1. COPERT 4
Dimitrios Gkatzoflias Charis Kouridis Giorgos Mellios Leon Ntziachristos
Copenhagen,

2. Activity data (Fleets project) General guidance
Contents
Background & History
Users and Uses
Versions
Methodology
Activity data (Fleets project)
General guidance
Exhaust PM and airborne particle emission factors
Non-exhaust PM
Comparison of centralised and national emission estimates
Wish List
Contact Info

3. Background & History

4. Status of COPERT – Administrative Info
The name stands for COmputer Programme to calculate Emissions from Road Transport
Now in its COPERT 4 Version (fourth update of the original COPERT 85)
It incorporates results of several research and policy assessment projects
It is basically funded by the European Environment Agency through the ETC-ACC budget
It is scientifically and technically supported by the Lab of Applied Thermodynamics
It has recently attracted much attention from the Joint Research Centre in Ispra who are further supporting its technical development

5. Status of COPERT – Technical Info
Calculates emissions of all (important) pollutants from road transport
Covers all (important) vehicle classes
Can be applied in all European countries and in several Asian ones
Can be used to produce total emission estimates from 1970 to 2020 (up to 2030 in TREMOVE)
Provides a user-friendly (MS-Office like) GUI to introduce and view data

6. History - Early Generations

7. History - COPERT II and III
COPERT II was the first one with a GUI, built on MS Access 2 (1996). It provided emission factors up to Euro 1
COPERT III was based on menus, similar to MS Office (2000) and it was built on VBA for MS Access 97. Compared to version II:
New hot emission factors for Euro 1 passenger cars
New reduction factors over Euro 1 according to AutoOil
Impact on emissions from 2000, 2005 fuel qualities
Cold-start methodology for post Euro 1 PCs
Emission degradation due to mileage
Effect of leaded fuel ban in Europe
Alternative evaporation methodology
Detailed NMVOC speciation (PAHs, POPs, Dioxins and Furans)
Updated hot emission factors for non regulated pollutants

8. History - COPERT 4
COPERT 4 is the ‘official’ version since Nov Main differences with Copert III include:
Software-wise
Possibility for time-series in one file
Possibility of more than one scenarios in one file
Enhanced import/export capabilities (mainly Excel)
Configuration of fleet (local/regional vehicle technologies)
Data can be changed at methodological level (emission functions)
Methodology-wise
Hot EFs for PCs and PTWs at post Euro 1 level
Hybrid vehicle fuel consumption and emission factors
N2O/NH3 Emission Factors for PCs and LDVs
Particulate Matter and airborne particle emission factors
Non-exhaust PM
New evaporation methodology
New corrections for emission degradation due to mileage
HDV methodology (emission factors, load factors, road-gradient)

9. Uses & Users

10. STEERS (CONCAWE) TERM TREMOVE COPERT FLEETS AEIG National Inventories
COPERT Usage
STEERS (CONCAWE)
GAINS/ RAINS / EC4MACS
TERM
TREMOVE
COPERT
FLEETS
AEIG
National Inventories
Individual Use

11. Field of applications - National level

12. Field of Applications – Literature 1(2)
Evaluation of COPERT
Robin Smit, Muriel Poelman, Jeroen Schrijver, Improved road traffic emission inventories by adding mean speed distributions, Atmospheric Environment, Volume 42, Issue 5, February 2008, Pages
Fabio Murena, Giuseppe Favale, Continuous monitoring of carbon monoxide in a deep street canyon, Atmospheric Environment, Volume 41, Issue 12, April 2007, Pages
Spyros P. Karakitsios, Vasileios K. Delis, Pavlos A. Kassomenos, Georgios A. Pilidis, Contribution to ambient benzene concentrations in the vicinity of petrol stations: Estimation of the associated health risk, Atmospheric Environment, Volume 41, March 2007, Pages
Ioannis Kioutsioukis, Stefano Tarantola, Andrea Saltelli, Debora Gatelli, Uncertainty and global sensitivity analysis of road transport emission estimates, Atmospheric Environment, Volume 38, Contains Special Issue section on Measuring the composition of Particulate Matter in the EU, December 2004, Pages
M. Ekstrom, A. Sjodin, K. Andreasson, Evaluation of the COPERT III emission model with on-road optical remote sensing measurements, Atmospheric Environment, Volume 38, Contains Special Issue section on Measuring the composition of Particulate Matter in the EU, December 2004, Pages
M. Pujadas, L. Nunez, J. Plaza, J. C. Bezares, J. M. Fernandez, Comparison between experimental and calculated vehicle idle emission factors for Madrid fleet, Science of The Total Environment, Volumes , Highway and Urban Pollution, December 2004, Pages
R. Smit, A.L. Brown, Y.C. Chan, Do air pollution emissions and fuel consumption models for roadways include the effects of congestion in the roadway traffic flow?, Environmental Modelling & Software, Volume 23, October-November 2008, Pages
Robert Joumard, Michel Andre, Robert Vidon, Patrick Tassel, Characterizing real unit emissions for light duty goods vehicles, Atmospheric Environment, Volume 37, Issue 37, 11th International Symposium, Transport and Air Pollution, December 2003, Pages
Morten Winther, Petrol passenger car emissions calculated with different emission models, The Science of The Total Environment, Volume 224, Issues 1-3, 11 December 1998, Pages

13. Field of Applications – Literature 2
Leonidas Ntziachristos, Marina Kousoulidou, Giorgos Mellios, Zissis Samaras, Road-transport emission projections to 2020 in European Urban environments, Atmospheric Environment, October 2008, accepted.
Rajiv Ganguly, Brian M. Broderick, Performance evaluation and sensitivity analysis of the general finite line source model for CO concentrations adjacent to motorways: A note, Transportation Research Part D: Transport and Environment, Volume 13, May 2008, Pages
Hao Cai, Shaodong Xie, Estimation of vehicular emission inventories in China from 1980 to 2005, Atmospheric Environment, Volume 41, December 2007, Pages
B.M. Broderick, R.T. O'Donoghue, Spatial variation of roadside C2-C6 hydrocarbon concentrations during low wind speeds: Validation of CALINE4 and COPERT III modelling, Transportation Research Part D: Transport and Environment, Volume 12, December 2007, Pages
Seref Soylu, Estimation of Turkish road transport emissions, Energy Policy, Volume 35, Issue 8, Pages
R. Bellasio, R. Bianconi, G. Corda, P. Cucca, Emission inventory for the road transport sector in Sardinia (Italy), Atmospheric Environment, Volume 41, February 2007, Pages
Pavlos Kassomenos, Spyros Karakitsios, Costas Papaloukas, Estimation of daily traffic emissions in a South-European urban agglomeration during a workday. Evaluation of several 'what if' scenarios, Science of The Total Environment, Volume 370, November 2006, Pages
G. Lonati, M. Giugliano, S. Cernuschi, The role of traffic emissions from weekends' and weekdays' fine PM data in Milan, Atmospheric Environment, Volume 40, Issue 31, 13th International Symposium on Transport and Air Pollution (TAP-2004), October 2006, Pages
R. Berkowicz, M. Winther, M. Ketzel, Traffic pollution modelling and emission data, Environmental Modelling & Software, Volume 21, Issue 4.
Jose M. Buron, Francisco Aparicio, Oscar Izquierdo, Alvaro Gomez, Ignacio Lopez, Estimation of the input data for the prediction of road transportation emissions in Spain from 2000 to 2010 considering several scenarios, Atmospheric Environment, Volume 39, Pages
Jose M. Buron, Jose M. Lopez, Francisco Aparicio, Miguel A. Martin, Alejandro Garcia, Estimation of road transportation emissions in Spain from 1988 to 1999 using COPERT III program, Atmospheric Environment Volume 38, February 2004, Pages
Roberto M. Corvalan, David Vargas, Experimental analysis of emission deterioration factors for light duty catalytic vehicles Case study: Santiago, Chile, Transportation Research Part D: Transport and Environment Volume 8, July 2003, Pages
Salvatore Saija, Daniela Romano, A methodology for the estimation of road transport air emissions in urban areas of Italy, Atmospheric Environment Volume 36, Issue 34, November 2002, Pages
C. Mensink, I. De Vlieger, J. Nys, An urban transport emission model for the Antwerp area, Atmospheric Environment, Volume 34, Issue 27, 2000, Pages

14. Notes:
Information in this presentation collected from people that downloaded COPERT 4 in the period Jun 2006 – Nov 2007
In total, 1131 individual downloads (without doubles) were registered
The registration is only for people that have actually downloaded COPERT, not just visiting the site.
COPERT 4 Statistics
The following form needs to be filled by users every time COPERT 4 is downloaded (example with artificial data is given).
User's info:
Name: John Smith
Country: Italy
Organization: University of Emissions
Found out from: EEA
Usage: Calculate pollutants emissions
The following charts were produced by processing the information contained in these forms

15. Continent Distribution

16. Distribution of users from Europe

17. Distribution of users from Africa

18. Distribution of users from Asia

19. Distribution of users from America

20. Monthly Distribution of Downloads

21. Daily Distribution of Downloads

22. User Affiliation
Private sector includes consultants, construction companies, emission and transport research, etc.
International organizations include fuel, insurance and transport companies and authorities
Local authorities mainly include regional environmental offices

23. Applications Academic use is for lectures, courses, theses
Evaluation / research : General application not specified in more detail by the users
Emissions / emission factors: Application on particular studies necessitating total estimates or just derivation of emission factors

24. Summary of Copert (III) application – 1(3)
There is a great interest for national inventories
Requires simplicity in interface and limited input from the user
There is a great interest for GHGs emissions
They require a link to higher-level software (i.e. IPCC tables, CollectER, etc.)
Several new MSs and NIS countries still consider that input data are difficult to collect
How to allocate technology classes
How to estimate mileage and road shares
Sometimes use “rule of thumb” methods of questionable quality

25. Summary of Copert (III) application – 2(3)
Several “advanced” countries hesitate using a common methodology
Have developed own tools and are familiar with
Trust own methods provide more accurate results than a generic model
Politics and priorities may also play a role
As a result:
Countries’ absolute contribution may be misjudged
Time-series reporting is less uncertain
Introduction of a new model will require re-estimation in time series
Such a model is a very elegant tool for centralised emission estimates

26. Summary of Copert (III) application - 3
Number of specialised uses is rather infinite
In South Africa, it has been applied to a road 550 km between Durban and East London. Problem was level of maintenance
In Chile and Mexico, it is used for urban inventories in high altitude
Eurocontrol considers its use for estimating road transport contribution to local air quality in airport areas
Particular cases (Greek taxis, small vehicle categories in Italy < 800 cc, technology classes in Eastern Europe, etc.)

27. Versions COPERT 4 VX.Y X… Methodology update Y… Software update

28. COPERT 4 V4.0 – October 2007
Consistent with the following EMEP/CORINAIR Guidebook chapters:
B710: Road Transport (Activities – ) Ver. 6.0
B760: Fuel Evaporation (Activity ) Ver 2.1
Methodology issues added/updated in this version:
Emissions from CNG Buses
Emissions with use of Biodiesel
Distinction of primary NOx emissions to NO2 and NO
Emission factors of Euro 4 Diesel Passenger Cars
Reductions for future emission standards Euro 5, Euro 6 and Euro V, Euro VI
Revised CO2 calculation equations (biofuels and alternative fuels)
Revised CH4 emission factors
Corrected N2O and NH3 emission factors
Revised calculation algorithm for CH4, N2O and NH3 hot/cold emissions

29. COPERT 4 Version 5.0 - December 2007
Consistent with the following EMEP/CORINAIR Guidebook chapters:
B710: Road Transport (Activities – ) Ver. 6.0 with modified N2O emission factors for HDV
B760: Fuel Evaporation (Activity ) Ver 3.0
B770: Road vehicle tyre and break wear (Activity ) Ver 1.0
Methodology issues added/updated in this version:
Determination of the fraction of Elemental and Organic Carbon in exhaust PM
New methodology to calculate evaporation emissions
Inclusion of non-exhaust (tyre & break wear) PM
Updated N2O emission factors for HDV

30. COPERT 4 Version 5.1 - February 2008
Mainly a software update (bug corrections and additions)
Mileage used for N2O and NH3 emission degradation changed (was annual - > became cumulative)
Different RVP and Temperature values per year can be imported from Excel
Corrected mileage import from Excel
Warning message on evaporation emissions removed
Evaporation method now works also for negative temperature values

31. COPERT 4 Version 6.0 - December 2008
Methodology:
Hot emission factors for Hybrid vehicles based on more experimental data (these are considered to include cold-start emissions as well)
Heavy metals emissions include metals from tyre and brake wear
Year 2009 specs fuel added
Software:
Export function for a CRF Reporter XML file. This allows direct exporting of COPERT results for UNFCCC reporting.
Reports regrouped in pollutants without Evaporation Emissions, Pollutants with Evaporation and Heavy Metals.
Information label for the calculation of ‘beta’ (cold-start mileage) added in the “Run Details” table
Inclusion of the NMVOC speciation calculation when pressing the 'All Emissions' button
Modification of 'Country' > Fuel Info' form:
Fuel Consumption can be provided in tonnes or TJ using COPERT, IPCC default or User Conversion Factors.
Selection of the Fuel Effect Year moved from 'Calculation Factors' > 'Fuel Effect' form to 'Country' > 'Fuel Info' > 'Advanced' form.
Improved Fuel Quality Specifications table is moved to 'Country' > 'Fuel Info' > 'Advanced' form.
Modification of the Statistical Annual Fuel Consumption and Fuel Specifications import Excel format so that the user can import different values for each country's year.
Corrected Cold-start Emission Factors calculation. (Bug fixed when only one vehicle type is selected in fleet configuration.)
Corrected PM2.5 and PM10 Emissions calculation (Bug fixed when Emissions for multi-year runs resulted in zero.)
Corrected NO and NO2 Emissions calculation
Corrected Corinair DBF file Export process (Bug fixed concerning multi-years runs.).
Bug fixed concerning the different Regional Settings (comma vs. full-stop format).
Bug fixed concerning runs including more than 18 years.
Bug fixed when Highway Speed was equal to Top Speed of Hot Emissions Factors Parameters.
Amended help topics

32. COPERT 4 version 6.1 - February 2009
Bug fixed when user changed Fuel Specifications and Fuel Effect Year on 'Country' > 'Fuel Info' and 'Advanced' form respectively. An error message might occur with version 6.0.
Bug fixed during Export Data (Excel File) under some specific Windows regional settings. An error message might occur with version 6.0.
The user is now allowed to enter mileage share for urban busses and mopeds also in rural and highway modes. In the previous versions, only urban share was allowed.
The Euro 5 and 6 gasoline passenger car and light duty trucks emission factors of CH4, N2O, NH3 have been inherited by default from Euro 4. They were zero in the previous version.

33. Methodology

34. Vehicle Categories
Passenger Cars
Light Duty Vehicles
Heavy Duty Vehicles
Mopeds
Motorcycles

35. Light Duty Vehicles (Trucks & Vans)
Vehicle Categories
Passenger Cars
Gasoline (<1.4 l, l, >2.0 l)
Diesel (<2.0 l, >2.0 l)
LPG
Light Duty Vehicles (Trucks & Vans)
Gasoline
Diesel
Heavy Duty Vehicles
Diesel (11 weight categories)
Power Two Wheelers
Mopeds (< 50 cc)
Motorcycles (2-stroke, <250 cc, cc, >750 cc)

36. Vehicle Categories – Heavy Duty Vehicles

37. Vehicle Categories – Rigid Trucks (Lorries)

38. Vehicle Categories – Articulated Vehicles= +
Tractor
Semi-Trailer

39. Vehicle Technologies: Passenger Cars & Light Duty Vehicles
PRE ECE (~1970 technology)
Conventional
ECE 15/00-01
LD Euro /59/EEC
ECE 15/02
LD Euro /69/EEC
ECE 15/03
LD Euro /69/EC Stage2000
ECE 15/04
LD Euro /69/EC Stage2005
Improved Conventional
LD Euro 5 - EC 715/2007
Open Loop
LD Euro 6 - EC 715/2007
PC Euro /441/EEC
PC Euro /12/EEC
PC Euro /69/EC Stage2000
PC Euro /69/EC Stage2005
PC Euro 5 - EC 715/2007 (2010 and on)
PC Euro 6 - EC 715/2007 (2015 and on)

40. Vehicle Technologies: HDVs, Busses, & PTWs
Heavy Duty Trucks/Buses
Mopeds/Motorcycles
Conventional
HD Euro I - 91/542/EEC Stage I
Euro /24/EC
HD Euro II - 91/542/EEC Stage II
Euro /24/EC
HD Euro III Standards
Euro 3 – 2002/51/EC (only motorcycles)
HD Euro IV /55/EC
HD Euro V /55/EC
HD Euro VI - COM(2007)851

41. Pollutants which are estimated based on fuel consumption
Pollutants for which a detailed methodology exists, based on specific emission factors
Pollutants which are estimated based on fuel consumption
Group 1
Carbon monoxide (CO)
Nitrogen oxides (NOx: NO and NO2)
Volatile organic compounds (VOCs)
Methane (CH4)
Non-methane VOCs (NMVOCs)
Nitrous oxide (N2O)
Ammonia (NH3)
Particulate matter (PM)
PM number and surface area
Group 2
Carbon dioxide (CO2)
Sulphur dioxide (SO2)
Lead (Pb)
Cadmium (Cd)
Chromium (Cr)
Copper (Cu)
Nickel (Ni)
Selenium (Se)
Zinc (Zn)

42. Pollutants which are derived as a fraction of total NMVOC emissions.
Pollutants for which a simplified methodology is applied, mainly due to the absence of detailed data
Pollutants which are derived as a fraction of total NMVOC emissions.
Group 4
Alkanes (CnH2n+2):
Alkenes (CnH2n):
Alkynes (CnH2n-2):
Aldehydes (CnH2nO)
Ketones (CnH2nO)
Cycloalkanes (CnH2n)
Aromatic compounds
Group 3
Polycyclic aromatic hydrocarbons (PAHs) and persistent organic pollutants (POPs)
Polychlorinated dibenzo dioxins (PCDDs) and polychlorinated dibenzo furans (PCDFs)

43. General Concept for Exhaust Emissions/Consumption
ECOLD [g/veh] = β x M [km] x EFHOT [g/km] x (eCOLD/eHOT-1)
EHOT [g/veh] = M [km] x EFHOT [g/km]
β = lCOLD/lTOTAL

44. What are exhaust emissions dependent on?
Activity
Number of vehicles [veh.]
Distance travelled [km/period of inventory]
Hot Emissions
Technology / Emission Standard
Mean travelling speed [km/h]
Cold Emissions
Ambient temperature [Celsius]
Mean trip distance [km]

45. Methodology: Total Emissions
Total Exhaust Emissions: EEXH = EHOT + ECOLD
Hot (stabilized engine temperature): EHOT = N · M · eHOT
Cold-start emissions: ECOLD =  · N · M · eHOT · (eCOLD/eHOT-1)
Non-Exhaust Emissions
NMVOC from Fuel Evaporation: EEVAP = EDIURNAL + ESOAK + ERUNNING
PM from tyre and brake attrition: EHOT = N · M · ePM

46. Non-exhaust emissions (evaporation)
Breathing Losses
Canister
Vent
Fuel Line
Vapour
Liquid
Engine
Fuel Tank
Permeation / Leakages
Mechanisms causing evaporation emissions
Diurnal emissions
Hot soak emissions
Running losses
Only relevant for Gasoline!
Parked vehicle
Engine running

47. What is evaporation dependant on
Vehicle technology
Tank (vehicle) size
Canister (vehicle) size
Vehicle mileage (adsorption potential)
Temperature variation
Fuel vapour pressure (kPa)
Fuel tank fill level
Parking time distribution
Trip duration

48. Particulate Matter due to road transport is also produced by:
Non – Exhaust PM
Particulate Matter due to road transport is also produced by:
Tyre abrasion
Brake abrasion
Road wear
Emission rates depend on:
Vehicle category (car, truck, motorcycle)
Number of axles/wheels (trucks)
Vehicle load
Vehicle speed

49. Activity Data (FLEETS Project)

50. General Guidance

51. Guide to national road-transport inventory compilation - 1
List open to suggestions
Obtain fuel consumption from national statistics
Estimate effects of tank tourism, black market
From 1 and 2 estimate true consumption of road transport
Collect data on total fleet in operation per category
National registers (cars, light trucks, heavy trucks, busses, motorcycles)
Police (mopeds)
Collect data on vehicle distribution per fuel and sub-category
National registers
Data from countries with similar structure (data from the Fleets project)

52. Guide to national road-transport inventory compilation - 2
Use age distributions to allocate vehicles to emission standards
pre ECE vehicles up to 1971
ECE & to 1977
ECE to 1980
ECE to 1985
ECE to 1992
Euro to 1996
Euro to 2000
Euro to 2004
Euro to 2010
Use information on sales/new registrations
Watch out for second-hand registrations
Obtain average min and max monthly temperatures for major cities and produce average. Data can be found on websites (e.g as well.
Estimate travelling speeds for urban areas (e.g. 25 km/h), rural areas (e.g. 60 km/h) and highways (e.g. 90 km/h). Estimation needs to be reasonable but not exact.

53. Guide to national road-transport inventory compilation - 3
Estimate mileage shares in the three modes. The sum should make up 100%. Reasonable but not exact estimation is required.
Assume mileage values in the order of
PCs: 11 – 15 Mm/year
LDVs: 15 – 25 Mm/year
HDVs: 50 – 80 Mm/year (national km only!)
Busses: 50 – 70 Mm/year
Mopeds: 2 – 5 Mm/year
Motorycles: 4 – 8 Mm/year
One could adjust mileage per age based on the ‘Fleets’ data
Perform COPERT run
Compare statistical with calculated fuel consumption per year
Total fuel consumption
Fuel consumption per fuel
Adjust mileage to equalize calculated with statistical values

54. Hot Emission Factors of Regulated Pollutants from Conventional PCs – Example Comparison COPERT III and 4 – Euro 2 Diesel NOx

55. Hot Emission Factors of Regulated Pollutants from Conventional PCs – Example Comparison COPERT III and 4 – Euro 3 Gas CO

56. Typical Variability of Measured Data - CO

57. Typical Variability of Measured Data – CO2

58. Performance of Individual Vehicles

59. Importance of Input Variables
Parameter
Importance
Availability of statistics
Notes /Particular Issues
Total number of vehicles per class  
Question is the scooter and mopeds registration availability
Distinction of vehicle to fuel used
Question is the availability of records for vehicles retrofitted for alternative fuel use
Distribution of cars/motorcycles to engine classes  
Not important for conventional pollutants, more important for CO2 emission estimates
Distribution of heavy duty vehicles to weight classes
Vehicle size important both for conventional pollutant and CO2 emissions
Distinction of vehicles to technology level
Imported, second-hand cars and scrappage rates are an issue
Annual mileage driven
Can be estimated from total fuel consumption. The effect of mileage with age requires attention.
Urban driving speed
Affects the emission factors
Rural, highway driving speeds 
Little affect the emission factors, within their expected range of variation
Mileage share in different driving modes
Little affect emissions, within their expected range of variation

60. Exhaust Particulate Matter and Airborne Particle Emission Factors

61. Airborne Particle Information
Total Particle Number (7 nm – 1 μm) (negligible particle number above this range)
Integrated active surface concentration of total particle population (7 nm – 1 μm)
Number of solid particles of three different size ranges (value equivalent to PMP protocol)
7 – 50 nm
50 – 100 nm
10 nm – 1 μm
Distinguished according to:
Vehicle category
Technology
Aftertreatment
Fuel
Sulphur content (for non solid particles)

62. Examples of emission factors of active surface concentration and total particle number (solid and volatile particles)

63. Emission factors for solid particle number in the size ranges 7-50 nm, nm and 100 nm-1 μm (aerodynamic diameter)

64. PM Speciation (OC/EC) Definitions
Elemental Carbon (EC): It appears in PM samples mainly as graphitic particles formed in combustion. It is determined by thermal optical methods where carbon is converted to CO2.
Black Carbon (BC): It corresponds to the light attenuation elements of carbon and it is determined by aethalometers. Black carbon is mainly EC. However, it also includes highly refractory elements of organic carbon (such as OCX2). Also, EC from different sources may exhibit different light absorption efficiencies, hence there is no global equivalence between BC and EC.
Organic Carbon (OC): It is the carbon desorbed when PM is heated at high temperature (i.e °C) in inert atmosphere. Some of the organic species present in PM pyrolyse, instead of desorbing, and this falsely allocates them to EC instead of OC.
Organic Material (OM): It is the total mass of organic material (including the mass of hydrogen) that corresponds to the organic carbon. The organic mass corresponding to the organic carbon depends on the species profile. Usually, an empirical correction of ~1,2-1,4 is applied to OC to derive OM.

65. Emission Factors from tunnel measurements

66. Emission factors from dynamometer measurements (excerpt)

67. Conclusions from dyno studies
In Diesel heavy duty engines, the EC fraction increases and the OC/EC ratio decreases with engine load. At full load over 80% of total PM is EC
In Diesel light duty vehicles, EC is over 80% regardless of operation condition, due to the oxidation catalyst which significantly reduces OC.
In Gasoline light duty vehicles (non GDI), EC is a less than 30% fraction of total PM. The OC/EC ratio exceeds 100% (can reach up to 500% or higher)

68. Values proposed in the software (excerpt)
In cases where advanced aftertreatment is used (such as catalysed DPFs) then the EC and OM does not sum up to 100%. The remaining fraction is assumed to be ash, nitrates, sulphates, water and ammonium, that can be a significant fraction of total PM.

69. Non-Exhaust PM

70. TEi,j = Nj ∙ Mj ∙ (EF)j ∙ fi ∙ S(V)
General Methodology
Sources
Tyre wear
Brake wear
Road surface wear
TEi,j = Nj ∙ Mj ∙ (EF)j ∙ fi ∙ S(V)
TE... Total Emissions [g]
N… Number of vehicles [veh.]
M… Mileage driven by “average” vehicle [km/veh.]
EF… TSP mass emission factor [g/km]
fi… Mass fraction attributed to particle size class i
S(V)… Correction factor for speed V (for road wear S(V)=1)
and indices,
i… TSP, PM10, PM2.5, PM1 and PM0.1 size classes,
j… Vehicle category

71. Example PM10 Non-Exhaust Emission Factors from different sources and comparison with exhaust PM

72. Tyre wear rates

73. Tyre wear vs tyre PM emissions
Not all wear becomes airborne!
Particle size class (i)
Mass fraction (fT,i) of TSP
TSP
1.000
PM10
0.600
PM2.5
0.420
PM1
0.060
PM0.1
0.048

74. Heavy Duty Vehicles

75. Heavy Duty Vehicle Coverage
Average Speed Model – Artemis
Fuel consumption CO HC
NOx PM
Categories
Heavy Goods Vehicles (Copert weight categories)
Buses
Coaches
Effects
Vehicle Load
Road Gradient

76. Heavy Duty Vehicles – Example of Emission Factor Rigid Truck <=7,5t Euro 3
Vehicle Technologies
1980’s
Euro 1 to 5
Taking into account the unexpected behaviour of Euro 2 NOx

77. Heavy Duty Vehicles – Example of effect of vehicle load on emissions Urban bus midi <15t Euro 3

78. Heavy Duty Vehicles – Example of road gradient on emissions Truck-trailer (artic. Truck) 50-60t Euro 2

79. Hybrid Vehicles

80. Hybrid Vehicles – Measurements
Emissions measurements
The measurement protocol included the standard type-approval NEDC test and real world driving cycles (ARTEMIS cycles)
2 repetitions were conducted, during which all legislated gaseous pollutants and fuel consumption were measured
ΔSOC was measured using the vehicle SOC indicator
Fuel consumption and state-of-charge
ΔSOC was again measured using the vehicle SOC indicator
Repetitions of UDC, EUDC, Artemis urban and Artemis road in order to study the effect of ΔSOC and evaluate the measurements

81. Hybrid Vehicles How do measurements compare against conventional PCs

82. Centralised vs National Emission Calculations

83. Background: Data sources and usage
In 2008, EC (DG ENV) collected and produced streamlined road stock and activity data for all EU27 MSs + (CH, HR, NO, TR) to feed COPERT and TREMOVE (FLEETS project)
Base year: 2005
Historic years : Mostly back to 1995 (some countries already starting 1970)
EC (DG ENV) will base transport projections to 2030 on these data
TREMOVE for impact assessments
EC4MACS (GAINS, PRIMES) for integrated assessment

84. Methodology: National submissions
For main pollutants (CO, VOC, NOx, PM): emission data officially submitted to CLRTAP
For CO2: emission data officially submitted to UNFCCC
Data collected for EEA30 countries (except Iceland and Liechtenstein), years 2000 and 2005
Aggregated and sectoral (except CO2) data available for most countries

85. Methodology: Centralised calculations
Transport activity data from the FLEETS database (vehicle stock, mileage, speeds, shares, etc.)
Data obtained from international sources (Eurostat, ACEA, …) and national data (experts, projects)
Data collected for EEA30 countries (except Iceland and Liechtenstein) and for years 2000 and 2005
Calculations performed with COPERT 4 (v6.1) to estimate pollutant and CO2 emissions
Mileage adjusted to match national fuel use statistics (from UNFCCC submissions)
Bias to be introduced if UNFCCC and CLRTAP equivalent fuel consumptions differ

86. Results: Emissions comparison
Preliminary results only shown in this presentation
Total emissions (kt)
Indicators (g/kg fuel)

87. Results: Total emissions (kt)
National data
2000
Centralised
Countries with no data
2005
EU15 CO
14915
14520
DK, GR, LU
9608
9222
DK, LU
NMVOC
2407
2261
1453
1329
NOx
4765
4863
GR, LU
3779
4039 LU
PM2.5
259
222
217
171
CO2
758743
760157
786181
790687
EU27
15387
14898
BG,CZ,DK,GR,HU, LT,LU,MT,PL,RO
11860
11128
DK, LU, MT
2477
2318
BG,CZ,DK,GR,HU, LT,LU,PL,RO
1821
1621
4862
4970
BG,CZ,GR,HU,LT LU,PL,RO
4547
4710
264
226
253
195
BG, GR, LU, RO
836381
836377
CY,LU,MT
886457
885369
CY, LU, MT
EEA30
15925
15631
BG,CZ,DK,GR,HU,LTLU,MT,PL,RO,TR
12243
11535
DK, LU, MT, TR
2548
2418
BG,CZ,DK,GR,HU,LT LU,PL,RO,TR
1868
1674
DK, LU, TR
4961
5127
BG,CZ,GR,HU,LT LU,PL,RO,TR
4625
4815
LU, TR
269
231
257
199
BG,GR,LU,RO,TR
890892
889462
945948
940660

88. Results: CO Indicators
Increasing National CO

89. Results: Classification of CO deviations

90. Results: ΝOx Indicators
Increasing National NOx

91. Results: Classification of NOx deviations

92. Wish List

93. Wish List - 1 User Request Status Ferreiro Antonio (2007)
IPCC Uncertainty Calculations
Project initiated by JRC Ispra
Ricardo de Lauretis (2007)
Mopeds (separation to 4S and 2S)
New emission factors under production
Martin Adams
Correction for CO2 (based on weight classes or more detailed capacity classes)
Project pending
Antonella Bernetii
Include slope correction as a geographical parameter and not a vehicle specific parameter
No progress
Helen Heintalu
Send information on updates / new versions to national experts
Done
Provide export files to communicate to new CollectER and XML formats

94. Wish List - 2 User Request Status Antonella Bernetti
Make possible importing different fuel specifications per year from the Excel spreadsheets
Done
Andrei Pilipchuk
Include the effect of idling (in particular cold idling) on road transport emissions
No progress

95. More Information

96. Leon Ntziachristos (LAT/AUTh)
More Information
Leon Ntziachristos (LAT/AUTh)
Dimitris Gkatzoflias (Emisia)