Biochar-modified constructed wetlands using Eclipta alba as a plant for sustainable rural wastewater treatment.

Constructed wetlands (CWs) provide a low-cost, effective solution for domestic wastewater treatment in developing nations compared to costly traditional wastewater systems. Biochar which is an organic material created by pyrolysis offers straightforward, affordable methods for treating wastewater and lowering carbon footprint by acting as a substrate in CWs. Batch mode biochar-amended subsurface flow (SSF) CWs planted with Eclipta alba (L) with a hydraulic retention time (HRT) of 3 days were used for the treatment of rural domestic wastewater in the present investigation. Two control CWs, without plants (C1) and with plants (C2), and five different amendments of biochar 5% (B5), 10% (B10), 15% (B15), 20% (B20) and 25% (B25) in ratio with soil were set up to check the treatment efficiency of CWs. Removal efficiency (RE%) of the CWs for parameters namely chemical oxygen demand (COD), biochemical oxygen demand (BOD), phosphate (PO42-), sulphate (SO42-), nitrate (NO3-) and total Kjeldhal nitrogen (TKN) was determined using standard methods. Removal efficiency of 93%, 91%, 74% and 77% was observed for BOD, COD, nitrate and sulphate, respectively, in the B25 amendment at HRT 72 h. The highest removal of TKN (67%) was also observed in the B25 amendment at HRT of 72 h. No stable trend for the removal of phosphates was found during the study, and maximum removal was observed at HRT 48 h; afterward, phosphate was slightly inclined with the increasing HRT. The findings of one-way ANOVA using Tukey's test show significant variations (p < 0.05) in the removal efficiencies of pollutants after 72 h between two controls (C1 and C2) and various biochar amendments in CWs, indicating a significant role of the wetland plants and concentration of the biochar as substrate. Biochar shows a positive impact on the removal of organic pollutants and nitrates. Hence, biochar-amended CWs can be a sustainable way of treating rural domestic wastewater.

Determining groundwater quality using indices and multivariate statistical techniques: a study of Tosham block, Haryana, India.

Water is the most important component for human survival and often the most misused one. The present study deals with the assessment of groundwater quality of Tosham block, Bhiwani District, Haryana, India, and its nearby villages. A total of 23 samples were collected from different groundwater sources and were analysed for 16 different physico-chemical parameters. Correlation coefficients were calculated to identify highly correlated and interrelated water quality parameters. It provides an excellent tool for the prediction of parameter values within the reasonable rank of exactness. A strong correlation was observed between total hardness, magnesium and total dissolved solids, especially between total dissolved solids and electrical conductivity. The obtained results were compared with Indian Standard Drinking water specifications IS: 10500-2012. Concentration of total hardness, iron and chloride was found above the permissible limit in all the samples. Multivariate statistical techniques, namely cluster analysis and principal component analysis, were used to find the relationship between studied parameters. Water quality index (WQI) was also calculated. The WQI of groundwater samples ranged from 125 to 556. The water quality index revealed that out of 23 samples, 13 were found to have poor water quality and 6 samples were of very poor water quality. High value of WQI was found mainly from total dissolved solids, electrical conductivity, total hardness, Mg, Cl and Fe. Groundwater analysis of the studied water samples indicated that there is a need to treat the water before its use for drinking and other domestic activities. Necessary precautions should be taken to prevent the groundwater from being contaminated.

A multivariate statistical approach for monitoring of groundwater quality: a case study of Beri block, Haryana, India.

The present research deals with assessment of groundwater quality of Beri block, Jhajjar district, Haryana, India and its nearby villages. Multivariate statistics is an efficient technique to display relationship between different limiting factors. Around 24 groundwater samples were collected. A total of 16 variables were analysed: pH, potassium, total dissolved solids (TDS), hardness (calcium, magnesium and total), sulphate, sodium, electrical conductivity and phosphate, chloride (Cl-) and heavy metals, namely iron, chromium, lead and zinc. Principal component analysis is one of the commonly used tools in water quality assessment because it effectively reduces number of variables. Multivariate statistical tools "principal component analysis (PCA)" and "cluster analysis" were used to set up relationship among the studied parameters. PCA showed the existence of up to five significant PCs which account for 80.35% of the variance. Few parameters such as pH, sodium, potassium, sulphate, phosphate and zinc were found to be well within limits as approved by WHO and BIS, whereas parameters such as chloride, alkalinity, hardness, total dissolved solids and metals (Pb, Cr and Fe) were found to go beyond the prescribed limits. High levels of hardness, total dissolved solids and chlorides are responsible for saline behaviour of water. The correlation matrices for 16 parameters were executed. EC, TDS, chloride and total hardness were significantly and positively correlated with each other. pH and phosphate (PO42-) were negatively correlated with majority of the physicochemical variables. After studying the physiochemical properties of groundwater samples, it is recommended that water quality parameters should be analysed periodically to conserve the water resources and emphasis should be laid on water quality management practices.