More about environmental proficiency.
More about environmental proficiency.
The CALPUFF air dispersion model uses a wide variety of input. Many of the variables change little from time to time and the defaults supplied with the model work just fine, and often are preferred by the regulatory authorities reviewing and using their expert judgement to approve the projects. Some appear in the switch settings for the CALPUFF sister program, CALMET, used for meteorological pre-processing.
CALMET, a 3-dimensional meteorological model that accepts weather data (e.g. MM5), analyzes and scrutinizes it, and then produces an output data file to be read directly by the CALPUFF model. To get wind fields, modelers use an initial guess field for CALMET to refine, incorporating local terrain, land use and meteorological data. This requires quite a bit of expert judgement on its own, and from this collection of data, the program generates the Step 1 wind field (where model meteorological data such as MM5 and terrain/land use data are integrated, and subsequentially a Step 2 wind field where empirical data is incorporated.
Other input parameters are obviously project-specific and include things that change with each job regardless of the model selected for assessment. They may apply to source emission characteristics, location, terrain and so forth.
The third group of variables requires expert judgement. Their use applies specifically to this modelling system and the sensitive results coming from their choices may greatly affect the outcome of the modelling and the approval process. These switches include:
BIAS - Determines how the program incorporates surface and upper air observations to interpolate Step 1 winds and assign a value to each vertical layer grid cell. What does this mean? Each layer receives a contribution from the surface observation and an upper air observation. Use your expert judgement. A positive bias favours the upper air data while a negative value gives more weight to the surface data.
A bias value from -1 to +1 is assigned to each pre-defined atmosphere layer. If bias is zero, the upper and surface winds receive equal weighting in the interpolations. If Bias is +1, the full weighting is assigned to the upper air observations, and if bias is -1 the surface data gets all the weighting.
A good dispersion modeler can use bias in a situation involving a narrow winding valley where observations are sparse, say, a distant upper-air station and a single surface observation station in the valley. Employing our expert judgement, we could assign a value of +1 to bias for the upper layers, thereby ignoring the surface obs at these levels. And a value of -1 near the ground to accept surface observations only at the lowest levels. Intermediate values could then be used to fill the intermediate layers. A bias value indicates the percentage of reduction in each data source's weighting.
IEXTRP - Usually set to a value of -4 to incorporate similarity theory. IEXTRP determines how/whether surface winds are extrapolated in the vertical and if layer 1 data from upper air stations (for which data is available only twice per day) are used.
INFLUENCE-RADIUS PARAMETERS - RMAX1 over land at surface layer, RMAX2 over land aloft and RMAX3 over water. In preparing step 2, these expert judgement parameters dictate the maximum horizontal distance influence from the grid location observed data is considered.
WIND FIELD PARAMETERS - Includes RMIN (minimum radius of influence for wind interpolations), TERRAD (terrain radius of influence), R1 and R2 (distances to point of equal weighting between initial guess and observed data for surface and upper layers respectively); others include RPROG (weighting for forecast wind data), DIVLIM (divergence), NITER (number of iterations), CRITFN (Froude Number), ALPHA (weighting for kinematic effects).
BARRIER PARAMETERS - These include NBAR (number of wind interpolation barriers) , KBAR (number of relevant levels), XBBAR/YBBAR/XEBAR/YEBAR (starting and ending coordinates of barriers). Barriers are used only when effects from terrain are not strong enough for wind blocking effects to be resolved.
DIAGNOSTIC OPTIONS - Here we get into more specialty options where the model defaults are selected in many cases.
After the CALMET process finishes, modellers input data into the CALPUFF model, and another set of parameters needing expert judgement emerges.
Puff or Slug? - MSLUG accepts the value for the puff/slug (stretched puff) option. Use puffs normally, if the emissions are constant or causality is not critical, as the model runs more efficiently in this case.
Puff Splitting - MSPLIT. Best for long range transport calculations and nighttime emissions. It allows the model to break the puff and more accurately account for the effects of wind shear and also becomes more relevant when grid resolution is fine. Puffs split into three sections and if this happens many times in succession, it can overload the computing resources, which can be controlled using the MXPUFF command. The modeller's expert judgement helps him determine what combination of parameters to use here.
Dispersion Coefficients - MDISP. These allow CALPUFF to take on some characteristics resembling familiar ones in ISC3, CTDM or AERMOD. The default selects PG, Pasquill-Gifford, dispersion coefficients.
Subgrid-scale - MCTSG and MSGTIBL. Used for determining impacts on terrain features too small to be captured by gridded topographical data. Use of CTSG allows the model to resolve these special features. The SGTIBL option allows the user to incorporate his expert judgement and high resolution coastline modelling and effects of coastal fumigation.
Chemical Transformations - Sometimes molecules interact with each other and change as a result. CALPUFF can handle some of these and a certain expert judgement in chemistry is needed. Some chemical reactions require input files of background concentrations of other substances, such as ammonia or ozone, and default values are sufficient in other cases. In some jurisdictions, the modeler would be best advised to check with the regulators for special rules about these situations.
If you need a good group of modellers for your project, please contact Calvin Consulting Group Ltd. Call Barry at at 403-547-7557 or email - barry.lough @ calvinconsulting.ca (remove spaces).
Absolute probability expert judgement receives a lot of attention when dealing with statistics of human behaviour, an endeavour with many independent variables. We can see also that it applies well to something more straightforward, such as the physical science of atmospheric dispersion. As our models improve over the decades, one would hope that fluid predictions will become easier from a practitioner's point of view, but this is not too likely. After all we have not been able to put an end to our human problems.
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