Carbonyl sulphide
eddy covariance fluxes as a proxy
for gross primary production
Arnaud P. Praplan
Division of Atmospheric Sciences, University of Helsinki, Helsinki, Finland
3rd ICOS Finland Science Workshop
28.5.2014
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27/05/14
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Introduction (I)
Carbonyl sulphide (COS = OCS)


Most abundant sulphur containing natural trace
gas in the atmosphere (~500 pptv)
Seasonal variations
(stronger in the Northern Hemisphere)

Low reactivity → long lifetime (3-4 years)

Vertical gradient
Campbell et al. (2008)
Montzka et al. (2012)
Berry et al. (2013)
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Introduction (II)
OCS sources and sinks (1)
?
DMS
(SC2H6)
...or 2.5 Tg[S] or 0.94 Tg[C]
(Atmosphere: 720'000 Tg[C])
Chin and Davis (1995)
Watts (2000)
Falkowski (2000)
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Introduction (III)
OCS sources and sinks (2)
...are roughly balanced
2.5
Photolysis
Reaction with O(3P)
Reaction with OH
Vegetation
Annual flux (Tg/yr)
2
largest
Oxic soils
Anthropogenic (direct)
1.5
uncertainty
Biomass Burning
CS2 oxidation
Sinks
Sources
DMS oxidation
1
Precipitation
Volcanism
Wetlands
Anoxic soils
0.5
Coastal ocean (including salt-marshes and estuaries)
Open ocean
0
Sinks
Sources
Watts (2000)
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Introduction (IV)
Eddy covariance (EC)


Burba (2013)
Statistical method to determine exchange rates of
trace gases over ecosystems.
No single methodology, but unifying networks
(e.g. ICOS).
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Introduction (V)
Gross primary productivity
￶
Vargas et al. (2012)
Kolari et al. (2009)
GPP: Gross primary productivity
= 0 (if solar elevation angle<0.02)
= -NEE+Reco
= from light response
(9 days moving time window)
NEE: Net Ecosystem Exchange
= measued
= -GPP+Reco
Reco: ecosystem Respiration
(always measured, night time)
RAp: plant respiration
RS: soil respiration
RAs: autotrophic soil respiration
Rh: heterotrphic soil respiration
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Introduction (VI)
GPP from OCS EC fluxes
CO2 + H2O ↔ H+ + HCO3reversible
OCS + H2O → H2S + CO2
irreversible (enzymatic)
Here: LRU* ~1.6 (Leaf-scale relative uptake)
(leaf-scale normalized ratio of COS to CO2 assimilation rates (diffusivity, dissolution,
reaction rates), ignore soil)
Asaf et al. (2013)
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Introduction (VII)
SMEAR II: Hyytiälä



Station for Measuring
Ecosystem-Atmosphere
Relations
located in a boreal pine
forest environment
(99% Scots pine)
comprehensive and
continuous
measurements
–
gas phase
–
particles
–
ions
Kulmala et al. (2001)
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Introduction (VIII)
COS measurements (2013)
127m



23m
Location:
Eddy tower/REA cottage
(close to main SMEAR II
cottage and mast)
Sampling
Above canopy (23m)
Period:
Since April 2013
(with interruptions)
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“COS instrument” (I)
COMPACT CW-QC-TILDAS-76-CS

Continuous Wave - Quantum Cascade –
Tunable Infrared Laser Differential Absorption
Spectrometer – 76 – Carbonyl Sulphide
= “QCL Mini Monitor” (1-20 Hz)
0.5 L, 30-60 Torr
2050 cm-1
(T-depenent)
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“COS instrument” (II)
absorption spectrum
Beer-Lambert Law
N = A / (σ L)
OCS
CO2
H2O
N: number density
A: fractional absorption
σ: absorption cross section
L: optical path length
→ no calibration required!
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Results (I)
Mixing ratio time series
Montzka et al. (2012)
Hyytiälä 2013 (SMEAR II)
Southern hemisphere
Northern hemisphere
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Results (II)
CO2 and H2O
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Results (III)
OCS fluxes
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Results (IV)
sites comparison
SMEAR II, Hyytiälä (Finland)
3 pine forests, wheat and
cotton fields (Israel)
Asaf et al. (2013)
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Results (V)
GPPCOS
Pine forest, Israel
(710mm annual precipitation)
Pine boreal forest (SMEAR II), Finland
(700mm annual precipitation)
Asaf et al. (2013)
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Results (VI)
GPPCOS (corrected for night flux)
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Results (VII)
GPP comparison
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Results (VIII)
Night vs day flux
Night: ca. - 6 pmol m-2 s-1
Day: ca. - 25 pmol m-2 s-1
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Preliminary results 2014 (I)
Mixing ratio
2013
2014
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Preliminary results 2014 (III)
Spring comparison (1)
2013
2014
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Preliminary results 2014 (III)
Spring comparison (2)
2013
(final fluxes)
2014
(preliminary fluxes)
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Conclusions

We derived sub-canopy OCS fluxes in Hyytiälä.

We also derived GPP values based on OCS fluxes.



The mini QCL Mini Monitor agrees well with the LICOR instrument (CO2 and H2O) fluxes
Due to low mixing ratio and trouble with the
instrument, COS fluxes are noisy.
Measurement restarted in 2014 show a reduced
scattering.
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Future work

Data filtering? Which criteria?

Integration in the online processing/plotting
(http://www.atm.helsinki.fi/Eddy_Covariance/OnlineECdata.php)

Compute GPP directly from OCS flux routinely?

Model(s) integration?

Effect of snow? Other effects?
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Thank you!
Questions? Comments?
University of Helsinki:
Timo, Ivan, Pasi, Sami
Aerodyne Research, Inc.:
Mark
Academy of Finland
Center of Excellence
(projects no 1118615 and 272041)
Nordic Center of Excellence
CRAICC
SMEAR II:
Janne, Veijo
The spring campaigns
2013/2014 “shifters”
ICOS 271878,
ICOS-Finland 281255
and ICOS-ERIC 281250
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