Bioaccessibility of heavy metals in soils cannot be predicted by a single model in two adjacent areas

Abstract

The objective of this study was to examine whether a single model could be used to predict the bioaccessibility of heavy metals in soils in two adjacent areas and to determine the feasibility of using existing data sets of total metal concentrations and soil property parameters (e.g., pH, total organic carbon, and soil texture) when predicting heavy metal bioaccessibility. A total of 103 topsoil samples were collected from two adjacent areas (Baotou and Bayan Obo). A total of 76 samples were collected from Baotou, and 27 were collected from Bayan Obo. The total and bioaccessible concentrations of arsenic (As), copper (Cu), lead (Pb), and zinc (Zn) were measured following complete composite acid digestion and a simple bioaccessibility extraction test. The average total concentrations of As, Cu, Pb, and Zn were 8. 95, 27.53, 28.40, and 79.50 mg/kg, respectively, in Baotou and 18.12, 30.75, 38.09, and 87.62 mg/kg in Bayan Obo. Except for As, these values were similar in both areas. The average bioaccessible heavy metal concentrations (Bio-HMs) for each target HM were also similar. In Baotou, the average Bio-HM values for As, Cu, Pb, and Zn were 1.16, 3.76, 16.31, and 16.10 mg/kg, respectively, and 1.26, 2.51, 14.31, and 8.68 mg/kg in Bayan Obo. However, the relative bioaccessibilities for each HM in Baotou were greater than those in Bayan Obo, with mean values for Pb, Zn, Cu, and As of 57, 20, 17, and 12 %, respectively, in Baotou and 40, 11, 9, and 8 % in Bayan Obo. In both areas, prediction models were successfully created using heavy metal concentrations and soil physicochemical parameters; however, models of the same target element differed between the areas, which indicated that a common model for both sites does not exist. Bio-HMs were highly affected by soil properties, which were found to differ between the adjacent areas. In addition, soil properties with large variations played major roles in the predictive models. This study highlights the importance of incorporating physical and chemical parameters that vary greatly when building predictive models of heavy metal bioaccessibility in soil. A similarity in soil properties between areas might be a prerequisite for the creation of a common predictive model for soil Bio-HMs.

Factors Affecting the Bioaccessibility and Intestinal Transport of Difenoconazole, Hexaconazole, and Spirodiclofen in Human Caco-2 Cells Followingin VitroDigestion

“…To have a negative health effect in the human body, a contaminant must be bioavailable, which relies on the degree of bioaccessibility. , Studies of bioaccessibility suggest that the amount of compound absorbed may be less than the level of a contaminant in the liquid or food. , However, despite this, most human risk assessments conservatively assume complete desorption of total concentrations, , potentially resulting in overestimates of the resulting risks. In recent years, bioaccessibility studies have therefore received a great deal of attention, having been used to evaluate the total content of heavy metals and other contaminants in soil and dust …”

Simulation of Heavy Metals Migration in Soil of Rare Earth Mining Area

“…In the mining area, the heavy metal content at Point 6 is much higher than that at Point 1, which may be related to mining activities (such as blasting and mineral transportation). Mining areas' unique geological formations may also be one of the reasons for the abnormal heavy metal content in this area (Zhu et al, 2016). The concentration of heavy metals at Point 4 was much higher than that at Point 7 for the dump area, which may be related to local transportation activities.…”

Study of Factors Influencing the Bioaccessibility of Triazolone in Cherry Tomatoes Using a Static SHIME Model

“…It is defined as the ratio of the fraction of contaminant mobilized from the food substrate during gastrointestinal digestion to the total amount of contaminants, enabling the correlation of contaminants in matrixes with the amount actually absorbed and metabolized by the gastric mucosa and intestinal epithelium [ 9 ]. Many studies have focused on the oral bioaccessibility of heavy metals [ 10 , 11 ] and other contaminants, e.g., mycotoxins [ 12 ] and polycyclic aromatic hydrocarbons (PAHs) [ 13 ]. For pesticide residues, a Simulator of the Human Intestinal Microbial Ecosystem (SHIME) method for assessing the dietary exposure of pesticide residue accurately have been adopted and shown to be serviceable, based on our previous work [ 14 , 15 ].…”