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Even though emission inventories indicate that wood combustion is a major source of polycyclic aromatic hydrocarbons (PAHs), estimating its impacts on PAH concentration in ambient air remains challenging. In this study the effect of local small-scale wood combustion on the benzo[a]pyrene (BaP) concentrations in ambient air in the Helsinki metropolitan area in Finland is evaluated, using ambient air measurements, emission estimates, and dispersion modeling. The measurements were conducted at 12 different locations during the period from 2007 to 2015. The spatial distributions of annual average BaP concentrations originating from wood combustion were predicted for four of those years: 2008, 2011, 2013, and 2014. According to both the measurements and the dispersion modeling, the European Union target value for the annual average BaP concentrations (1 ng m−3) was clearly exceeded in certain suburban detached-house areas. However, in most of the other urban areas, including the center of Helsinki, the concentrations were below the target value. The measured BaP concentrations highly correlated with the measured levoglucosan concentrations in the suburban detached-house areas. In street canyons, the measured concentrations of BaP were at the same level as those in the urban background, clearly lower than those in suburban detached-house areas. The predicted annual average concentrations matched with the measured concentrations fairly well. Both the measurements and the modeling clearly indicated that wood combustion was the main local source of ambient air BaP in the Helsinki metropolitan area.

Even though emission inventories indicate that wood combustion is a major source of polycyclic aromatic hydrocarbons (PAHs), estimating its impacts on PAH concentration in ambient air remains challenging. In this study the effect of local small-scale wood combustion on the benzo[a] pyrene (BaP) concentrations in ambient air in the Helsinki metropolitan area in Finland is evaluated, using ambient air measurements, emission estimates, and dispersion modeling. The measurements were conducted at 12 different locations during the period from 2007 to 2015. The spatial distributions of annual average BaP concentrations originating from wood combustion were predicted for four of those years: 2008, 2011, 2013, and 2014. According to both the measurements and the dispersion modeling, the European Union target value for the annual average BaP concentrations (1 ngm(-3) ) was clearly exceeded in certain suburban detached-house areas. However, in most of the other urban areas, including the center of Helsinki, the concentrations were below the target value. The measured BaP concentrations highly correlated with the measured levoglucosan concentrations in the suburban detached-house areas. In street canyons, the measured concentrations of BaP were at the same level as those in the urban background, clearly lower than those in suburban detached-house areas. The predicted annual average concentrations matched with the measured concentrations fairly well. Both the measurements and the modeling clearly indicated that wood combustion was the main local source of ambient air BaP in the Helsinki metropolitan area. ; Peer reviewed

In diesem Beitrag wird ein Einblick in die aktuelle Veranstaltung "Ausbreitungsmodellierung von Stoffen in der Atmosphäre" des Masterkurses Umweltingenieurwesen an der Ruhr-Universität Bochum gegeben. Neben einer kurzen Einführung in die didaktische Konzeption werden die verschiedenen Kursinhalte und die Durchführung der Veranstaltung beschrieben.

FRONT MATTER -- Contents -- EXECUTIVE SUMMARY -- 1 INTRODUCTION -- 2 USER NEEDS -- 3 OBSERVATIONAL CAPABILITIES AND NEEDS -- 4 DISPERSION MODELING: APPLICATION TO C/B/N RELEASES -- REFERENCES -- ACRONYMS AND ABBREVIATIONS -- COMMITTEE BIOGRAPHIES -- APPENDIXES -- A Workshop Agenda and Participant List, 65 -- B Overview of Atmospheric Transport and Dispersion Modeling, 69 -- C Meteorological Observing Systems for Tracking and Modeling C/B/N Plumes, 72 -- D Scientific and Technical Information Needs of Emergency First Responders, 78 -- E Ensemble Simulations with Coupled Atmospheric Dynamic and Dispersion Models: Illustrating Uncertainties in Dosage Simulations, 80 -- F Modeling Studies of the Dispersion of Smoke Plumes from the World Trade Center Fires, 85 -- G Use of Atmospheric Models in Response to the Chernobyl Disaster, 87 -- H Preparatory Exercises at the Salt Lake City Olympics, 89 -- I URBAN 2000 Overview, 91 -- COLOR PLATES.

Summarization: Depleted uranium is a low-cost radioactive material that, in addition to other applications, is used by the military in kinetic energy weapons against armored vehicles. During the Gulf and Balkan conflicts concern has been raised about the potential health hazards arising from the toxic and radioactive material released. The aerosol produced during impact and combustion of depleted uranium munitions can potentially contaminate wide areas around the impact sites or can be inhaled by civilians and military personnel. Attempts to estimate the extent and magnitude of the dispersion were until now performed by complex modeling tools employing unclear assumptions and input parameters of high uncertainty. An analytical puff model accommodating diffusion with simultaneous deposition is developed, which can provide a reasonable estimation of the dispersion of the released depleted uranium aerosol. Furthermore, the period of the exposure for a given point downwind from the release can be estimated (as opposed to when using a plume model). The main result is that the depleted uranium mass is deposited very close to the release point. The deposition flux at a couple of kilometers from the release point is more than one order of magnitude lower than the one a few meters near the release point. The effects due to uncertainties in the key input variables are addressed. The most influential parameters are found to be atmospheric stability, height of release, and wind speed, whereas aerosol size distribution is less significant. The output from the analytical model developed was tested against the numerical model RPM-AERO. Results display satisfactory agreement between the two models. ; Παρουσιάστηκε στο: Health Physics

The results of four gas tracer experiments of atmospheric dispersion on a regional scale are used for the benchmarking of two atmospheric dispersion modeling codes, MINERVE-SPRAY (CEA), and NOSTRADAMUS (IBRAE). The main topic of this comparison is to estimate the Lagrangian code capability to predict the radionuclide atmospheric transfer on a large field, in the case of risk assessment of nuclear power plant for example. For the four experiments, the results of calculations show a rather good agreement between the two codes, and the order of magnitude of the concentrations measured on the soil is predicted. Simulation is best for sampling points located ten kilometers from the source, while we note a divergence for more distant points results (difference in concentrations by a factor 2 to 5). This divergence may be explained by the fact that, for these four experiments, only one weather station (near the point source) was used on a field of 10 000 km2, generating the simulation of a uniform wind field throughout the calculation domain.

Recent events have increased awareness of the risk posed by terrorist attacks. Bacillus anthracis has resurfaced in the 21st century as a deadly agent of bioterrorism because of its potential for causing massive civilian casualties. This analysis presents the results of a computer simulation of the dispersion of anthrax spores in a typical 50‐story, high‐rise building after an intentional release during a bioterrorist incident. The model simulates aerosol dispersion in the case of intensive, small‐scale convection, which equalizes the concentration of anthrax spores over the building volume. The model can be used to predict the time interval required for spore dispersion throughout a building after a terrorist attack in a high‐rise building. The analysis reveals that an aerosol release of even a relatively small volume of anthrax spores during a terrorist incident has the potential to quickly distribute concentrations that are infectious throughout the building.

Publisher's version (útgefin grein) ; Volcanic ash in the atmosphere is a hazard to aviation. To predict which areas of airspace are most likely to be affected by the presence of ash, Volcanic Ash Advisory Centers (VAACs) use observations and atmospheric dispersion models. These models are initialized with, among other parameters, a mass eruption rate (MER), which quantifies the emission rate into the atmosphere at the source. This influences the predicted spatial–temporal evolution and concentration of the ash cloud. Different models are available to estimate MER from the volcanic plume height and some models also include the weather conditions (e.g., wind speed). The REFIR software tool uses time-series of plume height estimated from observations and weather data to provide estimates of MER through time. Here we present an updated version of REFIR that can now be used also to calculate MER for past eruptions and produce output parameters in a format suitable for use with the NAME dispersion model (UK Met Office—London VAAC). We also investigate how uncertainty in input parameters is propagated through to dispersion model output. Our results show that a +/−1 km uncertainty on a 6 km high plume can result in the affected area ranging by a factor of three between the minimum and maximum estimates. Additionally, we show that using wind-affected plume models results in affected areas that are five times larger than using no-wind-affected models. This demonstrates the sensitivity of MER to the type of plume model chosen (no-wind- vs. wind-affected). ; We thank Larry Mastin, Arnau Folch, and an anonymous reviewer for their comments and suggestions that contributed to the improvement of the manuscript, and Lynn Russell for the editorial handling. We also thank Dr. Susan Loughlin (British Geological Survey), Dr. Susan Leadbetter (UK Met Office) and Dr. Claire Witham (UK Met Office) for their valuable suggestions. Fabio Dioguardi and John A. Stevenson have been supported from UK National Capability funding (BGS Innovation Flexible Fund). Fabio Dioguardi has also been supported by the European Union's Horizon 2020 project EUROVOLC (grant agreement no 731070). Tobias D?rig's work is supported by the Icelandic Research Fund (Rann?s) grant no. 206527-051. This work is published with permission of the Executive Director of British Geological Survey (UKRI) ; Peer Reviewed

Abstract. In this communication, I improve the detection and modeling of the over-dispersion of winter storm occurrence. For this purpose, the generalized Poisson distribution and the Bayesian information criterion are introduced; the latter is used for statistical model selection. Moreover, I replace the frequently used dispersion statistics by an over-dispersion parameter which does not depend on the considered return period of storm events. These models and methods are applied in order to properly detect the over-dispersion in winter storm data for Germany, carrying out a joint estimation of the distribution models for different samples.