浮床植物多样性及组合影响生活污水的净化效果

生态浮床系统是目前水环境综合治理领域的研究和应用热点,为了研究其植物多样性及组合对生活污水净化的影响,该研究以芦竹为建群种和优势种构建了5个多样性水平和2种组合模式,并比较分析了它们的植株生长、系统生产力和N、P、COD去除率。结果表明:随着多样性的增加,芦竹等湿地植物的单株生物量及相对生长速率(RGR)呈下降趋势,但中生植物的生存与生长受到促进。系统生产力随多样性的增加呈下降趋势,而N、P、COD去除率随多样性增加而显著增加。在同一多样性水平下,中生植物种占多数的组合虽然系统生产力低于湿地植物种占多数的组合,但前者的N、P、COD去除率高于后者。同一多样性及组合条件下,P去除率最高,N去除率次之,COD去除率最低。随着生态浮床系统建立时间的增加,N、P、COD去除率呈现先快速增加后缓慢降低的趋势。以上结果说明生态浮床系统中植物多样性及组合影响生活污水的净化效果,除了植物直接吸收与吸附外,微生物的去除作用可能更为重要。

Plant diversity and composition of ecological floating bed affect domestic sewage purification

Ecological floating bed system has been the hotspot of research and application in the comprehensive management of polluted water environment. In order to analyze the effects of its plant diversity and composition on purification of domestic sewage, we established five species diversity levels and two composition arrangements by using Arundo donax as dominant and constructive species, and measured the plant growth, system productivity and N, P, COD removal rates. The results showed that the individual biomass and relative growth rate(RGR)of wetland plants(such as A. donax)decreased with increasing species diversity, while the survival and growth of mesophytes were promoted. Higher species diversity decreased the productivity of the system, but increased significantly the removal rates of N, P and COD. At the same level of species diversity, the combination with more mesophytes had lower system productivity than that with more wetland plant species, but the former had higher N, P and COD removal rates. Under the same species diversity and combination, P removal rate was the highest, N removal rate was followed, and COD removal rate was the lowest. Moreover, their removal rates showed a trend of slow decline after rapid increase with time. These results indicate that the species richness and combination of ecological floating bed system can affect domestic sewage purification. In the process, pollutants can be removed by direct absorption and adsorption of plants, but the role of microorganisms may be more important.