ABSTRACT
This study compares biochar (BCW) systems' pollutant removal effectiveness to conventional subsurface flow (CCW) in constructed wetland systems to treat textile wastewater. The two systems were identical in construction, but the biochar was 0.1 m thick over gravel and sand (maximum flow rate of 0.021 m3 h-1) as the primary medium over CCW (flow rate of 0.02 m3 h-1). The results revealed that the BCW approach was more efficient than the CCW system (pebble over sand and gravels) in removing and lowering heavy metals below thresh hold limits such as Cr, Cd, Cu, Pb, Ni, and Zn. The alkaline nature of textile water achieves neutrality in both CCW and BCW. However, BCW is more efficient due to a larger active surface area and the ability to filter out more metal and organic ions. TDS reduction efficiency in BCW was 53.07%, compared to 40.04% in CCW. Heavy metal removal was 100% in BCW at 3 to 12 h, whereas it takes 6 to 24 h in CCW (82% for Cr to 93% for Cu). The quick removal of Na from textile wastewater by BCW was reversed and achieved equilibrium in 24 h in contrast to the CCW system (> 24 h). The findings obtained at the lab scale level demonstrated that the BCW system was more effective in reducing TDS, neutralizing the alkalinity of textile wastewater, and removing heavy metals. This study strongly supports the potential application of biochar-constructed wetlands for textile wastewater treatment.
ABSTRACT
This study evaluated the effects of water stress on rice yield over Punjab and Haryana across North India by integrating Weather Research Forecasting (WRF) and Decision Support System for Agrotechnology Transfer (DSSAT) models. Indian Remote Sensing Satellite datasets were used to define land use/land cover in WRF. The accuracy of simulated rainfall and temperature over Punjab and Haryana was evaluated against Tropical Rainfall Measuring Mission and automated weather station data of Indian Space Research Organization, respectively. Data from WRF was used as weather input to DSSAT to simulate rice yield in Punjab and Haryana for 2009 and 2014. After simulated yield has been evaluated against district-level observed yield, the water balance components within the DSSAT model were used to analyze the impact of water stress on rice yield. The correlation (R2) between the crop water stress factor and the rice yield anomaly at the vegetative and reproductive stage was 0.64 and 0.52 for Haryana and 0.73 and 0.68 for Punjab, respectively. Severe water stress during the flowering to maturity stage inflicted devastating effects on yield. The study concludes that the regional climate simulations can be potentially used for early water stress prediction and its impact on rice yield.
