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Accurate modeling of ash clouds from volcanic eruptions requires knowledge about the eruption source parameters including eruption onset, duration, mass eruption rates, particle size distribution, and vertical-emission profiles. However, most of these parameters are unknown and must be estimated somehow. Some are estimated based on observed correlations and known volcano parameters. However, a more accurate estimate is often needed to bring the model into closer agreement with observations. This paper describes the inversion procedure implemented at the Norwegian Meteorological Institute for estimating ash emission rates from retrieved satellite ash column amounts and a priori knowledge. The overall procedure consists of five stages: (1) generate a priori emission estimates, (2) run forward simulations with a set of unit emission profiles, (3) collocate/match observations with emission simulations, (4) build system of linear equations, and (5) solve overdetermined systems. We go through the mathematical foundations for the inversion procedure, performance for synthetic cases, and performance for real-world cases. The novelties of this paper include a memory efficient formulation of the inversion problem, a detailed description and illustrations of the mathematical formulations, evaluation of the inversion method using synthetic known-truth data as well as real data, and inclusion of observations of ash cloud-top height. The source code used in this work is freely available under an open-source license and is able to be used for other similar applications.

Between 27 June and 14 July 2019 aerosol layers were observed by the United Kingdom (UK) Raman lidar network in the upper troposphere and lower stratosphere. The arrival of these aerosol layers in late June caused some concern within the London Volcanic Ash Advisory Centre (VAAC) as according to dispersion simulations the volcanic plume from the 21 June 2019 eruption of Raikoke was not expected over the UK until early July. Using dispersion simulations from the Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME), and supporting evidence from satellite and in situ aircraft observations, we show that the early arrival of the stratospheric layers was not due to aerosols from the explosive eruption of the Raikoke volcano but due to biomass burning smoke aerosols associated with intense forest fires in Alberta, Canada, that occurred 4 d prior to the Raikoke eruption. We use the observations and model simulations to describe the dispersion of both the volcanic and forest fire aerosol clouds and estimate that the initial Raikoke ash aerosol cloud contained around 15 Tg of volcanic ash and that the forest fires produced around 0.2 Tg of biomass burning aerosol. The operational monitoring of volcanic aerosol clouds is a vital capability in terms of aviation safety and the synergy of NAME dispersion simulations, and lidar data with depolarising capabilities allowed scientists at the Met Office to interpret the various aerosol layers over the UK and attribute the material to their sources. The use of NAME allowed the identification of the observed stratospheric layers that reached the UK on 27 June as biomass burning aerosol, characterised by a particle linear depolarisation ratio of 9 %, whereas with the lidar alone the latter could have been identified as the early arrival of a volcanic ash–sulfate mixed aerosol cloud. In the case under study, given the low concentration estimates, the exact identification of the aerosol layers would have made little substantive difference to the decision-making process within the London VAAC. However, our work shows how the use of dispersion modelling together with multiple observation sources enabled us to create a more complete description of atmospheric aerosol loading.

Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6–12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m−2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones within scenes. The impact of ice and liquid-water clouds on the detection and retrieval of volcanic ash, implies that to fully appreciate the location and amount of ash, hyperspectral and spectral band measurements by satellite instruments should be combined with ash dispersion modelling.

Background: Recently, magnetic resonance (MR)-conditional implantable cardioverter defibrillator (ICD) systems have become available. However, associated cardiac MR image (MRI) quality is unknown. The goal was to evaluate the image quality performance of various cardiac MR sequences in a multicenter trial of patients implanted with an MR-conditional ICD system., Methods and Results: The Evera-MRI trial enrolled 275 patients in 42 centers worldwide. There were 263 patients implanted with an Evera-MRI single- or dual-chamber ICD and randomized to controls (n=88) and MRI (n=175), 156 of whom underwent a protocol-required MRI (9-12 weeks post implant). Steady-state-free-precession (SSFP) and fast-gradient-echo (FGE) sequences were acquired in short-axis and horizontal long-axis orientations. Qualitative and quantitative assessment of image quality was performed by using a 7-point scale (grades 1-3: good quality, grades 6-7: nondiagnostic) and measuring ICD- and lead-related artifact size. Good to moderate image quality (grades 1-5) was obtained in 53% and 74% of SSFP and FGE acquisitions, respectively, covering the left ventricle, and in 69% and 84%, respectively, covering the right ventricle. Odds for better image quality were greater for right ventricle versus left ventricle (odds ratio, 1.8; 95% confidence interval, 1.5-2.2; P<0.0001) and greater for FGE versus SSFP (odds ratio, 3.5; 95% confidence interval, 2.5-4.8; P<0.0001). Compared with SSFP, ICD-related artifacts on FGE were smaller (141±65 versus 75±57 mm, respectively; P<0.0001). Lead artifacts were much smaller than ICD artifacts (P<0.0001)., Conclusions: FGE yields good to moderate quality in 74% of left ventricle and 84% of right ventricle acquisitions and performs better than SSFP in patients with an MRI-conditional ICD system. In these patients, cardiac MRI can offer diagnostic information in most cases., Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT02117414., (© 2016 American Heart Association, Inc.)

Aims: Unwanted phrenic nerve stimulation (PNS) has been reported in ∼1 in 4 patients undergoing left ventricular (LV) pacing. The occurrence of PNS over mid-term follow-up and the significance of PNS are less certain., Methods and Results: Data from 1307 patients enrolled in pre-market studies of LV leads manufactured by Medtronic (models 4193 and 4195 unipolar, 4194, 4196, 4296, and 4396 bipolar) were pooled. Left ventricular lead location was recorded at implant using a common classification scheme. Phrenic nerve stimulation symptoms were either spontaneously reported or identified at scheduled follow-up visits. A PNS-related complication was defined as PNS resulting in invasive intervention or the termination of LV pacing. Average follow-up was 14.9 months (range 0.0-46.6). Phrenic nerve stimulation symptoms occurred in 169 patients (12.9%). Phrenic nerve stimulation-related complications occurred in 21 of 1307 patients (1.6%); 16 of 738 (2.2%) in the unipolar lead studies, and 5 of 569 (0.9%) in the bipolar lead studies (P = 0.08). Phrenic nerve stimulation was more frequent at middle-lateral/posterior, and apical LV sites (139/1010) vs. basal-posterior/lateral/anterior, and middle-anterior sites (20/297; P= 0.01). As compared with an anterior LV lead position, a lateral LV pacing site was associated with over a four-fold higher risk of PNS (P= 0.005) and an apical LV pacing site was associated with over six-fold higher risk of PNS (P= 0.001)., Conclusion: Phrenic nerve stimulation occurred in 13% of patients undergoing LV lead placement and was more common at mid-lateral/posterior, and LV apical sites. Most cases (123/139; 88%) of PNS were mitigated via electrical reprogramming, without the need for invasive intervention.

Aims: Predictors of Response to Cardiac Resynchronization Therapy (CRT) (PROSPECT) was the first large-scale, multicentre clinical trial that evaluated the ability of several echocardiographic measures of mechanical dyssynchrony to predict response to CRT. Since response to CRT may be defined as a spectrum and likely influenced by many factors, this sub-analysis aimed to investigate the relationship between baseline characteristics and measures of response to CRT., Methods and Results: A total of 286 patients were grouped according to relative reduction in left ventricular end-systolic volume (LVESV) after 6 months of CRT: super-responders (reduction in LVESV > or =30%), responders (reduction in LVESV 15-29%), non-responders (reduction in LVESV 0-14%), and negative responders (increase in LVESV). In addition, three subgroups were formed according to clinical and/or echocardiographic response: +/+ responders (clinical improvement and a reduction in LVESV > or =15%), +/- responders (clinical improvement or a reduction in LVESV > or =15%), and -/- responders (no clinical improvement and no reduction in LVESV > or =15%). Differences in clinical and echocardiographic baseline characteristics between these subgroups were analysed. Super-responders were more frequently females, had non-ischaemic heart failure (HF), and had a wider QRS complex and more extensive mechanical dyssynchrony at baseline. Conversely, negative responders were more frequently in New York Heart Association class IV and had a history of ventricular tachycardia (VT). Combined positive responders after CRT (+/+ responders) had more non-ischaemic aetiology, more extensive mechanical dyssynchrony at baseline, and no history of VT., Conclusion: Sub-analysis of data from PROSPECT showed that gender, aetiology of HF, QRS duration, severity of HF, a history of VT, and the presence of baseline mechanical dyssynchrony influence clinical and/or LV reverse remodelling after CRT. Although integration of information about these characteristics would improve patient selection and counselling for CRT, further randomized controlled trials are necessary prior to changing the current guidelines regarding patient selection for CRT.