of which significantly reduce the effectiveness of CDWSs management. Therefore, this study utilized data on 11 HMs and water quality from 114 CDWSs, covering 71 prefecture-level cities (PLC) in 15 provinces (cities), to map unprecedented geospatial distribution of HMs in the YRB region and examine their concentrations in relation to water chemistry parameters. The findings revealed that the frequency of detection (FOD) of 11 HMs ranged from 28.59% (Hg) to 99.64% (Ba). The mean concentrations are ranked as follows: Ba (40.775 μg/L) > B (21.866 μg/L) > Zn (5.133 μg/L) > V (2.668 μg/L) > Cu (2.049 μg/L) > As (1.989 μg/L) > Mo (1.505 μg/L) > Ni (1.108 μg/L) > Sb (0.613 μg/L) > Pb (0.553 μg/L) > Hg (0.002 μg/L). Concentrations of Zn, As, Hg, Pb, Mo, Sb, Ni, and Ba exhibited decreasing trends from 2018 to 2022. Human activities, including industrial and agricultural production, have led to higher pollution levels in the midstream and downstream of the river than in its upstream. Additionally, the high concentrations of Ba and B are influenced by natural geological factors. Anion concentrations and nutrient levels, play a significant role in the transport of HMs in water. Probabilistic health risk assessment indicates that As, Ba, and Sb pose a potential carcinogenic risk. Additionally, non-carcinogenic risk to children under extreme conditions should also be considered.

Comprehensive distribution characteristics and factors affecting the migration of chromium in a typical chromium slag-contaminated site with a long history in China.

The contamination of abandoned chromium slag-contaminated sites poses serious threats to human health and the environment. Therefore, improving the understanding of their distribution characteristics and health risks by multiple information is necessary. This study explored the distribution, accumulation characteristic, and the role in the migration process of chromium. The results showed that the contents of total Cr and Cr (VI) ranged from 12.00 to 7400.00mg/kg, and 0.25 to 2160.00mg/kg, respectively. The average contents of both total Cr and Cr (VI) reached the highest value at the depth of 7-9m, where the silt layer retaining total Cr and Cr (VI) was. The spatial distribution analysis revealed that the total contamination area percentages of total Cr and Cr (VI) reached 7.87% and 90.02% in the mixed fill layer, and reduced to 1.21% and 34.53% in the silty layer, and the same heavily polluted areas were located in the open chromiumresidue storage. Soil pH and moisture content were the major factors controlling the migration of total Cr and Cr(VI) in soils. Results of probabilistic health risk assessment revealed that carcinogenic risk was negligible for adults and children, and the sensitive analysis implied that the content of Cr(VI) was the predominant contributor to carcinogenic risk. The combination of chemical reduction and microbial remediation could be the feasible remediation strategy for soil Cr(VI) pollution. Overall, this study provides scientific information into the chromium post-remediation and pollution management for various similar chromium-contaminated sites.

Concentration of Tetrabromobisphenol-A in fish: systematic review and meta-analysis and probabilistic health risk assessment.

Tetrabromobisphenol A (TBBP-A) is an emerging pollutant that enters water resources and affects various marine organisms, such as fish. Consequently, numerous studies globally investigated TBBP-A concentrations in fish fillets of the current study were meta-analyze concentration of TBBP-A in fish fillets and estimate the associated health risks for consumers. The search encompassed international databases, including Science Direct, PubMed, Scopus, Embase, and Web of Science from January 1, 2005, to July 20, 2023. The ranking of countries based on the pooled (Mean) concentration of TBBP-A in fish was as follows: China (1.157 µg/kg-ww) > Czech Republic (1.027 µg/kg-ww) > France (0.500 µg/kg-ww) ∼ Switzerland (0.500 µg/kg-ww) > Netherlands (0.405 µg/kg-ww) > Germany (0.33 µg/kg-ww) > Sweden (0.165 µg/kg-ww)>UK (0.078 µg/kg-ww) > Belgium (0.065 µg/kg-ww) > South Korea (0.013 µg/kg-ww) ∼ Japan (0.013 µg/kg-ww) > Ireland (0.005 µg/kg-ww). The risk assessment showed that the carcinogenic and non-carcinogenic risks of TBBP-A in China and France are higher compared to other countries; however, within all countries, these risks were found to be within acceptable limits.

Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area.

Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.

Determining priority control toxic metal for different protection targets based on source-oriented ecological and human health risk assessment around gold smelting area

Determining the priority control source and pollutant is the key for the eco-health protection and risk management around gold smelting area. To this end, a case study was conducted to explore the pollution characteristics, source apportionment, ecological risk and human health risk of toxic metals (TMs) in agricultural soils surrounding a gold smelting enterprise. Three effective receptor models, including positive matrix factorization model (PMF), ecological risk assessment (ERA), and probabilistic risk assessment (PRA) have been combined to apportion eco-human risks for different targets. More than 95.0% of samples had a Nemerow pollution index (NPI) > 2 (NPImean=4.27), indicating moderately or highly soil TMs contamination. Four pollution sources including gold smelting activity, mining source, agricultural activity and atmosphere deposition were identified as the major sources, with the contribution rate of 17.52%, 44.16%, 13.91%, and 24.41%, respectively. For ecological risk, atmosphere deposition accounting for 30.8% was the greatest contributor, which was mainly loaded on Hg of 51.35%. The probabilistic health risk assessment revealed that Carcinogenic risks and Non-carcinogenic risks of all population were unacceptable, and children suffered from a greater health risk than adults. Gold smelting activity (69.2%) and mining source (42.0%) were the largest contributors to Carcinogenic risks and Non-carcinogenic risks, respectively, corresponding to As and Cr as the target pollutants. The priority pollution sources and target pollutants were different for the eco-health protection. This work put forward a new perspective for soil risk control and management, which is very beneficial for appropriate soil remediation under limited resources and costs.

Probabilistic health risk assessment of heavy metals in rice produced in Mazandaran province, Iran

The purpose of this study was to assess the health risk of the heavy metals (HMs) (arsenic [As], cadmium [Cd], chromium [Cr], copper [Cu], iron [Fe], lead [Pb], Manganese [Mn], and zinc [Zn]) in rice produced in Mazandaran province (Amol and Mahmoudabad), Iran. A number of 60 rice samples were randomly collected and analyzed for the HMs by ICP-MS. The non-carcinogenic and carcinogenic health risks of the HMs were probabilistically assessed based on Monte Carlo simulation in terms of hazard quotient/index (HQ/HI) and incremental lifetime cancer risk (LTCR), respectively. The average concentration of HMs in rice grains in the studied areas was ranked as follows: Fe > Zn > Mn > Pb > Cu > Cr > As > Cd. THQΣmi showed that non-carcinogenic risk for area residents was largely related to Pb (1.77), As (0.59), Fe (0.57) and Cr (0.41). The average HI values of the HMs in rice produced in Amol and Mahmoudabad were assessed to be 2.42 (1.10–4.14) and 1.91 (0.43–3.9), respectively. The average LTCR values of the HMs in rice were in the following order: Cd (3.46 × 10−4 [1.34 × 10−4 to 6.96 × 10−4] for Amol and 3.97 × 10−4 [1.35 × 10−4 to 9.57 × 10−4] for Mahmoudabad) > As (8.60 × 10−5 [1.47 × 10−5 to 2.42 × 10−4] for Amol and 1.04 × 10−4 [6.17 × 10−6 to 2.83 × 10−4] for Mahmoudabad) > Cr (5.71 × 10−5 [2.88 × 10−5 to 9.61 × 10−5] for Amol and 4.75 × 10−5 [1.59 × 10−5 to 8.69 × 10−5] for Mahmoudabad). The average total LTCR value of the HMs in rice was within the acceptable range (10−6 to 10−4). The findings showed that exposure to the HMs via rice consumption could threaten human health, and an appropriate strategy to reduce concentrations of the HMs in rice is needed.

Probabilistic Health Risk Assessment of Aflatoxin M1 in Pasteurized Milk from Different Cities of Iran

Probabilistic Health Risk Assessment of Aflatoxin M1 in Pasteurized Milk from Different Cities of Iran

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation. For the Sundarban part of Bangladesh, the SOM clustering approach yielded six clusters, while it yielded five for the Indian Sundarbans. The SOM results showed high correlations among Ca2+, Mg2+, and K+, indicating a common origin. In the Bangladesh Sundarbans, mixed water predominated in all clusters except for cluster 3, whereas in the Indian Sundarbans, Cl−-Na+ and mixed water dominated in clusters 1 and 2, and both water types dominated the remaining clusters. Coupling of SOM, PMF, and ionic ratios identified rock weathering as a driving factor for groundwater chemistry. Clusters 1 and 3 were found to be influenced by mineral dissolution and geogenic inputs (overall contribution of 47.7%), while agricultural and industrial effluents dominated clusters 4 and 5 (contribution of 52.7%) in the Bangladesh Sundarbans. Industrial effluents and agricultural activities were associated with clusters 3, 4, and 5 (contributions of 29.5% and 25.4%, respectively) and geogenic sources (contributions of 23 and 22.1% in clusters 1 and 2) in Indian Sundarbans. The probabilistic health risk assessment showed that NO3− poses a higher PN-CHR risk to human health than F− and As, and that potential risk to children is more evident in the Bangladesh Sundarban area than in the Indian Sundarbans. Local authorities must take urgent action to control NO3− emissions in the Indo-Bangla Sundarbans region.

A probabilistic health risk assessment of potentially toxic elements in edible vegetable oils consumed in Hamadan, Iran

In this study, potential toxic element (PTEs) including lead (Pb), arsenic (As), cadmium(Cd), iron (Fe) and zinc (Zn) in traditional and industrial edible vegetable oils (peanut, sunflower, olive and sesame) collected from Hamadan, west of Iran were determined using Inductivity Coupled Plasma Optical Emission Spectrometry (ICP-OES). Besides, probabilistic health risk assessment (non-carcinogenic and carcinogenic risks) was identified via total target hazard quotient (TTHQ) and cancer risk (CR) by the Monte Carlo Simulation (MCS) model. The ranking of concentration PTEs in traditional and industrial edible vegetable oils was Fe > Zn > As > Pb > Cd. The in all samples, content of PTEs in industrial oils were upper than traditional oils (p < 0.001). The level of PTEs in most of vegetable oils was lower than permissible concentration regulated by Codex and national standard. In term of non-carcinogenic, consumers were at acceptable range (TTHQ < 1) due to ingestion both traditional and industrial vegetable oils content of PTEs. In term of carcinogenic, CR the both adults and children was higher than acceptable range (CR < 1E-6), Hence consumer are at unacceptable risk due to ingestion industrial vegetable oils content of inorganic As. Therefore, it is recommended to implement control plans for PTEs in vegetable oils consumed in Hamadan, Iran.

Source-specific probabilistic health risk assessment of potentially toxic elements in groundwater of a copper mining and smelter area

Source-specific probabilistic health risk assessment of potentially toxic elements in groundwater of a copper mining and smelter area

Bioaccessibility-corrected probabilistic health risk assessment of dietary metal(loid) exposure in six major food groups in children from Northwest China

Dietary exposure to heavy metals and metalloids [metal(loid)s] deserves increased attention; however, there is a lack of a comprehensive understanding of the risks of dietary exposure from multi-type food intake and multi-metal(loid) exposure using a bioaccessibility-corrected method. Here, we determined the concentration and bioaccessibility of six toxic metal(loid)s in six major food groups in an industrial city with intensive smelting activity. By incorporating children’s dietary patterns, the probability distribution of health risks from dietary metal(loid)s exposure was assessed. Marked differences were observed in the dietary exposure characteristics within metal(loid)s and major food groups. Cereal and vegetables were the major food groups local children intake. Cereals, meat, beans, and aquatic products had the highest concentrations of Cu and Cd, Pb and Cr, Ni, and As, respectively. Generally, meat, eggs, and aquatic products exhibited higher bioaccessibility than cereals, beans, and vegetables. The bioaccessibility of metal(loid)s decreased in the following order: Pb > Cr > Cu > Ni > As > Cd. For non-carcinogenic risks, the average hazard index was 7.3, with 99.6% exceeding acceptable levels. Arsenic was the dominant risk element and aquatic product was the main risk source. The aggregated carcinogenic risk was 3.4 × 10–3, with Cr the major risk contributor and cereals and meat the dominant food sources. The findings demonstrated that (1) the metal(loid) dietary exposure risk of children from areas with intensive smelting activities should be taken seriously, and (2) it is necessary to identify the specific food category and metal(loid) based on a comprehensive analysis of the metal(loid) concentration and bioaccessibility, and dietary habits of the population to effectively reduce risk.

Lettuce Response to Enhanced Struvite Recovered from Faecal Sludge Effluent and the Probabilistic Health Risk Assessment of Heavy Metals Through the Intake of the Lettuce.

Precipitating magnesium ammonium phosphate (MAP) to include potassium (K) has been explored to improve the fertilizing ability of the product. The present study aims to precipitate a MAP that also contains K and determine the probable risk to human health through the daily consumption of lettuce cultivated with the enhanced struvite. Analysis of the precipitate revealed that adding cocoa bean husk as seed produced MAP with potassium (K) content. The concentration of the heavy metals in the fresh leaves (concentration range, safe limits in mg/kg) was Cu (6.14 – 12.13, 73.3), Cd (0.11 – 0.43, 0.2), Ni (0.44 – 0.85, 67.9), Pb (0.85 – 1.38, 0.3). The estimated daily intake of heavy metals via the consumption of lettuce grown with struvite was below the tolerable upper dietary intake levels. The 95th percentile of the hazard index for the control, NPK and struvite are 0.047, 0.605, (0.214 – 0.759) respectively. The struvite produced can significantly improve its performance as an alternate phosphorus fertilizer and also show if struvite is safe for use as a fertilizer.

Dietary Exposure to Polycyclic Aromatic Hydrocarbons and the Probabilistic Health Risk Assessment of Eating Roasted Yams (Dioscorea Species) by African Population

The roasting of food is one of the oldest food preparation and preservation technologies. Although roasted foods have been associated with potential health hazards, this processing method is still used in many foods. This study was carried out to ascertain the health risks of ingesting white (Dioscorea rotundata), and bitter yam (Dioscorea dumetorum) roasted with firewood, charcoal, and charcoal augmented with PET bottles. The PAH content in all the roasted yam samples was identified and analyzed using gas chromatography-mass spectroscopy (GC-MS). A total of 8 PAHs were identified in both yam species; however, bitter yam roasted with augmented charcoal contained 9 PAHs. The total EDI showed that bitter yam roasted with augmented charcoal (6.59E-1) had the highest PAH content while white yam roasted with only charcoal contained the lowest (1.27E-1). The hazard quotients and indexes revealed that bitter yam had the highest HQ in all the roasting methods except for napathalene, fluoranthene and benzo (a) pyrene in samples roasted with charcoal.  The HI for both species in all the roasting methods was above 1 (&gt;1), while firewood produced the highest HI. Benzo (a) anthracene was the most potent PAH identified across the yam species and the roasting techniques. The evaluated ILCR showed that dibenzo (a, h) anthracene identified in white yam smoked with charcoal had the highest tendency to cause cancer (6.38E-1) while the least PAH was acenaphthylene (3.35E-6) which was seen in bitter yam roasted with charcoal. Therefore, it is necessary to inform the consumers of the possible health implications associated with consuming roasted yams and especially yam roasted with augmented charcoal