Bert Scheeren and Peter Bergamaschi - Europa

First three years of CO 2 , CH 4 , N 2 O, and SF 6
observations, and 222 Radon-based emission estimates
from the JRC-Ispra (Italy) monitoring station.
1
What have we learned so far
Bert Scheeren and Peter Bergamaschi
European Commission Joint Research Centre
Institute for Environment and Sustainability
Ispra, Italy
Acknowledgements:
Dough Worthy, Martina Schmidt, Ingeborg Levin, Sander van der Laan, Ingrid van der
Laan-Luikx for their support and advice.

2
Outline
• Site description
• Time series
• 222 Radon based flux estimates
• Case studies
• TM5 model simulations of CH 4
• Link to monitoring networks
• Summary

Why is the JRC involved in monitoring GHGs
3
To be an active member of the European GHG monitoring community;
* contributing to the sparse GHG monitoring network in Southern Europe,
* having access to important databases for our inverse modeling activities.
To support regional scale emission estimates;
* providing direct input for inverse modeling,
* to allow model independent emission estimates based on 222 Radon.
Jungfraujoch
3580 m
Plateau Rosa
3480 m
JRC-Ispra
220 m
Po Valley
Monte Cimone
2165 m

The Ispra GHG monitoring site since 2007 (223 m asl)
4
15 m sampling mast
Agilent 6890N GC-FID/μ-ECD for CO 2 , CH 4 , N 2 O, SF 6
PICARRO G1301 for CO 2 and CH 4
ANSTO 222 Radon monitor
Horiba AMPA-370 for CO

The Ispra GHG station set-up and performance
5
Agilent 6890N GC-system equipped with FID/ECD for CO 2 , CH 4 , N 2 O and SF 6
• Measurement sequence GC-system: WH – WL – AM1 – AM2 – AM3 – AM4 – WH – WL
and every 6 hrs 2 ambient samples are replaced by a Target sample.
• Typical instrument precisions are in good agreement with WMO precision requirements based
on the targets for one month of sampling:
GC:

6
Ispra GHG station data coverage
Ispra data coverage
2007 2008 2009 2010 2011
Instrument Species 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4
Agilent 6890N GC-FID CO2
Agilent 6890N GC-FID CH4
Agilent 6890N GC-ECD N2O
Agilent 6890N GC-ECD SF6
ANSTO 222Radon monitor 222Rn
PICARRO G1301
PICARRO G1302
HORIBA AMPA 370A
CO2
CH4
CO

Regional GHG monitoring stations around the Po Valley
7
Jungfraujoch
3580 m
Plateau Rosa
3480 m
JRC-Ispra
220 m
Po Valley
Monte Cimone
2165 m

Po Valley pollution hot-spot: strong anthropogenic methane emissions from
agriculture by the EDGAR emission database
8
Anthropogenic methane emissions on a 0.1 x 0.1 degree grid from the EDGAR v4 database
for the year 2005 (http://edgar.jrc.ec.europa.eu/) show the Po Valley (dark blue) as a strong
regional source area, mainly related to emissios from the agricultural sector.

Catchment area for methane emissions calculated by the TM5 model 9
Footprint for methane for the Ispra station expressed as the sensitivity of
the measurements to methane emissions in ppbv CH 4 / kg CH 4 / s
calculated by the TM5 (4DVAR) model for the year 2008 (Bergamaschi et
al., 2010).

Meteorological conditions and air mass origin at Ispra
10
We distinguish three major meteorological
conditions:
Northerlies:
• Clean, e.g. Föhn events, to moderately polluted
air masses.
• 12 h footprint up to several hundred km at Föhn.
• Dominating during the fall and winter season.
Stagnant conditions:
• Very low wind speeds (

Highest GHG concentrations are found during southerly “Po Valley”
winds and at low wind speed conditions
11
600
550
CO2
CH4
Ispra CO2 and CH4 as function of wind direction for 2008
Wind direction
2700
2500
2300
600
550
Ispra CO2 and CH4 as function of wind speed for 2008
Wind speed
CO2
CH4
2700
2500
2300
500
450
500
2100
CH 4 CH 4
1900
450
2100
1900
400
350
1700
CO 2
400
1500
CO 2
1300
0 45 90 135 180 225 270 315 360
350
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
North South North Low High
1700
1500
1300
360
355
350
345
340
335
330
325
320
315
310
N2O
SF6
Ispra N2O and SF6 as function of wind direction for 2008
Wind direction
N 2 O
5
0 45 90 135 180 225 270 315 360
North South North
19
17
15
13
11
9
7
360
355
350
345
340
335
330
325
320
315
310
Ispra N2O and SF6 as function of wind speed for 2008
N2O
5
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
Low
N 2 O
Wind speed
High
SF6
19
17
15
13
11
9
7

Time series
12

ppmv
ppmv
CO 2 at Ispra from October 2007 to December 2010
13
550
530
510
490
470
450
430
410
390
370
350
All data CO 2 Ispra October 2007 to December 2010
550
530
510
490
470
450
430
410
390
370
350
Mid-day CO 2 Ispra vs Mace Head flask samples 2007-2010

ppbv
ppbv
CH 4 at Ispra from October 2007 to December 2010
14
3200
All data CH 4 Ispra October 2007 to December 2010
3000
2800
2600
2400
2200
2000
1800
3200
Mid-day CH 4 Ispra vs Mace Head flask samples 2007-2010
3000
2800
2600
2400
2200
2000
1800

ppbv
ppbv
N 2 O at Ispra from October 2007 to December 2010
15
355
All data N 2 O Ispra October 2007 to December 2010
350
345
340
335
330
325
320
315
355
Mid-day N 2 O at Ispra vs continuous Mace Head data 2007-2010
350
345
340
335
330
325
320
315

pptv
pptv
SF 6 at Ispra from October 2007 to December 2010
16
30
All data SF 6 Ispra October 2007 to December 2010
25
20
15
10
5
0
30
Mid-day SF 6 at Ispra vs continuous Mace Head data 2007-2010
25
20
15
10
5
0

222
Radon at Ispra from September 2008 to December 2010
17
35
Hourly mean Radon at Ispra from September 2008 to December 2009
30
222 Radon (Bq m
-3 )
25
20
15
10
5
0
25
Monthly mean Radon at Ispra from September 2008 to December 2009
222 Radon (Bq m
-3 )
20
15
10
5
0

difference in ppmv
difference in ppbv
Good agreement between the PICARRO and GC-system for simultaneous CO 2 and CH 4
measurements (year 2009 data)
18
50
40
30
20
10
0
-10
-20
-30
-40
-50
200
150
100
Agreement between the PICARRO and the GC for CO 2
SD Picarro data
PIC - GC-data
20 70 120 170 220 270 320 370
Day of Year
Agreement between the PICARRO and the GC for CH 4
SD Picarro data
PIC - GC-data
50
0
-50
-100
-150
-200
20 70 120 170 220 270 320 370
Day of Year

Good agreement between the PICARRO and GC-system for
simultaneous CO 2 and CH 4 measurements for 2009
19
ppmv CO2
ppbv CH4
550
530
510
490
470
450
430
410
390
370
350
2800
2700
2600
2500
2400
2300
2200
2100
2000
1900
1800
PICARRO
GC-FID
2009 CO 2 PICARRO vs GC
0 50 100 150 200 250 300 350
Day of Year
PICARRO
GC-FID
2009 CH 4 PICARRO vs GC
0 50 100 150 200 250 300 350
Day of Year
560
510
460
410
360
2800
2600
2400
2200
2000
1800
2009 CO 2 PICARRO vs GC
y = 0.9965x + 1.239
R² = 0.9965
360 410 460 510 560
2009 CH 4 PICARRO vs GC
y = 0.9971x + 7.6626
R² = 0.9955
1800 2000 2200 2400 2600 2800

Radon-based regional flux estimates
20

ppbv CH4
222 Radon flux in Bq m
-2 h
-1
Radon based flux estimate
Provided that the 222 Radon soil exhalation rate F Rn is known the F GHG can be estimated from the
slope Δ[GHG]/ Δ[Rn] expressed as:
F GHG / F Rn = Δ[GHG] / Δ[Rn] (Dörr and Münnich, Tellus, 1990)
21
2150
2100
Night time CH4 vs 222Radon on
27/03/2009
80
70
Ispra 222 Radon soil flux
2050
2000
60
50
annualmean
1950
1900
1850
y = 88.23x + 1411.3
R² = 0.78
4.0 9.0 14.0 19.0
Bq Radon
40
30
20
Estimated flux
Measured flux
0 100 200 300 400
DOY
• Only hourly mean night time measurement between 19:00 – 7:00 h with a R > 0.7 (R 2 > 0.49) are
used.
• 222 Radon decay during this time interval ( 222 Radon lifetime of 5.5 days) is neglected.
• Based on dynamic chamber measurements (Alphaguard) of the 222 Radon soil exhalation rate at
Ispra we estimate a yearly mean value of 56 Bq m -2 h -1 . Here we assume a seasonal deviation of -
20% in winter and +20% in summer.

Overview of all 2008-2010 GHG fluxes
22
2500
All CO 2 fluxes 2008-2010
0.30
All N 2 O fluxes 2008-2010
2000
0.25
Flux in mg m -2 h -1
1500
1000
500
Flux in mg m -2 h -1
0.20
0.15
0.10
0.05
0
0 50 100 150 200 250 300 350 400
0.00
0 50 100 150 200 250 300 350 400
5.0
All CH 4 fluxes 2008-2010
5.E-04
All SF 6 fluxes 2008-2010
4.5
4.0
4.E-04
Flux in mg m -2 h -1
3.5
3.0
2.5
2.0
1.5
1.0
0.5
Flux in mg m -2 h -1
3.E-04
2.E-04
1.E-04
0.0
0.E+00
0 50 100 150 200 250 300 350 400
0 50 100 150 200 250 300 350 400
• Enhanced methane fluxes are found during winter time mostly from the Po
Valley region
• Occasionally high N 2 O fluxes
• A strong (night time) biogenic respiration signal is apparent in Spring
• No strong sign of rice paddy methane emissions at Ispra

Annual mean fluxes for Ispra compared to other European estimates
23
Area Annual mean CH 4 -flux sd Reference
Rn-flux mg m -2 h -1
Western Europe, 1996-04 Annual 57 1.36 0.23 Messager et al., ACPD, 2008
Germany, Schaunsland 1991-95 Wintertime 53 1.06 0.55 Schmidt et al., Tellus, 1996
Germany, Heidelberg 1996-08 Annual 57 0.72 0.43 Levin et al., Phil. Trans R. Soc., 2011
Italy, Po Valley 2008 Wintertime 47 1.36 0.54 this work
Italy, Po Valley 2009 Annual 56 1.12 0.44 this work
Italy, Po Valley 2010 Annual 56 1.04 0.62 this work
Europe 1996-04 Annual Inventory 0.83 0.10 UNFCCC, 2005 (in Messager et al., 2008)
Area Annual mean CO 2 -flux sd Reference
Rn-flux g m -2 h -1
Western Europe, 1996-04 Annual 57 0.468 0.171 Messager et al., ACPD, 2008
Germany, Schaunsland 1991-95 Wintertime 53 0.458 0.189 Schmidt et al., Tellus, 1996
Italy, Po Valley 2008 Wintertime 47 0.422 0.105 this work
Italy, Po Valley 2009 Annual 56 0.576 0.224 this work
Italy, Po Valley 2010 Annual 56 0.493 0.256 this work
Europe 1996-04 Annual Inventory 0.543 0.030 ORCHIDEE + UNFCCC, 2005 (in Messager et al., 2008)
Area Annual mean N 2 O-flux sd Reference
Rn-flux ug m -2 h -1
Western Europe, 1996-04 Annual 57 59 15 Messager et al., ACPD, 2008
Germany, Schaunsland 1996-98 Annual 57 66 6 Schmidt et al., JGR, 2001
Germany, Heidelberg, 1996-98 Annual 57 68 8 Schmidt et al., JGR, 2001
Italy, Po Valley 2008 Wintertime 47 42 9 this work
Italy, Po Valley 2009 Annual 56 56 23 this work
Italy, Po Valley 2010 Annual 56 42 26 this work
Europe 1996-04 Annual Inventory 64 7 UNFCCC, 2005 (in Messager et al., 2008)

Annual mean fluxes of CH 4 and N 2 O for the Po Valley compared to other European estimates
24
FLux in mg m -2 h -1
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
European flux estimates for CH 4 compared
Western
Europe, 1996-
04 Annual
Germany,
Schaunsland
1991-95
Wintertime
Germany,
Heidelberg
1996-08
Annual
Italy, Po Valley
2008
Wintertime
Italy, Po Valley
2009 Annual
Italy, Po Valley
2010 Annual
Flux in ug m -2 h -1
100
90
80
70
60
50
40
30
20
10
0
Western
Europe, 1996-
04 Annual
European N 2 O flux estimates compared
Germany,
Schaunsland
1996-98
Annual
Germany,
Heidelberg,
1996-98
Annual
Italy, Po Valley
2008
Wintertime
Italy, Po Valley
2009 Annual
Italy, Po Valley
2010 Annual

Flux data partitioning into three sectors based on HYSPLIT 12 hr back-trajectory
analysis and local meteorology data (wind speed, wind direction, and RH%)
25
1.North-Northwest sector: (blue)
2.Stagnant conditions: (red)
3.South-Po Valley: (green)
2
2.00
2008 October-December
1.80
Northerlies
1.60
Stagnant
Flux in g m -2 h -1
1.40
1.20
1.00
0.80
0.60
Po-Valley
2.00
1.80
2010 annual average
Northerlies
0.40
1.60
Stagnant
Flux in g m -2 h -1
0.20
0.00
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
F_CO2 F_CH4 (*10-3) F_N2O (*10-4) SF6 (*10-6)
2009 annual average
Northerlies
Stagnant
Po-Valley
F_CO2 F_CH4 (*10-3) F_N2O (*10-4) SF6 (*10-6)
Flux in g m -2 h -1
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
Po Valley
F_CO2 F_CH4 (*10-3) F_N2O (*10-4) SF6 (*10-6)
• Enhanced GHG fluxes are related
to air masses coming from the Po
Valley region (in green).

Annual flux average per sector
26
Flux in g m -2 h -1
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
2008
2009
2010
CO 2 annual mean
Flux in mg m -2 h -1
2.00
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
2008
2009
2010
CH 4 annual mean
0.10
0.20
0.00
0.00
Northerlies Regional Po Valley
Northerlies Regional Po Valley
Flux in ug m -2 h -1
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
2008
2009
2010
N 2 O annual mean
Flux in pg m -2 h -1
0.35
0.30
0.25
0.20
0.15
0.10
0.05
2008
2009
2010
SF 6 annual mean
0.00
0.00
Northerlies Regional Po Valley
Northerlies Regional Po Valley

High methane fluxes in air masses are mainly coming from the Po Valley
with a slight tendency towards higher values during winter time
27
mg CH4 m -2 h -1
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
All sectors
Po Valley
Ispra 2008-2010 methane flux
0 50 100 150 200 250 300 350
Day of Year
Po Valley CH 4 flux
winter (NDJF):
1.22±0.56
summer (MJJAS):
0.99±0.57
March-April:
1.02±0.60
Is there a seasonality in anthropogenic emissions of CH 4 that we don’t know off
EDGAR4.2 2008 CH 4 emissions for Italy
16 20 78
14
48
495
mg CH 4 m -2 h -1
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Seasonal CH 4 Po Valley flux
NDJF MJJAS MA
Agricultural soils
Enteric fermentation (cattle)
Manure management
Gas production and
distribution
Heating
661
Oil refineries
Landfills
EDGAR4.2 data by
courtesy of Greet
Janssen-Maenhout
199
Transport
Industry
6 31
215
Waste water treatment
Others

28
Further highlights:
High N 2 O events
Clean air episodes at Ispra
The potential contribution of Po
Valley rice paddy emissions to the
Ispra flux estimates

ppbv N2O
Large N 2 O point source 40 km south of Ispra can explain N 2 O flux “outliers”
29
Radici Chimica SPA in Novarra (asl 149 m, lon 8.6433, lat 45.4599, ~40 km South of Ispra) is one of the main
production plants in Europe of nitric and adipic acid.
Foreward Hysplit trajectories starting at the factory (at 200 m altitude) at 21-12-2009 were N 2 O values reach to
340 ppbv arriving at Ispra in less then half a day.
344
342
340
338
336
334
332
330
328
326
324
322
N2O
CH4
Elevated N 2 O and CH 4 from the Novarra area
2900
2700
2500
2300
2100
1900
1700
1500
ppbv CH4
ISPRA
F N2O for this event:
189±40 μg m -2 h -1
Average 2009 Po Valley F N2O :
54±23 μg m -2 h -1 NOVARRA nitric acid plant

ppbV CH4
RH%
Strong Föhn events simultaneously observed at Ispra and Jungfraujoch station
30
2100
2050
2000
1950
Clean air Föhn events at Ispra
CH4 JFJ
CH4 Ispra
Föhn air
RH% Ispra
100
90
80
70
60
1900
50
1850
1800
1750
1700
03/23/08
00:00
03/24/08
00:00
03/25/08
00:00
DAY-TIME (9:00 - 16:00)
Föhn
03/26/08
Ispra
03/27/08 03/28/08 03/29/08
JFJ
03/30/08 03/31/08
difference
04/01/08 04/02/08Match
00:00 00:00 00:00 00:00 00:00 00:00 00:00 00:00
events Mean sd Mean sd JFJ-Ispra
RH% 21 7
WS 3.2 DAY-TIME 2.2 (9:00 - 16:00)
04/03/08
00:00
Föhn O3 Ispra 42 8 JFJ 52 10 difference 10 Match 1.24
events CO Mean 190 sd 23.7 Mean 159 sd 13 JFJ-Ispra -30 0.84
RH% CH4 21 1885 716 1881 21 -4 1.00
WS N2O 3.2 322.25 2.2 0.65 322.27 1.5 0.02 1.00
O3 SF6 42 6.64 80.12 52 6.76 10 0.33 10 0.12 1.24 1.02
CO 190 23.7 159 13 -30 0.84
CH4 1885 16 1881 21 -4 1.00
Excellent agreement N2O 322.25 is found 0.65 between 322.27 the 1.5 ambient 0.02 air composition 1.00 observed at
Ispra and SF6 JFJ during 6.64Föhn 0.12 events 6.76 as seen 0.33during 0.12January 1.02 to April of 2008.
04/04/08
00:00
04/05/08
00:00
40
30
20
10
0
04/06/08
00:00

Po Valley rice paddies flooded between April-September
31
Meteosat-7, visible channel, 26
April 2001, 11:00 UTC
Landsat-7 Thematic Mapper (TM), 20 May 2001
(courtesy US Geological Survey).

July-August peak in methane fluxes from a Po Valley rice paddy: can
32
we see that in the data at Ispra
2009 June-August highest rice paddy emissions
~ 0.3 μmol CH 4 m -2 s -1
Data and plot from Meijide
et al., BGD, 2011.
2400
2300
Ispra CH 4 May to October 2009
June-August high CH 4
2200
ppbv CH4
2100
2000
1900
1800
EDGAR4.2 agricultural soils emissions estimate for 2008: ~48 kTon y -1 .
A mean methane flux of 0.3 μmol CH 4 m -2 s -1 extrapolated to a total rice paddy area of 2 * 10 9 m 2
and an emission period of 60 days corresponds to ~50 kTon from the Po Valley.

Potential event flux contribution from rice paddies
33
~50 kTon from rice paddies corresponds to a potential flux contribution of
the order of ~0.5 mg CH 4 m -2 h -1 evenly distributed over the Po Valley basin
(7 * 10 10 m 2 ) during July and August.
mg CH4 m -2 h -1
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Ispra 2008-2010 methane flux
All sectors
Po Valley
0 50 100 150 200
Day of Year
250 300 350
N.B. compared to the potential strength of other major source the contribution
from rice paddies is relatively small.

34
The greenhouse gas monitoring activity in
support of the JRC TM5 inverse modeling
and the EDGAR emission database:
To improve our understanding of the role of
the Po Valley hotspot in the European GHG
emission budget

Ispra (green) and Milan in the TM5 grid
35

Comparison between 2008 CH 4 observations and the TM5 model for Ispra 36
TM5 forward simulation of methane for 2008 for a 1 x 1 degree resolution. Black dots denote
the hourly mean measured methane, the blue line is the mean model output, whereas the light
blue shaded area represents the uncertainty range due to the model representativeness error.

Total EDGAR based a-priori CH 4 emissions in the TM5 model Ispra
domain versus our flux estimates
37
Catchment area Emission in mg CH 4 m 2 h -1
Model 1x1 degree grid 0.93
Model 30 km footprint total 1.02
Model 30 km footprint North 0.68
Model 30 km footprint South 1.35
Measured flux North: 0.36 – 0.46
Measured flux South (Po Valley) 1.04 – 1.36

Total EDGAR based a-priori N 2 O emissions in the TM5 model Ispra
domain versus our flux estimates
38
Catchment area Emission in mg N 2 O m 2 h -1
Model 1x1 degree grid
0.312 (biased from factory point source!)
Model 30 km footprint total 0.032
Model 30 km footprint North 0.021
Model 30 km footprint South 0.043 (factory point source not included!)
Measured flux North: 0.012 – 0.030
Measured flux South (Po Valley) 0.042 – 0.054
38

39
Link of the Ispra GHG-monitoring
activity to monitoring networks and
programs
39

Connection of the JRC-Ispra GHG-Station to international
monitoring programmes and networks
40
GEOMON (http://www.geomon.eu/)
ICOS (http://icos-infrastructure.eu/)
InGOS (www.ingos-infrastructure.eu/)
40

Near real-time data presentation on the GEOMON-IMECC and ICOS data site
41
41

42
Outlook
Set-up of a 65 m tower starting in 2012 at the JRC-
Ispra site to establish a long-term GHG monitoring
facility combined with the Ispra EMEP/GAW activity.

Summary; what have we learned from the Ispra GHG
station so far
43
• The Ispra station is the currently the only ground based station bordering the Po Valley region
which is one of the global pollution hotspots, complementing a number of mountain station in
the area.
• The Ispra station encounters clean continental background level northerly air masses
comparable to high altitude mountain stations that strongly contrast polluted southerly Po Valley
air masses.
• The 222 Radon based flux estimates allows for model independent emission estimates for the Po
Valley region.
• Our flux estimates indicate significantly enhanced emissions from the Po Valley relative to air
masses from the North.
• Model simulations are consistent within the model representativeness error.
• Our regional flux estimates for CH 4 and N 2 O are in good agreement with total a-priori estimates
from EDGAR.
• A higher sampling mast will increase the catchment area of the station and lower the influence
of local sources and the strong local influence of ecosystem respiration.