Pieber, Simone: Simulations of atmospheric CO₂ and δ¹³C-CO₂ compared to real-time observations at the high altitude station Jungfraujoch

Simone.Pieber@empa.ch – Laboratory for Air Pollution and Environmental Technology ICOS Science Conference 2020 Page 1Page 1Simone.Pieber@empa.ch – Laboratory for Air Pollution and Environmental Technology ICOS Science Conference 2020
Pieber SM1, Tuzson B1, Henne S1, Karstens U2, Gerbig C3, Brunner D1,
Steinbacher M1 , Emmenegger L1
1 Laboratory for Air Pollution and Environmental Technology at Empa, Dübendorf, Switzerland
2 ICOS Carbon Portal, Lund University, Sweden
3 Max Planck Institute, Jena, Germany
SIMONE.PIEBER@EMPA.CH
MSc
Environmental &
Analytical Chemistry
PhD @ETH-Z
Atmospheric &
Aerosol
Chemistry
currently:
PostDoc @Empa
Atmospheric
Trace Gases &
Stable Isotopes
Upcoming Project (2021+)
GHGs & Pollutants
from Wildfires
© Konsta Punkka
Simulations of atmospheric CO2 and δ13C-CO2 compared to
real-time observations
at the high altitude station
Jungfraujoch

Jungfraujoch,
Swiss Alps,
3580 m asl
European and Global Background
Air Quality Monitoring since around 1970
ICOS Class 1
© Konsta Punkka
CO2

12
C
16
O
18
O
13
C
16
O2
Lukas Emmenegger (Empa)
with QCLAS optical unit in 2008
Natural Abundance
12C16O2 98.42 %
13C16O2 1.100 %
12C16O18O 0.395 %
δ Notation
𝛿𝛿13C = (
[13C/12C]𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
[13C/12C]𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅
− 1)
𝛿𝛿18O = (
[18O/16O]𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
[18O/16O]𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅
− 1)
continuous/in-situ QCLAS
2008
© Konsta Punkka
STABLE ISOTOPES OF CO2:
 Element with equal numbers of protons but different numbers of neutrons .
 Isotopes differ in relative atomic mass but not chemical properties.
 Chemical, physical and biological processes (may) fractionate between different isotopes.
 Ideal tracers of environmental processes.
CO2
Jungfraujoch,
Swiss Alps,
3580 m asl
European and Global Background
Air Quality Monitoring since around 1970
ICOS Class 1

Outline
Methods:
(a) Quantum Cascade Laser Absorption Spectroscopy
(b) Atmospheric simulations
I. Decadal trend &
seasonality of
CO2, δ13C and δ18O
observations
II. CO2 simulations at JFJ:
contributions per
process, plant and fuel type
III. δ13C-CO2
simulation estimates
vs. observations

Measurement Technique
References:
Nelson et al., 2008
Tuzson et al., 2008ab
Sturm et al., 2013
© Béla Tuzson
QCLAS
Empa, B. Tuzson & L. Emmenegger
Transmittance,%
Wavenumber, cm-1
1.0
0.9
0.8
2310.0 2310.2 2310.4
 4.3 µm pulsed QC laser,
 scans 3 spectral lines, frequency near 2310 cm-1
 2 multi-pass cells (sample and reference)
 spectral ratio method, external calibration

STILT-ECMWF
(Carbon Portal)
FLEXPART-
COSMO
(Empa)
Atmospheric Transport Simulations
Meteorological Input
- ECMWF (25x25 km)
- COSMO7 (7x7 km)
Lagrangian Particle Dispersion Model (LPDM), 3h time-resolution
- STILT Carbon Portal, U. Karstens / MPI-BGC, C. Gerbig
https://stilt.icos-cp.eu/worker/
- FLEXPART Empa, S. Henne/D. Brunner
Boundary conditions
- Jena CarboScope for CO2 MPI-BGC, C. Rödenbeck
- Scaling Factors for δ13C-CO2 NOAA)
Regional fluxes
- Anthropogenic: EDGAR v4.3 for 14 fuel types JRC, G. Janssens-Maenhout
- Biosphere: VPRM v3/v2020 for 7 PFTs MPI-BGC, C. Gerbig
Source δ13C
- Literature-based assumptions
Example: LPDM Domain Boundary

Simone.Pieber@empa.ch – Laboratory for Air Pollution and Environmental Technology ICOS Science Conference 2020 Page 7Page 7Simone.Pieber@empa.ch – Laboratory for Air Pollution and Environmental Technology ICOS Science Conference 2020© Konsta Punkka
RESULTS
I.
II.
III.

I. Decadal Trend & Seasonalityδ18O,‰CO2,ppmδ13C,‰
380400420-2-1012
2010 2012 2014 2016 2018
-10.0-9.0-8.0-7.0
-0.50.00.5
J F M A M J J A S O N D
-0.4-0.20.00.20.4-505
January to December, mean±1SD
(2009-2017)
August
April
June
highly time-resolved measurments (10-min),
from 2009 to 2017
+2.31 ppm yr-1
-0.03 ‰ yr-1
+0.00 ‰ yr-1
2010 2012 2014 2016 2018 J F M A M J J A S O N D
Δ=9.9 ppm
Δ=0.47 ‰
Δ=0.73 ‰

II. «Regional signal»: shorter-term CO2 variationsΔCO2,ppm
CO2 event characterisation:
(1) Intensity and frequency of events
(2) Geographic origin of events
(3) Source composition of events
a) Model simulations
b) Isotopic composition
A B C D E F G H I
5101520253035
ΔCO2,ppm
Local
Pollution
ΔCO2>5 ppm (Oct-Apr) as function of
residence time clusters
North-
West
Central
Europe
West
South-
West
South
-East
East
(2) Intensity & Geographic Origin(1) Intensity & Frequency
ΔCO2
frequency Oct-Apr,
days yr-1
avg. min-max
>5 ppm 35 18-53
>10 ppm 9.7 2-21
>15 ppm 4.2 1-6

II. CO2 simulation vs. observation
420
400
380
CO2,ppm
420
400
380
FLEXPART-COSMO
STILT-ECMWF
OBS
SIM+BG
BG
REGIONAL
SIGNAL
TOTAL SIGNAL =
REGIONAL SIGNAL + BACKGROUND

420
400
380
CO2,ppm
420
400
380
FLEXPART-COSMO
STILT-ECMWF
OBS
SIM+BG
BG
TOTAL SIGNAL =
REGIONAL SIGNAL + BACKGROUND
0.0
0.5
1.0
1.5
slope
0.0
0.2
0.4
0.6
0.8
1.0
r2
0.0
1.0
2.0
3.0
RMSE
0.0
0.5
1.0
1.5
slope
0.0
0.1
0.2
0.3
0.4
0.5
r2
a
b
c
a-2
b-2
STILT-
ECMWF
FLEXPART-
COSMO
STILT-
ECMWF
FLEXPART-
COSMO
all year
DJF-winter
MAM-spring
JJA-summer
SON-autumn
REGIONAL
SIGNAL
TOTAL
SIGNAL
1.8 – 2.8 ppm

-5.5
-4.5
-3.5
-2.5
-1.5
-0.5
0.5
1.5
2.5
1 2 3 4 5 6 7 8 9 10 11 12
regionalCO2,ppm
month of year
REGIONAL
SIGNAL
0.0
0.5
1.0
1.5
1 2 3 4 5 6 7 8 9 10 11 12
anthropoenic,ppm
month of year
0
1
2
3
4
5
1 2 3 4 5 6 7 8 9 10 11 12
respiration,ppm
-10
-8
-6
-4
-2
0
1 2 3 4 5 6 7 8 9 10 11 12
gee,ppm
month of year
ANTHROPOGENIC CO2
RESPIRATION
«UPTAKE»
May - SeptJan - Apr Oct - Dec

Example for 2013, https://stilt.icos-cp.eu/viewer/
CO2.fuel
CO2.net.biosphere
CO2.biospheric.respiration («RESP»)
CO2.photosynthetic.uptake («GEE»)
CO2.cement
CO2,ppm
GROSS RESPIRATION:
primarily cropland and mixed forests
II. CO2 simulations by fuel and process
Light & Heavy OIL
GAS
COAL
BIOMASS
RelativeContribution
2009-2017
CEMENT

fuel
formation
biomass is
strongly depleted
in 13C compared
to atmosphere
Ecosystem Respiration
(CO2 Source)
Photosynthetic Uptake
(CO2 Sink)
fossil and biogenic fueles
are consequently also
strongly depleted in 13C
compared to atmosphere
LAND
OCEANS
ATMOSPHERE
Fuel burning
(CO2 Emission)
using diverse fuels
and processes
(natural wildfires)
e.g.,
δ13C ~ -22‰ C3-Plants, dry
δ13C ~ -37‰ C3-Plants, tropical
δ13C ~ -12‰ C4-Plants
Respiration CO2
Fuel Burning CO2
e.g.,
δ13C ~ -24‰ coal
δ13C ~ -27‰ oil
δ13C ~ -44‰ gas
Atmospheric CO2
e.g., free troposphere or
marine boundary layer
δ13C= ~ -8.5‰
III. δ13C simulation

III. δ13C simulation
δ13Ces
Literature-
compilation
FOSSIL FUELS
OIL (liquid) -26.5‰
OIL_heavy
OIL_light
OIL_mixed
GAS (gas) -44.0‰
GAS_natural
GAS_derived
COAL (solid) -24.1‰
COAL_hard
COAL_brown
COAL_peat
BIOGENIC FUELS
BIOMASS (solid) -24.1‰
BIOGAS (gas) -60.0‰
BIOFUEL (liquid) -26.5‰
OTHER SOURCES
OTHER_solid (solid) -25‰
CEMENT -0‰
ECOSYSTEM (w/seasonality)
BIOSPHERE RESPIRATION -27 to -22‰
PHOTOSYNTHETIC UPTAKE -25 to -20‰
δmixed_es_sim = Σ(|fes_sim, i| × δes, i) / Σ(|fes_sim, i|)
FLEXPART-COSMO
CO2 subcategories
(in ppm)
Literature based
δ13Cemissions_signature in ‰
δambient_sim = [(fb×δb) + (Σ(fes_sim, i)×δmixed_es_sim)] / [fb+Σ(fes_sim, i)]
Background assumptions for the model
(CO2 and δ13C)
δmixed_es_sim
References:
Vardag et al., 2015
Vardag et al., 2016

III. δ13Cambient simulation vs. observation
400410420-9.5-9.0-8.5
Background
Pollution
CO2,ppmδ13C,‰
15th October 2015
00:00 08:00 16:00 00:00
-9.6-9.2-8.8-8.
00:00 04:00 08:00 12:00 16:00 20:00 00:00
d13C sim w / GPP
d13C sim w /o GPP
d13C obs
δambient,‰
observation
simulation (v1)
simulation (v2)
a
b g
f
d i
hc
je
FLEXPART-COSMO
winter,
DJF
spring,
MAM
summer,
JJA
autumn,
SON
STILT-ECMWF
all
year
regional CO2 observation
regionalCO2simulation
δambient,‰

Summary
THANK YOU!
Nine years of highly time-resolved
QCLAS measurements of atmospheric CO2, δ13C and δ18O
at the high alpine measurement site Jungfraujoch.
Nine years of CO2 simulations with 2 models:
FLEXPART-COSMO and STILT-ECMWF.
Simulated regional CO2 components at Jungfraujoch
dominated by biosphere respiration and uptake.
Best agreement of CO2 and δ13C-CO2 simulation with
observations is achieved in spring, autumn and winter,
larger discrepancies in summer.
Acknowledgements
HFSJG – High Altitude Research Stations Jungfraujoch & Gornergrat
Swiss National Science Foundation (ICOS-CH Phase 2) and
Swiss Federal Office for the Environment (BAFU) for supporting the Swiss RINGO activities
Atmosphere Open-Access Journal for my post-doctoral travel award 2020
SIMONE.PIEBER@EMPA.CH

Simone.Pieber@empa.ch – Laboratory for Air Pollution and Environmental Technology ICOS Science Conference 2020 Page 18
QCLAS for in-situ stable CO2 isotope measurements
Nelson DD, et al. 2008: https://link.springer.com/article/10.1007/s00340-007-2894-1
Tuzson B, et al, 2008a: https://link.springer.com/article/10.1007/s00340-008-3085-4
Tuzson B, et al, 2008b: https://doi.org/10.1016/j.infrared.2007.05.006
Tuzson B, et al, 2011: https://doi.org/10.5194/acp-11-1685-2011
Sturm P, et al, 2013: https://doi.org/10.5194/amt-6-1659-2013
STILT-ECMWF
Lin JC, et al, 2003: https://doi.org/10.1029/2002JD003161
Trusilova K, et al, 2010: https://doi.org/10.5194/acp-10-3205-2010
Vardag SN, et al, 2016: https://doi.org/10.5194/bg-13-4237-2016
Kountouris P, et al, 2018: https://doi.org/10.5194/acp-18-3047-2018
FLEXPART-COSMO
Stohl A, et al, 2005: https://doi.org/10.5194/acp-5-2461-2005
Baldauf, M et al, 2011: https://doi.org/10.1175/MWR-D-10-05013.1
Henne S, et al, 2016: https://doi.org/10.5194/acp-16-3683-2016
Pisso I, et al, 2019: https://doi.org/10.5194/gmd-12-4955-2019
Anthropogenic emissions inventory (EDGAR)
Janssens-Maenhout G, et al, 2019: https://doi.org/10.5194/essd-11-959-2019
Vegetation Photosynthesis and Respiration Model (VPRM)
Mahadevan P, et al, 2008: https://doi.org/10.1029/2006GB002735
Gerbig Ch., online at:
https://www.bgc-jena.mpg.de/bgc-systems/index.php/Staff/GerbigChristoph
CarboScope
Rödenbeck Ch., online at: https://www.bgc-jena.mpg.de/CarboScope/
δ13C-CO2 source signatures
e.g.,
CDIAC, online at https://cdiac.ess-dive.lbl.gov/
Vardag SN, et al, 2015 : https://doi.org/10.5194/acp-15-12705-2015
Vardag SN, et al, 2016. : https://doi.org/10.5194/bg-13-4237-2016
BIBLIOGRAPHY

BONUS SLIDES

Keeling plot intercept method
0.4-0.2-0.8400410420-9.5-9.0-8.5
Background
Pollution
δ18O,‰CO2,ppmδ13C,‰
15th October 2015
00:00 08:00 16:00 00:00
δ18O Signature
at 1/CO2=0:
-20.0 (±1.7) ‰
Pollution
Background
1/CO2, ppm-1
0.00235 0.00245 0.00255
δ18O,‰
-0.5-1.0-1.50.00.5
Pollution
Background
δ13C Signature
at 1/CO2=0:
-39.3 (±1.3) ‰
1/CO2, ppm-1
0.00235 0.00245 0.00255
δ13C,‰
-9.5-8.5-8.0-10.0-9.0

CO2,ppm
-10.0-9.0-8.0-7.0
δ13C,‰
-2-1012
2010 2012 2014 2016 2018
δ18O,‰
380400420
Time Series
GC-FID and IRMS data provided by MPI-BGC Jena (A. Jordan, H. Moossen, M. Rothe)

380 390 400 410 420
38039040041042
-9.5 -9.0 -8.5 -8.0 -7.5
-9.5-9.0-8.5-8.0-7.
-1.0 -0.5 0.0 0.5 1.0
-1.0-0.50.00.51.0
δ18O-CO2,‰CO2, ppm
QCLAS
δ13C-CO2, ‰
GC-FID IRMS
n=151
slope (se) = 0.98 (0.01)
n=141
slope (se) = 1.01 (0.11)
n=138
slope (se) = 1.00 (0.04)
IRMS
Comparison QCLAS vs IRMS and GC-FID, 2009-2017
GC-FID and IRMS data provided by MPI-BGC Jena (A. Jordan, H. Moossen, M. Rothe)

1. perform calculations:
STILT on-demand calculator
https://stilt.icos-cp.eu/worker/
2. view calculations:
STILT results visualisation:
https://stilt.icos-cp.eu/viewer/
3. analyze simulations output:
contact CP (U. Karstens) &
use Jupyter Notebooks
Atmospheric Transport Simulations at CP
JFJ

FLEXPART-COSMO
Empa, w/ inventory input from ICOS Carbon Portal & JRC
Transport Simulation w/ FLEXPART-COSMO
• FLEXPART (Lagrangian Particle Dispersion Model)
• COSMO (Numerical weather forecast model)
• CO2 Emissions and Transport Simulation
Emissions
• EDGARv4.3fuel (Emission Database from JRC)
fuel categories:
fossil: oil, coal, gas
biogenic: biofuels, biomass, biogas
others: peat- and wild-fires,
waste-as-industry-fuel
• VPRM
(Vegetation Photosynthesis and Respiration Model)
output:
biospheric respiration
photosynthetic uptake
• Literature based δ13C emissions signatures
Residence Time Clustering

E2
E4 E3
E1
STILT-ECMWF
FLEXPART-ECMWF
FLEXPART-COSMO
FLEXPART-ECMWF.cropped
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
(i) E1 vs E2 (ii) E3 vs E2 (iii) E1 vs E4 (iv) E3 vs E4
slope
7PFT
cropland
mixed forest
5PFT
a
b
c
0.0
0.2
0.4
0.6
0.8
1.0
r2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
BRMS

STILT-
ECMWF
FLEXPART-
ECMWF
FLEXPART-
COSMO
FLEXPART-
ECMWF.
cropped
E1 E2 E3 E4
winter
summer
winter
summer
winter
summer
winter
summer
all year all year all year all year
syntheticCO2(ppm)
time in UTC+1
summer

Pieber, Simone: Simulations of atmospheric CO₂ and δ¹³C-CO₂ compared to real-time observations at the high altitude station Jungfraujoch

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Pieber, Simone: Simulations of atmospheric CO₂ and δ¹³C-CO₂ compared to real-time observations at the high altitude station Jungfraujoch