Photodegradation of amaranth in aqueous solution catalyzed by immobilized nanoparticles of titanium dioxide

The use of suspensions of nanoparticles of titanium dioxide in photocatalytic degradation of dye solution has disadvantages of inconvenient separation of fine particles for reuse and limited penetration of light for effective degradation. These problems can be minimized by supporting titanium dioxide on various inert supports. The present study involves the preparation of immobilized titanium dioxide films by three different techniques and characterization of the prepared films. The immobilized films of nanocrystals of titanium dioxide were prepared using sol?Cgel technique, polyvinyl alcohol?Cformaldehyde binder and acrylic emulsion. The photocatalytic performance of the prepared films for degradation of amaranth dye has also been evaluated and compared. Combination of photodegradation and adsorption processes induces strong beneficial effects on removal of dyes. Addition of high adsorption capacity activated carbon to photoactive titanium dioxide in photodegradation of dyes improves the efficiency of dye mineralization. The activated carbon has also been immobilized along with titanium dioxide in the present work to examine the dual effect of photodegradation and adsorption in the removal of amaranth. The films formed with the help of polyvinyl alcohol?Cformaldehyde binder showed better dye degradation capabilities.     

Is the interdecadal variation of the summer rainfall over eastern China associated with SST?

The present study examined the major features of the interdecadal variation of the summer rainfall over eastern China (IVRC) and the possible association with sea surface temperature (SST). We noted that the first leading mode of IVRC (accounting for nearly half of the total variance and with maximum loading for the summer rainfall anomalies over South China) may be not forced by SST. On the other hand, the second and third leading modes [accounting for 17.1 and 13.6 % of the total variance and mainly associated with the summer rainfall anomalies over the Yangtze River valley (YRV) and North China, respectively] in some extent are forced by SST anomalies. These observational results are confirmed by atmospheric general circulation model (AGCM) simulations forced by observed SST. By eliminating the internal dynamical process driven rainfall though ensemble mean, the simulations further suggest an overall enhancement of the intensity of IVRC in the corresponding ensemble mean, especially in the YRV and North China regions, but not in South China. That implies the different role of SST in driving IVRC over different regions.     

An analysis of prediction skill of monthly mean climate variability

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30?C40?days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability.     

Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2

An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001–2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.     

气候变化对喜马拉雅中部甘达基河流域濒危物种的影响预测（英文）

甘达基河流域位于喜马拉雅山脉中部,是众多濒危野生物种的重要栖息地。然而气候变化使该流域的生态环境变得愈发脆弱。本研究利用最大熵物种分布模型(Max Ent)评估气候变化对喜马拉雅黑熊(Ursus thibetanus laniger)和印度花豹(Panthera pardus fusca)等濒危物种空间分布变化的潜在影响。研究基于物种出没地点、生物气候和地形(海拔、坡度和坡向)等数据拟合模拟并预测物种在目前与未来的潜在分布情况。研究结果显示,目前喜马拉雅黑熊的高度适宜区面积约为1642 km²,占流域面积的5.01%,预计至2050年,其高度适宜区面积在甘达基河流域内将会增加约51 km²;印度花豹的高度适宜区面积约为3999 km²,占流域面积的12.19%,预计至2050年可能会增加到4806 km²。喜马拉雅黑熊的栖息地面积可能会在研究区域的东部(伯塞里、塔托潘尼和班塞以北)增加,而在东部(颂当、切坎帕)、西部(布尔提邦和波邦)和北部(桑波切、玛南、切坎帕)减少;印度花豹的栖息地面积则将在研究...     

Surface layer turbulence spectra and dissipation rates during low winds in tropics

Spectral characteristics of surface layer turbulence in an urban atmosphere are investigated. The observations used for this purpose represent low wind conditions in the tropics. The normalized power spectral shapes exhibit the usual characteristics in the inertial subrange and obey Monin-Obukhov scaling. However, the low-frequency behaviours do not conform to the previous observed relations. For horizontal components, large energy is contained in the low frequencies in contrast to the vertical component where roll-off to zero frequency is faster.The turbulent kinetic energy dissipation rate estimated from the spectra using Kolmogorov's inertial subrange law is found to be isotropic unlike the velocity variances. The expressions for the dimensionless dissipation rate do not seem to work well in low winds in an urban atmosphere. For the data considered, the dissipation rate exhibits a power law relationship with the mean windspeed and the friction velocity.     

Artificial Neural Network as a Tool for Backbreak Prediction

Backbreak is one of the destructive side effects of the blasting operation. Reducing of this event is very important for economic of a mining project. Involvement of various parameters has made the backbreak analyzing difficult. Currently there is no any specific method to predict or control the phenomenon considering all the effective parameters. In this paper, artificial neural network (ANN) as a powerful tool for solving such complicated problems is used to predict backbreak in blasting operation of the Sangan iron mine, Iran. Network training was fulfilled using a collected database of the practiced operation including blast design details and rock condition. Trying various types of the networks, a network with two hidden layers was found to be optimum. Performance of the ANN model was compared with statistical analysis using datasets which were kept apart from the original database. According to the obtained results, for the ANN model there existed a higher correlation (R² = 0.868) and lesser error (RMSE = 0.495) between the predicted and measured backbreak as compared to the regression model. Also, sensitivity analysis revealed that the inputs rock factor and number of rows are the most and the least sensitive parameters on the output backbreak, respectively.     

Age of the Marwar Supergroup,NW India:A note on the U–Pb geochronology of Jodhpur Group felsic volcanics

The Marwar Supergroup(NW Peninsular India)is thought to be of Ediacaran-Cambrian age,based on previous paleontological and geochronological studies.However,direct constraints on the onset of sedimentation within the Marwar basin are still scarce.In this study,we report U–Pb zircon,LA-ICP-MS,and SIMS ages from the Chhoti Khatu felsic volcanic rocks,interlayered with the Jodhpur Group sandstones(Lower Marwar Supergroup).The cathodoluminescence images of the zircons indicate complex morphologies,and core-rim textures coupled with the wide range of ages indicate that they are likely inherited or in the case of thin poorly indurated ash-beds,detrital in origin.The age spectra of 68 zircon analyses from our sampling display a dominant 800–900 Ma age peak corresponding to the age of basement"Erinpura granite"rocks in the region.The youngest inherited zircon from a felsic ash layer yielded a U–Pb age of651 Ma±18 Ma that,together with previous studies and paleontological evidence,indicates a postCryogenian age for the initiation of Marwar sedimentation following a~125 Ma hiatus between the end of Malani magmatism and Marwar deposition.