铁-碳内电解质下4种水生植物的净水效果

为比较湿地生态系统中常见水生植物的净水效果,在铁-碳内电解质下以凤眼莲、睡莲、菖蒲、芦苇4种水生植物为研究对象,比较分析植物及其组合在不同试验时间(1～5 d)对污水中铵氮、化学需氧量(COD)、总磷(TP)的净化效果.结果表明:与无植物的对照相比,铁-碳内电解质下单种水生植物对污水中的铵氮、COD、TP去除效果更好,但物种间存在明显差异.在污水处理2 d时,凤眼莲对铵氮的去除率达到100%;3 d时,铵氮在菖蒲水体中的浓度接近0;各类型植物组合对铵氮的去除效果均较好.在污水处理2 d时,凤眼莲的水体COD浓度接近0,菖蒲次之,凤眼莲-菖蒲组合水体的COD浓度降为最低(4.33 mg·L^-1),去除率为85.1%.在处理4 d时,凤眼莲的TP浓度最低,芦苇次之;处理2 d时,凤眼莲-菖蒲水体的TP浓度最低.内电解质与植物的组合效果比单纯内电解质对污水的净化效果好,植物的配置应依据污染物水平进行优化.

Water purification of four aquatic plant species with the presence of iron-carbon interior electrolytic substrates.

To compare water purification of common aquatic plants in wetland ecosystem, four common aquatic plant species (Eichhornia crassipes, Nymphaea tetragona, Acorus calamus and Phragmites australis) were used as study species. The effect of aquatic plants on the change of sewage ammonium nitrogen, COD, TP content during different experimental time (1-5 d) with the presence of iron-carbon interior electrolytic substrates were analyzed in small scale experimental apparatus. The results showed that single and combined aquatic plants could effectively remove ammonium nitrogen, COD, TP from the sewage compared with the no-plant control group, but the efficiencies were significantly different among the different species. Ammonium nitrogen removal up to 100% was achieved with E. crassipes in two days, and A. calamus in three days. Each plant combination performed well on ammonium nitrogen removal. Concentration of the sewage COD approached zero with E. crassipes in three days, A. calamus performed secondly. The concentration of COD in combination of E. crassipes and A. calamus water decreased by 85.1% to a minimum of 4.33 mg·L^-1. The concentration of TP was the lowest with E. crassipes in four days, and second with P. australis. The lowest concentration of TP was found with the combination of E. crassipes and A. calamusin two days. The combination effect of interior electrolyte and plant was better than that of pure interior electrolyte on the purification of sewage. Plant configuration should be optimized according to the level of pollutants.