AQI prediction using layer recurrent neural network model: a new approach.

The air quality index (AQI) prediction is important to evaluate the effects of air pollutants on human health. The airborne pollutants have been a major threat in Delhi both in the past and coming years. The air quality index is a figure, based on the cumulative effect of major air pollutant concentrations, used by Government agencies, for air quality assessment. Thus, the main aim of the present study is to predict the daily AQI one year in advance through three different neural network models (FF-NN, CF-NN and LR-NN) for the year 2020 and compare them. The models were trained using AQI values of previous year (2019). In addition to main air pollutants like PM10/PM2.5, O3, SO2, NOx, CO and NH3, the non-criteria pollutants and meteorological data were also included as input parameter in this study. The model performances were assessed using statistical analysis. The key air pollutants contributing to high level of daily AQI were found to be PM2.5/PM10, CO and NO2. The root mean square error (RMSE) values of 31.86 and 28.03 were obtained for the FF-NN and CF-NN models respectively whereas the LR-NN model has the minimum RMSE value of 26.79. LR-NN algorithm predicted the AQI values very closely to the actual values in almost all the seasons of the year. The LR-NN performance was also found to be the best in post-monsoon season i.e., October and November (maximum R2 = 0.94) with respect to other seasons. The study would aid air pollution control authorities to predict AQI more precisely and adopt suitable pollution control measures. Further research studies are recommended to compare the performance of LR-NN model with statistical, numerical and computational models for accurate air quality assessment.

Parametric optimization of additive manufactured biocarrier submerged in sequencing batch reactor for domestic wastewater treatment.

The high nutrient concentration in domestic wastewater effluent can endanger the aquatic life via eutrophication. Thus, research have been carried out to prevent harm to aquatic life. In regard biofilm reactors have been successful by far with few limitations. Bio-carrier fabrication of desired shape is one of the limitations. Recently, the invention of additive manufacturing (AM) of object made it feasible to fabricate the desired shape. In this study additive manufactured bio‒carrier (AMB) was printed using AM technique, with high surface area to volume ratio as well as density higher than water. The submerged attach growth sequencing batch biofilm reactor (SAGSBBR) for organic and nutrient removal from domestic wastewater (DWW) was conducted to determine the optimum bio‒carrier filling ratio (FR) and cycle time (CT) by using response surface methodology (RSM) with CT ranging between 12 h and 24 h and FR ranging between 0 and 20%. The maximum chemical oxygen demand (COD), ammonia-nitrogen (NH4 +‒N), and total phosphorus (TP) removal was 96.8 mg/L, 93.32 mg/L, and 88.89 mg/L respectively, which was achieved in submerged attached growth sequential biofilm batch reactor with 10% FR (SAGSBBR‒10). The optimization study determined the optimal solution of CT and FR to be 17.07 h and 12.38% respectively, with desirability of 0.987. The predicted mean of responses for the optimal solution were 96.64%, 94.40% and 89.94% for COD removal, NH4 +‒N removal and TP removal, respectively. The rate of biomass attachment at the first stage in SAGSBBR‒10 and SAGSBBR‒20 was about 11.39 mg/carrier.d and 8.64 mg/carrier.d, whereas the highest accumulation achieved was 98.27 mg/carrier and 80.15 mg/carrier respectively. Thus, this study can assist us to achieve sustainable development goal (SDG) 6.

Simultaneous modelling of coagulant recovery and reuse by response surface methodology.

Surface water from rivers, lakes, reservoirs etc. needs to be treated prior to municipal supplies. The treatment scheme includes coagulation, flocculation, sedimentation, filtration and finally disinfection process. Huge volume of sludge or waste is generated during the coagulation-flocculation. Disposal of the sludge so generated in the treatment plants require careful consideration for managing it sustainably and in an environment friendly manner. Constructive utilization of the inevitable waste may help in finding a sustainable solution to sludge disposal problems. Presently, response surface methodology (RSM) with central composite design (CCD) has been applied to simultaneously model coagulant recovery as well as reuse parameters. In order to simplify the process and increase the applicability, the effect of three significant variables, acid dose, sludge ratio, and recovered coagulant dose are studied. A second order regression model has been developed which gave the optimum combination of acid dose of 30 ml/L, sludge ratio of 1% and recovered coagulant dose of 12 ml/L for maximum turbidity removal. The predicted value of turbidity removal is 95.4%. In the confirmatory experiments, the turbidity removal value was observed to be about 96.2%, which is in good agreement with the predicted value. In addition to turbidity removal, it also helps to effectively remove other impurities from the raw water for it to meet the standards prescribed for potable supply. Thus, the regenerated alum or recovered coagulant has the potential to substitute the conventional coagulants, fully or partially at water treatment plants.

Sludge quantification at water treatment plant and its management scenario.

Large volume of sludge is generated at the water treatment plants during the purification of surface water for potable supplies. Handling and disposal of sludge require careful attention from civic bodies, plant operators, and environmentalists. Quantification of the sludge produced at the treatment plants is important to develop suitable management strategies for its economical and environment friendly disposal. Present study deals with the quantification of sludge using empirical relation between turbidity, suspended solids, and coagulant dosing. Seasonal variation has significant effect on the raw water quality received at the water treatment plants so forth sludge generation also varies. Yearly production of the sludge in a water treatment plant at Ghaziabad, India, is estimated to be 29,700 ton. Sustainable disposal of such a quantity of sludge is a challenging task under stringent environmental legislation. Several beneficial reuses of sludge in civil engineering and constructional work have been identified globally such as raw material in manufacturing cement, bricks, and artificial aggregates, as cementitious material, and sand substitute in preparing concrete and mortar. About 54 to 60% sand, 24 to 28% silt, and 16% clay constitute the sludge generated at the water treatment plant under investigation. Characteristics of the sludge are found suitable for its potential utilization as locally available construction material for safe disposal. An overview of the sustainable management scenario involving beneficial reuses of the sludge has also been presented.

Characterization of water treatment sludge and its reuse as coagulant.

Coagulation-flocculation process results in the generation of large volume of waste or residue, known as water treatment sludge (WTS), in the purification of surface water for potable supplies. Sustainable management of the inevitable waste requires careful attention from the plant operators and sludge managers. In this study, WTS produced with the optimum alum dose of 30 ml/L at the laboratory scale has been treated with sulphuric acid to bring forth a product known as sludge reagent product (SRP). The performance of SRP is evaluated for its efficiency in removing the colloidal suspensions from the Yamuna river water over wide pH range of 2-13. 1% sludge acidified with sulphuric acid of normality 2.5 at the rate of 0.05 ml/ml sludge has been observed as the optimum condition for preparing SRP from WTS. The percentage turbidity removal is greater at higher pH value and increases with increasing the dosage of SRP. The optimum SRP dosage of 8 ml/L in the pH range of 6-8 performed well in removing the colloidal suspension and other impurities from the Yamuna water. The quality of treated water met the prescribed standards for most of the quality parameters. Thus, SRP has the potential to substitute the conventional coagulants partially or completely in the water treatment process, depending on the quality needed at the users end.