Centre for Water Resources Research, School of Architecture, Landscape and Civil Engineering, University College Dublin, Belfield, Dublin, Ireland.
J Environ Sci Health A Tox Hazard Subst Environ Eng. 2011;46(5):490-9. doi: 10.1080/10934529.2011.551729.
The objective of this study was to assess the suitability of statistical and the k-C* models to projecting treatment performance of constructed wetlands by applying the models to predict the final effluent concentrations of a pilot field-scale constructed wetlands system (CWs) treating animal farm wastewater. The CWs achieved removal rates (in g/m(2).d) ranging from 7.1-149.8 for BOD(5), 49.8-253.8 for COD and 7.1-47.0 for NH(4)-N. Generally, it was found that the statistical models developed from multiple regression analyses (MRA) were stronger in predicting final effluent concentrations than the k-C* model. However, both models were inadequate in predicting the final effluent concentrations of NO(3)-N. The first-order area-based removal rate constants (k, m/yr) determined from the experimental data were 200.5 for BOD(5), 80.1 for TP and 173.8 for NH(4)-N and these indicate a high rate of pollutant removal within the CWs.
本研究的目的是评估统计模型和 k-C模型在预测人工湿地处理性能方面的适用性，将模型应用于预测一个中试规模的人工湿地系统（CWs）处理养殖场废水的最终出水浓度。CWs 对 BOD（5）的去除率（以 g/m(2).d 计）为 7.1-149.8，对 COD 的去除率为 49.8-253.8，对 NH（4）-N 的去除率为 7.1-47.0。通常，发现基于多元回归分析（MRA）建立的统计模型在预测最终出水浓度方面比 k-C模型更强。然而，两种模型在预测 NO（3）-N 的最终出水浓度方面都不足。从实验数据确定的基于面积的一阶去除率常数（k，m/yr）分别为 BOD（5）200.5、TP 80.1 和 NH（4）-N 173.8，这表明 CWs 内的污染物去除率很高。
