Fossil fuel biofuel and biomass burning emissions for 2000 2007 trace gases and particles
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Fossil fuel, Biofuel and Biomass Burning emissions for 2000-2007 (trace gases and particles). C. Liousse, B. Guillaume, A. Konaré, C. Junker, C. Granier, J.M. Grégoire, A. Poirson and E. Assamoi. Fossil fuel and Biofuel emissions.

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Fossil fuel biofuel and biomass burning emissions for 2000 2007 trace gases and particles
Fossil fuel, Biofuel and Biomass Burning emissions for 2000-2007 (trace gases and particles)

C. Liousse, B. Guillaume, A. Konaré, C. Junker, C. Granier, J.M. Grégoire, A. Poirson and E. Assamoi


Fossil fuel and biofuel emissions
Fossil fuel and Biofuel emissions

++ For the first time to our knowledge a coherent inventory for gases and particles based on the same method and proxy data (fuel consumption, fuel usage..)

- - Africa data are extracted from our global model of emissions

Pollutants : CO, CO2, NOx, NMVOC, SO2, BC, OCp, OCtot

African Emissions are provided country by country

Spatialization is done by using the GISS population map


A bottom-up method (based on Junker and Liousse, ACPD 2006)

United Nations : Energy database

Fuel consumption data for 185 countries, 33 different fuels and over 50 different

usage/technology categories

Emissions are fuel-dependant, fuel usage-dependant and technology-dependant

Our « lumping » :

Industrial/Domestic/Traffic

Developed/Semi developed/Developing

=> Emission factors for 3 country classifications, 8 different fuels and 3 usage categories

Population density within each country (population map) and emissions country/country =>

1°X1° spatial distribution of emissions


EF values for gases

CO, NOx, SO2, NMVOC

CO2


EF (BC)…

EF (OCp)…

EF values for Black carbon and primary organic carbon


BC (tons/1°x1°)

0

250

500

1000

2500

5000

Year 2000 Africa

Fossil fuel and biofuel combustions

BC

0.64 Mt(BC)

CO

49.7 Mt(CO)

CO (kt/1°x1°)

0

25

50

100

250

500


0

0.05

0.1

1000

1

2.5

5

100

0.25

0.5

10

(kt/1°x1°)

Year 2000 Africa

Biofuel and Fossil fuel combustions

SO2

NMVOC

NOx

10.1 Mt(SO2)

5.5 Mt(NMVOC)

5.6 Mt(NO2)




Comparison with edgar 2000
Comparison with EDGAR 2000

  • NMVOC : 8,35 Mtons/(5,5-6,7)* Mtons : (-20%)->(-34%)

  • CO : 72,6 Mtons/49,7 Mtons : -31,5%

  • Less domestic emissions

  • NOx : 4,9 Mtons/5,6 Mtons : + 14%

  • SO2 : 4,17 Mtons/10,1 Mtons : +142%

    => Important role of South Africa

(*depending on NMVOC Emission factors)


To conclude
To conclude

  • We have constructed a flexible and coherent inventory for gases and particles with the same proxidata and assumptions

African Biofuel and fossil fuel emissions :

In AMMA : EF characterization for unknown fuels (zems, trucks…)

On going in our programs (POLCA and SACCLAP) :

An improvement of African fuel consumption database

  • UNdata update from African database (in construction)

    ex : diesel consumption in Ivory Coast : + 200% when considering Africaclean database => phD E. Assamoi 2007-2010

  • By considering the appropriate fuel consumption (zems, trucks..)


Urban emission characterization at Cotonou - May 2005, August 2006

A fixed station at the most polluted place

(Aerosol size, chemical composition, optical properties, CO/CO2…. )

Measurements of emission factors (« zem », trucks…)

First example : CO/CO2 = 0.42

EF(Black carbon) = 0.79g/kgdm


Urban emission characterization at Cotonou - May 2005 August 2006

A mobile experiment : transects in Cotonou with

a taxi equipped by different samplers) : high level

of concentrations


Biomass burning emissions savanna forest and agricultural fires
Biomass burning emissions August 2006(savanna, forest and agricultural fires)

The most adapted method to derive african BB emissions:

  • a bottom up method based on satellite burnt area map (see BBSO workshop, Dec. 2005))

    Pollutants : BC, OCp, OCtot, CO, CO2, NOx, NMVOC, SO2

    and all the species listed in Andreae and Merlet, 2004

    Emissions = SB x GLCv x BEv x BDv x EFv

    SB : area burned => GBA 2000 product (0.5°x0.5°, monthly)

    => L3JRC 2000-2007 products (1kmx1km, daily)

    GLCv : quantity of vegetation v present in cell (%) => GLC 2000 map (0.5°x0.5°)

    BEv,BDv : biomass density and burning efficiency by vegetation type

    EFv : emission factor by vegetation type

    => An important work based on Liousse et al., 2005, Michel et al., 2006 with inputs of P. Mayaux (Ispra) considering the GLC vegetation types


Intercomparison with our other August 2006

African Biomass burning BC emissions

Hao statistical data

Mouillot Burnt areas

AVHRR Burnt areas

ATSR-GBA products

SPOT GBA Burnt areas


GLC map (Ispra) ( 0.5°x0.5°) August 2006

Our assumptions…


Burned areas (km August 20062/0.5°x0.5°)

0

250

500

1000

2500

5000

January 2000

July 2000

August 2000

92000 km2

73000 km2

51000 km2

December 2000

125000 km2


Burned Areas August 2006

Burned Biomass

723 Mt(dry matter)

125000 km2

CO

BC

448 kt(BC)

51 Mt(CO)

December 2000


BC (tons/0.5°x0.5°) August 2006

5000

0

07/2000

08/2000

01/2000

BC emissions in TgC in 2000

12/2000

448 kt(BC)

  • Suitable comparison between UMD/GLC

  • High difference if comparing with the old inventory


Comparison with edgar 20001
Comparison with EDGAR 2000 August 2006

  • CO : 222,5 Mtons/285 Mtons : +28%

  • NOx : 11 Mtons/18 Mtons : + 64%

  • SO2 : 2,03 Mtons/1,9 Mtons : -6,4%


BC (tons/1°x1°) August 2006

0

250

500

1000

2500

5000

10000

25000

African BC emissions by source types

Biomass

burning

These inventories have been tested

In ORISAM-TM4 and RegCM3 models

2.28 Mt(BC)

Biofuel

combustions

Fossil fuel

combustions

0.20 Mt(BC)

0.44 Mt(BC)


What is available? August 2006

All these inventories available for the AMMA people.

=> Fossil fuel and biofuel : 1°x1°, yearly, 2000-2003

=> Biomass Burning :

2000 : 0.5°x0.5°, monthly => now

2000-2007 : 1kmx1km, daily => in autumn 2007

(upon request with your needed spatial and temporal scales)


CAPEDB : August 2006

Fossil fuel and biofuel sources


GBBE : August 2006

Biomass burning sources


Impact of NO emissions from soils on ozone formation under tropical conditions.

C. Delon*, D. Serça, J.P. Chaboureau, R. Dupont, C.Mari

Model: MesoNH Chemistry.

Res: 20km/20km, 100/100 points.

52 vertical levels (surface to 28km).

From 05/08 00h to 07/08 2006 00h.

ECMWF every 6h dynamic forcing.

Vertical profiles of clean atmosphere for chemical initialisation.

RACM chemical scheme.

Parameterized convection (Bechtold et al., 2001) and NOx from lightning (Mari et al., 2006).

NO source from soil from a Neural Network parameterization (Delon et al., 2007).

SOIL NOX EMISSIONS in the ANN parameterization are linked to surface temperature and WFPS, deep soil temperature (20-30cm), fertilization rate, soil pH, sand percentage, and wind speed.

pH and soil moisture are the most determinant parameters.


Impact on ozone and nox concentrations
Impact on ozone and NOx concentrations tropical conditions.

NOx CONCENTRATIONS from 0 to 2000m without (left) and with (right) NO emissions from soils. Concentrations reach 300 ppt at noon when NO are emitted by the soil (<20ppt if no emissions). Measured NOx concentrations range from 100 to 500 ppt at 500m height.

OZONE FORMATION in the lower troposphere (0-2000m) is enhanced by NO emissions from soils (+10 ppb). Measured O3 concentrations reach 43 ppb.

NOx concentrations (ppt) 2006/08/06 noon.

Vertical cross section along the BAE-227 flight path (NE of Niamey).

The introduction of an on line soil NO emissions calculation in MesoNHC is an important step to improve chemistry description in the lower troposphere. The relation between NO flux and physical and meteorological parameters ensures an immediate impact of NO emissions on ozone levels (not possible with monthly inventories).

O3 concentrations (ppb) 2006/08/06 noon.


What is available
What is available? tropical conditions.

  • Soil NO flux parameterisation:

    with j=17

    where x1 to x7 correspond to surface WFPS, surface soil temperature, deep soil temperature, fertilisation rate, sand percentage, pH and wind speed respectively

    Easily pluggable in regional chemistry transport models.

. Available soon: NO flux inventory for the rainy season in West Africa (4-21°N, -5-13°E).

Other seasons (dry and transition) will come in 2008.


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