Journal articles: 'Atmospheric processing'

1

Wahlgren, Roland. "Atmospheric water vapour processing." Waterlines 12, no. 2 (October 1993): 20–22. http://dx.doi.org/10.3362/0262-8104.1993.039.

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Zhao, R., A. K. Y. Lee, L. Huang, X. Li, F. Yang, and J. P. D. Abbatt. "Photochemical processing of aqueous atmospheric brown carbon." Atmospheric Chemistry and Physics Discussions 15, no. 2 (January 30, 2015): 2957–96. http://dx.doi.org/10.5194/acpd-15-2957-2015.

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Abstract. Atmospheric Brown Carbon (BrC) is a collective term for light absorbing organic compounds in the atmosphere. While the identification of BrC and its formation mechanisms is currently a central effort in the community, little is known about the atmospheric removal processes of aerosol BrC. As a result, we report a series of laboratory studies of photochemical processing of BrC in the aqueous phase, by direct photolysis and OH oxidation. Solutions of ammonium sulfate mixed with glyoxal (GLYAS) or methylglyoxal (MGAS) are used as surrogates for a class of secondary BrC mediated by imine intermediates. Three nitrophenol species, namely 4-nitrophenol, 5-nitroguaiacol and 4-nitrocatechol, were investigated as a class of water soluble BrC originating from biomass burning. Photochemical processing induced significant changes in the absorptive properties of BrC. The imine-mediated BrC solutions exhibited rapid photo-bleaching with both direct photolysis and OH oxidation, with atmospheric half-lives of minutes to a few hours. The nitrophenol species exhibited photo-enhancement in the visible range during direct photolysis and the onset of OH oxidation, but rapid photo-bleaching was induced by further OH exposure on an atmospheric timescale of an hour or less. To illustrate atmospheric relevance of this work, we also performed direct photolysis experiments on water soluble organic carbon extracted from biofuel combustion samples and observed rapid changes in optical properties of these samples as well. Overall, these experiments indicate that atmospheric models need to incorporate representations of atmospheric processing of BrC species to accurately model their radiative impacts.

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Zhao, R., A. K. Y. Lee, L. Huang, X. Li, F. Yang, and J. P. D. Abbatt. "Photochemical processing of aqueous atmospheric brown carbon." Atmospheric Chemistry and Physics 15, no. 11 (June 4, 2015): 6087–100. http://dx.doi.org/10.5194/acp-15-6087-2015.

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Abstract. Atmospheric brown carbon (BrC) is a collective term for light absorbing organic compounds in the atmosphere. While the identification of BrC and its formation mechanisms is currently a central effort in the community, little is known about the atmospheric removal processes of aerosol BrC. As a result, we report on a series of laboratory studies of photochemical processing of BrC in the aqueous phase, by direct photolysis and OH oxidation. Solutions of ammonium sulfate mixed with glyoxal (GLYAS) or methylglyoxal (MGAS) are used as surrogates for a class of secondary BrC mediated by imine intermediates. Three nitrophenol species, namely 4-nitrophenol, 5-nitroguaiacol and 4-nitrocatechol, were investigated as a class of water-soluble BrC originating from biomass burning. Photochemical processing induced significant changes in the absorptive properties of BrC. The imine-mediated BrC solutions exhibited rapid photo-bleaching with both direct photolysis and OH oxidation, with atmospheric half-lives of minutes to a few hours. The nitrophenol species exhibited photo-enhancement in the visible range during direct photolysis and the onset of OH oxidation, but rapid photo-bleaching was induced by further OH exposure on an atmospheric timescale of an hour or less. To illustrate the atmospheric relevance of this work, we also performed direct photolysis experiments on water-soluble organic carbon extracted from biofuel combustion samples and observed rapid changes in the optical properties of these samples as well. Overall, these experiments indicate that atmospheric models need to incorporate representations of atmospheric processing of BrC species to accurately model their radiative impacts.

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4

Stoffels, E. "“Tissue Processing” with Atmospheric Plasmas." Contributions to Plasma Physics 47, no. 1-2 (February 2007): 40–48. http://dx.doi.org/10.1002/ctpp.200710007.

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5

Ellison, G. Barney, Adrian F. Tuck, and Veronica Vaida. "Atmospheric processing of organic aerosols." Journal of Geophysical Research: Atmospheres 104, no. D9 (May 1, 1999): 11633–41. http://dx.doi.org/10.1029/1999jd900073.

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6

Tilmes, C., C. Tilmes, M. Linda, and A. J. Fleig. "Atmospheric Composition Processing System (ACPS)." IEEE Transactions on Geoscience and Remote Sensing 47, no. 1 (January 2009): 51–58. http://dx.doi.org/10.1109/tgrs.2008.2002883.

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7

KOGOMA, Masuhiro. "Atmospheric Pressure Plasma Processing for Surface Finishing. The Characteristics of Atmospheric Pressure Non-Equilibrium Plasma Processing." Journal of the Surface Finishing Society of Japan 51, no. 2 (2000): 147–54. http://dx.doi.org/10.4139/sfj.51.147.

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8

Langmann, Baerbel. "Volcanic Ash versus Mineral Dust: Atmospheric Processing and Environmental and Climate Impacts." ISRN Atmospheric Sciences 2013 (June 12, 2013): 1–17. http://dx.doi.org/10.1155/2013/245076.

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This review paper contrasts volcanic ash and mineral dust regarding their chemical and physical properties, sources, atmospheric load, deposition processes, atmospheric processing, and environmental and climate effects. Although there are substantial differences in the history of mineral dust and volcanic ash particles before they are released into the atmosphere, a number of similarities exist in atmospheric processing at ambient temperatures and environmental and climate impacts. By providing an overview on the differences and similarities between volcanic ash and mineral dust processes and effects, this review paper aims to appeal for future joint research strategies to extend our current knowledge through close cooperation between mineral dust and volcanic ash researchers.

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9

Katkovsky, Leonid. "Atmospheric correction of multispectral satellite imagery." Ukrainian journal of remote sensing, no. 25 (June 25, 2020): 4–11. http://dx.doi.org/10.36023/ujrs.2020.25.170.

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Atmospheric correction is a necessary step in the processing of remote sensing data acquired in the visible and NIR spectral bands.The paper describes the developed atmospheric correction technique for multispectral satellite data with a small number of relatively broad spectral bands (not hyperspectral). The technique is based on the proposed analytical formulae that expressed the spectrum of outgoing radiation at the top of a cloudless atmosphere with rather high accuracy. The technique uses a model of the atmosphere and its optical and physical parameters that are significant from the point of view of radiation transfer, the atmosphere is considered homogeneous within a satellite image. To solve the system of equations containing the measured radiance of the outgoing radiation in the bands of the satellite sensor, the number of which is less than the number of unknowns of the model, it is proposed to use various additional relations, including regression relations between the optical parameters of the atmosphere. For a particular image pixel selected in a special way, unknown atmospheric parameters are found, which are then used to calculate the reflectance for all other pixels.Testing the proposed technique on OLI sensor data of Landsat 8 satellite showed higher accuracy in comparison with the FLAASH and QUAC methods implemented in the well-known ENVI image processing software. The technique is fast and there is using no additional information about the atmosphere or land surface except images under correction.

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10

Luo, Chin-Hsiang, San-Ho Liu, and Chung-Shin Yuan. "Measuring Atmospheric Visibility by Digital Image Processing." Aerosol and Air Quality Research 2, no. 1 (2002): 23–29. http://dx.doi.org/10.4209/aaqr.2002.06.0003.

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11

Rowe, Amy A., Lisa A. Totten, Gregory J. Cavallo, and John R. Yagecic. "Watershed Processing of Atmospheric Polychlorinated Biphenyl Inputs." Environmental Science & Technology 41, no. 7 (April 2007): 2331–37. http://dx.doi.org/10.1021/es062136o.

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12

de la Torre Juárez, M., G. A. Hajj, E. R. Kursinski, D. Kuang, A. J. Mannucci, and L. J. Romans. "Single frequency processing of atmospheric radio occultations." International Journal of Remote Sensing 25, no. 18 (September 2004): 3731–44. http://dx.doi.org/10.1080/0143116031000156800.

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13

Al-Shamma'a, A. I., S. R. Wylie, J. Lucas, and Jiu Dun Yan. "Atmospheric microwave plasma jet for material processing." IEEE Transactions on Plasma Science 30, no. 5 (October 2002): 1863–71. http://dx.doi.org/10.1109/tps.2002.805371.

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14

KIYOKAWA, Kazutoshi, and Kazuo SUGIYAMA. "Atmospheric Pressure Plasma Processing for Surface Finishing. Atmospheric Pressure Non-Equilibrium Plasma Processing Induced by Electrically Conductive Ceramics." Journal of the Surface Finishing Society of Japan 51, no. 2 (2000): 155–60. http://dx.doi.org/10.4139/sfj.51.155.

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15

Richter, R., and D. Schläpfer. "Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction." International Journal of Remote Sensing 23, no. 13 (January 2002): 2631–49. http://dx.doi.org/10.1080/01431160110115834.

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16

Karabanov, A. G. "Return Signal Processing in Vertical Probing Atmospheric Radars." Telecommunications and Radio Engineering 52, no. 6 (1998): 63–69. http://dx.doi.org/10.1615/telecomradeng.v52.i6.100.

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17

LeelaRani, D., S. Varadarajan, and M. Sadasiva. "Atmospheric Radar Signal Processing using Complex Wavelet Transforms." International Journal of Computer Applications 91, no. 11 (April 18, 2014): 33–36. http://dx.doi.org/10.5120/15927-5194.

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18

NOZAKI, Tomohiro, and Ken OKAZAKI. "Materials Processing in Atmospheric Pressure Glow Plasma CVD." Journal of The Institute of Electrical Engineers of Japan 126, no. 12 (2006): 788–91. http://dx.doi.org/10.1541/ieejjournal.126.788.

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19

Nickovic, S., A. Vukovic, and M. Vujadinovic. "Atmospheric processing of iron carried by mineral dust." Atmospheric Chemistry and Physics Discussions 13, no. 1 (January 24, 2013): 2695–723. http://dx.doi.org/10.5194/acpd-13-2695-2013.

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Abstract. Nutrification of the open ocean originates mainly from deposited aerosol in which the bioavaliable iron is likely to be an important factor. The relatively insoluble iron in dust from arid soils becomes more soluble after atmospheric processing and could contribute to marine primary production. To numerically simulate the path of iron on its atmospheric route from desert sources to sinks in the ocean, we developed a regional atmospheric dust-iron model that included parameterization of the transformation of iron to a soluble form caused by dust mineralogy, cloud processes and solar radiation. When compared with sample data on the aerosol iron, which were collected during several Atlantic cruises, the results from the higher-resolution simulation experiments showed that the model was capable of reproducing the major observed patterns.

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20

Kra¨mer, Martina. "Alteration of atmospheric particle solubility by cloud processing." Journal of Aerosol Science 29 (September 1998): S3—S4. http://dx.doi.org/10.1016/s0021-8502(98)00078-0.

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21

Marcolli, Claudia, and Ulrich K. Krieger. "Relevance of Particle Morphology for Atmospheric Aerosol Processing." Trends in Chemistry 2, no. 1 (January 2020): 1–3. http://dx.doi.org/10.1016/j.trechm.2019.11.008.

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22

CHANDRAIAH, G., and REDDY T. SREENIVASULU. "ATMOSPHERIC RADAR SIGNAL PROCESSING USING HYBRID WINDOW FUNCTIONS." i-manager’s Journal on Electronics Engineering 9, no. 1 (2018): 14. http://dx.doi.org/10.26634/jele.9.1.14427.

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23

Nickovic, S., A. Vukovic, and M. Vujadinovic. "Atmospheric processing of iron carried by mineral dust." Atmospheric Chemistry and Physics 13, no. 18 (September 16, 2013): 9169–81. http://dx.doi.org/10.5194/acp-13-9169-2013.

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Abstract. Nutrification of the open ocean originates mainly from deposited aerosol in which the bio-avaliable iron is likely to be an important factor. The relatively insoluble iron in dust from arid soils becomes more soluble after atmospheric processing and, through its deposition in the ocean, could contribute to marine primary production. To numerically simulate the atmospheric route of iron from desert sources to sinks in the ocean, we developed a regional atmospheric dust-iron model that included parameterization of the transformation of iron to a soluble form caused by dust mineralogy, cloud processes and solar radiation. When compared with field data on the aerosol iron, which were collected during several Atlantic cruises, the results from the higher-resolution simulation experiments showed that the model was capable of reproducing the major observed patterns.

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24

Uma Maheswara Rao, D., T. Sreenivasulu Reddy, and G. Ramachandra Reddy. "Atmospheric radar signal processing using principal component analysis." Digital Signal Processing 32 (September 2014): 79–84. http://dx.doi.org/10.1016/j.dsp.2014.05.009.

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25

Yang, Xiao Feng, and Xing Ping Wen. "Atmospheric Correction of Landsat ETM+ Remote Sensing Data Using 6S Code and its Validation." Applied Mechanics and Materials 29-32 (August 2010): 2365–68. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.2365.

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Atmospheric correction is one of the most important pre-processing steps in quantitative remote sensing. To extract quantitative information from the Enhanced Thematic Mapper-Plus (ETM+) imagery accurately, atmospheric correction is a necessary step. Furthermore, multi-temporal images after atmospheric correction can be compared to each other quantitatively. The Second simulation of satellite signal in the solar spectrum (6S) radiative code can process many types of satellite data and provide several standard atmosphere and aerosol models for atmospheric correction. This paper demonstrates atmospheric correction of Landsat ETM+ data using 6S code. Comparing images before and after atmospheric correction, the different of image before and after correction was not obvious using visual interpretation. Therefore, different ground object spectral curves after atmospheric correction are illustrated. They were similar with the standard ground object spectra. The correlation coefficient of ETM+ band 1 to band 4 and NDVI (Normalized Difference Vegetation Index) after atmospheric correction increases. The atmospheric correction removed the atmosphere effect, so the inherent relevant increased. 6S code was an effective tool for atmospheric correction of remote senisng data.

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26

Aggrey, John, and Sunil Bisnath. "Improving GNSS PPP Convergence: The Case of Atmospheric-Constrained, Multi-GNSS PPP-AR." Sensors 19, no. 3 (January 30, 2019): 587. http://dx.doi.org/10.3390/s19030587.

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GNSS positioning performance has been shown to improve with the ingestion of data from Global Ionospheric Maps (GIMs) and tropospheric zenith path delays, which are produced by, e.g., the International GNSS Service (IGS). For both dual- and triple-frequency Precise Point Positioning (PPP) processing, the significance of GIM and tropospheric products in processing is not obvious in the quality of the solution after a few hours. However, constraining the atmosphere improves PPP initialization and solution convergence in the first few minutes of processing. The general research question to be answered is whether there is any significant benefit in constraining the atmosphere in multi-frequency PPP? A key related question is: regarding time and position accuracy, how close are we to RTK performance in the age of multi-GNSS PPP-AR? To address these questions, this paper provides insight into the conceptual analyses of atmospheric GNSS PPP constraints. Dual- and triple-frequency scenarios were investigated. Over 60% improvement in convergence time was observed when atmospheric constraints are applied to a dual-frequency multi-GNSS PPP-AR solution. Future work would involve employing the constraints to improve low-cost PPP solutions.

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Xing Su, Xing Su, Longguang Xia Longguang Xia, Kan Liu Kan Liu, Peng Zhang Peng Zhang, Ping Li Ping Li, Runchang Zhao Runchang Zhao, and Bo Wang Bo Wang. "Fabrication of a large-aperture continuous phase plate in two modes using atmospheric pressure plasma processing." Chinese Optics Letters 16, no. 10 (2018): 102201. http://dx.doi.org/10.3788/col201816.102201.

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Rosu, Iulian-Alin, Marius-Mihai Cazacu, Otilia Prelipceanu, and Maricel Agop. "A Turbulence-Oriented Approach to Retrieve Various Atmospheric Parameters Using Advanced Lidar Data Processing Techniques." Atmosphere 10, no. 1 (January 18, 2019): 38. http://dx.doi.org/10.3390/atmos10010038.

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The article is aimed at presenting a semi-empirical model coded and computed in the programming language Python, which utilizes data gathered with a standard biaxial elastic lidar platform in order to calculate the altitude profiles of the structure coefficients of the atmospheric refraction index C N 2 ( z ) and other associated turbulence parameters. Additionally, the model can be used to calculate the PBL (Planetary Boundary Layer) height, and other parameters typically employed in the field of astronomy. Solving the Fernard–Klett inversion by correlating sun-photometer data obtained through our AERONET site with lidar data, it can yield the atmospheric extinction and backscatter profiles α ( z ) and β ( z ) , and thus obtain the atmospheric optical depth. Finally, several theoretical notions of interest that utilize the solved parameters are presented, such as approximated relations between C N 2 ( z ) and the atmospheric temperature profile T ( z ) , and between the scintillation of backscattered lidar signal and the average wind speed profile U ( z ) . These obtained profiles and parameters also have several environmental applications that are connected directly and indirectly to human health and well-being, ranging from understanding the transport of aerosols in the atmosphere and minimizing the errors in measuring it, to predicting extreme, and potentially-damaging, meteorological events.

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Otkin, Jason A., Derek J. Posselt, Erik R. Olson, Hung-Lung Huang, James E. Davies, Jun Li, and Christopher S. Velden. "Mesoscale Numerical Weather Prediction Models Used in Support of Infrared Hyperspectral Measurement Simulation and Product Algorithm Development." Journal of Atmospheric and Oceanic Technology 24, no. 4 (April 1, 2007): 585–601. http://dx.doi.org/10.1175/jtech1994.1.

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Abstract A novel application of numerical weather prediction (NWP) models within an end-to-end processing system used to demonstrate advanced hyperspectral satellite technologies and instrument concepts is presented. As part of this system, sophisticated NWP models are used to generate simulated atmospheric profile datasets with fine horizontal and vertical resolution. The simulated datasets, which are treated as the “truth” atmosphere, are subsequently passed through a sophisticated forward radiative transfer model to generate simulated top-of-atmosphere (TOA) radiances across a broad spectral region. Atmospheric motion vectors and temperature and water vapor retrievals generated from the TOA radiances are then compared with the original model-simulated atmosphere to demonstrate the potential utility of future hyperspectral wind and retrieval algorithms. Representative examples of TOA radiances, atmospheric motion vectors, and temperature and water vapor retrievals are shown to illustrate the use of the simulated datasets. Case study results demonstrate that the numerical models are able to realistically simulate mesoscale cloud, temperature, and water vapor structures present in the real atmosphere. Because real hyperspectral radiance measurements with high spatial and temporal resolution are not available for large geographical domains, the simulated TOA radiance datasets are the only viable alternative that can be used to demonstrate the new hyperspectral technologies and capabilities. As such, sophisticated mesoscale models are critically important for the demonstration of the future end-to-end processing system.

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30

ISHIGAKI, Takamasa. "Atmospheric Pressure Plasma Processing for Surface Finishing. Thermal Plasma Technology for Advanced Materials Processing." Journal of the Surface Finishing Society of Japan 51, no. 2 (2000): 161–66. http://dx.doi.org/10.4139/sfj.51.161.

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31

Weerasinghe, Janith, Wenshao Li, Rusen Zhou, Renwu Zhou, Alexander Gissibl, Prashant Sonar, Robert Speight, Krasimir Vasilev, and Kostya (Ken) Ostrikov. "Bactericidal Silver Nanoparticles by Atmospheric Pressure Solution Plasma Processing." Nanomaterials 10, no. 5 (May 1, 2020): 874. http://dx.doi.org/10.3390/nano10050874.

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Silver nanoparticles have applications in plasmonics, medicine, catalysis and electronics. We report a simple, cost-effective, facile and reproducible technique to synthesise silver nanoparticles via plasma-induced non-equilibrium liquid chemistry with the absence of a chemical reducing agent. Silver nanoparticles with tuneable sizes from 5.4 to 17.8 nm are synthesised and characterised using Transmission Electron Microscopy (TEM) and other analytic techniques. A mechanism for silver nanoparticle formation is also proposed. The antibacterial activity of the silver nanoparticles was investigated with gram-positive and gram-negative bacteria. The inhibition of both bacteria types was observed. This is a promising alternative method for the instant synthesis of silver nanoparticles, instead of the conventional chemical reduction route, for numerous applications.

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32

Sathe, P. V., and P. M. Muraleedharan. "Retrieval and processing of atmospheric parameters from satellite data." Computers & Geosciences 24, no. 8 (October 1998): 797–803. http://dx.doi.org/10.1016/s0098-3004(98)00058-2.

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33

Kusano, Yukihiro. "Atmospheric Pressure Plasma Processing for Polymer Adhesion: A Review." Journal of Adhesion 90, no. 9 (April 21, 2014): 755–77. http://dx.doi.org/10.1080/00218464.2013.804407.

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34

Li, Duo, Na Li, Xing Su, Peng Ji, and Bo Wang. "Atmospheric Pressure Plasma Processing of an Optical Sinusoidal Grid." Micromachines 10, no. 12 (November 28, 2019): 828. http://dx.doi.org/10.3390/mi10120828.

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Sinusoidal grid with nanometric precision is adopted as a surface encoder to measure multiple degree-of-freedom motions. This paper proposes the atmospheric pressure plasma processing (APPP) technique to fabricate an optical sinusoidal grid surface. The characteristics of removal function and surface generation mechanism are firstly presented. Both simulation and experiment validate the effectiveness of APPP to fabricate a sinusoidal grid surface with nanometric precision. Post mechanical polishing experiments show that APPP features can be well maintained while the surface roughness is greatly reduced to meet the optical requirement.

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35

Wang, Dong Fang. "Study on Atmospheric Pressure Plasma Processing of Fused Silica." Advanced Materials Research 706-708 (June 2013): 270–73. http://dx.doi.org/10.4028/www.scientific.net/amr.706-708.270.

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In order to get ultra-smooth surface without subsurface damage efficiently for fused silica, the atmospheric pressure plasma processing (APPP) is developed. It is based on chemical reaction between active radicals excited by plasma and workpiece surface atoms, so the subsurface damage caused by contact stress can be avoided and atomic-level precision machining can be achieved. In this paper, the influence on material removal function by the key factors of APPP including the flow rate of reaction gases, input power, and processing distance are discussed. In addition, by the regression model a quantitative mathematical model of the material removal function of the atmospheric pressure plasma processing on fused silica is established. And this model is verified by experimental data.

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Pappas, Daphne. "Status and potential of atmospheric plasma processing of materials." Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films 29, no. 2 (March 2011): 020801. http://dx.doi.org/10.1116/1.3559547.

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37

J. BUIST, Peter, and Bert-Johan VOLLMULLER. "On-board Data Processing for Earth and Atmospheric Observations." TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, AEROSPACE TECHNOLOGY JAPAN 12, ists29 (2014): Tn_25—Tn_30. http://dx.doi.org/10.2322/tastj.12.tn_25.

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38

Wylie, S. R., A. I. Al-Shamma’a, J. Lucas, and R. A. Stuart. "An atmospheric microwave plasma jet for ceramic material processing." Journal of Materials Processing Technology 153-154 (November 2004): 288–93. http://dx.doi.org/10.1016/j.jmatprotec.2004.04.061.

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39

Collett, Jeffrey L., Pierre Herckes, Sarah Youngster, and Taehyoung Lee. "Processing of atmospheric organic matter by California radiation fogs." Atmospheric Research 87, no. 3-4 (March 2008): 232–41. http://dx.doi.org/10.1016/j.atmosres.2007.11.005.

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40

Mazur, Anna, Mariusz Kacprzak, Katarzyna Kubiak, Jan Kotlarz, and Krzysztof Skocki. "The influence of atmospheric light scattering on reflectance measurements during photogrammetric survey flights at low altitudes over forest areas." Forest Research Papers 79, no. 1 (March 1, 2018): 59–68. http://dx.doi.org/10.2478/frp-2018-0007.

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Abstract In this article, we describe methods for the correction of multispectral aerial images by accounting for atmospheric interference. We also summarize the first correction results for images acquired at flight altitudes and evaluate the suitability of selected methods for the atmospheric correction of these images. Furthermore, processes and phenomena occurring in the atmosphere that potentially affect image quality and interfere with the electromagnetic radiation registered by the imaging sensors are discussed as well. The purpose of atmospheric correction is to reduce or eliminate atmospheric interference during multispectral image processing. Here we present methodology for image correction based on data gathered at various altitudes during the autumn flights conducted as a part of the HESOFF project.

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41

Morata, Antonio. "Emerging Trends in Beverage Processing." Beverages 7, no. 1 (January 28, 2021): 8. http://dx.doi.org/10.3390/beverages7010008.

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Beverage processing is open to new technologies; among them, nonthermal physical technologies such as discontinuous hydrostatic pressure (HHP), ultrahigh-pressure homogenization (UHPH), pulsed electric field (PEF), ultrasound (US), atmospheric pressure cold plasma (APCP), or pulsed light (PL) are growing increasingly in the food industry [...]

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CASTREJÓN GARCÍA, R., J. R. VARELA, A. A. CASTREJÓN PITA, and J. R. CASTREJÓN PITA. "DEVELOPMENT AND EVALUATION OF AN ALTERNATIVE METHOD FOR PROCESSING ELASTIC-LIDAR RETURN SIGNALS." International Journal of Modern Physics B 20, no. 02 (January 20, 2006): 141–50. http://dx.doi.org/10.1142/s0217979206033218.

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A method for interpreting elastic-lidar return signals in heavily-polluted atmospheres is presented. It is based on an equation derived directly from the classic lidar equation, which highlights gradients of the atmospheric backscattering properties along the laser optical path. The method is evaluated by comparing its results with those obtained with the differential absorption technique. The results were obtained from locating and ranging measurements in pollutant plumes and contaminated environments around central México.

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Berdou, G., S. Shrestha, and M. Hahn. "INTEGRATION OF SENTINEL-2 AND LANDSAT-8 DATA FOR SURFACE REFLECTANCE TIME-SERIES ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 205–10. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-205-2019.

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Abstract. Integration of Sentinel-2 and Landsat-8 imagery is a key factor to provide earth observation data at a global scale with higher temporal resolution. Integration of data from two sensors is possible with the consistent harmonized data framed in common reference and processing, which can be used for comparing geophysical surface characteristics. This study focuses on the analysis of the atmospheric correction methods available for both Landsat-8 and Sentinel-2 products to convert the top of the atmosphere to the bottom of atmosphere reflectance. Other investigations (De Keukelaere, 2018) carried out similar analyses focusing on data acquired over water, while this study emphasises the analyses over land covers. Two processing algorithms iCOR and Sen2COR are utilized to perform atmospheric corrections, and results are statistically and visually compared. Comparisons based on same images processed with different algorithms show very strong correlation for some classes (urban: 0.99), while correlation values around 0.85 were achieved between images from different sensors.

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Li, Duo, Bo Wang, Jun Wang, and Qiang Xin. "Study of Form Control Algorithm in Atmospheric Pressure Plasma Processing." Key Engineering Materials 620 (August 2014): 49–54. http://dx.doi.org/10.4028/www.scientific.net/kem.620.49.

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Atmospheric Pressure Plasma Processing (APPP) has demonstrated that it can achieve high removal rate and induce no sub-surface damage on the silica based material of optical surface. Compared with traditional mechanical polishing and ion beam figuring, APPP technology is cost effective and very promising in the optics fabrication field. In principle, Atmospheric Pressure Plasma Processing can be described by the two-dimensional convolution equation with dwell time function and plasma removal function. Thus, dwell time function can be solved theoretically by the process of de-convolution, which is the essence of form control algorithm. First, this paper compares and analyzes common de-convolution algorithms by the simulated processing. From the simulation results, the algorithm based on the principle of image restoration has good solving speed, high calculation accuracy. Therefore, we choose it as the form control algorithm for Atmospheric Pressure Plasma Processing. However, the high temperature of plasma plume results in the non-linear relationship between the removal depth and time, further affecting the stability of the algorithm. Then, using the actual experiment data, we build the nonlinear relationship function model to compensate the heat effect in the algorithm. Finally, the modified algorithm is verified by the 7um uniform removal on the fused silica using Atmospheric Pressure Plasma Processing.

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Su, Xing, Peng Ji, Kan Liu, David Walker, Guoyu Yu, Hongyu Li, Duo Li, and Bo Wang. "Combined processing chain for freeform optics based on atmospheric pressure plasma processing and bonnet polishing." Optics Express 27, no. 13 (June 13, 2019): 17979. http://dx.doi.org/10.1364/oe.27.017979.

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Sokolov, Anton, Egor Dmitriev, Ioannis Cheliotis, Hervé Delbarre, Elsa Dieudonne, Patrick Augustin, and Marc Fourmentin. "Automated multi-classifier recognition of atmospheric turbulent structures obtained by Doppler lidar." E3S Web of Conferences 223 (2020): 03013. http://dx.doi.org/10.1051/e3sconf/202022303013.

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We present algorithms and results of automated processing of LiDAR measurements obtained during VEGILOT measuring campaign in Paris in autumn 2014 in order to study horizontal turbulent atmospheric regimes on urban scales. To process images obtained by horizontal atmospheric scanning using Doppler LiDAR, the method is proposed based on texture analysis and classification using supervised machine learning algorithms. The results of the parallel classification by various classifiers were combined using the majority voting strategy. The obtained estimates of accuracy demonstrate the efficiency of the proposed method for solving the problem of remote sensing of regional-scale turbulent patterns in the atmosphere.

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Griesser, Thomas, and Hans Richner. "Multipeakverarbeitungsverfahren zur Erkennung des atmosphärischen Signals in Dopplerradar Windprofiler Spektren." Meteorologische Zeitschrift 7, no. 6 (December 15, 1998): 292–302. http://dx.doi.org/10.1127/metz/7/1998/292.

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Lolli, Simone, Fabio Madonna, Marco Rosoldi, James R. Campbell, Ellsworth J. Welton, Jasper R. Lewis, Yu Gu, and Gelsomina Pappalardo. "Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects." Atmospheric Measurement Techniques 11, no. 3 (March 26, 2018): 1639–51. http://dx.doi.org/10.5194/amt-11-1639-2018.

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Abstract. In the past 2 decades, ground-based lidar networks have drastically increased in scope and relevance, thanks primarily to the advent of lidar observations from space and their need for validation. Lidar observations of aerosol and cloud geometrical, optical and microphysical atmospheric properties are subsequently used to evaluate their direct radiative effects on climate. However, the retrievals are strongly dependent on the lidar instrument measurement technique and subsequent data processing methodologies. In this paper, we evaluate the discrepancies between the use of Raman and elastic lidar measurement techniques and corresponding data processing methods for two aerosol layers in the free troposphere and for two cirrus clouds with different optical depths. Results show that the different lidar techniques are responsible for discrepancies in the model-derived direct radiative effects for biomass burning (0.05 W m−2 at surface and 0.007 W m−2 at top of the atmosphere) and dust aerosol layers (0.7 W m−2 at surface and 0.85 W m−2 at top of the atmosphere). Data processing is further responsible for discrepancies in both thin (0.55 W m−2 at surface and 2.7 W m−2 at top of the atmosphere) and opaque (7.7 W m−2 at surface and 11.8 W m−2 at top of the atmosphere) cirrus clouds. Direct radiative effect discrepancies can be attributed to the larger variability of the lidar ratio for aerosols (20–150 sr) than for clouds (20–35 sr). For this reason, the influence of the applied lidar technique plays a more fundamental role in aerosol monitoring because the lidar ratio must be retrieved with relatively high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much less variable, the data processing is critical because smoothing it modifies the aerosol and cloud vertically resolved extinction profile that is used as input to compute direct radiative effect calculations.

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Möller, Gregor, and Daniel Landskron. "Atmospheric bending effects in GNSS tomography." Atmospheric Measurement Techniques 12, no. 1 (January 3, 2019): 23–34. http://dx.doi.org/10.5194/amt-12-23-2019.

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Abstract. In Global Navigation Satellite System (GNSS) tomography, precise information about the tropospheric water vapor distribution is derived from integral measurements like ground-based GNSS slant wet delays (SWDs). Therefore, the functional relation between observations and unknowns, i.e., the signal paths through the atmosphere, have to be accurately known for each station–satellite pair involved. For GNSS signals observed above a 15∘ elevation angle, the signal path is well approximated by a straight line. However, since electromagnetic waves are prone to atmospheric bending effects, this assumption is not sufficient anymore for lower elevation angles. Thus, in the following, a mixed 2-D piecewise linear ray-tracing approach is introduced and possible error sources in the reconstruction of the bended signal paths are analyzed in more detail. Especially if low elevation observations are considered, unmodeled bending effects can introduce a systematic error of up to 10–20 ppm, on average 1–2 ppm, into the tomography solution. Thereby, not only the ray-tracing method but also the quality of the a priori field can have a significant impact on the reconstructed signal paths, if not reduced by iterative processing. In order to keep the processing time within acceptable limits, a bending model is applied for the upper part of the neutral atmosphere. It helps to reduce the number of processing steps by up to 85 % without significant degradation in accuracy. Therefore, the developed mixed ray-tracing approach allows not only for the correct treatment of low elevation observations but is also fast and applicable for near-real-time applications.

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Kleinert, A., G. Aubertin, G. Perron, M. Birk, G. Wagner, F. Hase, H. Nett, and R. Poulin. "MIPAS Level 1B algorithms overview: operational processing and characterization." Atmospheric Chemistry and Physics 7, no. 5 (February 28, 2007): 1395–406. http://dx.doi.org/10.5194/acp-7-1395-2007.

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Abstract. This paper gives an overview of the MIPAS Level 1B (L1B) processor whose main objective is to calibrate atmospheric measurements radiometrically, spectrally and geo-located. It presents also the results of instrument characterization done on ground and during the first years in-flight. An accurate calibration is mandatory for high quality atmospheric retrievals. MIPAS has shown very good performance and stability. The noise equivalent spectral radiance ranges from 3 to 50 nW/(cm2 sr cm−1) and is well within the requirements over nearly the whole spetral range. The systematic radiometric error is estimated to be within 1 or 2% in most situations.

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Journal articles on the topic 'Atmospheric processing'

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