Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).Peer reviewe

Haemophilus influenzae type b vaccine formulation and risk of childhood leukaemia

Incidence of childhood leukaemia was studied among subjects of a vaccine trial in Finland comparing the polysaccharide–diptheria toxoid conjugate and oligosaccharide–CRM197 conjugate Haemophilus influenzae type b conjugate vaccine formulations. Eighty cases of childhood leukaemia were detected: 35 among children on the polysaccharide–diptheria toxoid conjugate arm, and 45 among children on the oligosaccharide–CRM197 conjugate arm, which was not statistically significant

Sensitivity analysis of the meteorological preprocessor MPP-FMI 3.0 using algorithmic differentiation

The meteorological input parameters for urbanand local-scale dispersion models can be evaluated by pre-processing meteorological observations, using a boundarylayer parameterisation model. This study presents a sensitivity analysis of a meteorological preprocessor model (MPP-FMI) that utilises readily available meteorological data as input. The sensitivity of the preprocessor to meteorological input was analysed using algorithmic differentiation (AD). The AD tool used was TAPENADE. The AD method numerically evaluates the partial derivatives of functions that are implemented in a computer program. In this study, we focus on the evaluation of vertical fluxes in the atmosphere and in particular on the sensitivity of the predicted inverse Obukhov length and friction velocity on the model input parameters. The study shows that the estimated inverse Obukhov length and friction velocity are most sensitive to wind speed and second most sensitive to solar irradiation. The dependency on wind speed is most pronounced at low wind speeds. The presented results have implications for improving the meteorological preprocessing models. AD is shown to be an efficient tool for studying the ranges of sensitivities of the predicted parameters on the model input values quantitatively. A wider use of such advanced sensitivity analysis methods could potentially be very useful in analysing and improving the models used in atmospheric sciences.Peer reviewe

Particle production and equilibrium properties within a new hadron transport approach for heavy-ion collisions

The microscopic description of heavy-ion reactions at low beam energies is achieved within hadronic transport approaches. In this article a new approach SMASH (Simulating Many Accelerated Strongly-interacting Hadrons) is introduced and applied to study the production of non-strange particles in heavy-ion reactions at $E_{\rm kin}=0.4-2A$ GeV. First, the model is described including details about the collision criterion, the initial conditions and the resonance formation and decays. To validate the approach, equilibrium properties such as detailed balance are presented and the results are compared to experimental data for elementary cross sections. Finally results for pion and proton production in C+C and Au+Au collisions is confronted with HADES and FOPI data. Predictions for particle production in $\pi+A$ collisions are made.Comment: 30 pages, 30 figures, replaced with published version; only minor change