Dept. of Engineering, University of Ferrara, Via Saragat 1, I-44122 Ferrara, Italy; Terra&Acqua Technopole, University of Ferrara, Via Borsari 46, I-44121 Ferrara, Italy.
Dept. of Environmental Chemistry, Institute of Environmental Assessment and Water Studies (IDAEA), Spanish Council of Scientific Research (CSIC), Jordi Girona 18-26, E-08034 Barcelona, Spain.
Sci Total Environ. 2014 Feb 1;470-471:844-54. doi: 10.1016/j.scitotenv.2013.10.026. Epub 2013 Nov 5.
The aim of this study is to compare measured and predicted concentrations of 11 antibiotics and the antiepileptic carbamazepine in wastewater and surface water and to discuss the accuracy and usefulness of applied predictive models in assessing their concentrations. The occurrence (exposure assessment) of the target compounds was monitored in the influent and effluent of a large municipal wastewater treatment plant, and in its receiving water body, situated in the Po Valley, Italy. Information on the consumption and sales of pharmaceuticals in Italy, along with data related to their excretion and removal during wastewater treatment, were used to predict the concentrations of the selected pharmaceuticals for the studied site. The measured and predicted concentrations were compared for all three sampling points, and according to a criterion available in literature and already adopted in similar studies, the prediction was considered "acceptable" when the ratio of predicted and measured concentrations was between 0.5 and 2. The results show that the concentrations were accurately predicted for ciprofloxacin in wastewaters, and for azithromycin, trimethoprim and carbamazepine in surface water. For all the other compounds and sampling points, the difference between the measured and the predicted concentrations was very high. Possible reasons for these discrepancies are discussed and the main potential factors that influence both measured and predicted concentrations are identified by means of an assessment of the uncertainties in the measured values and sensitivity of all the parameters required for predicting concentration ones. The potential factors are sampling mode for measured values and dilution factor, removal and excretion for predicted ones.
本研究旨在比较废水和地表水中 11 种抗生素和抗癫痫药卡马西平的实测浓度和预测浓度，并讨论应用预测模型评估其浓度的准确性和实用性。目标化合物的出现（暴露评估）在意大利波河谷的一个大型城市污水处理厂的进水和出水以及其受纳水体中进行了监测。意大利的药品消费和销售信息，以及与污水处理过程中排泄和去除相关的数据，用于预测所选药品在研究地点的浓度。将实测浓度和预测浓度进行了比较，对于所有三个采样点，根据文献中提供的标准以及已经在类似研究中采用的标准，当预测浓度与实测浓度的比值在 0.5 到 2 之间时，预测被认为是“可接受的”。结果表明，在废水中，环丙沙星的浓度得到了准确的预测，而在地表水中，阿奇霉素、甲氧苄啶和卡马西平的浓度也得到了准确的预测。对于所有其他化合物和采样点，实测浓度与预测浓度之间的差异非常大。对这些差异的可能原因进行了讨论，并通过评估实测值的不确定性和预测浓度所需的所有参数的敏感性，确定了影响实测和预测浓度的主要潜在因素。潜在因素是实测值的采样模式和稀释因子，预测值的去除和排泄。
