Exercise #1

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Dispersion Modeling Using SCREENView™ Model
SCREEN3 Startup Instructions:
1. Open Lakes Environmental/SCREENView Icon from Desktop or Start Menu.
2. Click “OK” on the About screen that appears.
3. Click “New” on the toolbar.
4. Select directory where the file will be saved (C:\temp\) with a valid filename.
Exercise #1
Vehicular traffic is one of the biggest sources of CO emissions in many cities. Consider a flat urban area of 10 km x
10 km. This area has 100,000 vehicles operating and each vehicle emits an average of 5 lbs CO per hour per car.
Run the SCREEN3 model for an area source over the full range of meteorological conditions to determine the
maximum CO concentration in all directions (100 to 10000 m distance) of this source area. Use a source release
height of 0.6 m and a receptor height of 1 m.
1. For an area source, you need the total emission rate in units of g/s/m 2 (2.2 lbs = 1 kg). Compute the emission
rate.
2. Fill in your model options:
 Source type:
 Dispersion Coefficient:
 Larger side length of rectangular area:
 Smaller side length of rectangular area:
 Search through range of wind directions?
 Meteorology:
 Automated distances: min =
 Simple, flat terrain
max =
3. Run the model and view the results (the graph). Sketch the shape of the model output graph.
4. From looking at your results, what is the maximum 1-hr concentration of CO (in mg/m3) determined by the
model?
Exercise #2
Look at the case of a neighborhood of about 85 homes in a 1500 m by 500 m area. During the winter the homes in
this neighborhood operate woodstoves for heat. An emission inventory of the area indicates that the woodstoves
emit 9000 lbs of PM2.5 every 30 days. Run the SCREEN3 model for an area source to determine the impacts of this
burning on the local area (within 3000 m downwind of the neighborhood). Assume that the source release height is
10 m and that the receptor height is 1.5 m. During the winter, meteorological conditions are poor; use a wind speed
of 2 m/s and a stability class of E. The prevailing winds are from the south (90 degrees to the long dimension).
1. For an area source, you need the total emission rate in units of g/s/m 2 (2.2 lbs = 1 kg). Compute the emission
rate.
2. Fill in your model options:
 Source type:
 Dispersion Coefficient:
 Source release height:
 Larger side length of rectangular area:
 Smaller side length of rectangular area:
 Receptor height above ground:
 Automated distances: min =
 Simple, flat terrain
max =
3. Run the model and view the results (the graph). Sketch the shape of the model output graph.
4. From looking at your results, what is the maximum 1-hr concentration of PM2.5 (in µg/m3) determined by the
model? How does this compare with the 24-hour NAAQS for PM2.5?
Revised 2/16/16
Dispersion Modeling Using SCREENView™ Model
Exercise #3
You will use the SCREEN3 model to estimate downwind concentrations of SO2 from a proposed new stack at a
refinery. A simple air monitoring network is planned to obtain data; you must also determine the location of the two
SO2 monitors of which the network will consist. You do not need to consider building downwash, complex terrain
or fumigation conditions in your model.
The refinery is located in a rural area and is situated in a flat valley. The nearest population center is a small town
five kilometers (5 km) east of the refinery. A background SO2 concentration of 10 µg/m3 exists. Run the model for
your assigned month using the data given. Assume the prevailing winds come from the West.
Data:











Source Type: Point
Dispersion Coefficient: Rural
Emission rate: 4.78 g/s/m2
Stack height: 35 m
Stack diameter: 1.56 m
Stack gas velocity: 13.2 m/s
Stack gas temperature: 394 K
Average ambient temperature: 291.5 K
Simple, Flat Terrain
Automated Distances: 100 m to 7000 m
Meteorology:
35mStack
Month
Wind
Speed
(m/s)
Stability
Class
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
3
3
6
4
3
4
4
2
2
4
3
2
D
E
D
C
C
B
B
A
C
D
D
E
Peak conc
incl bkgr
(µg/m3) @
5000m
Peak conc
incl bkgr
(µg/m3)
70mStack
Distance (m)
of peak
conc.
Peak conc.
incl bkgr
(µg/m3) @
5000m
Peak conc.
incl bkgr
(µg/m3)
Distance (m)
of peak
conc.
To answer the questions below, review the results from the entire classs.
1.
Given the meteorological parameters, what is the highest ambient concentration of SO2 (in µg/m3) that would be
seen at a 10 m high monitor placed at the western edge of the town (5000 m from the source)?
2.
What is the highest ambient concentration of SO2 (in µg/m3) that would be seen at any distance from the
proposed stack?
3.
Now assume the stack height is 70 m. Run the model again and note what differences you see. What is the
highest concentration at 5000m and at any distance given the adjusted stack height?
4.
What inferences can you make about how the stack height affects downwind receptors? Would it be to the
town’s advantage to advocate for the higher stack, according to the model results? Why or why not?
Revised 2/16/16
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