In the early 1800’s, when the first railroad lines were being constructed, miles and miles of track were being laid every day. People were now able to travel great distances unlike they were before, completely unimpeded. Well, not really, at first.

In the early days of the railroad, private companies and governments building the railroad lines had a little problem; there was no established standard on how wide to make the tracks. It was common place when a train reached the end of one railroad company’s line or crossed a country border, all the passengers had to get off the train and walk to another train waiting on another set of tracks that had a different spacing between the rails.

Once standards were established, it was great for customers (no more changing training in the middle of nowhere) and great for business (more suppliers could enter the market). The moral of the story is standardization (providing boundaries) allows for greater freedom.

Developing and implementing standards in the dispersion modeling space is at the core of NaviKnow’s objectives.

What do trains and standards and boundaries have to do with dispersion modeling results? More than you think.

Compiling Modeling Results

One of my pet peeves when it comes to dispersion modeling, whether it is putting the input data together or graphically viewing the results, is I still have to jump from program to program to program, and reformat the data each time I make a jump to do what I need to do.

Overtime I have come up with generalized standard format for modeling output that minimizes the flips and spins I have to do regardless of what platform or application I use to display the data.

Keeping It Simple

To make the format easily portable, I use a comma delimited ASCII text (CSV) file. Nearly every graphics program can handle CSV. Be sure to have all text values within quotes (“). It is best practices to have all values considered text. You can just leave numeric values as is, but if a stray character has found its way into your data, it will raise an error when the data are imported.

When putting the file together, include only the data fields that are necessary. Anything extra may lead to errors when imported or will just take more time to import. Also, have extraneous values are more likely to confuse the user. Keep it simple!

The suggested fields to include are:

• Air contaminant
• Averaging time
• Scenario or source group
• X – UTM East
• Y – UTM North
• Predicted concentration
• Standard value
• Fraction of standard value

These fields should contain all the information needed to understand and interpret the modeling results.

Displaying AERMOD Results

Once you have your AERMOD results compiled and formatted, you should be able to easily import the results into most graphic display or mapping programs or platforms.

If you have ESRI’s ArcGIS available, it is a two-step process to import your modeling results. It is recommended you use a geodatabase (GDB) to house all of your project data. First, use the Table To Table tool to import the data. Then use the Create Feature Class from XY Table. That’s all it takes. With other GIS software packages, the procedure shouldn’t be much different.

If you want to go the inexpensive to free route to display your results, there is an option: Google fusion tables. If you have used Google Maps or Google Earth, there is a limit on the number of points that can be displayed (2000) and number of different layers (10). The good thing about fusion tables is you can display thousands of points, and polygons, too. The down side is that fusion tables are still considered experimental. They have been around for a while, but the means to create them is not as refined as using Maps or Earth.

Summary

Completing a task can be easier and quicker if standardized procedures are used. The task of compiling modeling results and having them displayed graphically can be more efficient for the person creating the graphics and well as the person reviewing the graphic if two principles are used:

• Have data in a  single comma delimited ASCII text (CSV) file
• Use only the data fields necessary to present the results (shown above)

To help the reviewer, particularly if there is a lot of information to convey, compile the same information in the report tables into a spreadsheet, with the tabs corresponding to the tables in the report.

 

If you found this article informative, there is more helpful and actionable information for you.  Go to http://learn.naviknow.com to see a list of past webinar mini-courses. Every Wednesday (Webinar Wednesday), NaviKnow is offering FREE webinar mini-courses on topics related to air quality dispersion modeling and air quality permitting. If you want to be on our email list, drop me a line at [email protected].

One of the goals of NaviKnow is to create an air quality professional community to share ideas and helpful hints like those covered in this article. So if you found this article helpful, please share with a colleague.