Soil Arsenic Concentrations Research Articles

Crop rotation and green manure type enhance organic carbon fractions and reduce soil arsenic content

Green manure incorporation has recently emerged as a promising strategy for mitigating heavy metals (HMs) contamination and enhancing soil quality. However, there are still many uncertainties regarding the effects of crop rotation and the type of incorporated green manure on soil organic carbon fractions and arsenic (As) mitigation in As-contaminated soil. Thus, a two-phase experiment was conducted to determine the effects of crop rotation and green manure type on the distribution of organic carbon fractions and As accumulation in soil and brown rice plants. It was found that green manure incorporation increases soil nutrient content with an increase in total carbon of 18.64 %, 18.10 %, and 19.83 % under BC-R, AS-R, and LP-R respectively, and enhances organic carbon fractions. Furthermore, soil As concentration was significantly decreased by green manure incorporation for 20.65 %, 20.02 % and 19.99 % under BC-R, AS-R and LP-R respectively while As concentration in brown rice various parts was under permissible limits. This study highlights the complex interactions between green manure-brown rice rotation and green manure incorporation on soil organic carbon fractions, and As content in soil and brown rice, and emphasizes further research to elucidate optimal cultivation strategies of continuous crop rotation and green manure incorporation for sustainable remediation of As-contaminated soils while ensuring food safety.

Predicting the risk of arsenic accumulation in soil-rice system in Asian monsoon region

Rice is a staple food for a significant portion of the global population. Arsenic (As) accumulated in rice grains influences rice quality which threatens human health. In this study, we used three machine learning models to predict arsenic accumulation in rice based on over 300 surveys. The prediction results of soil arsenic indicate that high-arsenic soil areas are mainly distributed in South and Southeast Asia such as India, China, and Thailand. In addition, higher bioaccumulation factors (BAF), associated with higher temperature, are predominantly observed in eastern India and southern Myanmar. However, arsenic content in soil is relatively lower in these areas. About 5.5 billion population may be threatened by the consumption of high-arsenic rice. It can be concluded that temperatures may influence the BAF except for soil arsenic, and soil physicochemical properties. Further research on the relationship between climate parameters and BAF should be conducted to address and adapt to future climate change. Additionally, understanding the mechanism of arsenic accumulation under different climatic conditions is crucial for developing agricultural technologies to reduce arsenic accumulation in rice.

Identification of key factors and mechanism determining arsenic mobilization in paddy soil-porewater-rice system

Arsenic (As) mobilization in paddy fields poses significant health risks, necessitating a thorough understanding of the controlling factors and mechanisms to safeguard human health. We conducted a comprehensive investigation of the soil-porewater-rice system throughout the rice life cycle, focusing on monitoring arsenic distribution and porewater characteristics in typical paddy field plots. Soil pH ranged from 4.79 to 7.98, while porewater pH was weakly alkaline, varying from 7.2 to 7.47. Total arsenic content in paddy soils ranged from 6.8 to 17.2 mg/kg, with arsenic concentrations in porewater during rice growth ranging from 2.97 to 14.85 μg/L. Specifically, arsenite concentrations in porewater ranged from 0.48 to 7.91 μg/L, and arsenate concentrations ranged from 0.73 to 5.83 μg/L. Through principal component analysis (PCA) and analysis of redox factors, we identified that arsenic concentration in porewater is predominantly influenced by the interplay of reduction and desorption processes, contributing 43.5 % collectively. Specifically, the reductive dissolution of iron oxides associated with organic carbon accounted for 23.3 % of arsenic concentration dynamics in porewater. Additionally, arsenic release from the soil followed a sequence starting with nitrate reduction, followed by ferric ion reduction, and subsequently sulfate reduction. Our findings provide valuable insights into the mechanisms governing arsenic mobilization within the paddy soil-porewater-rice system. These insights could inform strategies for irrigation management aimed at mitigating arsenic toxicity and associated health risks.

Characteristics and risk assessment of arsenic contamination in a lead and zinc plant area in Yunnan Province

Taking a lead and zinc plant plot in Yunnan as the research object, the land use status and planting types of the region were investigated, the original enterprise distribution area and crop growing area of the plot were defined, and 67 surface soil samples and 14 columnar soil samples were systematically arranged in the plot for monitoring. Combined with the monitoring results and analysis, it is concluded that there is no definite basis that the high arsenic content in soil in the region is caused by the enterprise production, and the high arsenic content in the region may be caused by the background value. Based on the monitoring and investigation results, the risk assessment of the area was carried out. The results showed that the non-carcinogenic risk and carcinogenic hazard index of arsenic exceeded the prescribed acceptable level when the area was developed as the second type of construction land, and soil remediation should be carried out. At the same time, the collaborative distribution monitoring of regional crops showed that the arsenic content of crops was low, which met the requirements of food standards, possibly because the cultivated crops did not have strong adsorption and enrichment effects on the arsenic occurrence form in the regional soil.

Distribution Prediction of Soil Heavy Metals Based on Remote Sensing Temporal-Spatial-Spectral Features and Random Forest Model

Obtaining soil heavy metal content characteristics and spatial distribution is crucial for preventing soil pollution and formulating environmental protection policies. We collected 304 surface soil samples (0-20 cm) in the Changqing district. At the same time, the spectral, temporal, and spatial features of soil heavy metals were derived from multi-remote sensing data; the temporal-spatial-spectral features closely related to soil heavy metals were selected via correlation analysis and used as input independent variables. The measured soil arsenic (As) content was used as the dependent variable to establish a spatial prediction model based on the random forest (RF) algorithm. The results showed the following:the As content in the soils exceeded the background value by 43.17% but did not exceed the risk screening values and intervention values, indicating slight heavy metal pollution in the soil. The accuracy ranking of the spatial prediction models with one feature type from high to low was spatial features (ratio of performance to inter-quartile range (RPIQ)=3.87)>temporal features (RPIQ=2.57)>spectral features (RPIQ=2.50). The spatial features were the most informative for predicting soil heavy metals. The models using temporal-spatial, temporal-spectral, and spatial-spectral features were superior to those using only one feature type, and the RPIQ values were 4.81, 4.21, and 4.70, respectively. The RF model with temporal-spatial-spectral features achieved the highest spatial prediction accuracy (R2=0.90; root mean square error (RMSE)=0.77; RPIQ=5.68). The As content decreased from the northwest to the southeast due to Yellow River erosion and industrial activities. The spatial prediction of soil heavy metals incorporating remote sensing temporal-spatial-spectral features and the random forest model provides effective support for soil pollution prevention and environmental risk control.

From ground to gut: Evaluating the human health risk of potentially toxic elements in soil, groundwater, and their uptake by Cocos nucifera in arsenic-contaminated environments

This study aimed to gauge the toxicity of potentially toxic elements (PTEs) in coconut crops cultivated in arsenic-contaminated areas while offering a global perspective encompassing more than 100 impacted countries. The current investigation provides crucial insights into the assessment of PTEs pollution using the Bioaccumulation factor, Geo-accumulation index, Potential ecological risk index, Hazardous index, and Lifetime cancer risk (LCR) and highlights the potential human health risks posed by contaminated food, water, and soil. From 22 severely polluted sites in West Bengal, India, soil, groundwater (GW), and coconut water (CW) samples were collected, acidified, and digested using microwave digestion, for PTEs quantification using inductively coupled plasma-optical emission spectroscopy (ICP-OES). Results revealed that despite high concentrations of arsenic in soils (4.6 ± 3.4 mg kg−1), and GW (22.2 ± 150.9 μg L−1), CW (0.7 ± 3.1 μg L−1) levels were within permissible limits. Groups of PTEs with comparable sources and distributions were discovered through Principal Component Analysis (PCA). A speciation diagram was used to predict the prevalence of arsenic species in all three matrices. The Hazardous Index (HI < 1) indicated no probability of non-carcinogenic diseases for children and adults in all the compartments. However, exposure to GW and soil contaminated with Cr, As, and Cd by children (9.02 × 10−13 to 2.77 × 10−4) and adults (6.51 × 10−14 to 1.18 × 10−4) would increase their susceptibility to cancer (LCR >10−6). The study concluded that moderate lifetime consumption of CW is safe and has no significant impact on healthy individuals. Additionally, CW is a rich source of essential micronutrients such as Zn, Fe, Mn, and B. Overall, the findings of this study could help in developing appropriate strategies for reducing PTEs contamination and protecting human health.

From risk assessment to land planning. The case of a trace element‐contaminated area in Chile

AbstractWhile abundant scientific literature focuses on diagnosing contaminated areas, solutions with a scientific base are far from balanced. This is the case of the Quintero‐Puchuncaví Bay, a widely known contaminated area in the central coast of Chile. Here, arsenic in soils surrounding the industrial complex has been reported as a threat to human health. However, land planning based on As contamination becomes a challenge since the whole area is identified as contaminated. Such a lack of land‐planning constrains the occupation and remediation of contaminated soil leading to a brownfield‐like landscape. To face this challenge, we proposed using a geospatial decision support system (S‐DSS) to integrate the contamination assessment, health and ecosystem risks, and potential land uses. When characterizing soil arsenic concentration thresholds for different land uses in a S‐DSS, we could categorize the land in suitable, caution, and unsuitable areas (based on human health risks). This way, we unravel areas with potential use in the current condition while also discerning caution and unsuitable categories, that can undergo extensive and intensive remediation techniques. Similarly, we took a conservational approach to estimate emerging risk from the industrial complex associated to explosions. Altogether, it highlights the potential of S‐DSS to integrate different geographic information. We finally feature two APPs regarding current land‐use suitability and a modeled one considering future arsenic emissions.

Phosphate-solubilizing fungi enhances the growth of Brassica chinensis L. and reduces arsenic uptake by reshaping the rhizosphere microbial community.

High concentrations of arsenic in soil and plant systems are a threat to human health and ecosystems. The levels of phosphate ions in the soil strongly influence the soil efficacy and arsenic absorption by plants. This study investigated the effects of phosphate-solubilizing fungi (PSF) on environmental factors and structural changes in microbial community in soils contaminated with arsenic. Four experimental groups were created: control (CK), Penicillium GYAHH-CCT186 (W186), Aspergillus AHBB-CT196 (W196), and Penicillium GYAHH-CCT186 + Aspergillus AHBB-CT196 (W186 + W196), with Pakchoi (Brassica chinensis L.) as the test plant. Analysis of altered nutrient levels, enzyme activities and microbial community structure in the soil as well as the growth and physiological characteristics of Pakchoi, revealed a significant increase in the available phosphorus (AP), organic matter (OM), cation exchange capacity (CEC) and available arsenic (AAs) content of the soil following W186 + W196, W196 and W186 treatments. All experimental treatments enhanced the activity of soil β-glucosidase (β-GC) and soil catalase (S-CAT). W186 + W196 and W196 treatments significantly enhanced soil acid phosphatase (S-ACP) activity. Besides, W186 + W196 treatment significantly induced dehydrogenase (S-DHA) activity. Further, of the treatment with PSF increased the fresh weight, root length, plant height and chlorophyll levels while decreasing the arsenic accumulation in Pakchoi. Exposure to PSF also increased the activity of Ascomycota, Basidiomycota, Chytridiomycota, unclassified_Fungi, Mortierellomycota, Cryptomycota and Rozellomycota in the soil. The relative abundance of Ascomycota, Basidiomycota, and Mortierellomycota was positively correlated with the available nutrients (except iron) in the soil as well as enzyme activities. Consequently, the PSF improved the quality of soil and the safety of Pakchoi, suggesting that PSF can be utilized for the remediation of arsenic-contaminated soil.

Lung cancer mortality and soil content of arsenic and cadmium: an ecological study in 26 EU countries

Abstract Background Environmental risk factors, such as exposure to air pollution, are linked with lung cancer. However, potential health impacts of exposure to carcinogenic pollutants in soil are less defined. In this ecological study, we evaluated at a regional scale potential associations between lung cancer mortality and the soil content of two carcinogens: arsenic and cadmium. Methods Data on deaths from lung cancer were from EUROSTAT. Soil content of arsenic and cadmium were from the Land use/cover area frame (LUCAS) 2009 survey. Analysis covered 26 EU countries and 21,035 sampling points. Three socioeconomic indicators and seven lung cancer risk factors were included. Data were linked at the NUTS2 level (n = 219) and analysed by negative binomial regression. Results After inclusion of significant predictors, the ratio of lung cancer mortality rates in the population resident in the regions within the highest quantile of arsenic concentration in soil, compared to the rest of the dataset, was 1.062 for females (95% CI 1.024 - 1.101) and 1.037 for males (95% CI 1.020 - 1.074). In the regions within the highest quantile of cadmium in soil, compared to the lower quantiles, the ratio of the mortality rates was 1.062 for females (95% CI 1.019 - 1.101) and 1.075 for males (95% CI 1.033 - 1.117). When data were stratified by land cover, significant (p &amp;lt; 0.05) positive associations in males were only shown for cadmium sampled from agricultural land (cropland and grassland) but not from the non-agricultural land. Conclusions Higher rates of lung cancer mortality were reported in regions with high concentration of arsenic or cadmium in soil, relative to regions with lower concentration. Due to the ecological design, this study cannot prove causality but is in agreement with other reports linking exposure to arsenic or cadmium and lung cancer. This warrants future investigations at a finer geographical scale, focused on regions with high soil levels of arsenic and cadmium. Key messages • Higher lung cancer mortality rates were reported in regions with high concentration of arsenic or cadmium in soil, relative to regions with their lower concentration. • There was an association between cadmium in soil and lung cancer mortality in males for the subset of sampling points from the agricultural land but not for the non-agricultural land.

Immobilization of arsenic in soil using modified bentonite and red mud to reduce its bio-availability in Brassica juncea

The influence of modified clay mineral and red mud on biological yield and arsenic bioavailability to mustard were investigated. The total biomass of the mustard was increased by application of clay mineral and red mud products. At higher doses (5.00 g/kg), Fe-bentonite treated soil recorded the highest total plant biomass (11.2 g/pot). DMSO-bentonite (1.23 mg/kg) and Fe-bentonite (1.28 mg/kg) were proved to be most effective in reducing the extractable arsenic concentration in soil at the rate of 5.00 g/kg doses. These products also help in lowering the hazard quotient (0.20–0.08) values for human consumption of arsenic through mustard leaf. This means that modified types of bentonites and red mud boost mustard productivity by reducing arsenic concentration.

Two-tiered mutualism improves survival and competitiveness of cross-feeding soil bacteria

Metabolic cross-feeding is a pervasive microbial interaction type that affects community stability and functioning and directs carbon and energy flows. The mechanisms that underlie these interactions and their association with metal/metalloid biogeochemistry, however, remain poorly understood. Here, we identified two soil bacteria, Bacillus sp. BP-3 and Delftia sp. DT-2, that engage in a two-tiered mutualism. Strain BP-3 has low utilization ability of pyruvic acid while strain DT-2 lacks hexokinase, lacks a phosphotransferase system, and is defective in glucose utilization. When strain BP-3 is grown in isolation with glucose, it releases pyruvic acid to the environment resulting in acidification and eventual self-killing. However, when strain BP-3 is grown together with strain DT-2, strain DT-2 utilizes the released pyruvic acid to meet its energy requirements, consequently rescuing strain BP-3 from pyruvic acid-induced growth inhibition. The two bacteria further enhance their collective competitiveness against other microbes by using arsenic as a weapon. Strain DT-2 reduces relatively non-toxic methylarsenate [MAs(V)] to highly toxic methylarsenite [MAs(III)], which kills or suppresses competitors, while strain BP-3 detoxifies MAs(III) by methylation to non-toxic dimethylarsenate [DMAs(V)]. These two arsenic transformations are enhanced when strains DT-2 and BP-3 are grown together. The two strains, along with their close relatives, widely co-occur in soils and their abundances increase with the soil arsenic concentration. Our results reveal that these bacterial types employ a two-tiered mutualism to ensure their collective metabolic activity and maintain their ecological competitive against other soil microbes. These findings shed light on the intricateness of bacterial interactions and their roles in ecosystem functioning.

Ground-Based Hyperspectral Retrieval of Soil Arsenic Concentration in Pingtan Island, China

The optimal selection of characteristic bands and retrieval models for the hyperspectral retrieval of soil heavy metal concentrations poses a significant challenge. Additionally, satellite-based hyperspectral retrieval encounters several issues, including atmospheric effects, limitations in temporal and radiometric resolution, and data acquisition, among others. Given this, the retrieval performance of the soil arsenic (As) concentration in Pingtan Island, the largest island in Fujian Province and the fifth largest in China, is currently unclear. This study aimed to elucidate this issue by identifying optimal characteristic bands from the full spectrum from both statistical and physical perspectives. We tested three linear models, namely Multiple Linear Regression (MLR), Partial Least Squares Regression (PLSR) and Geographically Weighted Regression (GWR), as well as three nonlinear machine learning models, including Back Propagation Neural Network (BP), Support Vector Machine Regression (SVR) and Random Forest Regression (RFR). We then retrieved soil arsenic content using ground-based soil full spectrum data on Pingtan Island. Our results indicate that the RFR model consistently outperformed all others when using both original and optimal characteristic bands. This superior performance suggests a complex, nonlinear relationship between soil arsenic concentration and spectral variables, influenced by diverse landscape factors. The GWR model, which considers spatial non-stationarity and heterogeneity, outperformed traditional models such as BP and SVR. This finding underscores the potential of incorporating spatial characteristics to enhance traditional machine learning models in geospatial studies. When evaluating retrieval model accuracy based on optimal characteristic bands, the RFR model maintained its top performance, and linear models (MLR, PLSR and GWR) showed notable improvement. Specifically, the GWR model achieved the highest r value for the validation data, indicating that selecting optimal characteristic bands based on high Pearson’s correlation coefficients (e.g., abs(Pearson’s correlation coefficient) ≥0.45) and high sensitivity to soil active materials successfully mitigates uncertainties linked to characteristic band selection solely based on Pearson’s correlation coefficients. Consequently, two effective retrieval models were generated: the best-performing RFR model and the improved GWR model. Our study on Pingtan Island provides theoretical and technical support for monitoring and evaluating soil arsenic concentrations using satellite-based spectroscopy in densely populated, relatively independent island towns in China and worldwide.

A Study on the Soil Passivation of Nano-Manganese Dioxide-Modified Biochar under High-Arsenic Water Irrigation

[Objective] The irrigation area in northern Henan is an important grain producing area in China. Native high arsenic groundwater exists in the area and has long been used for agricultural irrigation. Increased soil arsenic (As) content under long-term irrigation threatens the quality and safety of crop products. Soil passivation is the use of adding passivators to the soil to fix pollutants to achieve the purpose of limiting their migration. Therefore, the preparation of an efficient and clean passivator and its arsenic fixation effect in soil are important research areas to reduce the risk of high arsenic groundwater. [Method] Firstly, nano-manganese dioxide (MnO2)-modified biochar was prepared via the pyrolysis of sawdust biochar, potassium permanganate and manganese sulfate monohydrate at a mass ratio of 1:0.18:0.29. Secondly, the adsorption characteristics were explored using adsorption kinetics and adsorption isothermal experiments. Scanning electron microscopy (SEM), X-ray powder diffraction (XRD) feature mapping and other characterization methods were used to study its physical properties and adsorption mechanism. Finally, a potting experiment was designed to explore the changes in arsenic content in soil when the passivator dosages were 0%, 1% and 5%. [Results] (1) The nano-MnO2 modified biochar could reach the adsorption dynamic equilibrium after 180 min, and its maximum adsorption capacity was 58.12 μg/g. (2) When the dosing ratio was 1%, the fixed efficiency of soil effective As content in potted crops of unplanted crops and planted crops was 4.18–5.51% and 1.99–3.83%. When the dosing ratio was 5%, it was 7.48–8.75% and 5.58–9.58%. [Conclusions] The results show that when the addition ratio is 0–5%, the passivation effect of soil effective As is positively correlated with the passivator dosage.

Assessing the Impact of Altered Clay Mineral and Red Mud Derivatives on the Characteristics of Mustard (B. juncea) and the Soil Arsenic Content

A pot experiment was conducted during the winter season (rabi) of 2020-21 at ICAR-Indian Agricultural Research Institute, New Delhi. Indian mustard (Brassica juncea) was cultivated to investigate the impact of modified clay mineral (Bentonite) and Red mud on yield characteristics and total arsenic content in the soil. The main objective was to examine how the application of modified clay mineral and red mud (Fe-exchanged bentonite, Dimethyl sulfoxide-intercalated bentonite, and Iron-exchanged red mud) would affect the yield attributes of Indian mustard. The initial soil's total arsenic content was 16.2 mg kg-1. The results revealed that all the mentioned treatments led to a significant increase in leaf biomass and root volume compared to the control pot. Significantly, highest leaf biomass (g pot-1) was recorded in Fe-exchanged bentonite (4.10 g pot-1) followed by Dimethyl sulfoxide-intercalated bentonite (4.00 g pot-1), and Iron-exchanged redmud (3.93 g pot-1) respectively at the rate of 5.00 g product per kg soil. The highest root volume (6.6 cm2) was observed in soil treated with 5.00 g kg-1 of Fe-exchanged bentonite. Dimethyl sulfoxide-intercalated bentonite, and Iron-exchanged red mud also showed positive effects but to a lesser extent. total As content in contaminated soil was thoroughly investigated, and the results revealed that these clays did not exert a significant influence on the total As content under the given application rates.

Arsenic Levels in Soil and Rice and Health Risk Assessment via Rice Consumption in Industrial Areas of East Java, Indonesia

Industrial use of arsenic can potentially cause environmental problems in water, soil, and air. Arsenic is one of heavy metals that is highly toxic and carcinogenic. Arsenic contamination in the environment is harmful to human health because it can enter the body through the food chain. This study determined the concentration of arsenic in soil and rice and its impact on human health risks. Sampling was carried out in several East Java industrial cities or districts, for instance, Gresik, Mojokerto, Sidoarjo, Nganjuk, Ponorogo, and Surabaya. The measurement of arsenic in soil was done using Energy Dispersive X-Ray fluorescence (EDXRF), while the measurement of arsenic in rice was done by Total X-Ray Fluorescence (TXRF). The results showed that arsenic concentration in several areas of East Java has varying levels. The concentration of arsenic in soil was highest in Gresik (13,786 mg/kg). The highest arsenic concentration in rice was found in Mojokerto (0.154 mg/kg). The results of risk assessment in this study showed that the Hazard Quotient (HQ) value was &gt;1 and the Excess Cancer Risk (ECR) was &gt;10-4 in all areas at the age of children &lt;2 years. Health risk assessment of adults showed HQ&gt;1 and ECR&gt;10-4 in several areas of East Java. This indicates that consumption of rice contaminated with arsenic has the potential to pose non-carcinogenic and carcinogenic health risks.

Accumulation and transport of nutrient and pollutant elements in riparian soils, sediments, and river waters across the Thames River Watershed, Connecticut, USA

Understanding drivers of nutrient and pollutant elements (NPEs) in soils, sediments, and river water is important for protecting water resources and aquatic ecosystems. The objectives of this study were to quantify accumulation and transport of NPEs (P, As, Cd, Cu, Ni, Pb, and Zn) in riparian soils, sediments, river water, and watershed-scale exports within seven post-industrial subwatersheds of the Thames River, Connecticut, USA. Suspended sediments and river water samples were collected from February 2019 to January 2020. Arsenic concentrations in soil (6 to 18 mg kg−1) and sediments (8 to 85 mg kg−1) generally exceeded state and federal EPA quality targets but not river water. Elevated Pb ‘hot spots’ occurred in some riparian soils (>2000 mg kg−1) and sediments (>200 mg kg−1), but the other NPEs concentrations were below toxic thresholds. Riparian soil concentrations and watershed land cover were generally weak predictors for NPE concentrations in bottom sediments, suspended sediments, and river water. DOC, Mn, and Fe concentrations were important predictors for area-normalized dissolved and sediment-bound export of NPEs across the seven watersheds. Dissolved export was greater than sediment export for Mn, P, As, Cd, Cu, and Ni but not for Fe, Pb, and Zn. Watersheds with higher farmland had higher P river water concentrations, but the larger, more urbanized watershed had the highest total and area-normalized P export. An estuarine sediment core that captures sediment from the whole watershed and spans pre-industrial conditions through present shows that export of most NPEs has decreased since its peak, but all remain above baseline throughout the Thames River watershed. Future constraints on surface soil-river exchange and erosion inputs are needed to investigate rates of NPE sourcing to the watersheds.

Intercropping efficiency of Pteris vittata with two legume plants: Impacts of soil arsenic concentrations

Intercropping of hyperaccumulators with crops has emerged as a promising method for remediating arsenic (As)-contaminated soil in agroecosystems. However, the response of intercropping hyperaccumulators with different types of legume plants to diverse gradients of As-contaminated soil remains poorly understood. In this study, we assessed the response of plant growth and accumulation of an As hyperaccumulator (Pteris vittata L.) intercropped with two legume plants to three gradients of As-contaminated soil. Results indicated that soil As concentration had a substantial effect on the As uptake by plants. P. vittata growing in slightly As-contaminated soil (80 mg kg−1) exhibited higher As accumulation (1.52–5.49 folds) than those in higher As-contaminated soil (117 and 148 mg kg−1), owing to the lower soil pH in high As-contaminated soil. Intercropping with Sesbania cannabina L. increased As accumulation in P. vittata by 19.3%− 53.9% but decreased in intercropping with Cassia tora L. This finding was attributed to S. cannabina providing more NO3--N to P. vittata to support its growth, and higher resistance to As. The decreased rhizosphere pH in the intercropping treatment also resulted in the increased As accumulation in P. vittata. Meanwhile, the As concentrations in the seeds of the two legume plants met the national food standards(<0.5 mg kg−1). Therefore, the intercropping P. vittata with S. cannabina is a highly effective intercropping system in slightly As-contaminated soil and provides a potent method for As phytoremediation.

Relations between personal exposure to elevated concentrations of arsenic in water and soil and blood arsenic levels amongst people living in rural areas in Limpopo, South Africa

Exposure to arsenic even at low levels can lead to adverse health outcomes, however, there is a paucity of research from South Africa in relation to human exposure to arsenic. We investigated long-term exposure of residents in Limpopo province, South Africa, in a cross-sectional study by analysing water, soil and blood arsenic concentrations from two arsenic-exposed (high and medium–low exposure) villages and one non-exposed (control) village. There were statistically significant differences in the distribution of arsenic in water, soil and blood amongst the three sites. The median drinking water arsenic concentration in the high-exposure village was 1.75 µg/L (range = 0.02 to 81.30 µg/L), 0.45 µg/L (range = 0.100 to 6.00 µg/L) in the medium- / low-exposure village and 0.15 µg/L (range = < limit of detection (LOD) to 29.30 µg/L) in the control site. The median soil arsenic concentration in the high-exposure village was 23.91 mg/kg (range = < LOD to 92.10 mg/kg) whilst arsenic concentrations were below the limit of detection in all soil samples collected from the medium-/low-exposure and control villages. In the high-exposure village, the median blood arsenic concentration was 1.6 µg/L (range = 0.7 to 4.2 µg/L); 0.90 µg/L (range = < LOD to 2.5 µg/L) in the medium-/low-exposure village and 0.6 µg/L (range = < LOD to 3.3 µg/L) in the control village. Significant percentages of drinking water, soil and blood samples from the exposed sites were above the internationally recommended guidelines (namely, 10 µg/L, 20 mg/kg and 1 µg/L, respectively). Majority of participants (86%) relied on borehole water for drinking and there was a significant positive correlation between arsenic in blood and borehole water (p-value = 0.031). There was also a statistically significant correlation between arsenic concentrations in participants’ blood and soil samples collected from gardens (p-value = 0.051). Univariate quantile regression found that blood arsenic concentrations increased by 0.034 µg/L (95% CI = 0.02–0.05) for each one unit increase in water arsenic concentrations (p < 0.001). After adjusting for age, water source and homegrown vegetable consumption in multivariate quantile regression, participants from the high-exposure site had significantly higher blood concentrations than those in the control site (coefficient: 1.00; 95% CI = 0.25–1.74; p-value = 0.009) demonstrating that blood arsenic is a good biomarker of arsenic exposure. Our findings also provide new evidence for South Africa on the association between drinking water and arsenic exposure, emphasising the need for the provision of potable water for human consumption in areas with high environmental arsenic concentrations.

Assessing and Understanding Arsenic Contamination in Agricultural Soils and Lake Sediments from Papallacta Rural Parish, Northeastern Ecuador, via Ecotoxicology Factors, for Environmental Embasement

The concentration of arsenic (As), considered a toxic and carcinogenic metalloid, in agricultural soils has become a global challenge. Sources of arsenic in soils can be both anthropogenic and natural. Contaminated water is used for the irrigation of crops and vegetables, and therefore it is the main pathway for arsenic to enter the human food chain, creating a potential health risk. This study evaluated the concentrations of arsenic in agricultural soils in the rural parish of Papallacta, located 67 km east of the city of Quito, Northeastern Ecuador, and constitutes an analysis of the problem of arsenic in agricultural soils. Shallow groundwater and geothermal water discharges laced with arsenic are frequently used for irrigation and have raised the level of arsenic in agricultural soils. This work is focused on evaluating the environmental quality and contamination of agricultural soils through environmental quality indices such as geo-accumulation index, enrichment, and contamination factor. The average arsenic levels in the agricultural soils of the four studied areas fluctuate between 20.4 and 43.0 mg kg−1, while in the sediments of the Papallacta Lake, higher values were found in the range between 16.8 and 102.4 mg kg−1; all of which exceed the permissible limit by the Ecuadorian Environmental Legislation for agricultural use (12 mg kg−1). The results of the study in the five studied sites of the Papallacta civil parish indicate low to moderate levels of arsenic enrichment, soils enriched by bedrock, and moderate to considerable contamination.

Coupling phytotoxicity and human health risk assessment to refine the soil quality standard for As in farmlands.

In the present study, a field experiment was conducted to investigate arsenic (As) concentrations in soils and in grains of 15 rice varieties in a contaminated site in Taiwan. The studied site was divided into two experimental units, namely plot A and plot B. The results showed that mean total As concentrations were 70.94 and 61.80mgkg-1 in plot A and plot B, respectively, and thus greater than or approximate to the soil quality standard for total As in Taiwan (60mgkg-1). The As levels in rhizosphere soil in plot A (19.71-32.33mgkg-1) were much higher than in plot B (6.41-8.60mgkg-1); however, As accumulation in brown rice did not significantly differ between the plots. These results implied that a significant variation in the bioconcentration factor (BCF) value of As existed among different rice genotypes, and a negative correlation was observed between BCF value and rhizosphere As level in the soil. In phytotoxicity, the median values of the ecological risk indicator were 104.85 and 103.89 in plot A and plot B, respectively, indicating considerable risk. In human health risk assessment, the median and 97.5%-tile values for cancer risk for both male and female residents were markedly higher than the acceptable risk (1 × 10-4). Furthermore, non-cancer and cancer risks were higher for males than females, mainly due to the greater rice ingestion rate of males. Sensitivity analysis showed that total As concentration in soil was the main factor affecting health risks, suggesting that priority should be given to the reduction of soil As levels. To better manage the phytotoxicity of As on rice, as well as the health risk to residents resulting from exposure to As-contaminated soils, the soil quality standard for As in farmland soils should be set between 5 and 10mgkg-1. The methodology developed in this study could also be applied to provide the basis for refining and revising the soil quality standard for heavy metals in farmland in other regions and countries.