Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data

Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.

Graphene oxide-Fe3O4 nanoparticle composite with high transverse proton relaxivity value for magnetic resonance imaging

The potential of graphene oxide-Fe3O4 nanoparticle (GO-Fe3O4) composite as an image contrast enhancing material in magnetic resonance imaging has been investigated. Proton relaxivity values were obtained in three different homogeneous dispersions of GO-Fe3O4 composites synthesized by precipitating Fe3O4 nanoparticles in three different reaction mixtures containing 0.01 g, 0.1 g, and 0.2 g of graphene oxide. A noticeable difference in proton relaxivity values was observed between the three cases. A comprehensive structural and magnetic characterization revealed discrete differences in the extent of reduction of the graphene oxide and spacing between the graphene oxide sheets in the three composites. The GO-Fe3O4 composite framework that contained graphene oxide with least extent of reduction of the carboxyl groups and largest spacing between the graphene oxide sheets provided the optimum structure for yielding a very high transverse proton relaxivity value. It was found that the GO-Fe3O4 composites possessed good biocompatibility with normal cell lines, whereas they exhibited considerable toxicity towards breast cancer cells. (C) 2015 AIP Publishing LLC.

Looking beyond parks: the conservation value of unprotected areas for hornbills in Arunachal Pradesh, Eastern Himalaya

The loss of tropical forests and associated biodiversity is a global concern. Conservation efforts in tropical countries such as India have mostly focused on state-administered protected areas despite the existence of vast tracts of forest outside these areas. We studied hornbills (Bucerotidae), an ecologically important vertebrate group and a flagship for tropical forest conservation, to assess the importance of forests outside protected areas in Arunachal Pradesh, north-east India. We conducted a state-wide survey to record encounters with hornbills in seven protected areas, six state-managed reserved forests and six community-managed unclassed forests. We estimated the density of hornbills in one protected area, four reserved forests and two unclassed forests in eastern Arunachal Pradesh. The state-wide survey showed that the mean rate of encounter of rufous-necked hornbills Aceros nipalensis was four times higher in protected areas than in reserved forests and 22 times higher in protected areas than in unclassed forests. The mean rate of encounter of wreathed hornbills Rhyticeros undulatus was twice as high in protected areas as in reserved forests and eight times higher in protected areas than in unclassed forests. The densities of rufous-necked hornbill were higher inside protected areas, whereas the densities of great hornbill Buceros bicornis and wreathed hornbill were similar inside and outside protected areas. Key informant surveys revealed possible extirpation of some hornbill species at sites in two protected areas and three unclassed forests. These results highlight a paradoxical situation where individual populations of hornbills are being lost even in some legally protected habitat, whereas they continue to persist over most of the landscape. Better protection within protected areas and creative community-based conservation efforts elsewhere are necessary to maintain hornbill populations in this biodiversity-rich region.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

Modelling the influence of land-use changes on biophysical and biochemical interactions at regional and global scales

Land-use changes since the start of the industrial era account for nearly one-third of the cumulative anthropogenic CO2 emissions. In addition to the greenhouse effect of CO2 emissions, changes in land use also affect climate via changes in surface physical properties such as albedo, evapotranspiration and roughness length. Recent modelling studies suggest that these biophysical components may be comparable with biochemical effects. In regard to climate change, the effects of these two distinct processes may counterbalance one another both regionally and, possibly, globally. In this article, through hypothetical large-scale deforestation simulations using a global climate model, we contrast the implications of afforestation on ameliorating or enhancing anthropogenic contributions from previously converted (agricultural) land surfaces. Based on our review of past studies on this subject, we conclude that the sum of both biophysical and biochemical effects should be assessed when large-scale afforestation is used for countering global warming, and the net effect on global mean temperature change depends on the location of deforestation/afforestation. Further, although biochemical effects trigger global climate change, biophysical effects often cause strong local and regional climate change. The implication of the biophysical effects for adaptation and mitigation of climate change in agriculture and agroforestry sectors is discussed. center dot Land-use changes affect global and regional climates through both biochemical and biophysical process. center dot Climate effect from biophysical process depends on the location of land-use change. center dot Climate mitigation strategies such as afforestation/reforestation should consider the net effect of biochemical and biophysical processes for effective mitigation. center dot Climate-smart agriculture could use bio-geoengineering techniques that consider plant biophysical characteristics such as reflectivity and water use efficiency.

Isolating the impacts of land use and climate change on streamflow

Quantifying the isolated and integrated impacts of land use (LU) and climate change on streamflow is challenging as well as crucial to optimally manage water resources in river basins. This paper presents a simple hydrologic modeling-based approach to segregate the impacts of land use and climate change on the streamflow of a river basin. The upper Ganga basin (UGB) in India is selected as the case study to carry out the analysis. Streamflow in the river basin is modeled using a calibrated variable infiltration capacity (VIC) hydrologic model. The approach involves development of three scenarios to understand the influence of land use and climate on streamflow. The first scenario assesses the sensitivity of streamflow to land use changes under invariant climate. The second scenario determines the change in streamflow due to change in climate assuming constant land use. The third scenario estimates the combined effect of changing land use and climate over the streamflow of the basin. Based on the results obtained from the three scenarios, quantification of isolated impacts of land use and climate change on streamflow is addressed. Future projections of climate are obtained from dynamically downscaled simulations of six general circulation models (GCMs) available from the Coordinated Regional Downscaling Experiment (CORDEX) project. Uncertainties associated with the GCMs and emission scenarios are quantified in the analysis. Results for the case study indicate that streamflow is highly sensitive to change in urban areas and moderately sensitive to change in cropland areas. However, variations in streamflow generally reproduce the variations in precipitation. The combined effect of land use and climate on streamflow is observed to be more pronounced compared to their individual impacts in the basin. It is observed from the isolated effects of land use and climate change that climate has a more dominant impact on streamflow in the region. The approach proposed in this paper is applicable to any river basin to isolate the impacts of land use change and climate change on the streamflow.

Visible light-induced cytotoxicity of a dinuclear iron(III) complex of curcumin with low-micromolar IC50 value in cancer cells

Photoactive metal complexes have emerged as potential candidates in the photodynamic therapy (PDT) of cancer. We present here the synthesis, characterization and visible light-triggered anticancer activity of two novel mixed-ligand oxo-bridged iron(III) complexes, viz., {Fe(L)(acac)}(2)(mu-O)](ClO4)(2) (1) and {Fe (L)(cur)}(2)(mu-O)](ClO4)(2) (2) where L is bis-(2-pyridylmethyl)-benzylamine, acac is acetylacetonate and cur is the monoanion of curcumin (bis(4-hydroxy-3-methoxyphenyl)-1,6-diene-3,5-dione). The crystal structure of complex 1 (as PF6 salt, 1a) shows distorted octahedral geometry of each iron(III) centre formed by the FeN3O3 core. The 1: 2 electrolytic complexes are stable in solution and retain their oxo-bridged identity in aqueous medium. Complex 2 has a strong absorption band in the visible region and shows promising photocytotoxicity in HeLa and MCF-7 cancer cells in visible light giving respective IC50 values of 3.1 +/- 0.4 lM and 4.9 +/- 0.5 lM while remains non-toxic in the dark (IC50 > 50 lM). The control complex 1 is inactive both in the light and dark. Complex 2 accumulates in cytoplasm of HeLa and MCF-7 cells as evidenced from fluorescence microscopy and triggers apoptotic cell death via light-assisted generation of reactive oxygen species (ROS). Taken together, complex 2 with its promising photocytotoxicity but negligible dark toxicity in cancer cells has significant photochemotherapeutic potential for applications in PDT. (C) 2015 Elsevier B.V. All rights reserved.