968 resultados para Atmospheric humidity
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Atmospheric chemistry is a branch of atmospheric science where major focus is the composition of the Earth's atmosphere. Knowledge of atmospheric composition is essential due to its interaction with (solar and terrestrial) radiation and interactions of atmospheric species (gaseous and particulate matter) with living organisms. Since atmospheric chemistry covers a vast range of topics, in this article the focus is on the chemistry of atmospheric aerosols with special emphasis on the Indian region. I present a review of the current state of knowledge of aerosol chemistry in India and propose future directions.
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PEFCs employing Nafion-silica (Nafion-SiO2) and Nafion-mesoporous zirconium phosphate (Nafion-MZP) composite membranes are subjected to accelerated-durability test at 100 degrees C and 15% relative humidity (RH) at open-circuit voltage (OCV) for 50 h and performance compared with the PEFC employing pristine Nafion-1135 membrane. PEFCs with composite membranes sustain the operating voltage better with fluoride-ion-emission rate at least an order of magnitude lower than PEFC with pristine Nafion-1135 membrane. Reduced gas-crossover, fast fuel-cell-reaction kinetics and superior performance of the PEFCs with Nafion-SiO2 and Nafion-MZP composite membranes in relation to the PEFC with pristine Nafion-1135 membrane support the long-term operational usage of the former in PEFCs. An 8-cell PEFC stack employing Nafion-SiO2 composite membrane is also assembled and successfully operated at 60 degrees C without external humidification.
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We have demonstrated a simple, scalable and inexpensive method based on microwave plasma for synthesizing 5 to 10 g/h of nanomaterials. Luminescent nano silicon particles were synthesized by homogenous nucleation of silicon vapour produced by the radial injection of silicon tetrachloride vapour and nano titanium nitride was synthesized by using liquid titanium tetrachloride as the precursor. The synthesized nano silicon and titanium nitride powders were characterized by XRD, XPS, TEM, SEM and BET. The characterization techniques indicated that the synthesized powders were indeed crystalline nanomaterials.
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Polyaniline-CaTiO3 nanocomposites with their various weight percentages were prepared by chemical oxidative in situ polymerization technique. The prepared composites were characterized by Fourier transform infrared spectroscopy, scanning electronic microscope, and X-ray diffraction. The temperature-dependent dc conductivity of polyaniline-CaTiO3 nanocomposite was studied within the range of 40-200 degrees C and found that 50 wt% shows high conductivity compared to other composites. Humidity sensor properties of polyaniline-CaTiO3 nanocomposite show better sensing properties and exhibit good linearity in sensing response curve, which discuss the implications of distortions and nonstoichiometry on their physical properties. Among all composites, 50 wt% of polyaniline-CaTiO3 nanocomposites show high sensitivity up to similar to 90% and their response-recovery times are 500 and 453 s, respectively.
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The failure of atmospheric general circulation models (AGCMs) forced by prescribed SST to simulate and predict the interannual variability of Indian/Asian monsoon has been widely attributed to their inability to reproduce the actual sea surface temperature (SST)-rainfall relationship in the warm Indo-Pacific oceans. This assessment is based on a comparison of the observed and simulated correlation between the rainfall and local SST. However, the observed SSTconvection/rainfall relationship is nonlinear and for this a linear measure such as the correlation is not an appropriate measure. We show that the SST-rainfall relationship simulated by atmospheric and coupled general circulation models in IPCC AR4 is nonlinear, as observed, and realistic over the tropical West Pacific (WPO) and the Indian Ocean (IO). The SST-rainfall pattern simulated by the coupled versions of these models is rather similar to that from the corresponding atmospheric one, except for a shift of the entire pattern to colder/warmer SSTs when there is a cold/warm bias in the coupled version.
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Recent studies show that fast climate response on time scales of less than a month can have important implications for long-term climate change. In this study, we investigate climate response on the time scale of days to weeks to a step-function quadrupling of atmospheric CO2 and contrast this with the response to a 4% increase in solar irradiance. Our simulations show that significant climate effects occur within days of a stepwise increase in both atmospheric CO2 content and solar irradiance. Over ocean, increased atmospheric CO2 warms the lower troposphere more than the surface, increasing atmospheric stability, moistening the boundary layer, and suppressing evaporation and precipitation. In contrast, over ocean, increased solar irradiance warms the lower troposphere to a much lesser extent, causing a much smaller change in evaporation and precipitation. Over land, both increased CO2 and increased solar irradiance cause rapid surface warming that tends to increase both evaporation and precipitation. However, the physiological effect of increased atmospheric CO2 on plant stomata reduces plant transpiration, drying the boundary layer and decreasing precipitation. This effect does not occur with increased solar irradiance. Therefore, differences in climatic effects from CO2 versus solar forcing are manifested within days after the forcing is imposed.
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We present here, an experimental set-up developed for the first time in India for the determination of mixing ratio and carbon isotopic ratio of air-CO2. The set-up includes traps for collection and extraction of CO2 from air samples using cryogenic procedures, followed by the measurement of CO2 mixing ratio using an MKS Baratron gauge and analysis of isotopic ratios using the dual inlet peripheral of a high sensitivity isotope ratio mass spectrometer (IRMS) MAT 253. The internal reproducibility (precision) for the PC measurement is established based on repeat analyses of CO2 +/- 0.03 parts per thousand. The set-up is calibrated with international carbonate and air-CO2 standards. An in-house air-CO2 mixture, `OASIS AIRMIX' is prepared mixing CO2 from a high purity cylinder with O-2 and N-2 and an aliquot of this mixture is routinely analyzed together with the air samples. The external reproducibility for the measurement of the CO2 mixing ratio and carbon isotopic ratios are +/- 7 (n = 169) mu mol.mol(-1) and +/- 0.05 (n = 169) parts per thousand based on the mean of the difference between two aliquots of reference air mixture analyzed during daily operation carried out during November 2009-December 2011. The correction due to the isobaric interference of N2O on air-CO2 samples is determined separately by analyzing mixture of CO2 (of known isotopic composition) and N2O in varying proportions. A +0.2 parts per thousand correction in the delta C-13 value for a N2O concentration of 329 ppb is determined. As an application, we present results from an experiment conducted during solar eclipse of 2010. The isotopic ratio in CO2 and the carbon dioxide mixing ratio in the air samples collected during the event are different from neighbouring samples, suggesting the role of atmospheric inversion in trapping the emitted CO2 from the urban atmosphere during the eclipse.
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Two atmospheric inversions (one fine-resolved and one process-discriminating) and a process-based model for land surface exchanges are brought together to analyse the variations of methane emissions from 1990 to 2009. A focus is put on the role of natural wetlands and on the years 2000-2006, a period of stable atmospheric concentrations. From 1990 to 2000, the top-down and bottom-up visions agree on the time-phasing of global total and wetland emission anomalies. The process-discriminating inversion indicates that wetlands dominate the time-variability of methane emissions (90% of the total variability). The contribution of tropical wetlands to the anomalies is found to be large, especially during the post-Pinatubo years (global negative anomalies with minima between -41 and -19 Tg yr(-1) in 1992) and during the alternate 1997-1998 El-Nino/1998-1999 La-Nina (maximal anomalies in tropical regions between +16 and +22 Tg yr(-1) for the inversions and anomalies due to tropical wetlands between +12 and +17 Tg yr(-1) for the process-based model). Between 2000 and 2006, during the stagnation of methane concentrations in the atmosphere, the top-down and bottom-up approaches agree on the fact that South America is the main region contributing to anomalies in natural wetland emissions, but they disagree on the sign and magnitude of the flux trend in the Amazon basin. A negative trend (-3.9 +/- 1.3 Tg yr(-1)) is inferred by the process-discriminating inversion whereas a positive trend (+1.3 +/- 0.3 Tg yr(-1)) is found by the process model. Although processed-based models have their own caveats and may not take into account all processes, the positive trend found by the B-U approach is considered more likely because it is a robust feature of the process-based model, consistent with analysed precipitations and the satellite-derived extent of inundated areas. On the contrary, the surface-data based inversions lack constraints for South America. This result suggests the need for a re-interpretation of the large increase found in anthropogenic methane inventories after 2000.
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Two Pd-6 molecular aggregates (1 and 2), self-sorted via a template-free three-component self-assembly process, represent new examples of discrete architectures exhibiting very high proton conductivity 0.78 x 10(-3) S cm(-1) (1) and 0.22 X 10(-3) S cm(-1) (2)] at 300 K at low relative humidity (B46%) with low activation energy comparable to that of currently used Nafion in fuel cells.
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Systematic investigation on synergetic effects of geometry, length, denticity, and asymmetry of donors was performed through the formation of a series of uncommon Pd-II aggregates by employing the donor in a multicomponent self-assembly of a cis-blocked 90 degrees Pd-II acceptor and a tetratopic donor. Some of these assemblies represent the first examples of these types of structures, and their formation is not anticipated by only taking the geometry of the donor and the acceptor building units into account. Analysis of the crystal packing of the X-ray structure revealed several H bonds between the counteranions (NO3-) and water molecules (OHON). Moreover, H-bonded 3D-networks of water are present in the molecular pockets, which show water-adsorption properties with some variation in water affinity. Interestingly, these complexes exhibit proton conductivity (1.87x10(-5)-6.52x10(-4)Scm(-1)) at 296K and low relative humidity (ca. 46%) with activation energies of 0.29-0.46eV. Moreover, the conductivities further increase with the enhancement of humidity. The ability of these assemblies to exhibit proton-conducting properties under low-humidity conditions makes these materials highly appealing as electrolytes in batteries and in fuel-cell applications.
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This study reports characteristics of inertia-gravity waves (IGWs) in the atmospheric boundary layer during the passage of Tropical Cylone-03B, using the Doppler Sound Detection and Ranging (SODAR) observations at the Indian tropical station of Gadanki (13.45 degrees N, 79.2 degrees E; near the east coast of India). Wavelet analysis of horizontal winds indicates significant wave motion (60h) near the characteristic inertial period. The hodograph analysis of the filtered winds shows an anti-cyclonic turning of horizontal wind with height and time, indicating the presence of IGW. This study finds important implications in boundary layer dynamics during the passage of tropical cyclones.
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In the present work, the spray structure of diesel from a 200-mu m, single-hole solenoid injector is studied using microscopic imaging at injection pressures of 700, 1000 and 1400 bar for various gas pressures. A long-distance microscope with a high resolution camera is used for spray visualization with a direct imaging technique. This study shows that even at very high injection pressures, the spray structure in an ambient environment of atmospheric pressure reveals presence of entangled ligaments and non-spherical droplets during the injection period. With increase in the injection pressure, the ligaments tend to get smaller and spread radially. The spray structure studies are also conducted at high gas pressures in a specially designed high pressure chamber with optical access. The near nozzle spray structure at the end of the injection shows that the liquid jet breakup is improved with increase in gas density. The droplet size measurement is possible only late in the injection duration when the breakup appears to be complete and mostly spherical droplets are observed. Hence, droplet size measurements are performed after 1.3 ms from start of the injection pulse. Spatial and temporal variation in Sauter Mean `Diameter (SMD) is observed and reported for the case corresponding to an injection pressure of 700 bar. Overall, this study has highlighted the importance of verifying the extentof atomization and droplet shape even in dense sprays before using conventional dropsizing methods such as PDPA.
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Strong atmospheric turbulence is a major hindrance in wireless optical communication systems. In this paper, the performance of a wireless optical communication system is analyzed using different modulation formats such as, binary phase shift keying-subcarrier intensity modulation (BPSK-SIM), differential phase shift keying (DPSK), differential phase shift keying-subcarrier intensity modulation (DPSK-SIM), Mary pulse position modulation (M-PPM) and polarization shift keying (PoISK). The atmospheric channel is modeled for strong atmospheric turbulences with combined effect of turbulence and pointing errors. Novel closed-form analytical expressions for average bit error rate (BER), channel capacity and outage probability for the various modulation techniques, viz. BPSK-SIM, DPSK, DPSK-SIM, PoISK and M-PPM are derived. The simulated results for BER, channel capacity and outage probability of various modulation techniques are plotted and analyzed. (C) 2014 Elsevier GmbH. All rights reserved.
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Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.
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The sensing of relative humidity (RH) at room temperature has potential applications in several areas ranging from biomedical to horticulture, paper, and textile industries. In this paper, a highly sensitive humidity sensor based on carbon nanotubes (CNTs) coated on the surface of an etched fiber Bragg grating (EFBG) sensor has been demonstrated, for detecting RH over a wide range of 20%-90% at room temperature. When water molecules interact with the CNT coated EFBG, the effective refractive index of the fiber core changes, resulting in a shift in the Bragg wavelength. It has been possible to achieve a high sensitivity of similar to 31 pm/% RH, which is the highest compared with many of the existing FBG-based humidity sensors. The limit of detection in the CNT coated EFBG has been found to be similar to 0.03 RH. The experimental data shows a linear response of Bragg wavelength shift with increase in humidity. This novel method of incorporating CNTs on to the FBG sensor for humidity sensing has not been reported before.