Page 1 HyWays Riunione COPERT Users – Milano 21 Giugno 2005 HyWays Use of COPERT model for...

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Riunione COPERT Users – Milano 21 Giugno 2005

HyWays

Use of COPERT model for environmental analysis

Antonio Mattucci

ENEA

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Summary

HyWays Project

Aim of environmental analysis

COPERT description

Approach for environmental analysis

Present status and results

Considerations

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HyWays Project

HyWays is an integrated project, whose aim is to evaluate selected stake-holder scenarios for future sustainable hydrogen energy systems. This will lead to recommendations for a European Hydrogen Energy Roadmap, reflecting country specific aspects in the participating member states.

The Roadmap will consider real life conditions, by taking into account not only technological but also institutional, geographic and socio/ economic barriers and opportunities as representative for the different member states.

The Roadmap will describe systematically the future steps to be taken for large-scale introduction of hydrogen as an energy carrier in the transport and power market and as storage medium for renewable energy. It will result in an action plan for the implementation of the hydrogen deployment in Europe, describing at the same time the effects and impacts of this introduction on the EU economy, society and environment. The action plan will propose concrete policy measures, priorities in technology development and train-ing/education.

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HyWays Project

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Aim of environmental analysis

The environmental analysis looks at the effects on environment, as consequence of The environmental analysis looks at the effects on environment, as consequence of

HH22 introduction, in terms of both global and local effects. introduction, in terms of both global and local effects.

Global effects are already considered by Global effects are already considered by MARKAL modelMARKAL model,, which is able able to which is able able to

calculate COcalculate CO2 2 emissions from energy sectors. emissions from energy sectors.

Looking at Looking at local effectslocal effects, , residential residential applications can be important and are to be applications can be important and are to be

taken into account for all the places where they have taken into account for all the places where they have significant impactsignificant impact on on

population, but only for MS where this can be important. Such analysis requires a population, but only for MS where this can be important. Such analysis requires a

clear idea of the new energy systems and their territorial localization. clear idea of the new energy systems and their territorial localization.

Therefore the most important field where the environmental impact can be evaluated Therefore the most important field where the environmental impact can be evaluated

in a general way is the in a general way is the road transportroad transport.. Such analysis will be carried out using Such analysis will be carried out using

COPERTCOPERT modelmodel..

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COPERT model evaluates the emissions from road transport, considering the following vehicle categories, reflecting the UN-ECE classification:

Passenger Cars Passenger Cars M1M1 Light Duty Vehicles Light Duty Vehicles N1N1 Heavy Duty Vehicles Heavy Duty Vehicles N2, N3N2, N3 Urban Buses & Coaches Urban Buses & Coaches M2, MM2, M Two Wheelers Two Wheelers L1, L2, L3, L4, L5L1, L2, L3, L4, L5

Pollutant emissions are calculated considering the different legislations that have imposed specific vehicle emission limits during the last years. To this end the vehicle population for each of the above category is divided according to the specific applicable legislations (i.e. pre-EURO, EUROx, etc.).

COPERT descriptionCOPERT description

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Data to be provided as input:Data to be provided as input:

1. 1. Base Fuel DataBase Fuel Data (overall consumption of the different fuels, in order to check (overall consumption of the different fuels, in order to check the adequacy of the results, fuel specifications, etc.)the adequacy of the results, fuel specifications, etc.)

2. 2. Activity DataActivity Data (fleet composition, number of vehicles , vehicle mileage, …) (fleet composition, number of vehicles , vehicle mileage, …) 3. 3. Usage DataUsage Data (speeds and shares in the different domains, etc) (speeds and shares in the different domains, etc)4. 4. MiscellaneousMiscellaneous (i.e. monthly temperatures, average daily trip distance, (i.e. monthly temperatures, average daily trip distance,

evaporation data, average load for freight transport, etc.) evaporation data, average load for freight transport, etc.)

Data required by COPERT modelData required by COPERT model

COPERT description (2)COPERT description (2)

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Many of COPERT inputs are coming from MARKAL results. Among them we can insert the number of vehicles, organized in categories and types, the annual traveled mileage, the share of their use in different domains, the fuel consumption, etc. This doesn’t mean that MARKAL information can be automatically transferred to COPERT, as:1. The assumptions made under the two models are different; therefore a simple association of MARKAL values to similar COPERT structures is normally inadequate, as often there is neither a mutual complete overlapping, nor any easy formal way to modify MARKAL data to fit the COPERT schematisation in all the cases2. MARKAL data are typically cumulative values averaged in a decade and their distribution to the many vehicle technologies considered in COPERT for the same category can hardly be schematized in a clear and consistent way for all the vehicles3. COPERT, as it is normally used to calculate road transport emission inventory, imposes a consistency check on the overall fuel consumption, comparing the fuel result with total fuel sold in the MS, to qualify the emission calculation, but this requires real data on fuel and fleet composition, instead of PRIMES forecasts.

Input/output – Framework considerationsInput/output – Framework considerations

Approach for environmental analysisApproach for environmental analysis

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COPERT needs other inputs in addition to MARKAL results, in particular the number of vehicles belonging to the technologiestechnologies that are applicable to each specific vehicle category, and this is required for each countryeach country.

Therefore a modelmodel, able to determine year by year the relative sharerelative share of the technologies for each vehicle type in the fleet for the time span from 2000 to 2050, has been developed.To this end a synergy has been activated with TREMOVE DBTREMOVE DB that provides the information, country by countrycountry by country, on the original fleet composition original fleet composition in a way consistent with COPERT, together with the theoretical information to extend the vehicle fleet forecast. . In fact a forecast model is required, as the data provided by TREMOVE DB cover only a time span up to 2020, while under HyWays the timeframe is to be extended to 2050.

Approach for environmental analysisApproach for environmental analysis (2)(2)


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Using TREMOVE database, for each class of vehicles, through the selection of

related data (vehicle type, technology vehicle type, technology and year year), it is possible to build the curves

of vehicle survival probability vehicle survival probability to be used to make the fleet forecast. Such

functions are specific for the different categories of vehicles (passenger cars,

LDVs, buses, etc.) and are also determined for each Member State on the basis of

statistical information.

The survival probability trends are held constant during the forecast period and

for all the technologies belonging to the same vehicle category.



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Survival probability functions

0

0,2

0,4

0,6

0,8

1

1,2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

age

pro

bab

ility

Busses

Cars

Heavy duty vehicles

Light duty vehicles

Motorcycles

Italy

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Survival probability functions

0

0,2

0,4

0,6

0,8

1

1,2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

age

pro

bab

ilit

y

Busses

Cars

Heavy duty vehicles

Light duty vehicles

Motorcycles

Germany

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The results provided by COPERT runs have been discussed with the other Project partners in the general meeting held in April at Munich. Presently it is under execution a second run of the models. In any case the following additional assumptions/positions are considered for COPERT analysis: for the reference year (2000) COPERT model has been made consistent with country statistics in road transport consumption of fuels and with MS vehicle fleet statistics; the parameters (share, speed, etc.) are not changed for all the forecasts two new EURO legislations (V and VI) have been considered in the model (through direct

modification of the ACCESS database), with changes on pollutant limits (EURO V) and in fuel consumption for both of them (i.e. as result of Voluntary Agreements between

car manufacturers and EC) for hydrogen, due to lack of information on specific emissions (mainly NOx for ICE vehicles), no pollutant emission has been considered the new limits on fuel content of SO2 for 2010 have been also introduced the COPERT vehicle population fits the results provided by MARKAL outputs

Present status and resultsPresent status and results

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Preliminary results (IT baseline)Preliminary results (IT baseline)Vehicle population

0

5000000

10000000

15000000

20000000

25000000

30000000

35000000

Year 2000 Year 2010 Year 2020 Year 2030 Year 2040 Year 2050

years

no

. of

veh

icle

s

Passenger Cars

Light Duty Vehicles

Heavy Duty Vehicles

Buses

Motorcycles

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Preliminary results (IT baseline)Preliminary results (IT baseline)CO emissions

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

4500000


years

ton

s

CO urban

CO extra-urban

CO highways

CO total

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HyWays


Preliminary results (IT baseline)Preliminary results (IT baseline)VOC emissions

0

100000

200000

300000

400000

500000

600000


years

ton

s

URBAN

EXTRA_URBAN

HIGHWAY

TOTAL

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HyWays


Preliminary results (IT baseline)Preliminary results (IT baseline)

NOx emissions

0

100000

200000

300000

400000

500000

600000

700000

800000


years

ton

s

URBAN

EXTRA_URBAN

HIGHWAY

TOTAL

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Preliminary results (IT baseline)Preliminary results (IT baseline)PM emissions

0

5000

10000

15000

20000

25000

30000

35000

40000

45000


years

ton

s

URBAN

EXTRA_URBAN

HIGHWAY

TOTAL

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Fuel consumption

0

5000000

10000000

15000000

20000000

25000000

30000000

35000000

40000000

45000000


years

ton

s

URBAN

EXTRA_URBAN

HIGHWAY

TOTAL

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CO2 emissions

0

20000000

40000000

60000000

80000000

100000000

120000000

140000000


years

ton

s

URBAN

EXTRA_URBAN

HIGHWAY

TOTAL

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Preliminary results (Hydrogen scenario Low - DE)Preliminary results (Hydrogen scenario Low - DE)CO emission reduction

0,0%

20,0%

40,0%

60,0%

80,0%

100,0%

120,0%


years

%

CO urban

CO extra-urban

CO highway

CO total

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Preliminary results (Hydrogen scenario Low - DE)Preliminary results (Hydrogen scenario Low - DE)NOx emission reduction

0,0%

20,0%

40,0%

60,0%

80,0%

100,0%

120,0%

Year 2000 Year 2010 Year 2020 Year 2030 Year 2040 Year 2050years

%

NOx urban

NOx extra-urban

NOx highway

NOx total

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Preliminary results (Hydrogen scenario Low - DE)Preliminary results (Hydrogen scenario Low - DE) PM emissions

0,0%

20,0%

40,0%

60,0%

80,0%

100,0%

120,0%


years

%

PM urban

PM extraurban

PM highway

PM total

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HyWays


Preliminary results (Hydrogen scenario Low - DE)Preliminary results (Hydrogen scenario Low - DE)VOC emission

0,0%

20,0%

40,0%

60,0%

80,0%

100,0%

120,0%


years

%

VOC urban

VOC extraurban

VOC highway

VOC total

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Preliminary results (Hydrogen High – MS cumulative)Preliminary results (Hydrogen High – MS cumulative)

Ye

ar

200

0

Ye

ar 2

010

Ye

ar

202

0

Ye

ar

2030

Ye

ar

204

0

Ye

ar 2

050 FR

DEGR

ITNL

NO

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

%

years

Countries

CO emissions

FR

DE

GR

IT

NL

NO

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Yea

r 20

00

Yea

r 20

10

Yea

r 20

20

Yea

r 20

30

Yea

r 20

40

Yea

r 20

50 FRDE

GRIT

NLNO

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

%

years

Countries

NOx emissions

FR

DE

GR

IT

NL

NO

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Ye

ar

200

0

Ye

ar

201

0

Ye

ar

202

0

Ye

ar

203

0

Ye

ar

204

0

Ye

ar

205

0 FRDE

GRIT

NLNO

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

%

years

Countries

VOC emissions

FR

DE

GR

IT

NL

NO

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Ye

ar

200

0

Ye

ar

201

0

Ye

ar

202

0

Ye

ar

203

0

Ye

ar

204

0

Ye

ar

205

0 FRDE

GRIT

NLNO

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

%

years

Countries

PM emissions

FR

DE

GR

IT

NL

NO

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Ye

ar

200

0

Ye

ar

201

0

Ye

ar

202

0

Ye

ar

203

0

Ye

ar

204

0

Ye

ar

205

0 FRDE

GRIT

NLNO

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

%

years

Countries

Fuel consumption

FR

DE

GR

IT

NL

NO

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For all the MS the introduction of hydrogen vehicles provides interesting benefits, at least for the regulated emissions. For the other emissions the analysis has not yet been done.Due to the larger initial penetration of hydrogen vehicles, the most consistent effects are detected in the urban domains, while in the highways the effects are of lower, as trucks are not converted and this keeps high the pollutant emissions.Looking at the two H2 scenarios, the effects are quite different at 2050; from the point of view of the emission the “low” scenario can be considered as delayed of 10-15 years respect to the “high” one. Of course, the main driving factor for pollutant emission reduction is the number of vehicles, as H2 is almost emission free.

Considerations Considerations

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