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

++ 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 countrySpatialization is done by using the GISS population

map

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

United Nations : Energy databaseFuel consumption data for 185 countries, 33 different fuels and over 50 differentusage/technology categories

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

Our « lumping » :

Industrial/Domestic/TrafficDeveloped/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

Com Dom Ind Com Dom Ind Com Dom Ind Com Dom Ind

Solid fuel

Develop. 13,6 45 a 4,1a 3,85 2,02a 7,34a 16,3 14 19 0.29 1,7 0.05

Semi-Dev. 24,6 73,8 8,2 6,97 3,31 14,7 29 23 38 0,53 2,8 0.10

Developing 47,3 73,8 30,3 13,4 3,31 54,3 57 23 141 1 2,8 0,4

Fuelwood

Develop. 20,7 63d 6,8d 1,84 1,1ad 3,1ad 0.4 0.2 0.75 3 7,3 1.25

Semi-Dev. 20,7 63 6,8 1,84 1,1 3,1 0.4 0.2 0.75 3 7,3 1.25

Developing 24,8 75,6 8,16 2,21 1,33 3,67 0.46 0.4 0.9 3,6 8,8 1,5

Charcoal

Dévelop. 200 200e 0 5,97 5,97e 0 0.4 0.4 0. 2.7 2.7 0

Semi-Dev. 200 200 0 5,97 5,97 0 0.4 0.4 0. 2.7 2.7 0

Developing 200 200 0 5,97 5,97 0 0.4 0.4 0. 2.7 2.7 0

Peat

Develop. 200 200 0 5,97 5,97 0 0.4 0.4 0. 4,9 4,9 0

Semi-Dev. 200 200 0 5,97 5,97 0 0.4 0.4 0. 4,9 4,9 0

Developing. 200 200 0 5,97 5,97 0 0.4 0.4 0. 4,9 4,9 0

Aviation

Develop. 6b 6 6 14b 14 14 1 1 1 1.7 1.7 1.7

Semi-Dev. 6 6 6 14 14 14 1 1 1 1.7 1.7 1.7

Developing 6 6 6 14 14 14 1 1 1 1.7 1.7 1.7

Diesel/Heavy fuel

Develop. 7,4c 0,24a 4 6,88c 3,3a 5 0,14 2,8 1,5 2,17 0.13 1 ,2

Semi-Dev. 14,8 0,31 5,8 13,8 4,29 7,25 0,29 3,64 2,2 4,3 0.17 1,74

Developing 37 1,2 13,3 34,4 16,5 16,6 0,72 14 5 10,8 0.65 4

Motor gazoline

Develop. 9,76c 4,55c 4,55c 9,76c 4,55c 4,55c 0.5 0.5 0.5 17 8,4 8,4

Semi-Dev. 48,8 22,7 22,7 48,8 22,7 22,7 2,4 2,4 2,4 85 42 42

Developing 48,8 22,7 22,7 48,8 22,7 22,7 2,4 2,4 2,4 85 42 42

Gaz (natural, GPL…)

Develop. 3,02 2,29d 3,98d 3,02 2,29d 3,98d 8.e-4 1.e-4 7.e-3 0,63 1,66 0,24

Semi-Dev. 3,02 2,29 3,98 3,02 2,29 3,98 8.e-4 1.e-4 7.e-3 0,63 1,66 0,24

Developing 3,02 2,29 3,98 3,02 2,29 3,98 8.e-4 1.e-4 7.e-3 0,63 1,66 0,24

Table 2: Emission factors for CO, NOx, SO2 and NMVOC for different uses ; Comb = Combined (or traffic) ; Dom = Domestic ; Ind = Industrial Ref : (a) http://www.aeat.co.uk/netcen/airqual/naei/annreport/annrep96 (b): http://www.ipcc-nggip.iges.or.jp/public/gp/bgp/2_5_Aircraft.pdf (c): http://www.ipcc-nggip.iges.or.jp/public/gl/guidelin/ch1ref4.pdf (d): http://www.transport.govt.nz/business/multimodal/environment/vehicle/hapinz/28.php (e): Andreae et Merlet, 2001

CO2 (CO2 g/kg) All sectors Solid fuel 2483 (a) Fuelwood 1550 (b) Charcoal 2611 (b) Peat 2611 Aviation 3212 (a) Diesel/Heavy fuel 3108 (a) Motor gazoline 3168 (a) Gas (Natural, GPL, …) 2435 (a)

EF values for gases

CO, NOx, SO2, NMVOC

CO2

Com Dom Ind Com Dom Ind

Solid fuel

Develop. 0.46 1.39 0.15 0.66 2.92 0.15

Semi-Dev. 0.82 2.28 0.30 1.19 4.77 0.30

Developing 1.58 2.28 1.1 2.29 4.77 1.1

Fuelwood Develop. 0.67 0.75 0.6 2.02 2.25 1.8

Semi-Dev. 0.67 0.75 0.6 2.02 2.25 1.8

Developing 0.81 0.9 0.72 2.43 2.7 2.16

Charcoal Develop. 0.75 0.75 0.75 2.25 2.25 2.25

Semi-Dev. 0.75 0.75 0.75 2.25 2.25 2.25

Developing 0.75 0.75 0.75 2.25 2.25 2.25

Peat Develop. 0.3 0.67 0.13 2.71 6.07 1.21

Semi-Dev. 0.3 0.67 0.13 2.71 6.07 1.21

Developing 0.3 0.67 0.13 2.71 6.07 1.21

Aviation Develop. 0.1 0.1 0.1 1.15 1.15 1.15

Semi-Dev. 0.1 0.1 0.1 1.15 1.15 1.15

Developing 0.1 0.1 0.1 1.15 1.15 1.15

Diesel/Heavy fuel Develop. 1 0.07 0.2 0.5 0.05 0.42

Semi-Dev. 2 0.09 0.28 1 0.07 0.63

Developing 5 0.35 1 2.5 0.25 2.76

Motor Gazoline Develop. 0.03 0.03 0.03 0.07 0.07 0.07

Semi-Dev. 0.15 0.15 0.15 0.73 0.73 0.73

Developing 0.15 0.15 0.15 0.73 0.73 0.73

Gases (natural, GPL..)

Develop. 6.e-5 1.2e-4 1.e-5 1.1e-4 5.8e-4 2.e-5

Semi-Dev. 6.e-5 1.2e-4 1.e-5 1.1e-4 5.8e-4 2.e-5

Developing 6.e-5 1.2e-4 1.e-5 1.1e-4 5.8e-4 2.e-5

EF (BC)…

EF (OCp)…

EF values for Black carbon and primary organic carbon

Fossil fuel and biofuel combustions

0.64 Mt(BC)BC CO 49.7 Mt(CO)

Year 2000 Africa

0

BC (tons/1°x1°)

500 1000 50002500250 0

CO (kt/1°x1°)

50 100 50025025

Biofuel and Fossil fuel combustions

Year 2000 Africa

NMVOC5.5 Mt(NMVOC)

NOx5.6 Mt(NO2)

SO210.1 Mt(SO2)

0 1000100

(kt/1°x1°)0.1 0.25 1052.510.50.05

Regional differences on the predominant sources over Africa

Biofuel BC Fossil fuel BC

EAST_AFRICAWEST_AFRICANORTH_AFRICASOUTHERN_AFRICACENTRAL_AFRICA

African BF and FF emissions per regions

CO BC

NOx

NMVOC

SO2

EAST_AFRICA

NORTH_AFRICA

WEST_AFRICA

CENTRAL_AFRICA

SOUTHERN_AFRICA

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

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..)

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

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 = 0.42EF(Black carbon) = 0.79g/kgdm

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11/5 08:40 11/5 09:52 11/5 11:04 11/5 12:16

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COTempRHk# partµgBCCO2

A mobile experiment : transects in Cotonou witha taxi equipped by different samplers) : high levelof concentrations

Urban emission characterization at Cotonou - May 2005

Biomass burning emissions (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 EFvSB : 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 typeEFv : 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

African BB emissions of BC (TgC/an)

0

0,5

1

1,5

2

2,5

1900-19101910-19201920-19301930-19401940-19501950-19601960-19701970-19801981-19821982-19831985-19861986-19871987-19881988-19891989-19901990-19911980-19901990 decade

1997199819992000

1990-2000

2000200120022003

Mouillot Burnt areas

AVHRR Burnt areas

SPOT GBA Burnt areas

ATSR-GBA products

Hao statistical data

Intercomparison with our otherAfrican Biomass burning BC emissions

GLC map Density biomass (kg/m2) Combustion efficiency EFCO (g/kg)Broadleaf evergreen GLC1 23,35 0,25 104Closed broadleaf deciduous GLC2 20 0,25 107Open Broadleaf deciduous GLC3 3,3 0,4 65Evergreen needleleaf forest GLC4 36,7 0,25 107Deciduous needleleaf GLC5 18,9 0,25 107Mixed leaf type GLC6 14 0,25 106,9571Tree Cover, regularly flooded, fresh (-brackish) GLC7 27 0,25 104,003Tree Cover, regularly flooded, saline, (daily variation) GLC8 14 0,6 82,7543Mosaic : tree cover/other natural vegetation GLC9 10 0,35 86Shrub, closed-open, evergreen GLC11 1,25 0,9 65Shrub, closed-open, deciduous GLC12 3,3 0,4 65Herbaceous cover, closed open GLC13 1,425 0,9 65Sparse herbaceous or sparse shrub cover GLC14 0,9 0,6 77,69Cultivated and managed areas GLC16 0,44 0,6 92Mosaic : cropland/tree cover/other natural vegetation GLC17 1,1 0,8 70Mosaic : cropland/shrub or grass GLC18 1 0,75 73,812

GLC map (Ispra) ( 0.5°x0.5°)

Our assumptions…

January 2000

December 2000

July 2000 August 2000

0 250 500 1000 2500 5000

Burned areas (km2/0.5°x0.5°)

92000 km2 73000 km2 51000 km2

125000 km2

December 2000

Burned BiomassBurned Areas

BC CO

448 kt(BC)

125000 km2 723 Mt(dry matter)

51 Mt(CO)

0 5000

BC (tons/0.5°x0.5°)

01/2000

12/2000

07/2000 08/2000

448 kt(BC)

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0,05

0,1

0,15

0,2

0,25

0,3

0,35

0,4

0,45

0,5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

GBA:UMD (Konare et al) GBA:GLC (this work) Liousse et al., 1996

BC emissions in TgC in 2000

Suitable comparison between UMD/GLCHigh difference if comparing with the old inventory

Comparison with EDGAR 2000

• CO : 222,5 Mtons/285 Mtons : +28%• NOx : 11 Mtons/18 Mtons : + 64%• SO2 : 2,03 Mtons/1,9 Mtons : -6,4%

African BC emissions by source types

Biomassburning

Biofuel combustions

Fossil fuelcombustions

2.28 Mt(BC)

0.44 Mt(BC) 0.20 Mt(BC)

0

BC (tons/1°x1°)

500 1000 50002500250 10000 25000

These inventories have been testedIn ORISAM-TM4 and RegCM3 models

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)

What is available?

CAPEDB : Fossil fuel and biofuel sources

GBBE : Biomass burning sources

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).

Impact of NO emissions from soils on ozone formation under tropical

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

Soil humidity (%) NO emissions (gN/ ha/ d)

40

35

30

25

20

15

10

5

0

8

7

6

5

4

3

2

1

0

Mali Niger

Bur kina FasoNiger ia

Benin

Togo

Ghana

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

1000ppt

500

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0

Without soil NO emission With soil NO emission

6.5°E17.5°N

2 km1.81.61.41.210.80.60.40.20

2.3°E13.5°N

1000ppt

500

200

100

50

20

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5

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NOx concentrations (ppt) 2006/08/06 noon.Vertical cross section along the BAE-227 flight path (NE of Niamey).

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.

44 ppb424038363432302826242220

44ppb424038363432302826242220

With soil NO emissionWithout soil NO emission

2.3°E13.5°N

6.5°E17.5°N

2 km1.81.61.41.210.80.60.40.20

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

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).

What is available?• Soil NO flux parameterisation:

with j=17

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.

)tanh(.)tanh(.)tanh(. 32722612524 SwSwSwwNOfluxnorm +++=

∑

∑

∑

=

=

=

+=

+=

+=

23

17,163

15

9,82

7

1,01

inormji

inormji

inormji

xwwS

xwwS

xwwS

. 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.