Gaseous emissions from soil quantified by a photoacoustic

method

Dr. Martina Predotova

ICRAF, KenyaJuly 2011

Origin

INNOVA monitor originally product of Brüel & Kjær(www.bksv.com)

Sound and vibration analyses/measurements

LumaSense Technologies, Inc.(www.lumasenseinc.com)

Over 50 yearsTemperature and gas sensing intruments

Industry, energy and cleaning technologies

Gas monitor: Innova

Uses- Quantitative analyses of up to 5 gases + H2O, separated

or in mixtures- Health and safety measurements- Indoor air-quality and ventilation measurements- Detection of accidental releases of gases/vapours- Gaseous emissions in agriculture

Gas monitor: Innova

- Selectively measures a wide range of gases/vapours- Accurate: Self-testing procedures- Compensates for: water vapour interference

interference from other gases- Portable- Distanced sample collection- Operates immediately

no long warm-up, immediate analyses - Real time measurement data on screen,

background memory- Offline or online measuring task possible- User-friendly handling

Gas monitor: InnovaFunctional diagram

Methodology: Method comparison

1. Innova2. Li-Cor CO2 analyzer3. Gas chromatograph

(GC)

Closed chamber

(1)

(1)

(2)

(3) (3)

Methodology: Method comparisonInnovaChamber closure time: 6 minSampling interval: every 2 minAnalyzed gases: CO2, N2O and CH4

Li-CorChamber closure time: 5 minSampling interval: continousAnalyzed gases: CO2

GCChamber closure time: 30 minSampling interval: at 0, 10, 20 and 30 minAnalyzed gases: N2O and CH4

5 chambers per site

Methodology: Method comparison

Kakamega district: forests / areas converted to cropland

3 conversion categories (3 farms + 3 forests per category)- Converted in 50‘s- Converted in 80‘s- Recent conversion

Results: Method comparison

0

5

10

15

20

25

30

50's 80's Recent

Conversion category

CO

2(k

g ha

-1h-1

)

CO2 emissions from farms and forests(means and stdev., n = 15)

Farm / InnovaFarm / Li-CorForest / InnovaForest / Li-Cor

Results: Method comparisonN2O emissions from farms and forests

(means and stdev., n = 15)Farm / InnovaFarm / GCForest / InnovaForest / GC

0

2

4

6

8

10

12

14

16

50's 80's Recent

Conversion category

N2O

(g h

a-1h-1

)

Methodology: Spatial variability of GHG

Measured with Innova, 12 rings per site

Sites

1. Heavy soil, recent conversion, high Corg., maize

2. Heavy soil, old conversion, low Corg.,maize

3. Forest, high Corg.

4. Sandy degraded soil, no vegetation

5. Sandy soil, rehabilitated, acacia

(1) (3)

(4) (5)

Results: Spatial variability of GHG

Heavy soil, high Corg.

6.06.57.07.58.08.59.09.5

10.0

CO

2(k

g ha

-1h-1

) 3 rings

4 rings

5 rings

6 rings

7 rings

8 rings

9 rings

10 rings

11 ringsRehabilitated sandy soil, low Corg

1.01.52.02.53.03.54.04.55.0

Increasing number of rings

CO

2(k

g ha

-1h-1

)

Differences between sites (means, n = 3-11)

Results: Spatial variability of GHG

2

3

4

5

6

7

8

N2O

(g h

a -1

h-1)

Heavy soil, high Corg.

3 rings

4 rings

5 rings

6 rings

7 rings

8 rings

9 rings

10 rings

11 rings

N2O

(g h

a -1

h-1)

Degraded sandy soil, low Corg.

-2

-1

0

1

2

3

4

Increasing number of rings

Differences between sites (means, n = 3-11)

Results: Spatial variability of GHGC

O2

(kg

ha-1

h-1)

Increasing number of rings

Degraded sandy soil, low Corg.

01

2345

67

Heavy soil, high Corg.

2468

1012141618

CO

2(k

g ha

-1h-1

)

Number of rings to measure (means and stdev., n = 3-11)

3 rings

4 rings

5 rings

6 rings

7 rings

8 rings

9 rings

10 rings

11 rings

8 rings?

7 rings or less?

Results: Spatial variability of GHGNumber of rings to measure (means and stdev., n = 3-11)

-202468

101214

Heavy soil, high Corg.

N2O

(g h

a -1

h-1)

3 rings

4 rings

5 rings

6 rings

7 rings

8 rings

9 rings

10 rings

11 rings

8 rings?

7 rings?

Heavy soil, low Corg.

N2O

(g h

a -1

h-1)

Increasing number of rings-2

0

2

4

6

8

10

12

Methodology: Temporal variability of GHG

24 hours experiment, with Innova

Measuring in 2 h interval, 8 rings

Sites1. field maize, beans intercropping2. forest

Results: Temporal variability of GHG

N2O

(g h

-1ha

-1)

-4-202468

1012

CH

4(g

h-1

ha-1

)

-500

50100150200250300350

16:00

18:00

20:00

22:00

00:00

02:00

04:00

06:00

08:00

10:00

12:00

14:00

Time of a day (hours)

CO

2(k

g h-

1ha

-1)

456789

1016

:0018

:0020

:0022

:0000

:0002

:0004

:0006

:0008

:0010

:0012

:0014

:00

Time of a day (hours)

(Means and stdev: chamber temp. n=16, soil temp. n=1, gas flux n=8)

05

10152025303540

Tem

p. (C

°)

ChamberSoil 0.1m depth

16:00

18:00

20:00

22:00

00:00

02:00

04:00

06:00

08:00

10:00

12:00

14:00

Conclusions

The three tested methods delivered comparable results of CO2 and N2O fluxes from forests and farm land.

Manual sampling for GC with subsequent sample analyses is more labour and time intensive.

Spatial variability of gaseous emissions vary between different ecosystems.

Measurements on 8 spots covered the spatial variability of CO2 and N2O fluxes on most tested sites.

The emissions of CO2, N2O and CH4 fluctuate strongly in a course of 24 hours.

Thank you

Detection limits

NH3: 200 ppbN2O: 30 ppbCO2: 3.4 ppmCH4: 400 ppb