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Food safety is an important issue in the world. This study assessed the health risk for the Chinese public when consuming vegetables grown in China, based on 1335 data records from 220 published papers during 2007–2016. The results showed that the average of Pb, Cd, and Hg concentration in vegetables was 0.106, 0.041, and 0.008 mg/kg, which were lower than the maximum allowable concentrations, respectively. Leaf vegetables contained higher heavy metals than root vegetables and fruit vegetables. On a provincial scale, the highest Pb, Cd, and Hg concentrations in vegetables were determined by those in soil and atmosphere. The total health risk index showed that people in Guizhou, Yunnan, Guangxi, Hunan, Guangdong, Hubei provinces in southern China, and Liaoning Province in northeast China, faced a high risk of Pb, Cd, and Hg when consuming vegetables.

Heavy metals in the agricultural soils of reclaimed mining areas can contaminate food and endanger human health. The objective of this study is to effectively estimate the concentrations of heavy metals, such as zinc, chromium, arsenic, and lead, using hyperspectral sensor data and the random forest (RF) algorithm in the study area of Xuzhou, China. The RF’s built-in feature selection ability and modeling expressive ability in heavy metal estimation of soil were explored. After the preprocessing of the spectrum obtained by an ASD (analytical spectral device) field spectrometer, the random forest algorithm was carried out to establish the estimation model based on the correlation-selected features and the full-spectrum features respectively. Results of all the different processes were compared with classical approaches, such as partial least squares (PLS) regression and support vector machine (SVM). In all the experimental results, from the perspective of models, the best estimation model for Zn ( R 2 = 0.9061; RMSE = 6.5008) is based on the full-spectrum data of continuum removal (CR) pretreatment, and the best models for Cr ( R 2 = 0.9110; RMSE = 4.5683), As ( R 2 = 0.9912; RMSE = 0.5327), and Pb ( R 2 = 0.9756; RMSE = 1.1694) are all derived from the correlation-selected features. And these best models of these heavy metals are all established by the RF method. The experiments in this paper show that random forests can make full use of the input spectral data in the estimation of four kinds of heavy metals, and the obtained models are superior to those established by traditional methods.

Heavy metals are a common class of toxic contaminants in soil, water and air, yet their occurrence in indoor environments is less known. Heavy metals enter people's bodies through ingestion, inhalation and dermal contact, causing various diseases and even cancer. Here we review the concentrations, sources, influencing factors and hazards of heavy metals in indoor and outdoor dust. The average concentration of indoor metals in 23 samples from 19 regions is 509.5 ± 886.2 mg kg −1 for zinc, 149.0 ± 136.2 mg kg −1 for copper, 123.0 ± 438.1 mg kg −1 for lead, 78.3 ± 51.1 mg kg −1 for chromium, 37.8 ± 34.4 mg kg −1 for nickel and 2.3 ± 6.0 mg kg −1 for cadmium. The sources of heavy metals are complex, with industry and transportation as the main likely contributors. Reports on health risk assessment suggest that the impact of chromium and lead on children's health should not be underestimated.

In this study, we investigated the possible role of hemin in alleviating zinc (Zn), lead (Pb) and chromium (Cr) toxicity in rice seedlings grown hydroponically by analyzing the morphological and physiological parameters. Our results showed that exposure of rice seedlings to excess Zn, Pb or Cr could cause severe leaf chlorosis, inhibit photosynthetic activity and consequently suppress plant growth. The concentration of O 2 •− and H 2 O 2 significantly increased and the activities of antioxidative enzymes decreased in roots of rice seedlings under metal exposure. The combined treatments (hemin + ZnSO 4 , hemin + Pb(NO 3 ) 2 and hemin + K 2 Cr 2 O 7 ), on the other hand, significantly enhanced the photosynthesis- and plant growth-related parameters compared with their corresponding heavy-metal-stress alone. Combined treatments dramatically stimulated the activities of superoxide dismutase (SOD), ascorbic peroxidase (APX) and glutathione reductase (GR) as well as the concentrations of ascorbic acid (AsA) and glutathione (GSH) as compared with the metal- stress alone. The concentrations of reactive oxygen species (ROS, e.g. O 2 •− and H 2 O 2 ) were significantly reduced in the metal plus hemin treatments. Hemin addition also reduced metal accumulation in rice seedlings especially in root tissues. These findings suggest that hemin-elevated levels of antioxidants, activities of antioxidative enzymes and hemin-reduced accumulation of heavy-metal could confer resistance against Zn, Pb, and Cr stress in rice seedlings, resulting in improved pigments accumulation, photosynthetic attributes and plant growth.

Fresh water resources have always been an extremely invaluable economic and strategic resource in the world. There are about 1.4 billion people who have no access to pure water resources mainly due to the discharge of 95% of unpurified wastewater and 70% of industrial wastes into water resources in underdeveloped and developing countries. More than half of the world’s rivers are contaminated. Eighty percent of diseases are caused by contaminated waters in developing countries. Among the pollutants in these streams, heavy metals are of particular significance, as heavy metals do not dissolve and degenerate easily in nature. They also tend to bio-accumulate. This is why determining heavy metal concentrations is of great importance because it can help detect risk zones and risk levels. This study aims to determine the alteration of some heavy metal concentrations during a year in Bartin River on a point and seasonal base. Within the scope of the study, samples were collected from 5 chosen locations on Bartin River during a year and the alteration of Cu, Fe, Zn, Mn, Ni, and Pb concentration amounts were determined monthly. As a result of the study, it was determined that there were various rates of contamination with heavy metals at all stations, and that the amount of all studied heavy metal concentrations decreased depending on seasonal alteration when precipitation and hence the flow rates were high, and the highest concentrations were calculated in samples that were collected from L3 and L5 stations. Results shows that some of the toxic metals’ accumulations are higher than the suggestion of value, which recommended that the Bartin River is to some extent a toxic metal polluted river and that animals are not totally safe. Since this study constitutes a sample, all international samples should be controlled especially in the Organized Industrial Zone and foundation areas and the wastewater entering the river should be controlled and the pollution source should be determined and precautions should be taken. According to the results of the study, it also shows the water quality of the rivers in general. Pollution levels of rivers should be taken into account in the use of river water and care should be taken to use river water directly or indirectly in agricultural activities that may cause harm to human health. The results of this study can be a guide for identifying suitable areas to use the water of rivers. In future river planning, these studies will have an important guide value.

The indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0–30 cm and 30–60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0–30 cm and 30–60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716–0.751 (Cu), 2.981–3.327 (Fe), 23.464–30.113 (Zn), 1.115–1.21 (Pb), 2.6–2.912 (As), and 0.133–0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611–0.618 (Cu), 2.233–2.516 (Fe), 12.841–15.736 (Zn), 0.887–0.903 (Pb), 1.669–1.911 (As), and 0.091–0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster ( p  < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.

Potentially toxic elements from heavy metal pollution in soils and water pose significant health risks to humans and ecosystems. This study aims to assess heavy metal pollution in active dumpsite soils in northern Ondo State, Nigeria, and evaluate associated hazards across different Nigerian geological environments using multi-pollution indices and statistical optimization. Twenty-seven soil samples from three major active dumpsites around Owo and Ikare-Akoko were collected from nine profiles at different depths. These samples were analyzed for concentrations of various heavy metals including Na, K, Ca, Mg, Cr, Fe, Pb, Zn, Ni, and Mn. The concentration of earth and heavy metals were considerably low compared to other parts of Nigeria and Africa. Pairwise correlations among heavy metal concentrations in the three dumpsite soils revealed both strong and weak correlations. Only Fe–Zn showed a strong correlation. Interestingly, no common correlation was found among the three geological environments, indicating that the concentrations might not be impacted by the varying geological conditions. In Ondo State’s dumpsite soils, contamination factor (CF) ratings indicate moderate to very high contamination, while pollution load index (PLI) values suggest very high pollution. Index of geo-accumulation ( I geo )  and ecological risk factor (ERF) values reflect moderately high to very high pollution and low ecological risk, respectively. The mean I geo values follow this order: Cr < Ni < Mn < Zn < Pb < Fe (Tertiary environments); Cr < Ni < Mn < Pb < Zn < Fe (Cretaceous environments); and Ni < Cr < Zn < Mn < Pb < Fe (Basement environments). For mean ERF values, the order is Cr < Zn < Ni < Mn < Pb < Fe in Tertiary, Cr < Zn < Mn < Ni < Pb < Fe in Cretaceous, and Zn < Cr < Ni < Mn < Pb < Fe in Basement environments. The CF sequence is Cr < Ni < Zn < Mn < Pb < Fe in Tertiary, Cr < Zn < Ni < Mn < Pb < Fe in Cretaceous, and Cr < Ni < Zn < Pb < Mn < Fe in Basement environments. All samples exhibit extremely high contamination, with basement areas dominated by notably high Fe and other heavy metal concentrations, while the Tertiary environments show the lowest concentrations. Based on the research findings, regular monitoring and remediation efforts are essential in other areas to mitigate imminent pollution and risks.

Integrative passive samplers, such as DGT (Diffusive Gradients in Thin-films), are identified in European Technical Guidance Documents as promising tools to improve the quality of the assessment, in the context of the WFD (EU Water Framework Directive). However, DGT results cannot yet be used directly in a regulatory framework to assess the chemical status of water bodies, as DGT labile concentrations cannot be directly compared to the metal AA-EQSmarine water (Annual Average Environmental Quality Standard) established by the WFD, which are defined in the dissolved concentration. Therefore, prior to using DGT results in a regulatory context, for cadmium, nickel and lead, an adaptation of existing AA-EQSmarine water for DGTs should be pursued, ensuring at least the same level of protection. In this sense, in the framework of the MONITOOL project, a robust database of dissolved and labile metal concentrations in transitional and coastal waters, for adapting the existing AA-EQSmarine water for DGT technique, was obtained. Building on these results, this study proposes a methodology and provides values and equations for using DGT results for the chemical status assessment of marine waters, by adapting the EQSmarine water to adapted EQSDGT or predicting dissolved concentrations from DGT results. Based on available dataset, a first simulation of “chemical status” assessment per MONITOOL sampling site using DGT measured labile concentrations was carried out and the results were compared to an assessment based on dissolved concentration to check their compliance. These results demonstrate that the use of DGT passive samplers is appropriate for the metal concentrations level encountered in the marine environment. Further work is recommended to test the effectiveness of the methodology proposed in this study under WFD conditions on more sites and to establish common strategy guidelines for the use of DGT passive samplers in monitoring.

To obtain a general understanding of heavy metal contamination in peri-urban agricultural soils in China, this study investigates the concentrations of eight heavy metals, i.e., Cd, Pb, Zn, As, Cu, Cr, Hg, and Ni, in the peri-urban agricultural soils of 31 provincial capital cities in China. The data were obtained via exhaustive literature searches in both the Web of Science and China National Knowledge Infrastructure (CNKI) as well as from statistical yearbooks published in China. To evaluate the pollution status of each city and identify a variety of potential sources, various contamination indexes, e.g., the enrichment factor (EF), geoaccumulation index (Igeo), and integrated pollution index (IPI), were calculated based on the peri-urban agricultural soil dataset. The results of the analysis of the heavy metal concentrations, EF values and Igeo values showed that the peri-urban agricultural soils were enriched in most heavy metals, and Cd and Hg concentrations greatly exceeded the Chinese Environmental Protection Administration (CEPA) guidelines. The IPI results showed that 15 of the 31 cities, i.e., 48%, exhibited varying extents of heavy metal pollution. Although the mean IPI value for peri-urban agricultural soils in all cities (0.83) was slightly lower than that for urban soil (0.9), the IPI values for peri-urban agricultural soils from 65% of the cities were greater than those for urban soils, indicating that peri-urban agricultural soils are more polluted than urban soils in these large cities. These results are important for guiding future research on heavy metal pollution in peri-urban agricultural soils of presently expanding Chinese cities.

In this study, the pattern of metals concentration in water, sediment, plants, and three edible fish species ( Channa striata , Labeo rohita , and Catla catla ) of different trophic levels, captured from Jajmau (Kanpur), an important fishery area of river Ganga in Uttar Pradesh, India was examined. The heavy metals, Ni, Pb, Fe, Cu, Zn, Cd, Cr, and Co, were estimated in the liver, kidney, muscles, and gill tissues of abovesaid species of fish. The highest metal concentration was reported in the bottom feeder fish as compared with the column and surface feeders. The result obtained after analysis of water sample reflects the order of occurrence of heavy metals as Fe > Cr > Pb > Ni > Cd > Zn > Cu > Co. Sediments analysis indicates high concentration of Fe and Cr, making the entire environment from top to bottom, stressful. Target hazard quotient (THQ) and hazard index (HI) of the three species suggest a potential risk to the health of consumers, the humans. Thus, it is inevitable that the river Ganga should be closely monitored to safeguard human health. Graphical Abstract