1. Biogenic emissions from tropical ecosystems
Silde 1: Title Slide
Michael Barkley & Paul Palmer
University of Edinburgh

2. HCHO August 2001 (Ozone Monitoring Experiment)
biogenic, pryogenic, anthropogenic
pryogenic
anthropogenic
biogenic
pyrogenic
Thomas Kurosu, Harvard-Smithsonian
Isoprene is the main driver of variability in ΩHCHO
(Palmer et al., JGR, 2003,2006)

3. Inverting HCHO columns for isoprene emissions
GOME slant columns (July 96)
So if we have convinced ourselves that isoprene is the main contributor to the formaldehyde column, how do we then derive the isoprene emissions from the satellite column measurements?
Well it is essentially a four step process:
The slant columns are determined from the satellite spectral measurements
The slant columns are then converted into vertical columns by dividing them by the air mass factor which is calculated using a radiative transfer model and the global chemistry transport model GEOS-CHEM
The air mass formulation is important as it accounts for scattering processes within the atmosphere both from clouds and aerosols, and also Rayleigh scattering, and importantly the vertical distribution of the formaldehyde with the vertical column.
It is the product of the geometrical air mass factor with the integral of the scattering weights (as calculated by the radiative transfer model) multiplied by the shape factor or the formaldehyde vertical profile from GEOS-Chem where the blue line here represents what GOME ‘sees’.
Typical errors on the AMF are about 30%
This process ensures consistency between model and satellite comparisons
Once the vertical columns have been obtained, we then determine a linear transfer function, using GEOS-CHEM, that relates the model formaldehyde columns, sampled along the satellites ground track, to the model isoprene emissions which are based on the MEGAN emission inventory data.
The intercept represents the formaldehyde background.
The slope is dependent on model yield of formaldehyde from isoprene and the loss rate constant for formaldehyde.
We can invert the transfer function and use the GOME, or OMI, formaldehyde columns to then estimate the isoprene emissions.

4. Inverting HCHO columns for isoprene emissions
GOME slant columns (July 96)
what
GOME
sees
Instrument
sensitivity w(s)
(“scattering
weight”)
Apply AMF
GOME vertical columns (July 96)
Vertical shape
factor S(s)
(normalized mixing ratio)
VCD = SCD / AMF

5. Model Transfer Function
GOME slant columns (July 96)
Apply AMF
GOME vertical columns (July 96)
ΩHCHO=SEisop+B

6. Model Transfer Function
GOME slant columns (July 96)
Apply AMF
GOME vertical columns (July 96)
Eisop~ (ΩHCHO-B) / S
ΩHCHO=SEisop+B

7. Model Transfer Function
GOME slant columns (July 96)
Apply AMF
GOME vertical columns (July 96)
Eisop~ (ΩHCHO-B) / S
GOME
isoprene
emission
inventory
ΩHCHO=SEisop+B

8. The tropics: GOME observations: Jan-June 1997
Plots smoothed with 3x3 box-car filter!

9. The tropics: GOME observations: July-Dec 1997
Plots smoothed with 3x3 box-car filter!

10. Significant pyrogenic HCHO source
Grey diamonds = fires detected by ATSR
Plots smoothed with 3x3 box-car filter!

11. Partition Amazon into West & East regions
Plots smoothed with 3x3 box-car filter!

12. East region: Contribution of wild fires
Maximum in dry season
Biomass burning is the main source of HCHO

13. Partition Amazon into West & East regions
Plots smoothed with 3x3 box-car filter!

14. Isolate West Amazonian + remove fires
Plots smoothed with 3x3 box-car filter!

15. 5 yr time series over western Amazonian
If we look at the GOME data over the tropics, focussing over South America, during the wet season January to May we find there doesn’t seem to be a lot happening.
However, when we move into the dry season there is a significant increase in the formaldehyde slant columns
This is increase is mostly attributable to both biomass burning emissions of formaldehyde, which is assumed to be dominant, and an increase in leaf-level isoprene emission rates from the wet to dry seasons.
By over plotting the positions of wild fires as detected by the ATSR instrument, we can see that the formaldehyde enhancements, are spatially closely correlated with the biomass burning events.
The ATSR wild fire atlas is useful in that, if we over plot it onto the GOME data over several years, we find that we can identify two distinct regions. An eastern region where biomass burning events are very common and a western area in which wild fires are less frequent
Focussing on the eastern Amazonian, if we plot the time series of GOME monthly means over this region against the number of fire counts then a clear correlation exists indicating that biomass burning is the main source of the increase formaldehyde.
If we want to determine biogenic isoprene emissions we need to remove the biogenic component.
We can attempt this by isolating the western region and removing all grid boxes where fire occur.
When we now plot the formaldehyde time series over this region, we see notice that the columns are lower with a

16. 5 yr time series over western Amazonian
In situ isoprene 2.8°S, 59.4 ° W (Trostdorf et al., ACPD, 2004)
Rainfall
Yr = 2002
If we look at the GOME data over the tropics, focussing over South America, during the wet season January to May we find there doesn’t seem to be a lot happening.
However, when we move into the dry season there is a significant increase in the formaldehyde slant columns
This is increase is mostly attributable to both biomass burning emissions of formaldehyde, which is assumed to be dominant, and an increase in leaf-level isoprene emission rates from the wet to dry seasons.
By over plotting the positions of wild fires as detected by the ATSR instrument, we can see that the formaldehyde enhancements, are spatially closely correlated with the biomass burning events.
The ATSR wild fire atlas is useful in that, if we over plot it onto the GOME data over several years, we find that we can identify two distinct regions. An eastern region where biomass burning events are very common and a western area in which wild fires are less frequent
Focussing on the eastern Amazonian, if we plot the time series of GOME monthly means over this region against the number of fire counts then a clear correlation exists indicating that biomass burning is the main source of the increase formaldehyde.
If we want to determine biogenic isoprene emissions we need to remove the biogenic component.
We can attempt this by isolating the western region and removing all grid boxes where fire occur.
When we now plot the formaldehyde time series over this region, we see firstly, that the columns are lower and secondly, that there is two maximums during the course of the year.
In situ isoprene data, at a point location, within the Amazonian basin, published Trotsdorf, shows similar behaviour.
The peak in September/October during the dry season, most likely arises from increased isoprene emissions owing limited water availability, whilst the peak in March may possibly be related to the transport of biomass burning.
Transport of biomass burning ?
Water availability

17. Tropics: GEOS-CHEM 3 vs. GEOS-CHEM 4
August 2001
Plots smoothed with 3x3 box-car filter!

18. GOME VCDs: July-Dec 1997
Plots smoothed with 3x3 box-car filter!

19. GEOS-CHEM v4 VCDs: July-Dec 1997
We need to clarify the origin of these features and try to replicate them using GEOS-CHEM so we can be confident we can model the isoprene emissions over this region correctly.
However, from the simulations we have done so far, we have noticed a significant difference between the GEOS-CHEM 3 to GEOS-CHEM 4 vertical formaldehyde columns, over the southern hemisphere tropical regions (both over the Amazon and the Congo basin). More precisely, GEOS-CHEM 4 are unrealistically higher, with respect to GEOS-CHEM 3 as illustrated by these plots here, and also with respect to GOME.
This is evident by plotting the GOME verticals columns over the course of the dry season, shown here, and then the corresponding GEOS 4 model columns. As you can see there the model columns are way to high.
Hmm?
Plots smoothed with 3x3 box-car filter!

20. August 2001 T2M TS Environmental factors affecting isoprene emissions:
temperature (exponential dependn)
solar irradiance
leaf area index
leaf age
T2M TS
We believe that the difference in the vertical columns may be related to the input 3 hour average temperature fields which in turn directly affect isoprene emissions. [Comment on temp eqn]
On the left hand side of these plots we have the GEOS-CHEM 4 surface air temperature and isoprene emissions and the right hand side is the corresponding data for GEOS 3. They are quite different.
Plotting the difference between the temperature
GEOS 4
GEOS 3

21. 4-3
T2M TS
4-3
GEOS 4
GEOS 3

22. Initial emission estimates: using GEOS-CHEM 3
9.90 TgC
8.01 TgC
15.98 TgC
GOME
GOME
GOME
MEGAN
MEGAN
MEGAN
9.01 TgC
9.26 TgC
11.91 TgC
Plots smoothed with 3x3 box-car filter!

23. Contribution of other VOCS ?
Mean hourly VOC emissions 1-13 June 2006 in northern Benin ~9.3°S, 1.4°W (Data from African Monsoon Multidisciplinary campaign)
Future work: Use Master Chemical Mechanism to estimate time-dependent production of HCHO from limonene

24. Summary GOME & OMI HCHO columns
Have the potential to help improve our understanding of isoprene in tropical regions & better quantify isoprene emission inventories
GEOS-CHEM 4 very high HCHO columns over tropics
Welcome thoughts & suggestions
Can produce initial estimates (using GEOS-CHEM 3)
Separate out pyrogenic component
Identify contributions of other VOCs (e.g. limonene)