scholarly journals An approach to retrieve information on the carbonyl fluoride (COF<sub>2</sub>) vertical distributions above Jungfraujoch by FTIR multi-spectrum multi-window fitting

2009 ◽  
Vol 9 (1) ◽  
pp. 3167-3205
Author(s):  
P. Duchatelet ◽  
E. Mahieu ◽  
R. Ruhnke ◽  
W. Feng ◽  
M. Chipperfield ◽  
...  
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Linear Trend ◽  
Lower Boundary ◽  
Ir Absorption ◽  
Absorption Bands ◽  
Data Set ◽  
Fitting Procedure ◽  
Significant Bias ◽  
Carbonyl Fluoride

Abstract. We present an original multi-spectrum fitting procedure to retrieve volume mixing ratio (VMR) profiles of carbonyl fluoride (COF2) from ground-based high resolution Fourier transform infrared (FTIR) solar spectra. The multi-spectrum approach consists of simultaneously combining, during the retrievals, all spectra recorded consecutively during the same day and with the same resolution. Solar observations analyzed in this study with the SFIT-2 v3.91 fitting algorithm correspond to more than 2900 spectra recorded between January 2000 and December 2007 at high zenith angles, with a Fourier Transform Spectrometer operated at the high-altitude International Scientific Station of the Jungfraujoch (ISSJ, 46.5° N latitude, 8.0° E longitude, 3580 m altitude), Switzerland. The goal of the retrieval strategy described here is to provide information about the vertical distribution of carbonyl fluoride. The microwindows used are located in the ν1 or in the ν4 COF2 infrared (IR) absorption bands. Averaging kernel and eigenvector analysis indicates that our FTIR retrieval is sensitive to COF2 inversion between 17 and 30 km, with the major contribution to the retrieved information always coming from the measurement. Moreover, there was no significant bias between COF2 partial columns, total columns or VMR profiles retrieved from the two bands. For each wavenumber region, a complete error budget including all identified sources has been carefully established. In addition, comparisons of FTIR COF2 17–30 km partial columns with KASIMA and SLIMCAT 3-D CTMs are also presented. If we do not notice any significant bias between FTIR and SLIMCAT time series, KASIMA COF2 17–30 km partial columns are lower of around 25%, probably due to incorrect lower boundary conditions. For each times series, linear trend estimation for the 2000–2007 time period as well as a seasonal variation study are also performed and critically discussed. We further demonstrate that all time series are able to reproduce the COF2 seasonal cycle, which main seasonal characteristics deduced from each data set agree quite well.

scholarly journals An approach to retrieve information on the carbonyl fluoride (COF<sub>2</sub>) vertical distributions above Jungfraujoch by FTIR multi-spectrum multi-window fitting

2009 ◽  
Vol 9 (22) ◽  
pp. 9027-9042 ◽  
Author(s):  
P. Duchatelet ◽  
E. Mahieu ◽  
R. Ruhnke ◽  
W. Feng ◽  
M. Chipperfield ◽  
...  
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Linear Trend ◽  
Meteorological Data ◽  
Lower Boundary ◽  
Ir Absorption ◽  
Absorption Bands ◽  
Data Set ◽  
Significant Bias ◽  
Carbonyl Fluoride

Abstract. We present an original multi-spectrum fitting procedure to retrieve volume mixing ratio (VMR) profiles of carbonyl fluoride (COF2) from ground-based high resolution Fourier transform infrared (FTIR) solar spectra. The multi-spectrum approach consists of simultaneously combining, during the retrievals, all spectra recorded consecutively during the same day and with the same resolution. Solar observations analyzed in this study with the SFIT-2 v3.91 fitting algorithm correspond to more than 2900 spectra recorded between January 2000 and December 2007 at high zenith angles, with a Fourier Transform Spectrometer operated at the high-altitude International Scientific Station of the Jungfraujoch (ISSJ, 46.5° N latitude, 8.0° E longitude, 3580 m altitude), Switzerland. The goal of the retrieval strategy described here is to provide information about the vertical distribution of carbonyl fluoride. The microwindows used are located in the ν4 or in the ν4 COF2 infrared (IR) absorption bands. Averaging kernel and eigenvector analysis indicates that our FTIR retrieval is sensitive to COF2 inversion between 17 and 30 km, with the major contribution to the retrieved information always coming from the measurement. Moreover, there was no significant bias between COF2 partial columns, total columns or VMR profiles retrieved from the two bands. For each wavenumber region, a complete error budget including all identified sources has been carefully established. In addition, comparisons of FTIR COF2 17–30 km partial columns with KASIMA and SLIMCAT 3-D CTMs are also presented. If we do not notice any significant bias between FTIR and SLIMCAT time series, KASIMA COF2 17–30 km partial columns are lower of around 25%, probably due to incorrect lower boundary conditions. For each times series, linear trend estimation for the 2000–2007 time period as well as a seasonal variation study are also performed and critically discussed. For FTIR and KASIMA time series, very low COF2 growth rates (0.4±0.2%/year and 0.3±0.2%/year, respectively) have been derived. However, the SLIMCAT data set gives a slight negative trend (−0.5±0.2%/year), probably ascribable to discontinuities in the meteorological data used by this model. We further demonstrate that all time series are able to reproduce the COF2 seasonal cycle, which main seasonal characteristics deduced from each data set agree quite well.

scholarly journals OH defect contents in quartz in a granitic system at 1–5 kbar

2019 ◽  
Vol 174 (12) ◽  
Author(s):  
Alexander Potrafke ◽  
Roland Stalder ◽  
Burkhard C. Schmidt ◽  
Thomas Ludwig
Keyword(s):  
Secondary Ion Mass Spectrometry ◽  
Chemical System ◽  
Absorption Feature ◽  
Ir Absorption ◽  
Absorption Bands ◽  
Data Set ◽  
Piston Cylinder ◽  
Oh Defect ◽  
Pressure Interval ◽  
Water Saturated

Abstract Quartz is able to incorporate trace elements (e.g., H, Li, Al, B) depending on the formation conditions (P, T, and chemical system). Consequently, quartz can be used as a tracer for petrogenetic information of silicic plutonic bodies. In this experimental study, we provide the first data set on the OH defect incorporation in quartz from granites over a pressure/temperature range realistic for the emplacement of granitic melts in the upper crust. Piston cylinder and internally heated pressure vessel synthesis experiments were performed in a water-saturated granitic system at 1–5 kbar and 700–950 °C. Crystals from successful runs were analysed by secondary ion mass spectrometry (SIMS) and Fourier transform infrared (FTIR) spectroscopy, and their homogeneity was verified by FTIR imaging. IR absorption bands can be assigned to specific OH defects and analysed qualitatively and quantitatively and reveal that (1) the AlOH band triplet at 3310, 3378 and 3430 cm−1 is the dominating absorption feature in all spectra, (2) no simple trend of total OH defect incorporation with pressure can be observed, (3) the LiOH defect band at 3470–3480 cm−1 increases strongly in a narrow pressure interval from 4 kbar (220 µg/g H2O) to 4.5 kbar (500 µg/g H2O), and declines equally strong towards 5 kbar (180 µg/g H2O). Proton incorporation is charge balanced according to the equation H+ + A+ + P5+ = M3+ + B3+, with A+ = alkali ions and M3+ = trivalent metal ions.

scholarly journals Five years of CO, HCN, C<sub>2</sub>H<sub>6</sub>, C<sub>2</sub>H<sub>2</sub>, CH<sub>3</sub>OH, HCOOH and H<sub>2</sub>CO total columns measured in the Canadian high Arctic

2014 ◽  
Vol 7 (6) ◽  
pp. 1547-1570 ◽  
Author(s):  
C. Viatte ◽  
K. Strong ◽  
K. A. Walker ◽  
J. R. Drummond
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
High Arctic ◽  
Retrieval Algorithm ◽  
Data Set

Abstract. We present a five-year time series of seven tropospheric species measured using a ground-based Fourier transform infrared (FTIR) spectrometer at the Polar Environment Atmospheric Research Laboratory (PEARL; Eureka, Nunavut, Canada; 80°05' N, 86°42' W) from 2007 to 2011. Total columns and temporal variabilities of carbon monoxide (CO), hydrogen cyanide (HCN) and ethane (C2H6) as well as the first derived total columns at Eureka of acetylene (C2H2), methanol (CH3OH), formic acid (HCOOH) and formaldehyde (H2CO) are investigated, providing a new data set in the sparsely sampled high latitudes. Total columns are obtained using the SFIT2 retrieval algorithm based on the optimal estimation method. The microwindows as well as the a priori profiles and variabilities are selected to optimize the information content of the retrievals, and error analyses are performed for all seven species. Our retrievals show good sensitivities in the troposphere. The seasonal amplitudes of the time series, ranging from 34 to 104%, are captured while using a single a priori profile for each species. The time series of the CO, C2H6 and C2H2 total columns at PEARL exhibit strong seasonal cycles with maxima in winter and minima in summer, in opposite phase to the HCN, CH3OH, HCOOH and H2CO time series. These cycles result from the relative contributions of the photochemistry, oxidation and transport as well as biogenic and biomass burning emissions. Comparisons of the FTIR partial columns with coincident satellite measurements by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) show good agreement. The correlation coefficients and the slopes range from 0.56 to 0.97 and 0.50 to 3.35, respectively, for the seven target species. Our new data set is compared to previous measurements found in the literature to assess atmospheric budgets of these tropospheric species in the high Arctic. The CO and C2H6concentrations are consistent with negative trends observed over the Northern Hemisphere, attributed to fossil fuel emission decrease. The importance of poleward transport for the atmospheric budgets of HCN and C2H2 is highlighted. Columns and variabilities of CH3OH and HCOOH at PEARL are comparable to previous measurements performed at other remote sites. However, the small columns of H2CO in early May might reflect its large atmospheric variability and/or the effect of the updated spectroscopic parameters used in our retrievals. Overall, emissions from biomass burning contribute to the day-to-day variabilities of the seven tropospheric species observed at Eureka.

scholarly journals Effect of data gaps: comparison of different spectral analysis methods

2016 ◽  
Vol 34 (4) ◽  
pp. 437-449 ◽  
Author(s):  
Costel Munteanu ◽  
Catalin Negrea ◽  
Marius Echim ◽  
Kalevi Mursula
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Amplitude Spectrum ◽  
Large Data ◽  
Small Data ◽  
Gap Size ◽  
Data Set ◽  
Data Gaps ◽  
Data Gap ◽  
Single Data

Abstract. In this paper we investigate quantitatively the effect of data gaps for four methods of estimating the amplitude spectrum of a time series: fast Fourier transform (FFT), discrete Fourier transform (DFT), Z transform (ZTR) and the Lomb–Scargle algorithm (LST). We devise two tests: the single-large-gap test, which can probe the effect of a single data gap of varying size and the multiple-small-gaps test, used to study the effect of numerous small gaps of variable size distributed within the time series. The tests are applied on two data sets: a synthetic data set composed of a superposition of four sinusoidal modes, and one component of the magnetic field measured by the Venus Express (VEX) spacecraft in orbit around the planet Venus. For single data gaps, FFT and DFT give an amplitude monotonically decreasing with gap size. However, the shape of their amplitude spectrum remains unmodified even for a large data gap. On the other hand, ZTR and LST preserve the absolute level of amplitude but lead to greatly increased spectral noise for increasing gap size. For multiple small data gaps, DFT, ZTR and LST can, unlike FFT, find the correct amplitude of sinusoidal modes even for large data gap percentage. However, for in-situ data collected in a turbulent plasma environment, these three methods overestimate the high frequency part of the amplitude spectrum above a threshold depending on the maximum gap size, while FFT slightly underestimates it.

scholarly journals FTIR study of carbon monoxide adsorption on ion-exchanged X, Y and mordenite type zeolites

2003 ◽  
Vol 68 (4-5) ◽  
pp. 409-416 ◽  
Author(s):  
Vesna Rakic ◽  
Vera Dondur ◽  
Radmila Hercigonja
Keyword(s):  
Carbon Monoxide ◽  
Fourier Transform ◽  
Transition Metal ◽  
Room Temperature ◽  
Ir Absorption ◽  
Transition Metal Cation ◽  
Absorption Bands ◽  
Ftir Study ◽  
Adsorption Of Co ◽  
Charge Balancing

In this work Fourier transform infrared (FTIR) study has been applied to study the adsorption of carbon monoxide on transition metal (Mn2+, Co2 Ni2+) ion-exchanged zeolites type Y, X and mordenites. The adsorption of CO at room temperature produces overlapping IR absorption bands in the 2120?2200 cm-1 region. The frequency of the band around 2200 cm-1 is found to be dependent not only on the charge-balancing transition metal cation but also on the framework composition. The frequencies of the band near 1600 cm-1 was found to be dependent on the Si/Al ratio of the investigated zeolites.

scholarly journals Covid-19 Pandemic: Application of Machine Learning Time Series Analysis for Prediction of Human Future

2020 ◽  
Author(s):  
Vikas Chaurasia ◽  
Saurabh Pal
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Linear Trend ◽  
Moving Average ◽  
Arima Model ◽  
Series Data ◽  
Human Society ◽  
Data Set ◽  
Naive Method ◽  
The Government

Abstract Purpose:Coronavirus disease is an irresistible infection caused by the respiratory disease Coronavirus 2 (SARS-CoV-2). It was first found in Wuhan, China, in December 2019, and has since spread universally, causing a constant pandemic. On June 3, 2020, 6.37 million cases were found in 188 countries and regions. Prevention is the only cure for this disease. A study was carried out on Coronavirous to observe the number of cases, deaths and recovery cases worldwide within a specific time period of five months. Based on this data, this research paper will predict the future spread of this infectious disease in human society. Methods:In our study, the data set was taken from WHO "Data WHO Coronavirus Covid-19 cases and deaths-WHO-COVID-19-global-data". This dataset contains information about the observation date, provenance/state, country/region and latest updates. In this article, we implemented several forecasting techniques: naive method, simple average, moving average, single exponential smoothing, Holt linear trend method, Holt Winter method and ARIMA, for comparison, and how these methods improve the Root mean square error score.Results:The naive method is best suited as described over all other methods. In the ARIMA model, utilizing grid search, we recognized a lot of boundaries that delivered the best-fit model for our time series data. By continuing the model, future predictions of death cases indicate that the number of deaths will increased by more than 600,000 by January 2020.Conclusion:This survey will support the government and experts in making arrangements for what is about to happen. Based on the findings of instantaneous model, these models can be adjusted to guide long time.

An Improved Hurst Parameter Estimator Based on Fractional Fourier Transform

2007 ◽  
Author(s):  
YangQuan Chen ◽  
Rongtao Sun ◽  
Anhong Zhou
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Long Range ◽  
Fractional Fourier Transform ◽  
Estimation Method ◽  
Estimation Methods ◽  
Long Range Dependence ◽  
Hurst Parameter ◽  
Parameter Estimator ◽  
Data Set

A fractional Fourier transform (FrFT) based estimation method is introduced in this paper to analyze the long range dependence (LRD) in time series. The degree of LRD can be characterized by the Hurst parameter. The FrFT-based estimation of Hurst parameter proposed in this paper can be implemented efficiently allowing very large data set. We used fractional Gaussian noises (FGN) which typically possesses long-range dependence with known Hurst parameters to test the accuracy of the proposed Hurst parameter estimator. For justifying the advantage of the proposed estimator, some other existing Hurst parameter estimation methods, such as wavelet-based method and a global estimator based on dispersional analysis, are compared. The proposed estimator can process the very long experimental time series locally to achieve a reliable estimation of the Hurst parameter.

EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN

2017 ◽  
Author(s):  
Diaz Juan Navia ◽  
Diaz Juan Navia ◽  
Bolaños Nancy Villegas ◽  
Bolaños Nancy Villegas ◽  
Igor Malikov ◽  
...  
Keyword(s):  
Time Series ◽  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Extreme Values ◽  
Sea Surface ◽  
Absolute Maximum ◽  
Data Set ◽  
Arctic Oscillation Index ◽  
Colombian Pacific

Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.

Nevirapine Pharmaceutical Cocrystal: Design, Development and Formulation

2019 ◽  
Vol 9 (3) ◽  
pp. 240-247
Author(s):  
Prabhakar Panzade ◽  
Priyanka Somani ◽  
Pavan Rathi
Keyword(s):  
Dosage Form ◽  
In Vitro Dissolution ◽  
Soluble Form ◽  
Ir Absorption ◽  
Stoichiometric Ratio ◽  
Design Development ◽  
Formulation Development ◽  
Scanning Calorimetry ◽  
Absorption Bands ◽  
Pharmaceutical Cocrystal

Background and Objective: The top approach to deliver poorly soluble drugs is the use of a highly soluble form. The present study was conducted to enhance the solubility and dissolution of a poorly aqueous soluble drug nevirapine via a pharmaceutical cocrystal. Another objective of the study was to check the potential of the nevirapine cocrystal in the dosage form. Methods: A neat and liquid assisted grinding method was employed to prepare nevirapine cocrystals in a 1:1 and 1:2 stoichiometric ratio of drug:coformer by screening various coformers. The prepared cocrystals were preliminary investigated for melting point and saturation solubility. The selected cocrystal was further confirmed by Infrared Spectroscopy (IR), Differential Scanning Calorimetry (DSC), and Xray Powder Diffraction (XRPD). Further, the cocrystal was subjected to in vitro dissolution study and formulation development. Results: The cocrystal of Nevirapine (NVP) with Para-Amino Benzoic Acid (PABA) coformer prepared by neat grinding in 1:2 ratio exhibited greater solubility. The shifts in IR absorption bands, alterations in DSC thermogram, and distinct XRPD pattern showed the formation of the NVP-PABA cocrystal. Dissolution of NVP-PABA cocrystal enhanced by 38% in 0.1N HCl. Immediate release tablets of NVP-PABA cocrystal exhibited better drug release and less disintegration time. Conclusion: A remarkable increase in the solubility and dissolution of NVP was obtained through the cocrystal with PABA. The cocrystal also showed great potential in the dosage form which may provide future direction for other drugs.

Human Activity Recognition using Fourier Transform Inspired Deep Learning Combination Model

2019 ◽  
Vol 9 (1) ◽  
pp. 16-31
Author(s):  
Kyungkoo Jun
Keyword(s):  
Fourier Transform ◽  
Deep Learning ◽  
Short Term Memory ◽  
Window Size ◽  
Sensor Data ◽  
Data Sets ◽  
Data Set ◽  
Proposed Model ◽  
Testing Data ◽  
Labeling Scheme

Background & Objective: This paper proposes a Fourier transform inspired method to classify human activities from time series sensor data. Methods: Our method begins by decomposing 1D input signal into 2D patterns, which is motivated by the Fourier conversion. The decomposition is helped by Long Short-Term Memory (LSTM) which captures the temporal dependency from the signal and then produces encoded sequences. The sequences, once arranged into the 2D array, can represent the fingerprints of the signals. The benefit of such transformation is that we can exploit the recent advances of the deep learning models for the image classification such as Convolutional Neural Network (CNN). Results: The proposed model, as a result, is the combination of LSTM and CNN. We evaluate the model over two data sets. For the first data set, which is more standardized than the other, our model outperforms previous works or at least equal. In the case of the second data set, we devise the schemes to generate training and testing data by changing the parameters of the window size, the sliding size, and the labeling scheme. Conclusion: The evaluation results show that the accuracy is over 95% for some cases. We also analyze the effect of the parameters on the performance.

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