Transcript Author(s) Name(s)

LABORATORY OF APPLIED THERMODYNAMICS
Leon Ntziachristos
Dimitrios Gkatzoflias
Charis Kouridis
Giorgos Mellios
Savvas Geivanidis
Zissis Samaras
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
COPERT 4
Copenhagen, 2008-06-19
Contents
1.
2.
3.
4.
5.
6.
7.
8.
Background & History
Users and Uses
Methodology and Comparison with the Guidebook
New Elements compared to Spring/Summer 2007
Activity data (results of the Fleets project)
Important, less important data
Exhaust PM and airborne particle emission factors
Non-exhaust PM
LABORATORY OF APPLIED THERMODYNAMICS
Background & History
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
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 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 willing to support its further development
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
History - Early Generations
1988
1989
COPERT85
DGXI
CORINAIR Group
1990
1991
1992
1993
1994
1995
COPERT90
EEA Task Force
CORINAIR Group
1997
COPERTII
EEA
MEET Group
COST319 Report
National
COST319 participants
ForeMove 1.0
DGXI
LAT/EnviCon
1996
ForeMove 2.0
DGXI/Concawe
Auto Oil I
1998
1999
2000
COPERTIII
EEA
MEET
MEET Deliverables
DGVII
MEET Partners
ForeMove Upgr.
ACEA
Auto Oil II
CASPER
DGXI
IFARE/LAT/EnviCon
Legend:
Product/Tool
Funding
Working Group
TRENDS
Eurostat/DGVII
LAT/DTU/INFRAS/Kalivoda
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
History - COPERT 4
 COPERT 4 is the ‘official’ version since Nov. 2006. 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
LABORATORY OF APPLIED THERMODYNAMICS
Uses & Users
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
COPERT Usage
STEERS
TERM
TREMOVE
COPERT
TRENDS
EMEP
Guidebook
National
Inventories
Individual
Use
Auto Oil II
(CONCAWE)
ACEA





Auto - Oil II: Forecast scenarios on behalf of ACEA to estimate emission evolution up to 2015
EMEP/CORINAIR: COPERT methodology is the road transport and off-road machinery emission
chapter in the EMEP/CORINAIR Emission Inventory Guidebook
EEA Activities: National and Central Estimates for Air Emissions from Road Transport
TERM : Transport and Environment Reporting Mechanism (EEA)
TRENDS: Development of a Database system for the Calculation of Indicators of Environmental
Pressure Caused by Transport (DG TrEn study) supported by EEA
Field of applications - National level
Country
EU27
Austria
Model
Contact Person
GLOBEMI
Belgium
COPERT
Bulgaria
Cyprus
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Malta
Netherlands
Poland
Portugal
Romania
Slovakia
Slovenia
Spain
Sweden
UK
Other Countries
Belarus
Bosnia Herzegovina
Croatia
Moldova
Norway
Switzerland
Turkey
Tier 1
COPERT
COPERT
COPERT
COPERT
LIPASTO
COPERT
TREMOD
COPERT
COPERT
COPERT
COPERT
COPERT
COPERT
COPERT
Tier 1
Agg. VERSIT+
COPERT
COPERT
COPERT
COPERT
COPERT
COPERT
EMV
National System
Barbara SCHODL
Laurent BODARWE (Brussels)
Pascal THATE (Wallon)
Ina DE VLIEGER (Flanders)
Tzvetina TZENOVA
Chrysanthos SAVVIDES
Jiri DUFEK
Morten WINTHER
Helen HEINTALU
Kristina SAARINEN
Jean Pierre CHANG
Gunnar GOHLISCH
Dimitrios HADJIDAKIS
Tamas MERETEI
Eimer COTTER
Riccardo DE LAURETIS
Intars CAKAR
Aurelija CICENAITE
Frank THEWES (to be replaced)
Christofer CAMILLERI
Anco HOEN
Janina FUDALA
Pedro TORRES
Vlad Ioan GHIUTA TARALUNGA
Janka SZEMESOVA
Martina LOGAR, Alenka FRITZEL
Antonio FERREIRO
Magnus LINDGREN
Justin GOODWIN
COPERT
COPERT
COPERT
COPERT
COPERT
National System
Tier 1
Hanna MALCHYKHINA
Martin TAIS
Zeljko JURIC, Vjeko BOLANCA
Victor AMBROCI
Alice GAUSTAD
Felix REUTIMANN
Fatma Betül BAYGÜVEN
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 916-926.
Fabio Murena, Giuseppe Favale, Continuous monitoring of carbon monoxide in a deep street canyon, Atmospheric Environment,
Volume 41, Issue 12, April 2007, Pages 2620-2629.
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 1889-1902.
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 6609-6620.
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 6631-6641.
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 334-335, Highway and Urban Pollution,
December 2004, Pages 133-140.
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
1262-1270.
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 5217-5225.
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 149-160.
Field of Applications – Literature 2
Application
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 198-205.
Hao Cai, Shaodong Xie, Estimation of vehicular emission inventories in China from 1980 to 2005, Atmospheric Environment, Volume 41,
December 2007, Pages 8963-8979.
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
537-547.
Seref Soylu, Estimation of Turkish road transport emissions, Energy Policy, Volume 35, Issue 8, Pages 4088-4094.
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 677-691.
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 480-490.
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
5998-6011.
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
5585-5596.
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 715-724.
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 315-322.
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 5377-5383.
C. Mensink, I. De Vlieger, J. Nys, An urban transport emission model for the Antwerp area, Atmospheric Environment, Volume 34, Issue
27, 2000, Pages 4595-4602.
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
LABORATORY OF APPLIED THERMODYNAMICS
The registration is only for people that have actually downloaded
COPERT, not just visiting the site.
The following form needs to be filled by users every time
COPERT 4 is downloaded (example with artificial data is given).
COPERT 4
Statistics
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
User's info:
Name: John Smith
Country: Italy
E-mail: [email protected]
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
Continent Distribution
Distribution of users from Europe
Distribution of users from Africa
Distribution of users from Asia
Distribution of users from America
Monthly Distribution of Downloads
Daily Distribution of Downloads
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
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
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
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
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.)
LABORATORY OF APPLIED THERMODYNAMICS
Methodology and
Comparison to the
Guidebook
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
Pollutants – 1(2)
Pollutants for which a detailed
methodology exists, based on
specific emission factors
Pollutants which are estimated
based on fuel consumption
Group 1
Group 2
Carbon monoxide (CO)
Carbon dioxide (CO2)
Nitrogen oxides (NOx: NO and NO2)
Sulphur dioxide (SO2)
Volatile organic compounds (VOCs)
Lead (Pb)
Methane (CH4)
Cadmium (Cd)
Non-methane VOCs (NMVOCs)
Chromium (Cr)
Nitrous oxide (N2O)
Copper (Cu)
Ammonia (NH3)
Nickel (Ni)
Particulate matter (PM)
Selenium (Se)
PM number and surface area
Zinc (Zn)
Pollutants - 2
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
Group 3
Alkanes (CnH2n+2):
Polycyclic aromatic hydrocarbons
(PAHs) and persistent organic
pollutants (POPs)
Alkenes (CnH2n):
Polychlorinated dibenzo dioxins
(PCDDs) and polychlorinated
dibenzo furans (PCDFs)
Alkynes (CnH2n-2):
Aldehydes (CnH2nO)
Ketones (CnH2nO)
Cycloalkanes (CnH2n)
Aromatic compounds
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
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
 Technology / Emission Standard
 Mean travelling speed [km/h]
 Ambient temperature [Celsius]
 Mean trip distance [km]
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
Parked vehicle
Engine running
Only relevant for
Gasoline!
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
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
Vehicle Categories – Heavy Duty Vehicles
Vehicle Categories – Rigid Trucks (Lorries)
Vehicle Categories – Articulated Vehicles
=
+
Tractor
Semi-Trailer
LABORATORY OF APPLIED THERMODYNAMICS
New Elements
(Compared to Spring/Summer 2007)
COPERT 4 VX.Y
X… Methodology update
Y… Software update
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
COPERT 4 V4.0 – October 2007
 Consistent with the following EMEP/CORINAIR Guidebook chapters:
 B710: Road Transport (Activities 070100 – 070500) Ver. 6.0
 B760: Fuel Evaporation (Activity 070600) 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
COPERT 4 Version 5.0 - December 2007
 Consistent with the following EMEP/CORINAIR Guidebook chapters:
 B710: Road Transport (Activities 070100 – 070500) Ver. 6.0 with
modified N2O emission factors for HDV
 B760: Fuel Evaporation (Activity 070600) Ver 3.0
 B770: Road vehicle tyre and break wear (Activity 070700) 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
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
LABORATORY OF APPLIED THERMODYNAMICS
Activity Data
(Results of the Fleets
project)
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
LABORATORY OF APPLIED THERMODYNAMICS
Important, less important
data
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
Guide to national road-transport inventory compilation - 1
List open to suggestions
1. Obtain fuel consumption from national statistics
2. Estimate effects of tank tourism, black market
3. From 1 and 2 estimate true consumption of road transport
4. Collect data on total fleet in operation per category
 National registers (cars, light trucks, heavy trucks, busses,
motorcycles)
 Police (mopeds)
5. Collect data on vehicle distribution per fuel and sub-category
 National registers
 Data from countries with similar structure (data from the Fleets
project)
Guide to national road-transport inventory compilation - 2
6. Use age distributions to allocate vehicles to emission standards
•
•
•
•
•
•
•
•
•
pre ECE vehicles
ECE 15 00 & 01
ECE 15 02
ECE 15 03
ECE 15 04
Euro 1
Euro 2
Euro 3
Euro 4
up to 1971
1972 to 1977
1978 to 1980
1981 to 1985
1985 to 1992
1992 to 1996
1996 to 2000
2000 to 2004
2005 to 2010
 Use information on sales/new registrations
 Watch out for second-hand registrations
7. Obtain average min and max monthly temperatures for major cities and
produce average. Data can be found on websites (e.g
www.weatherbase.com) as well.
8. 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.
Guide to national road-transport inventory compilation - 3
9. Estimate mileage shares in the three modes. The sum should make up
100%. Reasonable but not exact estimation is required.
10. 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
11. Perform COPERT run
12. Compare statistical with calculated fuel consumption per year
 Total fuel consumption
 Fuel consumption per fuel
13. Adjust mileage to equalize calculated with statistical values
Hot Emission Factors of Regulated Pollutants from Conventional PCs
– Example Comparison COPERT III and 4 – Euro 2 Diesel NOx
Diesel, Euro II, NOx
2
1.8
75
Artemis, All capacities
COPERT, All capacities
1.6
Artemis, All capacities
[g/km]
1.4
25
1.2
139
70
1
38
94
60
0.8
53
36
70
0.6
67
68
35
3
0.4
0.2
0
0
15
30
45
60
75
90
Average Speed [km/h]
105
120
135
Hot Emission Factors of Regulated Pollutants from Conventional
PCs – Example Comparison COPERT III and 4 – Euro 3 Gas CO
Petrol, Euro III, CO
7
31
Artemis, All capacities
COPERT, <1.4 l
COPERT, 1.4-2.0 l
6
COPERT, >2.0 l
Artemis, All capacities
[g/km]
5
4
3
136
87
2
88
84
104
1
206
97
142
162
132
45
90
75
60
Average Speed [km/h]
136
79
0
0
15
30
105
120
135
Typical Variability of Measured Data - CO
Typical Variability of Measured Data – CO2
Performance of Individual Vehicles
1.2
1
HC [g/km]
0.8
0.6
0.4
0.2
0
0
20
40
60
80
100
120
average speed [km/h]
Iveco 35/10
Mercedes-Benz 208D
VW LT 35
VW T4 Diesel
Iveco 35-10 Turbo Daily
VW LT 35 2
Mercedes-Benz 210D
Ford Transit 120 2.5 TD
140
Importance of Input Variables
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

Rural, highway driving speeds

Mileage share in different driving
modes




Parameter
Affects the emission factors
Little affect the emission factors, within their
expected range of variation
Little affect emissions, within their expected
range of variation
LABORATORY OF APPLIED THERMODYNAMICS
Exhaust Particulate Matter and
Airborne Particle Emission
Factors
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
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)
Examples of emission factors of active surface concentration and
total particle number (solid and volatile particles)
Total particle population
2
Active surface area [m /km]
Total particle number [#/km] ×10
-14
Category
Fuel specs (EN590)
Urban
Road
Motorway
Urban
Road
Motorway
PC diesel Euro-1
2000-2009
20.97
19.13
29.36
4.0
3.0
3.2
2005-2009
16.82
17.05
27.77
PC diesel Euro-2
4.3
2.1
2000
2005-2009
15.31
13.43
36.19
7.1
18.51
2.8
PC diesel Euro-3
1.6
2000
2005-2009
2.0
1.7
39.31
0.012
0.013
12.3
0.22
PC diesel Euro-3 DPF
0.09
1.8
1.7
13.4
0.00067
2000
4.03
44.62
PC petrol Euro-1
later than 2000
0.68
0.43
0.50
0.088
0.073
0.18
PC petrol Euro-3
later than 2000
0.024
0.033
0.074
0.007
0.053
0.056
PC petrol Euro-3 DISI
later than 2000
2.04
1.77
2.48
0.15
0.11
0.90
Emission factors for solid particle number in the size ranges 7-50 nm,
50-100 nm and 100 nm-1 μm (aerodynamic diameter)
Solid particle population
[#/km] ×10
-13
Number of solid particles <50 nm
Number of solid particles 50-100 nm
Number of solid particles 100-1000 nm
Category
Urban
Road
Motorway
Urban
Road
Motorway
Urban
Road
Motorway
PC diesel Euro-1
8.5
8.6
7.2
9.3
7.8
7.3
5.4
3.8
4.0
PC diesel Euro-2
7.6
7.6
6.1
8.8
7.7
7.2
5.1
3.6
4.0
PC diesel Euro-3
7.9
7.1
5.8
8.7
6.8
6.9
4.5
3.2
3.5
PC diesel Euro-3 DPF
0.0055
0.0040
0.023
0.0023
0.0016
0.0094
0.0016
0.0012
0.0028
PC petrol Euro-1
0.32
0.24
0.086
0.14
0.10
0.034
0.052
0.037
0.012
PC petrol Euro-3
0.0096
0.011
0.0055
0.0044
0.0054
0.0028
0.0026
0.0034
0.0051
PC petrol Euro-3 DISI
0.81
0.61
0.28
0.65
0.36
0.19
0.41
0.21
0.15
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. 600-900°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.
Results from tunnel measurements
Study
Geller et al. (2006)
Grieshop et al. (2006)
Gillies et al.(2001)
Allen et al. (2002)
Laschober et al. (2004)
Tunnel
Temperature (oC)
Condition
DHDV
Fraction (%)
OC/EC PM10
EC/PM10
3,2-4,9%
0,25-0,54%
34-60%
170-490%
60-81%
32-55%
OC/EC PM2.5
EC/PM2.5
Caldecott, CA
Caldecott, CA
23
23
4,2% upgrade
4,2% upgrade
Squirell Hill, PA
9
High Speed
6
58%
70%
Squirell Hill, PA
9
Low Speed
3,4
82%
39%
Squirell Hill, PA
9
High Truck Share
14,5
75%
35%
29%
132%
60%
182%
52%
37%
57%
23%
Squirell Hill, PA
Sepulveda, Los Angeles
Caldecott, CA
Caldecott, CA
26
19-28
17
17
Low Speed
Kaisermühlen, Austria
14-30
Flat
4,2% upgrade
4,2% upgrade
3,4
1,7-4,3%
6-7,3%
0,24%
81%
52%
86%
45%
57%
58%
~12%
66%
39%
Emission Factors from tunnel measurements
Study
Vehicle Class
EC
OC
PM2.5
Grieshop et al. (2006)
LDV
HDV
26,6+/- 29,8
439+/- 109
31,2+/-32,4
269+/- 118
LDV
15+/-71
HDV
LDV
788+/-332
29,4+/-4,3
HDV
709+/-76
LDV
HDV
35+/-3
1300+/-300
LDV
1,6+/-0,21
8,53+/-0,47
HDV
122,7+/5,7
383,5+/-10,7
Allen et al. (2002)
Geller et al. (2006)
Kirchstetter et al. (1999)
Weingartner et al. (1997)
Units /Notes
OC/EC (%)
EC/PM2.5
30,6+/-43,8
1060+/-160
117%
61%
87%
41%
39+/-22
73+/-51
260%
21%
495+/- 105
1285+/-237
67,1+/-11,2
63%
61%
44%
mgC/ kg fuel
1015+/-127
53+/-8
500+/-40
70%
110+/-10
2500+/-200
151%
38%
mgC/ km (LDV
contain 5% diesel)
32%
52%
19%
32%
Emission factors from dynamometer measurements (excerpt)
Study
Vouitsis et al. (2007)
Vehicle/Engine
Euro 4 Diesel LDV
Euro 4+DPF LDV
Euro 3 Diesel LDV
Geller et al. (2006)
Euro 2 Gasoline LDV
Euro 3 DPF LDV
Kweon et al. (2002)
Research Single Cylinder
Engine, 350 ppm S
Operating Condition
OC/EC PM2.5
EC/PM2.5
NEDC
37%
79%
Urban
88%
53%
Rural
136%
22%
42%
43%
Rural
Rural
48%
24%
53%
38%
Rural
90 km/h
43%
81%
83%
50%
Rural
Rural
Road
90 km/h
196%
99%
10%
6%
243%
300%
18%
30%
Road
90 km/h
1200 rpm, 25%
583%
449%
300%
10%
7%
1200 rpm, 50%
1200 rpm, 75%
1200 rpm, 100%
1800 rpm, 50%
43%
6%
2%
124%
24%
70%
85%
95%
42%
82%
3%
95%
66%
36%
60%
74%
Motorway
Average Driving
1800 rpm, 75%
1800 rpm, 100%
ESC
ETC
75%
45%
20%
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)
Values proposed in the software (excerpt)
Category
Technology
No aftertreatment, carburettor
Carburettor, no aftertreatment or
oxidation catalyst
Carburettor, no aftertreatment or
oxidation catalyst
Carburettor or SPI (few models)
Gasoline PC
Carburettor or SPI and TWC
and LDT
MPI + closed loop TWC
MPI + closed loop TWC
MPI + closed loop TWC +twin
lambda
MPI + closed loop TWC +twin
lambda
No aftertreatment, Low Pressure
Injection
High-Pressure Injection (HPI)
Diesel PC and HPI +Ox Cat
LDT
HPI +OxCat+EGR
HPI+multi OxCat+EGR
HPI +OxCat+DPF
HPI+Oxcat+CDPF
EC/PM2.5
(%)
2
OM/EC
(%)
4900
Uncertainty
Range (%)
50
ECE 15 00/01
5
1900
50
ECE 15 02/03
5
1900
50
ECE 15 04
Open Loop
Euro 1
Euro 2
20
30
25
25
400
233
250
250
50
30
30
30
Euro 3
15
300
30
Euro 4
15
300
30
Conventional
55
70
10
Euro 1
Euro 2
Euro 3
Euro 4
Euro 3, Euro 4, Euro 5
Euro 3, Euro 4, Euro 5
70
80
85
87
10
20
40
23
15
13
500
200
10
10
5
5
50
50
Euro Standard
PRE-ECE
20
80
50
Conventional
No aftertreatment, IDI
 In cases where
advanced aftertreatment
is used (such
as
catalysed
DPFs)
20
40
65
No aftertreatment, DI, Line Pump Euro I
then the EC and
OM does not sum up to 100%. The
remaining
fraction is
20
40
Euro II
DI, Line Pump
aftertreatment,
No ash,
assumed
to be
nitrates,
sulphates,
water and65 ammonium,
that can
Diesel HDV
Imptoved design, high pressure
be a significant
fraction of total PM.
20
30
70
Euro III
injection
EGR+OxCat or SCR
ECR+OxCat or (mainly) SCR
SCR+CRT+Oxcat
Euro IV
Euro IV
Euro VI
75
75
15
25
25
300
20
20
30
LABORATORY OF APPLIED THERMODYNAMICS
Non-Exhaust PM
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
General Methodology
 Sources
 Tyre wear
 Brake wear
 Road surface wear
TEi,j = Nj ∙ Mj ∙ (EF)j ∙ fi ∙ S(V)
TE...
N…
M…
EF…
fi…
S(V)…
Total Emissions [g]
Number of vehicles [veh.]
Mileage driven by “average” vehicle [km/veh.]
TSP mass emission factor [g/km]
Mass fraction attributed to particle size class i
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
Example PM10 Non-Exhaust Emission Factors from different
sources and comparison with exhaust PM
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
Wish List - 1
User
Request
Ferreiro Antonio
IPCC Uncertainty Calculations
Ricardo de Lauretis
Mopeds
Martin Adams
Correction for CO2 (based on weight classes or more detailed capacity
classes)
Antonella Bernetii
Include slope correction as a geographical parameter and not a
vehicle specific parameter
Helen Heintalu
Send information on updates / new versions to national experts
Martin Adams
Provide export files to communicate to new CollectER and XML
formats
Wish List - 2
User
Request
Antonella Bernetti
Make possible importing different fuel specifications per year from the
Excel spreadsheets
Andrei Pilipchuk
Include the effect of idling (in particular cold idling) on road transport
emissions
LABORATORY OF APPLIED THERMODYNAMICS
N2O/NH3 Emission Factors
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
LAT Database on N2O/NH3
 Database with 3500 measurements from 40 literature sources (mainly US
input)
 Data organised according to:
 Mileage (vehicle/aftertreatment)
• Emission factor as a function of mileage
 Aftertreatment temperature (driving profile)
• Cold urban, hot urban, rural, highway
 Vehicle category
• PCs, LDVs, no info on HDVs & PTWs
 Vehicle technology
• Pre Euro, Euro 1 to Euro 4
 Fuel
• Gasoline, Diesel, CNG, LPG, Methanol Blends
 Fuel sulphur content
N2O/NH3
Example of N2O
PCs - EURO 2 - 90<=S<=150
Emission Factors
Επίπεδο εκπομπής
[mg/km]
40
UC
UH
RUR
HIGH
30
20
10
0
0
Επίπεδο εκπομπής
[mg/km]
100
40000
80000
120000
Διανυθείσα απόσταση [km]
160000
PCs - URBAN COLD - EURO 1
80
S<30
90<=S<=150
S>=350
60
40
20
0
0
40000
80000
120000
Διανυθείσα απόσταση [km]
160000
N2O/NH3
140
Example of NH3
Emission Factors
LDVs - EURO 3-4 - S=30
Επίπεδο εκπομπής [mg/km]
120
URBAN COLD
URBAN HOT
RURAL
HIGHWAY
100
80
60
40
20
0
0
120000
80000
40000
Διανυθείσα απόσταση [km]
160000
LABORATORY OF APPLIED THERMODYNAMICS
Emission Degradation
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
New Emission
degradation
correction
factor
parameters for
EURO 1 & EURO
2
New Emission degradation correction factor parameters for EURO 3
& EURO 4
Emission degradation correction factor as a function
of speed
LABORATORY OF APPLIED THERMODYNAMICS
Heavy Duty Vehicle
Methodology
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
 Average Speed Model – Artemis
 Fuel consumption
 CO
 HC
Heavy
 NOx Duty
Vehicle
Coverage
PM
 Categories
 Heavy Goods Vehicles
(Copert weight categories)
 Buses
 Coaches
 Effects
 Vehicle Load
Heavy Duty Vehicles
–
Example
Vehicle Technologies
of Emission Factor
 1980’s –
Rigid
Truck
Euro 3
 Euro
1 to<=7,5t
5
 Taking into account the unexcected behaviour
of Euro 2 NOx
–
Example of effect of vehicle load on emissions
–
Urban bus
midi <15t
Euro 3
–
Example of road gradient on emissions
–
Truck-trailer
artic. truck 50-60t
Euro 2
 The influence of fuel quality
 The influence of engine deterioration with time
 Heavy
The effect
of maintenance
Duty
 The
effect of particle traps (diesel particulate filters – DPFs)
Vehicles
 Alternative
– engine concepts
 Compressed natural gas (CNG)
Remaining
 Issues
Bio-diesel
 CO Euro 4 and 5 lower than COPERT
 HC Euro 4 and 5 lower than COPERT
 Heavy
NOx EuroDuty
2-5 higher than COPERT
Vehicles
 PM
generally similar with small differences
–
Comparison
with Copert 3
LABORATORY OF APPLIED THERMODYNAMICS
Cold Start
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
Cold Start Approach in Artemis
EE p,V , T ,    20,20 ( p)  f  p,V , T  h( p,  (d , p,V , T ))  g ( p, t )
Level 1: Excess Emission
per Start – Vehicle Level

EE:
Excess emission of pollutant p for a trip (g/veh.)

V:
Mean speed during the cold period (km/h)

T:
Ambient temperature (°C)

t=
Parking time (h)

d:
Actual travelled distance (km)

ω20,20: Reference excess emission (20 °C & 20 km/h) for a trip
distance longer or equal to the cold distance

dc:
Cold distance (km)

δ:
Dimensionless distance = d/dc(p,V,T)

f:
ω correction for speed V and the temperature T

h:
Fraction of cold overemission over distance δ

g:
Percentage of reference excess emission for parking time
less than 12 h
Cold Start Approach in Artemis
Level 2: Extension of Level 1 into fleet level


i
Ec ( p)=
Ec = traffic excess emissions corresponding to a traffic tfi,h (g/time unit)





t = parking time (h)
 p .p
 
ph
 under
 
i, j
m, j . ph , n
cm(s,
vi)
=
%
of
mileage
recorded
cold
start
or
intermediate
temperature
conditions
for
season
tf i ,h .
.
. f p, V j , T .h p,  .g  p, t n   s

6
and speed

ptf
.d m
h vehicle
vii ,of
type
in 
j
m


 


i = vehicle type
s = season (winter, summer, middle, year)
vi = traffic overall average speed for the vehicle type i (km/h)
h = hour (1 to 24, day)
tfi,h = traffic flow for the studied vehicle type i and the hour h(km.veh)
ph = relative cold start number for the hour h (average=1)
ptfi,h = relative traffic for the studied vehicle type i and the hour h (average=1)
j = speed class with a cold engine
m = trip length class
n = class of stops (0 -1, 1 - 2, ... , >12h)
pi,j = % of the distance travelled at speed j with a cold engine, for the average speed considered, and for
the studied vehicle type i (%)
pm,j = % of the distance started with a cold engine and distance dm, for speed Vj with a cold engine
ph,n= % of the distance travelled after a stop with a duration of tn, for hour h
dm = average distance of the trips under cold start conditions of class m (km)
Vj = average speed with a cold engine corresponding to class j (km/h)
T = ambient temperature (°C)






wi(p) = reference excess emission for the vehicle type i (g)
f(p,Vj,T) = plane function of the speed Vj and the temperature T, for the pollutant p
h(p,d) = (1-ea(p,T).d)/ (1-ea(p,T))
d = dimensionless distance = dm/dc(p,Vj,T)
dc(p,Vj,T) = cold distance for the pollutant p (km)
g(p,tn) = % of excess emission at 12h of parking as a function of the parking time tn for the pollutant p


 cms, vi 
 i ( p).

100

h














10


Cold Start Approach in Artemis
Level 3: Level 2 with assumptions/estimations for most parameters
Excess Emission [g/km]=f(pollutant, vehicle technology/category, season, ambient temperature,
mean speed, [hour of day])
Notes:
 Emissions in g/km difficult to perceive for a cold-start model
 Are directly multiplied with total mileage
 No differentiation for few starts/long trips
 No effect of different trip distributions (model assumes default ones)
 Model based on default parking-time profiles. This may be different for different
applications/countries
 Additional work will be required to transform this model into Copert approach.
LABORATORY OF APPLIED THERMODYNAMICS
Evaporation Losses
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
Hot Emission Factors of Regulated Pollutants from Conventional
PCs – Summary of Comparison COPERT and ARTEMIS
 Diesel Vehicles
 CO Euro 2 and 3 lower than COPERT
 HC Euro 3 lower than COPERT
 NOx similar results
 PM Euro 2 and 3 lower than COPERT
 Fuel Consumption higher than COPERT ay high engine capacities
 Gasoline Vehicles
 CO lower than COPERT at low speeds ranges
 HC similar results
 NOx Euro 3 and Euro 4 lower than COPERT at high speed ranges
 Fuel Consumption similar results
LABORATORY OF APPLIED THERMODYNAMICS
Hybrid Vehicles
ARISTOTLE UNIVERSITY THESSALONIKI
SCHOOL OF ENGINEERING
DEPT. OF MECHANICAL ENGINEERING
Hybrid Vehicles
–
Measurements 1/2
 The measurements were conducted on the LAT chassis dynamometer
between 26-31/05/2005
 Scope of the measurements was to obtain experience on hybrid
technology and to study the vehicle performance in “real world” driving
conditions
 We followed the specifications of the relevant European Directives
 Specific setup and conditioning guidelines given to us by Toyota Belgium
on the Prius II vehicle tested
Hybrid Vehicles
–
Measurements 2/2
 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
Hybrid Vehicles
–
How do measurements compare against
conventional PCs
[email protected] Leon
Ntziachristos +30 2310
996031
[email protected] Dimitris
Gkatzoflias +30 2310 996051