Denise Hertwig

Large Scale Urban Simulations with FCT

Airborne contaminant transport in cities presents challenging new requirements for CFD. The unsteady flow physics is complicated by very complex geometry, multi-phase particle and droplet effects, radiation, latent and sensible heating effects, and buoyancy effects. Turbulence is one of the most important of these phenomena and yet the overall problem is sufficiently difficult that the turbulence must be included efficiently with an absolute minimum of extra memory and computing time. This paper describes the Monotone Integrated Large Eddy Simulation (MILES) methodology used in NRL’s FAST3D-CT simulation model for urban contaminant transport (CT) (see Boris in Comput. Sci. Eng. 4:22–32, 2002 and references therein). We also describe important extensions of the underlying Flux-Corrected Transport (FCT) convection algorithms to further reduce numerical dissipation in narrow channels (streets).

Measurements and Computations of Flow in an Urban Street System

We present results from laboratory and computational experiments on the turbulent flow over an array of rectangular blocks modelling a typical, asymmetric urban canopy at various orientations to the approach flow. The work forms part of a larger study on dispersion within such arrays (project DIPLOS) and concentrates on the nature of the mean flow and turbulence fields within the canopy region, recognising that unless the flow field is adequately represented in computational models there is no reason to expect realistic simulations of the nature of the dispersion of pollutants emitted within the canopy. Comparisons between the experimental data and those obtained from both large-eddy simulation (LES) and direct numerical simulation (DNS) are shown and it is concluded that careful use of LES can produce generally excellent agreement with laboratory and DNS results, lending further confidence in the use of LES for such situations. Various crucial issues are discussed and advice offered to both experimentalists and those seeking to compute canopy flows with turbulence resolving models.

Developing a research strategy to better understand, observe and simulate urban atmospheric processes at kilometre to sub-kilometre scales

A Met Office/Natural Environment Research Council Joint Weather and Climate Research Programme workshop brought together 50 key international scientists from the UK and international community to formulate the key requirements for an Urban Meteorological Research strategy. The workshop was jointly organised by University of Reading and the Met Office.

Development and demonstration of a Lagrangian dispersion modeling system for real‐time prediction of smoke haze pollution from biomass burning in Southeast Asia

Abstract Transboundary smoke haze caused by biomass burning frequently causes extreme air pollution episodes in maritime and continental Southeast Asia. With millions of people being affected by this type of pollution every year, the task to introduce smoke haze related air quality forecasts is urgent. We investigate three severe haze episodes: June 2013 in Maritime SE Asia, induced by fires in central Sumatra, and March/April 2013 and 2014 on mainland SE Asia. Based on comparisons with surface measurements of PM10 we demonstrate that the combination of the Lagrangian dispersion model NAME with emissions derived from satellite‐based active‐fire detection provides reliable forecasts for the region. Contrasting two fire emission inventories shows that using algorithms to account for fire pixel obscuration by cloud or haze better captures the temporal variations and observed persistence of local pollution levels. Including up‐to‐date representations of fuel types in the area and using better conversion and emission factors is found to more accurately represent local concentration magnitudes, particularly for peat fires. With both emission inventories the overall spatial and temporal evolution of the haze events is captured qualitatively, with some error attributed to the resolution of the meteorological data driving the dispersion process. In order to arrive at a quantitative agreement with local PM10 levels, the simulation results need to be scaled. Considering the requirements of operational forecasts, we introduce a real‐time bias correction technique to the modeling system to address systematic and random modeling errors, which successfully improves the results in terms of reduced normalized mean biases and fractional gross errors.

A statistical model for the prediction of wind-speed probabilities in the atmospheric surface layer

Wind fields in the atmospheric surface layer (ASL) are highly three-dimensional and characterized by strong spatial and temporal variability. For various applications such as wind-comfort assessments and structural design, an understanding of potentially hazardous wind extremes is important. Statistical models are designed to facilitate conclusions about the occurrence probability of wind speeds based on the knowledge of low-order flow statistics. Being particularly interested in the upper tail regions we show that the statistical behaviour of near-surface wind speeds is adequately represented by the Beta distribution. By using the properties of the Beta probability density function in combination with a model for estimating extreme values based on readily available turbulence statistics, it is demonstrated that this novel modelling approach reliably predicts the upper margins of encountered wind speeds. The model’s basic parameter is derived from three substantially different calibrating datasets of flow in the ASL originating from boundary-layer wind-tunnel measurements and direct numerical simulation. Evaluating the model based on independent field observations of near-surface wind speeds shows a high level of agreement between the statistically modelled horizontal wind speeds and measurements. The results show that, based on knowledge of only a few simple flow statistics (mean wind speed, wind-speed fluctuations and integral time scales), the occurrence probability of velocity magnitudes at arbitrary flow locations in the ASL can be estimated with a high degree of confidence.

Large Eddy Simulation of Accidental Releases

First responders need a more or less instant estimate of danger zones resulting from accidentally released hazardous materials in order to take immediate action, to coordinate rescue teams and to protect human population and critical infrastructure. To fulfill the need for a sufficient dispersion modeling accuracy while maintaining efficient access to reliable results in a first responders environment, systematic high resolution pre-accidental LES modeling can be combined with ’physical data reduction’ in an emergency assessment tool. A typical example of such an approach adjusted to the geometry of the Hamburg inner city area will be presented. It gives a glimpse into the application of LES-modeling for real-world problems.

Evaluation of fast atmospheric dispersion models in a regular street network

The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where near real-time hazard predictions are needed. This challenge is aggravated in cities, where models need to have some degree of building-awareness, alongside the ability to capture effects of dominant urban flow processes. We use a combination of high-resolution large-eddy simulation (LES) and wind-tunnel data of flow and dispersion in an idealised, equal-height urban canopy to highlight important dispersion processes and evaluate how these are reproduced by representatives of the most prevalent modelling approaches: (1) a Gaussian plume model, (2) a Lagrangian stochastic model and (3) street-network dispersion models. Concentration data from the LES, validated against the wind-tunnel data, were averaged over the volumes of streets in order to provide a high-fidelity reference suitable for evaluating the different models on the same footing. For the particular combination of forcing wind direction and source location studied here, the strongest deviations from the LES reference were associated with mean over-predictions of concentrations by approximately a factor of 2 and with a relative scatter larger than a factor of 4 of the mean, corresponding to cases where the mean plume centreline also deviated significantly from the LES. This was linked to low accuracy of the underlying flow models/parameters that resulted in a misrepresentation of pollutant channelling along streets and of the uneven plume branching observed in intersections. The agreement of model predictions with the LES (which explicitly resolves the turbulent flow and dispersion processes) greatly improved by increasing the accuracy of building-induced modifications of the driving flow field. When provided with a limited set of representative velocity parameters, the comparatively simple street-network models performed equally well or better compared to the Lagrangian model run on full 3D wind fields. The study showed that street-network models capture the dominant building-induced dispersion processes in the canopy layer through parametrisations of horizontal advection and vertical exchange processes at scales of practical interest. At the same time, computational costs and computing times associated with the network approach are ideally suited for emergency-response applications.

Modelling Short-Term Maximum Individual Exposure from Airborne Hazardous Releases in Urban Environments. Part ΙI: Validation of a Deterministic Model with Wind Tunnel Experimental Data

The capability to predict short-term maximum individual exposure is very important for several applications including, for example, deliberate/accidental release of hazardous substances, odour fluctuations or material flammability level exceedance. Recently, authors have proposed a simple approach relating maximum individual exposure to parameters such as the fluctuation intensity and the concentration integral time scale. In the first part of this study (Part I), the methodology was validated against field measurements, which are governed by the natural variability of atmospheric boundary conditions. In Part II of this study, an in-depth validation of the approach is performed using reference data recorded under truly stationary and well documented flow conditions. For this reason, a boundary-layer wind-tunnel experiment was used. The experimental dataset includes 196 time-resolved concentration measurements which detect the dispersion from a continuous point source within an urban model of semi-idealized complexity. The data analysis allowed the improvement of an important model parameter. The model performed very well in predicting the maximum individual exposure, presenting a factor of two of observations equal to 95%. For large time intervals, an exponential correction term has been introduced in the model based on the experimental observations. The new model is capable of predicting all time intervals giving an overall factor of two of observations equal to 100%.

Trends in the Field of Quality Assurance of Urban Flow and Dispersion Models

Caused by synoptic changes and the diurnal cycle, the atmospheric boundary layer is never steady state. The unsteadiness is especially pronounced within and above the urban canopy layer. In former times, it was not possible to take the natural variability of the urban atmosphere properly into account, due to a lack of both computer power for models of adequate sophistication and sufficiently matured measurement techniques. Instead of this, quasi-steady situations were assumed, despite the fact that in reality they do not exist. The situation has improved now. After a brief description of the numerical tools which are presently available, their potential to simulate urban flow and dispersion episodes is assessed. The importance of validating these tools is stressed, and the question of how to obtain reliable validation data is discussed. Using combinations of field and laboratory data for the validation procedure is recommended. Finally, at the concrete example of puff dispersion within the urban canopy layer, it is demonstrated how such data sets can be generated and actually applied.