研究了创新的分散式多级人工湿地(DMCW)处理机构废水的性能,涵盖了三个季节。带有美娜百合的DMCW系统可有效去除有机物污染物,如COD和BOD,和废水中的营养物质,显示其对气象因素的依赖性。总的来说,夏季表现最高,季风表现最低,夏季COD去除率为85.6%,冬季为82.5%,季风为61.2%。去除TSS(67.7-85.5%),PO43--P(52.1-64.4%),NH4+-N(56.6-71.6%),NO3--N(47.3-63.4%)和NO2--N(62-75.4%)与Cr等重金属一起实现,Mn,Fe,Ni,Cu,Zn,As,Cd,Hg和Pb。弧菌等病原体的去除率>98%,大肠杆菌95%,假单胞菌99%,观察到63%的气单胞菌。COD的质量去除率在夏季最大(97.3g/m2/d),其次是冬季(78.7g/m2/d)和季风(43.5g/m2/d)。通过气相色谱-质谱(GCMS)和傅里叶变换红外光谱(FTIR)强调了处理过程中的大部分有机物去除,证实了废水是复杂的。美娜百合在治疗过程中积累了各种元素和氧化物,对其健康没有压力。处理后的水质在允许的范围内,适合灌溉目的。花园中更好的植物健康和增加的微生物多样性证明了处理过的水适合灌溉活动。使用Mann-WhitneyU检验和主成分分析等统计工具对结果进行了验证。
The performance of an innovative decentralized multistage constructed wetland (DMCW) treating institutional wastewater is studied covering three seasons. The DMCW system with Canna lily efficiently removed organics contaminants like COD and BOD, and nutrients from the wastewater, showing its dependency on meteorological factors. Overall the performance is maximum in summer and least in monsoon, with a COD removal of 85.6% in summer followed by 82.5% in winter and 61.2% in monsoon. Removal of TSS (67.7-85.5%), PO43--P (52.1-64.4%), NH4+-N (56.6-71.6%), NO3--N (47.3-63.4%) and NO2--N (62-75.4%) were achieved along with heavy metals like Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, Hg and Pb. Removal of pathogens like Vibrio is >98%, E. coli 95%, Pseudomonas 99%, and Aeromonas 63% was observed. Mass removal rate of COD was maximum in summer (97.3 g/m2/d) followed by winter (78.7 g/m2/d) and monsoon (43.5 g/m2/d). Majority of organics removal during the treatment was highlighted through Gas Chromatography-Mass Spectrometry (GCMS) and Fourier Transform Infrared Spectroscopy (FTIR) confirmed wastewater to be complex. The Canna lily accumulated various elements and oxides during the treatment with no stress on its health. The treated water quality is within the permissible limits and stands suitable for irrigational purposes. Better plant health and increased microbial diversity in the garden proves the suitability of treated water for irrigational activities. The results were validated using statistical tools like Mann-Whitney U test and principal component analysis.