SAWA experiment ? properties of mineral dust aerosol as seen by synergic lidar and sun-photometer measurements

International audienceWe propose a method of retrieving basic information on mineral dust aerosol particles from synergic sun-photometer and multi-wavelength lidar measurements as well as from the observations of lidar light depolarisation. We use this method in a case study of mineral dust episode in Central Europe. Lidar signals are inversed with a modified Klett-Fernald algorithm. Aerosol optical depth measured with the sun-photometer allows to reduce uncertainties in the inversion procedure through which we estimate vertical profile of aerosol extinction. Next we assume that aerosol particles may be represented by ensemble of randomly oriented, identical spheroids. Having calculated vertical profiles of aerosol extinction coefficients for lidar wavelengths, we compute the profiles of local Angstrom exponent. We use laser beam depolarisation together with the calculated Angstrom exponents to estimate the shapes (aspect ratios) and sizes of the spheroids. Numerical calculations are performed with the transition matrix (T-matrix) algorithm by M. Mishchenko. The proposed method was first used during SAWA measurement campaign in Warsaw, spring 2005, to characterise the particles of desert dust, drifting over Poland with a southern-eastern wind (13?14 April). Observations and T-matrix calculations show that mode radii of spheroids representative for desert aerosols' particles are in the range of 0.15?0.3 ?m, while their aspect ratios are lower than 0.7 or larger than 1.7

Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry

Background: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients\u2019 clinical phenotypes and analyse the differential clinical course. Methods: We performed a hierarchical cluster analysis based on Ward\u2019s Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients\u2019 prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P <.001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27\u20133.62; HR 3.42, 95%CI 2.72\u20134.31; HR 2.79, 95%CI 2.32\u20133.35), and Cluster 1 (HR 1.88, 95%CI 1.48\u20132.38; HR 2.50, 95%CI 1.98\u20133.15; HR 2.09, 95%CI 1.74\u20132.51) reported a higher risk for the three outcomes respectively. Conclusions: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes