School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin, 300401, China.
School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin, 300401, China.
Chemosphere. 2021 Aug;277:130219. doi: 10.1016/j.chemosphere.2021.130219. Epub 2021 Mar 13.
In this study, an integrated migration and transformation (IMT) model based on microbial action, plant absorption, sediment release and substrate adsorption was firstly established to evaluate the temporal-spatial distribution of N and P in Lingang hybrid constructed wetland (CW), Tianjin. Compared to the conventional transformation model that only considers the microbial action, the IMT model could accurately predict the occurrence characteristics of N and P. In Lingang CW, NO-N (0.56-3.63 mg/L) was the most important form of N, and the TP was at a relatively low concentration level (0.04-0.07 mg/L). The spatial distribution results showed that a certain amount of N and P could be removed by CW. Form the temporal perspective, the N and P concentrations were greatly affected by the dissolved oxygen (DO). The simulated values obtained by IMT model indicated that the distribution of N and P was more affected by the temporality compared with the spatiality, which was consistent with measured values. Besides, the PCA indicated that TN, NO-N and DO were important factors, which affected the water quality of CW. The Nemerow pollution index method based on the simulated values indicated that Lingang CW was overall moderately polluted, and the subsurface area was the main functional unit of pollutants removal in CW. This work provides a new model for accurately predicting the occurrence characteristics of N and P pollutants in CW, which is of great significance for identifying its environmental risks and optimizing the construction of wetlands.
本研究建立了一种基于微生物作用、植物吸收、沉积物释放和基质吸附的综合迁移转化(IMT)模型,首次评估了天津临港混合人工湿地(CW)中氮磷的时空分布。与仅考虑微生物作用的传统转化模型相比,IMT 模型可以更准确地预测氮磷的发生特征。在临港 CW 中,硝态氮(NO-N)(0.56-3.63mg/L)是最重要的氮形态,总磷(TP)浓度处于较低水平(0.04-0.07mg/L)。空间分布结果表明,CW 可以去除一定量的氮和磷。从时间角度来看,氮和磷浓度受溶解氧(DO)的影响较大。IMT 模型模拟值表明,氮磷的分布受时间因素的影响大于空间因素,与实测值一致。此外,主成分分析(PCA)表明,总氮(TN)、硝态氮(NO-N)和 DO 是影响 CW 水质的重要因素。基于模拟值的内梅罗污染指数法表明,临港 CW 整体处于中度污染状态,地下区域是 CW 去除污染物的主要功能单元。本研究为准确预测 CW 中氮磷污染物的发生特征提供了一种新模型,对于识别其环境风险和优化湿地建设具有重要意义。