High Rate Capability Lithium Iron Phosphate Wired by Carbon Nanotubes and Galvanostatic Transformed to Graphitic Carbon

Lithium iron phosphate (LiFePO4) electronically wired by multi-walled carbon nanotubes (MWCNTs) and in-situ transformed graphitic carbon for lithium-ion batteries are discussed here. Presence of MWCNTs up to a maximum of 0.5% in porous LiFePO4 (abbreviated as LFP-CNT) resulted in remarkable reversible cyclability and rate capability compared to LFP coated with highly disordered carbon (abbreviated as LFP-C). In the current range (30-1500) mAg(-1), specific capacity of LFP-CNT (approximate to 150-50 mAhg(-1)) is observed to be always higher compared to LFP-C (approximate to 120-0 mAhg(-1)). At higher currents of 250-1500 mAg(-1) LFP-C performed poorly compared to LFP-CNT. LFP-C showed considerable decay in capacity with increase in cycle number at intermediate high currents (approximate to 250 mAg(-1)) whereas at very high currents (approximate to 750 mAg(-1)) it is nearly zero. The LFP-CNT showed no such detrimental behavior in battery performance. The exemplary performance of the LFP-CNT is attributed to combination of both enhanced LFP structural stability, as revealed by Raman spectra and formation of an efficient percolative network of carbon nanotubes which during the course of galvanostatic cycling gets gradually transformed to graphitic carbon. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.015204jes] All rights reserved.

A model investigation of vegetation-atmosphere interactions on a millennial timescale

A terrestrial biosphere model with dynamic vegetation capability, Integrated Biosphere Simulator (IBIS2), coupled to the NCAR Community Atmosphere Model (CAM2) is used to investigate the multiple climate-forest equilibrium states of the climate system. A 1000-year control simulation and another 1000-year land cover change simulation that consisted of global deforestation for 100 years followed by re-growth of forests for the subsequent 900 years were performed. After several centuries of interactive climate-vegetation dynamics, the land cover change simulation converged to essentially the same climate state as the control simulation. However, the climate system takes about a millennium to reach the control forest state. In the absence of deep ocean feedbacks in our model, the millennial time scale for converging to the original climate state is dictated by long time scales of the vegetation dynamics in the northern high latitudes. Our idealized modeling study suggests that the equilibrium state reached after complete global deforestation followed by re-growth of forests is unlikely to be distinguishable from the control climate. The real world, however, could have multiple climate-forest states since our modeling study is unlikely to have represented all the essential ecological processes (e. g. altered fire regimes, seed sources and seedling establishment dynamics) for the reestablishment of major biomes.

Jatropha cultivation in southern India: assessing farmers' experiences

Together with 106 farmers who started growing Jatropha (Jatropha curcas L.) in 20042006, this research sought to increase the knowledge around the real-life experience of Jatropha farming in the southern India states of Tamil Nadu and Andhra Pradesh. Launched as an alternative for diesel in India, Jatropha has been promoted as a non-edible plant that could grow on poor soils, yield oil-rich seeds for production of bio-diesel, and not compete directly with food production. Through interviews with the farmers, information was gathered regarding their socio-economic situation, the implementation and performance of their Jatropha plantations, and their reasons for continuing or discontinuing Jatropha cultivation. Results reveal that 82% of the farmers had substituted former cropland for their Jatropha cultivation. By 2010, 85% (n = 90) of the farmers who cultivated Jatropha in 2004 had stopped. Cultivating the crop did not give the economic returns the farmers anticipated, mainly due to a lack of information about the crop and its maintenance during cultivation and due to water scarcity. A majority of the farmers irrigated and applied fertilizer, and even pesticides. Many problems experienced by the farmers were due to limited knowledge about cultivating Jatropha caused by poor planning and implementation of the national Jatropha program. Extension services, subsidies, and other support were not provided as promised. The farmers who continued cultivation had means of income other than Jatropha and held hopes of a future Jatropha market. The lack of market structures, such as purchase agreements and buyers, as well as a low retail price for the seeds, were frequently stated as barriers to Jatropha cultivation. For Jatropha biodiesel to perform well, efforts are needed to improve yield levels and stability through genetic improvements and drought tolerance, as well as agriculture extension services to support adoption of the crop. Government programs will -probably be more effective if implementing biodiesel production is conjoined with stimulating the demand for Jatropha biodiesel. To avoid food-biofuel competition, additional measures may be needed such as land-use restrictions for Jatropha producers and taxes on biofuels or biofuel feedstocks to improve the competitiveness of the food sector compared to the bioenergy sector. (c) 2012 Society of Chemical Industry and John Wiley & Sons, Ltd

Hierarchical Clustering Algorithm for Land Cover Mapping Using Satellite Images

This paper presents hierarchical clustering algorithms for land cover mapping problem using multi-spectral satellite images. In unsupervised techniques, the automatic generation of number of clusters and its centers for a huge database is not exploited to their full potential. Hence, a hierarchical clustering algorithm that uses splitting and merging techniques is proposed. Initially, the splitting method is used to search for the best possible number of clusters and its centers using Mean Shift Clustering (MSC), Niche Particle Swarm Optimization (NPSO) and Glowworm Swarm Optimization (GSO). Using these clusters and its centers, the merging method is used to group the data points based on a parametric method (k-means algorithm). A performance comparison of the proposed hierarchical clustering algorithms (MSC, NPSO and GSO) is presented using two typical multi-spectral satellite images - Landsat 7 thematic mapper and QuickBird. From the results obtained, we conclude that the proposed GSO based hierarchical clustering algorithm is more accurate and robust.

Is land really a constraint for the utilization of solar energy in India?

This article compares the land use in solar energy technologies with conventional energy sources. This has been done by introducing two parameters called land transformation and land occupation. It has been shown that the land area transformed by solar energy power generation is small compared to hydroelectric power generation, and is comparable with coal and nuclear energy power generation when life-cycle transformations are considered. We estimate that 0.97% of total land area or 3.1% of the total uncultivable land area of India would be required to generate 3400 TWh/yr from solar energy power systems in conjunction with other renewable energy sources.

Albedo enhancement over land to counteract global warming: impacts on hydrological cycle

A recent modelling study has shown that precipitation and runoff over land would increase when the reflectivity of marine clouds is increased to counter global warming. This implies that large scale albedo enhancement over land could lead to a decrease in runoff over land. In this study, we perform simulations using NCAR CAM3.1 that have implications for Solar Radiation Management geoengineering schemes that increase the albedo over land. We find that an increase in reflectivity over land that mitigates the global mean warming from a doubling of CO2 leads to a large residual warming in the southern hemisphere and cooling in the northern hemisphere since most of the land is located in northern hemisphere. Precipitation and runoff over land decrease by 13.4 and 22.3%, respectively, because of a large residual sinking motion over land triggered by albedo enhancement over land. Soil water content also declines when albedo over land is enhanced. The simulated magnitude of hydrological changes over land are much larger when compared to changes over oceans in the recent marine cloud albedo enhancement study since the radiative forcing over land needed (-8.2 W m(-2)) to counter global mean radiative forcing from a doubling of CO2 (3.3 W m(-2)) is approximately twice the forcing needed over the oceans (-4.2 W m(-2)). Our results imply that albedo enhancement over oceans produce climates closer to the unperturbed climate state than do albedo changes on land when the consequences on land hydrology are considered. Our study also has important implications for any intentional or unintentional large scale changes in land surface albedo such as deforestation/afforestation/reforestation, air pollution, and desert and urban albedo modification.

Hybrid molecules of carvacrol and benzoyl urea/thiourea with potential applications in agriculture and medicine

Benzoyl phenyl urea, a class of insect growth regulator's acts by inhibiting chitin synthesis. Carvacrol, a naturally occurring monoterpenoid is an effective antifungal agent. We have structurally modified carvacrol (2-methyl-5-1-methylethyl] phenol) by introducing benzoylphenyl urea linkage. Two series of benzoylcarvacryl thiourea (BCTU, 4a-f) and benzoylcarvacryl urea (BCU, 5a-f) derivatives were prepared and characterized by elemental analysis, IR, H-1 and C-13 NMR and Mass spectroscopy. Derivatives 4b, 4d, 4e, 4f and 5d, 5f showed comparable insecticidal activity with the standard BPU lufenuron against Dysdercus koenigii. BCTU derivatives 4c, 4e and BCU 5c showed good antifungal activity against phytopathogenic fungi viz. Magnaporthe grisae, Fusarium oxysporum, Dreschlera oryzae; food spoilage yeasts viz. Debaromyces hansenii, Pichia membranifaciens; and human pathogens viz. Candida albicans and Cryptococcus neoformans. Compounds 5d, 5e and 5f showed potent activity against human pathogens. Moderate and selective activity was observed for other compounds. All the synthesized compounds were non-haemolytic. These compounds have potential application in agriculture and medicine. (C) 2012 Elsevier Ltd. All rights reserved.

Algal biofuel production and mitigation potential in India

Energy and energy services are the backbone of growth and development in India and is increasingly dependent upon the use of fossil based fuels that lead to greenhouse gases (GHG) emissions and related concerns. Algal biofuels are being evolved as carbon (C)-neutral alternative biofuels. Algae are photosynthetic microorganisms that convert sunlight, water and carbon dioxide (CO2) to various sugars and lipids Tri-Acyl-Glycols (TAG) and show promise as an alternative, renewable and green fuel source for India. Compared to land based oilseed crops algae have potentially higher yields (5-12 g/m(2)/d) and can use locations and water resources not suited for agriculture. Within India, there is little additional land area for algal cultivation and therefore needs to be carried out in places that are already used for agriculture, e.g. flooded paddy lands (20 Mha) with village level technologies and on saline wastelands (3 Mha). Cultivating algae under such conditions requires novel multi-tier, multi-cyclic approaches of sharing land area without causing threats to food and water security as well as demand for additional fertilizer resources by adopting multi-tier cropping (algae-paddy) in decentralized open pond systems. A large part of the algal biofuel production is possible in flooded paddy crop land before the crop reaches dense canopies, in wastewaters (40 billion litres per day), in salt affected lands and in nutrient/diversity impoverished shallow coastline fishery. Mitigation will be achieved through avoidance of GHG, C-capture options and substitution of fossil fuels. Estimates made in this paper suggest that nearly half of the current transportation petro-fuels could be produced at such locations without disruption of food security, water security or overall sustainability. This shift can also provide significant mitigation avenues. The major adaptation needs are related to socio-technical acceptance for reuse of various wastelands, wastewaters and waste-derived energy and by-products through policy and attitude change efforts.

Quasi-based hierarchical clustering for land cover mapping using satellite images

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

Remote sensing applications in water resources

With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent temporal resolution sufficient to represent the dynamics of the hydrologic processes, remote sensing techniques have significantly changed the water resources assessment and management methodologies. Remote sensing techniques have been widely used to delineate the surface water bodies, estimate meteorological variables like temperature and precipitation, estimate hydrological state variables like soil moisture and land surface characteristics, and to estimate fluxes such as evapotranspiration. Today, near-real time monitoring of flood, drought events, and irrigation management are possible with the help of high resolution satellite data. This paper gives a brief overview of the potential applications of remote sensing in water resources.

Integrating biodiversity and conservation with modern agricultural landscapes

To achieve food security and meet the demands of the ever-growing human populations, farming systems have assumed unsustainable practices to produce more from a finite land area. This has been cause for concern mainly due to the often-irreversible damage done to the otherwise productive agricultural landscapes. Agro-ecology is proclaimed to be deteriorating due to eroding integrity of connected ecological mosaics and vulnerability to climate change. This has contributed to declining species diversity, loss of buffer vegetation, fragmentation of habitats, and loss of natural pollinators or predators, which eventually leads to decline in ecosystem services. Currently, a hierarchy of conservation initiatives is being considered to restore ecological integrity of agricultural landscapes. However, the challenge of identifying a suitable conservation strategy is a daunting task in view of socio-ecological factors that may constrain the choice of available strategies. One way to mitigate this situation and integrate biodiversity with agricultural landscapes is to implement offset mechanisms, which are compensatory and balancing approaches to restore the ecological health and function of an ecosystem. This needs to be tailored to the history of location specific agricultural practices, and the social, ecological and environmental conditions. The offset mechanisms can complement other initiatives through which farmers are insured against landscape-level risks such as droughts, fire and floods. For countries in the developing world with significant biodiversity and extensive agriculture, we should promote a comprehensive model of sustainable agricultural landscapes and ecosystem services, replicable at landscape to regional scales. Arguably, the model can be a potential option to sustain the integrity of biodiversity mosaic in agricultural landscapes.

Employing synergistic interactions between few-layer WS2 and reduced graphene oxide to improve lithium storage, cyclability and rate capability of Li-ion batteries

The aim of the contribution is to introduce a high performance anode alternative to graphite for lithium-ion batteries (LiBs). A simple process was employed to synthesize uniform graphene-like few-layer tungsten sulfide (WS2) supported on reduced graphene oxide (RGO) through a hydrothermal synthesis route. The WS2-RGO (80:20 and 70:30) composites exhibited good enhanced electrochemical performance and excellent rate capability performance when used as anode materials for lithium-ion batteries. The specific capacity of the WS2-RGO composite delivered a capacity of 400-450 mAh g(-1) after 50 cycles when cycled at a current density of 100 mA g(-1). At 4000 mA g(-1), the composites showed a stable capacity of approximately 180-240 mAh g(-1), respectively. The noteworthy electrochemical performance of the composite is not additive, rather it is synergistic in the sense that the electrochemical performance is much superior compared to both WS2 and RGO. As the observed lithiation/delithiation for WS2-RGO is at a voltage 1.0 V (approximate to 0.1 V for graphite, Li* /Li), the lithium-ion battery with WS2-RGO is expected to possess high interface stability, safety and management of electrical energy is expected to be more efficient and economic. (C) 2013 Elsevier Ltd. All rights reserved.

Seasonal variability of rainfall recorded in growth bands of the Giant African Land Snail Lissachatina fulica (Bowdich) from India

Seasonal rainfall patterns in Bangalore, India, have been reconstructed using stable isotopic ratios in the growth bands of Giant African Land Snail shells. The present study was conducted at Bangalore, India which receives rain during the summer months. The oxygen isotopic record in the rainwater samples collected during different months covering the period of the summer monsoon of the year 2008 is compared with the isotopic ratio in the gastropod growth bands deposited simultaneously. The chronology of the shell growth band is independently established assuming the growth rate observed in a chamber experiment maintaining similar relative humidity and temperature conditions. A consistent pattern observed in the isotopic ratio in the gastropod growth bands and rainwater is demonstrated and provides a novel approach for precipitation reconstruction at seasonal and weekly time scales. This approach of using isotopic ratios in the gastropod growth bands for rainfall can serve as a substitute for filling gaps in rainfall data and for cases where no rain records are available. In addition, they can be used to determine the frequencies and magnitudes of dry spells from the past records. (C) 2013 Elsevier B.V. All rights reserved.

Assimilation of endmember variability in spectral for urban land cover extraction mixture analysis

Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.