Budge, Amy

Bunderson, Landon

Crimmins, Theresa

Hudspeth, William

Huete, Alfredo

Krapfl, Heide

Levetin, Estelle

Luvall, Jeffrey C.

Nickovic, Slobodan

Pejanovic, Goran

Prasad, Anup

Sprigg, William A.

Toth, Barbara

VandeWater, Peter K.

Vujadinovic, Miram

Vukovic, Ana

Welzin, Jake

Zelicoff, Alan

NASA Technical Reports Server

Integration of Airborne Aerosol Prediction Systems and Vegetation 
Phenology to Track Pollen for Asthma Alerts in Public Health Decision 
Support Systems
Jeffrey C Luvall  Marshall Space Flight Center
William A. Sprigg,  Goran Pejanovic, & Slobodan Nickovic,
Anup Prasad, Chapman University
Ana Vukovic and Miram Vujadinovic University of Belgrade, Serbia 
Estelle Levetin & Landon Bunderson Dept. Biology University of Tulsa 
Peter K. Van de Water  California State University, Fresno 
Amy Budge & Bill Hudspeth  Earth Data Analysis Center, University of New Mexico
Alfredo Huete, University of Technology Sydney
Alan Zelicoff, St. Louis University & ARES Corporation
Theresa Crimmins & Jake  Weltzin USGS National Phenology Network
Heide Krapfl and Barbara Toth, New Mexico Department of Health
https://ntrs.nasa.gov/search.jsp?R=20130010248 2019-08-31T00:13:13+00:00Z
Moscow Birch Pollen
Pollen Release
Pollen per cone
Sonora 472,000 pollen grains/cone
Dallas 402,000 pollen grains/cone
San Marcos 374,000 pollen grains/cone
Junction 363,000 pollen grains/cone
Cone and pollen production for 
representative trees 
Cones/tree Total pollenpotential
Santa Fe - LCP 52,808 1.53 x 1010
Santa Fe - HCP 646,496 1.87 x 1011
Jemez Springs - HCP 269,946 7.83 x 1010
Summary Statistics for 2010 and 2011 Juniperus 
pinchotii pollen seasons at source
Location
Average daily 
concentration  
Pollen 
grains/m3
Peak daily 
concentration 
Pollen 
grains/m3
Date of 
peak
Peak hourly 
concentration 
Pollen grains/m3
Time of 
peak hour
Date of 
peak hour
2010
Erick, OK 337 5,563 25-Oct 15,898 10:00 AM 25-Oct
Sonora, TX 286 3,019 25-Oct 12,152 10:00 AM 25-Oct
San Angelo, TX 653 5,542 1-Nov 10,195 Noon 1-Nov
2011
Erick, OK 12 214 16-Oct 800 10:00 AM 16-Oct
Sonora, TX 64 428 26-Oct 2,422 10:00 AM 31-Oct
San Angelo, TX 60 493 26-Oct 2,747 4:00 AM 26-Oct
Quanah, TX 22 190 19-Oct 703 8:00 PM 19-Oct
Influence of preseason meteorological 
variables for Juniperus ashei
 Start date
 Significantly correlated with mean monthly temperature 
in December (r = 0.467, p = 0.038) and November 
rainfall (r = 0.468, p = 0.038)
 Cumulative Season Total (CST)
 Significantly correlated with mean maximum temperature 
in December (r = 0.4740, p = 0.035)
Correlation of average daily Juniperus pollen 
concentration with meteorological variables from 1987 
to 2006
Meteorological Variable Main season r
Max daily temperature 0.607***
Min daily temperature 0.371***
Mean daily temperature 0.546***
Rainfall -0.143***
Rainfall (1 day lag) -0.164***
Rainfall (2 day lag) -0.069        
RH -0.282***
Mean wind speed 0.117**
Sunshine 0.257***
* p <0.05      ** p<0.01       *** p<0.001
Multiple regression model for main season pollen 
concentration and meteorological variables
R2 Meteorological variable Beta value p
0.379 <0.001
Max daily temperature 0.583 <0.001
Rainfall -0.071 0.014
Rainfall (1 day lag) -0.064 0.027
Mean wind speed 0.033 0.253
Multiple Regression Model for Start Date and 
Preseason Meteorological Variables
R2 Meteorological variable Beta value p
0.736 <0.003
November rain 0.795 0.001
December mean T 0.566 0.004
January rain 0.559 0.009
October rain -0.500 0.016
November mean T 0.502 0.032
August rain 0.316 0.104
Multiple Regression Model for CST and 
Preseason Meteorological Variables
R2 Meteorological variable Beta value p
0.639 <0.019
December maximum T 0.754 0.002
June rain 0.469 0.021
December rain -0.384 0.045
January mean T -0.237 0.211
September rain -0.285 0.148
January rain -0.208 0.262
Red Cedar Encroachment
 Oklahoma has 17 million acres of  prairie, shrub land, 
cross timbers forests and other forests
 1950: 1.5 million acres with cedar problems
 1985: 3.5 million acres with cedar problems
 1994: 6.3 million acres with 50 trees/acre and 2.5 million 
acres with 250 trees/acre - 37% loss of  native ecosystems
 2001: 8.0 million acres with 50 trees/acre and 5.0 million 
acres with 250 trees/acre - this represented a 47% loss of  
native ecosystems
 2013 projection: 12.6 million acres with 50 trees/acre and 
8.00 million with 250 trees/acre 
Northerly Flow
Southerly Flow
Within Texas
Trajectory Wind Directions
Southerly Northerly Within TX Other
2007 to 2008 Pollen Year
17% 54% 24% 5%
2008 to 2009 Pollen Year
12% 68% 7% 12%
2009 to 2010 Pollen Year
31% 50% 7% 11%
2010 to 2011 Pollen Year
26% 41% 30% 4%
2011 to 2012 Pollen Year
18% 54% 16% 13%
Incursion of J. ashei Pollen into Tulsa
 Each winter since 1980 J. ashei pollen has been registered 
by our Tulsa air samplers
 Levetin and Buck,  Annals of Allergy, 1986.
 Levetin,  Aerobiologia, 1998
 Rogers and Levetin, Int J Biometeorol, 1998
 Van de Water and Levetin, Grana, 2001
 Van de Water et al, Int J Biometeorol, 2003
 Pollen recorded on 48% of the days in Dec and Jan (range 
11% to 79%) 
 Concentrations typically low; however, “Very High”
concentrations have been registered on several occasions  
(based on National Allergy Bureau level of very high 
>1500 pollen grains/m3)
25 Oct 2010 incursion of Juniperus pollen into the 
Tulsa atmosphere with a average daily concentration 
of 106 pollen/m3
Hourly concentration of Juniperus pollen on 25 Oct 2010 in Tulsa 
0
100
200
300
400
500
600
700
2:00 6:00 11:00 14:00 18:00 22:00
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Trajectory analysis indicates the pollen originated in 
southwest Texas approximately 8 hours earlier
Juniperus pinchotii concentrations at Sonora 
and San Angelo confirm the trajectory model
Hourly concentrations of Juniperus pinchotii pollen 
25 Oct 2010 - Sonora, TX
0
2000
4000
6000
8000
10000
12000
14000
2:00 6:00 10:00 14:00 18:00 22:00
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Hourly concentrations of Juniperus pinchotii pollen 
25 Oct 2010 at San Angelo, TX
0
1000
2000
3000
4000
5000
6000
7000
8000
2:00 6:00 10:00 14:00 18:00 22:00
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R² = 0.7925
4.50E‐06
5.00E‐06
5.50E‐06
6.00E‐06
0% 20% 40% 60% 80% 100%
P
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Relative humidity
R² = 0.7072
3.50E‐06
4.00E‐06
4.50E‐06
5.00E‐06
0% 20% 40% 60% 80% 100%
P
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Relative humidity
Estimated weight per pollen grain (J. monosperma) after 2 hrs across 
the range of relative humidity levels at 20° C 
Estimated weight per pollen grain (J. pinchotii) after 2 hrs across the 
range of relative humidity levels at 20° C 
While J. monosperma and J. pinchotii were 
larger in size, their percent weight gain was 
similar to that of J. ashei.
Hygroscopic Weight Gain of Juniperus
Pollen
R² = 0.8543
2.30E‐06
2.50E‐06
2.70E‐06
2.90E‐06
0% 20% 40% 60% 80% 100%
P
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Relative humidity
Estimated weight per pollen grain (J. ashei) after 2 hrs across the 
range of relative humidity levels at 20° C 
•Juniperus ashei, J. monosperma, 
and J. pinchotii were dusted on 
greased slides and exposed to a 
range of temperatures and 
humidity levels and weighed at 2 
hrs and 6 hrs.
•J. ashei was weighed at 
temperatures 4° C, 15° C, and 
20° C at relative humidity levels; 
20%, 40%, 50%, 75%, 86%, 97%.
•Weight was not significantly 
affected by temperature or time.

Pollen release potential Source Map/Mask 
(PRPSM_of_Ji) of a Juniper species ‘‘i” is calculated as:
PRPSM_of_Ji = Ti × Mi × Hi × Ci × Pi                                                                                                         
Where 
Ti = Number of Ji trees
Mi = Male/Female ratio of Ji
Hi = HCP_LCP/All ratio for Ji
Ci = Cones per Ji tree 
Pi = Pollens per cone for Ji
The number of trees of a Juniper species “i” per grid cell is calculated as
Ti = GAPi × MODIS× TC
Where
GAPi = Fraction of Ji at 1 km grid (range 0-1)
MODIS = MODIS derived percent tree cover per 1 km2 grid cell (in fraction, range 0-1)
TC = Tree count or number of trees. 
Ground	truth	(transect	data)
(a)	Male	to	Female	ratio	
(b)	HCP_LCP	to	All	ratio
 0	– Only	enough	cones	to	determine	gender
 1	– Low	Cone	Production	(LCP)	tree
 2	– High	Cone	Production	(HCP)	tree
(c)	Cones	per	tree	
(d)	Pollens	per	cone	
(d)	Age	
(Height		&	edge	effect)
Juniper	Species	and	Pollination	Season
 Juniper	Ashei (Ja) is	mostly	found	to	be	distributed	over	Texas	and	
Oklahoma	and	pollinates	during	December	to	January.	Thus,	the	
dispersion	of	juniper	pollens	during	December‐January	is	mostly	
restricted	to	Ja type..
 Juiper Pinchotti (Jp)	is	mostly	distributed	over	Texas	and	pollinated	
during	late	September‐November.	Thus,	the	dispersion	of	juniper	
pollens	during	this	period	is	mostly	restricted	to	Jp type.	
 Juniper	monosperma (Jm)	and	Juniper	scopulurum (Js)	are	
prevalent	in	New	Mexico	and	pollinates	during	March‐May period.	
Thus,	the	dispersion	of	juniper	pollens	during	this	period	is	mostly	
restricted	to	Jm and	Js type.	
Field	data
• Juniper	Ashei
• Juniper	Pinchotii
• Juniper	monosperma and	scopulorum
Information	Needed	(to	update	mask):
For	all	sampling	sites:
• HCP/LCP/0
• Male/Female	ratio
• Number	of	trees	(tree	density)
• Number	of	cones
• Pollens/cone
Juniper	PinchotiiJuniper	Ashei Juniper	
Monosperma	&	Scopulorum
Spatial	resolution:	~1	km	(990	m)
December	to	January late	September‐November
March‐May
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PREAM
Pollen Plume Simulation for Juniper Emissions
For the period 15 December 2009 – 1 January 2010 
Run by Slobodan Nickovic, September 2012
Atmosphere Model Setup 
Model horizontal domain: Southwest US
Model resolution: ~40 km
Simulation period: 
15 December 2009 – 1 January 2010
Boundary conditions: 1 degree global forecasts used to refresh
• initial conditions every 24 hours
• boundary conditions every 6 hours
PREAM
Pollen Plume Simulation for Juniper Emissions
For the period 15 December 2009 – 1 January 2010
PREAM – Pollen Regional Atmospheric Model
Derived from DREAM (dust), modified to simulate pollen 
‐ 4 particles bins
‐ PREAM is online driven by the NCEP/ETA
Emission: 
‐ Viscous‐sublayer parameterization
‐ Emission dependent on friction velocity
The PREAM 15 December 2009– 1 January 2010 Run
• “cold start” used for the very first day
• simulated 3D concentration from the previous day 
is the initial condition for the next day simulation

Model Validation ( Juniper pollen count/ m2 )
Observed                         Forecast   
Status of Transitioning 
Pollen Data Into NM EPHT
• Progress in year 1 
(green oval):
• Prepare interface 
for health client 
server
• Prepare server for 
pollen data output
• Test server functions: 
(yellow oval):
• Dependent upon 
receiving sample 
data from modeling 
team
• Activities for out 
years: (blue boxes)
Post‐processing Workflow
Newport, Rhode Island Sep 18‐20, 2012
Sample Animation for Juniperus ashei
(Dec 29, 2010 to Jan 1, 2011)
Newport, Rhode Island Sep 18‐20, 2012




Integration of Airborne Aerosol Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

Integration of Airborne Aerosol Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

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