Abstract

The release of airborne hazardous substances in the atmosphere has a direct effect on human health as, during the inhalation, an amount of concentration is inserted through the respiratory system into the human body, which can cause serious or even irreparable damage in health. One of the key problems in such cases is the prediction of the maximum individual exposure. Current state of the art methods, which are based on the concentration cumulative distribution function and require the knowledge of the concentration variance and the intermittency factor, have limitations. Recently, authors proposed a deterministic approach relating maximum individual exposure to parameters such as the fluctuation intensity and the concentration integral time scale. The purpose of the first part of this study is to validate the deterministic approach with the extensive dataset of the MUST (Mock Urban Setting Test) field experiment. This dataset includes 81 trials, which practically cover various atmospheric conditions and stability classes and contains in total 4004 non-zero concentration sensor data with time resolutions of 0.01–0.02 s. The results strengthen the usefulness of the deterministic model in predicting short-term maximum individual exposure. Another important output is the estimation of the methodology uncertainty involved.

Abstract

A key issue, in order to be able to cope with deliberate or accidental atmospheric releases of hazardous substances, is the ability to reliably predict the individual exposure downstream the source. In many situations, the release time and/or the health relevant exposure time is short compared to mean concentration time scales. In such a case, a significant scatter of exposure levels is expected due to the stochastic nature of turbulence. The problem becomes even more complex when dispersion occurs over urban environments. The present work is the first attempt to approximate on generic terms, the statistical behavior of the abovementioned variability with a beta distribution probability density function (beta-pdf) which has proved to be quite successful. The important issue of the extreme concentration value in beta-pdf seems to be properly addressed by the [5] correlation in which global values of its associated constants are proposed. Two substantially different datasets, the wind tunnel Michelstadt experiment and the field Mock Urban Setting Trial (MUST) experiment gave clear support to the proposed novel theory and its hypotheses. In addition, the present work can be considered as basis for further investigation and model refinements.

Abstract

Within the framework of the EPHECT project (Emissions, exposure patterns and health effects of consumer products in the EU), irritative and respiratory health effects were assessed in relation to acute and long-term exposure to key and emerging indoor air pollutants emitted during household use of selected consumer products. In this context, inhalation exposure assessment was carried out for six selected ‘target’ compounds (acrolein, formaldehyde, benzene, naphthalene, d-limonene and α-pinene). This paper presents the methodology and the outcomes from the micro-environmental modelling of the ‘target’ pollutants following single or multiple use of selected consumer products and the subsequent exposure assessment. The results indicate that emissions from consumer products of benzene and α-pinene were not considered to contribute significantly to the EU indoor background levels, in contrast to some cases of formaldehyde and d-limonene emissions in Eastern Europe (mainly from cleaning products). The group of housekeepers in East Europe appears to experience the highest exposures to acrolein, formaldehyde and benzene, followed by the group of the retired people in North, who experiences the highest exposures to naphthalene and α-pinene. High exposure may be attributed to the scenarios developed within this project, which follow a ‘most-representative worst-case scenario’ strategy for exposure and health risk assessment. Despite the above limitations, this is the first comprehensive study that provides exposure estimates for 8 population groups across Europe exposed to 6 priority pollutants, as a result of the use of 15 consumer product classes in households, while accounting for regional differences in uses, use scenarios and ventilation conditions of each region.

Abstract

In a previous study, new approaches have been introduced in the CFD-RANS modelling, according to which the concentration time scales are estimated as a function not only of the flow turbulence time scales but also of the pollutant travel times. The new approaches have been implemented for the calculation of the concentration fluctuation dissipation time scale and the maximum individual exposure at short time intervals using the k-ζ model for turbulence parameterisation. The purpose of this study is to implement and validate again the new methodology using the widely known standard k-ε model. The validation is performed using two selected trials of the MUST experiment under neutral conditions. Special emphasis is given on the selection of the constant value of the concentration fluctuation dissipation time scale when the k-ε model is used. Also, an intercomparison of the results between the two turbulence models is performed with a view to identifying model strengths and limitations.

Abstract

Local grid refinement aims to optimise the relationship between accuracy of the results and number of grid nodes. In the context of the finite volume method no single local refinement criterion has been globally established as optimum for the selection of the control volumes to subdivide, since it is not easy to associate the discretisation error with an easily computable quantity in each control volume. Often the grid refinement criterion is based on an estimate of the truncation error in each control volume, because the truncation error is a natural measure of the discrepancy between the algebraic finite-volume equations and the original differential equations. However, it is not a straightforward task to associate the truncation error with the optimum grid density because of the complexity of the relationship between truncation and discretisation errors. In the present work several criteria based on a truncation error estimate are tested and compared on a regularised lid-driven cavity case at various Reynolds numbers. It is shown that criteria where the truncation error is weighted by the volume of the grid cells perform better than using just the truncation error as the criterion. Also it is observed that the efficiency of local refinement increases with the Reynolds number. The truncation error is estimated by restricting the solution to a coarser grid and applying the coarse grid discrete operator. The complication that high truncation error develops at grid level interfaces is also investigated and several treatments are tested.

Abstract

Urban flow fields computed by two steady Computational Fluid Dynamics models based on the Reynolds-averaged Navier Stokes equations (CFD-RANS) are compared to validation data measured in a boundary-layer wind-tunnel experiment. The numerical simulations were performed with the research code ADREA and the commercial code STAR-CD. Turbulent flow within and above a 1:225-scale wind-tunnel model representing a novel semi-idealized urban complexity represents the test case. In a systematic study the quality of the numerical predictions of mean wind fields is evaluated with a focus on the identification of model strengths and limitations. State-of-the-art validation metrics for numerical models were used to quantify the agreement between the data sets. Based on detailed spatial identification of locations of good or bad comparison the study showed how unsteady flow effects within street canyons are a major cause for discrepancies between numerical and experimental results.

Abstract

One of the key problems in coping with deliberate or accidental atmospheric releases, which in many cases are short or/and result in high concentrations, is the ability to reliably predict the individual exposure during the event. Furthermore, for consequence assessment and countermeasures application, it is more realistic to rely on the maximum expected dosage rather than on the actual dosage. Recently, Bartzis et al. (2008) have introduced an approach relating maximum dosage to parameters such as concentration variance and turbulence integral time scale. The need for an estimation of these parameters poses new challenges to CFD models. In the CFD RANS model ADREA, new approaches have been implemented recently, where the parameterization of the dispersion of a pollutant emitted from a point source depends not only on the parameters of turbulence, but also on the pollutant travel times. In this study the new methodology is tested against MUST and FLADIS field experimental data, which consist of high resolution concentration time series enabling the production of short term dosage data. The present comparisons further strengthen the evidence that the applied methodology is capable of dealing properly with complex transient dispersion phenomena.

Abstract

The aim of this paper is to describe the use of a general methodology tailored to the evaluation of micro-scale meteorological models applied to flow and dispersion simulations in urban areas. This methodology, developed within COST 732, has been tested through a large modelling exercise involving many groups across Europe. The major test case used is the Mock Urban Setting Test (MUST) experiment representing an idealised urban area. It is emphasised that a full model evaluation is problem-dependent and requires several activities including a statistical validation that requires a careful choice of the metrics for the comparison with measurements.

Abstract

In this work a new approach for CFD RANS modelling of dispersion of airborne point source releases is presented. The key feature of this approach is the model capability to predict concentration time scales that are functions not only of the flow turbulence scales but also of the pollutant travel time. This approach has been implemented for the calculation of the concentration fluctuation dissipation time scale and the maximum individual exposure at short time intervals. For the estimation of travel time in the Eulerian grid the new ‘radioactive tracer method’ is introduced. The new approaches were incorporated in the CFD code ADREA. The capabilities of the new approaches are validated against the Mock Urban Setting Trial field experiment data under neutral conditions. The comparisons of model and observations gave quite satisfactory results.

The concentration fluctuations of a dispersing hazardous gaseous pollutant in the atmospheric boundary layer, and the hazard associated with short-term concentration levels, demonstrate the necessity of estimating the magnitude of these fluctuations using predicting models. To predict and estimate the maximum expected dosage and the exposure time within which the dosage exceeds certain health limits, the knowledge of the behaviour of concentration fluctuations at the point under consideration is needed. The whole effort is based on the field experiment MUST (Biltoft, 2001) and the computational simulations have been performed with the CFD code ADREA.