Appendix F
Analysis Using HYSPLIT Trajectories for Days with Largest Contribution to Haze by Various Species of Particles

Contents of Appendix F
Discussion of trajectories and results
Summary of trajectories (Table 3-4 from the FIP)
Maps of trajectories
Procedure used for trajectories

Discussion of trajectories and results

	Where do the particles come from that affect visibility in the Virgin Islands National Park?  The HYSPLIT model plots paths taken by particles blown by the wind through the air. The HYSPLIT model has historical meteorological data, to see where the air traveled enroute to the IMPROVE monitor, located on St. John, near Cruz Bay, on days when visibility was worst as measured by the samples taken by the IMPROVE monitor.  Explorers traveling by balloon use trajectory models to find the most favorable winds to get them where they want to go. 

	By calculating trajectories, we can test our suppositions about where the various kinds of particles come from.  For example, if the major cause of obstruction to visibility on a given day is due to sulfates or nitrates, and sulfates and nitrates are products of combustion, trajectories on those days would be likely to come through areas with lots of sources of combustion on the way to affecting visibility at the IMPROVE site.

	HYSPLIT model uses weather data measured every three hours at the surface and twice a day aloft.  These data are converted to a grid of values of wind direction and speed and other weather factors for each hour of the day. 

	The user specifies the starting point (in our case, the IMPROVE monitoring site on St. John), how long to run the model (2 weeks) and the height above ground at the monitoring site. We used the model to go backwards from the IMPROVE site to see where the air came from.  We started at three different heights above the monitoring site within the well-mixed tropical surface layer, since tropical air is well mixed over land at these heights.  But wind can change direction at different altitudes and give different trajectories, even on the same day.
 
	Since the trade winds mostly blow from east to west across the Virgin Islands, it is not surprising that when the winds are traced backwards from the sampling site on the western end of St. John, the path that the air takes almost always passes eastward over the island of St. John. Many trajectories pass over neighboring islands like Antigua and St. Martin. Some trajectories pass over the British Virgin Islands, located to the northeast of St. John. 

	However, as the summary of the paths of the air parcels show (see the enclosed table) there is not any particular pattern where days with the highest amounts of light-scattering particles have trajectories that commonly pass through one or more of these likely sources of human air pollution. For example, only one of the days with high levels of haze that may be from combustion has trajectories that pass over St. Croix, home to a major industrial center. These trajectories show that even on days when visibility is reduced due to sulfates, nitrates, and carbon (likely suspects from sources of combustion), the air affecting the park usually does not pass over St. Croix, St. Thomas, or Puerto Rico. 

	More often, days with high concentrations of fine soil or coarse particulates in the atmosphere occur when air travels from Africa's Sahara Desert. For example, Figure 1 shows a set of backward trajectories originating at the Virgin Islands National park for 100 (red), 500 (blue), and 1,000 (green) meters above ground level for September 26, 2002, which is typical of days with high visibility impairment due to fine soils. This illustrates how a significant cause of reduced visibility in the Virgin Islands National Park is dust transported from the Sahara Desert, located over 5,000 miles away in Africa. The Virgin Islands can also be affected by other various natural sources, such as sulfate produced by plankton in the ocean, and ash from the Montserrat Volcano located over 200 miles away to the southeast. The effects of these natural sources on visibility can be very noticeable on some days, especially because there are not as many anthropogenic sources of pollution in the Islands in comparison with the more urban areas of the continental United States.
. 
Figure 1.   HYSPLIT trajectories for a low visibility day with high concentrations of fine soil.

References
Draxler, R.R. and Rolph, G.D., 2012. HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY Website (http://ready.arl.noaa.gov/HYSPLIT.php). NOAA Air Resources Laboratory, Silver Spring, MD. 

Rolph, G.D., 2012. Real-time Environmental Applications and Display sYstem (READY) Website (http://ready.arl.noaa.gov). NOAA Air Resources Laboratory, Silver Spring, MD. 

We  gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model via the READY website (http://ready.arl.noaa.gov)used in this analysis. 
The trajectories were run by Edward Finfer of EPA Region 2, Air Programs Branch and reviewed by Henry Feingersh, also from EPA-R2-APB



Table 3-4: Summary of Trajectory Analyses for Top Four Days with the Highest Visibility Impairment for Each Species 2000  -  2004
Species
Total Light Extinct-ion (bext)
Date
Source Region (Height of Trajectory in Meters Above Ground Level)



Local
Regional
Long-Distance
All Aerosols Combined
79.5
06 23 2004
St. John (100, 500)
Anguilla (100)
NW Africa (500, 1000)

77.4
08 01 2004
St. John (100, 500, 1000)
None
NW Africa (1000)

71.8
07 08 2004
St. John (100, 500, 1000)
Anguila (500)
Central Africa (1000)

71.1
08 01 2003
St. John (100, 500)
Anguila (100) 
St. Martin (500)
African Coast (1000)
Fine Soil
19.9
09 26 2002
None
None
Central Africa (500, 1000)

17.9
08 01 2004
St. John (100, 500, 1000)
None
NW Africa (1000)

17.3
08 03 2002
None
Guadeloupe (100)
Central Africa (1000)

16.9
06 14 2004
St. John (1000)
Guadeloupe (100, 500)
Central Africa (1000)
Sea Salt
24.2
03 07 2003
St. John (100, 500, 1000)
None
None

21.8
03 10 2003
St. John (100)
Anguila (100)
None

18.9
08 01 2003
St. John (100, 500)
Anguila (100) 
St. Martin (500)
African Coast (1000)

17.9
02 12 2001
St. John (100, 500, 1000)
None
None
Sulfate
42.0
04 24 2003
St. John (100)
Puerto Rico (1000)
None

34.9
11 21 2001
St. Thomas (100)
Puerto Rico (100, 500) Dominican Rep. (1000)
Florida (500)

26.8
08 03 2002
None
Guadeloupe (100)
Central Africa (1000)

26.6
02 27 2004
None
Montserrat (500)
Western U.S. (1000)
Nitrate
5.2
05 09 2003
St. John (100, 500, 1000)
Anguila (500)
Barbuda (1000)
None

4.8
11 15 2001
None
St. Martin (100)
Barbuda (500)
Canada (100, 500, 1000)

4.52
08 01 2003
St. John (100, 500)
Anguila (100) 
St. Martin (500)
African Coast (1000)

4.52
05 21 2003
Puerto Rico (500, 1000)
Dominica (100)
Guadeloupe (500)
None
Elemental Carbon
15.5
09 05 2002
St. John (500, 1000)
BVI (100)
None
Central Africa (1000)
African Coast (500)

14.0
01 08 2002
None
St. Martin (100)
Mideast U.S. (100)
Mexico, Florida (500, 1000)

13.3
08 13 2004
None
St. Martin (100, 500)
None

10.3
11 20 2003
None
BVI (100, 500)
Canada, N.E. U.S. (100)
Organic Carbon
18.4
01 08 2002
None
St. Martin (100)
Mideast U.S. (100)
Mexico, Florida (500, 1000)

17.2
09 05 2002
St. John (500, 1000)
BVI (100)
None
Central Africa (1000)
African Coast (500)

7.09
10 26 2002
St. John (100, 500, 1000)
None
Central Africa (1000)

7.05
08 13 2004
None
St. Martin (100, 500)
None
Coarse PM
34.4
09 26 2002
None
None
Central Africa (500, 1000)

33.4
06 23 2004
St. John (100, 500)
Anguilla (100)
NW Africa (500, 1000)

30.5
08 08 2001
St. John (100, 500, 1000)
BVI (100, 500, 1000)
W Africa (100, 500, 1000)

28.8
07 14 2003
St. John (500, 1000)
BVI (100, 500)
None
Dates in italics are days when it was a top four date for more than one species of particles.



The following maps are HYSPLIT trajectories output as.kmz files and plotted on Google Earth.

Figure 2. Trajectories with time and dates for worst haze days 2000-2004 for all types of particles. See Table 3-4 for list of days and type of particle.

Figure 3 Same as Figure 2  -  trajectories for worst haze days for all types of particles - but a wider view, including Puerto Rico and other islands in the area of the Virgin Islands	
Figure 4.  Global view of trajectories in Figure 2 for worst haze days 2000-2004 for all types of particles. 

Figure 5.  Trajectories for worst visibility days due to sulfate, 2000-2004
Figure 6. Global view of trajectories for worst visibility days due to sulfate, 2000-2004

Procedure Used for Trajectories
Trajectories for VI haze plan for selected IMPROVE monitoring days 2001- 2004.  24 hour (midnight to midnight) particulate matter filter sampler using READY HySplit trajectories program, Internet version, click on :
http://ready.arl.noaa.gov/hysplit-bin/trajtype.pl?runtype=archive .
Instructions:  
Click on the box under:  First, select the meteorologcal data:  Select: REANALYSIS met data; Enter latitude:   +18.336, and longitude: -64.796
Click:  Continue
Select Select the reanalysis File
For the month and year for the date of the trajectory we want, 
e.g., RP200205 is year 2002, month 05 (May 2002).
Click:  Next
Trajectory direction:  backward 
Vertical Motion:  model vertical velocity.  
Start time (UTC):  Fill in year month and day from the data and hour = 18 (for 1800 UTC, which is 2pm time in the Virgin Islands).
Total run time (hours):  515
Start a new trajectory every: should be 0
Start 1 latitude (degrees): should already be 18.336
Start 1 longitude (degrees): should already be -64.796
Leave Start 2 and 3 blank
Level 1 height:  100 (meters)
Level 2 height:  500
Level 3 height:  1000

Display options:
Don't change any defaults, except for:  GIS output?  Click:  Google Earth (kmz)

Click:  Request trajectory
Wait for graphics files.  When they are ready, they will look something like this:

HYSPLIT MODEL RESULTS FOR JOB NUMBER 33054
                                Model
Status: 
Top of Form

Bottom of Form

                                    RESULTS
              Click on text link to view images in a new window.

                                   GIF Plots
                              Google Earth Plots




                                 Trajectories
GIF
KMZ













Right click on gif and save in directory with time and date in file name
Right click on kmz and save in directory with time and date in file name
For example, this example can have a file name with the year, month, day, hour, 
e.g., 2002 05 05 18.gif
and 2002 05 05 18.kmz
Save the trajectory plots.
The gif version should look like this:
                                       

Additional runs can be made for multiple trajectories by following these directions:
 
Click on the box under:  First, select the meteorologcal data:  Select: REANALYSIS met data; Enter latitude:   +18.336, and longitude: -64.796
Click:  Continue
Select Select the reanalysis File
For the month and year for the date of the trajectory we want, 
Click:  Next
Trajectory direction:  backward 
Vertical Motion:  model vertical velocity.  
Start time (UTC):  Fill in year month and day from the data and hour = 18 (for 1800 UTC, which is 2pm time in the Virgin Islands).   But for the day, fill in the day *plus 1 day*, e.g., day in this case would be 06 instead of 05.  Enter a time of 03 .
Start a new trajectory every:
 3 hrs Maximum number of trajectories: 8
Total run time (hours):  515
Start a new trajectory every: should be 0
Start 1 latitude (degrees): should already be 18.336
Start 1 longitude (degrees): should already be -64.796
Leave Start 2 and 3 blank
Level 1 height:  100 (meters)
Level 2 height:  blank
Level 3 height:  blank

Display options:
Don't change any defaults, except for:  GIS output?  Click:  Google Earth (kmz)

Click:  Request trajectory
Wait for graphics files.  
This file should look like the graphic on the next page.
Then save the file as year date height
e.g., 2002 05 05 100m.gif
and the kmz file as 2002 05 05 100m.kmz
Then go back and run the same information, changing only the Level 1` height to 500 and after you get the maps for that run, change the Level 1 height to 1000 and get the maps for that run.

