Energy conditions for Bianchi type I universe in f(G) gravity

In this paper, we discuss energy conditions in modified Gauss-Bonnet gravity for locally rotationally symmetric Bianchi type I universe model with perfect fluid. The matter contents are constructed to discuss the energy conditions bounds. We take two specific f(G) models along with present day values of Hubble, deceleration, jerk and snap parameters. It is found that weak and null energy conditions are satisfied while strong energy conditions are violated for both models which represents the accelerated expansion of the universe.     

Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed

Future climate projections of Global Climate Models (GCMs) under different emission scenarios are usually used for developing climate change mitigation and adaptation strategies. However, the existing GCMs have only limited ability to simulate the complex and local climate features, such as precipitation. Furthermore, the outputs provided by GCMs are too coarse to be useful in hydrologic impact assessment models, as these models require information at much finer scales. Therefore, downscaling of GCM outputs is usually employed to provide fine-resolution information required for impact models. Among the downscaling techniques based on statistical principles, multiple regression and weather generator are considered to be more popular, as they are computationally less demanding than the other downscaling techniques. In the present study, the performances of a multiple regression model (called SDSM) and a weather generator (called LARS-WG) are evaluated in terms of their ability to simulate the frequency of extreme precipitation events of current climate and downscaling of future extreme events. Areal average daily precipitation data of the Clutha watershed located in South Island, New Zealand, are used as baseline data in the analysis. Precipitation frequency analysis is performed by fitting the Generalized Extreme Value (GEV) distribution to the observed, the SDSM simulated/downscaled, and the LARS-WG simulated/downscaled annual maximum (AM) series. The computations are performed for five return periods: 10-, 20-, 40-, 50- and 100-year. The present results illustrate that both models have similar and good ability to simulate the extreme precipitation events and, thus, can be adopted with confidence for climate change impact studies of this nature.     

Water temperature modelling: comparison between the generalized additive model,logistic, residuals regression and linear regression models

Water temperature has a significant influence on aquatic organisms, including stenotherm fish such as salmonids. It is thus of prime importance to build reliable tools to forecast water temperature. This study evaluated a statistical scheme to model average water temperature based on daily average air temperature and average discharge at the Sainte-Marguerite River, Northern Canada. The aim was to test a non-parametric water temperature generalized additive model (GAM) and to compare its performance to three previously developed approaches: the logistic, residuals regression and linear regression models. Due to its flexibility, the GAM was able to capture some of the nonlinear response between water temperature and the two explanatory variables (air temperature and flow). The shape of these effects was determined by the trends shown in the collected data. The four models were evaluated annually using a cross-validation technique. Three comparison criteria were calculated: the root mean square error (RMSE), the bias error and the Nash-Sutcliffe coefficient of efficiency (NSC). The goodness of fit of the four models was also compared graphically. The GAM was the best among the four models (RMSE = 1.44°C, bias = ?0.04 and NSC = 0.94).     

Influence of Electrokinetic Process on Compressibility Behaviour of Salt Affected Soils

Geotechnical and Geological Engineering - The improvement of salt affected lands is a major environmental challenge in arid and semi arid regions all over the world. Electrokinetic treatment is one...     

On radiative forcing of sulphate aerosol produced from ion-promoted nucleation mechanisms in an atmospheric global model

A significant fraction of the total number of particles present in the atmosphere is formed by nucleation in the gas phase. Nucleation and the subsequent growth process influence both number concentration of particles and their size distribution besides chemical and optical properties of atmospheric aerosols. Sulphate aerosol nucleation mechanisms promoted by ions have been evaluated here in a tropospheric interactive chemistry-aerosol module for mass and number concentration in a global atmospheric model. The indirect radiative forcing of sulphate particles is assessed in this model; indirect radiative forcing is different for ion-induced (IIN) and ion-mediated (IMN) mechanisms. The indirect radiative forcing in 10-year simulation runs has been calculated as ?1.42?W/m² (IIN) and ?1.54?W/m² (IMN). The 5% emission of primary sulphate particles in simulations changes the indirect radiative forcing from ?1.42 to ?1.44?W/m² for IIN case, and from ?1.54 to ?1.55 W/m² for the IMN case. More precisely, owing to greater nucleation rates, IMN mechanisms produces greater cooling than the IIN mechanisms in the backdrop that both mechanisms produce almost identical distribution of CDNC in their pre-industrial runs. The inclusion of primary particles in simulations with IIN and IMN mechanisms increases both CDNC and the indirect radiative forcing.     

High-performing antifouling bacterial consortium for submerged membrane bioreactor treating synthetic wastewater

Biofouling, associated with membranes, is considered as a major operational challenge in membrane bioreactor (MBR) technology. Interrupting the process for the formation of biofilm by the action of interspecies quorum quenching (QQ) has received a significant attention since recent years. An antifouling bacterial consortium was identified to improve biofouling inhibition performance during MBR operation. For this purpose, various QQ bacteria were isolated from laboratory-scale MBR using enrichment culture method and identified via 16S rRNA. Potential quenching strains including Enterobacter cloaca, Delftia sp., and Pseudomonas sp. were utilized to control biofouling in the MBR operated in the continuous mode for 38 days. Three laboratory-scale MBRs, including two MBRs with different anti fouling consortium and a control, were operated in parallel under similar operating conditions. Biofouling control by QQ bacteria was compared based on the membrane permeability and EPS secretion from biofilm on the membrane. Both MBRs with antifouling consortium (AC-MBRs) experienced around three times less biofouling as compared to conventional MBR leading to significant decrease in acyl homoserine lactones (AHLs) concentration in the biocake. More than 90, 45, and 49% of COD, NH₄–N, and PO₄ ^3?–P removal efficiencies elucidate that QQ bacterial consortium could effectively reduce membrane biofouling without compromising the MBR efficiency. Comparatively lower concentration of bound EPS in AC-MBRs restricted the bacterial adhesion to membrane resulting in enhanced membrane permeability depicting that a broader range of signal molecules could be hydrolyzed using antifouling consortium than single or no QQ strain in the submerged MBR.     

Depositional environment of a Kimmeridgian carbonate 'black band' (Akkuyu Formation, south-western Turkey)

The Upper Jurassic Akkuyu Formation of south-western Turkey consists of pale-coloured carbonate facies, but includes a peculiar ‘black band’ at its base. In order to characterize the depositional environment of this level, a sedimentological, organic and inorganic geochemical study was performed on 30 samples. Three units are distinguished. Unit 1 consists of black marlstones, very rich in organic carbon (22–30%) with HI (hydrogen index) values around 600. The organic matter is an amorphous homogeneous material even at nanoscopic scale. This unit is also characterized by a very high concentration of V ( >1000 p.p.m.) and a δ¹³C_org value around ?26·5‰. Unit 2 shows thin-bedded black limestones with chert layers. Its organic content varies from 2% to 6%. As in unit 1, the HI values are uniformly high (600), and gas chromatography shows a high quantity of hopanes. The V concentration is also high (≈400 p.p.m.). The unit has a high Sr/Ca ratio, an organic carbon isotopic ratio close to ?28·7‰ and diffuse, nanoscopically amorphous organic material that is closely associated with pyrite. Unit 3 corresponds to the white limestones overlying the ‘black band’. This calcitic facies is almost devoid of organic carbon (<0·1%). The δ¹³C_org values are similar to those of unit 1 (?25·5‰ to ?26‰). Deposition occurred in a basinal environment surrounded by a carbonate platform. Primary productivity was high but not exceptional; terrestrial organic inputs were scarce. Bottom waters were probably euxinic during the deposition of unit 1. The presence of both hopane-rich and sulphur-rich nanoscopically amorphous organic matter may be the result of strong sulphate-reducing bacterial activity. Coupled with low amounts of iron, this led to intense vulcanization of the organic matter and thus good preservation. With the onset of unit 2 deposition, environmental conditions became less extreme, perhaps because of cooler water temperatures. Finally, the depositional conditions became oxic, leading to the accumulation of pale-coloured organic-poor limestones of unit 3.     

Comparison of two alluvial aquifers shows the probable role of river sediments on the release of arsenic in the groundwater of district Vehari,Punjab, Pakistan

The study was done to assess the effect of the river Sutlej on arsenic (As) contamination. Sampling was done from the alluvial plain with increasing distance from the river Sutlej in district Vehari and compared with the study done in the proximity of River Sutlej. Sixty (60) groundwater samples mostly from shallow depths were collected and analyzed for As concentrations. Multivariate statistical tools (PCA and CA), saturation index, piper plots and Gibbs diagrams were used to detect evidence about the interrelationship and sources of As and other water quality variables responsible for groundwater contamination. Results revealed that As concentration ranged from below detection limit to 156 µg/L indicating that 50% samples exceeding the WHO guidelines (10 µg/L) and 17% exceeding the Pakistan National Environmental Quality Standards (NEQS) limits (50 µg/L) Sutlej. The piper plot revealed that water chemistry of the study area was Ca–HCO₃^?, Ca–Mg–Cl, type. Correlations between As and HCO₃^? (r²?=?0.433) was positive, while negative correlations were observed between As–Mn²⁺ and As–Fe²⁺ (r²?=???0.102), (r²?=?0.107) respectively. Geochemical signatures of the groundwater in the study area showed that the As could be released by oxidative dissolution to some extent and elevated evaporation in the arid environment of the study area under the stimulus of alkaline water and high pH (range 7.1–8.4). Although the concentrations are exceeding the WHO limit in 50% of the water samples but, are less than the previous study done in Mailsi near River Sutlej. Further, the concentrations decreased as the distance from the River increased which shows the probable role of sediments deposited by the River Sutlej.     

Statistically downscaled probabilistic multi‐model ensemble projections of precipitation change in a watershed

This paper presents the development of a probabilistic multi‐model ensemble of statistically downscaled future projections of precipitation of a watershed in New Zealand. Climate change research based on the point estimates of a single model is considered less reliable for decision making, and multiple realizations of a single model or outputs from multiple models are often preferred for such purposes. Similarly, a probabilistic approach is preferable over deterministic point estimates. In the area of statistical downscaling, no single technique is considered a universal solution. This is due to the fact that each of these techniques has some weaknesses, owing to its basic working principles. Moreover, watershed scale precipitation downscaling is quite challenging and is more prone to uncertainty issues than downscaling of other climatological variables. So, multi‐model statistical downscaling studies based on a probabilistic approach are required. In the current paper, results from the three well‐reputed statistical downscaling methods are used to develop a Bayesian weighted multi‐model ensemble. The three members of the downscaling ensemble of this study belong to the following three broad categories of statistical downscaling methods: (1) multiple linear regression, (2) multiple non‐linear regression, and (3) stochastic weather generator. The results obtained in this study show that the new strategy adopted here is promising because of many advantages it offers, e.g. it combines the outputs of multiple statistical downscaling methods, provides probabilistic downscaled climate change projections and enables the quantification of uncertainty in these projections. This will encourage any future attempts for combining the results of multiple statistical downscaling methods. Copyright © 2011 John Wiley & Sons, Ltd.