Challenges in Scaling Up Flux

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Challenges in Scaling Up Flux

Measurements of CO ₂ , CH ₄ and N ₂ O from Terrestrial Ecosystems

R. Desjardins

¹

, D. Worth

¹

, M. Mauder

²

, A. VanderZaag

¹

, E. Pattey

¹

, R. Srinivasan

³

, W. Smith

¹

, and B. Grant

¹

Presented at the TERENO International Conference, Sept 29-Oct 3, 2014

1 Science and Technology Branch, Agriculture and Agri-Food Canada

2 Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology

3 National Research Council Canada, Aerospace Portfolio

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2 Outline

• Review GHG flux measuring systems for a wide range of scales

• Present N ₂ O and CH ₄ flux

measurements from agroecosystems.

• Discuss the advantages and limitations

of various techniques.

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3 Flux measuring tools for a wide range of scales

1 hour

1 Day

1 Month

1 Year

Aircraft

EC & REA

Laser bLS

1 m

²

1 Hectare 1 km

²

Representative Area of Measurements

10 km

²

Chamber

Re pre s e ntativ e T ime o f Me a s ure m e nt

Tall Tower/ Flask Inverse modeling

Flux Tower

EC & REA

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4 Obtaining GHG emission estimates at regional and national scales

Develop

‘Model’

Measure GHG’s

Verified GHG Models

time

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Global annual total emissions

Optimized

Carbon Tracker Flux Estimates using an Inverse Modeling Technique

Source: CarbonTracker CT2013, http://carbontracker.noaa.gov

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Atmosphere

Animal Plant

Waste

Soil CO ₂ CO ₂ CO ₂

CH ₄ N ₂ O CO ₂

CH ₄ CH ₄

CO ₂ CH ₄ N ₂ O Agricultural GHG Emissions

Coupled processes in soil-plant atmosphere systems- S8

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7 Greenhouse Gas Emission Estimates from Canadian Agroecosystems

Worth, D. E., Desjardins, R.L., MacDonald, D., McConkey, B.G., Dyer, J.A., and X.P.C. Verge 2014. The greenhouse gas indicator for agriculture AEI report Agriculture and Agri-Food Canada

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8

0

10 20 30 40 50 60 70 80 90

1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998

Year Gg N

2

O -N

Estimated direct annual N₂O-N emissions Estimated direct spring N₂O-N emissions

Estimated Direct N ₂ O-N Emissions from Agriculture Soils in Canada Using DNDC (1970-1999)

On average spring emissions represented 30% of annual emissions. The

contribution of freeze-thaw cycles to annual emissions ranged from 8 to 81% in northern countries. Wang et al. (2008).

Smith, W.N., B. Grant, R.L. Desjardins, R. Lemke, and C. Li. 2004. Estimates of the interannual variations of N₂O emissions from agricultural soils in Canada Nutrient Cycling in Agroecosystems. 68: 37-45.

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Multi-scale estimation of N

₂

O emissions from agroecosystems

Pattey E., Edwards, G.C., Desjardins, R.L., Pennock, D., Smith W., Grant B., MacPherson, J.I., 2007.

Tools for quantifying N₂O emissions from Agroecosystems. Agric. Forest Meteorol.142(2-4): 103-119.

NRC Twin Otter

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10 4 3 2 1

5 6

9 10 11 12

8 7

16 15 14 13

17 18

21 22 23 24

20 19

28 27 26 25

29 30

33 34 35 36

32 31

P/W G G G G P G G

C C P/G G

G/C G/C G C P/G C P C

G G C G

C G G G G G P G

G P G G

P G/C G G G G G C/G

C G P P

P G G C C G G P/G

F C/F G G

P G G C P C C P/G

G P G C

G G G G G G P G

G G P G

G C C G C G C/G P

G G G C

P G G G C G C F

G F C C

G G G G P G F/G C/G

P C G G

P G G G G F/G P/G G

P G G P

P C G G G G/F G G

P G/C G F

G Grain P Pulse

F Forage/Pasture Sampled

Quarter-section

Township 43, Range 4, West of the Third Meridian

0 1600

meters

Laird Study Township: Land Use

C Canola

Scaling up chamber measurements of nitrous oxide emissions at the field scale in western Canada

Canada

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11 Wheat ^{(69.3 g N} 2 O-N ha ^-1 x 0.58)

Canola ^{(31.8 g N} 2 O-N ha ^-1 x 0.19)

Peas ^{(54.1 g N} 2 O-N ha ^-1 x 0.17)

Manured ^{(254. g N} 2 O-N ha ^-1 x 0.01) Total 58.7 g N ₂ O-N ha ^-1

Crop Weighted Chamber N ₂ O Flux

Canada

Pennock, D., Farrell, R., Desjardins R.L., Pattey, E., MacPherson, J. I., 2005. Upscaling chamber-based measurements of N₂O emissions at snowmelt. Can. J. Soil Sci. 85: 113-125.

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12 g N

2

O -N ha

-1

d

-1

04/05 04/09 04/11 04/13 04/15 04/17

0 5 10 15

-5

04/05 04/09 04/11 04/13 04/15 04/17

0 5 10 15

-5

g N

2

O -N ha

-1

d

-1

Chamber

Aircraft

∑ = 58.7

g N ₂ O-N ha ^-1

∑ = 47.7

g N ₂ O-N ha ^-1

Chamber/AC N ₂ O Flux Comparison

Pennock, D., Farrell, R., Desjardins R.L., Pattey, E., MacPherson, J. I., 2005. Upscaling chamber-based measurements of N₂O emissions at snowmelt. Can. J. Soil Sci. 85: 113-125.

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13 Relaxed Eddy Accumulation (REA)

• Alternate to eddy covariance technique to measure fluxes of trace gases for which fast- response analyzers are not operational

• Air samples from updrafts and downdrafts are collected in two separate reservoirs for later analysis

• In EA, sample flow rate is proportional to w;

this requirement is ‘relaxed’ in REA (i.e., full flow into up or down reservoir depending on the

direction of the vertical wind)

 

F

_

 w ' ' = A   

_w _Up

 

_Down

Vent (Dead band) PTFE Sample Bag

DC Power supply 3-way Valve Mass-Flow

Controller 2-m

Filter Relief

valve Diaphragm Pump 12 l/min

Inlet

UP

DOWN

¼” PTFE tubing

Desjardins, R.L., J.I. MacPherson and P.H. Schuepp. 2000.

Aircraft-based flux sampling strategies. Encyclopedia of Analytical Chemistry. R.A. Meyers (Ed.) pp. 3573-3588. John Wiley & Sons Ltd. Chichester.

Pattey, E. Strachan, I.B., Desjardins, R.L., Edwards, G.C., Dow, D., and MacPherson, I.J. 2006. Application of a tunable diode laser to the measurement of CH₄ and N₂O fluxes from field to landscape scale using several micrometeorological techniques. Agric. Forest Meteorol.136: 222-236.

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14 Morewood

Casselman

N

0 5 km

5 km

Morewood

Casselman

N

0 5 km

5 km

N

0 5 km

5 km

Measuring N ₂ O flux at a regional scale

soy cereals

pasture/grass alfalfa

forest

corn town

LEGEND

Pattey E., Edwards, G.C., Desjardins, R.L., Pennock, D., Smith W., Grant B., MacPherson, J.I., 2007. Tools for quantifying N₂O emissions from Agroecosystems. Agric. Forest Meteorol.142(2-4): 103-119.

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15 Regional N ₂ O fluxes during and right after snowmelt at the Eastern Canada study sites in 2001 using the REA technique

Each data point represents the average of 3 samples, collected during two consecutive 10 km flight legs (total flight distance for one data point is ≈ 20 km)

-25 0 25 50 75 100 125

15-Mar 25-Mar 4-A pr 14-A pr 24-A pr 4-May 14-May 24-May 3-Jun 13-Jun

N

2

O Emi ssi on s (g N

2

O-N ha

-1

d

-1

) ^Casselman

Morewood

Pattey E., Edwards, G.C., Desjardins, R.L., Pennock, D., Smith W., Grant B., MacPherson, J.I., 2007. Tools for quantifying N₂O emissions from Agroecosystems. Agric. Forest Meteorol.142(2-4): 103-119.

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16 Multi-year comparison of N ₂ O emissions using aircraft-based systems and model estimates

-25 25 75 125 175

15-Mar 25-Mar 4-Apr 14-Apr 24-Apr 4-May 14-May 24-May 3-Jun 13-Jun

-25 25 75 125 175

DNDC Casselman

-25 25 75 125 175

N

2

O Flu x (g N

2

O -N ha

-1

d

-1

)

2000 2001

2003 2004

Total emissions (kg N₂O-N ha^-1) DNDC: 0.34 Aircraft: 0.53

Desjardins, R.L., Pattey, E., Smith, W.N., Worth, D., Grant, B., Srinivasan, R., MacPherson, J.I., and Mauder, M., 2010. Multiscale estimates of N₂O emissions from agricultural lands. Agric. Forest Meteorol., 150: 817-824.

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17 Measured Modeled (DNDC)

% difference kg N ₂ O-N ha ^-1 period ^-1

2000 0.53 0.34 +20

2001 0.55 0.76 -38

2003 1.87 1.44 +22

2004 1.77 1.11 +37

Comparing total measured and modeled N ₂ O flux estimates

In three out of the four measurement years, measured emissions exceeded modeled emissions by an average of 26%. In 2001, DNDC predicted a longer

‘spring burst’ than was measured, and total modeled emissions were 38%

greater than measured emissions.

Measurements incorporate indirect emissions, whereas DNDC does not. In the IPCC methodology we assume that indirect emissions are in the range of

25 to 30% of total emissions.

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18 Agricultural Sources of Methane in Canada in 2011

Enteric fermentation (digestion) by ruminant animals 18 Mt CO

₂

e per year

Management of animal manures 3 Mt CO

₂

e per year

Worth, D. E., Desjardins, R.L., MacDonald, D., McConkey, B.G., Dyer, J.A., and X.P.C. Verge 2014. The greenhouse gas indicator for agriculture AEI report. Agriculture and Agri-food Canada.

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Methane emissions from farms

 bLS inverse-dispersion technique

Unknown

Flesch 2011

Measured

Boreal lasers and reflectors

Ultrasonic Anemometer

 CH

₄

concentration and wind data synchronized

 WindTrax model ¹⁹

Flesch, T.K., Harper, L.A., Desjardins, R.L., Gao, Z., and Crenna, B.P. 2009. Multi-source emission determination using an inverse-dispersion technique. Boundary layer Meteorology.

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0 200 400 600 800 1000 1200 1400 1600 1800 0

10 20 30 40 50 60 70 80

Time series 15-min periods CH

4

F lu x (kg h r

-1

)

CH ₄ emissions from manure storage

 From June 2013 - May 2014

June, July, Aug. Sep., Oct., Nov. Dec., Feb. March to May 05

Transfer manure Large to small tank Aug, 03, 04, 11

Periods rainfall

Activities feed storage

Sep. 08

Manure agitation

July 24

20

Balde, H., VanderZaag, A.C., Desjardins R. L. 2014 .Measuring on-farm methane emissions (in preparation).

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CH ₄ emission estimates at a regional scale (2011)

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The NRC Twin Otter

22 Instrumented nose boom

in-flight REA sample collection & post-flight REA sample analysis using Picarro G1301

CH ₄ Analyzer (G2301) and real-time

display

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Location of the 7 transects flown at 150 m high

23

Desjardins,R.L., Worth, D.E.., Srinivasan, R., Pattey, E., VanderZaagA., Mauder, M., Worthy, D., Sweeney, C. and S. Metzger 2014.Verification

of methane emission inventory over an agricultural region using aircraft-based flux measurements (in preparation

).

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Water treatment facilities associated with increase in methane concentration

Wastewater treatment

Range in peak [CH

₄

]

Water treatment

WDIR 200˚

250˚

Flight track

Flesch, T.K., Desjardins, R.L. and Worth, D. 2011. Fugitive methane emissions from an agricultural biodigester. Biomass and Bioenergy. 35: 3927-3935.

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Waste treatment centres affect CH ₄ concentration over large areas

Flight Track

Waste Treatment

Centre

30 ppb

11 km

Cai, X., Flesch, T.K., Desjardins, R.L. Worth, D.E. VanderZaag, A. Measurement and modeling of methane emissions from a large waste treatment facility. In preparation.

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26 Summary

•Presented GHG flux measuring systems for a wide range of spatial and temporal scales- models are essential to integrate

•Presented some examples of comparisons between flux measuring techniques- There are some challenges but most of the differences observed are explainable

•Presented measurements of nitrous oxide emissions using an aircraft- based system. The combination of nitrous oxide emission estimates using aircraft- based flux measurements and the DNDC model

provided an independent estimate of indirect emissions assumed in the IPCC methodology

•The aircraft-based methane flux measurements showed that methane emission inventory estimates for agricultural sources appear

reasonable. It confirmed that some agricultural regions include other methane sources such as wetlands, biodigesters, waste treatment plants, etc. that can be quite large. This could put in question some of the sector-based methane emission estimates using atmospheric

inverse modelling techniques.

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Challenges in Scaling Up Flux