evaluation of atp3 unified field study results to identify the...
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1 ASU Confidential Proprietary
Evaluation of ATP3 Unified Field Study Results to Identify the Primary Factors Affecting Pond
Productivity Braden Crowe , Valerie Harmon, John McGowen, Todd Lane, Eric Knoshaug, Thomas Dempster, Thomas Igou, Chris Withstandley, Marcela Saracco , Phil
Pienkos
2015 Algae Biomass Summit Washington D.C.
September 1, 2015
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Motivation
2
What is a reasonable biomass yield?
5+ fold difference!
Huntley 2015
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Motivation
3
What is a reasonable biomass yield?
2013 harmonized value, ~13 g/m2-
day
Huntley 2015
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Test bed locations
4
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Test bed locations
5 Venteris 2014
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Test bed locations
6 Venteris 2014
Florida>Arizona>California>Georgia
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Controlled variables
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Controlled variables
• pH • Paddle wheel speed • Strain • Nutrient regime • …
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Year 1 of the UFS – What did it look like?
9
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Year 1 of the UFS – What did it look like?
10 Productivity calculated as slope of the batch growth curve. Incident light intensity and pond water temperature averaged over this time interval
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11
Daily Biomass Productivity, g AFDW/m2/day
Daily Productivity (g/m2-day) Based on change in total biomass in pond between AFDW data points (1-2 days typically) (area 4.2 m2, volume 1025L at 25 cm)
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N. oceanica batch productivity
0
2
4
6
8
10
12
14
0 50 100 150 200 250 300 350
Bio
mas
s Pr
oduc
tivity
, g A
FDW
/m2-
day
Day of year
Southwest, desert Pacific, tropical Western, Coastal Southeast, Florida Southeast, GA
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N. oceanica, annual average productivity
0
1
2
3
4
5
6
7
8
9
10
Bio
mas
s Pr
oduc
tivity
, g
AFD
W/m
2-da
y
Southeast, Florida Pacific, tropical Southwest, desert Western, Coastal Southeast, GA
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N. oceanica, influence of temperature
0
2
4
6
8
10
12
14
5 10 15 20 25 30 Bio
mas
s Pr
oduc
tivity
, g A
FDW
/m2-
day
Average pond water temperature over batch phase, ˚C
Southwest, desert Pacific, tropical Western, Coastal
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N. oceanica, influence of temperature
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0
2
4
6
8
10
12
14
0 10 20 30 40
Spec
ific
grow
th ra
te, 1
/day
Bio
mas
s Pr
oduc
tivity
, g A
FDW
/m2-
day
Average pond water temperature over batch phase, ˚C
ATP3, all sites umax, Huesemann 2013
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Average incident light intensity and productivity are linearly correlated
y = 0.0405x - 1.2961 R² = 0.8811
0
2
4
6
8
10
12
14
0 50 100 150 200 250 300 350 400 Bio
mas
s pr
oduc
tivity
, g A
FDW
/m2-
day
Average incident light intensity, W/m2 Southwest, desert Pacific, tropical Western, Coastal
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Influence of dilution rate, Desert Southwest
0 2 4 6 8
10 12 14 16 18 20
0 50 100 150 200 250 300 350
Bio
mas
s pr
oduc
tivity
, g A
FDW
/m2-
day
Day of Year
Batch 0.21 0.32
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Influence of dilution rate, Desert Southwest
0
2
4
6
8
10
12
14
16
18
20
Bio
mas
s pr
oduc
tivity
, g A
FDW
/m2-
day
0.21/day 0.32/day Batch
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Influence of dilution rate, Desert Southwest
0
2
4
6
8
10
12
14
16
18
20
Bio
mas
s pr
oduc
tivity
, g A
FDW
/m2-
day
0.21/day 0.32/day Batch
~30 MT/ha-yr
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Influence of dilution rate, Desert Southwest
0
200
400
600
800
1000
1200
0
5
10
15
20
25
30
35
40
6/30 0:00 7/1 0:00 7/2 0:00 7/3 0:00 7/4 0:00
Inci
dent
ligh
t int
ensi
ty, W
/m2
Pond
wat
er te
mpe
ratu
re, ˚
C
P1, water temperature P2, water temperature P3, water temperature P4, water temperature P5, water temperature P6, water temperature
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• Annual average productivity highest in Southeast Florida (~9.5 g AFDW/m2-day), although still low
• Venteris et al. productivity maps reasonably accurate, although rain affects underestimated
• Dilution rate doesn’t seem to matter, at least for N. oceanica
• High temperature of feed water potentially skews dilution rate interpretation
Conclusions
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Data available via Open EI
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Acknowledgments Florida Algae Steven Schlosser Chris Withstandley Mary Riddle Nancy Pham Ho (FIT) UTEX Schonna Manning Jerry Brand Commercial Algae Management Albert Vitale Robert Vitale Harmon Consulting Valerie Harmon
Cellana Marcella Saracco Egan Rowe Emily Knurek Kate Evans Peter Prentiss Reyna Javar Kari Wolff Keao Bishop-Yuan Christina Boyko Charlie O’Kelley Sandia National Labs Ron Pate Todd Lane Patricia Gharagozloo Thomas Reichardt Pamela Lane Deanna Curtis Kunal Poorey Lucy Cui Jessica Drewry NREL Phil Pienkos Lieve Laurens Ed Wolfrum David Crocker Stefanie Van Wychen Eric Knoshaug Ryan Davis
ASU Gary Dirks John McGowen Thomas Dempster Milt Sommerfeld William Brandt Pete Lammers Jessica Cheng Jordan McAllister Sarah Arrowsmith David Cardello Theresa Rosov Mary Cuevas Jeffrey Prairie Richard Malloy Xuezhi Zhang Henri Gerken Pierre Wensel Linda Boedeker Sarah Mason Travis Johnson Sydney Lines Wyatt Western Mariah Patton Maria Bautista Carlos Luna Delaney De Hertogh Shaylin Mcghee Caden Offield
Cal Poly Tryg Lundquist Braden Crowe Garrett Murawsky Eric Nicolai Aydee Melgar Gulce Ozturk Kaitlyn Jones Michael Antoine Trung K Tran Jake Bender Heather Freed Daniel McBroom Michele Hendrickson Gerard Nguyen Deven Diliberto Jack Sunderland Dan Averbuj Ann Marie Sequeira Lauren Miller Michele Hendrickson Emily Wang Jack Sunderland Ann Marie Sequeira Soroush Aboutalebi Lauren Miller Samantha Lui Letty Thottathil …..and more
Georgia Tech Thomas Igou Yongsheng Chen Steven Van Ginkel Thomas Igou Zixuan Hu Fariha Hassan Jerry Duncan Frazier Woodruff Shusuke Doi Hao Fu Patricia Penalver-Argueso Allison Dunbar Allison Carr Sichoon Park Priya Pradeep Terry Snell Catherine Achukwu Christine Yi
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Seasonal Variation in Yield Productivity
Nannochloropsis oceanica KA32 Chlorella vulgaris LRB-AZ-1201
• Typically ~4-fold or less difference in yield productivity across the seasons at any given site.
• GT experienced unusually wet and cold Winter season increasing the yield productivity differential.
• Greater variation in seasonal productivity for KA32