Uncertainties in future monsoon flow predictions in the context of projected climate change: A study of the Chaliyar River Basin

A major part of the annual rainfall in most parts of India is received during the monsoon. The Chaliyar River Basin in the state of Kerala is no exception with more than 85% of the annual rainfall occurring during the monsoon season. Evidences pointing towards the influence of anthropogenic activities on climate change have been reported from all over the world in recent years. One of the major problems encountered in the projection of future climate is the accumulation of uncertainties arising from different sources. This, in turn, would result in uncertainties in the predicted future streamflows. In this work, uncertainties in the monsoon flow predictions for a future period (2070-2099), stemming from the use of different climate models, hydrological models, and representative concentration pathways are analyzed. Uncertainty due to each of these sources and their interactions are partitioned by performing three-way analysis of variance. Results of the study indicate that the major source of uncertainty in the monsoon flow predictions is uncertainty from the climate models, which is about 83.73% of the total uncertainty in future monsoon flow predictions. Hydrological models account for about 5.38% and RCPs account for about 4.3% of the total uncertainty. About 6.57% is attributed to interactions between these three factors. Evaluation of the uncertainties in future monsoon flow predictions would facilitate informed decision making while formulating strategies for water management in the future.

Heavy Metal Removal from Contaminated Soil Using Soil Washing Techniques

Heavy metals are discharged into the soil around us from various anthropogenic sources and also by the use of fertilizers, pesticides, pharmaceuticals, etc. In most cases, industrialization can be pointed to as the reason behind soil pollution. Contamination of soil leads to large-scale environmental degradation and health impacts. Many investigators have studied techniques for removing heavy metals from soil. Soil washing is an emerging area that can be implemented for this purpose. Studies were carried out in the controlled conditions of a laboratory environment to determine the suitability of soil-washing techniques for removing lead from polluted land. The results showing the influence of various parameters in soil washing, such as duration of washing, molar strength of the solution used, the weight ratio of soil to wash solution, etc., are presented in this paper. Batch studies were conducted to investigate the performance of chelating agents such as Na2EDTA, HCl, HNO3 and CaCl2 with regard to the removal of lead from artificially contaminated locally available soil. Based on the batch studies, it is observed that the strength of the washing solution, the proportion of soil and solution, the period of agitation, etc. influence the removal of contaminants. Based on the studies, it is concluded that, while recommending soil washing using chelating agents for remediating lead-contaminated soils, it is essential to identify the influencing parameters and determine the optimum conditions so that higher removal can be achieved without any adverse effect.

Statistical downscaling of sea levels: application of multi-criteria analysis for selection of global climate models

Sea level rise is one of the serious aftermaths of global warming on the hydrosphere. The scientific community often depends on global climate models (GCMs) for projection of future sea levels. Numerous GCMs are available; thus, selecting the most appropriate GCM/GCMs is a critical task to be performed prior to downscaling. In this study, multi-criteria decision-making (MCDM) techniques, namely, Preference Ranking Organisation Method of Enrichment Evaluation (PROMETHEE-II), Elimination Et Choice Translating Reality (ELECTRE-II), and compromise programming, were used to identify appropriate GCMs whose projections can be used to downscale sea level projections at Ernakulam, Kerala, India. Support vector machine was employed to statistically downscale the sea level projections from the projections of GCMs. Five statistical metrics, namely, correlation coefficient ([Formula: see text]), normalized root mean square error, absolute normalized average bias, mean absolute relative error, and skill score, were adopted in this study as the performance criteria. The weightage of each criterion was computed using the entropy method. Six GCMs (GISS-E2-H, CanESM2, ACCESS1-0, CNRM-CM5, GFDL-CM3, and CMCC-CM) were considered for the analysis based on the availability of predictors. GISS-E2-H, CanESM2, and ACCESS1-0 occupied the first three positions respectively in all three MCDM techniques.

Prediction of land use/cover change in the Bharathapuzha river basin, India using geospatial techniques

The Bharathapuzha river basin, once endowed with dense vegetation and abundant water, has been experiencing acute water shortage and extreme climatic conditions in recent times. To understand the influence of human interventions on the natural environmental conditions, including the problems mentioned above, it is essential to critically examine the changes in land use/cover over these years. The objective of this study is to assess land use/cover change in the Bharathapuzha river basin, Kerala during the period 1990-2017 using LANDSAT series satellite images. The dynamics of land use/cover change were quantified and mapped using geospatial techniques. The multi-temporal LANDSAT images were classified by supervised maximum likelihood method to generate the corresponding land use/cover maps; changes in land use/cover in the river basin were subsequently detected by the post-classification technique. Results of the study revealed a drastic change in land use/cover in the period 1990-2017; the primary causes of this were deforestation and urbanization. The near- and long-term future land use/cover maps of the basin for 2020 and 2035 were generated from the historically retrieved land use/cover change pattern. Multi-Layer Perceptron Neural Network and Markov chain techniques were used to generate future land use/cover maps. These maps reveal that the predominant land use/cover class in the basin will be barren land and about 46.13% of the existing (in 2017) dense vegetation will diminish by 2035. The efficiency of sustainable watershed management activities in the river basin can be improved based on the critical observations from this study.

Degradation of rhodamine B with manganese dioxide nanorods

This is an investigation on oxidative degradation of rhodamine B (RhB) by manganese dioxide (MnO₂) nanorods synthesized by redox co-precipitation method. Field emission scanning electron microscopy of MnO₂ nanorods at an electron voltage of 10 kV revealed a rod-like morphology for the synthesized nanoparticles. Fourier transform infrared spectra exhibited characteristic peaks of MnO₂. Surface area of MnO₂ nanorods was 277 m²/g. Effect of various parameters like initial concentration and pH of RhB solution, time of contact between MnO₂ nanorods and RhB, dosage of MnO₂, and stirring speed on decolouration of RhB was evaluated in batch experiments. Rapid decolouration in the initial period of the reaction was observed due to the adsorption of RhB molecules onto the surface of MnO₂ nanorods followed by oxidative degradation. Percentage decolouration decreased with increase in initial concentration and increased with increase in dosage, speed of stirring the mixture and with increase in pH up to pH 7. Near complete decolouration was achieved at a dose of 0.5 g/L of MnO₂ nanorods from 20 mg/L RhB solution within 3 min. Observations fitted best to the pseudo second order kinetic model. This study could pave the way for development of cost-effective, nontoxic nanostructures for treatment of wastewaters containing RhB.

Adsorptive removal of cationic and anionic dyes using graphene oxide

This paper presents the results of comparative study on the application of graphene oxide (GO) for the adsorptive removal of crystal violet (CV) and methyl orange (MO) in batch mode. GO, synthesised from graphite, was characterised by field emission scanning electron microscopy (FESEM), Fourier transform infrared (FTIR) spectroscopy, point of zero charge (pH_PZC) and ultra violet (UV) spectroscopy. Dispersion of GO in water revealed the conversion of hydrophobic graphite into hydrophilic. Performance with regard to adsorption of CV and MO on GO was evaluated at different values of the operational parameters such as contact time between GO and the dye molecules, dosage of GO, and initial concentration and pH of the dye solution. Uptake and percentage removal of the dyes increased with increase in contact time and adsorbent dosage, but declined with increase in initial concentration of the dye. Experimental data on the uptake of dye molecules by GO showed good fit with the Freundlich isotherm model and the pseudo second order kinetic model. The maximum uptake by GO was higher for CV (207.4 mg/g) than that for MO (37.2 mg/g). Results indicate that GO is an effective adsorbent for the removal of CV but not for MO.

Pharmaceutical products as emerging contaminant in water: relevance for developing nations and identification of critical compounds for Indian environment

Pharmaceuticals and personal care products (PPCPs) are contaminants of emerging concern and have been detected worldwide in water bodies in trace concentrations. Most of these emerging contaminants are not regulated in water quality standards except a few in the developed countries. In the case of developing countries, research in this direction is at a nascent stage. For the effective management of Pharmaceutical contaminants (PC) in developing countries, the relevance of PCs as an emerging contaminant has to be analyzed followed by regular monitoring of the environment. Considering the resource constraints, this could be accomplished by identifying the priority compounds which is again region specific and dependent on consumption behavior and pattern. In this work, relevance of pharmaceutical compound as emerging contaminant in water for a developing country like India is examined by considering the data pertaining to pharmaceutical consumption data. To identify the critical Pharmaceutical Contaminants to be monitored in the Indian environment, priority compounds from selected prioritization methods were screened with the compounds listed in National List of Essential Medicine (NLEM), India. Further, information on the number of publications on the compound as an emerging contaminant, data on monitoring studies in India and the number of brands marketing the compound in India were also analyzed. It is found that out of 195 compounds from different prioritization techniques, only 77 compounds were found relevant to India based on NLEM sorting.

Adsorption of crystal violet onto functionalised multi-walled carbon nanotubes: Equilibrium and kinetic studies

Synthetic dyes present in effluent from textile, paper and paint industries contain crystal violet (CV), a known carcinogenic agent. This study investigates the modification of multiwalled carbon nanotubes by acid reflux method and equilibrium and kinetic behaviour of adsorption of CV onto functionalized multi-walled carbon nanotubes (fMWNTs) in batch system. High stability of the fMWNTs suspension in water indicates the hydrophilicity of fMWNTs induced due to the formation of functional groups that make hydrogen bonds with water molecules. fMWNTs were characterized by Fourier Transform Infra Red (FTIR) spectroscopy and the functional groups present on the fMWNTs were confirmed. Characteristic variation was observed in the FTIR spectra of fMWNTs after adsorption of crystal violet onto it. Adsorption characteristics were evaluated as a function of system variables such as contact time, dosage of fMWNTs and initial concentration and pH of the crystal violet solution. Adsorption capacity of fMWNTs and percentage removal of the dye increased with increase in contact time, adsorbent dosage and pH but declined with increase in initial concentration of the dye. fMWNTs showed higher adsorption capacity compared to that of pristine MWNTs. Data showed good fit with the Langmuir and Freundlich isotherm models and the pseudo-second order kinetic model; the maximum adsorption capacity was 90.52mg/g. Kinetic parameters such as rate constants, equilibrium adsorption capacities and regression coefficients were estimated. Results indicate that fMWNTs are an effective adsorbent for the removal of crystal violet from aqueous solution.

Removal of lead from wastewater by adsorption using acid-activated clay

The suitability of acid-activated clay for adsorbing lead from wastewater streams was tested by conducting experimental studies in the laboratory. The effect of initial concentration of the adsorbate on lead removal was analysed using solutions with lead concentrations ranging from 20-120 mg/l. Also, the effect of pH on removal of lead was studied in the pH range of 2-10 and the effect of adsorbent dosage was studied by varying the adsorbent dosage from 10-20 g/l. The tests were conducted at three different temperatures, 25 degrees C, 30 degrees C and 35 degrees C. The efficiency of lead removal was observed to be about 92.4% at an initial concentration of 100 mg/l of lead, at pH 6 and at a temperature of 30 degrees C. The adsorption isotherms were plotted. The Langmuir isotherm fitted the experimental data reasonably well. The adsorption process followed the pseudo second-order model.