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Updated: Jun 25, 2026

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
Published on: September 1, 2020
A chain modeling approach to estimate the impact of soil cadmium pollution on human dietary exposure
Eelco Franz1, Paul Römkens, Leo van Raamsdonk
1RIKILT-Institute of Food Safety, Wageningen University and Research Centre, Bornsesteeg 45, 6708 PD Wageningen, The Netherlands. eelco.franz@wur.nl
Abstract:
Cadmium in soil poses a risk for human health, due to its accumulation in food and feed crops. The extent of accumulation depends strongly on soil type and the degree of pollution. The objective of the present study was to develop a predictive model to estimate human dietary cadmium exposure from soil characteristics. This chain model consists of three basic steps: (i) calculation of plant cadmium levels from soil contamination levels and soil characteristics, (ii) calculation of animal transfer from consumption and contamination levels, and (iii) human exposure from both plant and animal products. Six soil scenarios were assessed, reflecting a specific contaminated region and ranging from 0.5 mg/kg of Cd (pH 4.5) to 2.5 mg/kg of Cd (pH 5.5). Cadmium levels in feed crops and vegetables were estimated with regression and mathematical models. Animal exposure and transfer to cattle kidneys, livers, and meat were calculated using a consumption database and a parameterized linear simulation model. Human exposure was estimated by Monte Carlo simulation, using a consumption database. The median human exposure for the different scenarios ranged from 0.24 to 0.98 microg/kg of body weight per day, which is comparable to results obtained from exposure levels based on observed field contamination data. The study shows that a chain model approach from soil contamination to human exposure, including animal exposure and transfer to animal products, can successfully be applied. The model can be used for fast evaluation of dietary cadmium exposure and the identification of risk areas based on soil conditions.
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