Transcript Chang, Hsin-I - Chequamegon Ecosystem

Direct Observations of Aerosol
Effects on Carbon and Water
Cycles Over Different
Landscapes
Hsin-I Chang
Ph D student
Department of Atmospheric Sciences
Email: [email protected]
Advisor: Dr. Dev Niyogi
Department of Atmospheric Sciences/Agronomy
Email: [email protected]
Purdue University
Collaborators:
Kiran Alapaty, UNC Chapel Hill, currently with National Science Foundation
Fitz Booker, USDA/ ARS, Air Quality-Plant Growth and Development Unit, NC
Fei Chen, National Center for Atmospheric Research, Boulder
Ken Davis, Department of Meteorology, Penn State University, University Park, PA
Lianhong Gu, Oak Ridge National Laboratory, TN
Brent Holben, GSFC, NASA, Greenbelt, MD
Teddy Holt, N. C. State Univ and Naval Research Laboratory, Monterey, CA
Tilden Meyers, ATDD/NOAA, Oak Ridge, TN
Walter C. Oechel, San Diego State University
Roger A. Pielke Sr. and Toshi Matsui Colorado State University
Randy Wells, Department of Crop Science, N. C. State University, Raleigh, NC
Kell Wilson, ATDD/NOAA, Oak Ridge, TN
Yongkang Xue, Department of Geography, UCLA, Los Angeles, CA
Outline:
Introduction
Importance and Hypothesis
Data and Methodology
Results and Discussion
Summary
Future Work
- AEROSOLS AFFECT THE
RADIATIVE FEEDBACK OF THE
ENVIRONMENT
-Majority of the studies have
focused on the ‘temperature
effects’ =>whether aerosols
cause cooling or warming effect
in the regional climate.
-In this study we propose that:
Aerosols also have a
significant biogeochemical
feedback on the regional
landscapes, and should be
considered in both carbon
and water cycle studies
Why would aerosols affect biogeochemical
pathways?
Total solar radiation = (Diffuse + Direct) solar radiation
For increased Cloud Cover or Increased Aerosol Loading,
Diffuse Component Increases => changes the DDR (Diffuse to Direct
Radiation Ratio)
Hypothesis:
Increase in DDR will impact the Terrestrial Carbon and Water
Cycles through Transpiration and Photosynthesis changes
(Transpiration is the most efficient means of water loss from land surface;
Photosynthesis is the dominant mechanism for terrestrial carbon cycle)
Data :
Need simultaneous observations of carbon and
water vapor fluxes, radiation (including DDR), and
aerosol loading.



Carbon, Water vapor flux and plant information –
Ameriflux
Radiation (including DDR) information from Ameriflux or
NOAA Surface Radiation (SURFRAD) sites
Aerosol loading information from NASA Aerosol Robotic
Network (AERONET)
Study sites
Six sites available across the U.S. that have
information on the required variables for our
study (AOD,diffuse radiation and latent heat flux).
Willow Creek, WI
Lost Creek, WI
(mixed forest,00,01)
Ponca, OK
(wheat 98,99)
Barrow, AK
(grassland 99)
Bondville, IL
(agriculture,
C3 / C4, 9802)
Walker Branch, TN
(mixed forest 2000)
Hypothesis to be tested from the
observational analysis :
Increase in the aerosol loading could increase
CO2 and latent heat flux at field scales


This would indicate a more vigorous terrestrial carbon
cycle because of aerosol interactions
This would also indicate potential for changes in the
terrestrial water cycle because of aerosol loading
Does DDR Change Cause Changes in the CO2
Flux at Field Scale?
Walker Branch Forest Site
-CO2 flux into the vegetation (due
to photosynthesis) increases with
increasing radiation
-For a given radiation, CO2 flux is
larger for higher DDR
Rg-total radiation
Rd-diffuse radiation
negative values indicate CO2 sink
(into the vegetation)
Effect of DDR on field scale CO2 Flux
Does DDR Change
Cause Changes in the
CO2 Flux at Field
Scale?
Yes!
Changes in CO2 flux Normalized for
changes in global Radiation versus
Diffuse Fraction
Increase in DDR
appears to increase
the observed CO2 flux
in the field
measurements.
Do clouds affect CO2 flux at Field Scale?
- Yes, clouds appear to affect field scale CO2 fluxes significantly.
-CO2 flux into the vegetation (due to photosynthesis) is larger for cloudy
conditions
Do Aerosols affect field scale CO2 Flux?
- Increase in AOD (no cloud conditions) causes increase in DDR (diffuse fraction)
- CO2 flux into the vegetation (due to photosynthesis) is larger for higher AOD
conditions
- Aerosol loading appears to cause field scale changes in the CO2 flux
Are these results true for different
landscapes?
Forests
Croplands
Grasslands
For Forests and Croplands, aerosol loading has a positive effect on
CO2 flux, where there shows a CO2 flux source at Grassland sites.
Hypothesis for LHF-aerosol relation:
At high vegetation LAI (leaf area index):
LHF is mainly due to transpiration;
with increasing aerosols,diffuse radiation
increases and air / leaf temperature decreases,
=> increase in transpiration and thereby
increase LHF
At low vegetation LAI:
LHF is mainly due to evaporation;
with increasing aerosols,diffuse radiation
increases, and air / leaf temperature decreases,
=> reduce the evaporation and therefore LHF
decreases.
Clustering AOD-LHF relation into different
landscapes.
350
500
450
300
350
300
250
200
150
WB(00)
LC(01)
WC(00)
100
50
400
300
200
100
BV(98)
BV(00)
BV(02)
BV(99)
0
0.2
0.4
0.6
Aerosol Optical Depth
Forest site
0.8
1
0
0.2
0.4
0.6
0.8
1
Aerosol Optical Depth
Cropland
250
200
150
100
50
Shidler 1998(LHF)
Shidler 1999(LHF)
0
-50
BV(01)
-100
0
Latent Heat Flux (W/m2)
Latent Heat Flux (W/m2)
La tent Heat Flux (W/m2)
400
1.2
Barrow 1999(LHF)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Aerosol Optical Depth
Grassland
(LHF values opposite in sign)
Latent heat flux appears to generally decrease with
increasing Aerosol Optical Depths for most of the
studied sites.
Observed data analyses:
Walker Branch (Forest site):
May 2001
June - Aug 1998
400.00
500
450
400
350.00
250.00
avg LHF
avg LHF
300.00
200.00
150.00
100.00
100
50
0
50.00
0.00
0.00
350
300
250
200
150
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Aerosol Optical Depth
0
0.2
0.4
0.6
0.8
1
Aerosol Optical Depth
Low LAI case (LAI < 2.5)
High LAI case (LAI >3)
LHF decrease with aerosol loading
LHF increase with aerosol loading
However, analyzed results vary for different
landscapes
Bondville (soy bean site(C3)):
BV June-Aug 1998
400
320
350
Latent Heat Flux (W/m2)
Latent Heat Flux (W/m2)
BV June-Aug 1998
340
300
280
260
240
220
300
250
200
150
200
180
0.1
0.2
0.3
0.4
Aerosol Optical Depth
Low LAI case
0.5
0.6
100
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Aerosol Optical Depth
High LAI case
For higher LAI, the AOD –ve dependence seems to be decreasing
Summary for water cycle study:
Forest:
- High LAI: LHF increase with AOD
- Low LAI: LHF decrease with AOD
need to consider Leaf effect for the flux change.
Corn: LHF decrease with AOD; Leaf area changes have more
influence on LHF compare to Air Temperature and Soil Moisture.
Soybean: LHF decrease with AOD; analyses found that Soil Moisture
may have influence on the decreasing trend of Latent Heat Fluxwithout Soil Moisture effect, LHF increase with aerosol loading.
Grassland: LHF increase with AOD; not considering leaf effect. (Soil
Moisture data not available)
Conclusions:
Aerosols affect land surface processes

Results confirmed for different canopy conditions (mixed forests,
corns, soybeans, winter wheat and grasslands).
CO2 sink increases with increasing aerosol loading over
forests and croplands (both C3 and C4)
CO2 source increases with increasing aerosol loading
over grasslands
Water Vapor Flux generally decreases with increasing
aerosol loading

Exceptions were one grassland, and high LAI forest sites
Design of experiments
Design configuration: Need to design confounding
Environmental Confounding:
(1) crop site: USDA Raleigh, Purdue AG Center
(2) forest site: ChEAS (?)
Radiation decreases in quantity, changing quality and spectral
changes and higher DDR.
Changes in temperature will change in VPD,
evaporation/transpiration, soil moisture, emmisivity and albedo, etc.
Experiments:
(1) for crops: use high/low diffuse radiation shed; change soil
moisture stress and stress from temperature and humidity => need
to design special chambers.
(2) for forest: repeat similar experiments for crops and need to
examine vertical profiles => responses in different vertical levels
may be important.
Related work:
Analysis for AOD – LHF
effects is still
underway. (need to
consider interaction
terms such as LAI,
soil moisture)
LI6400 CO2 / H2O Flux
system
Leaf and Canopy scale
measurements of CO2 and
Water Vapor Flux for plants
grown under different soil
moisture conditions at USDA
Facility in Raleigh.
Related work:
Effect of Diffuse Radiation
(Clouds and Aerosols) on
Plant Scale Response
Modeling of the plant scale
response for changes in
Diffuse Radiation
(with Dr. Booker and Dr.
Wells)
Potted plants
were grown in 2
sheds with
different diffuse
radiation screens
and CO2 / H2O
Exchange
Measured
Direct and diffuse radiation shed
Ongoing and Future work:
Regional Analysis of DDR Changes
on Latent Heat Fluxes using satellite
(MODIS) dataset.
Continue on GEM-RAMS
Modeling System for isolating the
effects of different variables in
understanding the aerosol
feedbacks on the land surface
response.
Thank you
Bondville (corn site(C4)):
BV LHF vs AOD 1999
BV LHF vs AOD 1999
Latent Heat Flux(W/m2)
Latent Heat Flux (W/m2)
450
300
250
200
400
350
300
250
200
150
150
0
0.2
0.4
0.6
0.8
Aerosol Optical Depth
Low LAI case
1
1.2
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Aerosol Optical Depth
High LAI case
LHF increase with aerosol
loading up to certain level.
AOD-LHF relation after accounting for
both leaf and air temperature effects:
BV June-Aug 1999
BV June-Aug 1998
3
8
LHF/LAI/Air Temperature
LHF/LAI/Air Temperature
7
2.5
2
1.5
1
6
5
4
3
2
1
0.5
0
0
0.1
0.2
0.3
0.4
0.5
0.6
Aerosol Optical Depth
corn site
0.7
0.8
0
0.2
0.4
0.6
0.8
Aerosol Optical Depth
soy bean site
Compare with previous slides, Latent heat fluxes still decrease
with aerosol loading without leaf and temperature effects.
1
Accounting for Soil Moisture effect:
BV 1999
BV 2000
2500
Latent Heat Flux/Soil Moisture
Latent Heat Flux/Soil Moisture
2500
2000
1500
1000
500
0
0.2
0.4
0.6
0.8
Aerosol Optical Depth
Corn Site
1
1.2
2000
1500
1000
500
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Aerosol Optical Depth
Soybean Site
For both high and low SM conditions, LHF decreases with aerosol
loading for agricultural sites (not shown).
With no Soil Moisture effect, Latent Heat Flux increases with aerosol
at Soybean site.
Glazing material treatment effects on average
photosynthetic photon flux density (PPDF) at upper canopy
height between 0800-1600 h (EST) during the experimental
period. The ratio of diffuse PPFD radiation to total PPDF
radiation is also shown. Values are means ± SE. Values
followed by a different letter were statistically significantly
different (P ≤ 0.05).
Glazing Material
Parameter
Ambient
Clear
Diffusing
PPFD (µmol m-2 s-1)
958 ± 6 a
840 ± 6 b
755 ± 5 c
0.389 ± 0.002 a
0.415 ± 0.002 b
Diffuse: Total
Soybean biomass and yield responses to growth under Clear and Diffusing
glazing materials (mean ± SE). Plants were harvested for determination of
biomass (Biomass) at 88 days after planting (DAP), and for determination of
seed yield (Yield) at 153 DAP. Values in parenthesis indicate percent change
from the Clear treatment. Statistics: P ≤ 0.1 (†).
Glazing Material
Harvest
Parameter
Clear
Diffusing
Height (cm)
55.6 ± 1.4
56.1 ± 1.4
Branch number (plant-1)
17.3 ± 1.4
18.0 ± 1.4
Leaf dry mass (g plant-1)
45.4 ± 3.0
52.0 ± 3.0
Main stem dry mass (g plant-1)
19.2 ± 1.5
19.8 ± 1.5
Branch dry mass (g plant-1)
51.7 ± 3.9
63.0 ± 3.9 (+22%) †
Pod dry mass (g plant-1)
67.3 ± 8.0
75.4 ± 8.0
Root mass (g plant-1)
30.1 ± 2.6
28.8 ± 2.6
Total dry mass (g plant-1)
213.7 ± 15.2
239.0 ± 15.2
Main stem leaf area (m2 plant-1)
0.19 ± 0.01
0.20 ± 0.01
Branch leaf area (m2 plant-1)
1.21 ± 0.08
1.41 ± 0.08 (+16%) †
Total leaf area (m2 plant-1)
1.40 ± 0.08
1.61 ± 0.08 (+15%) †
Pod number (plant-1)
397 ± 32
394 ± 32
Seed mass (g plant-1)
173 ± 15
179 ± 15
Mass per seed (g)
0.20 ± 0.01
0.19 ± 0.01
Stem mass (g plant-1)
43 ± 4
49 ± 4
Biomass
Yield
Net photosynthesis (A) of upper canopy leaves and whole-plants
treated with either Clear or Diffusing glazing materials (mean ± SE).
Net photosynthesis of upper canopy leaves on four plants per treatment
was measured weekly between 48 and 105 DAP (seven occasions). In
addition, whole-plant A of three sets of three plants was measured on
56 DAP. Treatment effects on A were not statistically significant.
Glazing Material
Clear
Diffusing
Upper canopy leaves
(µmol m-2 s-1)
28.4 ± 3.3
26.4 ± 2.6
Whole-plant
(µmol plant s-1)
14.7 ± 2.3
17.9 ± 0.7