road transport‘s emission inventory for the year 2000 · road transport‘s emission inventory...

Road transport‘s emission inventory for the year 2000

Jens Borken & Heike Steller - DLR – Transportation Research, Berlin/DETamas Meretei - KTI – Transportation Research Institute, Budapest/HUFilip Vanhove - TML – Transport & Mobility Leuven/BEwith contributions of S. Baidya and S. Martin (DLR)

with financial support from the EU FP6 within the IP QUANTIFY (www.pa.op.dlr.de/quantify)

2 > GEIA Paris 29.11.2006> Borken

Emission inventory for road transportEmission inventory from road transportation, here for the year 2000.

i.e. all movements of motorised vehicles on public roads; Differentiated by 5 vehicle categories and 4 fuel types.

Tail-pipe exhaust emissions: CO2, SO2, CO, VOC, NMVOC, CH4, NOx, prPMnot included (in this version):

Evaporative emissions (VOC); Brake, clutch + tyre wear, resuspension (PM); Discharges from accidents, maintenance, end-of-life (HFCs)

All countries on the world & on 1°x1° grid

~ to population density with modifications for each region and vehicle category, e.g.: Heavy duty trucks: ~90% in rural areas; mopeds: ~90% in urban areas.


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1970 1975 1980 1985 1990 1995

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% roadtotal

Importance of road transport‘s emissions for climate change

Growing absolute and relative emissions from road transport.

Share of … in 2000: Maritime: 3%, Aviation: 2%

How big climate impact of indirect greenhouse gases?

Data: EDGAR 3.2


Bottom-up (Tier 2), starting from transport activity for 2*5 vehicle categories, on country level:

Passenger tr. Freight transport FuelsCars Light duty vehicles Gasoline- LPG/CNG - (m)ethanolBus Heavy duty vehicles Diesel - biodiesel2 wheelers

activity data per country by TML Leuven (Vanhove et al.)

emission factors per region by KTI Budapest (Meretei et al.)relative to test cycle; regular maintenance assumed: Probably lower estimate

Essential validation: Fuel sales statistics per country/region! (IEA with modifications)

For many countries this is the first calculation for several exhaust gases at thisdifferentiation.

Activity based approach scaled to fuel consumption


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bio vkm HDVLDV

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NAMEU15

LAM

EASJP

NMEASEASASCISAFRCECOCN

bio vkmbuscarmoped

Global transport volumes in y2000

Passenger Freight

rest: 40%rest: 40%

Vanhove et al. 2006


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NAM EU15 LAM EAS JPN MEA SEA CIS AFR SAS CEC OCN

Mtoe

Road fuel consumption (calc.) vs. road fuel sales (IEA)

Global consumption (calc.): 1.370 MtoeGlobal fuel sales (IEA with corrections for CHN, IND): 1.403 Mtoe Δ: -2%

our calc. with5% error bar

IEA

only problematic region

We modelled the biggest consumers individually: USA, EU15, JP, KOR, CHN, HKG, TWN, IND, RUS, BRA, MEX, ARG, VEN

85% of global road fuel consumption !


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NAM EU15 LAM EAS JPN MEA SEA CIS AFR SAS CEC OCN

Mtoe

Road fuel consumption (calc.) vs. road fuel sales (IEA)

Δ Gasoline consumption (calc.) vs. sales (IEA): -3%OECD: -3% / non-OECD: -21%

Δ Diesel consumption (calc.) vs. sales (IEA): -1%OECD: +12% / non-OECD: +10%

diesel

gasoline

We recalculateIRN, SAU, TUR, ISR.

Almost perfect agreement for each fuel type.

All regions match within 5%, except MEA, AFR, OCN.


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Tg/aEDGAR 2.0 (Olivier et al. 1996)EDGAR 3.2 (Olivier et al. 2002)EDGAR 3.2FT (Olivier & v. Aardenne 2005)QUANTIFY (Borken et al. 2006)

Comparison with global road transport‘s emissions: EDGAR

CO2 CO NO2 NMHC w/o evaporation(EDGAR 2000: 27 Tg evap.)

10*CH4

1990 1995/7 2000

1990 1995/7 2000

4223

111

29

15

8

Using EDGAR‘s transport data: Eyring et al. 2005; Granier & Brasseur 2003; Matthes et al. 2003; Matthes 2005; Niemeier et al. 2006.

Borken et al. 2

006 Data: v20

0611

13


Hemispheric distribution of road transport emissions

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Emissions distributed ~ to population densitywith modifications:

2wheels ~90% urban, HDVs ~ 90% rural.

CO2 and NOx equal, for CO and NMVOC different level and distribution.

Of total road transport‘semissions

~60-75% in Northern mid-latitudes,

~33% in tropics,

<10% Southern hemisph. (exc. SO2: 22%)Bo

rken et al. 2

006 Data: v20

0611

13

Americas EUR-CIS

MEASAS

SEA-EAS-JP


Road transport‘s NOx emissions in the year 2000

<30°S: 2%

<0°S: 7%

>0°N: 23%

>30°N: 67%


NOx: Highest emission densities in OECD + IND + CHN

<30°S: 2%

<0°S: 7%

>0°N: 23%

>30°N: 67%


Road transport‘s NMVOC emissions in the year 2000

<30°S: 2%

<0°S: 7%

>0°N: 29%

>30°N: 61%


NMVOC: Highest emission densities in OECD + IND + CHN

<30°S: 2%

<0°S: 7%

>0°N: 29%

>30°N: 61%


Summary: Road transport emissions in 2000NMHCSO2

NOx prPMTotal: 111 Tg Total: 15 Tg

Total: 29 Tg Total: 1,33 Tg

Borken et al. 2

006 Data: v20

0611

3


Bulk (~75%) of road transport emissions in few countries onlyNMHCSO2

NOx prPMTotal: 111 Tg Total: 15 Tg

Total: 29 Tg Total: 1,33 Tg

Borken et al. 2

006 Data: v20

0611

3


Emissions by vehicle category in most important regions

High shares from passenger cars and light trucks –typical for OECD countries.

Gasoline powered vehicles dominate CO, VOC;

diesel powered vehicles dominate NOx, PM, SO2.

Borken et al. 2

006 Data: v20

0611

13

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Tg/a HDTLDTbus2wheelscar

USA

7.1



Borken et al. 2

006 Data: v20

0611

13

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High shares from mopeds, bus and truck;

very little travel with passenger cars (in 2000).

Development of both growth in transport volumes, shift to passenger cars, and reduction in emissionlimits is very dynamic!



Borken et al. 2

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0611

13

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Tg/a HDTLDTbus2wheelscar

USA

7.1

For comparison:

Level factor 2-4 lower, exc. sulfur (!),

Very different vehicleshares,

Each compound dominated by different vehicle types – different per region,

typical pattern,

=> Differentiation needed.


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Variation of emission estimates – the case of OECD countriesUncertainty mostly due to

• distribution between vehicle types,

• uncertainty of emission factors.

Compared to sales data:

• ΔCO2: gasoline <2%, diesel <5%;

• ΔSO2: gasoline <5%, diesel <10%

Compared to other regional inventories, variation in emission factors:

• ΔNO2 ~15%

• ΔCO ~30%

• ΔHC ~50%

• ΔPM ~80%

Borken et al. 2

006 Data: v20

0606

20

EU15


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Borken et al. 2

006 Data: v20

0611

3Variation of emission estimates – the case of non-OECD countries

Emissions estimates more uncertain, as

• irregular driving conditions (overloading),

• irregular maintenance (-> super-emitters),

• higher diversity of fleet with very old, old, and new vehicles,

• high dynamics,

• less reliable data gathering.

Compared to sales data:

• ΔCO2: gasoline ~5-10%, diesel ~10-15%;

• ΔSO2: gasoline ~10-20%, diesel ~20-30%

Compared to other regional inventoriesvariation in emission factors:

• ΔNO2 ~25% ΔCO ~50%

• ΔHC ~75% ΔPM ~100%

CHN


Summary and outlookValidated, consistent, comprehensive and differentiated emission inventory for roadtransport on country by country and 1° longitude by 1° latitude for the year 2000.

New: prPM from gasoline powered vehicles.

~2/3 of total emissions & highest emission densities in Northern mid-latitudes. Only ~10-15 countries are responsible for the bulk of global pollutant emissions:

USA, DE, FR, GB, I, JP, CHN, IND, RUS, BRA, (MEX, THA, IDN)

Vehicles in OECD: Abundant transportation, notably by passenger cars + trucks; Vehicles in non-OECD: High emissions from mopeds, busses, trucks,

but emission from passenger cars are rising.

In progress: Sensitivity of emissions wrt different shares of vehicles and super-emitters; Determine BC/OC & PM1 fractions; Develop transport stories compatible with SRES scenarios for 2025 – 2050 - 2100.


Further readingBorken, Steller, Vanhove, Meretei: GLOBAL AND COUNTRY INVENTORY OF ROAD PASSENGER AND FREIGHT TRANSPORTATION, THEIR FUEL CONSUMPTION AND THEIR EMISSIONS OF AIR POLLUTANTS IN THE YEAR 2000. Transportation Research Record/86th Annual Meeting of the Transportation Research Board, Washington/USA (submitted) www.trb.org

Steller & Borken: Global road transport’s emission inventory for the year 2000.Proceedings of the TAC-Conference, June 26 to 29, 2006, Oxford/UK (in print)www.pa.op.dlr.de/tac

Borken & Steller: Global road transport’s emission inventory for the year 2000.Meteorologische Zeitschrift (in preparition)

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