Extremely fast retrieval of volcanic SO2 layer heights from UV satellite data using inverse learning machines

2021 ◽  
Author(s):  
Pascal Hedelt ◽  
MariLiza Koukouli ◽  
Konstantinos Michaelidis ◽  
Taylor Isabelle ◽  
Dimitris Balis ◽  
...  
Keyword(s):  
Real Time ◽  
Accurate Determination ◽  
Principal Component ◽  
Volcanic Eruptions ◽  
Neural Network Approach ◽  
Layer Height ◽  
Precise Knowledge ◽  
Innovation Project ◽  
Learning Machine

<p>Precise knowledge of the location and height of the volcanic sulfur dioxide (SO<sub>2</sub>) plume is essential for accurate determination of SO<sub>2</sub> emitted by volcanic eruptions, however so far not available in operational near-real time UV satellite retrievals. The FP_ILM algorithm (Full-Physics Inverse Learning Machine) enables for the first time to extract the SO<sub>2</sub> layer height information in a matter of seconds for current UV satellites and is thus applicable in NRT environments.</p><p>The FP_ILM combines a principal component analysis (PCA) and a neural network approach (NN) to extract the information about the volcanic SO<sub>2</sub> layer height from high-resolution UV satellite backscatter measurements. So far, UV based SO<sub>2 </sub>layer height retrieval algorithms were very time-consuming and therefore not suitable for near-real-time applications like aviation control, although the SO<sub>2</sub> LH is essential for accurate determination of SO<sub>2</sub> emitted by volcanic eruptions.</p><p>In this presentation, we will present the latest FP_ILM algorithm improvements and show results of recent volcanic eruptions.</p><p>The SO<sub>2</sub> layer height product for Sentinel-5p/TROPOMI is developed in the framework of the SO<sub>2</sub> Layer Height (S5P+I: SO<sub>2</sub> LH) project, which is part of ESA Sentinel-5p+ Innovation project (S5P+I). The S5P+I project aims to develop novel scientific and operational products to exploit the potential of the S5P/TROPOMI capabilities. The S5P+I: SO<sub>2</sub> LH project is dedicated to the generation of an SO<sub>2</sub> LH product and its extensive verification with collocated ground- and space-born measurements.</p>

scholarly journals SO<sub>2</sub> Layer Height retrieval from Sentinel-5 Precursor/TROPOMI using FP_ILM

2019 ◽  
Author(s):  
Pascal Hedelt ◽  
Dmitry S. Efremenko ◽  
Diego G. Loyola ◽  
Robert Spurr ◽  
Lieven Clarisse
Keyword(s):  
Accurate Determination ◽  
Volcanic Eruptions ◽  
Critical Parameters ◽  
Retrieval Algorithm ◽  
Layer Height ◽  
Precise Knowledge ◽  
Learning Machine ◽  
The Impact ◽  
First Time

Abstract. Precise knowledge of the location and height of the volcanic SO2 plumes is essential for accurate determination of SO2 emitted by volcanic eruptions for aviation control applications, but so far very time-consuming to retrieve from UV satellite data. The SO2 height is furthermore one of the most critical parameters that determine the impact on the climate. We have developed an extremely fast yet accurate SO2 layer height retrieval algorithm using the Full-Physics Inverse Learning Machine (FP_ILM) algorithm, which, for the first time, is applied to TROPOMI aboard Sentinel-5 Precursor. In this work we demonstrate the ability of the FP_ILM algorithm to retrieve layer heights in near-real time applications with an accuracy of better than 2 km for SO2 total columns larger than 20 DU and show SO2 layer height results for selected volcanic eruptions.

FP_ILM: Extremely fast volcanic SO2 plume height retrieval based on S5P/TROPOMI data using inverse learning machines

2020 ◽  
Author(s):  
Dmitry Efremenko ◽  
Pascal Hedelt ◽  
Diego Loyola ◽  
Robert Spurr
Keyword(s):  
Accurate Determination ◽  
Volcanic Eruptions ◽  
Plume Height ◽  
Neural Network Approach ◽  
Layer Height ◽  
Learning Machines ◽  
Novel Method ◽  
Learning Machine ◽  
First Time

&lt;p&gt;We present here a novel method for the precise and extremely fast retrieval of volcanic SO2 layer height (LH) based on S5P/TROPOMI data. We have developed the Full-Physics Inverse Learning Machine (FP_ILM) algorithm using a combined principal components analysis (PCA) and neural network approach (NN) to extract the information about the volcanic SO2 LH from high-resolution UV backscatter measurement of TROPOMI aboard Sentinel-5 Precursor.&lt;/p&gt;&lt;p&gt;The SO2 LH is essential for accurate determination of SO2 emitted by volcanic eruptions. So far UV based SO2 plume height retrieval algorithms are very time-consuming and therefore not suitable for near-real-time applications. The FP_ILM approach however enables for the first time to extract the SO2 LH information in a matter of seconds for an entire S5P orbit and thus applicable in NRT application.&lt;/p&gt;&lt;p&gt;The FP_ILM SO2 LH product is developed as part of ESA&amp;#8217;s &amp;#8216;Sentinel-5p+ Innovation - SO2 Layer Height project&amp;#8217; (S5P+I: SO2 LH) project, dedicated to the generation of an SO2 LH product and its extensive verification with collocated ground- and space-born measurements.&lt;/p&gt;

scholarly journals Sulfur dioxide layer height retrieval from Sentinel-5 Precursor/TROPOMI using FP_ILM

2019 ◽  
Vol 12 (10) ◽  
pp. 5503-5517 ◽  
Author(s):  
Pascal Hedelt ◽  
Dmitry S. Efremenko ◽  
Diego G. Loyola ◽  
Robert Spurr ◽  
Lieven Clarisse
Keyword(s):  
Sulfur Dioxide ◽  
Accurate Determination ◽  
Volcanic Eruptions ◽  
Critical Parameters ◽  
Layer Height ◽  
Learning Machine ◽  
The Impact ◽  
First Time ◽  
Better Than

Abstract. The accurate determination of the location, height, and loading of sulfur dioxide (SO2) plumes emitted by volcanic eruptions is essential for aviation safety. The SO2 layer height is also one of the most critical parameters with respect to determining the impact on the climate. Retrievals of SO2 plume height have been carried out using satellite UV backscatter measurements, but, until now, such algorithms are very time-consuming. We have developed an extremely fast yet accurate SO2 layer height retrieval using the Full-Physics Inverse Learning Machine (FP_ILM) algorithm. This is the first time the algorithm has been applied to measurements from the TROPOMI instrument onboard the Sentinel-5 Precursor platform. In this paper, we demonstrate the ability of the FP_ILM algorithm to retrieve SO2 plume layer heights in near-real-time applications with an accuracy of better than 2 km for SO2 total columns larger than 20 DU. We present SO2 layer height results for the volcanic eruptions of Sinabung in February 2018, Sierra Negra in June 2018, and Raikoke in June 2019, observed by TROPOMI.

Extremely fast retrieval of volcanic SO2 layer heights from UV satellite data using inverse learning machines

2020 ◽  
Author(s):  
Pascal Hedelt ◽  
MariLiza Koukouli ◽  
Isabelle Taylor ◽  
Dimitris Balis ◽  
Don Grainger ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Volcanic Eruption ◽  
Accurate Determination ◽  
Volcanic Eruptions ◽  
Learning Machines ◽  
Precise Knowledge ◽  
First Results ◽  
Gas Measurements ◽  
Learning Machine ◽  
Atmospheric Trace Gas

&lt;p&gt;Precise knowledge of the location and height of the volcanic sulfur dioxide (SO&lt;sub&gt;2&lt;/sub&gt;) plume is essential for accurate determination of SO&lt;sub&gt;2&lt;/sub&gt; emitted by volcanic eruptions. So far, UV based SO&lt;sub&gt;2&lt;/sub&gt; plume height retrieval algorithms are very time-consuming and therefore not suitable for near-real-time applications like aviation control. We have therefore developed the Full-Physics Inverse Learning Machine (FP_ILM) algorithm for extremely fast and accurate retrieval of volcanic SO&lt;sub&gt;2&lt;/sub&gt; layer heights based on the UV satellite instruments Sentinel-5 Precursor/TROPOMI and MetOp/GOME-2.&lt;/p&gt;&lt;p&gt;In this presentation, we will present the FP-ILM algorithm and show results of the 2019 Raikoke eruption; a strong volcanic eruption which has emitted a huge ash cloud accompanied by more than 1300 DU of SO&lt;sub&gt;2&lt;/sub&gt;, which could be detected &amp;#160;even two months after the end of eruptive event. We will also present first results of the recent Taal volcanic eruption on 13 January 2020 in Indonesia, which has injected a huge ash and SO&lt;sub&gt;2&lt;/sub&gt; plume into the upper atmosphere, with plume heights of up to 20km.&amp;#160;&lt;/p&gt;&lt;p&gt;The algorithm is developed in the framework of ESA's&amp;#160; &quot;Sentinel-5p+ Innovation: SO&lt;sub&gt;2&lt;/sub&gt; Layer Height project&quot; (S5P+I: SO2 LH),&amp;#160; dedicated to the generation of an SO&lt;sub&gt;2&lt;/sub&gt; LH product and its extensive verification with collocated ground- and space-born measurements.&lt;/p&gt;&lt;p&gt;The high-resolution UV spectrometer GOME-2 aboard the three EPS MetOp-A, -B, and &amp;#8211;C satellites perform global daily atmospheric trace-gas measurements with a spatial resolution of &amp;#160;40x40km&lt;sup&gt;2&lt;/sup&gt; at an overpass time of 8:30h local time. The UV spectrometer TROPOMI aboard the ESA Sentinel-5P satellite provides a much higher spatial resolution of currently 5.6x3.6km&lt;sup&gt;2&lt;/sup&gt; per ground pixel, at an overpass time of 13:30h. In the future, also UV instruments aboard the Sentinel-4 (geostationary) and Sentinel-5 will complement the satellite-based global monitoring of atmospheric trace gases.&lt;/p&gt;

scholarly journals Left Bundle Branch Area Pacing guided by Continuous Uninterrupted Monitoring of the unipolar Pacing Characteristics.

2021 ◽  
Author(s):  
Kris Gillis ◽  
Jean-Yves Wielandts ◽  
Gabriela Hilfiker ◽  
Louisa O'Neill ◽  
Alina Vlase ◽  
...  
Keyword(s):  
Real Time ◽  
Group Performance ◽  
Accurate Determination ◽  
Septal Perforation ◽  
Validation Group ◽  
Pacing Lead ◽  
Qrs Morphology ◽  
Qrs Duration ◽  
Highly Correlated

Introduction. During left bundle branch area pacing (LBBAP) lead implantation, intermittent monitoring of unipolar pacing characteristics validates LBB capture and can detect septal perforation. We aimed to demonstrate that continuous uninterrupted unipolar pacing from an inserted lead stylet (LS) is feasible and facilitates LBBAP implantation. Methods. Thirty patients (mean age 76 ± 14 years) were implanted with stylet-driven pacing lead (Biotronik Solia S60). In 10 patients (validation-group) conventional, interrupted implantation was performed, with comparison of unipolar pacing characteristics between LS and connector-pin (CP)-pacing after each rotation step. In 20 patients (feasibility-group) performance and safety of uninterrupted implantation during continuous pacing from the LS were analyzed. Results. In the validation-group, LS and CP-pacing impedances were highly correlated (R=0.95, p<0.0001, bias 12±37Ω). Pacing characteristics from LS and CP showed comparable sensed electrograms and paced QRS morphologies. In the feasibility-group, continuous LS-pacing allowed beat-to-beat monitoring of impedance and QRS morphology to guide implantation. This resulted in successful LBBAP in all patients, after a mean of 1±0 attempts, with mean threshold 0.81 ± 0.4V, median sensing 6.5mV [IQR 4.4-9.5] and mean impedance 624 ± 101Ω, and positive LBBAP-criteria with median paced QRS duration 120ms [IQR 112-152ms] and median pLVAT 73ms [IQR 68-80.5ms]. No septal perforation occurred. Conclusion. Unipolar pacing from the LS allows accurate determination of pacing impedance and generates similar paced QRS morphologies and equal sensed electrograms, compared to CP pacing. Continuous LS pacing allows real-time monitoring of impedance and paced QRS morphology, which facilitates a safe and successful LBBAP lead implantation.

scholarly journals A Method for Real Time Detection of Reaction Endpoints Using a Moving Window T-Test of in Situ Time Course Data

2020 ◽  
Author(s):  
Elyse N. Towns ◽  
John Guo ◽  
Alexander O'Brien ◽  
Robert W. Bondi
Keyword(s):  
Real Time ◽  
Process Parameters ◽  
Time Course ◽  
Accurate Determination ◽  
Scale Up ◽  
Feasibility Studies ◽  
T Test ◽  
Moving Window ◽  
Test Algorithm

In-line mid-infrared spectroscopy (FTIR) was used to monitor a reaction which had a highly inconsistent rate due to sensitivity to changes in process parameters and the quality of the starting materials. Accurate determination of the endpoint in real time was needed to prevent formation of an impurity by degradation of the product. A moving window t-test algorithm was used to predict and determine the endpoint by analysis of FTIR trends during the reaction. The method was selected because it determined the endpoint in the correct range for reactions with different process parameters and data collected with different FTIR instruments. During development, the FTIR and t-test algorithm were used to monitor reactions for feasibility studies, process optimization, use tests, robustness DoE, and scale up to pilot plant. The method for monitoring the reaction may be useful in a GMP manufacturing environment where sampling and analysis are time consuming. <br>

scholarly journals Comparison Of Urinary Bladder Volume In Children Using Suprapubic Ultrasonic Bi-Planner Technique With Voided Urine Volume

2012 ◽  
Vol 17 (2) ◽  
pp. 4-7
Author(s):  
S Sadek ◽  
M Hossain ◽  
H Akther ◽  
A Sikdar
Keyword(s):  
Real Time ◽  
Accurate Determination ◽  
Urine Volume ◽  
Bladder Capacity ◽  
Bladder Volume ◽  
Bladder Function ◽  
Urethral Trauma ◽  
Fear And Anxiety ◽  
Real Time Ultrasonography

Accurate determination of intravesical residual urine volume as well as bladder capacity is of significant importance in children. The ability to confirm these measurements non invasively in children avoids discomfort, urethral trauma and the introduction of urinary tract infection. Also, by avoiding the need for catheterization this technique permits more physiological assessment and allows for repeated examinations without fear and anxiety on the part of the patients. In this prospective study we assess the accuracy of the real time, hand held, ultrasonic device using suprapubic views and biplanar technique to determine intravesical volumes. Real time ultrasonography with suprapubic views and the described bi-planar technique to determine intravesical urine volume is simple, accurate and reproducible. It also is rapid and noninvasive, and can detect accurately an empty bladder in children. A strong correlation was found between the estimated bladder volume with our method and voided urine volume (0 ml, residual volume) .This study concluded that the modality used in this study has the potential to provide useful and reproducible information in the clinical evaluation of bladder function in children.DOI: http://dx.doi.org/10.3329/jdnmch.v17i2.12199 J. Dhaka National Med. Coll. Hos. 2011; 17 (02): 4-7

Determination of cellulose, hemicellulose and lignin content using near-infrared spectroscopy in flax fiber

2019 ◽  
Vol 89 (23-24) ◽  
pp. 4875-4883 ◽  
Author(s):  
Jing Huang ◽  
Chongwen Yu
Keyword(s):  
Spectral Range ◽  
Near Infrared ◽  
Lignin Content ◽  
Full Range ◽  
Accurate Determination ◽  
Principal Component ◽  
Flax Fiber ◽  
Fiber Composition ◽  
Wet Chemical

The rapid and accurate determination of flax fiber composition is necessary for its application, but until now it has mainly been tested by the wet chemical method, which is time-consuming and not environmentally friendly. In this paper, near-infrared (NIR) spectroscopy was studied to determinate the main composition of flax, in which 43 flax samples were tested according to the traditional Chinese wet chemical component test standard. Five sets of spectra were generated to show the characteristic of each sample; in total 215 spectra sets were collected using a Fourier transform near-infrared spectrometer. The methods of partial least squares (PLS) and principal component regression (PCR) were used to establish the relationships between the data from the chemical and NIR methods. PLS proved to be a better quantitative method than PCR, based on the value of the coefficient of multiple determination for calibration ( Rc2) and prediction ( Rp2), the ratio of performance to standard deviate (RPD) and the root mean square error of prediction (RMSEP). With the best pretreatment method, the spectral range of 10,000–4000 cm–1yielded a better predictive result than the full range, with Rc2of 0.968, Rp2of 0.955, RMSEP of 1.060%, RPD of 4.641 for cellulose and Rc2of 0.958, Rp2of 0.906, RMSEP of 0.678%, RPD of 3.305 for hemicellulose, while the spectral range 6900–5600 cm–1yielded a better predictive result with Rc2of 0.936, Rp2of 0.769, RMSEP of 0.455%, and RPD of 2.366 for lignin. The study shows that NIR models can provide a simple and fast way to analyze flax fiber composition, which is also beneficial to evaluate its quality.

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