This document describes a methodology for calculating emissions from public transport in Greece using a bottom-up approach. The methodology involves determining activity data like passenger-kilometers from transportation operators, filling data gaps, selecting appropriate emission factors, and calculating emissions. The results show small differences between the bottom-up inventory developed and top-down statistics, but larger differences in calculated emissions, highlighting the need for country-specific emission factors. Next steps involve using the baseline inventory and collecting additional data through a new web platform to assess emission reductions over time.

1. Co-modal emission calculation and
inventory methodology
G-E. Kastori1, G. Papadimitriou1, P. Katsis1, C. Kouridis1 and G.K.D. Saharidis2
1 EMISIA SA, Thessaloniki
2 University of Thessaly

2. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Outline
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Introduction
Methodology
Results and Conclusions
Next Steps

3. INTRODUCTION
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4. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Introduction
Context: An emission inventory is a first step towards accounting
and monitoring emissions.
Objective: A bottom-up methodology for calculating emissions from
the public transport in Greece, resulting in a baseline scenario for
future emission inventories.
Result: An emission inventory, derived from detailed actual activity
data, which also combines co-modality (buses and railways).
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5. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
General procedure for emission inventories
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Step 1: Determination of the activity data needed for each emission
source
Step 2: Data collection
Step 3: Data processing
Quality Assurance and Quality Control (QA/QC) checking
Gap-filling
Step 4: Selection of the appropriate emission factors for each source,
based on the available activity data
Step 5: Calculation of emissions for each pollutant

6. METHODOLOGY
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Methodology step 1
Step 1: Determine the needed activity data
Passenger-kilometers
• Number of tickets for a specific time period for each route
• Distance in kilometers for each route
• Number of itineraries for each route
• 𝑝𝑘𝑚 = 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑖𝑐𝑘𝑒𝑡𝑠 ∗ 𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑜𝑓 𝑒𝑎𝑐ℎ 𝑟𝑜𝑢𝑡𝑒
Vehicle-kilometers
• 𝑣𝑘𝑚 =
𝑝𝑘𝑚
𝑜𝑐𝑐𝑢𝑝𝑎𝑛𝑐𝑦 𝑟𝑎𝑡𝑖𝑜 ∗𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑠𝑒𝑎𝑡𝑠
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8. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Methodology step 2
Step 2: Collect the corresponding activity data from the 16 cities of
Greece (connected with the railway network and with a population
greater than 50.000 citizens), using various methods
e-mail
Phone
Official letters
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City
Athens Lamia
Thessaloniki Larissa
Alexandroupolis Patras
Chalkida Serres
Florina Thiva
Ioannina Trikala
Katerini Volos
Komotini Xanthi

9. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Methodology step 2 cont’d
Replies received from urban buses and coaches (16 cities)
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31%
69%
Urban Buses
Yes
No
19%
81%
Coaches
Yes
No
Additional transport operators (in other cities) were contacted data from
7 additional transport operators were received.
TRAINOSE, the only railway operator in Greece, replied to the request

10. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Methodology step 3
Step 3: Perform the QA/QC analysis
Not all transport operators (urban buses and coaches) were able to provide the
requested information
Gap-filling procedure (for urban buses and coaches) was performed
1. Lack of distance? calculated using GYM platform
2. Lack of number of itineraries? retrieved from official web sites of transport operators
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Gap-filling Methodology
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In order to fill in the missing information for the 16 cities, a novel gap-
filling methodology was developed.
For each city, for which data were received:
𝑝𝑘𝑚
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛
𝑖𝑛𝑑𝑖𝑐𝑎𝑡𝑜𝑟
From official databases (2011 Population-
Housing Census, conducted by the Hellenic
Statistical Authority

12. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Gap-filling Methodology cont’d
If no updated data were received for a city, one of the following
options was used:
1st Option:
• Similar characteristics were identified between the cities; the pkm were calculated based on the
population of the city and the indicator of a city (which was selected as a similar city).
• Similar characteristics are demographic data (area, population)
2nd Option:
• If a similar city cannot be found, a weighted average was calculated from all the cities, for which data
exist
• The calculated weighted average was used, along with the population of each city, in order to
calculate the missing pkm
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Gap-filling – Example
Received data for urban buses in Ioannina:
Number of tickets and distance (in km) per route calculated pkm=16 050 700
Demographic data for Ioannina:
Area = 403 km2
Population = 112 486 calculated Indicator = pkm/population = 143
No data were received for Chalkida
Demographic data for Chalkida:
Area = 412 km2
Population = 102 223 Chalkida is characterized similar to Ioannina, thus
the calculated pkm = indicator (for Ioannina)*population = 7 630 146
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Methodology step 4
Step 4: Select the appropriate Emission Factors (EF)
More detailed emission factors were developed within Life-GYM project based on
various characteristics (i.e. country, speed, vehicle type)
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Railways
•Fleet characteristics (i.e. fuel type,
fuel consumption)
•Country submissions on the
production of public electricity
•Speed class
Country
and fleet
based EF
Buses
•Fleet characteristics (i.e. fuel
type, fuel consumption)
•Vehicle classification
•Speed class
Country
and fleet
based EF

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Methodology step 5
Step 5: Calculate the CO2 emissions for each transport mode
𝐶𝑂2 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 = 𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝐷𝑎𝑡𝑎 ∗ 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟
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Calculated vkm for each
transport mode
Country and fleet based EF
for each transport mode

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Calculation of the Emission Inventory
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Pkm Buses
Pkm Coaches
Data for the trimester (June-
August 2016)
X 4
Emission
Inventory for
2016
The emission inventory will be compared with a top-down methodology
Pkm Trains

17. RESULTS & CONCLUSIONS
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Results
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Transport Operator
Developed Inventory
(pkm)
EC Statistical
Pocketbook (pkm) Difference (%)
Urban Buses and Coaches 8,575 8,705 1%
Railways 1,087 1,100 1%
Transport Operator
Developed Inventory -
CO2 emissions (Mt) CO2 emissions (Mt) Difference (%)
Urban Buses and Coaches 0.3 1.52 406%
Railways 0.06 0.05 17%
Country-
based EF
Generic
EF

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Conclusions
Small differences between top-down and bottom-up
methodologies concerning the calculated pkm
Differences in calculated emissions need of
country and fleet specific emission factors!
The lack of activity data can be compensated with a
solid gap-filling methodology
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20. NEXT STEPS
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21. 5th International Conference on Energy, Sustainability and Climate Change, Mykonos, June 4-6, 2018
Next steps
The derived emission inventory will serve as a baseline scenario
for future emission calculations
Within Life-GYM project, data from transport operators will be
collected after the introduction of a web-platform aiming to
encourage the use of public transport
Emission inventories will be calculated based on the developed
methodology
The effect of the web-platform to the reduction of CO2 emissions
will be assessed
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Thank you for your attention!
Any questions?
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