Forest biomass estimation using remote sensing and field inventory: a case study of Tripura, India.

Forests are the potential source for managing carbon sequestration, regulating climate variations and balancing universal carbon equilibrium between sources and sinks. Further, assessment of biomass, carbon stock, and its spatial distribution is prerequisite for monitoring the health of forest ecosystem. Moreover, vegetation field inventories are valuable source of data for estimating aboveground biomass (AGB), density, and the carbon stored in biomass of forest vegetation. In view of the importance of biomass, the present study makes an attempt to estimate temporal AGB of Tripura State, India, using Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), leaf area index (LAI) and the field inventory data through geospatial techniques. A model was developed for establishing the relationship between biomass, LAI, and NDVI in the selected study site. The study also aimed to improve method for quantifying and verifying inventory-based biomass stock estimation. The results demonstrate the correlation value obtained between LAI and NDVI were 0.87 and 0.53 for the years 2011 and 2014, respectively. The correlation value between estimated AGB with LAI were found as 0.66 and 0.69, while with NDVI, the values were obtained as 0.64 and 0.94 for the years 2011 and 2014, respectively. The regression model of measured biomass with MODIS NDVI and LAI was developed for the data obtained during the period 2011-2014. The developed model was used to estimate the spatial distribution of biomass and its relationship between LAI and NDVI. The R2 values obtained were 0.832 for estimated and the measured AGB during the training and 0.826 for the validation. The results indicate that the methodology adopted in this study can help in selecting best fit model for analyzing relationship between AGB and NDVI/LAI and for estimating biomass using allometric equation at various spatial scales. The developed output thematic map showed an average biomass distribution of 32-94 Mg ha-1. The highest biomass values (72-95 Mg ha -1) was confined to the dense region of the forest while the lowest biomass values (32-46 Mg ha-1) was identified in the outer regions of the study site.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data.

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

Vigorous Appraisal of Fluoride on Industrial Proponent in Thermal Power Plant over Anthropoid Biosphere Using F(-) Ion-Selective Electrode.

This study was conducted to analyze the impact of fluoride in the anthropogenic condition in an industrial region promoting and affecting the health of the workers. Fluoride is toxic to humans in high concentrations, such as can occur in persons working in fluoride-containing mineral industries like aluminum industries. When workers are exposed to fluoride-containing minerals, they can suffer from a variety of health problems, such as dental disease. This paper presents the relationship of different clinical conditions correlated against the fluoride level. Contributing clinical aspects, such as morbidity, dysentery, overcrowding, and skin disease, are also studied to assess the consequences of fluoride upon consistent exposure. The relationship between pH and hardness of water with fluoride was measured, and then spatial maps were generated. The investigations resulted in a conclusion that hardness of water had a more pronounced impact on the level of fluoride concentration as compared with pH. Water with more hardness contains more fluoride concentration (25 mg/ml) as compared with soft water (4 mg/ml). This paper also revealed the concentration of fluoride content in the bodies of aluminum plant workers, which varied from 0.06 to 0.17 mg/L of blood serum in the case of pot room workers and 0.01 to 0.04 mg/L in the case of non-pot room workers. In fingernails, it varied from 0.09 to 3.77 mg/L and 0.39 to 1.15 mg/L in the case of pot room and non-pot room workers, respectively. In urine, it varied from 0.53 to 9.50 mg/L in pot room workers and 0.29 to 1.80 mg/L in non-pot room workers. This paper concluded that water was safe for drinking purposes if it has a low hardness (60-140 mg/ml) and pH (7.1-7.4).

Role of nanostructured networks as analytical tools for biological systems.

In recent years, nanostructured materials have emerged as potential candidates offering excellent prospects for interfacing the detection of biomolecules. Nanomaterials such as nanoparticles, nanostructured silicates, nano-sized metal oxides, nanostructured polymers, quantum dots, nanocomposites and sensing nanodevices are being utilized worldwide for fabrication of chemical sensors and sensor arrays with tailored characteristics and tuneable properties. Among above, the materials that create a matrix structure at the nanoscale level are particularly fascinating. The exceptional physical, chemical, mechanical and electrical properties of these matrices advocate their application in the electrode modification resulting in sensing devices and transducers with superior performance. Here we present an overview of different types of nanostructured networks that are applied in sensor development. The role of these materials in chemical sensors is described along with the techniques that are the backbone of the sensing process. Special attention has been given to some key sensors that are directly related to human physiology and have clinical significance.

Cyclohexanone and 3-aminopropyltrimethoxysilane mediated controlled synthesis of mixed nickel-iron hexacyanoferrate nanosol for selective sensing of glutathione and hydrogen peroxide.

We report the cyclohexanone and 3-aminopropyltrimethoxysilane (3-APTMS) mediated controlled synthesis of mixed nickel-iron hexacyanoferrate (Ni-Fehcf) nanosol of 34 nm average size. The new method allows the synthesis of a variety of mixed metal hexacyanoferrate (Mhcf) nanodispersion along with option for controlling the inversion of electrochemichemical behavior of Prussian blue(PB) into desired Mhcf. The typical process involves the mixing of 3-APTMS treated potassium ferricyanide with desired concentrations of nickel sulfate containing fixed amount of cyclohexanone resulting in a uniform spherical nanodispersion of mixed Ni-Fehcf. The different molar ratio of Ni : Fe (i.e. 1 : 1; 1 : 5 and 1 : 10) yielded a mixed Ni-Fehcf showing three different electrochemical properties ascribed to nickel hexacyanoferrate (Nihcf); both Nihcf and PB, and PB respectively. The mixed Ni-Fehcf resulting from a 1 : 5 Ni : Fe molar ratio has been found to be an excellent material for selective electroanalytic applications attributed to hydrogen peroxide and glutathione sensing due to the presence of PB and Nihcf behaviors respectively. The electrocatalytic property of Nihcf in mixed Ni-Fehcf is significantly better than that of conventional Nihcf for glutathione analysis and further increases on the incorporation of AuNPs.

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment.

This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.

3-Glycidoxypropyltrimethoxysilane mediated in situ synthesis of noble metal nanoparticles: application to hydrogen peroxide sensing.

The in situ synthesis is reported of noble metal nanoparticles via 3-glycidoxypropyltrimethoxysilane mediated reduction of 3-aminopropyltrimethoxysilane treated metal salts during sol-gel processing. The method described involves the synthesis of uniform spherical nanoparticles of gold, silver and palladium with controlled size that can be directly utilized for thin film preparation. A detailed study of the synthesis and application of gold nanoparticles to the electrochemical detection of hydrogen peroxide was carried out and reveals that the amplification of hydrogen peroxide sensing is size-dependent. In addition, these nanoparticles exhibit excellent compatibility towards composite preparation. As an example, a nanocomposite with Prussian Blue (PB) is synthesized and found to be useful for the fabrication of chemically modified electrodes (CME). The resulting CME shows dramatic improvement in the electrochemistry of PB with gradual enhancement in electrocatalytic efficiency towards hydrogen peroxide sensing. The nanocomposite is used to study the direct and horseradish peroxidase (HRP)-catalyzed reduction of hydrogen peroxide. The results recorded for hydrogen peroxide analysis show an improvement in sensitivity and limit of detection on decreasing the size of gold nanoparticles in all cases.