PDF(Pubmed)
Abstract：
Existing models for estimating pesticide bioconcentration in earthworms exhibit limited applicability across different chemicals, soils and species which restricts their potential as an alternative, intermediate tier for risk assessment. We used experimental data from uptake and elimination studies using three earthworm species (Lumbricus terrestris, Aporrectodea caliginosa, Eisenia fetida), five pesticides (log Kow 1.69-6.63) and five soils (organic matter content = 0.972-39.9 wt %) to produce a first-order kinetic accumulation model. Model applicability was evaluated against a data set of 402 internal earthworm concentrations reported from the literature including chemical and soil properties outside the data range used to produce the model. Our models accurately predict body load using either porewater or bulk soil concentrations, with at least 93.5 and 84.3% of body load predictions within a factor of 10 and 5 of corresponding observed values, respectively. This suggests that there is no need to distinguish between porewater and soil exposure routes or to consider different uptake and elimination pathways when predicting earthworm bioconcentration. Our new model not only outperformed existing models in characterizing earthworm exposure to pesticides in soil, but it could also be integrated with models that account for earthworm movement and fluctuating soil pesticide concentrations due to degradation and transport.
摘要：
估计蚯蚓中农药生物浓度的现有模型在不同化学品中的适用性有限，土壤和物种限制了它们作为替代品的潜力，风险评估的中间层。我们使用了三种蚯蚓（Lumbricusterrestriris，卡利吉诺萨立克托底，费蒂达艾塞尼亚)，五种农药（logKow1.69-6.63）和五种土壤（有机质含量=0.972-39.9wt％）产生一级动力学积累模型。根据文献报道的402个内部蚯蚓浓度的数据集评估了模型的适用性，其中包括用于产生模型的数据范围之外的化学和土壤性质。我们的模型使用孔隙水或整体土壤浓度准确预测身体负荷，身体负荷预测的至少93.5％和84.3％在相应观测值的10和5倍内，分别。这表明，在预测蚯蚓生物浓缩时，无需区分孔隙水和土壤暴露途径，也无需考虑不同的吸收和消除途径。我们的新模型不仅在表征土壤中蚯蚓暴露于农药的特征方面优于现有模型，但是，它也可以与模型相结合，这些模型可以解释蚯蚓的运动以及由于降解和运输而导致的土壤农药浓度的波动。
