Toxicity of chlorpyrifos and TCP alone and in combination to Daphnia carinata: the influence of microbial degradation in natural water

The acute toxicity of chlorpyrifos and its principal metabolite 3,5,6-trichloropyridinol (TCP) alone and in combination to a cladoceran, Daphnia carinata, was studied in both cladoceran culture medium and natural water collected from a local suburban stream. TCP was found to be more toxic than its parent chemical chlorpyrifos to Daphnia survival in cladoceran culture medium. However, TCP in natural water was not toxic to D. carinata up to 2 microgL(-1). The LC(50) values for chlorpyrifos, TCP and chlorpyrifos+TCP were 0.24, 0.20 and 0.08 microgL(-1), respectively, in cladoceran culture medium. Although the parent chemicals and their degradation products co-exist in natural waters, the existing guidelines for water quality are based on individual chemicals. The results of this investigation suggest that chlorpyrifos and TCP can interact synergistically, additively or antagonistically, resulting in an increase or decrease in the overall toxicity of the mixture compared to individual compounds. The indigenous microorganisms in natural water could play a significant role in degradation of these compounds thereby influencing their toxicity in receiving waters. This study clearly suggests that the joint action of pesticides and their degradation products should be considered in the development of water quality guidelines. To our knowledge, this is the first study on the interactive effect of chlorpyrifos and TCP to a cladoceran and suggests that these two compounds are non-toxic when present together at concentrations up to 0.12 microgL(-1). However, these compounds together act additively at and above 0.5 microgL(-1) to fresh water invertebrates and therefore pollution with these compounds may adversely affect natural ecosystems.     

Sustainable green synthesis of silver nanoparticles by using Rangoon creeper leaves extract and their spectral analysis and anti‐bacterial studies

The plant‐based biological molecules possess exceptionally controlled assembling properties to make them suitable in the synthesis of metal nanoparticles. In the present study, an efficient simple one‐pot method was employed for the synthesis of silver nanoparticles (SNPs) from the Rangoon creeper (RC) aqueous leaf extract. Biomolecules present in the leaf extract play a significant role as reducing agent as well as capping agent in the formation of RC‐SNPs. The formation of RC‐SNPs was confirmed by using several analytical techniques such as Fourier‐transform infrared spectroscopy and ultraviolet–visible spectrophotometer studies. The presence of a sharp surface plasmon resonance peak at 449 nm showed the formation of RC‐SNPs. X‐ray diffraction analysis showed the crystalline nature of the RC‐SNPs with a face‐centred cubic structure. Elemental analysis of RC‐SNPs was done by using energy‐dispersive X‐ray spectroscopy and X‐ray photoelectron spectroscopy. The morphology of RC‐SNPs was examined by transmission electron microscopy (TEM) in the nano range 12 nm, and thermogravimetric‐differential thermal analysis demonstrated the mechanical strength of RC‐SNPs at various temperatures. The authors’ newly synthesised RC‐SNPs exhibited significant anti‐bacterial activity against Staphylococcus aureus and Escherichia coli. Inspec keywords: silver, nanoparticles, X‐ray photoelectron spectra, antibacterial activity, ultraviolet spectra, microorganisms, X‐ray chemical analysis, differential thermal analysis, X‐ray diffraction, transmission electron microscopy, visible spectra, nanofabrication, surface plasmon resonance, Fourier transform infrared spectra, mechanical strengthOther keywords: silver nanoparticles, ultraviolet–visible spectrophotometry, antibacterial activity, sustainable green synthesis, plant‐based biological molecules, assembling properties, reducing agent, capping agent, Fourier‐transform infrared spectroscopy, surface plasmon resonance, Rangoon creeper aqueous leaf extract, X‐ray diffraction, face‐centred cubic structure, elemental analysis, energy‐dispersive X‐ray spectroscopy, X‐ray photoelectron spectroscopy, transmission electron microscopy, TEM, thermogravimetric‐differential thermal analysis, mechanical strength, Staphylococcus aureus, Escherichia coli, Ag     

Isolation of phosphate solubilizing bacteria and their potential for lead immobilization in soil

Lead (Pb), a highly toxic heavy metal forms stable compounds with phosphate (P). The potential of phosphate solubilizing bacteria (PSB) to immobilize Pb by enhancing solubilization of insoluble P compounds was tested in this research. Eighteen different PSB strains isolated from P amended and Pb contaminated soils were screened for their efficiency in P solubilization. The PSB isolated from P amended soils solubilized 217-479 mg/L of P while the PSB from Pb contaminated soil solubilized 31-293 mg/L of P. Stepwise multiple regression analysis and P solubility kinetics indicated that the major mechanism of P solubilization by PSB is the pH reduction through the release of organic acids. From the isolated bacteria, two PSB were chosen for Pb immobilization and these bacteria were identified as Pantoea sp. and Enterobacter sp., respectively. The PSB significantly increased P solubilization by 25.0% and 49.9% in the case of Pantoea sp., and 63.3% and 88.6% in the case of Enterobacter sp. for 200 and 800 mg/kg of rock phosphate (RP) addition, respectively, thereby enhancing the immobilization of Pb by 8.25-13.7% in the case of Pantoea sp. and 14.7-26.4% in the case of Enterobacter sp. The ability of PSB to solubilize P, promote plant growth, and immobilize Pb can be used for phytostabilization of Pb contaminated soils.     

Electron-Affinity Substituent in 2,6-Dicarbonitrile Diphenyl-1λ5-Phosphinine Towards High-Quality Organic Lasing and Electroluminescence under High Current Injection

Rationally manipulating the functional substituents plays a crucial role in tuning the luminescence and lasing properties of organic gain media. Herein, a cyanophenyl-moiety, which exhibits relatively weaker electron affinity, is connected to 2,6-dicarbonitrile diphenyl-1λ⁵-phosphinine (DCNP) via para-linking. Resultantly, the appreciated locally-excited characteristics ensuring a large oscillator strength and high radiative rate can be reserved in DCNP-4-(4-cyanophenyl) (DCNP-pCN). Interestingly, the weak charge-transfer state from the relative donor (D)/acceptor (A) interplay enables small singlet-triplet splitting (ΔE_ST ≈ 0.45 eV). Thus the triplets generated on DCNP-pCN can be efficiently scavenged by 4,4'-bis[(N-carbazole)styryl]biphenyl (BSBCz), which is used as the host with a lower-lying triplet energy level for DCNP-pCN. Moreover, benefitting from the mediation between the conjugated length extension and weak D/A interplay, the emission spectrum cannot be largely shifted, which can effectively suppress the overlap between the lasing emission of DCNP-pCN and the excited-state absorption of BSBCz, thereby avoiding detrimental singlet-triplet annihilation. Thus, high-quality distributed feedback lasings with ≈2.0 μJ cm⁻² thresholds are achieved, and the organic light-emitting diodes exhibit external quantum efficiency exceeding 2.0% without efficiency rolloff under high current injection, indicating the potential for electrical-pumping organic lasings.     

Downscaling Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios

Evaluating the impact of climate change at river basin level has become essential for proper management of the water resources. In the present study, Godavari River basin in India is taken as study area to project the monthly monsoon precipitation using statistical downscaling. The downscaling method used is a regression based downscaling termed as fuzzy clustering with multiple regression. Among the atmospheric variables simulated by global circulation/climate model (GCM) mean sea level pressure, specific humidity and 500 hPa geopotential height are used as predictors. 1^o × 1^o gridded rainfall data over Godavari river basin are collected from India Meteorological Department (IMD). A statistical relationship is established between the predictors and predictand (monsoon rainfall) to project the monsoon rainfall for the future using the Canadian Earth System Model (CanESM2) over IMD grid points under the Representative Concentration Pathways 2.6, 4.5 and 8.5 (RCP 2.6, 4.5, 8.5) scenarios of Fifth Coupled Model Inter-Comparison Project (CMIP 5). Downscaling procedure is applied to all 25 IMD grid points over the basin to find out the spatial distribution of monsoon rainfall for the future scenarios. For 2.6 and 4.5 scenarios results show an increasing trend. For scenario 8.5 rainfall showed a mixed trend with rainfall decreasing in the first thirty years of prediction and then increasing gradually over the next sixty years.     

Size selective excitonic transition energies in strongly confined CdSe quantum dots

We report on the synthesis of CdSe nanocrystal quantum dots (QDs) of different radii (R). Size dependent optical properties like increase in the confinement energy with decreasing radius for different excitonic transitions are studied. Different excitonic transitions are calculated from the second derivative of UV-vis absorption spectra of as synthesized CdSe QDs. The transitions are assigned to specific states by calculating the transition energies using effective mass approximation. A close matching of the transition energies with the experiment suggesting that the second derivative of the absorption spectra could provide a direct knowledge of the electronic transition for the direct band gap semiconductor quantum dots.     

Spatio-Temporal Variation of Water Availability in a River Basin under CORDEX Simulated Future Projections

In the present study, spatio-temporal variability of hydrological components under climate change is analysed over Wainganga River basin, India. In order to address the climate change projection, hydrological modelling is carried out using a macro scale, semi-distributed three (3)-Layer Variable Infiltration Capacity (VIC-3 L) model. The high-resolution (0.5^o?×?0.5^o) meteorological variables are divided into multiple periods to calibrate and validate the VIC-3 L model. The future projections (2020–2094) of the water balance components are achieved using the high resolution hydrological variables from the COordinated Regional Downscaling EXperiment (CORDEX) dataset under Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The uncertainty associated with the multi-model projections are evaluated using Reliability Ensemble Averaging (REA) and the bias correction is accomplished with non-parametric quantile mapping. A probabilistic based areal drought index is also computed for different scenarios using Standardized Precipitation Evapotranspiration Index (SPEI). From the results, it is observed that amount of rainfall, evapotranspiration, and runoff has increased over the basin with no change in the spatial pattern. However, temporal variability is noticed with an increasing trend for rainfall and runoff in the non-monsoon season than the monsoon. Streamflow is expected to increase significantly, especially for medium to low flows (those occurring between 0.2 and 0.9 probability of exceedance in a Flow Duration Curve). In addition, the area under the drought condition has decreased under the projected climate scenarios.     

Modelling Impacts of Climate Change on a River Basin: Analysis of Uncertainty Using REA & Possibilistic Approach

In the context of climate change, the uncertainty associated with Global Climate Models (GCM) and scenarios needs to be assessed for effective management practices and decision-making. The present study focuses on modelling the GCM and scenario uncertainty using Reliability Ensemble Averaging (REA) and possibility theory in projecting streamflows over Wainganga river basin. A macro scale, semi-distributed, grid-based hydrological model is used to project the streamflows from 2020 to 2094. The observed meteorological data are collected from the India Meteorological Department (IMD) and the streamflow data is obtained from Central Water Commission (CWC) Hyderabad. In REA, meteorological data are weighted based on the performance and convergence criteria (GCM uncertainty). Whereas in possibility theory, based on the projection of different GCMs and scenarios during recent past (2006–2015) possibility values are assigned. Based on the possibility values most probable experiment and weighted mean possible CDF for the future periods are obtained. The result shows that there is no significant difference in the outcomes is observed between REA and possibility theory. The uncertainty associated with GCM is more significant than the scenario uncertainty. An increasing trend in the low and medium flows is predicted in annual and monsoon period. However, flows during the non-monsoon season are projected to increase significantly. Moreover, it is observed that streamflow generation not only depends on the change in precipitation but also depends on the previous state of physical characteristics of the region.     

Non-Stationary Rainfall Intensity-Duration-Frequency Relationship: a Comparison between Annual Maximum and Partial Duration Series

The rainfall Intensity-Duration-Frequency (IDF) relationship is the primary input for storm water management and other engineering design applications across the world and it is developed by fitting an appropriate theoretical probability distribution to annual maximum (AM) series or partial duration series (PDS) of rainfall. The existing IDF relationship developing methods consider the extreme rainfall series as a stationary series. There exist few studies that compared AM and PDS datasets for developing rainfall IDF relationship in a stationary condition. However, during the last few decades, the intensity and frequency of extreme rainfall events are increasing due to global climate change and creating a non-stationary component in the extreme rainfall series. Therefore, the rainfall IDF relationship developed with the stationary assumption is no longer tenable in a changing climate. Hence, it is inevitable to develop non-stationary rainfall IDF relationship and to understand the differences in non-stationary rainfall IDF relationships derived using AM and PDS datasets. Consequently, the objectives of this study are: (1) to develop non-stationary rainfall IDF relationships using both AM and PDS datasets; (2) to compare them in terms of return level estimation. In particular, the non-linear trend in different durations’ PDS and AM datasets of Hyderabad city (India) rainfall is modeled using Multi-objective Genetic Algorithm (MGA) generated Time based covariate. In this study, the PDS datasets are modeled by the Generalized Pareto Distribution (GPD) while the AM datasets are modeled by the Generalized Extreme Value Distribution (GEVD). The time-varying component is introduced in the scale parameter of the GPD and the location parameter of the GEVD by linking the MGA generated covariate. In addition, the complexity of each non-stationary model is identified using the corrected Akaike Information Criteria (AICc) and the statistical significance of trend parameter in the non-stationary models is estimated using the Likelihood Ratio (LR) test. Upon detecting significant superiority of non-stationary models, the return levels of extreme rainfall event for 2-, 5-, 10- and 25-year return periods are calculated using non-stationary models. From the results, it is observed that the non-stationary return levels estimated with PDS datasets are higher than those estimated with AM datasets for short durations and smaller return periods while the non-stationary return levels estimated with AM datasets are higher than those estimated with PDS datasets for long durations and higher return periods.