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With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10−9) methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective, is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a five day period at Hohenpeißenberg, Germany. As a reference device a calibrated cavity ringdown spectrometer Picarro G2301 from the meteorological observatory was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to environmental influences. The obtained results show that relaxation effects due to fluctuating environmental conditions, e.g. ambient humidity, are a non-negligible factor in PA sensor systems. Applying algorithm compensation techniques, which are capable of calculating the influence of relaxational effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 % from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.
With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10−9), methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a 5 d period at Hohenpeißenberg, Germany. As a reference device, a calibrated cavity ring-down spectrometer, Picarro G2301, from the meteorological observatory of the German Weather Service (DWD) was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to fluctuating environmental conditions, e.g. ambient humidity. The obtained results show that for PA sensor systems non-radiative relaxation effects induced by varying humidity are a non-negligible factor. Applying algorithm compensation techniques, which are capable of calculating the influence of non-radiative relaxation effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 % from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.
The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Zenodo), data from several high-contrast ground-based instruments worldwide in which we injected synthetic planetary signals. The data challenge is hosted on the CodaLab competition platform, where participants can upload their results. The specifications of the data challenge are published on our website https://exoplanet-imaging-challenge.github.io/. The first phase, launched on the 1st of September 2019 and closed on the 1st of October 2020, consisted in detecting point sources in two types of common data-set in the field of high-contrast imaging: data taken in pupil-tracking mode at one wavelength (subchallenge 1, also referred to as ADI) and multispectral data taken in pupil-tracking mode (subchallenge 2, also referred to as ADI+mSDI). In this paper, we describe the approach, organisational lessons-learnt and current limitations of the data challenge, as well as preliminary results of the participants’ submissions for this first phase. In the future, we plan to provide permanent access to the standard library of data sets and metrics, in order to guide the validation and support the publications of innovative image processing algorithms dedicated to high-contrast imaging of planetary systems.
We present a sensitive and compact interband cascade laser (ICL) based photoacoustic setup for the detection of gaseous hydrocarbons and discuss its applicability towards trace gas analysis. We investigated the performance of the sensor for trace concentrations of methane, ethane and acetylene diluted in nitrogen. The excitation of methane and ethane was accomplished using one tunable diode laser, covering a range from 3360 to 3372 nm, which was replaced by a separate ICL at 3025 nm for acetylene detection. The influence of ambient parameters such as temperature, flow rate and pressure as well as potential cross-sensitivities towards O2 and H2O have been examined in terms of methane and acetylene detection. A series of simulations proved several of these influences to be attributed to relaxation effects. With a 3σ limit of detection (LoD) of 6.8 parts per billion (ppbV) in case of methane, 2.3 ppbV regarding ethane and 3.6 ppbV in terms of acetylene, the sensor demonstrates a great potential for applications in the field of trace gas analysis.
Successful transfer of photoacoustic gas sensors from laboratory to real-life applications requires knowledge about potential cross-sensitivities towards environmental and gas matrix changes. Multi-dimensional calibration in case of cross-sensitivities can become very complex or even unfeasible. To address this challenge, we present a novel algorithm to compute the collision based non-radiative efficiency and phase lag of energy relaxation on a molecular level (CoNRad) for photoacoustic signal calculation. This algorithmic approach allows to calculate the entire elaxation cascade of arbitrarily complex systems, yielding a theoretical photoacoustic signal. In this work the influence of varying bulk compositions, i.e. nitrogen (N2), oxygen (O2) and water (H2O) on the photoacoustic signal during methane (CH4) detection is demonstrated. The applicability of the algorithm to other photoacoustic setups is shown exemplary by applying it to the relaxational system investigated in [1]. Hayden et al. examined the effect of water on photoacoustic carbon monoxide (CO) detection.
Clot formation within membrane oxygenators (MOs) remains a critical problem during extracorporeal membrane oxygenation (ECMO). The composition of the clots—in particular, the presence of von Willebrand factor (vWF)—may be an indicator for prevalent nonphysiological flow conditions, foreign body reactions, or coagulation abnormalities in critically ill patients. Mats of interwoven gas exchange fibers from randomly collected MOs (PLS, Maquet, Rastatt, Germany) of 21 patients were stained with antibodies (anti‐vWF and anti‐P‐selectin) and counterstained with 4′,6‐diamidino‐2‐phenylindole. The extent of vWF‐loading was correlated with patient and technical data. While 12 MOs showed low vWF‐loadings, 9 MOs showed high vWF‐loading with highest accumulations close to crossing points of adjacent gas fibers. The presence and the extent of vWF‐fibers/“cobwebs,” leukocytes, platelet–leukocyte aggregates (PLAs), and P‐selectin‐positive platelet aggregates were independent of the extent of vWF‐loading. However, the highly loaded MOs were obtained from patients with a significantly elevated SOFA score, severe thrombocytopenia, and persistent liver dysfunction. The coagulation abnormalities of these critically ill patients may cause an accumulation of the highly thrombogenic and elongated high‐molecular‐weight vWF multimers in the plasma which will be trapped in the MOs during the ECMO therapy.
Coagulative disorders, especially clotting during extracorporeal membrane oxygenation, are frequent complications. Direct visualization and analysis of deposits in membrane oxygenators using computed tomography (CT) may provide an insight into the underlying mechanisms causing thrombotic events. However, the already established multidetector CT1 (MDCT) method shows major limitations. Here, we demonstrate the feasibility of applying industrial micro-CT (μCT) to circumvent these restrictions. Three clinically used membrane oxygenators were investigated applying both MDCT and μCT.
The scans were analyzed in terms of clot volume and local clot distribution. As validation, the clot volume was also determined from the fluid volume, which could be filled into the respective used oxygenator compared to a new device. In addition, cross-sectional CT images were compared with crosscut oxygenators. Based on the μCT findings, a morphological measure (sphericity) for assessing clot structures in membrane oxygenators is introduced. Furthermore, by comparing MDCT and μCT results, an augmentation of the MDCT method is proposed, which allows for improved clot volume determination in a clinical setting.
Während KPIs und Dashboards in großer Zahl für den Betrieb eines Unternehmens im eingeschwungenen Zustand zur Verfügung stehen, scheint es insbesondere in der digitalen Transformation besonders schwierig zu sein, Orientierung zu behalten und zu vermitteln. Welche Aspekte sind dabei wichtig? Was ist der Einfluss der Unternehmenskultur? In welcher Reihenfolge sollen wir vorgehen? Wie können wir die wichtigen Parameter messen und visualisieren? Auf diese Fragen geben wir unter Berücksichtigung unterschiedlicher Modelle und Perspektiven Antworten und zeigen am hypothetischen Beispiel eines Autohauses mögliche konkrete Aktionen exemplarisch auf.
Digital Twin of a Photoacoustic Trace Gas Sensor for Monitoring Methane in Complex Gas Compositions
(2022)
The digitalization of industrial processes requires smart sensor systems. Photoacoustic spectroscopy is well suited for this purpose as it allows for small-sized and low-cost trace gas analysis. However, the method is susceptible to changes in measurement conditions and standard calibration routines often fail to correct for all changes. We therefore created a Digital Twin (DT) of a photoacoustic trace gas sensor for methane and evaluated it regarding variations in gas composition (CH4, N2, O2, CO2, H2O), temperature and pressure. With a mean absolute percentage error of 0.8 % the accuracy of the sensor after DT compensation significantly exceeds the 24 % achieved based on standard calibration in nitrogen. For the first time, we can fully analytically compute the photoacoustic signal under moderate ambient conditions with an error in the ppbV range by taking a holistic approach. Assuming knowledge of the underlying energy transfer processes, the model of this Digital Twin can be adapted to any microphone based photoacoustic sensor for monitoring any analyte species.