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.

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.

Abstract: The surface of the aerial parts of the plant, also termed the phyllosphere, is a selective habitat for microbes. The bacterial composition of the phyllosphere depends on host plant species, leaf characteristics, season, climate, and geographic location of the host plant. In this study, we investigated the effect of an urban environment on the bacterial composition of phyllosphere communities. We performed a passive biomonitoring experiment in which leaves were sampled from ivy (Hedera sp.), a common evergreen climber species, in urban and non-urban locations. Exposure to traffic-generated particulate matter was estimated using leaf biomagnetic analyses. The bacterial community composition was determined using 16S rRNA gene sequencing on the Illumina MiSeq. The phyllosphere microbial communities of ivy differed greatly between urban and non-urban locations, as we observed a shift in several of the dominant taxa: Beijerinckia and Methylocystaceae were most abundant in the non-urban phyllosphere, whereas Hymenobacter and Sphingomonadaceae were dominating the urban ivy phyllosphere. The richness, diversity and composition of the communities showed greater variability in the urban than in the non-urban locations, where traffic-generated PM was lower. Interestingly, the relative abundances of eight of the ten most dominant taxa correlated well with leaf magnetism, be it positive or negative. The results of this study indicate that an urban environment can greatly affect the local phyllosphere community composition. Although other urban-related factors cannot be ruled out, the relative abundance of most of the dominant taxa was significantly correlated with exposure to traffic-generated PM.

Abstract: We present a computational model for simulating the dispersion of traffic emitted particulate matter inside a road tunnel, with an emphasis on the number concentration of ultrafine particles (UFP). The model primarily calculates the size distribution of the particle number concentration at each location inside the tunnel. The proposed model differs from existing models in the sense that it uses a continuous representation of the size distribution based upon the high-order finite element method and that it solves the governing equations using the state-of-the-art discontinuous Galerkin method. Next to the traditional transport processes, the model also implements the most important aerosol transformation processes such as coagulation, condensation and dry deposition. It is shown that based upon parametrisations found in literature, the process of condensation in a traffic tunnel cannot properly be modelled. Therefore, we present a correction factor that allows for a better parametrisation. The adequate performance of the model is demonstrated by both a verification study and a validation study. For the verification we show that the discretisation error converges consistently while for the validation we compare the modelled results with a suitable set of data from a UFP measurement campaign in a Taiwanese traffic tunnel. The model is shown to correctly simulate the observed behaviour and by applying a statistical model evaluation we demonstrate that the proposed model meets widely accepted air quality model acceptance criteria. (C) 2012 Elsevier Ltd. All rights reserved.