Modelling of Pollutant Transport in the Atmosphere - MANHAZ

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Direct Numerical Simulation DNS. DNS methods symbolize full and untruncated solutions of the Navier-Stokes equations including particle tracking on all scales. As the smallest scale of relevance for atmospheric dispersion is the Kolmogorov microscale (of the order of ~1 mm) it is evident that DNS methods are not relevant for atmospheric dispersion, where scales are ranging from meters to thousand of km, cf. Figure1. Again, neither DNS nor LES type models are suited for direct practical real-time air pollution control or emergency assessments, but should rather be considered as research tools. On-line Numerical Weather Prediction winds for dispersion Numerical weather forecast data are today available to dispersion modeller’s for download from the world’s national and international weather forecast centres. Limited Area Models (LAM) with an internal grid resolution down to ~10 x 10 km grid resolution, and with internal time steps of the order of minutes, produce regional scale (e.g. Europe) forecasts with a forecast length up to + 36 or + 48 hours. As an example the joint Scandinavian- European corporation project HIRLAM (for HIgh Resolution Limited Area Model) weather prediction code operates at several European national Met offices. HIRLAM is a complete 3-D regional atmospheric forecasting system. Within a vertical resolved grid containing some thirty levels, and running around the clock in a 6 hour updated data-assimilation cycle, HIRLAM produces wind, temperature, humidity and precipitation + 48 hours ahead. Numerical weather forecasts of local winds and stability are nowadays online available in Europe for use with local scale atmospheric dispersion forecasts. For instance are HIRLAM produced local wind and precipitation forecasts today operationally accessible for local scale dispersion calculations within two European Emergency management decision support systems, RODOS and ARGOS (Mikkelsen, 2000). 30
Atmospheric dispersion module for nuclear releases Prediction and assessment of the atmospheric transport of radionuclides released from a nuclear accident requires many different disciplines, including plume rise, windborne transport and turbulent mixing, irradiation from puffs and plumes, and deposition (both wet and dry), see Figure 5. Figure 5 In case of a nuclear release is the actual weather (real-time) and associated atmospheric dispersion of uttermost importance for actual transfer of radionuclides to the environment. Many disciplines are involved (From: European Commission - Safeguarding Europe's Citizens). We end this Chapter with a practical Example of a contemporary Nested Atmospheric dispersion Module nowadays under development and dissemination for Practical Emergency Preparedness in Europe. For a review of the corresponding American approach see e.g. Kramer and Porch( 1990). The Met-RODOS Atmospheric Dispersion Module for Real-time Decision Support In Europe, an on-line atmospheric dispersion modelling system called Met- RODOS has recently been developed and serves now as central part of the joint European decision support system for nuclear emergencies called RODOS. [Ehrhardt et al., 1997]. The Met-RODOS module [Mikkelsen, 2000] provides the decision support system with an 31
Page 1 and 2: MANHAZ position paper on: Modelling
Page 3 and 4: Troposphere. Trapped between the st
Page 5 and 6: The importance of the local wind fi
Page 7 and 8: Figure 2. Typical vertical wind spe
Page 9 and 10: Notice that this source of turbulen
Page 11 and 12: dient winds can approximate the reg
Page 13 and 14: y Russian and British researchers t
Page 15 and 16: σ () t = 2K t + σ () 0 2 2 z z z
Page 17 and 18: Figure 3 Pasquill stability classif
Page 19 and 20: Monin-Obukhov similarity scaling (z
Page 21 and 22: With Richardson's diffusivity KDN i
Page 23 and 24: The corresponding predicted puff gr
Page 25 and 26: The cyclic variation of the stabili
Page 27 and 28: Dispersion modelling has also high
Page 29: structure of the diffusion. In prin
Page 33 and 34: LSP is a local scale pre-processing
Page 35 and 36: It consists of nested modules, whic
Page 37 and 38: land uses the nearest land-based Me
Page 39 and 40: Another example, showing the effect
Page 41 and 42: Density calculations. Numerical dis
Page 43 and 44: cloud is expected to cover a larger
Page 45 and 46: Auxiliary parameters like concentra
Page 47 and 48: Variable atmospheric wind condition
Page 49 and 50: Busch, N.E., On the Mechanics of At
Page 51 and 52: Monin A.S. (1959) Smoke propagation
Page 53 and 54: Goldwire, H. C., McRae, T. G., John
Page 55: Table of Content Modelling of Pollu

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