SoundPLAN AirPLANs. Introduction to air pollution modeling with SoundPLAN Air Pollution Modules

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1 SoundPLAN SoundPLAN AirPLANs Introduction to air pollution modeling with SoundPLAN Air Pollution Modules Development Headquarters Braunstein + Berndt GmbH Etzwiesenberg Backnang GERMANY Tel: Fax: International Headquarters SoundPLAN International LLC 80 E Aspley Lane Shelton, WA USA Tel: Fax: Your local distributor:

2 2 Comments Results of air pollution calculations use a lot of disk space, making it impossible to create a small demo project with sensible in- and output for all the Air- PLAN models and modules. Users want to save time, too, so they will also simplify project data. Our demo shows what SoundPLAN does, how to use it, and how to correctly simplify projects. Demo projects are stored on our FTP server with slides and a short project description and a sum- mary of the results. Download projects and analyze how we have accomplished different tasks. Open SoundPLAN in the demo mode in order to have all air pollution modules available. In this mode you can do everything except store files. For more extensive investigations, order a temporary trial license from your local distributor. Distributor information is found at Rough Estimation or Detailed Analysis? Remember the three levels of investigation when you begin modeling: Prediction Don t be fooled by the illusion that air pollution concentrations can be exactly foreseen if you were to buy the right calculation model. Such a model would be too complex to even start from a PC! You will discover that it is nearly impossible to get the complete data needed for a good prognosis. You must create scenarios based on a few estimations instead of the many local measurements actually needed for precise work. This makes sense when you consider that forecasting air pollution concentrations can t be easier than forecasting weather because air pollution dispersion depends, in part, on weather conditions. Detailed analysis (we call it, fine screening ) allows you to simplify a model as much as needed. However, all that is gained from a simplified scenario is a good estimation of concentrations. How accurate can a detailed analysis be? You have to combine complex wind fields and dispersion conditions with a reliable emission scenario. What if the scenario doesn t work? Is there a simpler way to get reliable results? Of course! Rough estimation! Rough estimation (or, rough screening ) seems a simple task to beginners who have unreliable results, but this is not true! Experienced users carefully refine their tasks and choose rough estimation methods to save calculation time and win reliability and accuracy. They simplify models in ways that guarantee moderate, but secure overestimations. Using a rough screening model correctly, is simply not as easy as it seems! Thoughtfully operating outside the borders of reality requires a lot of skill to read reliable information from the results. Will limit values be exceeded? is a difficult question to answer, even using a fine screening model for detailed analysis. The answer yes or no requires evaluating the probability of error. This value can be estimated for measurement based validation calculations, but not for estimations based on freely defined scenarios. Can exceeded limits be excluded? is easily answered. A rough estimation is needed for a definitive no answer. The answer yes is based on a specific overestimation, so it is reliable. No is not reliable. It requires either an alternate plan or refinement of input data and finer screening.

3 Rough screening: Gauss (TA Luft 86) 3 GAUSS (TA Luft 86) (German national standard TA Luft ) Gauss was part of the official German standard "TA Luft 86" which was released to estimate the impact of new industrial air pollution sources, especially high emitting point sources like smoke stacks. It is a simplified version of the Gauss model defined in the VDI code The validation is associated to the evaluation of the VDI standard. It has a tendency to overestimate close to the source. Gauss models calculate very quickly. That means they can, and should, handle wind statistics with a very high resolution. They calculate a plume with a statistical pollutant distribution for each wind flow situation before evaluating statistics like mean, max and percentiles. The German model is not very sophisticated, but it brings solid results at least for comparable climate zones. We suggest looking for test data to compare if it fits your regional conditions and requirements. Because Gauss models are statistical models, use them only to analyze representative time periods. Don t use them for single case interpretations. Rough screening: Austal2000 AUSTAL2000 (German standard TA Luft since 2002) In 2002, TA Luft 02, which favors a diagnostic wind field and a Lagrange model to calculate the air pollution dispersion, replaced TA Luft 86. The reference model AUS- TAL2000 ( Dr. Janicke, Dunum, Germany) was developed for the German Environmental Agency. AUSTAL2000 has three advantages: It calculates a wind field which can regard terrain up to an inclination of 20% It has the reputation of the German government It is freeware; you pay only for the SoundPLAN interface. Austal2000 is very rudimentary, based on ASCII-input-text files and ASCII-output-text files. The SoundPLAN interface allows you to work in a comfortable program environment. You can apply your experience with the SoundPLAN Libraries, Geodatabase, Calculation Kernel and Graphics, plus you have full SoundPLAN support for the interface. Working with freeware does have some disadvantages: There is no international support for the original AUS- TAL2000 calculation kernel. SoundPLAN supports you as much as possible, but as we are not the authors of AUSTAL2000, our help is limited to our interface. You have no claim on reparations if AUSTAL2000 does not work or produces implausible results. The results are limited to the German/European requirements. If your national standards are more restrictive or require additional statistics, Austal2000 isn t suitable.

4 4 Fine Screening: MISKAM When we talk about fine screening, we talk first about calculating wind fields which can include turbulent effects between buildings. Then we talk about the spreading based on these precalculated wind fields. That means we need three dimensional grids with high resolution in x, y, AND z directions, which are calculated from the ground to a height far above the rooftops. MISKAM and AUSTAL2000 have different wind field models and also different pollution dispersion equations and are therefore used for different prognosis. MISKAM ( Dr. Eichhorn, University of Mainz, Germany) is a fine screening model with a respected international reputation. The model was carefully verified and validated while revising the code. The test calculations are mainly oriented to the guidelines of the VDI-Code 3783/9, Environmental meteorology - Prognostic microscale wind field models - Evaluation for flow around buildings and obstacles. Prognostic wind fields solve the physical equations describing the turbulent wind flow instead of matching physics with empirical assumptions as do the diagnostic models. This precision consumes a lot of time! Most highly developed CFD-programs are too oversized for a common planning job. They require a lot of input not available for an environmental impact study, because they are made for research or product development. To find the best compromise between the quality of prognosis of a CFD program and the time budget of a common planning job, MISKAM sets strict boundaries for its application scope: The turbulences caused by obstacles should be so dominant that thermal and terrain effects can be ignored. MISKAM does not regard terrain and is best used with neutral atmospheric stability. Calculating in stable conditions is possible, but requires much more calculation time. Unstable conditions are automatically set to neutral stability. If your investigation area allows these restrictions, MISKAM is one of the best models you can use! If you are not a meteorological expert, MISKAM's scope of application should be restricted to inner city simulations like street canyons, parking lots or situations where pollution sources are located close to the recipients and where local changes of wind speed and turbulence have to be regarded in a very high resolution. MISKAM is used for hot spots, not for entire cities! MISKAM allows simplifications: It is not necessary to calculate with high resolved wind statistics, because the building structures cause canalization effects. Also, it is not sensible to calculate with annual meteorological time rows to correlate emissions and meteorology, because all the single flow situations have to be calculated and stored. We found different approaches get an acceptable compromise. Never save time by exceeding the parameters of the model. Generate a sensible inflow by regarding a huge belt of buildings around your investigation area. Don t save time using rough calculation grids which can t simulate the physical conditions within a street canyon. SoundPLAN version 7.1 allows you to distribute calculations to several computers and multi-threading is available so you can use several calculation kernels on one computer to save time. The dispersion calculation uses an Eulerian approach. Pollution concentrations are transported from steadily emitting sources, one cell to the next, until the concentrations reach a steady state. Then these single wind flow situations are aggregated to statistical parameters like mean, max, percentiles, frequency of limit exceeding, etc. The single case results, concentrations as well as wind fields, can also be displayed as maps.

5 Fine Screening: Austal Austal2000 allows fine screening and rough screening. Adding buildings to an Austal2000 run automatically starts a fine screening calculating a much more detailed wind field and regarding all buildings. Take time to learn about this because it is not a less expensive alternative to MISKAM calculations for street canyons, even if you find examples of this misuse of Austal2000 in other software advertising and on the internet. Correct results require using the correct model for a specific situation. Austal2000 ( Dr. Janicke, Dunum, Germany) uses an easier approach than calculating an entire prognostic wind field. It matches known properties of simplified wind fields. Overlaying the general wind flow with the generally known behavior of flow distortions around an obstacle quickly derives a quite realistic wind field. However, if you have several obstacles close together, this approach works too quickly to preserve accuracy. The Austal2000 evaluation report, unfortunately only available in German, shows good accordance between calculations and wind channel data for single buildings. The comparisons for dense building structures are not very encouraging. Therefore, Austal2000 clearly defines its scope of application. Austal2000 rough screening, using roughness length to represent obstacles, can be used for sources with a height more than 17 times the roughness length (1,7 times the average obstacle height). Under free flow conditions, rough screening can also include ground level sources. Austal2000 is the standard model used for odor problems at animal farms. It is often sufficient to create an emission box instead of modeling buildings located on free terrain with receptors approximately 100 m distance. The box height replaces the initial vertical dispersion. Austal2000 fine screening is limited to sources between 1,2 and 1,7 times the average building height. Austal2000 should not be used for ground level sources between building structures. Comparisons with the well validated MISKAM model show grave differences. Use MISKAM instead. Even though Austal2000 was partly evaluated using MISKAM wind fields, the models are suited for different purposes because Austal2000 uses different turbulence assumptions. For example, it regards all neutral, stable and unstable atmospheric conditions. The decision to use MISKAM or Austal2000 for fine screening will usually be determined by the source height and if unstable conditions are regarded. Another point to consider is that usually the meteo data can t be received from a local measurement within the calculation area. Austal2000 requires an anemometer position within the calculation area to calibrate the standard wind field according to the real conditions. If an outside measurement is transferred in a calculation area using terrain information which does not fit with the meteo data (insufficient area size, data measured in different terrain ), the results can be very strange. Fine screening requires not only a highly developed calculation model and a high end computer, but also excellent input data, and most importantly, an idea what the model does with the data. To model everything as detailed as possible and assign responsibility for the results to a highly developed program, is not the right approach. Rather, know the scope of each model, and choose the correct model for the job in order to achieve accurate, beneficial results.

6 6 When are terrain effects negligible? Everybody knows terrain has an influence on wind speed and wind direction even though most models don t consider terrain. Is it too complex to take terrain into account or is its influence overestimated? The answer is yes to both questions. The size of the investigation area and the source height determine if terrain is needed. Terrain is not only an obstacle, it also influences the heat radiation balance and it produces local wind effects. An extreme expansion of the modeled investigation area is often needed (but not usually paid for), or local measurements with a much higher precision for these effects. fig. 1: Gauss flat terrain fig. 2: Austal2000 flat terrain fig. 3: Austal2000 undulated terrain fig. 4: Gauss flat terrain fig. 5: Austal2000 undulated terrain Rough screening for smoke stacks Which to use: Gauss flat, Austal2000 flat, or Austal2000 regarding terrain? When comparing results of a Gauss flat calculation (fig. 1) with an Austal2000 terrain regarding calculation (fig. 3), you probably expect to see big differences. Now calculate Austal2000 flat (fig. 2) and compare results again. You learn the big differences between fig. 1 and fig. 3 are not just a result of terrain effects, but are also determined by which calculation model was used. How can that be when the evaluation of both models is partly based on the same measured data? A statistical Gauss model uses a simplified plume shape, whereas the Lagrange model uses a wind field. Therefore, don t expect a Gauss model to calculate with Lagrange precision. In fig. 1, Gauss shows a high overestimation close to the source. This is easily explained because the models require a different number of calculation parameters. In other words, there are different assumptions made and built into the different models. Even though the Lagrange model is more sophisticated, it isn t always better. The more sophisticated a model, the more its sensitivity to errors! In fig. 2, the Austal2000 results show errors caused by too rough a wind classification which are completely hidden in the Gauss results. The results in fig. 3 show a high influence from the terrain, but don t show the terrain inclinations cross the boundaries of a diagnostic wind field nor do they show the wind statistics used do not fit the terrain model. To help determine which model to use, let yourself become the smoke stack. Envision the area around you and the anemometer position. With some background knowledge (and maybe some test calculations), you will quickly recognize if regarding terrain is important. In general, tall stacks aren t affected by small undulation, but ground level sources will have an effect. Austal2000 is based on a diagnostic wind field. That's a problem when vertical dispersion is influenced by stalls. Stalls are outside the realm of a diagnostic wind fields and cause an interruption of the calculation. However, using Austal2000 with steeper slopes than allowed prevents a plume leaving a valley too early. Be aware that this exceptional use is a work-around which requires modeling experience to avoid Austal2000 terminating the calculation or computing a wrong wind field. It also requires experience to extract a reliable statement from the results! Rough screening for bypass roads: When compared to other model results, Gauss results greatly overestimate the first m and show a moderate overestimation between m. After 200 m the results can be underestimated, but limits aren't usually exceeded. Embankments cause turbulences. They also cause problems in modeling. This is because they are not mentioned by the Gauss model and their inclination is too steep for Austal2000. If the air is already well mixed at the first buildings in the model area, road embankments and single obstacles lose importance. Otherwise a prognostic wind field model should be used. Rough screening for animal farms: It is often appropriate to use Austal2000 rough screening for Farms near communities. This model includes a special smell evaluation. It is the standard used in Germany. In undulated terrain you need local wind statistics because the model does not process local thermals and cold air flows.

7 When are obstacles negligible? 7 In impact studies, building usually represent recipients. This does not mean building details must always be taken into account. The calculation of wind fields around buildings is only important if there is a small distance between source and recipient. If there is a big distance, usually there is very little influence. Why is this true? Wind speed has a big influence on the initial concentration of pollutants close to the source. Low wind speed means a small air volume has to pick up the released exhaust. In contrast, high wind speed promotes lower concentrations. On the other hand, high ground turbulence counteracts these effects by producing a good vertical exchange. Gauss (TA Luft 86) This model ignores buildings and has no entry to adjust the vertical exchange except the thermal effects represented by the Klug/Manier stability classes (which included a roughness effect in 2009). This seems a very rough approach to include buildings. The Gauss model does use a statistically derived plume shape, but cannot mention detailed local effects like other, more sophisticated model types. Therefore, Gauss results are best when the source is far above any roughness influence and the recipients are not too close to the stack. If there is a bypass road with noise barriers, approximate the situation by lifting the source to the barrier height. Remember, this is a rough approach! Release the emission at a height where a higher wind speed exists. This is not appropriate close to barriers because re-circulations are ignored, but farther away, the results are reliable. If more exact results are needed, use MISKAM to model the barrier. No buildings needed Austal2000 Austal2000 lets you choose to regard buildings or use a rough building effect. Without buildings, use roughness length and displacement height as parameters to adjust wind speed and ground turbulence. Unfavorable roughness length and displacement height uses one value for the entire area. As the highest influence of ground roughness is close to the source, you must especially examine the area close to the source in order to find an appropriate value. If you were to choose to regard buildings, you would add buildings to your calculation and reduce roughness length and displacement height to represent the roughness between the buildings. Austal2000 would then calculate a much more sophisticated wind field library, which might take days to complete. Therefore, it is wise to consider if an approach without buildings would be reliable enough! Also, remember that Austal2000, in combination with buildings, is limited to source heights between 1,2 and 1,7 times the average obstacle height and it does not support street canyons! Austal2000 is very useful for calculating smell from animal farms. Typically, there is a group of barns around the source, then a long distance of free terrain, and then more houses. For this situation it is usually OK to ignore the buildings because the focus is on the odor near the houses. Model the vertical exchange around the farm buildings by creating an emission box with an estimated vertical expansion to define the initial turbulent dispersion. Turbulences within the community have little influence on the concentrations because the air arrives already well mixed. The roughness length for such a calculation without buildings usually corresponds to the space between farm and community. Buildings required MISKAM Because MISKAM is considered the best model, people often choose it, but then use a crudely rough grid without buildings because they can t spend time on modeling and calculation. This is nonsense and a misuse of MISKAM! MISKAM is a powerful, fine screening model for street canyons and hot spots. Don't misuse it for rough screening. It needs buildings to unfold its strength that s what it is made for and validated for! It requires an initial roughness length value for the space between buildings, which can be adjusted by adding local roughness areas if desired. Remember, the right model for the right situation equals correct results!

8 8 Perspectives Because of our extensive noise prognosis background, we developed synergy effects between air pollution tasks and noise prognosis tasks. All noise control software producers do this because many authorities require it. However, SoundPLAN does even more: We provide support for people working with air pollution prognosis full time! We continually search for and develop new ideas to compliment our air pollution suite. We are implementing a long list of SoundPLAN tools and have two interesting ideas for new models to interface or include in SoundPLAN. Outlook: Rough Screening IMMIS IVU-Umwelt GmbH in Freiburg, Germany, offers a GIS based suite to search for hot spots in cities, to analyze the impact of redirected traffic connections and to analyze traffic emission variants. The emission data are taken from the HBEFA, already standard in several European countries, which includes thousands of emission factors. IMMIS em helps users compose national fleets or local fleet variations and connects emission factors with localized traffic data. IMMIS luft combines road emissions with street canyon characteristics and local meteorology to get a rough screening of expected pollutant concentrations and one average value for an entire road section. The concentrations are derived from a huge database a box model creates. For a small fee, IVU-Umwelt GmbH adjusts meteorology to specific regional requirements. The first adjustment is even included in the sales price. With the first purchase order, SoundPLAN will create an interface and a tool to divide the street canyons into sensible road sections while regarding the road geometry and building structures. Let us know of your interest in the interface! Outlook: Fine Screening GRAMM/GRAL GRAMM was developed at the Technical University of Graz and is highly respected in the scientific world. Both GRAMM and the dispersion model GRAL are validated by many international comparisons and studies and both are recommended by the Austrian authorities. GRAMM utilizes a prognostic approach to calculate wind fields on large areas in complex terrain. The basin of Graz, on the southern side of the Alps, poses a very challenging evaluation area. The system has been used under different climate conditions, so it is a world wide solution. GRAL, the Lagrangian particle model of the University of Graz, completes GRAMM for air pollution calculations. GRAL, however, is all that is needed when working in less complex terrain areas. Because GRAMM calculations require solid meteorological understanding and a lot of time, SoundPLAN, together with the Technical University would like to offer a wind field calculation service for GRAL customers. GRAL has the best reputation for ground level sources in complex terrain flow conditions. Different roughness length can be used for rough calculations without buildings, plus there are other features, like a comfortable source receptor modeling approach, which Austal2000 does not have. GRAL is also one of only a few models validated for low wind speed conditions. If buildings are also to be considered, the quality of modeling is similar to micro scale models. The combination of GRAMM/GRAL/MISKAM in one software interface would meet the challenges of almost any task of urban and rural planning projects. SoundPLAN is working with the authors to create just such an interface within our AirPLAN suite.

9 Library Tools 9 All air pollution modules implemented in SoundPLAN need wind statistics. SoundPLAN has a Meteorological Station Library. It is a user defined library to edit, store and classify measurement data. Its elements can be used with Gauss (TA Luft 86) and MISKAM. Austal2000 requires statistics in several allowed ASCIIformats, which are provided by the German weather services. Even if Austal2000 doesn t read SoundPLAN s library, this tool is very useful to make the ASCII files visible or to export user data to the required file formats. To import free data formats, just arrange the columns in a spread sheet as required in the SoundPLAN library and copy them via clipboard to SoundPLAN. Meteorological raw data SoundPLAN stores raw measurement data in a table. Data can be organized as time rows or as classified statistics. We have started implementing a set of tools to transform data, with a special focus on atmospheric stability classifications. You can already calculate Klug/Manier classes from cloud covering, transpose them from one station to another, convert to Monin/Obukhov length, etc. Version 7.1 will introduce filter options to analyze meteorological data and related time series of pollutant background measurement. Classified view To show data in a diagram, a temporary classification to sectors and wind speeds is needed. Use the settings for the graphics display and to create a new, classified raw data set. The diagram can be copied to the clipboard as Windows metafile (scalable vector graphics and text). You can paste it into the project documentation text. The classification is temporary. For calculations, Sound- PLAN always uses the raw data table, but it takes only a click to create a new, really classified raw data set or an ASCII file for Austal Wind rose classification (Klug/Manier-Class: all - cumulative percentage) Wind rose classification (Klug/Manier-Class: all - cumulative percentage) Wind classes [m/s] < 1,4 1,4-1,8 1,9-2,3 2,4-3,8 3,9-5,4 5,5-6,9 7,0-8,4 8,5-10,0 > 10, Wind classes [m/s] < 1,4 1,4-1,8 1,9-2,3 2,4-3,8 3,9-5,4 5,5-6,9 7,0-8,4 8,5-10,0 > 10,0 Sometimes it is necessary to correlate a meteorological time row with an emission time row. This procedure increases calculation time, so is only sensible for Gauss or Austal2000. Version 7.0 allows only an emission day histogram for Gauss calculations. Version 7.1 offers a sophisticated library concept with easily defined hourly emission variations for the whole year, with simple, periodically repeated day or week histograms. The sources will also support time dependent emission variables like volume stream and humidity, to support all Austal2000 time row functions. Day histogram The basic definition is a set of day histograms, each with 24 separately defined hours. Week histogram There can be several typical weeks to regard seasonal differences of production cycles. Year histogram The year histogram links to week-histograms. SoundPLAN uses a reference date to know the week day for each date so you won t have to spend hours defining the periods, plus, you can insert single days which refer to different week histograms (include feast days, company holidays, etc.).

10 10 Grid operations After only a short time working with air pollution prognosis, you will notice that the simple calculation of immissions is not enough to get sensible results. The sources within a calculation model represent only a part of the whole emissions because other emissions are added from local sources or inflowing air. Plus, it is important to regard pollutants which are transformed during transport. This is not a problem for CO, because it becomes CO 2 and mitigates the concentrations. NO, however, becomes NO 2 and the concentrations increase within critical distances. Add preload (initial pollution of inflowing air) Pollutants which come from distant regions are usually added to the immission maps as single values. This is sometimes not enough when working with maximum values. Neighboring emissions might influence the results in a close dependence to wind directions. A good approach for this would be to calculate the local pollutants with MISKAM and overlay the results with a Gauss (TA Luft 86) calculation. Use sources only one time, and remember that the roads in a MISKAM calculation end at the border of the outer area. Overlay sources to adjust scenarios If you have few sources, it is wise to start separate dispersion calculations for each source with one standard pollutant and standard emission and add the results afterwards. This avoids rerunning the dispersion calculation. Use various factors to adjust the emissions to compare different scenarios. Convert NO to NO 2 Austal2000 and Gauss automatically transform NO into NO 2 using a time dependent conversion rate. This is sensible for tall stacks with strong emissions. However, below the Urban Canopy Layer, NO converts differently. For traffic emissions, pollutant NOx should be calculated instead of NO and NO 2. Include the NO x background into the conversion reaction, simulated by a post processing. In this case NO x should be emitted. There are several formulas which derive NO 2 from NO x concentrations that calculate the transformation as a post process using grid operations. This allows the total NO x to be regarded, including the background pollution. This is the better way, especially for ground level sources like traffic. Remember, prognosis conversion formulas that don t normally have entry for radiation and ozone concentrations are empirically founded and probably can t be used worldwide. SoundPLAN s functions are derived from German measurement campaigns. Find local studies with formulas that represent your investigation. If the formulas are too complex to insert into the grid operations, contact us for assistance. Remember, empirically derived formulas never fit single cases, but represent an entire year. A single case prediction would not only require information about solar radiation, temperature and all other pollutants in the air, but also information about short time correlations. It would be impossible to make such a detailed forecast!

11 Results 11 Gauss (TA Luft 86) calculates single monitoring stations or grid results. AUSTAL2000 has an option for single point results, but SoundPLAN doesn t support the display. You receive only the original AUSTAL2000 protocol. MISKAM doesn t display single points. We recommend grid calculations because all immission values should regard neighbouring cells. We offer a huge number of display options for grids - more options than can be shown here. MISKAM is the only model that displays wind fields.

12 12 What about a training session? The purchase process often begins with using a demo version to get an understanding of modeling techniques before making a decision to purchase. For air pollution propagation, there are many details to learn about the different models besides learning how to use the software. Especially if air pollution prognosis is a new field of study, we feel the most efficient way to begin is to attend a training session. Although air pollution prognosis is a complex matter, it doesn t take long to learn how to recognize and avoid problems throughout process. The model developers have done their work correctly, so you don t have to worry about the mathematics and the physic. We focus your attention on weather and pollution effects, much of which you already know, and then show you how these effects are parameterized as model input for the different model approaches. AirPLAN training shows the maximum reliability expected in projects and the minimum data quality required. It shows how the interaction between input data and the calculation model determines model selection. Above all, it shows how to maximize your time and efforts for efficient, accurate air pollution prognosis. Contents: The training includes the modules Gauss (TA Luft 86), Austal2000 and MISKAM. Topics include: Wind in Nature appearance and importance of large scale and local wind systems Modeling Wind measurement and parameterization of wind characteristics plumes and wind fields Model Approaches statistical approach diagnostic approach prognostic approach Source Modeling general approaches modeling in SoundPLAN HBEFA road emissions Calculation Control optimizing parameter settings control by files & graphics Result Display wind fields concentrations post processing operations The training projects and presentation slides are available on DVD. All three training days are required to fully cover the topics. Attendance from first to last session is mandatory. If you want to discuss project data, send them klaus.wilhelm@soundplan.de beforehand with a description of the situation. We ll look for ways to assist you with your particular projects. Sincerely, your B+B Team