1. business and industrial
2. energy
3. renewable energy

2nd Capacity Building Workshop – 21/3/2014, Zagreb, Croatia
Developing low C policies:
a step-by-step manual and illustrative
modeling examples
Elena Georgopoulou
Sebastian Mirasgedis
Yannis Sarafidis
NATIONAL
OBSERVATORY OF
ATHENS
Structure of presentation
Part A. Structure and content of the Step-by-step
Manual for developing low C policies
Part B. Focus on the estimation of the technical and
economic potential of PaMs (modeling)
Part A. Structure and content of the Step-by-step
Manual for developing low C policies
Aim of the Manual
The Manual aims to assist SEE
countries (but also other countries) in
the process of joining the EU to
develop, implement and monitor low
C policies and measures
 Guide describing the basic steps to follow
 Takes into account real problems and
barriers faced
 Concise and readable (does not enter into
too much technical detail on each topic/
sub-topic, but provides examples and
references for further reading)
Structure of the Manual
 Chapter 1: Introduction
 Chapter 2: Analyzing the broader scene regarding climate
change mitigation
 Chapter 3: Background analysis – Examining past trends and
current situation of GHG emissions
 Chapter 4: Assessing the potential and impacts of low carbon
measures
 Chapter 5: Developing projections of GHG emissions
 Chapter 6: Selecting low carbon targets and appropriate
measures and policies
 Chapter 7: Implementation and monitoring of policies and
measures
Chapter 2: Analyzing the broader scene on CC mitigation
Basic categories of commitments:
(a) Commitments deriving from international agreements (UNFCCC,
Kyoto Protocol, others)
EU enlargement
(b) Commitments deriving from EU legal acts (e.g. the ’20-20-20
Climate and Energy Package’, which has transformed EU
pledges for the 2013-2020 period of the Kyoto Protocol into a
legally binding target)
EC proposal (Jan 2014) ‘A policy framework for climate and energy
from 2020 to 2030’: 40% reduction of GHG emissions in 2030 relative
to 1990 (ETS: -43% and non-ETS: -30% compared to 2005, RES:
≥27%, EE: +nq)
Chapter 2: Analyzing the broader scene on climate change
EU legal acts on:
 GHG monitoring and reporting
 Emissions Trading Scheme (EUETS)
 Carbon Capture and Storage
 Transport and Fuels
 Renewable Energies
 Energy Efficiency (incl. CHP)
→ Challenging and demanding set
of commitments, both for now as
well as for the mid-term future
Chapter 3: Examining past trends and current situation of
GHG emissions
On the basis of IPCC Guidelines, UNFCCC and EU decisions
 Basic principles in developing GHG emissions inventories
 Greenhouse gases and Sources / Sinks of GHG emissions / removals to be
considered
 Overview of changes / additions introduced by 2006 IPCC Guidelines
 GHG emissions / removals estimation methods
 How to select appropriate estimation methods
 Dealing with data sources and data availability
 Calculation tools
o The IPCC inventory software application
 Updating estimations and maintaining consistency (Recalculations)
 Reporting templates and indicators to be estimated under EU legal acts
With a view to establish a National Inventory System which
will be operational when joining the EU
Chapter 4: Assessing the potential and impacts of low
carbon measures (I)
Measures vs. Policies:
 Measures are technologies, processes, and practices that reduce GHG
emissions below anticipated future levels.
 The development of a wind farm, the installation of double glazed windows
in a building, etc.
 Policies are taken and/or mandated by a government - often in
conjunction with business and industry within its own country, or with
other countries - or local authorities to accelerate mitigation measures.
 The implementation of feed-in tariffs for enhancing the penetration of RES,
the implementation of building thermal regulation, etc.
Chapter 4: Assessing the potential and impacts of low
carbon measures (II)
 A review of the most important mitigation technologies per sector
 Basic characteristics for selecting mitigation measures:
 CC mitigation effectiveness (potential for reducing GHG emissions)
 Cost-effectiveness (economic performance)
 Implications on the society, the economy and the environment (cobenefits and co-risks)
 Other issues related to the ease of application, social acceptance, etc.
Chapter 5: Developing projections of GHG emissions
 Aim:
 To analyze future evolution of GHG emissions at national / sectoral level
through scenarios
 Scope:
 To estimate the combined effects of mitigation measures
 To evaluate the effectiveness of various policies aiming at promoting
specific GHG mitigation technologies
 To estimate the total and marginal costs on the economy associated with
mitigation actions
 To investigate the role of carbon markets or the opportunities to mobilize
market forces in order to implement low cost mitigation actions
Chapter 5: Developing projections of GHG emissions
Scenarios to be considered:
 ‘With Measures’, ‘With Additional Measures’, ‘Without Measures’
 Other scenarios (Frozen technology, High / Low economic growth, High / Low
energy prices, etc.)
Chapter 5: Developing projections of GHG emissions (III)
Methodologies / tools – Energy sector
 What policy questions are
answered by each modeling
approach.
 Short presentation of the
most popular models used
for energy analysis and GHG
emissions projections
(MARKAL, MARKAL-MACRO,
EFOM, WASP,
ENPEP/BALANCE, LEAP,
NEMS, PRIMES, GACMO,
STAIR)
(source: Duerinck et al. 2008)
Chapter 6: Selecting low carbon targets and appropriate
measures and policies (I)
Rationale in setting low C targets:
•
Approach 1: Improving to some extent the present situation
•
Approach 2: Fulfillment of legal commitments
•
Approach 3: Moving fast towards a low carbon economy
Chapter 6: Selecting low carbon targets and appropriate
measures and policies
Step 1: Examine the marginal cost curve when only private costs and benefits are included in the economic analysis
Step 1.1:
Identify measures having a negative unit cost (i.e. net benefit) 
‘win-win’ measures

Win-win under all circumstances (‘Solid’ win-win measures)

Win-win under a high interest rate regardless of the rest remaining
conditions (‘Solid private’ win-win measures)

Rest measures (‘Uncertain’ win-win measures)
Step 1.2:
Explore measures having a positive unit cost

Becoming win-win under favorable conditions and a high interest rate
(‘Promising private measures’)

Presenting a net private cost regardless of the interest rate and
conditions faced (‘Low priority measures’)

In between these 2 groups (‘Medium priority measures’)
Step 2: Examine the performance of potential GHG emission reduction measures by considering also external costs and benefits
Chapter 6: Selecting low carbon targets and appropriate
measures and policies
Formulating an Action Plan for achieving a target:
 Selected target and set of measures and policies
 Detailed time schedule for the implementation of selected
measures
 Definition of the coordinator and the stakeholders to be
involved in the implementation of each measure
 List of preparatory actions per measure
 Milestones per measure
 Indicators of progress per measure
 Methodology for calculating GHG emissions reductions achieved
per measure during its implementation
Public consultation – Communication with stakeholders
Adoption process
Chapter 7: Implementation and monitoring of policies and
measures
Evaluating progress and results achieved so far:

Timeframe for the evaluation

Data collection sources and process (indices)

Methodological tools to be used for the evaluation
 Indicators reflecting the progress (expressed in physical terms) in
implementing the selected low carbon measures (progress indicators)
 Indicators showing the GHG emissions reduction achieved through the
implementation of selected low carbon measures (result indicators)
Chapter 7: Implementation and monitoring of policies and
measures
Reviewing and updating the mix of low carbon measures and
related policies / How?
•
The level of the target set for a specific measure was too
ambitious/ too low compared to the dynamics of the market 
modify target
•
The mix of policies for a specific measure failed to support the
implementation of the measure to the extent foreseen  modify
mix of policies
•
New potential low carbon measures/ technologies have emerged
 repeat measures’ evaluation and selection of support policies
 Update Action Plan and Monitoring Plan
Part B. Focus on the estimation of the technical
and economic potential of PaMs
(modeling)
Part B1. Buildings (FYROM, Montenegro)
Part B2. Transport (Croatia, Albania)
Part B3. Wastes (Serbia)
Part B1. Buildings (FYROM, Montenegro)
Bottom-up Energy Model for the Buildings’ Sector
 Energy consumption is analyzed and broken down to specific activities
(uses), technologies and energy sources related to GHG emissions
 Year 2010 is selected as the base year of the analysis
 Assumptions made are also extrapolated back to the year 2006
 Model results are compared to Official Energy Balances both for 2006
and 2010 (assumptions are modified in order to achieve convergence)
 Projections of future energy demand and consumption (Reference
Scenario)
 Model consists of two modules:
 Residential Sector Module
 Tertiary Sector Module
Structure of the Bottom-up Energy Model for Buildings
 Building types based on:
 Construction Period
 Building type for Residential Sector (detached houses, high-rise buildings with
multiple apartments, seasonal use)
 Use for Tertiary sector (e.g. Schools/Educational buildings, Hospitals, Hotels
etc.)
(6-7 types for residential, 6-15 types for tertiary)
 Energy consumption of each category is simulated with 6 end-uses:
 Space heating (further categorized in central and individual heating systems in
residential sector)
 Hot water
 Space cooling
 Cooking
 Lighting
 Electrical Appliances (5 types)
 Energy demand for each end-use is calculated:
 by applying methodologies which use typical meteorological data
 on the basis of existing information and data from international sectoral studies
Building Categories in FYROM
 Existing building stock in the FYROM regarding to the period of
construction is divided into three categories :
 until 1980 (buildings with lot of reinforced concrete elements, without thermal
insulation) and
 since 1980 (when first standards of thermal insulation was appeared)
 Buildings built according to the European standards on Energy Performance of
Buildings Directive
 Regarding the type of the residential buildings two main categories are
defined:
 low buildings with 1 or 2 floors (detached and semi-detached houses) and
 high residential buildings (with multiple apartments/flats)
 Regarding the type of the tertiary buildings five main categories are
defined:





Educational buildings
Hospitals
Hotels and accommodation facilities
Restaurants
Offices / Trade Stores
Building Categories in Montenegro
 Existing building stock in the FYR of Macedonia regarding to the period of
erection is divided into three categories :
 until 1980 (buildings with lot of reinforced concrete elements, without thermal
insulation) and
 since 1980 (when first standards of thermal insulation was appeared)
 Buildings built according to the European standards on Energy Performance of
Buildings Directive
 Regarding the type of the residential buildings three main categories are
defined:
 low buildings with 1 or 2 floors (detached and semi-detached houses) for
permanent housing
 high residential buildings (with multiple apartments/flats) for permanent housing
 low buildings with 1 or 2 floors (detached and semi-detached houses) for seasonal
use
 Regarding the type of the tertiary buildings two main categories are
defined:
 Hotels and accommodation facilities
 Offices / Trade Stores
Data Sources
FYROM:
 MAKStat Database of State Statistical Office  Energy Balances, HH size, population
etc.
 1st Energy Efficiency Action Plan (Ministry of Economy, 2011)  Age of the existing
building stock
 Household Consumption Survey (State Statistical Office, 2012)  Energy devices in
HHs (heating systems, cooling, hot water boilers, cooking ovens)
 Publications of the State Statistical Office (e.g. “Accommodation capacity in catering
trade and services 2011”, “Structural business statistics 2011”): data for the tertiary
Sector (e.g. total hospital area, number of educational buildings, total area of hotel
building stock, number of overnights etc.)
Montenegro:
 Statistical Office of Montenegro Database  Energy balances, age of the existing
building stock, tertiary Sector Data (e.g. number of hotels and accommodation
facilities, number of employees etc.)
 2011 Census of Population, Households, and Dwellings in Montenegro (Statistical
Office, 2012)  Population, HH Size
 The Household Budget Survey 2011 (Statistical Office of Montenegro 2012)  Energy
devices in HHs
Main elements defined for the purposes of the Reference Scenario
 Population growth
 Evolution of the average household size -> number of buildings,
appliances etc.
 Evolution of the average dwelling size
 Changes in the residential building stock (buildings to be
demolished/ abandoned/ renovated, new buildings)
 Evolution of the area of the tertiary sector buildings’ (hotels,
hospitals, offices etc.)
 Conformity of new buildings (i.e. constructed after 2010) to
European Standards (Directive 2002/91/EC on the Energy
Performance of Buildings)
Main assumptions made in the Reference Scenario (I)
 FYROM:
 The population will decrease from 2.036 million in 2006 to 2.025 million in 2020
and to 1.966 million in 2030 according to the UN demographic research
 The average HH size will decrease by 5% in each 5-yr period
 The average dwelling size will increase by 0.5% in each 5-yr period
 Residential buildings constructed before 1980 will be demolished / abandoned at
an average annual rate of 0.5% over the entire study period
 The number of the residential buildings constructed between 1980 and 2010 will
remain constant over the entire study period
 The area of the tertiary sector buildings’ (hotels, hospitals, offices etc.) increases
by 4% annually in 2015-2020, 3% in 2021-2025 and 2.5% in 2026-2030
 The area of the tertiary sector buildings constructed before 2010 remains constant
over the entire period
 All buildings constructed after the year 2010 are constructed according to
European Standards (Directive 2002/91/EC on the Energy Performance of
Buildings)
Main assumptions made in the Reference Scenario (II)
 Montenegro:
 Annual rate of population growth: 0.16% (medium-growth scenario/ Energy
Development Strategy by 2025, Ministry for Economic Development 2007)
 The average HH size will decrease by 2% in each 5-year period
 The average dwelling size will increase by an annual rate of 0.1%
 Residential buildings constructed before 1980 will be demolished/ abandoned at an
average annual rate of 0.5% over the entire study period
 The number of the residential buildings constructed between 1980 and 2010 will
remain constant over the entire study period
 All residential buildings constructed after the year 2010 will have diesel central
heating systems; heat pumps are gradually installed in 25% of the existing (built by
2010) buildings without central heating
 The area of the tertiary sector buildings’ will increase by an annual rate of 3.25%
for hotels and 2.5% for offices/trade sector
 The area of the tertiary sector buildings constructed before 2010 remains constant
over the entire period
 All buildings constructed after the year 2010 are constructed according to European
Standards (Directive 2002/91/EC on the Energy Performance of Buildings)
Reference Scenario – Energy Use per fuel
Tertiary Sector (FYROM)
Residential Sector (FYROM)
800
400,00
600
300,00
ktoe
500,00
ktoe
1.000
400
200
200,00
100,00
0
0,00
2010
Electricity
Diesel
LPG
2020
Natural gas
Solar
2025
Wood
Lignite
2030
2010
District heating
Gas/Diesel oil
Geothermal
300
30,00
ktoe
40,00
200
20,00
100
10,00
0
0,00
Electricity
2015
Diesel
2020
LPG
2025
Solar
Natural gas
Lignite
2020
Electricity
Fuel oil
2025
2030
Solar
District heating
LPG
Wood
50,00
400
2010
2015
Tertiary Sector (Montenegro)
Residential Sector (Montenegro)
500
ktoe
2015
Wood
2030
Lignite
2010
Gas/Diesel oil
2015
Electricity
2020
Solar
2025
LPG
Lignite
2030
Wood
Reference Scenario – Energy Use per end use
500,00
800
400,00
600
300,00
ktoe
ktoe
Tertiary Sector (FYROM)
Residential Sector (FYROM)
1.000
400
200
200,00
100,00
0
0,00
2010
Central Heating
Space cooling
2015
Individual Heating
Lighting
2020
2025
Cooking
Electric appliances
2030
Hot water
2010
Space heating
Lighting
Space Cooling
2020
Hot water
2025
Electric Appliances
2030
Cooking
Tertiary Sector (Montenegro)
Residential Sector (Montenegro)
500
50,00
400
40,00
300
30,00
ktoe
ktoe
2015
200
100
20,00
10,00
0
0,00
2010
Central Heating
Space cooling
2015
2020
2025
Individual Heating
Cooking
Lighting
Electric appliances
2030
Hot water
2010
Space heating
Lighting
2015
2020
Space Cooling
Hot water
2025
Electric Appliances
2030
Cooking
Reference Scenario – GHG Emissions
2.500
4.000
2.000
kt CO2eq
kt CO2eq
Residential Sector (FYROM)
5.000
3.000
2.000
Tertiary Sector (FYROM)
1.500
1.000
1.000
500
0
0
2010
2015
2020
Direct Emissions
2025
2030
2010
Indirect Emissions
250
800
200
600
400
0
0
2015
2020
2030
100
50
Direct Emissions
2025
Indirect Emissions
150
200
2010
2020
Tertiary Sector (Montnegro)
1.000
kt CO2eq
kt CO2eq
Residential Sector (Montenegro)
2015
Direct Emissions
2025
2030
2010
2015
2020
Indirect Emissions
Direct Emissions
Indirect Emissions
2025
2030
GHG Emissions Mitigation Measures examined
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Use of double glazing with thermal breaks frames (R,T)
External wall thermal insulation (R,T)
Roof insulation (R,T)
Retrofitting of old diesel boilers (R,T)
Use of natural gas for central heating systems (R,T)
Installation of high efficiency air conditioning units (R,T)
Installation of solar collectors for hot water (R,T)
Promotion of energy efficient light bulbs (R,T)
Promotion of energy efficient household appliances (R,T)
Installation of thermostats and heating controllers in buildings with diesel
central heating (R)
New energy efficient biomass stoves (R)
Installation of ceiling fans (R)
Installation of Building Management Systems (T)
Installation of heat pumps for space heating (T)
26,91
29,68
31,60
33,04
34,37
130,00
35,07
So lar C o llec to r s
Ro o f in su latio n
H eat p u m p s
Retr o fittin g d iesel
b o iler s D o u b le glazin g
Effic ien t A C
BM S
W all In su latio n
Natu r al gas b o iler s
1.200,00
Roof insulation
24,04
Solar collectors
19,0%
20,29
Double glazing
500,00
14,48
Retrofitting diesel
boilers 600,00
160,00
Heat pumps
170,00
BMS
Residential Sector (Montenegro)
Efficient AC
800,00
Effic ien t ligh tin g
Residential Sector (FYROM)
Wall Insulation
550,00
140,17
1.600,00
Effic ien t ap p lian c es
3.000,00
Refer en c e Sc en ar io
13,0%
kt C O 2 e q
3.400,00
kt CO2eq
1.800,00
Efficient lighting
136,49
Thermostats
and heating
controllers
279,10 336,04
388,22 420,40 443,26
460,34 475,04 485,23 493,54 495,13
Efficient appliances
126,54
Ceiling fans
4.000,00
Reference Scenario
650,00
Double
glazing
Retrofitting
diesel
boilers Efficient
wood stoves
Roof
insulation
Natural gas
boilers
Wall
Insulation
3.200,00
Ceiling fans
113,26
Double glazing
96,60
Roof insulation
79,77
Efficient AC
61,50
Efficient wood stoves
41,79
Solar collectors
21,30
Solar
collectors
3.600,00
Efficient AC
201,89
Efficient lighting
700,00
Efficient
lighting
104,53
Wall insulation
750,00
Efficient
appliances
Reference
Scenario
kt CO2eq
3.800,00
Efficient appliances
Reference Scenario
kt CO2eq
GHG Abatement Technical Potential
Year 2020
2.000,00
Tertiary Sector (FYROM)
182,60 255,03
301,73 343,97 373,16 390,76
408,14 424,06 435,20 442,73 444,17
1.400,00
1.000,00
24,1%
180,00
Tertiary Sector (Montenegro)
150,00
35,69
140,00
120,00
20,6%
GHG Abatement Cost Curve
Tertiary Sector (FYROM)
Residential Sector (FYROM)
800,00
600,00
600,00
400,00
400,00
200,00
€/t
€/t
200,00
0,00
0,00
‐200,000,00
‐200,00
50,00
100,00
150,00
200,00
250,00
300,00
350,00
400,00
450,00
500,00
‐400,00
‐400,00
‐600,00
‐600,00
0
100
200
300
400
500
‐800,00
600
kt CO2eq
kt CO2eq
‘win-’win’: 46% of total GHG mitigation
potential
‘win-’win’: 45% of total GHG mitigation
potential
Residential Sector (Montenegro)
Tertiary Sector (Montenegro)
500,00
1.000,00
400,00
800,00
300,00
600,00
€/t
€/t
200,00
100,00
400,00
200,00
0,00
‐100,00 0
20
40
60
80
100
120
140
160
0,00
‐200,00
0,00
‐200,00
‐300,00
‐400,00
kt CO2eq
‘win-’win’: 50% of total GHG mitigation
potential
5,00
10,00
15,00
20,00
25,00
30,00
35,00
kt CO2eq
‘win-’win’: 27% of total GHG mitigation
potential
40,00
Part B2. Transport (Croatia, Albania)
Structure of the Model for Transport (I)
•
•
•
•
Base year: 2010
Period of analysis: 2010-2030
Input data:
• Vehicles stock disaggregated by type, fuel, capacity and technology
(in accordance with EU Directives)
• Mileage
• Activity patterns (e.g modal shares)
• Additional characteristics (e.g. average speed per vehicle category,
passengers per vehicle etc.)
• Fuel characteristics (e.g NCV, density)
Data sources:
• National Inventory reports
• Energy Balances
• Statistical agencies
• National transport action plans
• National or international sector studies
• Eurostat, EEA etc.
Structure of the Model for Transport (II)
 Step 1. Total fuel consumption for the whole sector and for a specific year is
calculated ‘bottom-up’ by taking into account the stock, fuel
consumption and mileage per each type of vehicle:
Stock
(Eq-1)
FC  SFC  Mileage 
9
10
FC: fuel consumption, SFC: specific fuel consumption, Mileage: distance driven
per car, Stock: number of cars
 Step 2. The calculated energy consumption is compared with the data
provided in the relevant National Energy Balance. If necessary,
modifications are made in order to minimize differences.
 Step 3. The model is applied to 2010-2030 and future energy consumption
per vehicle type and fuel is calculated.
 Step 4. GHG emissions (CO2, CH4, N2O) are calculated by taking into account
the emission factor per gas and type of vehicle:
EFGHG
(Eq-2)
GHG  Stock  Mileage 
109
Data sources used
Croatia:
 The number of vehicles per vehicle type (e.g PC, LDV etc) in 2010 was provided
by the LOCSEE Croatian partner
 The disaggregation of vehicle stock per capacity and technology (following
COPERT) derived from the latest Croatian GHG Inventory for 1990-2010 (NIR
2012).
 Activity data (e.g. mileage, driving shares) derived also from NIR 2012.
 Net Calorific Value (NCV), fuel density and CO2 emission factors per type of fuel
derived from NIR 2012 and IEA.
Albania:
 The number of vehicles per type (passenger, HDV etc.) was obtained from the
Statistical Institute of Albania (INSTAT).
 The required further disaggregation of INSTAT data derived from assumptions
considering also the Croatian vehicles’ fleet distribution
 Net calorific values (NCV), CO2 emission factors data per type of fuel and
natural gas density were based on the 2006 IPCC Guidelines.
 Fuel densities for the rest of fuels derived from IEA.
General assumptions for the Reference Scenario

Stock per vehicle type (passenger cars, LDV, HDV, etc): considering the
evolution of vehicles fleet and socioeconomic factors (GDP growth, number
of vehicles per inhabitant and fuel consumption) up to 2010.

Disaggregation of the vehicles fleet per type of fuel and capacity (not
technology): based on the modal shares in 2010.

Disaggregation of the vehicles fleet per type of technology:
conventional vehicles (pre-EURO) and EURO 1 - 3 vehicles will be withdrawn
gradually by 2030 (Pre-EUROs by 2015, EURO 1 by 2020, EURO 2 by 2025,
EURO 3 by 2030)

Renewal rates of other vehicles: will be lower (especially for HDV) as the
adoption and market penetration of EURO standards presents a time lag
compared to EURO standards for passenger cars.

Energy efficiency per technology: will remain constant during 201520130 at the level of 2010.
Specific assumptions made in the Reference Scenario
Croatia




Vehicles stock for HDV and LDV during 2015-2030 will remain constant at
the level of 2010.
The number of buses and coaches will decrease slightly (up to -4% in
2030).
Passenger cars will increase by 7% every 5 years and up to 29% until
2030.
Motorcycles will increase by a total of 78% up to 2030.
Albania



Vehicles stock will evolve by a more conservative rate compared to Croatia
and the renewal rate is much lower.
The number of passenger cars, LDV and motorcycles will increase by a factor
of 1.2 in 2015 compared to 2010, 1.15 in 2020, 1.1 in 2025 and 1.05 in 2030.
The number of buses, coaches and HDV will remain constant during the whole
period 2010-2030.
Reference Scenario – Energy consumption
Εnergy consumption in the transport sector in Croatia
2500
2000
Electricity
CNG
Croatia
ktoe
1500
LPG
1000
Diesel
Gasoline
500
0
2010
2015
2025 in Albania
2030
Εnergy consumption
in2020
the transport sector
900
800
700
Albania
ktoe
600
500
Diesel
400
Gasoline
300
200
100
0
2010
2015
2020
2025
2030
Reference Scenario – GHG emissions
GHG emissions in the transport sector in Croatia
5,700
5,600
5,500
-11% from
2010
5,400
kt
Croatia
5,300
5,200
5,100
5,000
4,900
4,800
4,700
2010
2015
2020
2025
GHG emissions in the transport sector in Albania
2,550
2030
+7% from
2010
2,500
2,450
2,400
kt
Albania
2,350
2,300
2,250
2,200
2,150
2010
2015
2020
2025
2030
GHG Emissions Mitigation Measures examined
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Faster, compared to the
Renewal of gasoline passenger cars
Reference Scenario, penetration
Renewal of diesel passenger cars
rate of EURO 5 & 6 cars
Renewal of diesel LDV
Renewal of diesel HDV
Promotion of public transport
Use of hybrid passenger cars
Use of electric passenger cars
Eco-driving
Use of CNG buses
Increasing bus speed (traffic control, bus lanes)
Biodiesel penetration
 Directive 2009/28/EE asks for a biofuels’ share of 10% in the final consumption
of the transport sector
 Biodiesel is added to diesel
 In case of Croatia, this measure is not applicable due to the fact that it has
been already included in the Reference Scenario
GHG Abatement Potential and Cost Curve
Albania
Croatia
Energy conservation measures for the transport sector 4500
Energy conservation measures for the transport sector 4000
2000
3500
1500
2500
2000
euros/t
euros/t
3000
1500
1000
1000
500
500
0
-500
0
100
200
300
kt
400
500
600
0
0
50
100
150
200
-500
kt
250
300
Part B3. Waste (Serbia)
Waste Model - General Characteristics
 Estimates GHG emissions generated from municipal solid waste treatment
and disposal
 Waste treatment and disposal is broken down to specific technologies and
disposal options
 2010 is selected as the base year and the model’s results are compared
with the National Communication and other official sources
 GHG emissions calculated annually include:
 Process emissions from waste treatment and disposal (e.g. CO2 emissions
from the incineration of non-biodegradable part of wastes)
 Emissions from fuel and electricity use
 Avoided emissions due to electricity generated from Waste-to-Energy and
Anaerobic Digestion facilities
 Process GHG emissions are calculated according to Tier 1 (for Incineration
and Biological Treatment) and Tier 2 (for landfill) methods of the 2006
IPCC Guidelines
 GHG emissions are projected for the period 2010-2046
Structure of the Waste Model
T OT AL WASTE
BIO-WASTES
BIOLOGICAL
TREATMENT
MIXED WASTE
RECYCLABLES
RECYCLING
MBT
INCINERATION
LANDFILL
 Biological Treatment:
 Composting
 Anaerobic Digestion
 Recycling:
 At the source
 Material Recovery Facilities
 Mechanical Biological Treatment:
 Recovery of recyclables and
biological treatment of
organic fraction
 Bio-drying
 Incineration in WtE facilities:
 Mixed Wastes
 RDF / SRF from MBT
 Landfill:
 Unmanaged (deep/ shallow)
 Managed
 Managed semi-aerobic
 Uncategorized
Further Waste Treatment Options
 Biological Treatment
 Composting in covered windrows
 Dry Anaerobic Digestion followed by open air windrow composting
 Mechanical Biological Treatment of Mixed Waste
 MBT-1: Recovery of recyclables with a combination of advanced sorting
equipment, Production of RDF, Composting of the bio-stabilized organic
fraction
 MBT-2: Recovery of recyclables with a combination of advanced sorting
equipment, Production of RDF, Dry Anaerobic Digestion of the biostabilized organic fraction
 Bio-drying for production of SRF
 Incineration
 Incineration of mixed waste in grate combustor and power/heat
generation
 Incineration of RDF/SRF in fluidized bed combustor and power/heat
generation
Data sources used
 Total waste quantity and treatment options: data obtained from a
national database (“Waste Statistics and Waste Management in the
Republic of Serbia 2008-2010”, Statistical Office of the Republic of Serbia,
2012).
 Historical data on total waste quantity back to 1960: estimated on
the basis of population and an average daily waste generation of 0.60
kg/cap/day (2006 IPCC Guidelines).
 Waste composition: data obtained from official documents (“National
Waste Management Strategy 2012-2019”). Waste composition was
assumed to remain constant throughout the whole period
 Current level of recycling: data obtained from official reports ( “Report
on the management of packaging and packaging waste Years 2010-2012”,
Agency for Environmental Protection, Republic of Serbia 2013)
Main assumptions in the Reference Scenario
 Population growth: by an annual rate of +0.5% (“National Waste
Management Strategy 2012-2019”)
 Average per capita daily waste generation: will gradually reach the
present European average (i.e. 1.55 kg/cap/day) by 2030
 Waste Composition: will remain constant
 Legal targets regarding recycling-reuse and decrease of the
quantity of biodegradables disposed at landfill: will be achieved
 Regional landfills: fully compliant with EU Standards, will serve more
than 90% of the population by 2020 (currently 16% according to the
National Environmental Approximation Strategy for Serbia, 2011)
Reference Scenario – GHG Emissions
Waste Sector (Serbia)
2.500
-51% from 2010
2.000
kt CO2eq
1.500
1.000
500
0
‐500
2010
2015
2020
2025
2030
‐1.000
Direct Emissions
Indirect Emissions
Direct Emissions: Process Emissions and Fuel Emissions
Indirect Emissions: Electricity (consumption and generation) emissions
GHG Emissions Mitigation Measures examined
 4 GHG Emissions abatement scenarios were formulated
 In all scenarios:
 Residuals are disposed at managed landfills with biogas collection and
flaring
 Increase of recycling
 Separate collection of 20% of bio-wastes
 Composting (50%)
 Anaerobic digestion (50%)
 Treatment of the rest wastes (mixed):
 S1: MBT-1 (Advanced sorting equipment, Production of RDF, Composting
of the bio-stabilized organic fraction) & RDF incinerated in WtE facilities
 S2: MBT-2 (Advanced sorting equipment, Production of RDF, AD of the
bio-stabilized organic fraction) & RDF incinerated in WtE facilities
 S3: Bio-drying & SRF incinerated in WtE facilities
 S4: Incineration in WtE facilities
GHG Abatement Technical Potential
Waste Sector (Serbia)
2.500
kt CO2eq
2.000
1.500
1.000
500
Reference Scenario
Scenario 1
Scenario 2
Scenario 3
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
2010
0
Scenario 4
GHG emissions reduction by 2030 compared to the Reference
Scenario:




Scenario
Scenario
Scenario
Scenario
1:
2:
3:
4:
-18,5%
-69,8%
-28,1%
-61,4%
(189
(716
(288
(630
ktoe)
ktoe)
ktoe)
ktoe)
Thank you for your attention!
[email protected] (Elena Georgopoulou)
[email protected] (Sebastian Mirasgedis)
[email protected] (Yannis Sarafidis)