Improvement of source and wind field input of atmospheric dispersion model by assimilation of concentration measurements: Method and applications in idealized settings

AbstractThe problem of correcting the pollutant source emission rate and the wind velocity field inputs in a puff atmospheric dispersion model by data assimilation of concentration measurements has been considered. Variational approach to data assimilation has been used, in which the specified cost function is minimized with respect to source strength and/or wind field. The analyzed wind field satisfied the constraints derived from the conditions of mass conservation and linearized flow equations for perturbations from the first guess wind field. ‘Identical twin’ numerical experiments have been performed for the validation of the method. The first guess estimation errors of source emission rate and wind field were set to a factor of up to 10 and up to 6m/s respectively. The calculations results showed that in most studied cases an improvement of vector wind difference (VWD) error by about 0.7–1m/s could be achieved. The resulting normalized mean square error (NMSE) of concentration field was also reduced significantly

MODELLING THE CONCENTRATION FLUCTUATION AND INDIVIDUAL EXPOSURE IN COMPLEX URBAN ENVIRONMENTS

The concentrations 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. Moreover the computation of concentration fluctuations and individual exposure in case of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In order to predict or/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. In this study the whole effort is based on the ‘Mock Urban Setting Test – MUST’, an extensive field test carried out on a test site of the US Army in the Great Basin Desert in 2001 (Biltoft, 2001; Yee, 2004). The experimental data that was used for the model evaluation concerned the dispersion of a passive gas between street canyons which have been created by 120 standard size shipping containers. The computational simulations have been performed using the laboratory CFD code ADREA, which has been developed for simulating the dispersion and exposure of pollutants over complex geometries. The ADREA model is evaluated by comparing the model’s predictions with the observations utilizing statistical metrics and scatter plots. The present study has been performed in the frame of the Action COST 732 “Quality Assurance and Improvement of Micro-Scale Meteorological Models”

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%

Concentrations of VOCs and ozone in indoor environments: A case study in two Mediterranean cities during winter period

Building materials represent the largest surfaces indoors and are the major contributors of volatile organic compounds (VOCs) in the indoor environment. This study which is conducted in the frame of BUMA project (Prioritization of Building Materials Emissions), aims at assessing the human exposure to air hazards emitted by building materials. In this study, indoor and outdoor VOCs and ozone measurements from field campaigns in two Mediterranean cities (Nicosia and Athens in winter period) are presented and discussed. The field campaigns concern weekly measurements. The campaigns were conducted in four buildings in each city (1 Public building, 1 school and 2 houses) and concern weekly measurements. Passive samplers were used for collecting VOCs and ozone. Eight (8) hydrocarbons (benzene, toluene, ethylbenzene, m,p-xylene, a-pinene, o-xylene and d-limonene), five (5) carbonyl compounds (formaldehyde, acetaldehyde, proprionaldehyde, acetone and hexanaldehyde) and ozone have been measured. Additional air exchange measurements have been conducted using tracer gas techniques. Hazardous substances such as benzene, formaldehyde and acetaldehyde present indoor concentrations that range between 1.5-10.2, 5.8-43.2 and 4.5-15 μg/m3, respectively. VOC concentration data show a considerable variability due to the different indoor emission sources, ventilation rates and outdoor environment's influence. A significant contribution to indoor measured concentrations seems to come from the building materials. Ozone outdoor concentrations are reduced substantially inside, indicating relatively strong indoor ozone sinks

Modelling Exposure from Airborne Hazardous Short-Duration Releases in Urban Environments

When considering accidental or/and deliberate releases of airborne hazardous substances the release duration is often short and in most cases not precisely known. The downstream exposure in those cases is stochastic due to ambient turbulence and strongly dependent on the release duration. Depending on the adopted modelling approach, a relatively large number of dispersion simulations may be required to assess exposure and its statistical behaviour. The present study introduces a novel approach aiming to replace the large number of the abovementioned simulation scenarios by only one simulation of a corresponding continuous release scenario and to derive the exposure-related quantities for each finite-duration release scenario by simple relationships. The present analysis was concentrated on dosages and peak concentrations as the primary parameters of concern for human health. The experimental and theoretical analysis supports the hypothesis that the dosage statistics for short releases can be correlated with the corresponding continuous release concentration statistics. The analysis shows also that the peak concentration statistics for short-duration releases in terms of ensemble average and standard deviation are well correlated with the corresponding dosage statistics. However, for more reliable quantification of the associated correlation coefficients further experimental and theoretical research is needed. The probability/cumulative density function for dosage and peak concentration can be approximated by the beta function proposed in an earlier work by the authors for continuous releases

Modeling Short-Term Maximum Individual Exposure from Airborne Hazardous Releases in Urban Environments. Part I: Validation of a Deterministic Model with Field Experimental Data

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

Commuters’ Personal Exposure to Ambient and Indoor Ozone in Athens, Greece

This pilot study aimed to monitor the residential/office indoor, outdoor, and personal levels of ozone for people living, working, and commuting in Athens, Greece. Participants (16 persons) of this study worked at the same place. Passive sampling analysis results did not indicate any limit exceedance (Directive 2008/50/EC: 120 µg/m3, World Health Organization (WHO) Air Quality Guidelines 2005: 100 µg/m3). The highest “house-outdoor” concentration was noticed for participants living in the north suburbs of Athens, confirming the photochemical ozone formation at the northern parts of the basin during southwestern prevailing winds. The residential indoor to outdoor ratio (I/O) was found to be significantly lower than unity, underlying the outdoor originality of the pollutant. The highest “office-indoor” concentration was observed in a ground-level building, characterized by the extensive use of photocopy machines and printers. Personal ozone levels were positively correlated only with indoor-office concentrations. A clear correlation of personal ozone levels to the time spent by the individuals during moving/staying outdoors was observed. On the other hand, no correlation was observed when focusing only on commuting time, due to the fact that transit time includes both on-foot and in-vehicle time periods, therefore activities associated with increased exposure levels, but also with pollutants removal by recirculating air filtering systems, respectively

H13-85 PRESENTATION OF NEW LES CAPABILITY OF ADREA-HF CFD CODE

Abstract: The ADREA-HF is a general purpose Computational Fluid Dynamics (CFD) code, with extensive use in environmental applications. In the current work, the task of adding and testing the Large Eddy Simulation (LES) capability is presented. After simulating a fully developed channel flow, a simple street canyon geometry is examined. Flow field and Reynolds stresses' results are compared with experiment and other LES and Direct Numerical Simulations (DNS). The accuracy and efficiency of the modified code is presented along with comments about the applicability of LES in urban flows. Key words: CFD, Large Eddy Simulation, ADREA-HF, urban street canyon. INTRODUCTION Nowadays, CFD calculations like atmospheric dispersion modelling and urban flows become more demanding, as the computational power increases. New techniques, like the LES, previously used mainly for research, emerge as a promising alternative way of calculating atmospheric flow and pollutant dispersion. Compared to Reynolds Averaged Navier-Stokes (RANS) methodology, LES uses a natively transient approach, solves most of the turbulence, is capable of predicting the intermittent character of the flow and provides detailed information for the turbulence statistics, but computationally it is orders of magnitude more expensive and requires usually unavailable accuracy of boundary conditions data. Even if RANS and LES are fundamentally different, they end up in similar formulation of the main discretized equations, thus making it possible in most cases to use a pre-existing RANS code to develop a new LES one and having a single program for both techniques