Constructed wetlands as post treatment of a decanter digester followed by an anaerobic filter

Abstract The amount of wastewater has increased due to the considerable expansion of higher education institutions. When wastewater is released without treatment or with inefficient treatment, it causes significant water pollution. In this context, this study evaluated the performance of Constructed Wetlands as a post-treatment of a decanter digester followed by an anaerobic filter, operated with effluent from the Federal University of Mato Grosso, Cuiabá Campus, Mato Grosso State. Four wetlands were constructed to develop the research: planted with Typha domingensis, planted with Heliconia psittacorum, planted with Pontederia parviflora, and not planted. The following physicochemical parameters were analyzed: Color, Turbidity, pH, Temperature, Total Solids, Total Dissolved Solids (TDS), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Nitrogen, Sulfate, Nitrate and Nitrite. The results show an organic matter removal efficiency with mean removal results: 70% BOD5 for TCW, HCW and PCW; and COD 76% for PCW. The mean removal of total phosphorus was 78% for PCW and 92% NO-2, as macronutrients. Analysis of variance ANOVA shows significance in the results of TDS, SO4 and COD removal.

摘要
随着高等院校办学规模的大幅扩张，废水排放量随之显著增加。若废水未经处理或处理效率低下便直接排放，将造成严重的水体污染。
在此背景下，本研究以巴西马托格罗索州库亚巴校区联邦大学（Federal University of Mato Grosso, Cuiabá Campus）的污水处理出水为待处理废水，评估了人工湿地（Constructed Wetlands）作为“滗析消化池-厌氧滤池”组合工艺后处理单元的处理性能。
本研究共设置4组人工湿地实验装置：分别种植香蒲（Typha domingensis）、鹦鹉赫蕉（Heliconia psittacorum）、小花凤眼蓝（Pontederia parviflora），以及一组未种植植物的对照组。
本次实验分析的理化参数包括：色度、浊度、pH值、水温、总固体（Total Solids）、总溶解固体（Total Dissolved Solids, TDS）、生化需氧量（Biochemical Oxygen Demand, BOD）、化学需氧量（Chemical Oxygen Demand, COD）、总氮、硫酸盐、硝酸盐及亚硝酸盐。
结果显示，各组人工湿地对有机物均表现出良好的去除效果：香蒲人工湿地（TCW）、鹦鹉赫蕉人工湿地（HCW）与小花凤眼蓝人工湿地（PCW）的五日生化需氧量（BOD₅）平均去除率均达到70%；小花凤眼蓝人工湿地的化学需氧量（COD）平均去除率为76%。
此外，小花凤眼蓝人工湿地对总磷的平均去除率为78%，对亚硝酸盐（NO₂⁻）的平均去除率达92%，二者均属于宏量营养元素。
方差分析（Analysis of Variance, ANOVA）结果表明，总溶解固体、硫酸盐及化学需氧量的去除效果具有统计学显著性。