Development of a model for environmental risk assessment of growth promoters

Growth promoters are applied in significant amounts to attain a faster growth of pigs. As a considerable amount of the applied growth promoters is discharged with the manure on agricultural fields, it seems reasonable to assess the environmental risk for the use of growth promoters. It will require development of a model to obtain the predicted environmental concentration (PEC). This paper presents a model which is able to predict the allocation of growth promoters in the seven compartments that are the state variables of the model, namely the amount of growth promoter per square meter in two soil layers on 50 and 200 cm, in the soil water in the same two layers, in surface water, in crops and in ground water. The model could in principle be used in a concrete case of manure applied as natural fertilizer, but as the model is presented it is aimed towards indicating where in the environment the highest concentration of growth promoters should be expected and at what time which can be used to set up an analytical program, and to indicate some `worst caseʹ concentrations to be able to estimate the risk. The model is applied to simulate concentrations in the environment of two widely applied growth promoters, olaquindox and tylosine. The highest concentrations in crops, fish, surface water and ground water are attained after 20–30 days and the `worst caseʹ situation may lead to concentrations of several μg/l or μg/kg in fish (about 2 μg/kg for olaquindox and about 6 μg/kg for tylosine), in crops (at harvest about 30 μg/kg for olaquindox and 70 μg/kg for tylosine) and in surface water (a few μg/l). The concentrations in ground water were in the order of 30 ng/l for olaquindox and 70 μg/l for tylosine. A sensitivity analysis indicates that it is extremely important to assess the biodegradability. The results clearly indicate that the biodegradability should be estimated if not known from the literature, to obtain a reasonable reliability of model predictions.