|
|
“The shielding effect of the protective glazing of historical stained glass windows from an atmospheric chemistry perspective: case study Sainte Chapelle, Paris”. Godoi RHM, Kontozova V, Van Grieken R, Atmospheric environment : an international journal 40, 1255 (2006). http://doi.org/10.1016/J.ATMOSENV.2005.10.033
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1016/J.ATMOSENV.2005.10.033
|
|
|
|
“Speciation and diurnal variation of thoracic, fine thoracic and sub-micrometer airborne particulate matter at naturally ventilated office environments”. Horemans B, Van Grieken R, Atmospheric environment : an international journal 44, 1497 (2010). http://doi.org/10.1016/J.ATMOSENV.2010.01.010
Abstract: Thoracic (PM10), fine thoracic (PM2.5) and sub-micrometer (PM1) airborne particulate matter was sampled during day and night. In total, about 100 indoor and outdoor samples were collected for each fraction at ten different office environments. Energy-dispersive X-ray fluorescence spectrometry and ion chromatography were applied for the quantification of some major and minor elements and ions in the collected aerosols. During daytime, mass concentrations were in the ranges: 1129, 8.124, and 6.618 μg m−3, with averages of 20 ± 1, 15.0 ± 0.9, and 11.0 ± 0.8 μg m−3, respectively. At night, mass concentrations were found to be significantly lower for all fractions. Indoor PM1 concentrations exceeded the corresponding outdoor levels during office hours and were thought to be elevated by office printers. Particles with diameters between 1 and 2.5 μm and 2.5 and 10 μm were mainly associated with soil dust elements and were clearly subjected to distinct periods of settling/resuspension. Indoor NO3 − levels were found to follow specific microclimatic conditions at the office environments, while daytime levels of sub-micrometer Cl− were possibly elevated by the use of Cl-containing cleaning products. Indoor carbon black concentrations were sometimes as high as 22 μg m−3 and were strongly correlated with outdoor traffic conditions.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1016/J.ATMOSENV.2010.01.010
|
|
|
|
“Thin-window electron probe X-ray microanalysis of individual atmospheric particles above the North Sea”. de Hoog J, Osán J, Szalóki I, Eyckmans K, Worobiec A, Ro C-U, Van Grieken R, Atmospheric environment : an international journal 39, 3231 (2005). http://doi.org/10.1016/J.ATMOSENV.2005.02.025
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Laboratory Experimental Medicine and Pediatrics (LEMP)
DOI: 10.1016/J.ATMOSENV.2005.02.025
|
|
|
|
“Weathering of dolomitic sandstone under ambient conditions”. Sweevers H, Delalieux F, Van Grieken R, Atmospheric environment : an international journal 32, 733 (1998). http://doi.org/10.1016/S1352-2310(97)00341-5
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1016/S1352-2310(97)00341-5
|
|
|
|
“CFD modelling of small particle dispersion: the influence of the turbulence kinetic energy in the atmospheric boundary layer”. Gorlé, C, van Beeck J, Rambaud P, Van Tendeloo G, Atmospheric environment : an international journal 43, 673 (2009). http://doi.org/10.1016/j.atmosenv.2008.09.060
Abstract: When considering the modelling of small particle dispersion in the lower part of the Atmospheric Boundary Layer (ABL) using Reynolds Averaged Navier Stokes simulations, the particle paths depend on the velocity profile and on the turbulence kinetic energy, from which the fluctuating velocity components are derived to predict turbulent dispersion. It is therefore important to correctly reproduce the ABL, both for the velocity profile and the turbulence kinetic energy profile. For RANS simulations with the standard kå model, Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the kå turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 4647, 145153.) proposed a set of boundary conditions which result in horizontally homogeneous profiles. The drawback of this method is that it assumes a constant profile of turbulence kinetic energy, which is not always consistent with field or wind tunnel measurements. Therefore, a method was developed which allows the modelling of a horizontally homogeneous turbulence kinetic energy profile that is varying with height. By comparing simulations performed with the proposed method to simulations performed with the boundary conditions described by Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the kå turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 4647, 145153.), the influence of the turbulence kinetic energy on the dispersion of small particles over flat terrain is quantified.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 3.629
Times cited: 79
DOI: 10.1016/j.atmosenv.2008.09.060
|
|
|
|
“Stack gas dispersion measurements with large scale-PIV, aspiration probes and light scattering techniques and comparison with CFD”. Nakiboglu G, Gorlé, C, Horvath I, van Beeck J, Blocken B, Atmospheric environment : an international journal 43, 3396 (2009). http://doi.org/10.1016/j.atmosenv.2009.03.047
Abstract: The main purpose of this research is to manage simultaneous measurement of velocity and concentration in large cross-sections by recording and processing images of cloud structures to provide more detailed information for e.g. validation of CFD simulations. Dispersion from an isolated stack in an Atmospheric Boundary Layer (ABL) was chosen as the test case and investigated both experimentally and numerically in a wind tunnel. Large Scale-Particle Image Velocimetry (LS-PIV), which records cloud structures instead of individual particles, was used to obtain the velocity field in a vertical plane. The concentration field was determined by two methods: Aspiration Probe (AP) measurements and Light Scattering Technique (LST). In the latter approach, the same set of images used in the LS-PIV was employed. The test case was also simulated using the CFD solver FLUENT 6.3. Comparison between AP measurements and CFD revealed that there is good agreement when using a turbulent Schmidt number of 0.4. For the LST measurements, a non-linear relation between concentration and light intensity was observed and a hyperbolic-based function is proposed as correction function. After applying this correction function, a close agreement between CFD and LST measurements is obtained. (C) 2009 Elsevier Ltd. All rights reserved.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 3.629
Times cited: 15
DOI: 10.1016/j.atmosenv.2009.03.047
|
|
|
|
“Quantifying inflow uncertainties in RANS simulations of urban pollutant dispersion”. García Sánchez C, Van Tendeloo G, Gorle C, Atmospheric environment : an international journal 161, 263 (2017). http://doi.org/10.1016/J.ATMOSENV.2017.04.019
Abstract: Numerical simulations of flow and pollutant dispersion in urban environments have the potential to support design and policy decisions that could reduce the population's exposure to air pollution. Reynolds-averaged Navier-Stokes simulations are a common modeling technique for urban flow and dispersion, but several sources of uncertainty in the simulations can affect the accuracy of the results. The present study proposes a method to quantify the uncertainty related to variability in the inflow boundary conditions. The method is applied to predict flow and pollutant dispersion in downtown Oklahoma City and the results are compared to field measurements available from the Joint Urban 2003 measurement campaign. Three uncertain parameters that define the inflow profiles for velocity, turbulence kinetic energy and turbulence dissipation are defined: the velocity magnitude and direction, and the terrain roughness length. The uncertain parameter space is defined based on the available measurement data, and a non-intrusive propagation approach that employs 729 simulations is used to quantify the uncertainty in the simulation output. A variance based sensitivity analysis is performed to identify the most influential uncertain parameters, and it is shown that the predicted tracer concentrations are influenced by all three uncertain variables. Subsequently, we specify different probability distributions for the uncertain inflow variables based on the available measurement data and calculate the corresponding means and 95% confidence intervals for comparison with the field measurements at 35 locations in downtown Oklahoma City. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 3.629
Times cited: 17
DOI: 10.1016/J.ATMOSENV.2017.04.019
|
|
