Heavy metals in soil-vegetable system around E-waste site and the health risk assessment

Effects of Artificial Sweat Formulation and Extraction Temperature on Estimation of the Dermal Bioaccessibility of Potentially Toxic Elements in a Contaminated Soil from an E-Waste Recycling Site

Informal recycling of electronic waste leads to soil contamination that can impact human health. To accurately assess exposure to potentially toxic elements (PTE) in soil it is necessary to consider their bioavailability through ingestion, inhalation and dermal contact. However, bioaccessibility tests that estimate dermal absorption following adhesion of contaminated soil particles to skin are not well established. In this study the concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn were estimated in the <45 µm particle size fraction of a bulk composite soil from an e-waste recycling site using five different artificial sweat formulations. Extractions were performed at temperatures ranging from 17 to 47 °C to investigate the effect of ambient temperature on bioaccessibility. Results obtained using the different artificial sweats were not consistent with one another. In particular, the NIHS 96-10 formulation solubilized larger amounts of analytes (ranging from 6.3 times the next most effective extractant for Cu to 1700 times the next most effective for Pb). There was a general increase in release of PTE with increasing temperature, except for As. Although trends varied between analytes and formulations, this highlights the need to consider ambient temperature when estimating dermal bioaccessibility of PTE in soil.

Health Risk Assessment of Metals via Multi-Source Oral Exposure for Children Living in Areas with Intense Electronic Manufacturing Activities

Oral ingestion is the predominant pathway of metal(loid)s exposure. In this study, the health risks of typical metal(loid)s (including Mn, As, Cr, Cd, and Pb) via multi-source, oral pathways for children aged 3-12 years, living in an area of China dominated by the electronic manufacturing industry, were studied based on the field sampling of duplicated diet, soil, and drinking water. Child-specific ingestion parameters were measured (except the soil ingestion rates, which were from a previous study of the same population), and a Monte Carlo method was applied to determine the uncertainty of the risk assessment. It was observed that children living in such environments were at risk of metal(loid)s exposure, with the accumulative carcinogenic risk exceeding the maximum acceptable level. Food intake was identified to be the primary exposure pathway. Moreover, Pb and Cr were the major risk elements to local children's health. Compared with primary school students, kindergarten children experienced a higher risk. This study highlights that high attention should be paid to children living in suburban areas dominated by the electronic manufacturing industry, and that priority should be given to studies on metal(loid)s exposure deriving from different types of food and their corresponding bioavailability, in order to further discern the precise risk sources to protect children's health.

Uptake and translocation of organophosphate esters by plants: Impacts of chemical structure, plant cultivar and copper

Organophosphate esters (OPEs) are normally used as flame retardants, plasticizers and lubricants, but have become environmental pollutants. Because OPEs are normally present alongside heavy metals in soils, the effects of interactions between OPEs and heavy metals on plant uptake of OPEs need to be determined. In this study, we investigated the effects of OPEs chemical structure, plant cultivar and copper (Cu) on the uptake and translocation of OPEs by plants. The bioaccumulation of OPEs varied among plant cultivars. They were preferentially enriched in carrot, with the lowest concentrations observed in maize. OPEs with electron-ring substituents (ER-OPEs) exhibited a higher potential for root uptake than did OPEs with open-chain substituents (OC-OPEs), which could be attributed to the higher sorption of ER-OPEs onto root charged surfaces. This was explained by the stronger noncovalent interactions with the electron-rich structure of ER-OPEs. The presence of Cu slightly reduced the distinct difference in the ability of roots to take up OC-OPEs and ER-OPEs. This was explained by the interactions of Cu ions with the electron-rich structure of ER-OPEs, which suppressed the sorption of ER-OPEs on the root surface. A negative relationship between the logarithms of the translocation factor and octanol-water partition coefficient (K_ow) was observed in treatments with either OPEs only or OPEs + Cu, implying the significant role of hydrophobicity in the OPEs acropetal translocation. The results will improve our understanding of the uptake and translocation of OPEs by plant cultivars as well as how the process is affected by the chemical structure of OPEs and Cu, leading to improvements in the ecological risk assessment of OPEs in the food chain.

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Potentially toxic element (PTE) pollution in farmland soils and crops is a serious cause of concern in China. To analyze the bioaccumulation characteristics of chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) in soil-rice systems, 911 pairs of top soil (0–0.2 m) and rice samples were collected from an industrial city in Southeast China. Multiple linear regression (MLR), support vector machines (SVM), random forest (RF), and Cubist were employed to construct models to predict the bioaccumulation coefficient (BAC) of PTEs in soil–rice systems and determine the potential dominators for PTE transfer from soil to rice grains. Cr, Cu, Zn, and Ni contents in soil of the survey region were higher than corresponding background contents in China. The mean Ni content of rice grains exceeded the national permissible limit, whereas the concentrations of Cr, Cu, and Zn were lower than their thresholds. The BAC of PTEs kept the sequence of Zn (0.219) > Cu (0.093) > Ni (0.032) > Cr (0.018). Of the four algorithms employed to estimate the bioaccumulation of Cr, Cu, Zn, and Ni in soil–rice systems, RF exhibited the best performance, with coefficient of determination (R2) ranging from 0.58 to 0.79 and root mean square error (RMSE) ranging from 0.03 to 0.04 mg kg−1. Total PTE concentration in soil, cation exchange capacity (CEC), and annual average precipitation were identified as top 3 dominators influencing PTE transfer from soil to rice grains. This study confirmed the feasibility and advantages of machine learning methods especially RF for estimating PTE accumulation in soil–rice systems, when compared with traditional statistical methods, such as MLR. Our study provides new tools for analyzing the transfer of PTEs from soil to rice, and can help decision-makers in developing more efficient policies for regulating PTE pollution in soil and crops, and reducing the corresponding health risks.