danish emissions inventory for black carbon

NATIONAL ENVIRONMENTAL RESEARCH INSTITUTEAARHUS UNIVERSITY

Danish Emissions Inventory for Black Carbon

Joint TFEIP/EIONET Meeting and Workshop 2nd - 4th May 2011, Stockholm, Sweden

Morten Winther and Ole-Kenneth NielsenDepartment of Policy AnalysisNational Environmental Research InstituteAarhus University

NATIONAL ENVIRONMENTAL RESEARCH INSTITUTEAARHUS UNIVERSITY 3 May 2011Morten Winther and Ole-Kenneth Nielsen

Disposition› Background

› Environmental concerns› Inventory and general approach

› Activity data› Stationary sources› Mobile sources

› Emission factors› Stationary sources› Mobile sources

› Calculation method

› Results

› Conclusions


Background•The part of the total particles (TSP) emitted as primary carbonaceous aerosols during fuel combustion are classified as Black Carbon (BC) and Organic Carbon (OC). BC is the light-absorbing part of the particles (soot)

•BC has global warming properties due to it’s ability to absorb light over reflective surfaces, and due to it’s darkening effect when deposited to snow and ice surfaces

•Due to the relatively short residence time in the atmosphere (weeks), BC is regarded as a short-lived climate forcer (SLCF), and seen from a global warming perspective the short term benefits of reducing BC seems promising


Background

•This presentation explains the first BC emission inventory made for Denmark, covering all fuel consumption sources

•The inventory period is 1990-2030

•The full project also cover Greenland and the Faroe Islands, with OC estimates being made as well.

•Basis: A detailed inventory of TSP, and BC shares of TSP

•In general, the activity data and emf’s shown in the following are somewhat aggregated, due to the large number of emission layers in the inventory as such.


Activity data – stationary sources

Fuel consumption - residential plants

0

20

40

60

80

100

120

1990 1995 2000 2005 2010 2015 2020 2025 2030

PJ

Coal Wood Straw Gas oil Natural gas Total

Fuel consumption - other stationary

0

100

200

300

400

500

600

700

1990 1995 2000 2005 2010 2015 2020 2025 2030

PJ

Biogas Coal Fuel oil Gas oil

Natural gas Orimulsion Petroleum coke Straw

Waste Wood Total

•Residential plants: Stoves, boilers, fireplaces •Large point sources: Power plants, district heating plants, refineries

•Small comb. sources in commercial/institutional, agriculture, manufacturing industries sectors


Activity data

•Fuel data from Danish Energy Authority (DEA); historical and forecast

•Sharp increase from 2000-2008 is due to increase in fuel prices for other fuels than wood, and popularity (cosiness).

•Penetration of technologies from 2000+ examined by Illerup et al. (2007)

•Less detailed info exist for 1990-1999, assumptions are made in order to stratify into technologies

Fuel consumption - residential wood

0

5

10

15

20

25

30

35

40

1990 1995 2000 2005 2010 2015 2020 2025 2030

PJ

Old stove (<1990) New stove (1990-2005)Modern stove (>2005) Eco stoveFireplaces Old boiler w. acc. tank (<1980)Old boiler w/o. acc. tank (<1980) New boiler w. acc. tank (>1980)New boiler w/o. acc. tank (>1980) Pellet stove/boiler


Diesel passenger cars

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5

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40

45

50

55

60

1990 1995 2000 2005 2010 2015 2020 2025 2030

Fu

el

co

ns

um

pti

on

PJ

Conv. Euro 1 Euro 2 Euro 3 Euro 4 Euro 5 Euro 6

Diesel vans

0

5

10

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20

25

1990 1995 2000 2005 2010 2015 2020 2025 2030

Fu

el

co

ns

um

pti

on

PJ


Trucks

0

5

10

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25

30

35

40

45

50

1990 1995 2000 2005 2010 2015 2020 2025 2030

Fu

el

co

ns

um

pti

on

PJ

Conv. Euro I Euro II Euro III Euro IV Euro V Euro VI

Buses

0

1

2

3

4

5

6

7

8

9

1990 1995 2000 2005 2010 2015 2020 2025 2030

Fu

el

co

ns

um

pti

on

PJ


•Diesel fuel consumption stratified into technologies by using 1) DK fleet/mileage data, 2) COPERT IV FC factors, and 3) fuel data from DEA; fuel results aggregated from engine size/weight class•The later year’s dieselification of the car fleet is very visible; it is expected to continue in the future


Diesel consumption - other mobile

0

5

10

15

20

25

1990 1995 2000 2005 2010 2015 2020 2025 2030

PJ

Industry (1A2f) Railways (1A3c) Navigation (1A3d)

Ag./for. (1A4c) Military (1A5) Fisheries (1A4c)

Agricultural non road

0

5

10

15

20

25

1990 1995 2000 2005 2010 2015 2020 2025 2030

Fu

el

co

nsu

mp

tio

n P

J

<1981 1981-1990 1991-Stage I Stage I

Stage II Stage IIIA Stage IIIB Stage IV

Industrial non road

0

2

4

6

8

10

12

14

16

1990 1995 2000 2005 2010 2015 2020 2025 2030

Fu

el

co

nsu

mp

tio

n P

J

<1981 1981-1990 1991-Stage I Stage I


•DEA – straight out: Railways, military, fisheries•Non road machinery and navigation: Bottom-up •Fuel shares for Stage IIIB-IV (PM filters) are more dominant for agriculture compared to industry


Emission factors

•Residential wood and other stationary•TSP: Danish inventory (misc. sources)•BC: GAINS (Kupiainen and Klimont, 2004;2007)

•Road transport exhaust and non exhaust•TSP: COPERT IV•BC: COPERT IV (exh.)/GAINS (non exh.)

•Other mobile sources•TSP: Danish inventory (misc. sources)•BC: Railways, non road, military; road transport analogies•BC: Navigation (plume measurements; Lack et al. (2009))•BC: Aviation: (own assumptions based on GAINS)


Calculation method: Exhaust sources

E = emissions in tonnesFC = fuel consumption in PJEF = emission factor in g GJ-1

i = emission component, j = mobile category/stationary sectork = technology, f = fuel type, y = inventory year

yfkjiyfkjyfkji EFFCE ,,,,,,,,,,,

ykjiyjykji EFME ,,,,,,,

E = emissions in tonnesM = total mileage (109 km)EF = emission factor in mg km-1

i = emission component, j = vehicle typek = wear type, y = inventory year

Calculation method: Non-exhaust (brake/tyre/road

wear)


Results

TSP emissions

0

5000

10000

15000

20000

25000

1990 1995 2000 2005 2010 2015 2020 2025 2030

To

ns

Residential plants Other stationary Road (exhaust)

Road (non exhaust) Other mobile

BC emissions

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

1990 1995 2000 2005 2010 2015 2020 2025 2030

To

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Residential plants Other stationary Road (exhaust)

Road (non exhaust) Other mobile

•The total emissions of TSP and BC decrease by 14 % and 28 %, respectively from 1990-2030

•Residential plants is the largest source: TSP and BC emission shares were 70 % and 62 % in 2008.

•Residential plants: TSP and BC emissions drop by 16% and 28 % from 1990-2030

•TSP and BC emission changes for smaller sources: Road exhaust (-93%, -97%), other mobile (-84%,-87%),

other stationary (-3%,+9%),road non-exhaust (+65%, +68%)

.


TSP emissions - residential wood combustion

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2000 2005 2010 2015 2020 2025 2030

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ns


BC emissions - residential wood combustion

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2000 2005 2010 2015 2020 2025 2030

To

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•From 2008-2030, the TSP[BC] emissions decrease by 59%[61%]

•BC shares of TSP are assumed to be constant for stoves and boilers. This is due to lack of data.

Fuel consumption - residential wood

0

5

10

15

20

25

30

35

40

1990 1995 2000 2005 2010 2015 2020 2025 2030

PJ



TSP emissions - Diesel cars

0

100

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500

600

700

800

1990 1995 2000 2005 2010 2015 2020 2025 2030

To

ns


BC emissions - Diesel cars

0

100

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600

1990 1995 2000 2005 2010 2015 2020 2025 2030

To

ns

Conv. Euro 1 Euro 2 Euro 3 Euro 4 Euro 5 Euro VI

•Euro 5+ cars (vans), must have filters installed in order to meet the EU limits

•Filters even more efficiently removes black carbon

•The calculated BC share of TSP drops from 82 % in 2008 to 14 % in 2030

Diesel cars

BC% of TSP

Euro 1: 70%

Euro 2: 80%

Euro 3: 85%

Euro 4: 87%

Euro 5: 10%

Euro 6: 10%


TSP emissions - Trucks

0

100

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800

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1300

1990 1995 2000 2005 2010 2015 2020 2025 2030

To

ns


BC emissions - Trucks

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100

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600

700

1990 1995 2000 2005 2010 2015 2020 2025 2030

To

ns


•Euro VI trucks (buses), filters are required due to the emission legislation limits

•The BC share of TSP is expected to drop from 67 % in 2008 to 18 % in 2030

Trucks

BC% of TSP

Euro 1: 65%

Euro 2: 65%

Euro 3: 70%

Euro 4: 75%

Euro 5: 75%

Euro 6: 15%


TSP emissions - Agricultural non road

0

100

200

300

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500

600

700

800

900T

on

s

<1981 1981-1990 1991-Stage I Stage I


TSP emissions - Industrial non road

0

100

200

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400

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600

700

800

900

To

ns

<1981 1981-1990 1991-Stage I Stage I


BC emissions - Agricultural non road

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To

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<1981 1981-1990 1991-Stage I Stage I


BC emissions - Industrial non road

0

100

200

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To

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<1981 1981-1990 1991-Stage I Stage I


•Agriculture: Stage IIIB-IV are equipped with filters; hence BC reductions > TSP reductions

•Industry: No filter requirements for engines < 37 kW, fuel share being significant; hence low impact on BC


Conclusions

•The total emissions of TSP and BC decrease by 14 % and 28 %, respectively from 1990-2030

•Residential combustion is the largest source of TSP and BC emissions; 2008 calculated shares are 70 % and 62 %, respectively

•Filters very efficiently reduce BC: For diesel cars[trucks], the BC shares of TSP go from 82%[67%] in 2008 to 14%[18%] in 2030.


Conclusions

•Emission measurements of BC shares of TSP are needed for residential wood combustion installations in order to improve the BC inventories

•Filter technology for residential stoves and for small non road engines needs to be developed; the potential TSP and BC emission savings are large.

•The work made in this project may serve as an input for other inventory makers in Europe, and as input for dispersion modelling, following a GIS distribution of the emission results


Thank you for your attention!

The present project has been funded by the Danish Environmental Protection Agency as part of the environmental support program DANCEA – Danish Cooperation for Environment in the Arctic. The inventory emission results serve as an input for the Task Force on Short Lived Climate Forcers under the Arctic Council.

danish emissions inventory for black carbon

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