Characteristics and treatment of greywater—a review

Safe and sufficient quantity of water is necessary for a healthy growth of human beings. The gap between water demand and available water supply is increasing day by day. Proper sanitation, especially decentralized approach, can solve the problem of water supply and wastewater management and that can be done by reuse of greywater. Typically, from a household, greywater (GW) flow is around 65 % of the total wastewater flow. Further light greywater is around 50 % of the total GW. Hence, GW has a high potential for recycle and reuse. The aim of this article is to reveal the present state of art in GW treatment and to identify the further scope for research. Present article contains a review on per capita GW generation, GW characteristics, and its treatment. Around 22 treatment systems comprising different treatment processes are discussed in detail for removal efficiency of pollutants, effluent concentrations and their compliance with wastewater reuse guidelines and standards. Constructed wetland and filtration were found efficient in the removal of most of the reuse parameters compared to other technologies. Anaerobic followed by aerobic system with post-disinfection unit may be a sustainable option for GW treatment for reuse. There is a need to develop the technologies for GW treatment at household level to increase the reuse practises at grass root level. Further, there is need of development of flow diagram with different technologies by targeting the type of reuse (flushing, gardening, agriculture, etc.).     

Vermicomposting of source-separated human faeces by Eisenia fetida: effect of stocking density on feed consumption rate, growth characteristics and vermicompost production

The main objective of the present study was to determine the optimum stocking density for feed consumption rate, biomass growth and reproduction of earthworm Eisenia fetida as well as determining and characterising vermicompost quantity and product, respectively, during vermicomposting of source-separated human faeces. For this, a number of experiments spanning up to 3 months were conducted using soil and vermicompost as support materials. Stocking density in the range of 0.25-5.00 kg/m² was employed in different tests. The results showed that 0.40-0.45 kg-feed/kg-worm/day was the maximum feed consumption rate by E. fetida in human faeces. The optimum stocking densities were 3.00 kg/m² for bioconversion of human faeces to vermicompost, and 0.50 kg/m² for earthworm biomass growth and reproduction.     

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box–Behnken design

Purpose  

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control.     

广州市城区站点冬季PM2.5时间变化及碳氮同位素组成特征

于2018年冬季在广州城区磨碟沙站点开展细颗粒物(PM_2.5)样品采集,并获得PM_2.5中水溶性离子、含碳组分、稳定碳氮同位素的组成及时间变化特征,重点讨论了PM_2.5浓度升高时段的化学组成特征变化,进而利用稳定碳氮同位素变化特征探究了主要污染来源。结果表明：采样期间,研究站点PM_2.5平均质量浓度为22.1μg/m³,共出现两个PM_2.5浓度水平升高时段,所对应的平均质量浓度分别达46.0μg/m³和63.0μg/m³。风速降低、温度升高等不利气象条件是导致上述时段PM_2.5浓度上升的重要原因。在上述时段,伴随着PM_2.5浓度的升高,NO^-₃和NH⁺₄浓度均出现显著升高,NO^-₃与SO^2-₄的摩...     

Impact assessment of treated/untreated wastewater toxicants discharged by sewage treatment plants on health, agricultural, and environmental quality in the wastewater disposal area

Studies were undertaken to assess the impact of wastewater/sludge disposal (metals and pesticides) from sewage treatment plants (STPs) in Jajmau, Kanpur (5 MLD) and Dinapur, Varanasi (80 MLD), on health, agriculture and environmental quality in the receiving/application areas around Kanpur and Varanasi in Uttar Pradesh, India. The raw, treated and mixed treated urban wastewater samples were collected from the inlet and outlet points of the plants during peak (morning and evening) and non-peak (noon) hours. The impact of the treated wastewater toxicants (metals and pesticides) on the environmental quality of the disposal area was assessed in terms of their levels in different media samples viz., water, soil, crops, vegetation, and food grains. The data generated show elevated levels of metals and pesticides in all the environmental media, suggesting a definite adverse impact on the environmental quality of the disposal area. The critical levels of the heavy metals in the soil for agricultural crops are found to be much higher than those observed in the study areas receiving no effluents. The sludge from the STPs has both positive and negative impacts on agriculture as it is loaded with high levels of toxic heavy metals and pesticides, but also enriched with several useful ingredients such as N, P, and K providing fertilizer values. The sludge studied had cadmium, chromium and nickel levels above tolerable levels as prescribed for agricultural and lands application. Bio-monitoring of the metals and pesticides levels in the human blood and urine of the different population groups under study areas was undertaken. All the different approaches indicated a considerable risk and impact of heavy metals and pesticides on human health in the exposed areas receiving the wastewater from the STPs.     

Modeling and optimization of reductive degradation of chloramphenicol in aqueous solution by zero-valent bimetallic nanoparticles

Purpose

The present study aims to investigate the individual and combined effects of temperature, pH, zero-valent bimetallic nanoparticles (ZVBMNPs) dose, and chloramphenicol (CP) concentration on the reductive degradation of CP using ZVBMNPs in aqueous medium.

Method

Iron?Csilver ZVBMNPs were synthesized. Batch experimental data were generated using a four-factor statistical experimental design. CP reduction by ZVBMNPs was optimized using the response surface modeling (RSM) and artificial neural network-genetic algorithm (ANN-GA) approaches. The RSM and ANN methodologies were also compared for their predictive and generalization abilities using the same training and validation data set. Reductive by-products of CP were identified using liquid chromatography-mass spectrometry technique.

Results

The optimized process variables (RSM and ANN-GA approaches) yielded CP reduction capacity of 57.37 and 57.10?mg?g^?1, respectively, as compared to the experimental value of 54.0?mg?g^?1 with un-optimized variables. The ANN-GA and RSM methodologies yielded comparable results and helped to achieve a higher reduction (>6%) of CP by the ZVBMNPs as compared to the experimental value. The root mean squared error, relative standard error of prediction and correlation coefficient between the measured and model-predicted values of response variable were 1.34, 3.79, and 0.964 for RSM and 0.03, 0.07, and 0.999 for ANN models for the training and 1.39, 3.47, and 0.996 for RSM and 1.25, 3.11, and 0.990 for ANN models for the validation set.

Conclusion

Predictive and generalization abilities of both the RSM and ANN models were comparable. The synthesized ZVBMNPs may be used for an efficient reductive removal of CP from the water.     

Optimization of nitrate reduction by EDTA catalyzed zero-valent bimetallic nanoparticles in aqueous medium

The present study aims to investigate the EDTA catalyzed reduction of nitrate (NO ₃ ^? ) by zero-valent bimetallic (Fe?CAg) nanoparticles (ZVBMNPs) in aqueous medium and to enumerate the effect of temperature, solution pH, ZVBMNPs dose and EDTA concentration on NO ₃ ^? reduction. Batch experimental data were generated using a four-factor Box?CBehnken design. Optimization modeling was performed using the response surface method for maximizing the reduction of NO ₃ ^? by ZVBMNPs. Significance of the independent variables and their interactions were tested by the analysis of variance and t test statistics. The model predicted maximum reduction capacity (340.15?mg?g^?1 NO ₃ ^? ) under the optimum conditions of temperature, 60?°C; pH?4; dose, 1.0?g?l^?1; and EDTA concentration, 2.0?mmol?l^?1 was very close to the experimental value (338.62?mg?g^?1) and about 16?% higher than the experimentally determined capacity (291.32?mg?g^?1). Study demonstrated that ZVBMNPs had higher reduction efficiency than Fe⁰ nanoparticles for NO ₃ ^? . EDTA significantly enhanced the NO ₃ ^? reduction by ZVBMNPs. The EDTA catalyzed reduction of NO ₃ ^? by ZVBMNPs can be employed for the effective decontamination of water.     

Investigating hydrochemistry of groundwater in Indo-Gangetic alluvial plain using multivariate chemometric approaches

Groundwater hydrochemistry of an urban industrial region in Indo-Gangetic plains of north India was investigated. Groundwater samples were collected both from the industrial and non-industrial areas of Kanpur. The hydrochemical data were analyzed using various water quality indices and nonparametric statistical methods. Principal components analysis (PCA) was performed to identify the factors responsible for groundwater contamination. Ensemble learning-based decision treeboost (DTB) models were constructed to develop discriminating and regression functions to differentiate the groundwater hydrochemistry of the three different areas, to identify the responsible factors, and to predict the groundwater quality using selected measured variables. The results indicated non-normal distribution and wide variability of water quality variables in all the study areas, suggesting for nonhomogenous distribution of sources in the region. PCA results showed contaminants of industrial origin dominating in the region. DBT classification model identified pH, redox potential, total-Cr, and λ ₂₅₄ as the discriminating variables in water quality of the three areas with the average accuracy of 99.51 % in complete data. The regression model predicted the groundwater chemical oxygen demand values exhibiting high correlation with measured values (0.962 in training; 0.918 in test) and the respective low root mean-squared error of 2.24 and 2.01 in training and test arrays. The statistical and chemometric approaches used here suggest that groundwater hydrochemistry differs in the three areas and is dominated by different variables. The proposed methods can be used as effective tools in groundwater management.