III. Projections of Greenhouse Gas Emissions

Transcription

Biennial report
in accordance with article 3.2 under Council Decision No 280/2004/EC
on a Mechanism for Monitoring Community Greenhouse Gas Emissions and for
Implementing the Kyoto Protocol
2011
Hungary
TABLE OF CONTENTS
I. INTRODUCTION ......................................................................................................................... 11
I.1. General structure of policy implementation ...................................................................... 12
I.2. Structure and use of the current report ............................................................................... 13
II. NATIONAL POLICIES AND MEASURES .................................................................................... 14
II.1. Overall cross-sector policies, strategies and operational programmes ............................. 14
II.1.1. The Programme of National Cooperation ................................................................. 14
II.1.2. National Climate Change Strategy ............................................................................ 14
II.1.3. National Sustainable Development Strategy ............................................................. 15
II.1.4. National Environmental Protection Programme 2009-2014 .................................... 16
II.1.5. The New Széchenyi Plan ............................................................................................ 17
II.1.6. Green Investment Scheme (GIS) ................................................................................ 19
II.2. General legal background ................................................................................................. 21
II.3. Energy Sector (Supply and Demand Side) ....................................................................... 22
II.3.1. Strategy documents .................................................................................................... 22
II.3.2. Promotion of renewables ........................................................................................... 27
II.3.3. Support for combined heat and power generation .................................................... 38
II.3.4. Modernization of district heating systems ................................................................. 42
II.3.5. Nuclear power ........................................................................................................... 45
II.3.6. Emission Trading System in the energy industry ...................................................... 47
II.3.7. Energy performance and efficiency of buildings ....................................................... 49
II.3.8. Improvement of energy efficiency in households ....................................................... 54
II.3.9. Improvement of energy efficiency in governmental and public institutions .............. 58
II.4. Industry ............................................................................................................................. 61
II.4.1. Operation of ETS ....................................................................................................... 61
II.4.2. Support for renewable energy utilization .................................................................. 62
II.4.3. Energy Efficiency Credit Fund .................................................................................. 63
II.4.4. Large energy consumers: Compulsory employment of energy managers and
energy reporting. .................................................................................................................. 64
II.4.5. Voluntary agreements ................................................................................................ 65
II.4.6. Heat recovery ............................................................................................................ 66
II.5. Transport ........................................................................................................................... 67
II.5.1. Strategy documents .................................................................................................... 67
II.5.2. Subsidy for improving the accessibility of Hungary and regional centres by rail
and/or waterways ................................................................................................................. 72
II.5.3. Improving the accessibility of regions ....................................................................... 73
II.5.4. Support for the development of urban and suburban public transport ..................... 74
II.5.5. Support for intermodal transport .............................................................................. 75
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II.5.6. Promotion of renewable (bio) fuels ........................................................................... 75
II.5.7. Toll system for heavy vehicles ................................................................................... 77
II.5.8. P+R systems .............................................................................................................. 78
II.5.9. Subsidy for the development of the cycling route networks....................................... 79
II.6. Agriculture ........................................................................................................................ 80
II.6.1. General ...................................................................................................................... 80
II.6.2. National Rural Strategy until 2020 ........................................................................... 82
II.6.3. Support for renewable based energy supply in agriculture ...................................... 83
II.6.4. Support for small-scale bio fuel plants ...................................................................... 84
II.7. Land use change and forestry ........................................................................................... 85
II.7.1. National Forest Programme and National Afforestation Programme...................... 86
II.7.2. Support for afforestation of agricultural lands ......................................................... 88
II.8. Waste management ........................................................................................................... 89
II.8.1. Basic legislation and National Waste Management Plan 2009-2014 ....................... 89
II.8.2. Legislative tools ......................................................................................................... 91
II.8.3. Environmental levy on certain products .................................................................... 93
II.8.4. Support of waste-to-energy projects .......................................................................... 94
II.8.5. Subsidy for recultivation of communal waste landfills.............................................. 95
II.8.6. Implemented............................................................................................................... 96
II.9. Education, awareness........................................................................................................ 96
II.9.1. Model projects to promote sustainable lifestyle and consumption............................ 96
II.9.2. EE and environmental training materials for schools............................................... 97
II.9.3. Support for information, training and awareness raising, energy advisory network 97
II.9.4. Training for engineers, teachers, experts, municipal staff ........................................ 99
Minimum criteria and labelling of household appliances ................................................... 100
II.9.5. Labelling of household boilers, air-conditioning equipment, water heaters ............ 101
III. PROJECTIONS OF GREENHOUSE GAS EMISSIONS................................................................. 102
III.1. Fuel combustion .............................................................................................................. 102
III.1.1. Heat energy consumption ......................................................................................... 102
III.1.2. GHG emissions from district heat production ......................................................... 129
III.1.3. GHG emissions forecast in the electricity sector ..................................................... 129
III.1.4. GHG emissions from transport sector ..................................................................... 142
III.2. Fugitive emissions from fuels ......................................................................................... 151
III.2.1. Solid fuels ................................................................................................................. 151
III.2.2. Oil ............................................................................................................................. 152
III.2.3. Natural gas ............................................................................................................... 154
III.3. Industrial Processes ......................................................................................................... 158
III.3.1. Introduction .............................................................................................................. 158
III.3.2. Analysis and projections .......................................................................................... 161
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III.4. GHG emissions from solvent and other products ........................................................... 171
III.5. Calculations of GHG emissions in agriculture and LULUCF ........................................ 171
III.5.1. Agriculture ............................................................................................................... 172
III.5.2. Land use and land use change ................................................................................. 174
III.5.3. Forestry .................................................................................................................... 176
III.5.4. Driving factors ......................................................................................................... 176
III.5.5. Results ...................................................................................................................... 181
III.6. Waste ............................................................................................................................... 183
III.6.1. Solid waste................................................................................................................ 183
III.6.2. GHG emission pathways for wastewater management ............................................ 190
III.7. ETS non-ETS split .......................................................................................................... 195
IV. MEASURES RELEVANT TO COMMUNITY LEGISLATION AND COMMITMENTS UNDER THE
KYOTO PROTOCOL ...................................................................................................................... 197
V. GLOSSARY ............................................................................................................................... 201
VI. REFERENCES .......................................................................................................................... 203
VII. APENDIX A: THE HUNMIT MODEL: ENERGY CONSUMPTION AND CO2 EMISSION........... 208
VIII. APPENDIX B: DESCRIPTION OF THE REGIONAL POWER MODEL ................................... 210
VIII.1. Analyzed countries ....................................................................................................... 210
VIII.2. Demand data ................................................................................................................. 210
VIII.3. Supply data ................................................................................................................... 211
VIII.3.1. Availability and fuel efficiency .............................................................................. 211
VIII.3.2. Secondary reserve .................................................................................................. 212
VIII.3.3. Fuel-prices ............................................................................................................. 213
VIII.3.4. Cost of CO2 emission ............................................................................................. 213
VIII.3.5. OPEX ..................................................................................................................... 214
VIII.3.6. Installed capacities in the future............................................................................ 214
VIII.4. Cross-border interconnections ...................................................................................... 215
VIII.5. Neighbouring market prices ......................................................................................... 215
IX. APPENDIX C: METHANE EMISSION FACTORS FROM MANURE MANAGEMENT ..................... 216
X. APPENDIX D: N2O EMISSION FACTORS OF ANIMAL MANURE MANAGEMENT........................ 217
XI. APPENDIX E: FACTORS OF N2O FROM PLANT PRODUCTION ................................................ 218
XII. ACKNOWLEDGMENT ............................................................................................................ 219
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LIST OF FIGURES
Figure 1 The structure of the New Széchenyi Plan .................................................................. 18
Figure 2 The organisational structure of the Green Investment Scheme ................................. 21
Figure 3 Renewable power supplied to the grid ....................................................................... 30
Figure 4 Share of renewable sources in power generation ....................................................... 30
Figure 5 Distribution of supported renewable projects by the type of energy ......................... 36
Figure 6 The total co-generated power in Hungary 2003-2009 ............................................... 40
Figure 7 The total emission of power generation and the emission savings achieved by CHP
as calculated by an independent consultant.............................................................................. 40
Figure 8 Projected quantities of KÁT subsidised cogenerated power ..................................... 41
Figure 9: Specific fuel consumption of Hungarian fossil-based power generation ................. 49
Figure 10 Project types of the ZBR Panel Program ................................................................. 54
Figure 11 Trends and targets in freight transport modal split .................................................. 72
Figure 12 Trends of biofuel use ............................................................................................... 77
Figure 13 Contribution of agriculture to the GDP ................................................................... 81
Figure 14 Contribution of agriculture to employment ............................................................. 81
Figure 15 Tree species in the Hungarian forests ...................................................................... 85
Figure 16 Afforestation in Hungary 2001-2009 ....................................................................... 87
Figure 17 Treatment of wastes ................................................................................................. 91
Figure 18 Waste-generated power supplied to the grid............................................................ 95
Figure 19 Heat energy consumption (PJ) and its share in total primary energy consumption
(%), 1990-2009....................................................................................................................... 102
Figure 20 Distribution of the heat energy consumption in 2009, PJ and % ........................... 103
Figure 21 GHG emissions calculation methodology ............................................................. 104
Figure 22 Historical (1990-2009) and forecast (2010-2025) RES share in heat energy
consumption in the three scenarios ........................................................................................ 105
Figure 23 Heat energy consumption of petroleum refineries between 1990 and 2009, TJ, NCV
................................................................................................................................................ 106
Figure 24 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the iron
and steel sector, TJ, NCV ....................................................................................................... 107
Figure 25 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the
non-ferrous sector, TJ, NCV .................................................................................................. 108
non-metallic minerals sector, TJ, NCV .................................................................................. 109
Figure 27 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of
chemical sector, TJ, NCV ...................................................................................................... 110
food processing, beverages and tobacco sector, TJ, NCV ..................................................... 111
pulp, paper and print sector, TJ, NCV.................................................................................... 112
manufacture of solid fuels and other energy industries, TJ, NCV ......................................... 113
Figure 31 Historic (2000-2009) and forecast (2010-2025) heat energy consumption of smaller
industrial sub-sector, TJ, NCV ............................................................................................... 114
agriculture sector, TJ, NCV.................................................................................................... 115
Figure 33 Final energy consumption of the residential sector ............................................... 117
Figure 34 CO2 emissions of the residential sector between 2000 and 2009 (actual, without
temperature adjustment, thousand tonnes of CO2) ................................................................. 118
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Figure 35 Energy consumption in the commercial/institutional sector.................................. 122
Figure 36 Evolution of CO2 emission in the commercial/institutional sector........................ 123
Figure 37 Emission factors of the various fuel types in the analyzed sub-sectors, CO2t /TJ . 127
Figure 38 Carbon dioxide emissions from heat energy consumption in the three scenarios, kt
CO2 ......................................................................................................................................... 128
Figure 39 Carbon dioxide emission from district heat production in the various scenarios, CO2
kt ............................................................................................................................................. 129
Figure 40 EUA price in different scenarios ........................................................................... 130
Figure 41 Historical and forecast real GDP growth ............................................................... 131
Figure 42 Historical, adjusted and forecast gross electricity consumption, 1991-2025, GWh
................................................................................................................................................ 132
Figure 43 Energy savings in the electricity sectors in WEM and WAM scenarios, 2010-2025,
GWh ....................................................................................................................................... 134
Figure 44 Energy efficiency measures taken into account in the course of regional modelling
relative to the gross electricity consumption in 2020,% ........................................................ 135
Figure 45 Gross electricity consumption in different scenarios, TWh, 2010-2025 ............... 136
Figure 46 Share of renewable-based electricity production compared to the gross electricity
consumption between 2010 and 2025 in the different scenarios, % ...................................... 137
Figure 47 Model operation ..................................................................................................... 139
Figure 48 Electricity mix in 2010, 2015, 2020 and 2025 for various scenarios, TWh .......... 140
Figure 49 Emissions of electricity producers in 2010, 2015, 2020 and 2025 for various
scenarios, thousand tones ....................................................................................................... 141
Figure 50 Distribution of transport emissions in 2009, kt CO2eq ......................................... 142
Figure 51 Number of cars in Hungary between 1985 and 2009 ............................................ 143
Figure 52 Emissions from transport between 1985 and 2009 (kt CO2eq) ............................. 144
Figure 53 Performance of road and railway transport between 2001 and 2009 (freight tonkm)
................................................................................................................................................ 145
Figure 54 Emission from aviation between 1985 and 2009 (kt CO2eq) ................................ 146
Figure 55 CO2 emission scenarios, kt CO2eq (without international aviation) ....................... 150
Figure 56 Methane emissions from production, transportation and refining, and from flaring
and venting between 1995 and 2025, kt CH4 ......................................................................... 152
Figure 57 Carbon dioxide emission from oil flaring between 1995 and 2025, kt CO2.......... 153
Figure 58 Distribution of the methane emission in 2009 ...................................................... 154
Figure 59 Length of the distribution system of natural gas, km ............................................ 155
Figure 60 Fugitive methane emissions from natural gas, kt CH4........................................... 156
Figure 61 Methane and carbon dioxide emissions from natural gas venting and flaring, kt . 157
Figure 62 GHG emissions from industrial processes and its share in total GHG emissions, kt
CO2eq and % ........................................................................................................................... 158
Figure 63 Distribution of the different GHGs from industrial processes in 2009.................. 159
Figure 64 GHG emissions of the sub-sectors in the industrial processes in 2009 ................. 160
Figure 65 Carbon dioxide emission of mineral products, 1995-2009, kt CO2 ....................... 161
Figure 66 Historical and forecast clinker production, kt ........................................................ 162
Figure 67 Carbon dioxide emission from lime production and limestone and dolomite
production between 1995 and 2025, kt CO2 .......................................................................... 163
Figure 68 Glass production, 1995-2009, kt ............................................................................ 164
Figure 69 CO2 emission from glass production in the three scenarios, kt CO2 ..................... 165
Figure 70 Bricks and ceramics production, kt........................................................................ 165
Figure 71 Carbon dioxide emission from bricks and ceramics production, kt CO2 .............. 166
Figure 72 Natural gas non-energy consumption in ammonia production, TJ ........................ 167
Figure 73 Carbon dioxide emission in the ammonia production, kt CO2 .............................. 168
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Figure 74 Historical (1995-2009) and forecast (2010-2025) crude steel production, kt........ 169
Figure 75 Historical halocarbon emissions between 1995-2009 and forecast emissions, CO2eq
................................................................................................................................................ 170
Figure 76 Historical carbon dioxide emission of feedstocks between 1995-2009 and the
forecast value, kt CO2............................................................................................................. 171
Figure 77 GHG emissions in the agriculture sector in different scenarios, 2008-2025 ......... 182
Figure 78 GHG emissions in the land use, land use change (LULUC) and Forestry in different
scenarios, 2008-2020 .............................................................................................................. 182
Figure 79 Amount of non-hazardous wastes from production ............................................... 184
Figure 80 Resource productivity in Hungary, EU-15 and EU-27 countries, €/kg, 2000-2007
................................................................................................................................................ 185
Figure 81 Quantity of the hazardous waste ............................................................................ 186
Figure 82 MSW quantities, kt ................................................................................................ 187
Figure 83: The production of MSW per capita, kg/person .................................................... 187
Figure 84 Different types of solid waste productions in the various scenarios, mt ............... 189
Figure 85 Share of solid waste management tools in total waste production, % ................... 189
Figure 86 Projected GHG emissions by scenarios (kt CO2e/year)......................................... 194
Figure 87 Analyzed countries ................................................................................................ 210
Figure 88 Marginal cost estimation methodology in the market simulation.......................... 211
Figure 89 Estimated variable operating expenditures by technology and year of build ........ 214
Figure 90 Existing capacities for cross-border trade (below 1000 MW) ............................... 215
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LIST OF TABLES
Table 1 Projected share of renewable energies in various sectors according to the NCsT ...... 25
Table 2 Projected installed capacities of the various RES technologies according to the NCsT
.................................................................................................................................................. 26
Table 3 Projected shares in the total renewable final net energy consumption in the heatingcooling sector ........................................................................................................................... 26
Table 4 Projected shares in the total renewable final net energy consumption in the transport
sector ........................................................................................................................................ 26
Table 5 Forecast of RES consumption in the various segments, PJ ........................................ 28
Table 6 GHG emissions reduction due to the RES consumption, Mt CO2/year ...................... 28
Table 7 Feed-in prices, HUF/kWh ........................................................................................... 29
Table 8 RES-E generation, GWh ............................................................................................. 31
Table 9 GHG reduction effect of all the renewable power promotion policies ....................... 31
Table 10 The key parameters of the individual support schemes ............................................ 35
Table 11 Awarded plantation support for fast growing species by September 2010 ............... 38
Table 12 GHG mitigation effect of planting energy crops and forests .................................... 38
Table 13 Projected emission reduction achieved by cogeneration plants ................................ 42
Table 14 Projected emission reduction achieved by modernization of district heating systems
.................................................................................................................................................. 43
Table 15 Projected emission reduction achieved by individual measurement and control in
district heating .......................................................................................................................... 44
Table 16 Lifetime extension and capacity increase of the Paks nuclear plant ......................... 45
Table 17 Projected emission reduction achieved by lifetime extension and capacity increase of
the Paks nuclear plant ............................................................................................................... 46
Table 18 Projected emission reduction achieved by new nuclear units in the Paks NPP ........ 47
Table 19 Suggested U-values of some building structures, W/m2K ....................................... 50
Table 20 Projected emission reduction achieved by Regulation on the energy performance of
buildings ................................................................................................................................... 50
Table 21 Projected emission reduction achieved by energy certification of buildings ............ 51
Table 22 Projected emission reduction achieved by Subsidy for energy efficiency
improvement projects ............................................................................................................... 54
Table 23 Projected emission reduction achieved by minimum efficiency criteria for household
boilers and air conditioning equipment .................................................................................... 55
Table 24 Projected emission reduction achieved by support for the procurement of highly
efficient refrigerators and freezers, other appliances ............................................................... 57
Table 25 Projected emission reduction achieved by promotion of CFLs and other efficient
lighting equipment.................................................................................................................... 58
Table 26 Projected emission reduction achieved by promoting third party financing............. 59
Table 27 Projected emission reduction achieved by including EE promotion elements in the
Regional Operative Programmes ............................................................................................. 60
Table 28 Projected emission reduction achieved by including EE principles in public
procurement procedures ........................................................................................................... 61
Table 29 Projected emission reduction achieved by minimum efficiency requirements for
office equipment ....................................................................................................................... 61
Table 30 Projected emission reduction achieved by Energy Efficiency Credit Fund .............. 64
Table 31 Projected emission reduction achieved by compulsory employment of energy
managers and energy reporting ................................................................................................ 65
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Table 32 Projected emission reduction achieved by voluntary agreements ............................. 66
Table 33 Projected emission reduction achieved by heat recovery ......................................... 67
Table 34 Modal split figures in 2020 according to the New Széchenyi Plan .......................... 70
Table 35 Projected emission reduction achieved by promotion of renewable (bio) fuels ....... 77
Table 36 Projected emission reduction achieved by toll system for heavy vehicles ............... 78
Table 37 Projected emission reduction achieved by P+R systems .......................................... 79
Table 38 Projected emission reduction achieved by support for renewable based energy
supply in the agriculture ........................................................................................................... 84
Table 39 Projected forest area, ha ............................................................................................ 88
Table 40 The income of the state budget form the product levy, M HUF ............................... 93
Table 41 Support of waste-to-energy project, HUF/kWh ........................................................ 94
Table 42 Projected emission reduction achieved by compulsory take-over of waste-to energy
power at subsidized prices........................................................................................................ 95
Table 43 Projected emission reduction achieved by EE and environmental training materials
for schools ................................................................................................................................ 97
Table 44 Projected emission reduction achieved by support for information, training and
awareness raising, energy advisory network ............................................................................ 99
Table 45 Projected emission reduction achieved by training for engineers, teachers, experts,
municipal staff ........................................................................................................................ 100
Table 46 Projected emission reduction achieved by minimum criteria and labelling of
household appliances.............................................................................................................. 100
Table 47 Projected emission reduction achieved by labelling of household boilers, airconditioning equipment, water heaters................................................................................... 101
Table 48 Heat energy consumption reduction in WEM and WAM scenarios compared to the
WOM scenario, % .................................................................................................................. 116
Table 49 Data by residents (constant 2008 HUF) .................................................................. 120
Table 50 Energy consumption in the WOM, WEM and WAM scenarios (PJ) ..................... 126
Table 51 Electricity consumption of heat pumps in different scenarios, GWh ..................... 135
Table 52 Assumptions for the various scenarios .................................................................... 138
Table 53 Emission factors of transport fuels (t/TJ) ................................................................ 146
Table 54 WOM scenario parameters for passenger transport sector ..................................... 148
Table 55 Assumed bio-fuel penetration rates (%) .................................................................. 149
Table 56 Projected passenger car sales between 2011 and 2020 (1000 pieces) .................... 149
Table 57 Fuel consumption in the scenarios (PJ) ................................................................... 150
Table 58 Species and their CH4 emission factors, kg CH4/head/yr ....................................... 172
Table 59 Land use change matrix .......................................................................................... 175
Table 60 Carbon storage changes in biomass and soil, tC/ha ................................................ 175
Table 61 Summary of expected changes in the input data ..................................................... 178
Table 62 Land use change in the WOM scenario .................................................................. 179
Table 63 Land use change matrix in the WOM scenario, 2010-2020, ha .............................. 179
Table 64 Land use change in the WEM scenario ................................................................... 180
Table 65 Land use change matrix in the WEM scenario ....................................................... 180
Table 66 Land use change in the WAM scenario .................................................................. 180
Table 67 Land use change matrix in the EXT scenario ......................................................... 181
Table 68 Forecast for the treatment of MSW with existing measures until 2014, kt............. 188
Table 69 Main assumptions in the different scenarios ........................................................... 188
Table 70 Carbon dioxide emission from solid waste incineration in million tons, 2008-2025
................................................................................................................................................ 190
Table 71 Methane emission from landfills in million tons CO2eq, 2008-2025....................... 190
Table 72 Key assumptions of the scenarios ........................................................................... 193
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Table 73 CH4 emission estimates by gas for key years, ktCO2eq .......................................... 194
Table 74 N2O emission estimates by gas for key years, ktCO2eq.......................................... 195
Table 75 The average share of the ETS coverage in the various sectors and GHG gases
between 2006 and 2009 .......................................................................................................... 196
Table 76 Gross fuel conversion efficiency factors ................................................................. 212
Table 77 Self-consumption and expected availability of power plants ................................. 212
Table 78 Fuel prices, in 2008 real terms ................................................................................ 213
Table 79 CO2 emissions by fuel type ..................................................................................... 214
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I. Introduction
The European Parliament and the European Council adopted in February, 2004 the Decision
2004/280/EC concerning a mechanism for monitoring Community GHG emissions and for
implementing the Kyoto protocol.
This decision in Article 3(2) requires that Member States shall, for the assessment of
projected progress, report to the Commission every two years:

information on national policies and measures which limit and/or reduce greenhouse
gas emissions by sources or enhance removals by sinks;

national projections of greenhouse gas emissions by sources and their removal by
sinks;

information on measures being taken or planned for the implementation of relevant
Community legislation and policies and

information on institutional and financial arrangements and decision making
procedures to coordinate and support activities related to participation in the
mechanisms under Articles 6, 12 and 17 of the Kyoto Protocol.
This report provides the relevant information and projections as required under Article 3 (2)
of the Decision.
The current report covers the period between 2009, when the previous Biennial Report was
prepared and early 2011. In the meantime, radical changes have happened in Hungary: further
to the parliamentary elections in spring, 2010 a new government was formed with very strong,
more than 66% majority in the Parliament. This enabled the Government to launch very deep
reforms in all areas of economy and society. These reforms, among others, also include the
review of all the strategies that have impact on the GHG mitigation efforts. The process is still
under way at the time when the current report is being prepared.
The reforms and all the strategy changes stem from the basic strategic goals that the new
government set when coming to power. These strategic goals were made public in the
Programme of National Cooperation, declared in May, 2010 by the Parliament.
The basic priorities of the programme, as its subtitle states, are work, home, family, health
and order, and its implementation is to focus on the following objectives:
Reviving the economy, improving employment are considered as the key factors for success,
where agriculture, construction industry, tourism and creative services will have a key role.
Work shall be the key value of the society. Administrative burdens of the enterprises shall be
eased.
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
Improving public order, through strong legislation and regulation, fight against
corruption, acceleration of court processes.

Health reform.

Promoting social security. Increased assistance to families, encouraging couples to
have children and helping them buy and keep a home is a top priority of the
programme. It is also important to improve the situation of the disabled, provide better
conditions for the Roma minority and promote their integration in society, fight
poverty in general and increase the level of services for the elderly.

Restoring democratic norms.
It may appear from the list of priorities that sustainability, climate policy or GHG emissions
are not in the focus. This is not true: although the major goals target the most immediate
problems of the Hungarian society, as it will appear from the report, effective policies to
mitigate GHG emissions are in place, and the strategies, programmes that are to serve the
above objectives are and will be designed with sustainability, climate change and Hungary‘s
such international commitments in mind.
However, as said above, the formulation and the review of the dedicated strategies, such as
the energy strategy and the climate change strategy are still in progress. Therefore, the current
situation described in the report is not showing the final coherent approach that will found
long-term mitigation trends, but attempts to accurately describe the efforts so far and the
foreseen future on the basis of past trends and available information of future policies.
I.1. General structure of policy implementation
Policy implementation in Hungary follows a traditional top-down structure. The strategy
documents define the strategic objectives and the general instruments by which these
objectives are to be achieved. The strategies are then translated into action plans or
programmes. These work out and describe the actions in detail which are to achieve the
strategic objectives, identify the quantitative targets and preferably the source of funding
necessary to implement the planned actions.
The actions or the individual policies then are implemented through so-called operative
programmes to which appropriate funding is allocated from the budget. These operative
programmes are organized around certain strategy priorities. Thus for example KEOP
operative programmes implement energy and environment related policies (KEOP stand for
the Hungarian equivalent for Environment and Energy Operative Programme) or KÖZOP
programmes realise transport related actions. In some exceptional cases, where some
organisational, financial or other reasons so require, the policies are executed directly by the
responsible agency. Thus for example the Energy Efficiency Credit Fund – as there is no
funding from the state budget – is managed independently from the operational programmes.
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I.2. Structure and use of the current report
The report follows the structure required by the Article 3(2) of 2004/280/EC. The description
of national policies is organised according to the general policy implementation structure
described above. First those strategies and strategy documents are described that have general
cross-sector relevance. Then the policies of the individual sectors are presented. The
discussion of the sector policies also starts with the sectoral strategies and action plans, then
the concrete policies and measures are explained.
In some aspects the current report strongly relies on the previous biennial reports. Policies
that have been in place for a long time and properly discussed in the previous reports are
typically not presented in detail here, only the changes are pointed out.
Generally, wherever acronyms or abbreviations are used to refer to a Hungarian organization,
document or legislation, the original, generally used Hungarian abbreviations or acronyms are
used. Some exceptions, however, may occur, especially when no generally accepted
Hungarian acronym exists and/or the previous Biennial Reports used the acronym
extensively. Normally the full name of the entity referred to is given in its English translation
at the first occurrence of any abbreviation/acronym, but all acronyms are explained in the
Glossary.
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II. National Policies and Measures
II.1. Overall cross-sector policies, strategies and operational programmes
II.1.1. The Programme of National Cooperation
The major cornerstones of the Programme of National Cooperation were introduced in the
introduction, as this document defines the very basic strategic objectives of the government in
the coming years. As it was mentioned there, although the basic objectives are not focused on
GHG mitigation, the implementation of the program includes several such components, and
the Programme of National Cooperation itself has some priorities that serve this purpose.
These are briefly summarised here:

In reviving the economy, the construction industry has an important role. It is stated in
the programme that one tool to boost the construction industry is to promote the
European initiative to employ ―green‖ technologies and to develop the energy
efficiency of buildings and the construction materials.

A ―green‖ bank is to ensure financing for energy efficiency projects.

A large scale energy efficiency program is to be launched with components such as
deep-reconstruction of pre-fab buildings (reduce consumption by 80%), thermal
insulation projects of other buildings, reconstruction of public buildings etc.

Investments in renewable energy have to be encouraged.

Environmental considerations shall be integrated in the national development policy

Environmental protection shall be taken into consideration in the public procurement
procedures.

In order to boost the economy new take-off points need to be found. Green economy
and the utilisation of renewable energies are among the possible take-off points.
II.1.2. National Climate Change Strategy
The National Climate Change Strategy 2008-2025 (NÉS) was adopted by the Parliament
unanimously in early 2008 (Parliamentary resolution 29/2008. (III. 20.) OGY). It has not been
changed since, although its review is currently under way and the updated document is
expected by late 2011.
The NÉS was presented in detail in the previous biennial report [1]. Only its key points are
summarised here:

The GHG emission reduction target is 16-25% of the 1991 levels by 2025.

The responsibility of the government is to create the necessary regulatory-legal
framework; to review and adjust the subsidy systems; to raise the awareness of the
society, by giving priority to sustainability and providing good example.
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
The residential sector is a key field of change: peoples‘ lifestyle needs to be changed;
a large scale reduction of demands for energy and materials must be achieved (by
subsidised energy efficiency projects, among others);

Industry and other enterprises also need to reduce their energy consumption, adopt
emission reduction measures, ―to green‖ their profile, products, services.
 NGOs, civil organisations shall have increased role in the dissemination of
information, awareness raising and civil control.
 Main areas of intervention are:
o Energy efficiency in buildings
o Renewable energy utilisation
o Transport (road tolls, other economic incentives, modal split change)
o Afforestation
II.1.3. National Sustainable Development Strategy
As the Renewed EU Sustainable Development Strategy adopted by the European Council on
15/16 June 2006 requires, Hungary prepared the country‘s first National Sustainable
Development Strategy (NSDS) and submitted to the Council in 2007. The EU strategy
requires that the Member States would revise their National Strategies regularly, subsequent
to the revision of the EU SDS, in order to ensure consistency, coherence and mutual
supportiveness.
In terms of GHG emission mitigation, similarly to the NÉS and earlier Energy Strategy
documents the NSDS also includes among its objectives the utilisation of renewable energies;
bio-fuels in transports, improvement of energy efficiency to be achieved by:
 Review of the EU-ETS system to include stronger incentives for GHG mitigation;
 Implementation of the actions of the Energy Efficiency Action Plan
 Financial incentives for bio-fuels (preferential taxation)
 Financial support for renewable and energy efficiency projects
 Shift towards environment friendly transport modes
 Awareness raising
 Sustainable forestry
 Education and training
In 2009 the Commission adopted the 2009 Review of EU SDS, and in the light of this
document the revision of the Hungarian NSDS is under way. Since NSDS is to be based on
and harmonised with the Climate Change Strategy and the sectoral strategies, such as the
Energy Strategy or the Transport Strategy, which are still being prepared, the revised NSDS is
delayed and is expected by early 2012.
15
II.1.4. National Environmental Protection Programme 2009-2014
The Act LIII of 1995 on the General Rules for the Protection of the Environment stipulates
that a regularly (in every six year) revised and updated National Environmental Protection
Programme (NKP) would be prepared. The first such programme was approved by the
Parliament in 1995 and it was updated regularly as required by the law.
The currently effective National Environmental Protection Programme 2009-2014 (NKP-III)
was adopted by the Parliament in 2009 (Resolution of the Parliament 96/2009. (XII. 9.)
OGY).
Similarly to the previous programmes, the NKP-III identifies general objectives, which are
then broken down to specific actions, so-called thematic action programmes or TAPs.
The general objectives are the following:
 Improving the quality of the environmental and life locally
 Preservation of naturals resources
 Promotion of sustainable lifestyle, production and consumption
 Improvement of environmental safety
From among the TAPs the following have relevance from the aspect of GHG mitigation:
 Reinforcing environmental awareness
o Education, training within the education system from elementary schools to
universities
o Environmentally conscious production and consumption
o Access to environment-related information, information dissemination
 Combating climate change
o Reduction of GHG emissions (EU-ETS system, improvement of energy
efficiency [NEEAP],
o Reducing the environmental impact of transport (reducing demand,
restructuring modal split, alternative fuels)
o Reducing emissions from the agriculture (improvement of production
efficiency)
o Afforestation according to the National Afforestation Programme.
 Environment and health
o Transport and environment (Reverse the tendency of shifting to individual
transport)
 Protection and sustainable utilisation of waters
o Utilisation of the energy of geothermal waters
 Waste management
o Prevention (reduction of waste quantities)
16
o Utilisation of wastes and recycling
o Reduction of landfilled waste
II.1.5. The New Széchenyi Plan
The New Széchenyi Plan (ÚSZT) is the economic development programme of the Hungarian
government. This programme translates the economy-related objectives of the Programme of
National Cooperation into a concrete programme. The main objectives of the New Széchenyi
Plan starting on the 15th of January, 2011 are to improve the competitiveness of Hungary and
to create one million new jobs over the next ten years with the help of seven take-off points.
The seven take-off points of the New Széchenyi Plan are:
1.
2.
3.
4.
5.
6.
7.
Healing in Hungary – Health industry
Renewal of Hungary – Development of green economy
Home projects – Residential property policy
Network economy – Development of business environment
Knowledge economy - Science – Innovation – Growth
Employment
Transport – Transit Economy
Besides being a program, the New Széchenyi Plan is also a tool to provide financing for the
implementation of all strategic goals. The operative programs are financed through the New
Széchenyi Plan, and in this regard it is an important ―umbrella‖ policy for all other relevant
strategies including the Energy Strategy, Transport Strategy, Energy Efficiency Action Plan,
etc.
In this regard it is important to review the key programmes and principles of the ÚSZT –
being the latest decisive strategy document –, as it indicates the actual priorities of the
government.
17
Figure 1 The structure of the New Széchenyi Plan
The programmes of the ÚSZT with GHG mitigation relevance:
1. Energy policy
a. Energy policy is to serve economic growth and job creation, but also the
security of supply and diversity of resources, the reduction of import
dependence.
b. Production and utilization of renewable energies is to be encouraged. The
following measures are planned to stimulate the utilization of renewable
energies through domestic support funds:
i. Revision of discounts on fossil fuels (e.g. discounts on gas
consumption, carbon tax, etc.);
ii. Restructuring of the actual support system (revision of investment
support, preference of domestic added value, introduction of a green
certificate);
iii. Modification of the support mechanism to promote the
renewal/adaptation of heating systems;
iv. Facilitation of renewable energy producers‘ network connection.
c. The Plan regards projects affecting climate change and projects of mitigation
and adaptation in connection with the energy sector as of supreme priority.
These include the reduction of the emission of greenhouse gases, the
promotion of climate-friendly investments, as well as projects increasing social
18
acceptance and awareness of environmental protection issues. To this end, the
Plan works out and implements measures and development projects to support
the National Climate Change Strategy.
d. Nuclear energy is given high priority due to its favourable impact on the
security of supply and GHG mitigation.
2. Transport
a. Creating the financial resources necessary for a sustainable transport system.
b. Encouraging intermodal transports.
c. Enforcing environmental and climate policy considerations
d. Increasing environmental awareness, economic policies striving to achieve
(more) local operation spreading throughout Europe.
e. Transformation of the primary energy mix – a greater proportion of renewable
energy is necessary.
f. The advantages of Hungary‘s geographical situation can be realized only if,
having an adequate traffic and transport system, nodes as well as intermodal
and multifunctional logistics centres and related industrial parks established in
these nodes, it is possible to stop part of the transit traffic and ensure added
value.
II.1.6. Green Investment Scheme (GIS)
The Kyoto Protocol of the UNFCCC made carbon trading possible. Due to the restructuring
of the economy and the closing down of energy intensives industries in the past twenty years
Hungary is in the position to sell emission rights or allowances (so-called assigned amount
units, or AAUs). Due to criticisms from the international community who are doubtful about
the true mitigation effects of such ―hot-air‖ sales, nowadays such trading requires that the
revenues from the sales would be spent on emission reduction measures – the more concrete
and quantifiable results, the better. In order to make such transactions and the consequent
mitigation measures transparent, such deals and their revenues are to be managed through a
dedicated financial facility, the green investment scheme (GIS)
Hungary was the first to sell AAUs in 2008 and also among the first ones to create a
transparent GIS. The legal background for the GIS is provided by the amended Act LX of
2007 on the implementation framework for the United Nations Framework Convention on
Climate Change and its Kyoto Protocol, whereas the details of its operation are regulated by
Government Decree 323/2007 (XII. 11.) on the implementation rules of Act LX of 2007. The
latter unambiguously states that all revenues of the GIS, including interests can only be used
to support in form of grand, interest support, loan or other payments the following GHG
mitigation efforts:
 Improvement of building energy efficiency;
19
 Increasing the utilisation of renewable energies;
 Improvement of efficiency of district heating systems;
 Promotion of the construction of low-energy consumption buildings;
 Energy efficient modernisation of indoor and outdoor lighting systems;
 Promotion of creating carbon sinks;
 Emission reduction in the transport sector;
 Replacement of old inefficient household appliances and electronic devices with new
certified low energy consumption equipment;
 Other emission reduction.
Maximum 5% of the GIS revenues can be used for covering the administrative costs of the
GIS. It is also required by the regulation that the supported project should be additional (i.e.
not implemented without the support). Further details of the operation of the GIS including
the responsible organisations, procedure of contracting, process and rules of application for
support, reporting procedures etc) are regulated by the Ministerial Instruction 18/2011. (III.
29.) NFM.
Thus the areas where the carbon trade revenues can be used are not only controlled by the
sales contract but also restricted by the law, and the entire operation of the GIS is properly
regulated.
20
Figure 2 The organisational structure of the Green Investment Scheme
The GIS is considered a key source of funding GHG mitigation projects and efforts. Several
of the policies described in the current report have been or will be financed at least partly
from GIS sources.
The policies already implemented with funding from the GIS are presented in the current
report in detail (see points II.3.7.3, II.3.8.2, II.3.8.3). It is planned to restructure the GIS with
the following priorities in mind:
 Complex (deep) energy efficiency revamp of multi-flat and family houses, to increase
the approximately 40% energy saving achieved by GIS programmes so far to at least
60%
 Support for the construction of new highly efficient buildings.
 Loan guarantee for the investors of the above projects, so that they could take loans at
better conditions to provide their own share for the other supports from the GIS.
II.2. General legal background
The general legal background of all GHG mitigation policies is provided by:
 Act LXXXVI of 2007 on electric power;
 Act XL of 2008 on natural gas;
 Act LIII of 1995 on the General Rules for the Protection of the Environment;
 Act LX of 2007 on the implementation framework for the United Nations Framework
Convention on Climate Change and its Kyoto Protocol;
21
 Act XV of 2005 on the trading with emission units of greenhouse gases;
 Act XXXVII of 2009 on forests, forest protection and forest management;
 Act XLIII of 2000 on waste management
and their implementation decrees.
The major role of these pieces of legislation is to ensure the legal base for emission reduction
measures. All this legislation is still in place and their major GHG related stipulations that
serve this purpose were discussed in the previous biennial reports (see e.g. [1]). Minor
changes and amendments of the legislation, however are constantly made, but these have not
affected the legal base of GHG mitigation so far. Stipulations of the legislation with specific
GHG policy relevance are explained in the description of the individual policies later in this
report.
II.3. Energy Sector (Supply and Demand Side)
II.3.1. Strategy documents
II.3.1.1. National Energy Strategy
The Hungarian Energy Strategy is still legally defined by 40/2008. (IV.17.) Decree of the
Parliament, which is discussed in detail in the previous Biennial Report (2009). However,
serious efforts have been made by the current Government to re-define the energy strategy.
The project is managed by the Ministry of National Development. The new strategy is
expected to be finished by summer, 2011, therefore no official version is available yet.
Still, as the future trends of energy generation and consumption and hence GHG emissions
will be defined by this strategy it is important to review the outlines of the strategy on the
basis of available information (strategy draft issued for public consultation, press releases of
the MND).
The basic priorities, strategic goals have not changed. In line with the European strategy they
are still threefold: security of supply, competitiveness and sustainability. However, as far as
the tools to achieve these goals are concerned, the emphases within the strategy will shift
towards lower carbon intensity of conventional technologies and the support of viable
innovative ―green‖ technologies in order to accelerate the process of their introduction and
wide range awareness raising. The tools will include increased reliance on renewables and
nuclear energy as well as energy saving and efficiency improvement.
The foreseen key elements of the energy strategy from the aspect of GHG emission mitigation
are the following:
 Limitation of the increase of energy demands until 2030 and the simultaneous
reduction of GHG emission reduction. (Suggested, not yet official figures: maximum
22
10% increase of primary energy consumption, reduction of GHG emission of the
energy sector by 25-28%)
 Increase the share of district heating within heat supply along with the modernisation
of the district heating systems and much larger utilisation of renewable energies.
 Strong increase of the share of renewables in individual heat supply.
 Reduction of residential heat demands by some 30% through (building) energy
efficiency programmes.
 Reduction of carbon intensity (CO2/kWh) of the energy sector by some 30-33%
o Nuclear power generation
o Renewables in cogeneration plants.
o Shutting down old, inefficient capacities
 Improvement of the energy efficiency of transport
o by promoting railway cargo transport and
o by converting public transport to locally produced, sustainable fuels.
 Promoting decentralised power generation.
 Reliance on regional cooperation in diversifying sources, increasing the network
buffer capacities.
II.3.1.2. The amended National Energy Efficiency Action Plan
The energy efficiency related objectives of the original energy strategy were translated into
the National Energy Efficiency Action Plan (NEEAP) in 2008. A detailed account is given on
the original NEEAP in [1]. Having reviewed the progress and the changed priorities since
2008, the ministry responsible for the NEEAP (then the Ministry for Economy and Transport)
updated and amended the document and issued the amended NEEAP in January, 2010. The
results of the NEEAP are to be evaluated by 30 June, 2011, when the second amended
NEEAP is to be submitted, and a third NEEAP is to be prepared using the results and
experience gained by 30 June, 2014.
The major objectives were not changed. They remained the following:
 Compliance with 2006/32/EC
 1% reduction of energy consumption per year, between 2008-2016, which corresponds
to 6.38 PJ cumulative reduction per year, achieving an overall 57.4 PJ/year saving by
2016.
The key areas of action identified in the amended NEEAP are the following:
 Requirements of newly constructed buildings
 Building stock in the residential sector
 Building stock in the institutional sector (with special focus on municipal and
governmental institutions)
23
 Transport (passenger and cargo)
 Energy intensive products and processes
 Awareness raising
Improvement in these target areas is to be achieved by various policies, mainly by subsidies
and regulatory tools.
The NEEAP lists 11 concrete measures in the residential sector, 6 measures at the
governmental/municipal institutions, 8 policies in the industrial sector, 2 measures in the
transport sector and a cross-sectoral policy. Some of these policies have already been
implemented, other are still in the planning phase.
In order to avoid overlaps in the current document, these policies and measures are not listed
here, but among the concrete policies and measures of the individual sectors, with proper
references to the relevant points of the NEEAP. The expected or forecast savings and
emission reduction are not quoted here either, although the document includes numerical
forecasts, but the individual PAMs and the results are included in the WEM and WAM
scenarios of the projections.
II.3.1.3. Renewable Energy Action Plan
The Renewable Action Plan (the official title is: Hungary‘s Action Plan for the Utilisation of
Renewable Energies 2010-2020, in the context of the current document: NCsT, for short) was
published early 2011, after long discussion by the professional public.
Although the NCsT is, based to some extent on the Renewable Energy Strategy 2008-20201,
approved by the government in 2008 (Governmental Decree, 2148/2008.(X.31.)), it considers
the impacts of the global economic crisis since that time, and the new priorities of economy
development of the government, and it fully replaces and overwrites the strategy2.
Thus the NCsT is already part of the coherent strategic approach of the new government. It is
based on the priorities of the new Energy Strategy (most precisely on the support aspect of
viable innovative ―green‖ technologies) and stems from the Programme of National Cooperation, which considers green economy one of the prime movers of setting the national
economy in motion.
The NCsT reconfirms Hungary‘s overall target for the share of renewable energies and
identifies the key areas of intervention, stating individual quantitative targets. It sets more
ambitious targets than originally set by the European Union in order to support the overall
economic objectives (job creation, improving competitiveness, reducing energy import
1
This document is discussed in [1]
2
2148/2008.(X.31.) Government decree was deregulated in January 2011.
24
dependency) through boosting ―green‖ economy. While the RED Directive (2009/28/EC) of
the EU set the renewable target for Hungary as minimum 13% of the total gross final energy
consumption, the objective defined by the NCsT is 14.65%.
In conformity with the principles of the new Energy Strategy and the Programme of National
Co-operation, the NCsT is based on the following basic strategic goals:
 Safety of energy supply (reduction of import dependency)
 Climate protection, sustainability (mitigation of GHG emissions)
 Rural and agricultural development (waste utilisation of husbandry improves
competitiveness, growing markets for by-products of farming creates/preserves jobs)
 Development of green economy (construction and operation of renewable related
projects creates jobs, manufacturing of equipment for renewable technologies
contributes to the economic growth).
 Contribution to meeting community objectives.
The NCsT however takes a realistic approach and considers several constraints, as well, such
as:
 Load bearing capability of the population and market players
 Possible inefficiency of resource allocation (improvement is necessary)
 Controllability of the national power system
 Even distribution of revenues along the product chain (biomass producers – power
producers – distributors – consumers).
The overall and sectoral targets and forecast development of the share of renewables
according to the NCsT are summarised in the following table:
Table 1 Projected share of renewable energies in various sectors according to the NCsT
Share of renewables
2005
2010
2020
Heating and cooling
5.40%
9.00%
18.90%
Electric power
4.30%
6.70%
10.90%
Transport
0.22%
3.70%
10.00%
Total
4.20%
7.40%
14.65%
The NCsT also makes estimates as to the potential types of renewable energies and applicable
technologies in meeting the above targets.
For electric power generation the following forecasts are made in the NCsT:
25
Table 2 Projected installed capacities of the various RES technologies according to the NCsT
Installed capacity,
MW
Share in total
renewable power
generation
2010
2020
2010
2020
Hydro power
51
67
6.8%
4.2%
Geothermal
0
57
0.0%
7.3%
Solar PV
0
63
0.1%
1.4%
Wind power
330
750
24.3%
27.6%
Solid biomass
360
500
65.8%
48.0%
Biogas
14
100
3.0%
11.4%
Total
755
1537
-
-
The individual renewable energy sources (or technologies) are projected to have the following
shares in the total renewable final net energy consumption of the heating-cooling sector:
Table 3 Projected shares in the total renewable final net energy consumption in the heating-cooling sector
2010
2020
Geothermal
10.9%
19.2%
Solar
0.6%
4.4%
Solid biomass
87.8%
65.8%
Biogas
0.0%
3.0%
Heat pumps
0.6%
7.7%
The NCsT includes similar forecasts for the transport sector:
Table 4 Projected shares in the total renewable final net energy consumption in the transport sector
2010
2020
Bioethanol/bio-ETBE
22.7%
35.3%
Biodiesel
73.3%
59.3%
Hydrogen from renewables
0.0%
0.0%
Renewable electric power
4.0%
4.5%
Other (biogas in public transport)
0.0%
0.9%
The NCsT identifies a set of policies and measures (some of these are planned, some of these
are existing, although require re-shaping in some cases) that are to serve to achieve the
objectives. These PAMs and measures are only listed here but described later in detail:
1. Support schemes:
a. Direct subsidy of individual investments between 2011-2014
b. A new dedicated operative programme from 2014
c. Investment programmes financed from the EU-ETS
d. More active participation in community financed programmes
26
e. Development of green economy
2. Other financial incentives:
a. Green bank or targeted revolving credits
b. R+D in renewable energies
c. Subsidy of green (renewable) heat (from 2012)
d. Compulsory take-over (subsidy) of renewable power
e. Preferential prices for heat pump power (―Geo-tariff‖)
f. Compulsory share of biofuels in motor fuels
3. Legal/regulatory tools
a. New act on sustainable energy management
b. Creation of proper conditions to feed biogas to natural gas grid
c. Revision and simplification of licensing procedures
d. Compulsory share of renewables in building energy use.
Similarly to NEEAP, the expected or forecast savings and emission reduction projected to be
achieved through these measures, are not described here, but at the detailed description of the
individual PAMs and the results are included in the WEM and WAM scenarios of the
projections.
II.3.2. Promotion of renewables
Objectives and description
As it discussed in several points in the current document, various policies with the aim of
promoting the utilisation of renewable energies are already in place and others are planned in
order to meet the strategic goals set in the National Climate Change Strategy, and the National
Energy Strategy to be approved soon. The general framework and main components of such
policies are set in the NCsT, described in the previous chapter.
Many of these policies and measures, however, do not include individual quantifiable targets,
but are merely tools for achieving the overall goals set in the strategy documents and the
NCsT. Therefore, as it is referred to at the relevant points, it is also not possible to make
reasonable projections as to the effects of such policies individually. It is possible to derive
emission reduction forecast from the expected overall effects of the promotion of renewable
energies, though. These forecasts are presented in this section.
Type of policy instrument
Chiefly economic, see at the individual measures.
Status of implementation
See at the individual measures
Monitoring indicators
27
See at the individual measures
Effects and impacts
From the objectives of the NCsT described in section II.3.1.3, the following forecast can be
derived:
Table 5 Forecast of RES consumption in the various segments, PJ
2010
2015
2020
2025
Heating and cooling
Gross final consumption
433.2
445.3
406.9
368.6
Of which renewable
39.7
43.9
78.0
105.7
Electric power
153.9
172.4
185.0
197.3
Of which renewable
10.2
13.9
20.1
24.6
Transport
166.0
202.0
221.3
241.4
Of which renewable
6.3
11.1
22.4
38.3
When achieved, the above increase in the utilisation of renewables will results the following
emission reduction:
Table 6 GHG emissions reduction due to the RES consumption, Mt CO2/year
2010
2015
2020
2025
Change in emission reduction
-
0.03
0.75
0.75
Accumulated emission reduction
5.1
6.6
10.7
14.5
II.3.2.1. Compulsory take-over of renewable based power at subsidized prices (KÁT)
The objective of the policy is to promote the utilisation of renewable energies in power
generation by providing safe and attractive market for green power. The indirect objective is
to meet the renewable targets and thus mitigate GHG emissions. The objective is achieved by
• stipulating the mandatory purchase of renewable-generated electric power;
• providing financial support for the operators of renewable power plants in the form of
regulated and subsidised feed-in tariff (Hungarian abbreviation: KÁT).
The legal background of the system is provided by VET, which stipulates the compulsory
take-over of power generated from renewable energy sources and/or waste and of cogenerated
power. It is important to note that VET includes provisions for sustainability. Thus, for
example, it prohibits the application of the compulsory take-over system for electric power
generated from wood if the wood is of good quality (suitable for other purposes) or harvested
without licence. VET also ensures that the subsidised take-over price shall increase with
inflation, its real value would remain stable. It is a basic principle of the subsidy system that
28
subsidised prices can only be provided for the generated electricity during the economic
payback period of the renewable project.
The details of the subsidy system are regulated by Governmental Decree 389/2007. (XII. 23.).
The most important stipulation is that compulsory take-over and subsidised feed-in tariffs
only apply if the power generation is exclusively based on renewable energy sources/waste or
in case of co-firing the share of renewables/wastes is no less than 30%. In the latter case
subsidised price is given for the renewable/waste share of the total generated power only.
The take-over prices and their structure have changed several times (the Decree has been
amended many times since its issuance in 2007) in accordance with actual energy policy
priorities. The latest feed-in prices (as of 1st January, 2011) differentiate between the various
renewable energies and the size of the generation facilities, and are the following.
Table 7 Feed-in prices, HUF/kWh
Category of the generation facility
Solar and wind power
Licensed before
Non solar and non wind
01.01.2008.
Solar power
20 MW or smaller power
Licensed after
plants (non solar)
01.01.2008.
20 – 50 MW power plants
(Except: hydro
(non solar and non wind)
power >5 MW and
20 – 50 MW wind power
other power plants
plant
>50 MW)
Plants including old
equipment
Hydro power >5 MW and other power plants
>50 MW
Peak
30.71
34.31
29.84
33.35
Off-peak
30.71
30.71
29.84
29.84
Night rate
30.71
12.54
29.84
12.18
26.67
23.88
9.74
33.35
29.84
12.18
20.74
13.27
13.27
20.74
13.27
13.27
Regulatory, economic.
Implemented
• Quantity of electric power fed to the grid (kWh)
• Fuel use by the plants (GJ) where applicable
Electric power data are reported by the generation facilities to MAVIR (Hungarian
Transmission System Operator Company Ltd.) on regular (monthly) basis where they are
recorded. Annual generation, fuel use data and efficiency calculations are reported yearly to
MEH.
29
Effects and impacts
The compulsory take-over and the related subsidy system in its current form have been in
place since the beginning of 2003. The achieved results are demonstrated in the following
diagram (value for 2010 is estimated).
Figure 3 Renewable power supplied to the grid
Figure 4 Share of renewable sources in power generation
The continuously increasing trend and the dominance of biomass are clearly visible. The
latter, however, may be somewhat less marked in the future as there are serious plans in the
NCsT to promote windpower.
From past experience it is apparent that subsidy through the compulsory take-over system is
the most effective promotional tool. Still, the quantitative effect of this policy cannot be
30
separated from that of other policies of renewable promotion. The effect of all the renewable
promotional policies may be estimated on the basis of the forecast green power production
figures in the NCsT until 2020, and extrapolating the trends of the last 3 years of the forecast
to 2025. Thus the following green power generation figures are obtained:
Table 8 RES-E generation, GWh
2010
2015
2020
2025
Hydro power
194
196
237
275
Solid biomass
1 870
1 988
2 688
3334
Biogas
85
262
636
983
Windpower
692
1 377
1 545
1697
Geothermal
0
29
410
410
Solar PV
2
26
81
148
Total
2 843
3 878
5 597
6 847
The GHG emission reduction is calculated from these figures from the modelled forecast
BAU power generation mix. The forecast mitigation effect of all the renewable power
promotion policies, of which the currently discussed compulsory take-over system is decisive,
thus is the following.
Table 9 GHG reduction effect of all the renewable power promotion policies
2010
2015
2020
2025
2.3
3.2
4.6
5.6
II.3.2.2. Direct financial support for renewable projects
In line with the objectives and foreseen tools of the NCsT, direct financial supporting
schemes are provided to help realise renewable projects. Currently, i.e. before a dedicated
operative programme (see the details of the NCsT in section II.3.1.3 ) is launched for this
purpose, these supports are provided through various existing operative programmes.
The subsidies provided through the operative programmes (unlike the KÁT) –, which
improve the financial viability of renewable projects by boosting the cashflow –, provide
assistance upfront during the project development, investment and construction phase.
The support system has been in place for years now with slightly shifting emphasis according
to the actual energy policy priorities. In line with the forming Energy Strategy priorities and
the objectives of the NCsT, the most recent (2011) subsidies focus more on heating and
cooling based on renewables.
31
The individual support schemes and their key elements are briefly described below3:
Development of building energy systems in combination with renewable energy utilization
(KEOP-2011-4.9.0)
The subsidy scheme supports the construction or implementation of concrete energy
efficiency and renewable projects (combination of the two is preferred) of SME and public
institutions. The 10-85% of the total project cost can be received as a grant for the following
project types:

Improvement of thermal performance of buildings, reduction of heat losses,
including external insulation, replacement of doors and windows, installation of
heat recovery for the ventilation systems.

Modernisation of the heating, cooling and DHW supply systems in public
institutions and SME including the following:
o
o
o
o
o
o
o
o
Replacement of boilers with high efficiency equipment.
Automatic heating control systems.
Control system of heating and DHW systems, individual metering.
Energy saving measures in cooling systems.
Small scale local cogeneration or trigeneration.
Waste heat recovery.
Conversion of heat distribution systems from steam to hot water.
Hooking up to district heating systems.

Modernisation of lighting systems. Including replacement of light sources and
ballasts and better control of lighting.

Utilisation of renewable energies, including:
o Solar collectors for DHW generation and/or heating.
o Biomass for DHW generation and/or heating.
o Utilisation of geothermal energy.
o Heat pumps for DHW or heating.
o Solar PV panels for power generation mainly for local use.
Altogether HUF 8 billion is available within the framework of this support scheme for the
period between 2011-2013.
Renewable based power or CHP generation, bio-methane production. (KEOP-2011-4.4.0)
This support scheme provides HUF 23 billion for 2007-2013 in order to assist the
implementation of renewable power generation projects. Subsidies between one million and
3
The codes of the individual support schemes are given in brackets to assist identification
32
one billion HUF may be obtained which is to correspond to 10-85% of the total project cost
depending on who the applicant is and where within the country the project is implemented.
SME, entities of the public administration and non-profit organisations may apply for the
support. The following project types are eligible:

Solar PV systems (smaller than 500 kW if connected to the grid, no capacity
limitations if autonomous).

Biomass based combined heat and power generation.
o Solid biomass based new CHP capacities with high efficiency max.
20 MW capacity.
o Conversion of solid or liquid biomass to fuel such as ethanol, diesel oil and
its use for combined heated power generation.

Hydropower projects: construction or revamping of max. 2 MW hydropower
plants.

Biogas generation and utilisation
o from agricultural products or by-products
o from waste water
o from landfills.

Utilisation of geothermal energy for power generation or CHP.

Wind power projects:
o Max. 50 kW capacity wind power projects if connected to the grid.
o Any wind power plants if not connected to the grid.
Supplying local heat and power demands from renewable energy sources (KEOP-20114.2.0-A and KEOP-2011-4.2.0-B)
The purpose of the support scheme is to promote local, decentralised renewable-based energy
supply systems by providing grant funds in the value of HUF 1 million-1 billion,
corresponding to 10-85% of the project cost. The support is available for enterprises, public
institutions and non-profit organizations. Altogether HUF 19.67 billion is allocated for this
purpose for the period between 2007 and 2013. The supported project types are the following:

Solar collectors to supply heat demands

Solid or liquid biomass to supply heat demands including space heating, DHW
generation or direct heat demands of economic activities.)

Conversion of solid or liquid biomass to fuels to cover local (own) heat demands.

Biogas production from solid or liquid biomass and landfill gas collection to cover
local (own) heat demands.

Utilisation of geothermal energy (new production or reinjection wells or
revamping existing systems)

Heat pumps (meeting minimum efficiency criterion is required)
33

Renewable based cooling.

New renewable based district heating systems, or conversion of existing DH
systems to renewable energy
Renewable energy based regional development (KEOP-2011-4.3.0)
This subsidy scheme supports the implementation of renewable-based model projects that
have marked regional development impacts. Altogether HUF 6 billion is allocated for this
purpose between 2007 and 2013. Grants between HUF 70 million and 1.5 billion are
available. A wide range of renewable-based technologies can be supported including solar,
biomass hydro, biogas, geothermal – the scope is practically the same as with KEOP-20114.2.0-A and KEOP-2011-4.2.0-B. However, it is a precondition that the project would
demonstrate at least one of the following regional development impacts:

Increasing employment, job creation

Apparent increase of local income level

Resolving a local environmental problem (such as utilisation of wastes for energy
generation, landscape rehabilitation by utilising forestry by-products)

Improvement of the quality of life in socially challenged regions

Utilisation of local geographical or other endowments

Reinforcement of local community, creating community targets.
Increasing utilisation of renewable energies in Central Hungary (KMOP-3.3.3.-11)
The objective and scope of this support scheme is practically the same as those of KEOP2011-4.2.0-A and KEOP-2011-4.2.0-B, but due to administrative reasons a separate operative
programme is operated for Central Hungary, hence the support for renewables in this region
also appears separately. The total sum allocated for this purpose for 2011-13 is HUF 1 billion,
the grant available for the individual projects may range between HUF 3-100 million,
corresponding to 10-90% of the total cost.
Support for the preparation and development of geothermal heat and power projects
(KEOP-2011-4.7.0)
This support scheme addresses one of the bottlenecks of renewable projects: these projects are
often initiated by local entrepreneurs or communities lacking expertise and finance to
properly design, develop and prepare the project, which may well be a tedious and costly
process. The support is available for enterprises and public institutions, the total allocated
amount is HUF 3 billion for 2007-2013, of which 1.62 billion is still available.
The key parameters of the individual support schemes are summarised in the following table:
34
Table 10 The key parameters of the individual support schemes
Support scheme
Allocated amount
(timeframe)
Support available
per project
Support as % of project
cost
KEOP-2011-4.9.0
(Building EE plus renewable energy
utilization)
HUF 8 billion
(2011-2013)
HUF 1-250
million
10-85%
KEOP-2011-4.4.0
(Renewable power/CHP, bio-methane
production)
HUF 23 billion
(2007-2013)
HUF 1-1000
million
10-85%
KEOP-2011-4.2.0-A and KEOP-20114.2.0-B
(Renewable local heat and power )
HUF 19.67 billion
(2007-2013)
HUF 1-1000
million
10-85%
KEOP-2011-4.3.0
(Renewable energy based regional
development)
HUF 6 billion
(2007-2013)
HUF 70-1500
million
10-90%
KMOP-3.3.3.-1
(Renewable energies in Central
Hungary)
HUF 1 billion
(2011-2013)
HUF 3-100
million
10-90%
KEOP-2011-4.7.0
(geothermal heat and power project
development)
HUF 3 billion
(2007-2013)
HUF 3-100
million
10-90%
Economic
Implemented
Monitoring is through the following indicators:
 amount of subsidy used
 renewable energy used (where applicable);
 quantity of generated heat/electric power;
 calculated emission reduction.
The agency responsible for managing the support schemes maintains a monitoring unit, which
evaluates the annual performance reports submitted by the beneficiaries.
Effects and impacts
35
According to the accounts of the agency managing the subsidy schemes, there is large and
constantly growing interest on behalf of the potential beneficiaries. As of early 2010, the
number of applications was much larger than before, the demand for support was more than
2.5 times higher than the total support provided in 2007-2009. The interest towards
renewables was remarkably higher than earlier and also higher than for energy efficiency
improvement supports.
The share of the individual project types as of early 2010 was the following.
Figure 5 Distribution of supported renewable projects by the type of energy
It is clear that the support system strongly contributes to achieving the targets set in the NCsT.
As said in the previous point, it is not possible to estimate the projected emission savings
separately for the individual tools, they are included in the projection in point II.3.2.
II.3.2.3. Support for planting energy crops and forests
The general objective of the policy is to help overcome the difficulties of switching from
traditional farming to the cultivation of energy plantations, and so partly ensure the
maintenance of farming especially in backward regions, create or keep jobs and to provide
safe and reliable fuel supply for renewable energy utilisation projects. The specific objectives
include:
 ensure farming alternatives that can match local conditions;
 reduce the damages caused by wind and water erosion of soils;
 reduce the burden on natural forests that is due to the extensive use of biomass for
energy purposes;
 improve the standard of living in rural areas
 by providing fuel to contribute to the increase of renewable utilisation.
36
Two consecutive decrees of the Minister for Agriculture - 71/2007. (VII. 27.) and 72/2007.
(VII. 27.) - regulate the subsidy for creating new energy crop or energy forest plantations.
For herbaceous species and plantations the subsidy available for farmers is maximum EUR
735 thousand, but shall not exceed 40% of the project cost. Young farmers and backward
regions have preferential conditions. In such cases the subsidy may be 50% or even 60% of
the project costs. Also plant-specific subsidy limits expressed in HUF/ha apply.
In order to ensure longer term effects, efficiency, sustainability and careful use of funds,
several conditions apply, too, such as:
 Only lands larger than 1 ha are eligible and the minimum land size is also limited
through other criteria (EUME);
 Proper technology shall be used to prevent spontaneous proliferation of the species;
 For at least 5 years the plantation shall be maintained;
 Minimum density of plants on the area shall be adhered to.
In the evaluation of the applications for support it is considered a serious advantage if the
product of the energy plantation is used or processed by the farmer himself, such as for
supplying energy demands or pellet/briquette production.
Very similar conditions apply for wood-type energy plantations. The upper limit of support is
also maximum EUR 735 thousand, and 40-60% of the total project cost may be applied for.
However, the grant shall not exceed HUF 160,000/ha for locust and HUF 200,000/ha in case
of other species.
Economic
Implemented
The efficiency of the policy can be monitored by the area of new and existing plantations.
Effects and impacts
According to data of MGSzH (Central Agricultural Office – responsible for licensing and
monitoring the plantations) by June, 2009 altogether 2665 ha was licensed for plantation of
wood-type energy plants, 1505 ha of which was actually planted. The majority of the species
used was poplar, willow and locust playing a lesser part. By September 2010 altogether
6456 ha were awarded plantation support for fast growing species, as shown in the following
table.
37
Table 11 Awarded plantation support for fast growing species by September 2010
County
Poplar
Locust
Willow
Total
15
15
Bács-Kiskun
Baranya
1535
440
1975
Borsod-Abaúj-Zemplén
13
85
98
Budapest
341
167
401
909
Hajdú Bihar
168
446
631
1245
Heves
58
13
71
Somogy
1629
54
1683
Vas
174
Veszprém
18
192
178
178
90
Zala
35
55
Total
3953
864
1639
6456
Even if the absolute value of the area is not very large, the growth is apparent: it more than
doubled within one year. Forecasts of the MEH calculate with 100,000 ha of energy
plantations by 2020 in the base case, but the scenarios included more ambitious figures.
The GHG mitigation effect of the policy is indirect, it can only be assumed on the basis of
typical yield of the areas. The following projected savings due to the increase of fast growing
species are based on the following assumptions:
 The shares of various species are: poplar 60%; locust: 15%, willow: 25%
 The increase of areas is as indicated in the table (based on the MEH study,
extrapolated)
 The energy plants will replace natural gas firing, combustion efficiency is the same.
 100% of the production of the energy plantations is used within Hungary.
Table 12 GHG mitigation effect of planting energy crops and forests
2010
2015
2020
2025
Total area of plantations
6500
25,000
100,000
120,000
Produced energy, PJ
1.57
6.04
24.15
28.98
Emission reduction, Mt CO2eq/year
0.088
0.339
1.355
1. 626
II.3.3. Support for combined heat and power generation
As discussed in the previous biennial reports, a similar support system to that of the
renewable based power (see section II.3.2.1) has been in place in Hungary for co-generated
power since 2003, regulated first by the Decree of the Minister for the Economy
56/2002(XII.29) GKM, later by Governmental Decree 389/2007. (XII. 23.). This policy
promoted combined heat and power (CHP) also by:
38
• stipulating the mandatory purchase of co-generated electric power
• providing financial support for the operators of CHP plants in the form of regulated
and subsidised feed-in tariff.
Already at the outset the policy was designed to last for a limited period: the decree
56/2002(XII.29) GKM included a clause stating that the decree will cease to be effective as of
31st December, 2010. Already in 2006, the evaluation of the policy showed that the increase
of small-scale capacities was somewhat faster and larger than expected and desirable, leading
to higher burdens on the power consumers4 and problems in system control. (See Hungary‘s
Biennial Report of 2007) Therefore some reductions of subsidies were introduced limiting
further growth.
The policy now is considered to have achieved its goals and in order to avoid further increase
of general electricity prices and burdens of the consumers, further subsidies are not provided.
The exact details and possible retention of some of the subsidies are being discussed between
the relevant governmental institutions and the professional public. Results are expected by
mid 2011.
The key stipulation of the currently effective legislation (February, 2011) is that compulsory
take-over and subsidised tariff only applies if
• the plant came on-line (started commercial operation) before 31st December, 2010 and
• smaller than 20 MW or
• the heat co-generated with electric power is used in a district heating system or
• the heat co-generated with electric power is used in a special institution (governmental
or municipal buildings, public and non-profit organizations)
Regulatory, economic
Implemented (for the capacities that meet the above criteria)
Repealed (for other capacities)
Quantity of electric power feed in to the grid (kWh)
Effects and impacts
The safe market of compulsory take-over of generated power at subsidised prices triggered a
steady increase in the quantity of generated power, as shown in the following chart. The chart
4
The subsidy is indirectly covered by a component of the general electricity tariffs
39
shows the quantity of not subsidised co-generated power (large power stations – the trend is
practically steady) and also the subsidised co-gen power, which almost tripled in six years
owing to the policy (data for 2009 non-subsidised power is not available).
Figure 6 The total co-generated power in Hungary 2003-2009
Source: KPMG (2010)
The achieved emission reduction through the policy, as compared to a baseline scenario when
the cogenerated power would have been produced by all the other capacities in the Hungarian
energy system, is shown in the following chart.
Figure 7 The total emission of power generation and the emission savings achieved by CHP as calculated
by an independent consultant
Source: KPMG (2010)
As far as future projections are concerned, the following factors shall be considered:
40
• The currently valid regulation not only stops the subsidies for future new plants, but
also for several existing capacities.
• Those capacities that lose the subsidies may either stop operation or may try to operate
in the free market, depending on their financial situation, debts, etc. In any case the
quantity of generated power will be lower.
• It is foreseen that subsidies will gradually further decrease. According to preliminary
information, KÁT subsidies for cogeneration will cease to exist after 2015. A
reasonable forecast for the quantity of KÁT-subsidised cogenerated power is
shown in the following chart.
Figure 8 Projected quantities of KÁT subsidised cogenerated power
Source: KPMG (2010)
• On the other hand other promotional tools for cogeneration are possible to be
introduced. Preferential taxation, preferential allocation of emission allowances,
revision of system-utilisation fees etc. are recommended by professional
organisations. The declared target is to at least maintain the achieved results.
• It may be assumed that the non-subsidised portion of the cogenerated power, which
has always been generated and traded under free market conditions and has been
practically constant (see the figure above) will remain stable.
With the above considerations the projected emission reduction achieved is forecast as
follows.
41
Table 13 Projected emission reduction achieved by cogeneration plants
2010
2015
2020
2025
Total cogenerated power, TWh
9.1
7.2
6.8
6.8
Emission reduction achieved, Mt CO2/year
3.7
2.9
2.7
2.7
Subsidised cogenerated power, TWh
4.6
0.8
0.0
0.0
Emission reduction achieved, Mt CO2/year
1.8
0.3
0.0
0.0
II.3.4. Modernization of district heating systems
II.3.4.1. Subsidy for investment in energy modernisation of DH systems (KEOP-2011-5.4.0.)
District heating is an important sector of the Hungarian energy system, not only for its sheer
size (there are some 640.000 district heated homes and a large number of such public
institutions) but also due to its political importance: more than 2 million people of the 10million populace are affected. As shown in the previous Biennial Reports, policies for the
modernisation of DH systems have been in place for a long time. Still, most of the DH
systems of 92 cities in the country are more or less obsolete with substantial scope for
improvement.
In line with point 4.3.1.3 the NEEAP a support scheme is in place to help improving DH
systems.
The declared primary objectives of the policy are to save energy and thus both locally and on
national level to reduce GHG emissions via the improvement of heat generation and
distribution systems.
The policy provides grant money to finance energy saving or energy efficiency improvement
projects of DH companies in the range between HUF 10 and 500 million, which shall
correspond to 10-50% of the total project cost.
The following project types are eligible for the support.
 Waste heat recovery in the DH system
 Replacement/thermal insulation of primary supply pipe lines. Replacing overland
pipes to underground pipelines.
 Modernisation of DH substations, splitting large substations.
 Conversion to variable mass-flow rate control.
 Switching heat transfer medium (from steam to hot water)
 Recruiting new customers.
 CHP but only if the total generated power is used within the DH system.
 Heat storage systems, trigeneration.
 Replacement of electric chillers with district heat operated chillers (district cooling)
42
The total funds allocated for this purpose for 2007-2013 amount to HUF 5.44 billion, 2.08
billion of which is still available.
Economic
Implemented
Calculated energy saving achieved
Effects and impacts
The energy savings objective set in the NEEAP for DH modernisation is 2 PJ/year by 2016,
with an additional 0.1-0.3 PJ increase of savings every year. In projecting the GHG emission
savings, the following assumptions are considered:
 In Hungary practically all district heat is generated from natural gas. (More than 98%
according to 2006 statistical data). Thus it is reasonable to calculate the emissions and
emission reduction on pure natural gas basis, assuming 90% plant efficiency.
 It is assumed that after 2016 the achievable savings are reduced, as the available good
projects will have been implemented by then (‗cream skimming‘). The absolute values
of savings will be also lower, as due to the intensives modernisation of buildings (see
the relevant PAMs in the current report) the heat demand will substantially reduce,
thus to achieve the same absolute savings requires more intensive efforts. In order to
account for this, the calculation assumes that from 2016 the annual increment of
savings will be reduced to the 2008 levels of the NEEAP.
Table 14 Projected emission reduction achieved by modernization of district heating systems
2010
2015
2020
2025
Emission reduction Mt CO2/year
0.011
0.022
0.014
0.004
Accumulated emission reduction Mt CO2/year
0.021
0.120
0.208
0.246
II.3.4.2. Individual measurement and control in district heating
Mainly due to technical reasons it is general in Hungarian district heating systems that heat
consumption is metered only in the substations of the buildings. This metering is the basis for
billing, and the related charge is split among the individual consumers (homes) in various
ways, not necessarily in proportion to their actual consumption. In many systems, also owing
to technical reasons it is still not possible to control the temperature (heat consumption)
individually.
43
It has been proven that individual control and correct, accurate metering of the heat
consumption of the homes when coupled with consumption-related cost allocation and billing
results in significant savings.
In order to facilitate the necessary technical changes financial support is provided for such
projects.
Such support has been available for some years now in various forms, from various budgets.
The current scheme is named ―ÖKO-Program‖ which provides maximum 50% of the project
cost with an upper limit of HUF 77,000/flat. The supported interventions are the following:
 Installation of equipment for individual temperature control (thermostatic valves,
thermostats, room thermostats)
 Installation of individual metering equipment (heat meters or electronic cost
allocators)
 Conversion of the heat distribution system in the buildings (flow controllers, radiator
bypass lines in single pipe systems, new double-pipe systems)
It is foreseen that the support system will remain in place.
Economic
Implemented
 Number of projects
 Calculated energy saving
Effects and impacts
In 2009 altogether 297 projects were supported with the total amount of HUF 1.17 billion.
Based on the projected energy savings of the NEEAP, which takes into account the expected
effects of both the implemented and planned support schemes, the following effects are
projected:
Table 15 Projected emission reduction achieved by individual measurement and control in district heating
2010
2015
2020
2025
Change in energy saving PJ/year
0.15
0.17
0.11
0.00
Accumulated energy saving PJ/year
0.15
1.24
1.81
2.04
Change in emission reduction M tCO2/year
0.011
0.012
0.008
0.000
Accumulated emission reduction M tCO2/year
0.011
0.088
0.128
0.144
44
II.3.5. Nuclear power
II.3.5.1. Lifetime extension and capacity increase of the Paks nuclear plant
Hungary is operating four VVER-440 type pressurised water nuclear reactors in the Paks
nuclear power plant (Paks NPP). These were commissioned between 1982 and 1987, with a
planned technical lifetime of 30 years. Already at the end of the 1990s it was recognised that
the operation and preferably the increase of the capacity of the Paks NPP is crucial for the
safety of electric power supply of the country and also for limiting GHG emissions. Therefore
first the increase of the capacity of the units of the plant from 440 MW to 500 MW was
decided, then a decision on the extension of the technical lifetime of the plant (Resolution of
the Parliament 85/2005. (XI. 23.)) was made. The measures were implemented gradually,
according to the time schedule shown in the following table.
Table 16 Lifetime extension and capacity increase of the Paks nuclear plant
Unit start
operation
End of original
lifetime
500 MW capacity
on-line
End of extended
lifetime
Unit 1
14 Dec. 1982
2012
19 Jul. 2007
2032
Unit 2
26 Aug. 1984
2014
05 Dec. 2008
2034
Unit 3
15 Sep. 1986
2016
13 Nov. 2009
2036
Unit 4
09 Aug. 1987
2017
28 Sep. 2006
2037
Other: technical
Capacity increase: Implemented
Lifetime extension: Planned
In more details, as shown in the previous table the capacity increase of the last unit (Unit 3)
was finished in 2009. The lifetime extension is a long, tedious process, with the following
main stages:
 Feasibility study (Finished in 2002)
 Environmental licensing (finished in 2008)
 Development of the implementation program (finished in 2008)
 Checking of the program by the authorities (currently under way)
 Implementing the program (currently under way)
 Operation according to the new license for the extended lifetime (planned from 2012)
45
Quantity of electric power generated
Effects and impacts
The operation of the nuclear plant obviously substitutes fossil fired power generation
capacities, with zero GHG emission technology. The emission savings can be calculated if the
actual/planned situation is compared to a baseline, which, in this case is a scenario without the
capacity increase and lifetime extension (i.e. the original 440 MW capacities would be
available until the end of their original planned technical lifetime). In calculating the emission
reduction due to these measures, the following assumptions were considered:
 Only the exported power of the Paks NPP is calculated with, rather than the total
generated power in order to exclude the own consumption of the plant.
 In order to be conservative, it is assumed that in lack of nuclear power the same
quantity of power would be generated in a modern natural gas fired combined cycle
plant with an efficiency of 52%.
 Similar stable operation, own consumption figures and utilisation factors are assumed
as were actually measured between 2005 and 2009.
Table 17 Projected emission reduction achieved by lifetime extension and capacity increase of the Paks
nuclear plant
2010
2015
2020
2025
Emission reduction Mt, CO2/year
0.65
3.05
5.46
5.44
Accumulated emission reduction from 2005, Mt CO2
2.78
11.31
35.79
63.02
II.3.5.2. New nuclear units in the Paks NPP
Several energy policy considerations, such as security of supply, concerns regarding heavy
import dependence and the dominance of natural gas in energy supply, GHG emission
mitigation necessitated that the construction of new nuclear capacities would be considered.
After lengthy project development work, feasibility studies carried out by Paks NPP (Teller
project) the Parliament passed their resolution 25/2009. (IV. 2.), in which they approved the
starting of concrete preparation of constructing nuclear new unit(s). Based on this
authorisation, the concrete project development activities (licensing, tenders) have started
(Lévai project) and are still under way.
According to the latest plans it seems that two new units (Paks-5 and Paks-6) would be
constructed. The planned dates of the start of commercial operation are 2025 and 2030 for
Paks-5 and Paks-6, respectively.
The actual size of the two units is not yet determined, various options are being investigated.
The most likely size is 2x1000-1200 MW.
46
Other: technical
Planned
Quantity of electric power generated
Effects and impacts
As the time-span investigated in the current report is until 2025, conservatively assuming that
the foreseen commissioning dates of the new units are at the end of the years stated, only
Paks-5 can have an impact.
Assuming the similar baseline as in the previous point (no new nuclear units are constructed)
and similar utilisation and own consumption figures, a new 1000 MW unit coming on-line at
the end of 2020, would export around 7000 GWh electric power to the grid a year. Thus if
compared to a baseline when the same quantity of power is generated in a modern natural gas
fired combined cycle plant, the projected emission savings are the following.
Table 18 Projected emission reduction achieved by new nuclear units in the Paks NPP
2010
2015
2020
2025
0
0
0
2.72
II.3.6. Emission Trading System in the energy industry
Hungary, as an Annex I Party to the Kyoto Protocol, in accordance with Directive
2003/87/EC of the European Parliament, has been operating the Emission Trading Scheme
(ETS) since 2005. The legal background for the ETS is provided by Act LX of 2007 on the
implementation framework for the United Nations Framework Convention on Climate
Change and its Kyoto Protocol, whereas the organisation and operation of the ETS is
regulated by the amended Act XV of 2005 on the trading with emission units of greenhouse
gases.
The ETS is the key instrument in compelling the large energy consumers of the economy,
including the power sector and the industry to make efforts to mitigate their GHG emissions,
especially since the beginning of the second trading period, 2008.
Regulatory/Economic
47
Implemented
 Verified GHG emissions
 Power generation data
Effects and impacts
In the first trading period between 2005-2007 30.2 million tons CO2eq allowances amounting
to were allocated altogether, whereas the actual emissions were round 26 million tons.
Therefore, although the operation of the ETS certainly had awareness raising effect, it did not
impose a real urging need for GHG mitigation on the companies within the system. On the
contrary, it created an opportunity to generate some extra revenues from the trading of
emission allowances. This was similar in many other EU countries, therefore the price of
emission allowance significantly decreased in the international markets.
The situation has changed in the second trading period, from 2008. Then the original national
allocation plan included much lower amounts of emission allowances, but it was further
reduced by the decision of the European Commission of 17. April, 2007, which found that
some 3.8 million units to be allocated were not justified. Thus finally the total amount of
allowances allocated for 2008, the first year of the second trading period, was 25.044 million
tons. The verified emissions of the companies subject to ETS in the same year were 27.25
million tons, which shows that some 9% of the total allowance had to be procured on the
market, this providing ample incentive for GHG reduction measures. In the next trading
period, from 2013 further severe cuts in the quantity of available allowances are expected,
considering that the current plans will limit the total EU-ETS emission to 2.039 billion tons,
which would be reduced by 1.74% of the 2008-2012 average emission every year. Besides,
the auctioning of allowances will become general and mandatory from 2013. These measures
will create a very strong incentive for emission reduction measures.
The results of the policy so far cannot be directly detected if the emission values of the
industry are considered only, as the power demand of the county and therefore the amount of
generated power increased. Instead, the effects of efforts by the companies of the energy
industry (fossil fired power stations) to improve their efficiency can be well tracked if the
specific fossil fuel consumption normalised to power generation is examined. This is shown
in the following chart.
48
Figure 9: Specific fuel consumption of Hungarian fossil-based power generation
Although the improvement is clearly not entirely attributable to the ETS system only, as other
factors, such as fuel prices also have considerable influence, and awareness raising and
financial constrains from the ETS certainly played an important role.
Although projections for the energy industry overall emissions were made, it is not possible to
quantify the effect of the ETS system separately, exactly because of the complexity of the
calculation, the results of which are influenced by fuel prices, foreseen fuel mix and plant
efficiencies (decommissioning of old and construction of new plants) among several other
factors.
II.3.7. Energy performance and efficiency of buildings
II.3.7.1. Regulation on the energy performance of buildings
The energy performance of buildings is currently regulated by Decree 7/2006 (V. 24.). In the
decree both the methodology of evaluation (thermal calculations) and some key parameters
(e.g. U-values and normalised heat loss) of buildings and their structural elements are
prescribed. Meeting these prescribed values are the precondition for the issuance of licences
for construction or major refurbishment of buildings. As shown in the earlier Biennial
Reports, the decree already had considerable emission reduction effect.
The decree, however, was issued in 2006, and especially in the light of the new Directive
2010/31/EU of the European Parliament and of the Council, it is rather obsolete. Therefore, in
order to fully comply with the Directive by 2020, the Decree is being reconsidered. Although,
not officially approved yet, a gradual compliance plan is being discussed by the professional
public, suggested by the Chamber of Hungarian Engineers and the Chamber of Hungarian
Architects.
49
According to the plan, the compulsory values of the various energy performance parameters
will become stricter gradually, in 2012, 2015 and in 2019. In order to demonstrate the
foreseen progress, the suggested values of the U-value of some building structures are quoted
here.
Table 19 Suggested U-values of some building structures, W/m2K
2012
2015
2019
External walls
0.30
0.26
0.22
Glazing
1.10
1.00
0.80
Glazed window (wood or plastic frames)
1.30
1.15
1.00
The regulation is to become also stricter in relation to the regular inspection of HVAC
equipment, certification process, and the overall energy performance. As to the latter, in line
with the Directive, it is foreseen that all newly constructed public buildings after 31
December, 2018, and all other new buildings after 31 December, 2020 will have to be zero
energy buildings.
Regulatory
Implemented (the existing regulation)
Planned (the future changes)
 Number of issued building energy certificates.
 Number / heated volume of new or reconstructed housing.
Effects and impacts
The effects and impacts of the planned measure can be calculated on the basis of the structure
and number of the Hungarian building stock, the number of construction licences issued
annually and on the basis of typical building types. The calculated energy savings and the
related GHG emission reduction are the following.
Table 20 Projected emission reduction achieved by Regulation on the energy performance of buildings
2010
2015
2020
2025
0.63
0.91
1.2
1.2
0.63
4.62
10.02
16.02
Change in emission reduction Mt CO2/year
0.032
0.046
0.061
0.061
0.032
0.235
0.510
0.815
50
II.3.7.2. Energy certification of buildings
Further to the Directive 2002/91/EC, since 1 January, 2009, the system of energy certification
of buildings is effective in Hungary, as governed by Governmental Decree 176/2008.Korm.
Energy certification is compulsory for all buildings if larger than 50 m2, used more than 4
months a year, designed for more than 2 years of use, not protected (historical buildings), not
meant for agricultural or workshop use, or if internal heat gains are lower than 20 W/m3.
Churches are exempt. The energy certificate is necessary for the newly constructed buildings,
buildings sold or let for more than one year and all government buildings bigger than 1000
m2. The certificate does not only include the classification of the building, but if it is not at
least class ―C‖5, it shall include recommendations as to how the energy efficiency of the
building should be improved.
Regulatory
Implemented
None
Effects and impacts
The energy certificates provide effective and fast information on the energy performance of
buildings, and thus are expected to influence the market value of buildings, and so shifting the
preference of buyers and owners of new buildings or homes to more energy efficient
structures. In the long run this influences the design of new buildings and considerably
increases awareness.
Based on the estimates of the NEEAP the effects are projected as follows.
Table 21 Projected emission reduction achieved by energy certification of buildings
5
2010
2015
2020
2025
0.12
0.12
0.12
0.12
0.12
0.72
1.32
1.92
0.006
0.006
0.006
0.006
0.006
0.037
0.067
0.098
The overall combined energy consumption is at least 96-100% of the reference value (requirement)
51
II.3.7.3. Subsidy for energy efficiency improvement projects
Direct subsidy for improving energy efficiency of households and public buildings has been a
well proven GHG mitigation policy for years, since the early 2000s. Detailed account on the
content, structure and funding of the earlier support schemes (SZT-EN, NEP) was given in the
earlier Biennial Reports. Although the supported project types and the conditions of support
changed from year to year, the main focus remained the same. Typical target areas of support
were: replacement of doors and windows; external insulation; modernisation of heating and
DHW systems. The form of support was typically grant, but often preferential loan schemes
were operated, such as the ―For a Successful Hungary‖ Residential Energy Saving Loan in
2007.
Until 2011 the two following support schemes were in place:
ZBR Climate Friendly Home Energy Efficiency Programme (ZBR-EH-09)
The primary objective if the programme is climate protection. The programme supports
energy efficient refurbishment of traditional buildings, resulting in GHG emission mitigation.
The following project types are supported:
 Refurbishment or replacement of windows if proper individual heating controls are
already in place or is simultaneously installed;
 Passive solar energy utilisation;
 Passive cooling solutions (sun shades);
 Heat recovery in ventilation systems;
 Thermal insulation of building envelope if proper individual heating controls are
already in place or are simultaneously installed;
 Modernisation of heating and DHW systems, energy efficient boilers;
 Utilisation of renewable energy sources
 Construction of new, highly energy efficient homes.
The precondition of the support is that the energy efficiency class of homes (as per the
certification system, see point II.3.7.2) would improve by one category. In this case 30% of
the total project cost can be awarded as grant, with an upper limit between HUF 540,000 and
HUF 1,450,000, depending on project type. If the energy efficiency class of homes reaches at
least class ―B‖ as a result of the project, an additional ―Climate bonus‖ can be granted ranging
between HUF 200,000 and 1,000,000, depending on the energy efficiency class reached. The
maximum support for new energy efficient buildings is HUF 3.25 million and no homes
larger than 130 m2 can be supported.
ZBR Climate Friendly Home Panel Sub-programme
52
A large part of the Hungarian building stock is pre-fab buildings (commonly called as panel
buildings) and due to social considerations they receive special attention. The possible energy
efficiency measures are technically similar, too. Therefore a dedicated sub-programme is
created for the energy efficiency improvement of such buildings. Any project can be
supported provided that it can be proven that GHG emission reduction is achieved by it and
the energy efficiency improvement can be verified. The following project types are supported:
 Energy efficient refurbishment or replacement of windows;
 Thermal insulation of building envelope
 Modernisation of HVAV systems and electrical equipment (elevators)
 Utilisation of renewable energy sources
 Passive solar energy utilisation;
33% of the project cost, maximum of HUF 500,000 can be awarded as grant. Here a Climate
Bonus can also be applied if the conditions similar to those at the other ZBR Programme are
met.
The source of funding of both programmes is the Green Investment Scheme (ZBR).
According to the NEEAP, the two schemes will be continued and further supports will be
made available with similar objectives. Recent communication from the relevant authorities
confirmed it, although the content of the support schemes will be re-shaped: more intensive
complex modernisation (―in-depth‖ revamp) will be given preference.
Economic
Implemented/Planned
 Calculated emission reduction
Effects and impacts
The two ZBR programmes described above were first made available for applications in July
2009.
In the first stage, between July and December, 2009, almost one thousand (precisely 966)
applications for the ZBR Panel programme were accepted and a total grant of HUF 15.2
billion was allocated. It may be interesting that the majority of the projects were complex
interventions, combining at least two but more likely three of the supportable project types.
53
The shares of the various project types in terms of grant money and the number of projects are
shown in the charts.
Figure 10 Project types of the ZBR Panel Program
projected.
Table 22 Projected emission reduction achieved by Subsidy for energy efficiency improvement projects
2010
2015
2020
2025
0.36
2.87
2.11
2.46
0.36
11.09
22.43
34.03
0.018
0.146
0.107
0.125
0.018
0.564
1.142
1.732
II.3.8. Improvement of energy efficiency in households
II.3.8.1. Minimum efficiency criteria for household boilers and air conditioning equipment
The relevant regulation (7/2006.TNM, see point II.3.7.1) already defines minimum
requirements for the energy performance of buildings, of which the parameters of household
boilers are a very important component. The Governmental Decree on the regular inspection
54
of heat generation and air-conditioning equipment (264/2008. (XI. 6.)) creates the legal
background to find and replace old, inefficient equipment. Already some financial support is
available for projects that include the replacement of boilers (e.g. KEOP-2011-4.9.0 for public
institutions and the ZBR Climate Friendly Home Program for households) are in place which
are planned to be continued, but other tools to assist such projects are considered.
Regulatory/Economic
Implemented/Planned
It is noted here that only those effects can be monitored directly which are linked to projects
that are supported by some central schemes. The ―spontaneous‖ replacement of equipment
which results from the regulation (regular inspection) and financed by the equipment owners
themselves, cannot be monitored.
Effects and impacts
projected.
Table 23 Projected emission reduction achieved by minimum efficiency criteria for household boilers and
air conditioning equipment
2010
2015
2020
2025
0.051
0.099
0.058
0.000
0.096
0.551
0.944
1.060
0.004
0.007
0.004
0.000
0.007
0.040
0.069
0.078
II.3.8.2. Support for the procurement of highly efficient refrigerators and freezers, other
appliances
Surveys and studies confirm that more than 90% of the Hungarian households use
refrigerators and there are also freezers in around 60% of them. Due to their consumption
pattern these appliances are responsible for a large percentage of the household electric power
consumption. It is also suggested by the studies that a considerable part of the
refrigerators/freezers are rather old, not properly insulated and inefficient.
55
The situation is similar in case of washing machines, which are among the largest power
consumers in the households.
Financial support can considerably accelerate the replacement process of the inefficient
equipments, and it can also influence customer decision to buy more efficient (although more
expensive) appliances.
In the framework of the ZBR Energy Efficient Household Appliance Replacement Program,
subsidy is provided for the procurement of highly efficient refrigerators, freezers and washing
machines. The procurement of appliances with energy class ―A‖, ―A+‖ and ―A++‖ is supported.
The policy also includes some social considerations, as the support is provided through
foundations/organisations caring for large families, the elderly, the disabled and the
unemployed.
The value of the grant is HUF 60,000 and HUF 70,000 for refrigerators and washing
machines, respectively. The subsidy provided through one organisation is limited to
HUF 10 million.
Economic
Implemented
 Number of applications
 Number of appliances
Effects and impacts
In 2010 195 applications for the support were approved, an altogether HUF 1 billion was
granted to 11686 families. The expected effects of the policy in the long run are the following.
56
Table 24 Projected emission reduction achieved by support for the procurement of highly efficient
refrigerators and freezers, other appliances
2010
2015
2020
2025
0.039
0.076
0.045
0.000
0.074
0.424
0.726
0.815
0.009
0.017
0.010
0.000
0.017
0.097
0.166
0.187
II.3.8.3. Promotion of CFLs and other efficient lighting equipment
According to studies and surveys, still more than 95% of household lighting is by
incandescent light bulbs in Hungary. Lighting, on the other hand, is a significant part (some 810%) of household electric power consumption.
Although the Commission Regulation 244/2009 will eventually phase out incandescent and
other inefficient lighting by 2016, full success for quite some time is not expected, partly
because consumers are likely to stock the inefficient, but cheap bulbs, partly because the
black-market sale of the cheap bulbs imported from non-EU countries is still going on.
In order to improve the competitiveness of CFLs and other efficient lighting, to accelerate the
replacement of inefficient lights and also in order to improve public awareness and experience
with the novel technology, a subsidy programme is in place.
ZBR Energy Efficient Light Replacement Sub-programme, launched in 2010, provides grant
funding for the procurement of energy efficient lights. Similarly to the support for energy
efficient household appliances (see II.3.8.2) the subsidy is provided for special target groups
(large families, the elderly and the disabled) through their social organisations.
The amount of the grant is HUF 40,000 per family, but the total amount is limited to HUF 150
million per target group, and to HUF 10.million per organisation. The total amount allocated
for the purpose in 2010 was HUF 450 million.
Economic
Implemented
 Number of applications
57
Effects and impacts
The expected effects of the policy in the long run are the following.
Table 25 Projected emission reduction achieved by promotion of CFLs and other efficient lighting
equipment
2010
2015
2020
2025
0.201
0.392
0.392
0.000
0.381
2.178
4.137
4.921
0.046
0.090
0.090
0.000
0.087
0.499
0.947
1.126
II.3.9. Improvement of energy efficiency in governmental and public institutions
II.3.9.1. Promoting third party financing
The basic aim of the policy is to improve the energy efficiency in institutions of public
organisations, churches and foundations and thus contribute to GHG emissions. It is common
experience, however, that such organisations lack technical expertise and have no funding
available for implementing energy efficiency improvement projects. In this respect third party
financing and ESCOs can play a crucial role to make such projects happen in the institutions
of the target group of the policy.
In the framework of the policy support is provided for the implementation of energy
efficiency projects which are typically not sufficiently attractive under the Hungarian
economic conditions. In order to ensure professional project development and management
the support is provided through the ESCO.
Such policy has been in place for some time now (see the previous Biennial Reports) and
according to the NEEAP it is to be continued.
Economic
Implemented
Effects and impacts
Based on the experience of past years the following effects are expected.
58
Table 26 Projected emission reduction achieved by promoting third party financing
2010
2015
2020
2025
0.550
0.550
0.550
0.550
1.650
4.400
7.150
9.900
Change in emission reduction M tCO2/year
0.044
0.044
0.044
0.044
Accumulated emission reduction M tCO2/year
0.133
0.356
0.578
0.800
II.3.9.2. Inclusion of EE promotion elements in the Regional Operative Programmes
Within the general development strategy of Hungary subsidiary – and within that the
involvement of the regions in the planning and implementation of sectoral programmes – as
well as a stronger regional planning and regional role is a key element. Therefore, in order to
strengthen the regional role, several development policies are implemented through Regional
Operative Programmes (ROP). The typical target groups of the ROPs are municipalities,
public institutions, churches and civil organisations. These ROPs therefore are important tools
of allocating funding for projects that serve achieving strategic goals in the public sector.
Including EE promotion elements in the ROPs thus can play a special role not only in the
implementation of actual projects, but also in awareness raising by attaching EE elements to
other ROP priorities.
The ROPs designed for 2007-13 included support for the following project elements:
 reduction of energy use in public institutions
 modernisation of indoor and outdoor lighting systems
 improvement of thermal performance of buildings
 modernisation of secondary (demand-side) systems of energy supply
 reduction of energy use in street-lighting.
The support in the ROPs is maximum 90%, typically 30-50%.
Economic
Implemented
Effects and impacts
59
The following effects are projected.
Table 27 Projected emission reduction achieved by including EE promotion elements in the Regional
Operative Programmes
2010
2015
2020
2025
0.057
0.069
0.060
0.060
0.161
0.480
0.805
1.105
0.005
0.006
0.005
0.005
0.013
0.039
0.065
0.089
II.3.9.3. Including EE principles in public procurement procedures
As discussed in the chapter on the Programme of National Cooperation (II.1.1) greening of
public procurement is an important element of the overall strategy of the government. In line
with relevant European policy the idea was already part of the NEEAP. Therefore the
evaluation criteria of public procurement procedures shall include measurable, objective
environmental and/or energy efficiency criteria. The projects implemented in governmental
and municipal facilities and the consideration of related energy performance criteria of
buildings is of special importance in this regard.
The Governmental Decree 48/2011. (III. 30.) on the promotion of clean and energy-efficient
road transport vehicles was adopted in 2011 as a first step of the policy, although not yet
related to public institutions but rather to transport, in compliance with the Directive
2009/33/EC of the EU. This decree stipulates that the operators of public passenger transport
services by rail and by road shall take into account the operational lifetime energy and
environmental impacts (at least energy consumption, emissions of CO2, NOx and particulate
matter) when purchasing road transport vehicles.
Regulatory
Planned
None
Effects and impacts
The following effects are projected.
60
Table 28 Projected emission reduction achieved by including EE principles in public procurement
procedures
2010
2015
2020
2025
0.000
0.500
0.500
0.500
0.000
2.000
4.500
7.000
0.000
0.040
0.040
0.040
0.000
0.162
0.364
0.566
II.3.9.4. Minimum efficiency requirements for office equipment
It is recognised that with the modernisation of office work at public institutions the energy
consumption of office equipment has become a significant part of the overall energy use of
the sector. It is necessary to establish minimum criteria for typical office equipment (copiers,
computers, air conditioning equipment etc.). This is expected to lead to gradual phasing-out of
obsolete, low efficiency equipment and eventually savings in energy consumption and GHG
emissions.
Regulatory
Planned
None
Effects and impacts
Based on the forecast in the NEEAP, the following mitigation effects are projected.
Table 29 Projected emission reduction achieved by minimum efficiency requirements for office equipment
2010
2015
2020
2025
0.000
0.100
0.100
0.100
0.000
0.400
0.900
1.400
0.000
0.023
0.023
0.023
0.000
0.092
0.206
0.320
II.4. Industry
II.4.1. Operation of ETS
The key facts for the ETS system are summarised in point II.3.6. These are valid for the
industries subject to the ETS as well.
61
Regulatory/Economic
Implemented
 Verified GHG emissions
 Industrial GDP
Effects and impacts
The same is true here that was said about the effects of the ETS in the energy industry:
although the first trading period did not generate direct financial incentives for most of the
industry, it certainly increased awareness regarding the value of emissions. The second
trading period coupled this with directs economic interest, as the quantity of allowances was
below the actual emission at most companies. Further strong incentives will be provided in
the upcoming third trading period by stricter emission limits and mandatory auctioning.
Here again, the emission trends are determined by several factors, from fuel and energy prices
to market conditions of the industrial products, therefore it is not possible to attribute the
changes in emissions to a single policy, such as ETS, however it may have played an
important role. Therefore, although the detailed modelling provides projections for the
industry emissions, it cannot be broken down to this individual policy, so no projections for
the effects are provided here.
II.4.2. Support for renewable energy utilization
Although, within the general Hungarian energy strategy and the renewable strategy the
residential and tertiary sectors are given strong emphasis, the use of renewables is also
encouraged in the industry. Several of the operative programmes described elsewhere in the
current document include enterprises which can be companies of the industry in their target
groups.
The following policies support renewable projects (for details please refer to point II.3.2.2):
 Renewable based power or CHP generation, bio-methane production: KEOP-20114.4.0
 Supplying local heat and power demands from renewable energy sources: KEOP2011-4.2.0-A and KEOP-2011-4.2.0-B.
 Renewable energy based regional development: KEOP-2011-4.3.
 Increase of utilisation of renewable energies in Central Hungary: KMOP-3.3.3.-
62
 Support for the preparation and development of geothermal heat and power projects:
KEOP-2011-4.7.0
Economic
Implemented
Monitoring is through the following indicators:
 amount of subsidy used
 renewable energy used (where applicable);
 quantity of generated heat/electric power (where applicable);;
 calculated emission reduction.
Effects and impacts
It is not possible to quantify what percentage industrial enterprises will have in the foreseen
effects of the general renewable promotion policy. The forecast effects therefore are included
in the projections in point II.3.2.
II.4.3. Energy Efficiency Credit Fund
The Energy Efficiency Credit Fund (EHA) is a financial facility to assist implementing
energy efficiency projects in the form of preferential loans from a revolving fund. It has been
in place since the early 1990s. The current interest rate of the loan is 25% of the banking base
rate + 2.5%.
The conditions of the loan are rather strict:
 the energy cost saving shall be at least 50% of the total savings generated by the
project;
 the energy saving intensity of the investment shall be at least 30GJ/year/million HUF;
 the IRR of the project shall be at least 80% of the banking base rate;
 the maximum preferential loan can be 90% of the project cost, but not more than HUF
200 million;
 the loan period is maximum 6 years including a possible 2-year grace period.
The following project types are typically eligible for the loan:
 reducing the losses of energy generation, conversion; transport and end-use;
 application and proliferation of modern energy efficient technologies;
63
 heat recovery and energy-purpose use of wastes;
 utilisation of biomass, solar, geothermal and wind energy;
 thermal insulation;
 modernisation of indoor and outdoor lighting.
Economic
Implemented
Effects and impacts
The following impacts are foreseen.
Table 30 Projected emission reduction achieved by Energy Efficiency Credit Fund
2010
2015
2020
2025
0.31
0.31
0.26
0.21
0.930
2.480
3.890
5.040
0.036
0.036
0.030
0.024
0.107
0.284
0.446
0.578
II.4.4. Large energy consumers: Compulsory employment of energy managers and
energy reporting.
In case of large energy consumers there is usually considerable potential for energy saving by
good energy management, i.e. if energy use is under permanent expert control and the
potential is investigated by proper professionals. Several years ago the system of compulsory
employment of energy managers was in place and the experience with the system was good.
The relevant legislation however was deregulated and obviously due to budgetary
considerations, very few organisations employ energy managers today. This situation can be
remedied by reinstalling the obligation of employing proper experts as energy managers.
Parallel to the regulatory change, proper training of energy managers is planned to be ensured.
The policy is primarily targeted for the non-ETS companies and municipalities of larger than
5000 population.
Besides proper energy management it is also important that large consumers would closely
track their energy consumption. Therefore a system of compulsory annual reporting of energy
64
consumption is planned. Besides the obvious awareness raising and the consequent energy
savings, the system would provide governmental bodies with reliable energy consumption
data for decision making.
Regulatory
Planned
None
Effects and impacts
The estimated effects are the following.
Table 31 Projected emission reduction achieved by compulsory employment of energy managers and
energy reporting
2010
2015
2020
2025
0
0.6
0.54
0.45
0.00
1.80
4.68
7.13
0.000
0.069
0.062
0.052
0.000
0.206
0.536
0.817
II.4.5. Voluntary agreements
In their efforts to improve energy efficiency and mitigate GHG emissions several EU
countries such as Holland gained good experience with the voluntary agreements between the
government and large energy consumer enterprises. It is planned therefore that the system is
employed in Hungary. According to the concept the government contracts with important
players of the energy sector (non-ETS energy intensive industries, the energy industry,
manufacturers of certain end-user appliances) for the efficient use of energy. In order to meet
their obligations the companies reduce their energy consumption, apply more effective energy
supply technologies, develop products with better energy efficiency indicators.
In return the government provides favourable publicity for the contracting parties and can
provide financial assistance for the implementation of EE measures.
Legal/Economic
Planned
65
 Contracted energy saving
 Calculated GHG emission reduction
Effects and impacts
Table 32 Projected emission reduction achieved by voluntary agreements
2010
2015
2020
2025
0
0.15
0.13
0.1
0.00
0.51
1.22
1.79
0.000
0.017
0.015
0.011
0.000
0.058
0.140
0.205
II.4.6. Heat recovery
Large amounts of heat are often lost in various industrial processes. Recovering and utilising
such waste heat can save considerable primary energy. Especially in the non-ETS industries
the potential of waste heat utilization at boilers, driers, furnaces, compressors, transformers,
etc. is not yet properly exploited. Although some KEOP operative programmes support heat
recovery projects, industrial enterprises are not the target groups of these programmes.
Therefore it is planned that new elements that support heat recovery in the industry will be
included in the support system.
Financial
Planned

Calculated energy saving

Calculated GHG emission reduction
Effects and impacts
66
Table 33 Projected emission reduction achieved by heat recovery
2010
2015
2020
2025
0
0.2
0
0
0.00
0.42
0.84
0.84
0.000
0.014
0.000
0.000
0.000
0.029
0.057
0.057
II.5. Transport
II.5.1. Strategy documents
II.5.1.1. Unified Transport Development Strategy
The current transport strategy is based on the Hungarian Transport Policy, adopted by the
Parliament in 2004, the basic objectives of which were:
 improvement of the quality of life, preservation of health, reduction of regional
disparities, increasing the safety of transportation, protection of built-in and natural
environment;
 improvement and extension of connection to the neighbouring countries,
 promotion of the implementation of regional development objectives,
 creation of conditions for efficient operation and maintenance by regulated
competition.
The present general transport-related strategy of Hungary is set by the document entitled
―Unified Transport Development Strategy 2007-2020‖ (EKFS), developed by the government
in 2007. To achieve the strategic goals set by the EKFS, they were elaborated in more detail
in a subsequent document in 2008: ―Sub-branch strategies for achieving the objectives of the
Unified Transport Development Strategy 2008-2020‖.
It must be noted that the EKFS is currently being updated; the new version is expected by
summer of 2011.
The EKFS sets the following strategic objectives and foresees the following measures to
achieve them:
1. Development of passenger transport
a. Optimisation of modal split within passenger transport, preserving the largerthan-EU 27 average share of public transport. Measures/tools:
 Revision of public transport (bus, train) related legislation, with special
emphasis on passengers‘ rights.
 Restructuring of the tariff and tariff benefit system.
 Smart payment: introduction of a chipcard-based payment system.
 Demand-driven public transport services.
67
 Intelligent transport support systems.
b. Improvement of the efficiency of modal split within public transport by
ensuring commonality. Measures/tools:
 Sector neutral financing tools for constructing modern connection hubs.
 Intelligent transport systems.
 Detailed survey of transport demand, system design based on actual
demands.
 Safe storage of private vehicles at connection hubs to public transport.
 Development of cycling routes.
 Establishing the regional organisation of transport.
c. Increased mobility by ensuring equal opportunities
Measures/Tools:
in
mobility.
 Financing the removal of obstacles of the disabled in the transport
infrastructure.
 Appropriate tariff system to ensure equal access to public transport.
d. Ensuring economic sustainability of passenger transport by rational
organization. Measures/Tools:
 Proper support for maintaining public transport services, for
development and operation.
 Restructuring the tariff and benefit system.
 Intelligent (card-based) payment systems.
 Restructuring public transport service contracts.
2. Development of freight transport
a. Maintaining the share of environmentally friendly transport modes above the
EU-27 average in the modal split of freight transport. Measures/Tools:
 Infrastructure development by involving private capital.
 Electronic road-toll payment system.
 Introduction of TAF-TSI (Telematic Applications Freight Technical
Standard Interoperability).
 Compensation funding to increase competitiveness of railways.
b. Improving the profitability of environmentally friendly transport modes, and
their infrastructure maintenance capacity; Measures/Tools:
 Modernisation of railway tracks
 Proper tariffs and bilateral agreements on cross-border transport.
 Application TAF-TSI.
 Navigability of Danube.
c. Increasing the share of combined freight transport modes. Measures/Tools:
 Ensuring proper infrastructure, involving private capital.
68
 Restrictions on road transport, favourable conditions, discount for
railway transport.
 Compensation funding to increase competitiveness of railways
considering the external benefits of railways (environmental costs,
human safety, infrastructural costs, etc.).
d. Increasing the efficiency of intermodal logistic service centres.
Measures/Tools:
 Properly utilize and involve available EU funding for the necessary
infrastructural projects.
 Multimodal logistic centres.
3. Development of transport infrastructure
a. Development of a main road network structure in order to improve economic
competitiveness. Measures/Tools/Projects:
 Promotion of investments
 Network development including:
- Carriageway/Dual carriageway construction (M0 ring; TEN-T
network).
- New bridges on the Danube.
- Development of road network between the regions and the
regional centres.
- Railway corridors reconstruction for 160 km/h.
- Development of the Budapest airport.
b. Improvement of regional accessibility at various levels. Measures/Tools:
 Improvement of the quality of the road network tops.
 Increase maximum speed on railways (outside the TEN-T).
 Accessibility of regional airports.
c. Development of the infrastructure of urban and suburban public transport.
d. Prevention of increased road wear owing to the increasing axle loads of
vehicles. Tool:
 Reinforcing the relevant roads.
4. Horizontal objectives
a. Reduction of the death toll of road accidents under 500 per year. Tools:
 Efficient fining system with a ―revolving‖ utilisation of fine income for
improving the infrastructure.
 Safer infrastructure.
 Media campaigns and stabile media presence.
 Targeted training for children and drivers.
69
b. Implementation of more environmentally friendly and more energy efficient
transport systems.
c. Long term provision of sustainability by conscious infrastructural
development.
d. Acceleration of introduction of ITS (intelligent transportation systems)
applications.
II.5.1.2. New Széchenyi Plan transport chapter
The New Széchenyi Plan is the latest document which defines the strategic priorities of
transport development. It is to a large extent based on the EKFS but also reflects the redefined
priorities of the upcoming EKFS update and sets some quantifiable objectives as well. The
most important long term objectives are the following:
1. Improvement of modal split
The following modal split shall be achieved by 2020.
Table 34 Modal split figures in 2020 according to the New Széchenyi Plan
Freight transport
Passenger transport
Road
Railway
Water
Pipeline
67%
20%
8%
5%
Car
Bus
Railway
Air
65%
15%
15%
5%
Public
Individual
City traffic
50%
50%
In City centers
70%
30%
2. Development of road network. The roads by-passing cities and their proper
maintenance shall have priority in road construction. The future targets by 2020 and
beyond are the following:
a. Sustainable financing by applying the ―user pays‖ principle.
b. Carriageway system shall be integrated in the TEN-T network.
c. M0 ring-road around Budapest shall be completed and by-pass roads for cities
larger than 10,000 population shall be constructed.
d. The role of road transport in mid- and long range transport will be heavily
reduced.
e. The share of renewables (alternative fuels to diesel and gasoline) will be
considerably increased: it shall reach 30% in the long term.
f. Casualties of road accidents shall be reduced below 250 per year.
3. Development of railways.
70
a. The length of railway network shall be at least 6000 km.
b. Access to the railway in cities is assisted by proper road transport connections
(bus service) to ensure that railways could be reached in 15 minutes.
c. Larger industrial sites with transport demand bigger than 3000 TEU per year
shall be serviced with dedicated railway connection if closer to the railway
than 10 km.
d. Railway track shall be modernised so that a minimum speed of 80 km/h on any
line, 120 km/h on the trunk network and 200 km/h on the priority lines could
be maintained.
e. Timetable is upgraded so that maximum one hour interval (30 mins in
suburban traffic) would be reached.
4. Air traffic development
a. At least three airports besides the Budapest airport shall be capable for
international traffic.
b. Accessibility to international airports: 90 minutes.
5. Water navigation development:
a. Navigability of the Danube is improved: between 1811–1641 riverkilometres
the VI/B and between 1.641–1.433 riverkilometres the VI/C waterways are
constructed.
b. The Hungarian transport fleet is developed.
c. Ports are developed (the Csepel port is connected to the MO motorway,
logistics infrastructure is constructed).
6. Intermodal transport and logistics development
a. Logistics centres (terminals) are constructed to support combined modal freight
transport.
b. Road toll system to encourage switch to railway/water transport from road
transport.
c. Intermodal hubs for connecting local and long-range passenger transport.
7. Other development
a. P+R systems enable easy access to city public transport networks
b. Traffic reduction in city centres by reorganisation.
c. Promotion of cycling (improvement of cycling route networks, rental
facilities).
II.5.1.3. The overall effects of strategy implementation
If just the 2020 modal split targets of the strategies are compared against the trends so far, it is
apparent that the targets are rather ambitious. If freight transport is considered, it can be seen
that the trends must practically be reversed.
71
Figure 11 Trends and targets in freight transport modal split
The trend is similar in passenger transport, but if the measures foreseen in the strategies are
implemented, the railway will regain its former position in long distance transport and will
considerably increase in suburban traffic.
II.5.2. Subsidy for improving the accessibility of Hungary and regional centres by rail
and/or waterways
Several of the effective operative programmes are already aiming the implementation of the
strategic goals. Both the EKFS and the New Széchenyi Plan include the improvement of the
accessibility of regional centres and the country itself among the major strategic goals. One
tool of implementing this objective is to provide support for the realisation of the necessary
projects. This support is provided through two operative programmes of the New Széchenyi
Plan:
 Operative programme KÖZOP–2.4.0-09-11 Provides financing for the preparation of
such projects. The activities/costs that can be supported are:
o Preparation of feasibility study
o Environmental impact study
o Archaeological impact survey
o Licensing
o Preparation of detailed design
o Site preparation (archaeological site survey, unexploded ordinance survey,
utility supply design)
o Costs of the procedure for acquiring the land (legal fees, authority fees,
indemnification, etc.)
72
o Public procurement costs, authority procedures, PR costs.
The value of the support can be 100% of the total cost. The total amount allocated for
this purpose is HUF 61.98 billion.
 Operative programme KÖZOP-2.5.0-09-11 supports the implementation of projects
that serve the improvement of the accessibility of Hungary and regional centres by rail
and/or waterways. The objective of the support is to improve safe accessibility,
improve global and regional competitiveness. The supported railway development
projects focus on the sections of the TEN-T network. The waterway related projects
focus on the creation of a navigable waterway on the Danube.
The total amount allocated for this purpose in 2011-13 is HUF 116.44 billion.
Economic
Implemented
 Length of modernised railways
 Traffic data on the modernised railways
 Traffic data on the waterway
Effects and impacts
The improvement is expected to shift some of the transport from roads to railways and
waterways. The effects are not quantifiable separately; they are included in the overall
projections in point II.5.1.3.
II.5.3. Improving the accessibility of regions
 Operative programme KÖZOP–3.4.0-09-11: Provides financing for the preparation of
such projects. The activities/costs that can be supported are the same as for KÖZOP–
2.4.0-09-11 described in II.5.2. The total amount allocated for this purpose is
HUF 45.83 billion.
 Operative programme KÖZOP-3.5.0-09-11 supports the implementation of projects
aimed at improving the accessibility of regions by constructing connections to the
motorways, developing main roads that connect the regions, increase the capacity of
main roads, and reduce the traffic on the main roads around lake Balaton by
developing water transport on the lake. The total amount allocated for this purpose in
2011-13 is HUF 126.57 billion.
73
Economic
Implemented
 Length of modernised railways
 Traffic data on the modernised railways
 Traffic data on the waterway
Effects and impacts
Here the GHG mitigation is not of primary concern. However, the improvement is expected to
shift some of the transport from roads to waterway in case of Lake Balaton. The effects are
not quantifiable separately; they are included in the overall projections in point II.5.1.3.
II.5.4. Support for the development of urban and suburban public transport
 Operative programme KÖZOP–5.4.0-09-11: Provides financing for the preparation of
such projects. The activities/costs that can be supported are the same as for KÖZOP–
2.4.0-09-11 described in II.5.2. The total amount allocated for this purpose is HUF
58.96 billion.
 Operative programme KÖZOP–5.5.0-09-11 supports the implementation of projects
aimed at improving the efficiency, comfort, services of urban and suburban public
transport and improve its competitiveness compared to individual (car) transport. The
total amount allocated for this purpose in 2011-13 is HUF 63.14 billion.
Economic
Implemented
 Traffic data on the modernised railways/suburban railways/public transport systems
Effects and impacts
The improvement is expected to shift some of the transport from individual transport (cars) to
public transport. The effects are not quantifiable separately; they are included in the overall
projections in point II.5.1.3.
74
II.5.5. Support for intermodal transport
Operative programme GOP-2011-3.2.1 provides subsidy for projects that construct, develop
or improve intermodal logistics centres or regional logistics centres in order to provide high
added-value services for the international freight streams going through the country. It is also
an objective of the programme to improve the competitiveness of Hungarian SMEs that
provide complex logistical services, therefore subsidy is also available in the frameworks of
the policy for directly developing logistical services. The supported activities are the
following:
 Procurement of equipment
 Investment in infrastructure or property
 Development of information technology used
 Procurement of manufacturing licences, know-how
 Costs of market entry
 Development of company HR activity
 Using advisory services
 Introduction and/or certification of Quality Assurance, Environment and Management
systems.
 Project preparation
The value of the subsidy can be 30-50% of the total cost, ranging from HUF 25-500 million,
depending on the project type. The allocated amount for the programme is HUF 9 billion for
2022-13.
Economic
Implemented
 Traffic data on the modernised railways/suburban railways/public transport systems
Effects and impacts
The improvement is expected to shift some of the freight transport from road to alternative
modes, chiefly railway. The effects are not quantifiable separately; they are included in the
overall projections in point II.5.1.3.
II.5.6. Promotion of renewable (bio) fuels
75
The use of biofuels in transport has been regulated in Hungary since 2005. Until 2009 the use
of biofuels was promoted through the taxation system: until 2007 an excise duty refund
system was in place for biodiesel and bioethanol blended in normal diesel oil and gasoline,
then it was partly replaced by a preferential tax system - the bioethanol content of standard
E85 fuel, for example was exempt from tax.
This system in 2009 was replaced by the mandatory share of biofuels in automotive gasoline
and diesel oil. The current regulation (Act CXVII.of 2010 and Governmental Decree
343/2010.) stipulates that the monthly amount of automotive gasoline and diesel oil sold by
the individual traders, importers, producers shall include 3.1% and 4.4% biofuels in terms of
energy content, respectively.
The regulation also strictly stipulates that only biofuels produced in a sustainable way can be
used. The sustainability of the biofuels shall be certified by a sustainability certificate, which
is issued on the basis of the criteria in accordance with the Renewable Energy Directive
(2009/28/EC) and Fuel Quality Directive (2009/30/EC) of the EU.
Non-compliance with the stipulations of the mandatory share of biofuels is sanctioned with
heavy fines. (Currently 35 HUF/MJ, on the basis of the energy content of the biofuel missing
from the prescribed amount.)
The current regulation is to be adjusted so that the national targets for the share of renewables
would be met.
Regulatory/Fiscal
Implemented
 Amount of biofuel used
 Calculated GHG emission reduction
Effects and impacts
From the targets set in the NCsT (see point II.3.1.3) the following absolute energy
consumption data trends can be derived.
76
Figure 12 Trends of biofuel use
Based on this forecast the following effects of the policy are projected.
Table 35 Projected emission reduction achieved by promotion of renewable (bio) fuels
2005
2010
2015
2020
2025
Bioethanol - ETBE, PJ
0.21
1.42
3.10
7.91
8.10
Biodiesel, PJ
0.00
4.61
7.37
13.27
13.59
Other
(e.g. biogas in public transport), PJ
0.00
0.00
0.04
0.21
0.21
Emission reduction, Mt CO2/year
0.013
0.401
0.711
1.429
1.464
II.5.7. Toll system for heavy vehicles
In 2007 Hungary introduced toll for all commercial vehicles above 12 tons weight on the
majority of the national road network and plans to extend the toll to other lower priority roads
too. The toll was paid in the form of a sticker to be bought, on lump-sum basis. This has
already generated some positive effects, although in the beginning lot of problems were
caused by the traffic shifted form the toll roads to lesser roads through towns.
It is planned, however, that a more correct electronic toll system will be introduced, in line
with the European directives 2004/52/EC and 2006/38/EC. According to most recent
information, the new toll system of heavy vehicles will be operating from January 2013, and
for all vehicles from 2020.
It is expected that the new system will reduce the apparent advantages of road transport over
railways, and encourage the operators of the vehicles to optimise transport routes, and the
77
utilisation of the vehicles. Besides the obvious environmental benefits increased income for
the budget is foreseen.
Regulatory
Planned
 Income generated
 Transport kilometres
Effects and impacts
Table 36 Projected emission reduction achieved by toll system for heavy vehicles
2010
2015
2020
2025
0.41
0.5
0
0
1.130
3.540
4.790
4.790
0.026
0.032
0.000
0.000
0.072
0.226
0.306
0.306
II.5.8. P+R systems
Studies and experience show that the key bottleneck to shifting urban traffic to public
transportation is the lack of safe parking possibilities for commuters in the large cities. It is
planned therefore to develop a complex system of low cost, or free P+R parking system,
including the construction of parking facilities and electronic control system. This would lead
to considerable reduction of transport energy use and GHG emissions.
Infrastructure
Planned
 Number of P+R parking places
Effects and impacts
The following energy and GHG emission savings are projected.
78
Table 37 Projected emission reduction achieved by P+R systems
2010
2015
2020
2025
0.01
0.1
0.01
0.01
0.03
0.43
0.75
0.80
0.001
0.006
0.001
0.001
0.002
0.027
0.048
0.051
II.5.9. Subsidy for the development of the cycling route networks
The development of cycling routes is supported through various operative programmes: this
objective is included in the general traffic development program package (KÖZOP) and also
in the regional development programmes.
 Operative programme KÖZOP-3.2.0/C-08-11 provides co-financing for cycling road
projects, complementing the regional programmes. The following can be supported:
o Design (feasibility studies, licensing, tendering procedure)
o Site preparation (surveys, supervisor engineering services)
o Construction and commissioning
o Public procurement procedure
o Communication
Altogether HUF 6.47 billion is allocated for this policy for 2011-2013. The subsidy
can be between HUF 50-450 million, amounting to 85-90% of the project costs.
 Regional operative projects (ÉMOP-5.1.3-11, ÉAOP-3.1.3/A-11, DAOP-3.1.2/A-11,
DDOP-5.1.1-11, KDOP-4.2.2-11. NYDOP-4.3.1/B-11) support complex cycling
infrastructure development projects only, i.e. projects that address an entire town or
an independent part of a city, or that connect two towns directly and comfortably.
Basically the implementation of such projects are supported, but linked to these
projects, some auxiliary activities, such as B+R parking, awareness raising, lighting
of cycle routes etc. can also be supported. The support can range from 6% to 50% of
the costs, with a maximum of HUF 1.25-70 million depending on which part of
implementation is supported.
The total finance allocated for the six regional operative programmes is HUF 8.57
billion for 2011-13.
Economic
Implemented
79
 Length of cycling routes constructed
 Traffic data of the routes
Effects and impacts
The improvement is expected to shift some of the passenger transport from cars to bicycle.
The effects are not quantifiable separately; they are included in the overall projections in point
II.5.1.3.
II.6. Agriculture
II.6.1. General
Agriculture and forestry used to be one of the decisive branches of the Hungarian economy
for a long time. Hungary‘s natural endowments, the climate, the quality of the soils and the
long-time tradition and expertise can provide for excellent production results both in terms of
quality and quantity.
Out of the total 9.3 million hectares of the total area of Hungary, 7.8 million hectares are
productive land (including forests, fish ponds etc.), 5.8 million hectares of which are
agricultural land – a share which is uncommonly high in Europe. Of this, 78% is arable land
and 17% is grassland. Kitchen gardens, orchards and vineyards account for hardly 5% of the
agricultural land area.
However, due to the unavoidable restructuring of the economy in the early 1990s, the loss of
the traditional markets, agriculture lost much of its importance in terms of economic output
despite all the favourable conditions. While in 1989 the agriculture produced 13.7% of the
GDP, provided employment for 17.4% of the workforce and generated 22.8% of the export
revenues of the country, its share in the GDP production dropped to some 3% by today, and
less than 5% of the employed work in this sector. While only less than 2% of the population is
employed in the agriculture, still more than 30% of the populace lives in rural areas, where
agriculture often provides the sole opportunity of employment and work.
80
Figure 13 Contribution of agriculture to the GDP
Figure 14 Contribution of agriculture to employment
This figure indicates several other problems of rural Hungary: migration of the young
populace to cities, poor and dilapidating infrastructure, low income levels, lack of capital etc.
The Hungarian Government developed the new 10-year National Rural Strategy with the
primary aim of remedying the situation and reversing the adverse trends. The strategy is in the
social discussion stage, right before its approval by the Parliament.
81
II.6.2. National Rural Strategy until 2020
The goal of the strategy is to promote social and economic improvement for all affected in the
countryside.
Hungary, throughout the centuries has been able to renew itself by relying on the strength of
village communities and the roots of the countryside. It is recognised that the problems of
agriculture, the countryside and environment are not problems concerning only villages, but
the entire country and population is affected by the success and failure of the countryside.
The significant decay of the conditions of country life and the further deterioration of
agriculture requires a quick and effective approach to economic and social policies in order to
stop further decline.
The central and comprehensive goals of the strategy are:
 the preservation and increase of rural workplaces
 the preservation of the rural population and restoring demographic balance
 the guarantee of food production and ensuring food supply, to eliminate poverty in the
country
 increasing the vitality of agriculture and food production, improving our market
position, restoring the appropriate balance between crop production and animal
husbandry
 the protection of drinking water supplies, preservation of water sources, soil, natural
flora and fauna and the countryside, and increasing environment protection
 energy supply based on local resources and systems, security of energy, decreasing of
energy dependency
 improving the quality of rural life and diversification of the rural economy
 restoring the close connection between the city and its environs
 the national rural strategy is introducing concrete directives to achieve these
comprehensive goals and introduces a national program
It is the basic intention of the Strategy to turn Hungary into such a country where European
diversity, quality of agriculture, good management of the countryside and the environment is
becoming standard. Hungary will produce valuable, healthy, secure food without GMO
intervention and will simultaneously protect the soil, the drinking water supplies, the flora and
fauna, the countryside and local communities with their backgrounds. At the same time
Hungary will provide work and livelihood for as many people as possible.
As it is apparent from the above, GHG mitigation is not of primary concern in the strategy.
Still, the detailed goals of the planned programmes include several elements that are to reduce
GHG emissions or increase the carbon sink capacity (in the following list first the name of the
82
program is identified, then those elements/goals of the programs are listed that contribute to
GHG mitigation):
 Preservation of natural resources, sustainable management of resources and lands:
o Development of local energy generation and supply (Local energy supply is
typically based on renewable energies.)
 Quality of rural environment
o Support for energy efficient construction methods and environmentally friendly
heating systems.
o Increasing the share of railway freight transport and public passenger transport.
o Local food production and short-distance supply of consumer demands (lower
transport demand).
o Substituting soy-imports from faraway sources by utilising organic wastes for
fodder (lower transport demand).
 Sustainable agri-structure and production policy
o Support for low (fossil) energy production systems
o Local generation of protein for fodder (protein program), replacing soy-imports
from faraway sources (lower transport demand).
o Increasing the rate of afforestation in order to achieve 27% share of forests.
o Increase the utilisation of agricultural by-products for energy generation
purposes.
 Increasing added value, safe food supply, safe markets
o Taxation is shifted from labour to energy use, use of the environment and
transport, encouraging efficient use of these resources.
o Shortening the food chain, promoting local co-operation, local processing of
products (lower transport demand)
 Local economy development
o Restructuring the utilisation of the by-products of forestry and agriculture, and
other biomass for energy generation, creation of local energy (heat) supply
systems on small-region level for municipal institutions, and local processing
industries.
The effects of these elements of the new strategy cannot be separately quantified: as it is
apparent form the above list, the majority of the policies generate GHG mitigation effects in
other sectors (especially in the energy and transport sector).
Some policies directly targeted the agricultural sector are already in place, however, they are
described in the following points.
II.6.3. Support for renewable based energy supply in agriculture
83
Decree 78/2007. (VII. 30.) FVM provides subsidy for farmers to install renewable based
energy supply systems, especially biomass-fired boilers and heat distribution systems. The
amount of subsidy is maximum HUF 30 million, and not more than 35% of the eligible costs.
Economic
Implemented

Number of projects, technical data of equipment

Effects and impacts
Based on the share of agriculture in the total energy consumption and the foreseen share of
renewables in the heating and cooling sector, the estimated effects are the following.
Table 38 Projected emission reduction achieved by support for renewable based energy supply in the
agriculture
2010
2015
2020
2025
Renewable energy used for heating in the
agriculture PJ/year
1.2
1.4
2.4
3.3
0.82
0.096
0.165
0.226
II.6.4. Support for small-scale bio fuel plants
Decree 44/2009. (IV. 11.) FVM provides subsidy for farmers, agricultural producer groups, or
other enterprises for the construction of small capacity, vegetable-based raw spirit or oil
(biofuels). The objective of the support is to improve the competitiveness of the agricultural
producers and to contribute to increasing the share of biofuels. The support may be used for
equipment procurement, installation, civil construction, procurement of software and
hardware, laboratory equipment and the construction of the necessary infrastructure. The
value of the subsidy can range from EUR 60,000 to EUR 1 million, amounting to 40-60% of
the total cost, depending on who and where implements the project.
Economic
Implemented
84

Number of projects, production data of equipment

Effects and impacts
The effects of the policy appear in the transport sector and are included in the projections in
point II.5.6.
II.7. Land use change and forestry
In Hungary, forests represent the second biggest sector after arable land in terms of area, with
19,129 km2 forest and 20,393 km2 forestry-purpose (including the forests and plantations) of
country‘s total 93,030 km2. The share of various species in the forests in terms of area is
shown in the following diagram:
The ownership split of forests is the following:

State-owned:

Community-owned: 1.0%

Privately-owned:
42.9%

Other (mixed):
0.6%
55.5%
The long term data show continuous expansion of privately-owned forest areas. In 2009
altogether 6.8 million cubic metres of wood material was produced by the Hungarian forests,
the majority (66%) from the state owned forests.
Figure 15 Tree species in the Hungarian forests
The forests are an important carbon sink, and further afforestation is planned. Besides the
relevant legislation (Act XXXVII of 2009 on forests, forest protection and forest
85
management), the major objective of which is to ensure sustainability, the future of Hungarian
forests is determined by two basic strategic documents and some concrete policies, which are
discussed in the following points.
II.7.1. National Forest Programme and National Afforestation Programme
Long term forest related strategy planning was started in 1996-97, when the national longterm afforestation concept was completed and the first recent National Afforestation
Programme was drafted. Later it was recognised that due to various reasons (limited resources
available, changes of land ownership and lack of information for the new land owners) the
targets set in the programme were not met. This called for a reconsidering of the plans based
on Government resolution 1110/2004. (X. 27.) on the National Forest Programme 2006-2015,
which is still valid today.
The National Forest Programme 2006-2015 sets the following strategy objectives:

At least maintaining the current level of forestation, but preferably its increase must be
ensured. Neither the quantity, nor the quality and value of the forests must decrease.

Use of wood in the society, as an environmentally friendly raw material, shall be
encouraged.

Forest management shall ensure that the increased demands for wood would be met,
without endangering sustainability.

Knowledge and information on forests shall be increased in the society.
The key elements of implementing the strategic goals are the followings:
1. Protection of forests and natural processes in the forests. Perseverance of
biological and genetic values. Natural forest management.
2. Utilisation of forests. The competitiveness of forestry products shall be
increased. Utilisation areas may be widened, with respect to industrial and
energy-purpose utilisation of wood.
3. Development. Increasing forests with respect to biodiversity, landscape, and
erosion protection.
These elements are to be implemented through the following specialised targeted
programs/support schemes:

Development of state owned forests

Development of private forests

Rural development, forestation, forest restructuring

Nature conservation in the forests

Modern forest protection
86

Rational utilisation of wood

Forestry management

Research, education, product development

Communication about the forests in order to improve the forest-human relationship
Based on the National Forest Programme or more exactly on its focus-programme of ―rural
development, afforestation and forest restructuring‖ (5.3), which aimed at planting 100,000 ha
new forests as a strategic goal, in 2008 the National Afforestation Programme was completed.
The National Afforestation Programme is a long-term, some 35-50 year programme of
achieving the desirable 27% share of forests in the total area of the country. This target is only
valid for the natural sustainably managed forests, excluding the potential energy plantations.
According to the Afforestation Programme, the primary objective of afforestation is to reduce
the impacts of climate change. Forests can serve this purpose in two ways: new forests act as
extra carbon storage facilities (it is estimated that the new forests planted between 1990-2006
will have stored more than 1million tons of CO2 by 2012), and the some 50% of the annually
produced wood is used for power generation already.
The Afforestation Programme identified those areas in the country that are most suitable for
afforestation by using two soil-quality classification methodologies, and on the basis of a
dedicated 1999 survey and a 2004 research. Class 4 and Class 6 category areas are especially
recommended for afforestation, their total area is 6833 km2, which enables the target of 27%
share of forests to be achieved.
Figure 16 Afforestation in Hungary 2001-2009
The effect of the afforestation policy has been a steady increase of afforested area in the past
years, although at a slower rate than planned. Within the 10 years between 1991 and 2000,
some 66 thousand hectares of new forest was planted, which was around 44% of the plans,
87
whereas between 2001 and 2006 already some 77% of the original plans were implemented
and 69,213 hectares were afforested. The trend since 2001 is shown in the chart.
Based on the trends of the recent years and the reconfirmed intention of the Government (see
e.g. the National Rural Strategy, point II.6.2) to accelerate the afforestation, it is safe to state
that the desired 27% target can be reached until 2050, i.e. within the 25-50 year time span
defined in the National Afforestation Programme. The following progress is projected.
Table 39 Projected forest area, ha
2010
2015
2020
2025
1,927,600
2,001,900
2,076,200
2,150,500
II.7.2. Support for afforestation of agricultural lands
The above described afforestation programme is supported through a subsidy scheme
established by decree 88/2007. (VIII. 17.) FVM. The objectives of the scheme are to convert
territories with soils of low agricultural potential into forests, which serve as carbon sinks,
contribute to increasing biodiversity, provide renewable fuel, and not in the least serve the
recreation of the populace.
The subsidy can be used for plantation and maintenance of new forests and for compensation
of lost revenues due to afforestation.
The value of the subsidy is
 EUR 853-2065 per hectare depending on the type of the tree and the terrain for
plantation of new forests;
 EUR 262-519 per hectare depending on the type of the tree and the terrain for the
maintenance of the new plantations.
 The compensation for lost revenues range from 57 to 242 EUR per hectare per year for
5-15 years, depending on the type of the tree and the afforestation level.
Economic
Implemented

Area of afforested terrain
Effects and impacts
Included in the projections of the previous point.
88
II.8. Waste management
II.8.1. Basic legislation and National Waste Management Plan 2009-2014
The basis of Hungary‘s waste management policy is Act XLIII of 2000 on waste management
(modified several times since 2000, most recently in 2010) and the subsequent National
Waste Management Plans (NWMPs).
The Act on Waste Management defines the strategic goals of proper waste management,
practically all of them relevant to GHG mitigation:
 ensure sustainable development and proper conditions for the future generations;
 reduction of the consumption of energy and other resources, improving the efficiency
of utilising these and reducing the amount of wastes;
 reducing the waste-caused load on human health and the environment.
Based on the relevant EU guidelines (75/442/EC, 91/156/EC) the Act on Waste Management
introduced a waste management planning system, which prescribes the preparation of six year
long plans on national, regional and local levels. As a result, the National Waste Management
Plan, seven regional waste management plans and 2080 local plans for the settlements were
prepared first in 2003, defining the tasks for the period between 2003-2008.
The currently effective second National Waste Management Plan 2009-2013 follows the logic
and spirit of the previous NWMP, albeit with much stronger emphasis on sustainability and
global environmental problems and sets the following priorities and targets:
1. Prevention of waste generation, to stop the increase of waste volume generated,
preferably reversing the increasing trend by prevention measures. Targets:
a. The annual amount of waste shall be reduced by 12% of the 2008 values by
2014, below 20 million tons per year.
b. The specific amount of wastes shall be less than 0.7 kg per HUF 1000 GDP.
c. The per capita amount of wastes shall be below 2000 kg.
d. The amount of MSW shall not be more than 5 million tons (550 kg per capita)
in 2014.
e. The annual amount of hazardous wastes shall be less than 1 million tons.
f. The amount of wastes from the industry and other business activities shall be
reduced below 6 million tons per year.
2. Recycling. Targets:
a. At least 50% of the total waste shall be re-used, utilised.
b. The recycling of the wastes as materials shall be at least 40%.
c. Infrastructure for selective waste collection for 80% of the populace
d. 30% of the MSW shall be recycled, and 40% of it shall be re-used, utilised in
some form.
89
e. Utilisation of 35% of papers, glass, metals and plastic until 2015 (50% until
2020).
f. Separate treatment of degradable wastes so that maximum 820 thousand tons
of degradable wastes would be landfilled in 2016.
g. Increasing the utilisation for energy generation and incineration.
3. Safe treatment of not utilised wastes including the minimisation of landfilled wastes
by selective collection. Landfilling shall be below 40% and other treatment method
maximum 10%.
The tools of achieving the strategic goals are described in detail for each waste stream in the
NWMP, but here only their major types are summarised:
 Investments, subsidies, introducing recycling technologies, redesign of products,
treatment facilities,
 Maintaining existing systems (selective collection, recycling infrastructure, treatment
facilities)
 Regulation, specialised strategies, programmes.
 Economic incentives (preferential taxing of recycled goods, levy on waste generating
products, fees for landfilling, etc.)
 Development of the institutional background
The effects of this policy are summarised below:
90
Figure 17 Treatment of wastes
The amount of wastes has gradually reduced since 2000, mainly due to decreasing industrial
production. Still, the importance of this decrease should not be underestimated, as in the
meantime the value of the real GDP increased by 20% .
In the recent years, and also in the future, when a similar decreasing trend of waste generation
is forecast, the trend is more and more due to the policies implemented, rather than
spontaneous and independent economic processes. It is noted that the relatively large decrease
in 2009 is attributable to the economic crisis in that year.
In terms of waste utilisation and recycling, the trend is less marked, and the figures underline
that in order to meet the strategic goals, considerable efforts are needed.
The implementation of the NWMP, however, had significant effects on the waste
management industry. The investment in waste treatment projects practically doubled
between 2005 and 2009, from HUF 23.2 billion to HUF 35 billion at 2005 real prices.
II.8.2. Legislative tools
Treatment of wastes is regulated in detail in the Hungarian legal system. With regard to GHG
emission reduction the most important pieces of the relevant legislation are:
 Decree 20/2006. (IV. 5.) KvVM on the rules and conditions for landfilling of waste
and landfill sites
91
 Decree 3/2002. (II. 22.) KöM on the technical requirements and conditions of waste
incineration and its emission limits.
This regulation, among other, stipulates and ensures that
 prevention of waste generation has priority over waste treatment;
 recycling shall have priority over all other treatment technologies and energy
generation from the waste shall have the other treatment technologies;
 landfilling shall be considered as a last resort for treating the waste;
 treatment or processing of the waste shall happen as near to the location where the
waste was generated as possible;
 in landfills the landfill gases shall be collected, treated and if possible, utilised; if
utilisation of the gas is not possible, it shall be incinerated (flared);
 if the waste is incinerated (for energy generation purpose or only as a waste treatment
technology) the combustion would be of high efficiency, no organic carbon would
remain in the residues (TOC <3%), and the process would have minimum impact on
the environment.
These stipulations all contribute – directly or indirectly – to GHG mitigation. It is noted here
that recycling is also promoted by a series of regulations, such as:
 Governmental Decree 181/2008. (VII. 8.) Korm. on collecting the batteries
 Governmental Decree 267/2004. (IX. 23.) Korm. on vehicles turned into waste
 Governmental Decree 209/2005. (X. 5.) Korm. on the rules of deposits (paid with
certain products)
 Governmental Decree 264/2004. (IX. 23.) Korm. on collecting the wastes of electric or
electronic equipment
 Governmental Decree 94/2002. (V. 5.) Korm. on packaging and treatment of
packaging wastes.
Regulatory
Implemented
None
Effects and impacts
The effects are mostly indirect and complex, therefore they are not quantifiable separately;
they are included in the modelled results.
92
II.8.3. Environmental levy on certain products
Since 1996 certain products that either generate large amounts of waste or are particularly
harmful to the environment if wasted have been levied with a dedicated environmental
product levy. The purpose of Act LVI of 1995 on the environmental levy and the
environmental levy of certain products (modified several times, most recently in 2009) that
regulates the system is to prevent environmental pollution and the generation of wastes, and
to create finance for preventing or reducing harms to the environment caused by these
products.
The levy at the moment applies for tyres, packaging, certain crude oil products (lubricants),
batteries, paper for advertisements (flyers, posters), electric and electronic equipment.
The levy is paid by those who first use such products for their own purpose or who put such
products into commercial circulation. A 25% discount of the levy is possible to obtain, if the
product is marked as environmentally friendly according to 1980/2000/EC. Exemption from
the payment of the levy is also possible if the product is collected and recycled.
Fiscal
Implemented
None
Effects and impacts
The environmental levy is considered to be the most effective incentive and regulatory tool of
waste management. It successfully puts into practice the ―polluter pays‖ principle, provides
adequate incentive to reduce the amount of waste and generates considerable funds. The
income of the state budget form the product levy is shown in the following table.
Table 40 The income of the state budget form the product levy, M HUF
Flyers,
RefriElectric
posters,
Packaging Battery
Tyres
gerators
Lubricant
equipment
papers for
coolant
advertisment
Solvents
Total
2000
4 631
916
2 425
1 267
0
0
5 598
0
24 407
2001
5 191
1 076
3 110
1 372
0
0
5 753
0
26 404
2002
6 081
1 288
4 340
2 189
0
0
6 156
0
20 054
2003
5 572
1 137
5 918
4 173
0
310
7 048
1 300
25 459
93
2004
5 663
354
1 606
3 773
0
789
5 691
2 134
20 009
2005
8 520
203
-45
1 888
1 140
1 669
6 041
0
19 616
2006
7 642
287
471
1 427
1 865
2 100
6 339
0
20 131
2007
8 184
282
325
1 232
2 665
2 292
5 948
0
20 929
2008
13 471
205
703
392
1 504
2 500
5 897
0
24 675
The GHG mitigation effects, however, are indirect and rather complex, therefore they are not
quantifiable separately; they are included in the modelled results.
II.8.4. Support of waste-to-energy projects
II.8.4.1. Compulsory take-over of waste-to energy power at subsidized prices (KÁT)
Besides renewables, the KÁT system described in point II.3.2.1 provides subsidy for wastegenerated electric power, too. The conditions are the same, although the feed-in tariff is
somewhat different.
Table 41 Support of waste-to-energy project, HUF/kWh
Peak
Off-peak
Night rate
31.28
21.55
11.25
Regulatory, economic.
Implemented
Quantity of electric power fed to the grid (kWh)
Effects and impacts
The KÁT system has always included the waste-to-energy subsidy component, but probably
owing to the more difficult licensing procedures so far such projects were less attractive than
cogeneration or renewable power generation. The trend of KÁT-subsidised waste-based
power generation is shown in the chart below.
94
Figure 18 Waste-generated power supplied to the grid
The most recent changes in KÁT regulation (waste-to-energy projects have much less
constraints) and the relatively high feed-in tariff, however, may change the picture. The
increased interest on behalf of investors and landfill operators is already sensible in the
market. With the increasing trend in mind the following effects are forecast.
Table 42 Projected emission reduction achieved by compulsory take-over of waste-to energy power at
subsidized prices
2010
2015
2020
2025
Total KÁT subsidised power
generation, TWh
0.140
0.198
0.252
0.250
Emission reduction, Mt CO2eq/year
0.056
0.075
0.094
0.092
II.8.5. Subsidy for recultivation of communal waste landfills
The Operational Programme KEOP-2.3.0/B/11 provides subsidy for the rehabilitation of
communal landfill sites. Although the primary target of the policy is not GHG emission, in
line with the stipulations of the legislation (see point II.8.2) it also subsidises landfill gas
recovery and treatment systems as a part of the rehabilitation, which results in GHG
mitigation.
The available finance is HUF 10 billion for 2011-13. The subsidy can be as high as 100% of
the project cost, in the range of HUF 650-1000 million per project.
Economic.
95
II.8.6. Implemented
Number of projects
Effects and impacts
Not quantifiable.
II.9. Education, awareness
II.9.1. Model projects to promote sustainable lifestyle and consumption
Operative programmes KEOP-6.2.0/A/09-11 and KEOP-6.2.0/B/09-11 provide subsidy for
model projects that
 Present the harmonic relation between the society and its environs.
 Demonstrate material conservation, prevention of waste generation, benefits of
selective waste collection and recycled materials.
 Demonstrate energy saving, climate awareness and benefits of renewables.
 Present water conservation, utilisation of rainwater.
 Increase the demand for sustainable products, environmentally friendly packaging.
 Promote human cooperation for sustainability.
The target group is the populace in general, children, the youth, families, decision makers at
various levels. Especially the following activities are supported:
 Promotion of places of work, schools, or other dedicated public institutions, which
would be regularly accessed by bicycle by the population
 Promotion of composting in households or communities.
 Complex environmentally friendly conversion of public buildings (water conservation,
energy efficiency, waste minimisation)
 Non-profit information centres to promote sustainability.
 Development of markets for local, environmentally friendly food.
The funds allocated for this purpose between 2007 and 2013, is HUF 7.74 billion, 4.9 of
which is still available for 2011-2013. The subsidy can be as high as 95% of the project cost,
but not more than HUF 3-120 million, depending on the project type.
Other: education/awareness raising.
Implemented
96
None
Effects and impacts
Not quantifiable.
II.9.2. EE and environmental training materials for schools
Education at schools is the most important tool of awareness raising. The relevant regulation
(Governmental Decree 243/2003 Korm. on the National Basic Curriculum) ensures that
already in the elementary schools environmental protection, sustainable development would
be an integral part of the education. The National Basic Curriculum identifies environmental
awareness as one of the key competencies to be developed in students with the aim of
promoting sustainable development of the society. Several of the subjects within the
Curriculum, such as biology, science, geography, chemistry include environment-related
and/or energy related components with sustainability in mind.
Other: education/awareness raising.
Implemented
None
Effects and impacts
Based on NEEAP figures the following effects are estimated.
Table 43 Projected emission reduction achieved by EE and environmental training materials for schools
2010*
2015
2020
2025
0.01
0.03
0.05
0.05
0.030
0.130
0.320
0.570
0.0008
0.0024
0.0040
0.0040
0.0024
0.0105
0.0259
0.0461
*: Estimated realized
II.9.3. Support for information, training and awareness raising, energy advisory
network
97
In the NEEAP it was recognised that practical, expert advice from independent advisors is not
only an effective tool of awareness raising, but can result in direct practical savings if the
advice is implemented. Although advisory services are often provided by the utility
companies themselves, the policy seeks unbiased advisory services and more: organisation of
awareness raising events or campaigns, preferably provided by independent civil
organisations, NGOs. It is expected that the operation of an energy advisory network will
trigger energy efficiency projects, which will utilise the available support schemes. Further
support schemes are also planned to support the implementation of the projects.
However, the implementation of the policy has targeted a wider scope than that: the operative
programme that supports the energy advisory network policy is:
KEOP-6.1.0/A/09-11 and KEOP-6.1.0/B/09-11 Awareness raising, information, training –
campaigns to promote sustainable behaviour
This operative program targets the Hungarian population in general, but the specific target
groups include children (4-15 yo.), the youth (15-28 yo.) families, decision makers of
institutions, political decision makers, teachers, communication experts. The subjects of the
training and information dissemination include energy efficiency, water conservation, climate
awareness, sustainable shopping etc.
Besides local and regional campaigns, the program supports the development and operation of
residential advisory facilities.
The budget of component B, which includes the support of advisory activities, is
HUF 915 million per year between 2011 and 13.
Other: Education/awareness raising.
Adopted
None
Effects and impacts
The foreseen effects are the following.
98
Table 44 Projected emission reduction achieved by support for information, training and awareness
raising, energy advisory network
2010*
2015
2020
2025
0.15
0.15
0.15
0.15
0.45
1.20
1.95
2.70
0.012
0.012
0.012
0.012
0.036
0.097
0.158
0.218
*: Estimated realised
II.9.4. Training for engineers, teachers, experts, municipal staff
Other awareness training policies, such as advisory services, training programmes,
information dissemination can only be successful if they are backed up by proper, high-level
expertise. In order to ensure this, even the professionals need to be trained. It is also important
that engineers, artisans involved in the implementation of energy efficiency projects would be
up-to-date on modern technologies and methods. Municipals experts, especially those who
work for the construction licensing authorities are especially important target groups for EE
and sustainability focussed training, but the training of other municipality staff, including
those of municipal institutions is also very important, as the municipalities themselves are
relatively large energy consumers.
Other: awareness raising
Planned
None
Effects and impacts
The following effects are estimated.
99
Table 45 Projected emission reduction achieved by training for engineers, teachers, experts, municipal
staff
2010*
2015
2020
2025
0.12
0.12
0.12
0.12
0.36
0.96
1.56
2.16
0.010
0.010
0.010
0.010
0.029
0.078
0.126
0.175
*: Estimated realized
Minimum criteria and labelling of household appliances
Labelling of household appliances is a key tool of awareness raising and a precondition of
other household-appliance related policies, such as support for procuring highly efficient
equipment (II.3.8.2 or II.3.8.3) to be successful. The following regulation is effective in
Hungary in this regard:
 Decree 4/2002.GM (effective since 2003, amended in 2004) on information provision
about the energy consumption of household light sources
 5/2002.GM (effective since 2003) on energy efficiency criteria of refrigerators and
freezers and their certification:
 6/2002.GM (effective since 2002) on information provision about the energy
consumption of combined washing machine - driers:
 6/2002.GM (effective since 2002) on information provision about the energy
consumption of dishwashers
Regulatory
Implemented
Effects and impacts
Table 46 Projected emission reduction achieved by minimum criteria and labelling of household
appliances
2010*
2015
2020
2025
0.08
0.08
0.08
0.08
0.24
0.64
1.04
1.44
0.018
0.018
0.018
0.018
0.055
0.146
0.238
0.330
100
II.9.5. Labelling of household boilers, air-conditioning equipment, water heaters
The policy to define minimum criteria (II.3.8.1) shall be coupled by providing proper
information to the public about the efficiency and energy performance of these two important
household appliances. Similarly to the other equipment discussed in the previous point (0),
shifting consumers‘ preference towards more efficient equipment can only be successful if
clear, easy-to-understand information is provided.
Other: awareness raising
Planned
Sales data
Effects and impacts
The following effects are estimated.
Table 47 Projected emission reduction achieved by labelling of household boilers, air-conditioning
equipment, water heaters
2010*
2015
2020
2025
0
0.09
0.1
0.1
0.0
0.3
0.8
1.3
0.000
0.007
0.008
0.008
0.000
0.024
0.065
0.105
101
III. Projections of Greenhouse Gas Emissions
III.1. Fuel combustion
This chapter covers GHG emissions from fuel combustion. The first part discusses heat
energy consumption and the related emissions, whereas the second part deals with emissions
from electricity and heat generation. It is important to note that emissions from district heat
production are calculated in the first part of this chapter, but accounted for under the heading
of ―electricity and heat sector‖.
III.1.1. Heat energy consumption
Total heat energy consumption is distributed among the following sectors: industry,
residential and service sectors and agriculture. Approximately 35-45% of the total energy is
consumed in the form of heat, as the following figure shows.
Figure 19 Heat energy consumption (PJ) and its share in total primary energy consumption (%), 19902009
650
55%
50.9%
620
51.5%
600
50%
597
47.7%
48.0%
47.3%
47.1%
44.7%
550
44.9%
44.9%
44.1%
44.1%
44.8%
45%
44.0%
43.8%
42.5%
41.2%
530
515
500
509
508
40%
508
496
494
482
487
487
37.7%
37.3% 37.4%
493
483
476
475
467
450
35%
421
420
400
30%
Share in total primary energy consumption
Heat energy consumption, PJ
46.1%
400
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
20%
1992
300
1991
25%
1990
350
Source: Eurostat
The contribution of the various sectors is depicted in the following figure. The most important
sectors are the households and services (69%) within the total consumption.
102
Figure 20 Distribution of the heat energy consumption in 2009, PJ and %
Petroleum Refineries; 25;
6%
Coke Ovens; 3; 1%
Iron and Steel; 18; 5%
Non-Ferrous Metals; 5;
1%
Services; 84; 21%
Chemical and
Petrochemical; 13; 3%
Non-Metallic Minerals; 16;
4%
Other; 13; 3%
Food and Tobacco; 12;
3%
Paper, Pulp and Print; 4;
1%
Agriculture/Forestry; 16;
4%
Households; 191; 48%
Source: Eurostat
GHG emissions forecast is based on the following method (see Figure 21). First, the heat
energy consumption of all sub-sectors are forecast (TJ) and in parallel the aggregate RES
share in the heat energy consumption (%) is determined. By multiplying aggregate
consumption and RES share total RES consumption (TJ) are derived. This is distributed
among the various sub-sectors taken into account at the distribution of RES consumption in
the last three years, while the share of other fuels is calculated on the basis of historical
distribution. Finally, GHG emissions of the various sub-sectors are calculated by using the
respective emission factors.
103
Figure 21 GHG emissions calculation methodology
Individual projections of heat energy consumption
Petroleum
refining
Manufacture of solid fuels
and other energy industries
Iron and
steel
Non-ferrous
metal
Chemicals
Agriculture
Pulp, paper
and print
Food processing,
beverages and tobacco
Non-metallic
minerals
Other
industrial
Residential
Services
Total heat energy consumption
between 2010-2025
Average non-RES share of the
various sub-sector and the
various fuel between 2007-2009
Emission factors of
the various fuel types
RES share between 2010-2025
Yearly
RES consumption
Projected non-RES share
of various
sub-sectors and fuel types
Average RES share of the different
sub-sector between 2007-2009
Projected RES share
of the various sub-sector
between 2010-2025
GHG emissions of the various
sub-sectors between 2010-2025
104
III.1.1.1. RES share
An important input of emissions calculation is the share of renewables in the heat energy
consumption. In the WOM scenario RES share remains at its current level over the next 15
years. The WAM scenario uses the heat RES target defined by the National Renewable
Energy Action Plan (NREAP), i.e. 18.9 % by 2020. In the WEM scenario the RES share in
2020 is lower, i.e. the level defined by Renewable Directive. The following figure shows the
assumed RES shares in the various scenarios.
Figure 22 Historical (1990-2009) and forecast (2010-2025) RES share in heat energy consumption in the
three scenarios
25.0%
22.0%
20.0%
18.9%
19.5%
WAM
16.8%
15.0%
WEM
10.0%
Historical
8.3%
8.3%
WOM
5.0%
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
0.0%
Source: Eurostat
III.1.1.2. Petroleum refining
Total heat energy consumption of petroleum refineries stabilized around 36-40 PJ between
1990 and 1999 and interestingly did not collapse after 1990. However, 2000 brought a sharp
decrease to 27 PJ and it fluctuates around 22-27 PJ since. Similarly to the economic collapse
of 1990, the financial crises of 2009 did not affect the heat energy consumption of refineries.
105
Figure 23 Heat energy consumption of petroleum refineries between 1990 and 2009, TJ, NCV
45 000
40 000
39 964
38 666
39 259 39 583
37 886
36 604
37 253 37 112
36 960
35 950
35 000
30 000
27 271
TJ, NCV
27 147
25 020
25 617
24 950
24 244
25 000
23 894
22 028
21 877
22 007
20 000
15 000
10 000
5 000
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
0
Source: Eurostat
It is assumed that the average heat energy consumption of the last nine years (24.1 PJ) is a
good estimate for the future.
106
III.1.1.3. Iron and steel
Three major drops can be observed in the heat energy consumption of the iron and steel
sector: the first one in 1990, the second one in 1996 and a third one in 2009, each bringing a
30-40% reduction. Except for these dramatic changes it was quite stable within each period:
between 1991 and 1996 it was around 42 PJ, while between 1996 and 2008 around 23-27 PJ.
In 2009 the heat energy consumption dropped to 18.5 PJ. A consequent recovery period is
assumed so that heat energy consumption will reach the level of 2005 by 2015. Since then a
similar growth rate for crude steel production (see in the industrial processes chapter) is
assumed.
Figure 24 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the iron and steel
sector, TJ, NCV
70 000
60 000
40 000
30 000
20 000
10 000
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
50 000
Source: Eurostat
107
III.1.1.4. Non-ferrous metal
Heat energy consumption of the non-ferrous metal sector was quite stable between 1997 and
2008 (6-7 PJ). Due to the economic crisis in 2009 it dropped to 4.5 PJ. The same is assumed
in the iron and steel sector: quite a fast recovery by 2015, followed by an increase due to
higher crude steel production.
Figure 25 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the non-ferrous
sector, TJ, NCV
9 000
8 000
7 000
5 000
4 000
3 000
2 000
1 000
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
6 000
Source: Eurostat
108
III.1.1.5. Non-metallic minerals
Heat energy consumption of non-metallic sector has been determined by clinker, lime, lime
and dolomite, glass, bricks and ceramics production. Between 1991-2008 heat energy
consumption of these sub-sectors was quite stable, as the following figure shows. Due to the
economic crisis of 2009, heat energy consumption decreased by more than 30%. A moderate
increasing trend is forecast till 2025.
Figure 26 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the non-metallic
minerals sector, TJ, NCV
45 000
40 000
35 000
25 000
20 000
15 000
10 000
5 000
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
30 000
Source: Eurostat
109
III.1.1.6. Chemicals
Heat energy consumption of the chemical sector was very volatile in the past: while in 1990
and 1997 it exceeded 30 PJ, two years later (in 1992 and 1999) it dropped below 25 PJ. In the
last five years it fluctuated at 13-17 PJ. A relatively slow recovery is assumed from 2009 level
i.e. it will reach the average consumption of 2005-2008 only by 2020.
Figure 27 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of chemical sector, TJ,
NCV
35 000
30 000
20 000
15 000
10 000
5 000
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
25 000
Source: Eurostat
110
III.1.1.7. Food processing, beverages and tobacco
The first half of the 1990s brought about a sharp decrease in the heat energy consumption of
food processing, beverages and tobacco sector. Then it was stable until the early 2000s when
it started to decline. It is assumed that the heat energy consumption of this sector will be
characterized by a slow increasing trend until 2015, when it will reach the average energy
consumption level of 2004-2008. No significant change is expected in the heat energy
consumption of this sector.
Figure 28 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the food processing,
beverages and tobacco sector, TJ, NCV
40 000
35 000
30 000
20 000
15 000
10 000
5 000
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
25 000
Source: Eurostat
111
III.1.1.8. Pulp, paper and print
Heat energy consumption of pulp, paper and print sector increased threefold from 1990 to the
mid-1990s, peaking at a level of 5.8 PJ. This was followed by a stagnating period until the
economic crises when it dropped to 3.5 PJ. It is assumed to be followed by a recovery period
up to 2015 but no growth from that time on.
Figure 29 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the pulp, paper and
print sector, TJ, NCV
7 000
6 000
4 000
3 000
2 000
1 000
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
5 000
Source: Eurostat
112
III.1.1.9. Manufacture of solid fuels and other energy industries
The total heat energy consumption of manufacturing of solid fuels and other energy industries
sectors is quite small: in 2009 it was below 3 PJ. It is assumed that by 2015 it will reach the
average of the last four (2006-2009) years and remain constant from that time on.
Figure 30 Historic (1990-2009) and forecast (2010-2025) heat energy consumption of the manufacture of
solid fuels and other energy industries, TJ, NCV
4 000
3 500
3 000
2 000
1 500
1 000
500
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
TJ, NCV
2 500
Source: Eurostat
113
III.1.1.10. Other industrial sectors
Other industrial segments consist of the following sub-segments: mining and quarrying,
textile and leather, transport equipment, machinery, wood and wood products, construction
and other non-specifies industrial sub-segment. The following figure demonstrates the heat
energy consumption of these sectors in the last ten years and the projected figure till 2025.
Figure 31 Historic (2000-2009) and forecast (2010-2025) heat energy consumption of smaller industrial
sub-sector, TJ, NCV
20 000
18 000
16 000
14 000
Non-specified (Industry)
Construction
Wood and Wood Products
Machinery
Transport Equipment
Textile and Leather
Mining and Quarrying
10 000
8 000
6 000
4 000
2 000
20
24
20
22
20
20
20
18
20
16
20
14
20
12
20
10
20
08
20
06
20
04
20
02
0
20
00
TJ, NCV
12 000
Source: Eurostat
114
III.1.1.11. Agriculture
Heat energy consumption of the agriculture sector has been decreasing since 1990 from over
40 PJ to 15.8 PJ in 2009. It is assumed that this decreasing trend will continue till 2025 but at
a smaller rate.
Figure 32 Historic (1998-2009) and forecast (2010-2025) heat energy consumption of the agriculture
sector, TJ, NCV
30 000
25 000
y = -4035.9Ln(x) + 28204
R2 = 0.8472
15 000
10 000
Historic
5 000
Forecast
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
0
1998
TJ, NCV
20 000
Source: Eurostat
115
III.1.1.12. WEM and WAM scenarios in the industrial sectors
In the previous sections the projected heat energy consumptions of the various industrial
segments under the WOM scenario have been determined. In the WEM and WAM scenarios in some sectors - further energy reduction programs are assumed. All profitable reduction
measures of the HUNMIT model are taken into account6. In the WEM scenario these
investments will be realized fully by 2025, while in the WAM scenario by 2020. Although,
the EUA price will be lower in the WAM scenario, which results in lower energy prices, the
RES consumption is higher. Renewable based energy generation will not be profitable
without support financed by the energy consumers. Altogether these effects will lead to a
higher final energy price in the WAM scenario, which results in lower energy consumption
(or more energy efficiency investments). The following table shows the average heat energy
consumption reduction in the WEM and WAM scenarios.
Table 48 Heat energy consumption reduction in WEM and WAM scenarios compared to the WOM
scenario, %
WEM
WAM
2015
2020
2025
2015
2020
2025
Petroleum Refineries
2.7%
5.3%
8.0%
4.0%
8.0%
8.0%
Iron and Steel
4.0%
8.0%
12.0%
6.0%
12.0%
12.0%
Chemical and
Petrochemical
1.3%
2.7%
4.0%
2.0%
4.0%
4.0%
Non-Metallic Minerals
5.0%
10.0%
15.0%
7.5%
15.0%
15.0%
Food and Tobacco
2.0%
4.0%
6.0%
3.0%
6.0%
6.0%
Textile and Leather
2.0%
4.0%
6.0%
3.0%
6.0%
6.0%
Paper, Pulp and Print
1.7%
3.3%
5.0%
2.5%
5.0%
5.0%
Transport Equipment
2.7%
5.3%
8.0%
4.0%
8.0%
8.0%
Machinery
2.7%
5.3%
8.0%
4.0%
8.0%
8.0%
Non-specified (Industry)
2.3%
4.7%
7.0%
3.5%
7.0%
7.0%
Source: Calculations based on HUNMIT model
6
Short decsription of the HUNMIT modell can be found in the Appendix.
116
III.1.1.13. Residential sector
III.1.1.13.1
Energy consumption of the residential sector
Electricity and heat consumption of the residential sector accounts for a significant share
(30% in 2008) of total energy consumption.7 The domestic energy balance (published by
Energy Center) and international statistical data (Eurostat and Enerdata – which are partially
based on the former source) quote around 230 PJ in 2008.8 The figure below indicates the
historical trends of energy consumption.
Figure 33 Final energy consumption of the residential sector
300
250
200
Heat
PJ
Electricity
Oil
150
Bomass
Coal
Natural gas
100
50
0
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: Enerdata
The consumption trend (increasing up to 2003-2005, then decreasing) hides several changes
in the background variables. On one hand, the number of flats has increased from 4 to 4.2
million between 2000 and 2008, in parallel with an increase in the average floorspace (from
74 to 78 m2). Simultaneously, there was an 85% increase in energy prices (measured in real
gas price level in 2005€), having a significant effect on the households‘ energy bills.9
Temperature fluctuations in winter have significant impact on residential energy
consumption, that can easily move it in a +/- 15% range. In subsequent projections for the
7
Source: Enerdata
8
However, this figure is much higher in the household survey (joint research of the Hungarian Statistical OfficeEnergy Centre) that results in a 300 PJ final energy consumption for the residential sector. The difference is due
to the diverging estimation of biomass consumption.
9
Energy expenses grew from 11% to 14.5% in proportion of households‘ income (Hungarian Statistical Office
(KSH): Energy Consumption of Households 2008; in Hungarian)
117
future years average temperature was assumed, where the average temperature (with its
heating degree days - HDDs) of the last ten years were used in the forecast.
III.1.1.13.2
Evolution of CO2 emissions of residential energy consumption
Household CO2 emissions show similar tendencies as energy consumption over the last
decade. Figure 34 shows the direct and indirect emissions of the residential sector. Indirect
emissions are borne by electricity and district heat generation, and as they are accounted for
under ―power generators‖ due to the source-based carbon calculation rules, their savings
appear in the ETS sector.
Figure 34 CO2 emissions of the residential sector between 2000 and 2009 (actual, without temperature
adjustment, thousand tonnes of CO2)
20 000
18 000
16 000
14 000
kt CO2eq
INDIRECT EMISSIONS
12 000
10 000
8 000
DIRECT EMISSIONS
6 000
4 000
2 000
0
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: Enerdata
After a strong upward trend characterising CO2 emissions up to 2003, the trend reversed in
2004. On the one hand, this was partially due to the drop in coal and oil consumption in
parallel with the dynamic upswing of solid biomass (firewood); on the other hand, data show
the decline of total energy consumption since 2006. Interestingly, the decline did not coincide
with the beginning of the financial crisis of 2008, therefore the existence of increasing energy
efficiency/energy saving can neither be underpinned nor denied. Due to the relatively small
amount of information available on the energy savings of investments, the exact impact of
public support schemes for housing retrofits is not known. Temperature adjusted consumption
indicates that the majority of decreasing consumption in the period is simply due to higher
temperature. The next section gives an overview of the most important information available
on energy efficiency programs.
118
III.1.1.13.3
Residential energy saving schemes between 2006 and 2009
Residential energy-related state support exists since 2001 in Hungary. Although there are a
number of examples of refurbishment programmes (e.g. KEOP – Environment and Energy
Operative Programme, KIOP: Environment Protection and Infrastructure Operative
Programme) financed by other sources, the majority of different schemes for household
energy savings are operated by the Energy Centre10. The programmes have undergone
significant changes: whilst initially the applicants had a relatively large room in choosing the
level of energy refurbishment, the use of funds got tightened in two aspects. Firstly,
programmes have been moved towards complex refurbishment, namely it had to be ensured
that the energy category of the flats increased by at least one grade after renovation. If the
energy certification of a flat/building reached level B11 as a result of the refurbishment, then
the applicant was entitled to get a bonus payment. This way the programme encourages more
complex energy efficiency investments at higher quality. On the other hand, as it was
necessary to make both preliminary and subsequent energy efficiency survey, it also provides
more reliable information. Thus, the measurability of programmes increased, in parallel with
the ex post evaluation of their effectiveness. The table below sums up the available data on
the energy efficiency programmes (NEP: National Energy Saving Plan; ZBR EH: Green
Investment System Energy Efficiency Subprogramme).
Table 1: Main features of NEP and ZBR residential energy saving programmes (constant 2008 HUF)
Programme
code
Number of
applications
received (piece)
Amount of
funds
claimed
(Bn HUF)
Preferential
loan claimed
(Bn HUF)
Total
investment Number of
contracts
s claimed
(piece)
(Bn HUF)
Amount of
funds
contracted
(Bn HUF)
Total
investments
contracted
(Bn HUF)
NEP 2006
3 106
1.10
.-
3.92
2836
0.99
3.48
NEP-2007
5 284
1.28
3.32
8.92
3202
0.74
5.34
NEP 2008
6 541
2.27
1.21
9.42
4701
1.65
6.67
NEP 2009*
3 683
1.21
0.44
4.18
2344
0.79
2.65
ZBR-EH
2 363
4.20
0.69
12.29
881
1.21
3.40
ZBRPANEL
795
27.35
0.00
59.38
16
0.61
1.36
Source: Energy Centre
* Preliminary data: does not reflect the applications evaluated in the whole year
10
Energy Centre, www.energiakozpont.hu/index.php?p=230
Governmental Decree 176/2008 introduced energy efficiency certification of buildings (in colloquial: green
card for flats), which categorises the currently existing buildings to 10 grades, similarly to electronic appliances,
from A+ to – I. Buildings under construction need to meet category C at least since 2009, and from 2012
onwards it will also be required to use it in the case of rented and leased flats.
11
119
The table indicates a steady growth in the number of applications and an increasing amount of
the associated total investments12. It is important that in parallel with NEP 2009, two
subprogrammes of ZBR were launched. Within the ZBR system (ZBR panel subprogramme
in particular) the proportion of tender winners is much lower as compared to total submitted,
supposedly due to higher documentation standards. The peak of total investments realised
with financial support was only 6.67 billion HUF (yearly amount, 2008) out of which the
governmental contribution was 1.65 billion HUF. This is an important benchmark in the
assessment of total future investment needed to exploit the potential within residential energy
savings. Since 2008 preferential loans are available. The proportion of preferential loans
within total investments is very volatile.
Table 49 Data by residents (constant 2008 HUF)
Number of flats Average support
with investments
per flat
(piece)
(HUF)
Average loan
per flat
(HUF)
Average investment
per flat
(HUF)
NEP-2007
2 036
365 917
1 632 951
2 626 259
NEP 2008
3 053
541 006
395 491
2 184 367
NEP 2009
1 745
447 920
255 277
1 522 682
Source: Energy Centre
The average investment per flat is between 1.5 and 2.5 million HUF, which was usually
accompanied by 360-540 thousand HUF support (Table 49). The drop in the 2009 values is
influenced by the crisis, but other factors could have contributed, too.
III.1.1.13.4
The review of residential GHG abatement potential of the HUNMIT model
There is a consensus between experts and studies that there is a significant energy saving
potential in residential energy consumption in parallel with huge greenhouse gas emissions
abatement opportunities (Novikova-Ürge-Vorsatz (2008)13, Csoknyai interview, KSH 2010).
This is also reflected by the data of the HUNMIT model (Novikova and Ürge-Vorsatz
prepared the model for residential buildings). The model examines the following groups of
options for pre-2005 buildings (altogether over 2000 measures not accounting the appliances):

insulation of the external wall

insulation of cellar

insulation of roof
12
Energy efficiency and renewable energy investments (both eligible for support) are distinguished in the
statistics only since 2006 therefore the pre-2006 period is not included.
13
Novikova - Ürge-Vorsatz (2008): CO2 reduction opportunities and cost in the Hungarian residential sector (for
the Ministry of Environment and Water, KVVM) (in Hungarian)
120

replacement of windows

efficiency increase of individual boilers.
In contrast, two options are investigated for post-2005 buildings:

construction of passive energy buildings

the average efficiency increase of investments in individual boilers.
During the present analysis the following modifications were carried out in the HUNMIT
model that was also used in the previous submission:

The energy prices of the original HUNMIT were out-dated as it used constant prices
over the time period. This has been updated by the proposed energy prices of the
report (based on the PRIMES model results).

The MAC calculation of the model was further improved, in order to take full account
of the savings contributable to the measures. In the present version the optimal choice
of the measures depend on adapted net present value calculations to cover the whole
lifetime of the measures.

To reflect the scarcity of financial resources, a profitability index was also applied to
the various measures to put them in order according to their cost effectiveness. This
enables the modeller to choose the most efficient measures in case of the financial
resources are scarce.

Savings from heating – either from better insulation or from the use of more efficient
boilers – and savings from electric appliances are treated separately, as according to
the EU methodology they represent savings in different sectors. Electricity and district
heating savings are attributed to the respective power sector, and only the remaining
savings are attributed to the residential sector.
III.1.1.14. Buildings of the commercial/institutional sector
III.1.1.14.1
Introduction
Based on the definition of the HUNMIT model, building stock of the commercial/institutional
sector refers to a highly mixed group including buildings for educational, health, public
administration (i.e. central governmental and municipalities‘) and commercial purposes, as
well as hotels and restaurants. The commercial/institutional sector was characterised by a
final energy consumption of 111 PJ in 2009. Gas consumption accounts for half of it, while
one third originates from electricity consumption. District heating has shown a steep
downward trend (~11%) and this is supplemented by nearly disappearing consumption of oil
and solid fuels (coal and lignite) over the last five years. A further important factor to be
121
mentioned is that commercial/institutional account for more than a quarter of the final
domestic electricity consumption.
After peaking in 2004 and 2005, consumption is characterised by a steady downward trend, in
parallel with a significant decline in gas consumption. This was coupled with a fall in district
heating, therefore the two, mainly heating-related energy sources have shown the largest
drops.
Figure 35 Energy consumption in the commercial/institutional sector
160
140
District heating
Oil
Coal and lignite
Natural Gas
Biomass
Electricity
120
PJ
100
80
60
40
20
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
0
Source: Enerdata
After 2004, a steep downward slope can be observed in CO2 emissions. Total CO2 emissions
have shown almost a 30% fall between 2004 and 2009 (see Figure 36).
122
Figure 36 Evolution of CO2 emission in the commercial/institutional sector
12000
10000
total emissions
k t CO2
8000
Indirect
6000
4000
Direct
2000
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
0
Source: Enerdata
Direct emissions (fossil fuel consumption used for heating purposes) of the
commercial/institutional sector were characterised by a downward trend since 2004, whilst
indirect emissions (linked to electricity and district heat consumption) declines moderately
since 1996.
III.1.1.14.2
Abatement options
The HUNMIT model quantifies the heating demand and the electricity consumption of
electrical devices of the sector. The model distinguishes one and multi-storey buildings for
educational and healthcare purposes, while smaller and larger subcategories were identified
for public administration and commercial buildings. Sport facilities, cultural premises,
churches, market places were excluded from the model as their consumption is negligible
within the total commercial/institutional sector. The HUNMIT model is based on international
data on total floorspace (airspace), on heating demand per square meter, on future tendencies
of growth, as well as on the own data and estimations of the author (Novikova -Ürge-Vorsatz
2008, Ecofys 2009).
The two major energy consumption types of the sector are heating the airspace (mainly by
natural gas fired central heating and district heating) and the energy consumption of electric
devices (especially devices used in offices and cooling). For heating options, the HUNMIT
model follows a similar methodology to the one used for residential buildings. It outlines the
possible abatement options and then puts these abatement options in cost-efficiency order.
Abatement options are similar to the ones applied in the residential building sector, but this
123
section of the model excludes hot water production from the abatement options. In the case of
savings in heating, the model does not assume any energy saving opportunities in commercial
buildings, as these buildings were recently built therefore their construction technologies are
considered relatively modern. In the case of buildings with own boilers, the HUNMIT model
calculates with more detailed options, while it uses aggregate measure packages for buildings
with district heating or individual room heating. The model outlines 91 types of measures for
modelling the renovation of heating systems and insulation of public buildings.
With regard to electronic devices, as the commercial/institutional sector is the main user of
these devices (such as computers and monitors, printers and other office devices – like faxes,
scanners, etc., air conditioning and ventilation, lighting, etc.), the model investigates several
device packages. Since energy savings of these devices are electricity-related (hence ETS
saving), these are removed from the options in the calculations.
Firstly, the model builds up a ‘half-frozen‘ scenario in which the only energy efficiency
increase originates from the replacement of ageing devices with new ones. Afterwards, it
outlines the total abatement potential for the commercial/institutional sector – as seen in the
case of the residential sector.
Similar steps were followed as in the case of the residential sector when recalculating the
results of the HUNMINT model, namely:

The abatement options related to electronic office devices were removed, as these are
related to electricity consumption thus these are not quantified in this sector.

Price levels are revised according to the proposed EC levels.

Net present values of various measures were determined based on energy savings over
the whole lifespan and on total real investments.

On the basis of the above, a financial profitability indexes were calculated which rank
the various options by taking into account the net payback of measures as well as cost
efficiency.

Upon the above calculations, energy saving and CO2 abatement opportunities were
calculated for the economically efficient (with positive net present value) options of
the commercial/institutional sector.
III.1.1.15. WOM, WEM and WAM scenarios in households and services
One of the main conclusions of the previous chapters is that both the residential and the
commercial/institutional building sectors have a very significant GHG abatement potential.
The most significant obstacle in realising this potential is the lack of available resources.
Historical data (size of insulation investments) and survey results on investment attitudes
show that the energy efficiency improvement in housing would be suboptimal without state
124
intervention in the following ten years. Accordingly, our scenarios are framed by the
resources available.

WOM scenario. Starting from the real 2009 emissions from the building sector (both
in the residential and commercial/institutional sector) the growth rates assumed in the
original HUNMIT model were applied, which considered demographic trends and the
turnover of the building stock. The heating energy need and the corresponding
emission rates are calculated on the basis of an average HDD (heating degree day)
years for the future. It also has to be noted, that in the report emissions form the
electricity and district heating are excluded, as they are accounted in their respective
sectors.

WEM scenario. Definition of the WEM scenario consists of two parts. First the
regulations relevant to the energy consumption of buildings had to be translated to
measures that the model could handle. These regulations include the regulation on the
energy performance of the buildings, as well as the energy certificates system (see
PAM section II.3.7 for details), which are used in the model to set the energy
performance level of the measures for the retrofitted existing and for new buildings.
The second part of this modelling work was to estimate the financial resources
provided by the existing supporting mechanisms collected in the PAM (section II.3.7.3
on the ZBR, Panel and ROPs for institutional and public buildings). The financial
resources available for a building retrofit programme in the scenario are set according
to the estimated the available revenues from ETS quota sales (370 m€), where half of
it is assumed to be spent on programs on buildings efficiency. The estimated average
yearly subsidy of this scenario is 180 million €, which accounts for 48 billion HUFs.
A subsidy intensity of 50% is assumed, i.e. 50 of the 100 units of investment cost are
paid as a state subsidy or preferential loan. This support intensity has been estimated
by current studies (Negajoule 2011, Envincent 2011) as the necessary minimum to
engage households in retrofit investments. This also means that the frame amount of
48 billion HUFs could induce investments of close to 100 billion HUFs. This
investment size includes the additional investments, namely the projects in addition to
the BAU projects (autonomous investments).

WAM scenario: In the scenario it is assumed, that a more ambitious program is
financed from central budget, where the total achievable retrofit investment level
further increases, and increases to close to 200 billion HUFs, as this is the sector
where most of the cheapest energy saving measures exists according to the HUNMIT
model and the relevant assessments. The sources for these programmes are the quota
revenues and additional sources of private and state financing. This amount of
financing is required to achieve the energy reduction targets set in the NREAP of
Hungary for the heating/cooling demand.
125
It is furthermore assumed that the resources available are allocated between the two
subsectors (residential buildings and the building stock of the commercial/institutional sector)
in a cost effective way (no earmarking). For these cases, the discount rate is set to 6%
(adequate to the social discount rate), since it is assumed that the above mentioned resources
are available at state budget level. The most important uncertainties in the WEM and WAM
scenarios are the evolution of the ETS quota price and the decision on the share of quota
revenues to be spent on these programmes.
It has to be noted that energy savings connected to electricity consumption (subsidizing more
energy efficient freezers (PAM II.3.8.2. section), promotion of CFL and other efficient
lighting equipments (PAM II.3.8.2) and the minimum efficiency on office equipment (PAM
II.3.9.4) that are related to electricity savings are accounted separately in order to include
these savings in the electricity generation sector. Thus savings achieved by these measures
will appear in the power sector savings and not at the respective residential and institutional
sectors.
Based on these assumptions, the energy consumption and the GHG emissions of the three
scenarios (WOM, WEM and WAM) are computed that are shown in the following table.
Energy savings are accounted as the sum of all economically feasible measures of the model
realizable with the available budget line in the WEM and WAM scenarios over the period of
2011-2025. The corresponding fuel mix changes are calculated as described in the chapter.
Table 50 Energy consumption in the WOM, WEM and WAM scenarios (PJ)
2008
2010
2015
2020
2025
WOM
77.8
96.7
98.3
100.1
101.6
Commercial/Institutional WEM
77.8
96.7
87.9
80.6
73.8
WAM
77.8
96.7
85.5
76.8
69.0
WOM
191.9
198.2
201.0
201.9
201.2
WEM
191.9
198.2
191.8
187.4
185.0
WAM
191.9
198.2
186.1
174.2
164.4
Residential
126
III.1.1.16. Emission factors
Different emission factors are used in the various sub-sectors. Five main fuel types are
calculated with: solid, liquid, gas, renewable and district heating. Renewables emission
factors are zero, while the emission from district heating production is accounted for under
the heading of ―electricity and heat sector‖. The following figure shows the emission factors
of the various fuel types in the analyzed sub-sectors.
Figure 37 Emission factors of the various fuel types in the analyzed sub-sectors, CO2t /TJ
120.0
100.0
Liquid Fuels
Solid Fuels
Gaseous Fuels
60.0
40.0
20.0
Service
Households
Agriculture/Forestry
Non-specified
(Industry)
Construction
Wood and Wood
Products
Machinery
Transport Equipment
Paper, Pulp and Print
Textile and Leather
Food and Tobacco
Mining and Quarrying
Non-Metallic Minerals
Chemical and
Petrochemical
Non-Ferrous Metals
Iron and Steel
Coke Ovens
0.0
Petroleum Refineries
CO2 t /TJ
80.0
Source: Hungarian GHG Inventory
127
III.1.1.17. GHG emissions projections
The following figure depicts the carbon dioxide emissions from the heat energy consumption.
Figure 38 Carbon dioxide emissions from heat energy consumption in the three scenarios, kt CO2
25 000
20 000
15 000
kt CO2
Services
Households
Agriculture
Industry
10 000
5 000
0
2008
WOM WEM
WAM WOM WEM
WAM WOM WEM
WAM WOM WEM
2010
2015
2020
2025
WAM
It has to be noted that the GHG emissions of these sectors are not confined to carbon dioxide,
but include methane and N2O as well.
128
III.1.2. GHG emissions from district heat production
As it has been mentioned GHG emissions from district heating are reported in the electricity
sector but can be calculated from heat energy consumption. The district heating consumption
has already been determined14 in the various scenarios and with the emission factors the GHG
emissions can be calculated. It is assumed that the transformation and the distribution losses is
20%. In the WOM scenario all the district heating plants are fuelled by natural gas. In the
WEM and WAM scenarios it is assumed that by 2025 the share of RES based DH plants is
19% (WEM) and 22% (WAM), while the rest are natural gas. The following figure depicts
the carbon dioxide emission from district heat production.
Figure 39 Carbon dioxide emission from district heat production in the various scenarios, CO2 kt
4 500
4 000
WOM
WEM
Carbon dioixde emission, kt
3 500
3 000
WAM
2 500
2 000
1 500
1 000
500
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
0
III.1.3. GHG emissions forecast in the electricity sector
This section gives a detailed analysis of the GHG emissions forecast in the electricity sector.
Only GHG emissions related to electricity generation are included i.e. emission from heat
production (as well as the GHG emission from the heat production part of the cogeneration
plants) are not analysed.
First, the key parameters of the three emissions scenarios - WOM, WEM and WAM - are
defined, followed by the introduction of the regional power market model developed by
REKK, which computes the emissions of the scenarios. Finally, the results are presented.
14
It is derived similar to other types of fuels.
129
III.1.3.1. Definition of various scenarios
The three scenarios differ in quota price, in share of renewable sources, electricity
consumption and the expected commissioning year of the new Paks NPP units.
III.1.3.1.1 Assumptions on quota prices
The recommended carbon prices of DG CLIMA are used, which are depicted in the following
figure.
Figure 40 EUA price in different scenarios
35.0
32.0
30.6
30.0
29.2
27.8
26.4
25.0
25.0
WOM
WEM
WOM
24.0
23.0
22.0
21.0
20.0
20.0
€2008/t
18.6
17.2
15.8
15.0
14.4
13.0
13.1
13.2
13.3
13.4
13.5
14.1
14.7
15.3
15.9
16.5
16.9
16.7
17.1
17.3
17.5
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
13.0
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
10.0
5.0
0.0
2010
Source: DG Climate
III.1.3.1.2 Future electricity consumption in the modelled scenarios
The annual electricity consumption is estimated by a regression calculation based on
historical data of electricity consumption changes and GDP changes. The historic GDP values
are taken from the Hungarian Central Statistical Office (KSH), while the forecasts of several
institutes were utilized when forecasting future GDP. Up to 2014 the forecasts of five
institutes were used, including Ministry for National Economy (NGM)15, IMF16, National
Bank of Hungary (MNB)17, OECD18, and Economist Intelligence Unit (EIU)19. Until 2014
15
Source: http://www.kormany.hu/download/5/b4/10000/Szechenyi-2010-01-14%5B1%5D.pdf, January 2011
Source: http://www.imf.org/external/np/sec/pn/2011/pn1115.htm, February 2011
17
Source: http://www.mnb.hu/Kiadvanyok/mnbhu_inflacio_hu/mnbhu_inflation_20101201, November 2010
18
Source: http://www.oecd.org/document/61/0,3746,en_2649_33733_2483901_1_1_1_1,00.html, November
2010
19
Data disclosure: August 2009
16
130
real GDP growth estimate was derived from the average of the mentioned forecasts, while
after 2014 the EIU forecast was used as seen in the following figure.
Figure 41 Historical and forecast real GDP growth
8%
6%
Forecast
Real GDP growth
4%
2%
0%
-2%
Historical
-4%
-6%
-8%
1990
1995
2000
2005
2010
2015
2020
Source: OECD, IMF, MNB, Economist Intelligence Unit, KSH, NGM
The following figure shows the real electricity consumption in Hungary between 1991 and
2009, the temperature adjusted consumption and the forecast electricity consumption until
2025.
131
Figure 42 Historical, adjusted and forecast gross electricity consumption, 1991-2025, GWh
60 000
53 348
50 000
48 466
43 792
Historical
40 000
GWh
39 670
30 000
Forecast
Adjusted
20 000
10 000
0
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
Source: Hungarian Energy Office (MEH), REKK estimation
When forecasting electricity consumption, our assumptions were based on the relationship
between the historical GDP and the electricity consumption figures and thereby assumed that
energy efficiency measures will be realised to the same extent as in the base period of the
estimation, between 1999 and 2009. However, it is important to examine the impact of the
expected considerable additional energy efficiency investments on the future electricity
consumption. Other important factors that could have significant impact on the future are
electricity consumption of heat pumps and electricity consumption of electrical cars. While
energy efficiency investments decrease the electricity consumption, heat pumps and electrical
cars increase it. In the following these factors are examined and the final forecast electricity
consumption in the three scenarios is determined.
III.1.3.1.2.1 Energy efficiency measures in the WEM and WAM scenarios
As a starting point, the results of a comprehensive international study prepared for the EU
Commission20 was chosen that determined - comparing the current energy consumption
methods and the state-of-the-art technologies - what savings can be achieved in the given
sectors based on various assumptions. The study examined three scenarios:
20
Fraunhofer ISI et.al., Study on the Energy Savings Potentials in EU Member States, Candidate Countries and
EEA Countries (2009). The database established as a result of the study is available on the website
http://www.eepotential.eu/.
132

Low policy intensity potential (LPI): The assumption of this scenario was that only
those energy efficiency measures are realised that are profitable under regular market
conditions.

High policy intensity potential (HPI): The assumption of this scenario was that
administrative barriers significantly decrease, furthermore, all the investments are
realised that are profitable at an aggregated level i.e. not at consumer level.

Technological potentials: This scenario ignores the costs of energy efficiency
measures and observes the best available but rationally considerable cases.
The study includes the analysis of energy efficiency measures with regard to electricity
consumption in three sectors: industrial, household and tertiary. All the three sectors turned
out to have significant energy savings potentials that are profitable even on a market basis at a
magnitude of 5.4 TWh by 2020.
Although details of the methods applied in the quoted study are not known and consequently,
hence its findings cannot be debated, these figures are still considered unrealistically high.
For example, energy savings accounting for 5.4 TWh exceed 11% of the projected BAU
electricity consumption in 2020. As a comparison, Hungary in its preliminary National Action
Plan laying down the foundation for the implementation of the Europe 2020 Strategy, aims at
10% total energy savings, which, in the general opinion of the sector, can be fulfilled
primarily by the large-scale reduction of energy consumption for heating purposes.
Accordingly, it is deemed justified to downscale this figure or assume that its realisation takes
longer than 10-20 years. The argument behind these figures are the same as in the heat energy
sector: in the WAM scenario the final electricity price will be higher compared to WEM
scenario, which will result in a lower electricity consumption or more energy efficiency
investments will be realized. In the WOM scenario zero additional energy savings from
energy efficiency investments are assumed. These numbers are consistent with the results of
the HUNMIT model. Energy savings figures are depicted in the following figure.
133
Figure 43 Energy savings in the electricity sectors in WEM and WAM scenarios, 2010-2025, GWh
6 000
5 695
5 000
4 000
3 796
3 796
GWh
WAM
3 000
2 531
2 000
1 898
WEM
1 265
1 000
0
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
134
It is important to emphasise that in the regional electricity modelling it was assumed that in
the two scenarios energy efficiency projects are realised not only in Hungary but also in all of
the modelled countries. The following figure shows how much energy efficiency
improvements are forecast for the individual countries by the model.
Figure 44 Energy efficiency measures taken into account in the course of regional modelling relative to the
gross electricity consumption in 2020,%
6.0%
5.0%
%
4.0%
3.0%
2.0%
1.0%
0.0%
AL
AT
BA
BG
CZ
GR
HR
HU
ME
MK
PL
RO
RS
SI
SK
III.1.3.1.2.2 Heat pumps
Widespread use of heat pumps increases electricity consumption significantly. According to
the Hungarian NREAP by 2020 heat pumps will generate 6 PJ heat. To produce one Joule
heat energy from heat pumps, it needs 0.25 Joule electricity. If the target set in the NREAP is
reached, then electricity consumption will increase by 417 GWh. In the WEM scenario, when
the NREAP is not in force, it is assumed that half of the energy from heat pumps will be
realized, so the electricity growth is only 208 GWh by 2020. In the WOM scenario no
significant heat production from heat pumps are assumed. The following table demonstrates
the electricity growth due to heat pumps.
Table 51 Electricity consumption of heat pumps in different scenarios, GWh
WOM
WEM
WAM
2010
0
0
0
2015
0
104
208
2020
0
208
417
2025
0
255
509
135
III.1.3.1.2.3 Electrification in the transport sector
Rate of electrification is mainly dependent on the European-wide policies and measures
(PAMs), not really on the Hungarian PAMs. Until 2020 zero electricity consumption growth
is assumed due to the electric cars. Between 2020 and 2030 the optimistic PRIMES figures
are accepted, which assume that 9% of the fuel consumption in the transportation sector is
based on electricity (full electrical cars or plug-in hybrid cars). According to this figure the
consumption growth could reach 5.5 TWh by 2030. This figure is used in our WAM scenario.
In the WEM and WOM scenarios it is assumed that the whole electrification will be delayed
by five years, which means no electricity consumption growth is assumed because of the
electrification in the transport sector during the period.
III.1.3.1.2.4 Electricity consumption
Based on the previous analyses, the forecast gross electricity consumption in Hungary in the
different scenarios is shown in the following figure.
Figure 45 Gross electricity consumption in different scenarios, TWh, 2010-2025
55.0
53.3
53.0
50.9
TWh
51.0
49.0
48.5
47.0
46.1
45.0
43.8
49.8
WOM
WEM
WAM
45.1
42.6
43.0
42.1
41.0
39.0
37.0
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
35.0
It is visible that from 2023 the consumption in the WAM scenario exceeds the electricity
consumption in the WEM scenario, due to the higher electrification rate and the faster spread
of heat pumps.
III.1.3.1.3 Renewable-based electricity production in various scenarios
Scenarios also differ in the amount of renewable-based electricity (RES-E) production. The
NREAP modifies the share of renewables specified by the Renewable Energy Directive from
13% to 14.65% (these figures relate to the total energy consumption and not exclusively to the
136
electricity sector). It is assumed that in the WEM case the 13% - as specified in the Directive is realized, while in the WAM case the full NREAP target share of 14.6% is realized. In the
calculation of this scenario, this 1.65% growth is assumed uniform in the relevant
consumption sectors. Considering the RES-E generation these target figures (13% and 14.6%)
translates into 9.4 and 10.9%, respectively. In the WOM scenario it is assumed that the share
of renewable based power generation will not change in the analyzed period, it equals 6.7%.
Figure 46 Share of renewable-based electricity production compared to the gross electricity consumption
between 2010 and 2025 in the different scenarios, %
14.0%
12.7%
12.0%
11.1%
10.9%
10.0%
9.4%
8.1%
8.0%
7.0%
6.7%
6.7%
6.0%
6.7%
6.7%
WOM
WEM
WAM
4.0%
2.0%
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
0.0%
Source: MEH, NREAP, and REKK calculation
As the whole region is modelled, and not only Hungary – in order to capture the trade effects
as well -, it is assumed that the development of RES-E production in other EU Member States
is similar to Hungary. In the WOM scenario, renewable share will not change in the analysed
period, the WEM scenario assumes that the renewable production will be in line with the
requirements of the Renewable Directive, while in the case of WAM scenario, the given
Member States achieve the renewable electricity production amount specified in the
submitted NREAPs.
III.1.3.1.4 New PAKS NPP units
The new draft energy strategy of Hungary includes the construction of new nuclear units in
Paks. It is assumed that in the WOM and WEM scenarios none of the new units will be
commissioned before 2025, while in the WAM scenario it is assumed that one 1000 MW unit
will be commissioned between 2020 and 2025.
137
III.1.3.1.5 Summary of scenarios
In the above sections, a detailed picture is drawn on the assumptions of the parameters (EUA
price, electricity consumption, spread of renewable sources and new nuclear units in Paks) for
all the three scenarios. The following table gives a summary of these assumptions for
Hungary.
Table 52 Assumptions for the various scenarios
EUA price,
€2008/t
Gross electricity
consumption,
TWh
RES-E share, %
WOM
WEM
WAM
2010
13.0
13.0
13.0
2015
13.0
20.0
13.5
2020
13.0
25.0
16.5
2025
13.0
32.0
17.5
2010
39.7
39.7
39.7
2015
43.8
42.6
42.1
2020
48.5
46.1
45.1
2025
53.3
49.8
50.9
2010
6.7%
6.7%
6.7%
2015
6.7%
7.0%
8.1%
2020
6.7%
9.4%
10.9%
2025
6.7%
11.1%
12.7%
No new
unit(s) till
2025
No new unit(s)
till 2025
One new (1000 MW) unit
between 2020 and 2025
New Paks unit(s)
However, it is important to emphasise that these RES-E production figures and the estimated
gross electricity consumption figures for Hungary are contingent on the similar course of
action in other countries of the model.
III.1.3.2. Regional electricity market model
The effect of various scenarios on the electricity market is estimated with the help of a
regional power market model, which simultaneously models the electricity markets and the
commercial flows of Central and South European countries. This model is developed by the
Regional Centre for Energy Policy Research (REKK).
The applied power market model assumes that power plants are price takers, in other words,
(the owners of) power plants assume that changing their production decision does not have
any significant effect on market price. This assumption leads to the equilibrium of efficient
(‗perfect‘) competition applied in microeconomic modelling and to a welfare maximising
market outcome as well.
138
Power plants produce electricity if the marginal cost of their production is lower than the
electricity price in the given country, taking into account the generation capacity constraints
of the power plant.
Market prices are shaped by domestic demand and supply relations, and export and import
factors modifying the former ones. Export-import flows, however, are essentially shaped by
the power price level of neighbouring countries since traders would transport electricity from
cheaper countries to the more expensive ones. Accordingly, analysing the power sector of
several neighbouring countries (and their further neighbours) cannot be avoided at the same
time, which requires the application of a regional power market model. The following figure
depicts the operation of the model.
Figure 47 Model operation
Available
generation
capacity
Input
Marginal
generation
cost
Demand curves
by country
Equilibrium prices
by country
Electricity trade between
countries
Cross-border
transmission
capacity
Output
Model
Supply curves
by country
Production by plant
National supply curves can be set out for each country by determining the marginal costs and
the available capacities of power plants. The result is received by supplementing national
supply curves with cross-border capacities and the demand curves characteristic for the
various countries. The model calculates the equilibrium prices of the countries, the
commercial flows among the countries and also the production of power plant blocks21.
III.1.3.3. Key results
This section gives a detailed analysis on the effects of the various scenarios on the electricity
market including particularly on the electricity mix and carbon dioxide emissions.
III.1.3.3.1 Expected changes in the electricity mix
Total electricity consumption differs for the WOM, WEM and WAM scenarios, as it has been
already demonstrated in the previous sections. The following figure shows, that nuclear units
21
For detailed description of the operation of the model see in the appendix.
139
will produce 14.7 TWh electricity in all cases and years except in the WAM scenario in 2025,
when a new block will be commissioned. Coal-fired power generation will decrease until
2025, when it will totally disappear from the Hungarian energy mix. The amount of
renewable-based energy production is not the output but the input of the model. The share of
RES generation will be between 6-13% in the final gross electricity consumption between
2010 and 2025. Natural gas-fired power production in WAM scenario will be the smallest.
Net import will be quite significant, e.g. in 2020 in the WAM scenario the net import will be
8.4 TWh, which will satisfy nearly 20% of the total yearly electricity consumption.
Figure 48 Electricity mix in 2010, 2015, 2020 and 2025 for various scenarios, TWh
60
50
14.7
14.7
40
14.7
22.1
14.7
3.6
0.1
30
14.7
14.7
4.3
14.7
5.5
14.7
2.6
14.7
TWh
3.2
20
1.8
2.7
3.6
5.9
3.0
3.0
2.9
4.9
32.5
3.4
32.3
28.0
2.7
24.2
22.2
10
14.8
Nuclear
Coal
RES
Natural gas
Net export
6.4
15.9
15.2
13.5
12.1
2.9
1.1
0
-0.1
-2.5
WOM
-4.3
2010
-7.5
WEM
-6.2
2015
WAM
WOM
-3.6
-7.4
WEM
2020
WAM
-8.4
WOM
WEM
WAM
2025
-10
-20
140
III.1.3.3.2 Carbon dioxide emission
Carbon dioxide emission varies between 7.4 and 12.2 million tonnes in the various scenarios.
The emission is essentially determined by the production of gas-fired power plants and the
total domestic consumption: the less the consumption and the natural gas-based electricity
production are, the less the carbon dioxide emission is.
Figure 49 Emissions of electricity producers in 2010, 2015, 2020 and 2025 for various scenarios, thousand
tones
14 000
12 173 12 107
12 000
11 625
10 601
10 455 10 455 10 455
10 000
CO2 emission, kt
9 218
8 632
8 294
8 005
8 000
7 450
WOM
WEM
WAM
6 000
4 000
2 000
0
2010
2015
2020
2025
141
III.1.4. GHG emissions from transport sector
Based on the GHG inventory, transport sector made up 19% of the total GHG emission of
Hungary and one fourth of energy emissions in 2009. This figure excludes the emission of
aviation, which is separately included in the national inventory. However, aviation accounted
for 5% of transport emissions in 2009, while railway transport and navigation were
responsible for a still lower proportion of emissions (2 and 0.02%, respectively). It is
important to note that the 2% share includes only the direct railway emissions (primarily from
diesel engines running on non-electrified lines and used for traction), electricity consumption
is accounted among the emissions of the energy industry. A crucial proportion of transport
emissions (93%) are caused by road transport including passenger and freight transport.
Figure 50 Distribution of transport emissions in 2009, kt CO 2eq
Inland Water; 3; 0%
Rail; 266; 2%
Air; 716; 5%
Road; 12 407; 93%
Consequently, the share of transport in the total emission is significant, and the temporal
evolution of its emission makes it even more important amongst the emitting sectors. The
figure shows that it has been dynamically growing since the bottom in 1994 and nearly
doubled. The emission was declining after the economic transformation of the nineties until
1994, which was followed by a slow rise essentially due to the changes in road transport
emissions. Meanwhile, the fleet was increasing. This period witnessed a large-scale exchange
in fleet resulting in a much more modern fleet composition. Since then, however, the further
improvement of efficiency can purely moderate the extension of transport types of higher
emission (road transport) both in passenger and freight transport by road.
142
Figure 51 Number of cars in Hungary between 1985 and 2009
3 500
3 000
thousand car
2 500
2 000
1 500
1 000
500
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
0
Source: KSH
* The fallback in 1998 is caused by a change in methodology: the total fleet was then adjusted with the number
of withdrawn cars
143
Figure 52 Emissions from transport between 1985 and 2009 (kt CO 2eq)
16 000
14 000
Air
transport
12 000
kt CO2eq
10 000
Inland
Water
Rail
transport
8 000
6 000
4 000
Road
transport
2 000
0
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
The economic crisis had an effect also on the transport sector. There was a drop primarily in
the emissions of road transport and aviation. However, in ten years before the crisis (from
1998 to 2008) the total annual emission of the sector grew by as much as 5%, which exceeds
the emission increase of all the other sectors. Direct emissions of the railway transport were
declining until 2005, which was followed by a three-year stagnation and then an upswing
started again in 2009. The decline is primarily resulted from the railway‘s being driven back
by road transport both in passenger and freight transport.
144
Figure 53 Performance of road and railway transport between 2001 and 2009 (freight tonkm)
40 000
35 000
freight tonkilometer
30 000
Road
transport
25 000
20 000
Rail
transport
15 000
10 000
5 000
0
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: KSH
Emissions of navigation dropped to minor level at the beginning of the nineties. As the
inventory shows, aviation typically grows except for some shorter periods. The growth is
primarily due to increasing income and the evolving low-cost carriers. The data for aviation
emission has so far been an information tool based on the amount of kerosene sold in
Hungary (9672 TJ in 2009). Aviation will fall under the effect of ETS from 2012, therefore it
does not have to be taken into account in the transport sector not falling under ETS.
145
Figure 54 Emission from aviation between 1985 and 2009 (kt CO 2eq)
900
800
700
kt CO2eq
600
500
400
300
200
100
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
0
Source: NIR
Several pollutants are emitted from the combustion of fuels. In general, only CO2 and soot
emissions kept pace with the growing number of vehicles, while the specific values of the
other pollutants diminished. The lead and sulphur-dioxide emissions essentially ceased on the
effect of state regulation.
Road traffic entails methane and nitrogen-oxide emissions in addition to carbon-dioxide from
among greenhouse gases. CH4 and N2O emissions, however, are orders of magnitude lower
than CO2.
Table 53 Emission factors of transport fuels (t/TJ)
CO2
CH4
N2O
Petrol
68.61
0.0110
0.0135
Gas oil
73.33
0.0035
0.0041
Source: NIR 2009
III.1.4.1. Estimation of the future CO2 emission from transport sector
In the following chapters the details of the calculations will be introduced in more details.
Detailed modelling was applied in road transportation for setting up the WOM projection
(passenger and freight), as this is the most important transport mode from both GHG
emissions the point of view and its growing shares. For the GHG abatement options, the
HUNMIT model was applied for the road transport (passenger and freight). For the rest of the
modes (aviation 5%, rail 3% and inland waterways <1% by emissions in 2009) the trend
146
projected in the EU (2010)22 analysis is applied, but the starting year values were updated
(2009 energy consumption and emission values were used, as the 2010 values are not yet
available). By using the above-mentioned trend values for rail and inland waterways, the
projections also get near to the indicative values of the New Széchenyi Plan (introduced in
more details in the PAM), which foresees a growing share of these transport modes. For
railways the plan foresees 20% share for freight and 15% share for passenger transport, while
sets the target to 8% in inland waterways transport. This latter one is an especially ambitious
target, as its share now stands at 4% according to the latest figure of 2009 (Eurostat 2011). To
reach this target the policies mentioned in the PAM document, and also the effects of the
planned EU Danube strategy is required. Concerning the railway freight target, the plan
means the reversion of the trend, which showed an uninterrupted decreasing trend, and
presently stands at 20 %.
In case of the aviation sector, the passenger km values are cross-checked to the latest
Hungarian projections of the Budapest Airport on the number of air travellers. In air transport
no efficiency improvement in the engine technology is assumed, however according to the
source used (EU 2010), the trend of higher utilisation of the flights is carried forward for the
future.
III.1.4.1.1 Road transport modelling
In the estimations a detailed econometric model was applied for the road transportation
(passenger and freight) for the WOM scenario. Car penetration path was projected for private
cars, where the main driving parameter was the GDP, but also a slow convergence to the EU
car ownership level was assumed. In freight transport the statistical analysis showed again the
high importance of GDP growth that determines the transported volume of goods. The impact
of oil prices was also tested, but the impact was not statistically significant. This most
probably is due to the high tax content of the end user price of gasoline, which weakens the
impact of the price signal.
Three scenarios were prepared for the projection of emissions of the transport sector: WOM,
WEM and WAM. The WOM scenario contains the efficiency improvements expected from
the turnover of the fleet. Compared to this scenario, WEM and WAM contain further
reduction potentials primarily for new cars, and assume a larger scale extension of hybrid cars
and the high blending rate of bio-fuels. The scenarios have been prepared in order to examine
only CO2 emission (see above) taking into account the emissions from road transport
(passenger and freight transport), railway transport and navigation. As afore-mentioned, the
emission from the latter two lags by orders of magnitude behind the road transport emission.
22
EC DG Energy: EU energy trends to 2030, 2009 Revision, 2010. ISBN 978-92-79-16191-9
147
III.1.4.1.1.1 Emissions from passenger cars
The method of forecast is not uniform; it takes into account the various characteristics and
demand factors of the subsectors. The emissions of passenger cars are based on a passenger
car stock model, which estimates the average fuel consumption of passenger cars from the
average age of the stock of passenger cars and the consumption data of new passenger cars
sold. Assumptions on car use were made in line with the fuel consumption figures until 2010,
calculating with a lifespan of 19 year on the average. The coefficients of passenger car
penetration were calculated on the basis of a worldwide sample, where a slow convergence is
assumed to this theoretical figure for the period from 2010 to 2015 primarily due to the credit
barriers of households, which restrain passenger car sales from speedy recovery to the level
before the crisis. The table below shows the figures that are used to estimate model
parameters. The value of the average travelled km estimated for 2020 declines due to the
lower mileage of the second cars of households and to the lower population number.
Table 54 WOM scenario parameters for passenger transport sector
2015
2020
New car sales
171 thousand
359 thousand
-from which plug-in hybrid electric vehicles (PHEV), %
1%
5%
-from which electric car, %
1%
2%
Biofuel
5,75%
5,75%
passenger car penetration (passenger car/1000 persons)
325
395
Average petrol consumption of existing cars, l/100km
7.4
6.7
Average diesel consumption of existing cars, l/100km
5.8
5.4
Average petrol consumption of new cars, l/100km
5.3
4.4
Average diesel consumption of new cars, l/100km
4.8
4.0
2010-2015
2015-2020
Efficiency improvements of internal combustion engines
(new cars), % per year
3.5%
3.5%
Change in travelled kilometres, per year per passenger car
%
+1.5%
-0.5%
Passenger car penetration parameters are estimated from a database containing national and
historical data (KSH). The Hungarian passenger car market trends (efficiency improvement
and average fuel consumption of passenger cars) are calculated from EU data 23, while the
figures on electric and hybrid car sales are based on experts‘ estimations. The penetration
level of bio-fuels follows the pattern drawn in the following table, and it follows the National
Renewable Action Plan (NREAP Hungary 2011, see PAM for more details).
23
European Commission: Monitoring the CO2 emissions from new passenger cars in the EU (database)
148
Table 55 Assumed bio-fuel penetration rates (%)
2010
2015
2020
2025
WOM
5.75
5.75
5.75
5.75
WEM
5.75
7.875
10
10
WAM
5.75
7.875
10
12.5
The WOM scenario does not expect huge changes either in the relative prices nor in the tax
structure (assumptions exclude any subsidies to electric and hybrid cars).
It was also assumed that plug-in hybrid electric cars will have a negligibly small market share
up till 2015, and will have a relatively small market share still in 2020. The share of dieselfuelled cars is increasing, which will approximate to the European average (50%) by 2020.
This is, however, the most uncertain element of the estimation: if there is any breakthrough in
technology or costs occurring in that period (the probability of which is low in the current
market environment), the share of plug-in electric cars may hit higher levels. For cost
reduction, the industrial experience was taken as a base, which predicts that the price
advantage of internal combustion engines will still remain significant until 2020. There is a
huge uncertainty around the cost reduction of battery technology, however, considering the
slow changing pace of the Hungarian fleet, the estimated output should not be too sensitive to
this factor. The potential short-term changes of the tax/subsidy system would be much more
important, however, these are not involved in the WOM scenario.
Table 56 Projected passenger car sales between 2011 and 2020 (1000 pieces)
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Petrol
44
57
69
82
96
108
120
131
140
147
Gas oil
31
40
49
59
68
85
106
128
153
179
LPG
1
2
2
2
2
2
2
3
3
4
24
1
1
1
1
2
2
2
3
3
4
Hybrid
0
0
1
1
2
4
6
9
13
18
Electric
0
0
1
1
2
2
3
4
6
7
Total
78
100
123
147
171
203
240
279
318
359
CNG
III.1.4.1.1.2 Emission from trucks
Emissions from the freight transport are calculated on the basis of the consumption of freight
forwarding and aviation based on a GDP-based estimate. In the previous five years, the rise in
fuel consumption of freight forwarding was higher than the GDP-growth. According to the
trends, fuel consumption of freight forwarding will go parallel to the GDP-growth in the
period from 2011 to 2015. The projections assume a 1% decline in GDP intensity for the
period between 2015 and 2020, since the share of diesel fuel consumption is high in Hungary
24
CNG: Compressed natural gas
149
relative to Western Europe, and a service-focused economic growth is assumed for this
period. The assumed average GDP growth is annually 3.4% between 2010 and 2015, and
3.1% between 2015 and 2020 (REKK estimates based on IMF, the Hungarian Central Bank,
EUI, Hungarian Ministry of National Development projections).
III.1.4.2. CO2 emission scenarios
Based on the estimated fuel consumption forecast and its respective emission factors based on
2007 UN data (data.un.org), the GHG emission paths of the tree scenarios were calculated.
Table below shows the estimates on total fuel consumption of the transport sector for the
three scenarios.
Table 57 Fuel consumption in the scenarios (PJ)
1990
2005
2010
2015
2020
2025
WOM
114.0
165.5
173.1
196.7
203.6
209.9
WEM
114.0
165.5
173.1
189.9
191.0
190.8
WAM
114.0
165.5
173.1
184.9
183.1
178.7
Based on the 12.07 million tonne CO2 emission of 2010 (without aviation), the WOM
scenario estimates 14.65 million tonne emission for 2025. As a comparison, WEM includes
12.66 million tonnes, while WAM 11.59 million tonnes.
Figure 55 CO2 emission scenarios, kt CO2eq (without international aviation)
15.0
14.5
14.0
WOM
13.5
WEM
kt CO2eq
13.0
12.5
12.0
WAM
11.5
11.0
10.5
10.0
2008
2010
2015
2020
2025
The time series of historical CO2 emissions prepared on the basis of the National Inventory
(until 2009) and the already estimated WOM scenario starting from 2010 fit well. The 2010
150
estimate is lower than the 2009 data of the inventory (12 256 thousand t CO2). It results from
the verification of the 2008 emission data from various sources: that the energy balance issued
by the Energiaközpont (Energy Centre) and the consumption and emission data of IEA are
higher than the data of the inventory.25 The fallback in 2009-2010 is verified by the fuel sales
statistics of the Magyar Ásványolaj Szövetség (Hungarian Petroleum Association) according
to which sales of petrol dropped by 12.9%, while gas oil sales decreased by 6.2% in 2010
relative to the previous year.26 It is important to know, however, that these figures include
only the retail sales of Member States and exclude both the amounts sold directly through
wholesale and the sales of independent petrol stations.
III.2. Fugitive emissions from fuels
This category includes fugitive methane and carbon dioxide emissions released during coal
mining and handling, and from oil and natural gas activities, mainly at exploration, production
and transmission.
III.2.1. Solid fuels
According to the NIR (2010) surface mining emission factor is zero, while underground coal
mines varies between 0.67-13.065 kg CH4/t depending on the quality of coal. In 2009 the
released methane emission from coal mining was 0.66 kt CH4. The major source of this
emission was the mine in Márkushegy which will be closed by 2015. Due to this, fugitive
emissions from coal mining will be assumed to be zero after 2012.
25
26
IEA Oil Information 2010
www.petroleum.hu
151
III.2.2. Oil
Methane emissions are emitted during oil production, transportation, refining, venting and
flaring, so oil production is the main source of emissions. Oil extraction was 68 PJ in 1995, 44
PJ in 2001, which decreased to 33 PJ by 2009. It is assumed that the production will further
reduce to 26 PJ by 2025 (see Figure 56).
Figure 56 Methane emissions from production, transportation and refining, and from flaring and venting
between 1995 and 2025, kt CH4
4.5
4.0
3.5
Emission from production,
transportation and refining
2.5
2.0
1.5
1.0
Emission from flaring
and venting
0.5
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
0.0
1995
kt CH4
3.0
152
Flaring releases carbon dioxide, too. As CO2 emission is also linked to oil production, its
trend is very similar to that of methane, as the following figure shows. Emission from oil
flaring will be the same in the various (WOM, WEM and WAM) scenarios.
Figure 57 Carbon dioxide emission from oil flaring between 1995 and 2025, kt CO 2
140
120
100
kt CO2
80
Historical
Forecast
60
40
20
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
0
153
III.2.3. Natural gas
Methane emissions are emitted during natural gas production/exploration, transmission,
distribution, storage activities, venting and flaring, while carbon dioxide emission is released
during flaring. The distribution of the methane emission from fugitive emissions related to
natural gas is demonstrated in the following figure.
Figure 58 Distribution of the methane emission in 2009
Flaring; 0.1; 0%
Venting; 2.3; 3%
Storage; 2.1; 3%
Production; 10.2;
13%
Transmission;
18.9; 25%
Distribution;
43.0; 56%
154
Distributing natural gas causes methane emission. The emission can be predicted by forecast
the distribution network length: the longer the distribution system, the higher the methane
emission is. The following figure depicts the length of the distribution system.
Figure 59 Length of the distribution system of natural gas, km
100 000
90 000
80 000
70 000
km
60 000
50 000
40 000
30 000
20 000
10 000
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
0
The natural gas production forecast of REKK (2011) is used to project methane emission
from gas production. According to it, until 2017-2018 the production will be around 80 PJ,
and gradually decrease to 25 by 2020 and further during the 2020s.
It is assumed that natural gas storage activity level will not change significantly, i.e. methane
emission from storage will not change till 2025.
The last component of this category is natural gas transmission activity that can be estimated
by the yearly natural gas consumption, i.e. larger the natural gas consumption, higher the
methane emission is. The three scenarios employ different yearly consumption levels that are
derived from yearly electricity production based on natural gas and the heat energy
consumption.
155
Fugitive methane emissions from natural gas in the various scenarios are shown in the
following figure.27 A very sharp drop can be seen in 2018 caused by the dropping production.
Figure 60 Fugitive methane emissions from natural gas, kt CH 4
78.0
76.0
Historical
74.0
WOM
72.0
kt CH4
70.0
WEM
68.0
66.0
WAM
64.0
62.0
60.0
27
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
58.0
Excluding venting and flaring
156
The pattern of methane and carbon dioxide emissions from venting is very similar, as you can
see in the following figure.
Figure 61 Methane and carbon dioxide emissions from natural gas venting and flaring, kt
35
30
20
Carbon
dioxide
15
10
Methane
5
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
0
1995
kt, CH4 or CO2
25
157
III.3. Industrial Processes
III.3.1. Introduction
Industrial sector emissions are created by non-firing processes related to industrial production,
i.e. combustion borne emissions are reported under the combustion category. The industrial
processes category consists of the mineral products, chemical industry, metal production,
consumption of halocarbons and emissions from feedstocks. In 2009, GHG emissions from
industrial processes accounted for 6.3% of the total Hungarian GHG emissions (excluding
LULUCF) as demonstrated in the following figure.
Figure 62 GHG emissions from industrial processes and its share in total GHG emissions, kt CO 2eq and %
10 000
10.0%
9 000
9.0%
8 860
Share
8.0%
7 083
7 000
6 516
6 302 6 349
5 989
5 510
5 951 5 886
5 814
5 691
6 181
5 592
5 468
6.0%
5 694
5 046
5 000
4 853
5.0%
Emission
4 176
4 099
4 000
4.0%
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
0.0%
1997
0
1996
1.0%
1995
1 000
1994
2.0%
1993
2 000
1992
3.0%
1991
3 000
1990
kt CO2eq
6 000
7.0%
6 506
Share in total GHG emission, %
8 000
Source: Hungarian GHG inventory
158
Since 2005 emissions have decreased significantly, from 7 Mt in 2005 to 4.1 Mt by 2009. In
2009 almost 80% of the emitted GHG from industrial processes was carbon dioxide, 20% are
HFCs, other GHGs are not significant, as it can be seen in the following figure.
Figure 63 Distribution of the different GHGs from industrial processes in 2009
PFC; 1.7; 0%
SF6; 0.0; 0%
HFCs; 831.5; 21%
N2O; 14.8; 0%
CH4; 25.6; 1%
CO2; 3 082.5; 78%
159
The largest sub-sector – from an emissions point of view - in 2009 was mineral products
emitting 1.6 Mt CO2eq. Consumption of halocarbons/SF6 and feedstocks gave 20-20% of the
total GHG emissions of the industrial processes, while chemical industry and metal
production GHG emissions were below 0.5 Mt CO2eq.
Figure 64 GHG emissions of the sub-sectors in the industrial processes in 2009
1 800
1 615
1 600
1 400
kt CO2eq
1 200
1 000
833
855
Consumption of
Halocarbons and SF6
Feedstocks
800
600
473
400
180
200
0
Mineral Products
Chemical Industry
Metal Production
160
III.3.2. Analysis and projections
III.3.2.1. Mineral products
GHG emissions in mineral products consist of emissions from cement production, lime
production, limestone and dolomite use, glass production and bricks/ceramics production. The
figure below shows the carbon dioxide emission of these processes.28
Figure 65 Carbon dioxide emission of mineral products, 1995-2009, kt CO2
3 000
2 500
kt, CO2
2 000
Bricks and ceramics
Glass
Limestone and Dolomite
Lime
Clinker
1 500
1 000
500
0
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
28
Other GHGs are not emitted in these processes.
161
III.3.2.1.1 Clinker production
In the process of clinker production, the correlation between real GDP growth and clinker
production growth rate in the last 15 years are looked up29. Using the relationship between
these parameters and the forecast real GDP growth rate, which is demonstrated in the
previous chapter, the clinker production can be forecast, as shown in the following figure.
Figure 66 Historical and forecast clinker production, kt
3 000
Clinker production, kt
2 500
Historical
2 000
Forecasted
1 500
1 000
500
0
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
In order to calculate the carbon dioxide emission of clinker production, the emission factor of
the clinker production has to be determined, too. According to the Hungarian GHG inventory
one ton of clinker production caused 0.52 ton of CO2 emission in 2009. This emission factor
is assumed to remain constant till 2025.
29
Linear regression was used, where R2 equal 0.65 and real GDP growth rate as a parameter was significant.
162
III.3.2.1.2 Lime production, limestone and dolomite production
Lime, limestone and dolomite production has shown a very similar trend in the last decade to
clinker production. Because of this, the same growth rate is assumed. The figure below shows
the actual production between 1995 and 2009 and the forecast value till 2025. The emission
factor of lime is assumed to be 0.79 t/tCO2, while the limestone and dolomite emission factor
is 0.44 t/tCO2. These figures are equal with the implied emission factors in 2009.
Figure 67 Carbon dioxide emission from lime production and limestone and dolomite production between
1995 and 2025, kt CO2
450
400
350
Limestone and
dolomite
kt CO2
300
250
200
Lime
150
100
50
0
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
163
III.3.2.1.3 Glass
As there is no clear emissions trend in glass production (see the following figure), it is
assumed that the volume of glass production will remain constant for the next one and a half
decade at the level of the 1995-2009 average.
Figure 68 Glass production, 1995-2009, kt
600
500
484
472
457
450
448
426
417
422
433
431
416
404
403
384
400
kt
343
300
200
100
0
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
According to the Hungarian GHG inventory one ton of glass production caused 0.13 ton of
CO2 emission in 2009. It is assumed that this emission factor will not change till 2025. The
emissions of the WOM scenario are described above. In the WEM and WAM scenarios
different levels of technical GHG reductions are assumed, i.e. the use of cullet. According to
the HUNMIT model, the maximum reduction potential is 22.2 kt CO2 (WAM). Although the
EUA price is different in the various scenarios, all of these investments are profitable below
zero or around zero EUA price level, i.e. the reduction is not dependent on the EUA price,
only the attitude of the management of the glass companies. The following figure shows the
CO2 emission of glass production under the various scenarios.
164
Figure 69 CO2 emission from glass production in the three scenarios, kt CO 2
90
Historical
80
70
WOM
kt CO2
60
50
WEM
40
WAM
30
20
10
0
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
III.3.2.1.4 Bricks and ceramics
In the bricks and ceramics production a very dramatic drop was visible in 2008 and 2009, as
the following figure depicts.
Figure 70 Bricks and ceramics production, kt
6 000
5 000
4 841
4 784
4 438
Bricks production, kt
4 217
4 223
4 162
4 000
3 763
3 817
3 277
3 022
3 000
3 019
2 963
2 728
2 300
2 000
1 000
622
0
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
165
Bricks and ceramics sector are expected to recover by 2015 to the 2008 production level and
by 2020 it will reach the average production of 2003-2007. After 2020 a production pattern
similar to clinker is assumed, because the driving factor of these products is the same. The
following figure shows the forecast emission from bricks and ceramics production.
Figure 71 Carbon dioxide emission from bricks and ceramics production, kt CO2
450
400
350
250
200
150
100
50
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
0
1995
kt CO2
300
166
III.3.2.2. Chemical Industry
In the chemical industry carbon dioxide is emitted from ammonia production, N2O from nitric
acid production and a small amount of methane from carbon black and ethylene production.
Natural gas is used in ammonia production as a raw material (not for combustion). The
natural gas consumption reveals no clear tendencies, except the sharp decrease of the last two
years due to the financial crises.
Figure 72 Natural gas non-energy consumption in ammonia production, TJ
12 000
10 845
10 590
10 394
10 000
9 795
9 296
9 290
8 564
8 404
Natural gas usage, TJ
9 360
9 109
8 089
7 750
8 000
7 046
6 319 6 285
6 000
4 000
2 000
0
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: Hungarian GHG inventory, Eurostat
In the forecast it is assumed that in the WOM scenario natural gas consumption will increase
to the average level of 2005-2008 by 2020 and remains constant. The emission factor used is
55.82 t/tCO2. In the WEM and WAM scenario technical GHG emission reductions are
assumed. The four reduction options included in the HUNMIT model can altogether reduce
the carbon dioxide emission by 129.1 kt. This reduction will be achieved by 2025 in the
WEM scenario and by 2020 in the WAM scenario. Although the EUA price is different in the
various scenarios, all of these investments are profitable below zero or around zero EUA price
level, i.e. the reduction is not dependent on the EUA price, only the attitude of the
management of the chemical industry companies. The following figure shows the CO2
emissions forecast of ammonia production in the three scenarios.
167
Figure 73 Carbon dioxide emission in the ammonia production, kt CO 2
700
Historical
600
WOM
500
kt CO2
400
WEM
WAM
300
200
100
2025
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
0
In Hungary nitric acid is only produced by Nitrogénművek. Due to a major JI investment
between 2006 and 2008 N2O emission went down to almost zero from 1.5-1.9 Mt CO2eq.30 It
is assumed that the average emission of 2008-2009 (9.9 kt CO2eq) remains stable till 2025 in
all scenarios.
In 2009 the emission from carbon black and ethylene production was 25.6 kt CO2eq, which is
quite a typical value within the last decade. Consequently, it is assumed that the amount of
methane emission from these processes will not change till 2025 in all scenarios.
III.3.2.3. Metal Industry
Carbon dioxide emission of metal production can be derived from the annual crude steel
production. Production showed quite stable growth between 1995 and 2008 followed by a
very sharp drop in 2009. It is assumed that it will reach the 2005 production level by 2015.
Since 2015 a moderate increase is expected in this sector. The following figure shows the
actual and the forecast production of crude steel.
30
Nitrogénművek Annual Report 2008
168
Figure 74 Historical (1995-2009) and forecast (2010-2025) crude steel production, kt
2 500
1 861
1 963
1 963
1 813
2 011
2 053
2 084
2 107
2023
1 954
2 000
1 989
2021
2 241
2 122
1 776
1 690
1 588
1 500
kt
1 401
1 000
500
2025
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
0
In the calculation the emission factor of the Hungarian GHG inventory (0.13 t/tCO2) is used.
III.3.2.4. Consumption of halocarbons and SF6
The main source of halocarbons emissions are refrigeration and air conditioning equipments
covering 95% of the total emissions in this segment. The rest is emitted in foam blowing, fire
extinguishers and aerosols/metered dose inhalers. Most of these emissions are HFCs, and only
a small part of the emissions are PFCs.
Halocarbons emissions in the refrigeration and air conditioning equipments segment have
shown stable growth since 1995, in average of 60.6 kt CO2eq per year. Unfortunately, no clear
marginal abatement costs are known regarding to halocarbons, but according to expert
forecasts in the WOM scenario the increasing trend will continue until 2015 when a strong
decrease trend will start. In the WEM and WAM scenarios emissions from halocarbons will
not increase in the next five years, and after 2015 a similar trend will be seen as in the WOM
scenario.
169
Figure 75 Historical halocarbon emissions between 1995-2009 and forecast emissions, CO2eq
1 400
1 200
WOM
1 000
CO2eq
800
Historical
WEM
600
WAM
400
200
0
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
III.3.2.5. Feedstocks
This category was created for calculating carbon dioxide emissions from fuels used as
feedstock or other non-energy purposes. The use of fossil fuels as feedstock or for other nonenergy purposes is reported in an aggregated manner by Energy Statistics under ―Non-Energy
Use‖ for each individual fuel. It is an aggregated category because the real consumers of these
fuels are unknown (NIR, 2010). The following figure shows the actual emission between
1995 and 2009 and the forecast value. In the projection it is assumed that the forecast
emission will equal the average of the last five years.
170
Figure 76 Historical carbon dioxide emission of feedstocks between 1995-2009 and the forecast value, kt
CO2
1 400
1 200
1 000
Forecast
kt CO2
800
600
400
Historical
200
2023
2021
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
0
III.4. GHG emissions from solvent and other products
There are four main sources of GHG emissions within the solvents and other product uses
category: paint application, degreasing and dry cleaning, use of N2O for anesthesia and use of
N2O for whipped cream. While in the first two processes carbon dioxide is emitted, in the
other two N2O is used.
Emissions from degreasing and dry cleaning, and whipped cream are not significant:
altogether their emissions are below 5 kt CO2eq in 2009, and the emissions from these
processes are assumed to decrease and by 2025 go down to nearly zero. Assumed carbon
dioxide emission from paint application will be constant in the future at a level of 68 kt CO2,
which is the average of the last ten years. Finally, GHG emissions from anesthesia will also
not change in the future; N2O use will equal 0.94 kt N2O, which is equal with the average of
the last five years.
III.5. Calculations of GHG emissions in agriculture and LULUCF
For the purpose of modelling GHG emissions till 2025 there are three separate models
developed: one is dealing with GHG emissions from agriculture and contains all driving
factors and input data necessary for the calculations. The second model calculates land use
and land use change related to GHG emissions. The third model focuses exclusively on
171
forestry and estimates carbon flux due to both land use related and management related
changes.
III.5.1. Agriculture
First the agricultural model will be described. GHG emissions in the agricultural model
consist of the following emissions:

CH4 emissions from enteric fermentation

CH4 and N2O emissions from manure management

CH4 emissions from rice production

Direct and indirect N2O emissions from soil
In case of enteric fermentation the statistical data on livestock was considered as the main
input. Methane emissions characteristic of certain species were taken from the previous
National Inventory Report 1985-2010 (NIR 2010). These are the CH4 emission factors (EF,
kg CH4/head/yr) summarised in Table 58.
Table 58 Species and their CH4 emission factors, kg CH4/head/yr
Dairy cow
132.7
Non-dairy cattle
57.44
Bulls
82.05
Young cattle
82.05
Buffalo
55
Sheep
8
Goats
5
Horses
18
Donkey and mules
10
Saw
1.5
Boars
1.5
Piglets
1.5
Poultry
0.015
Rabbits
0.08
Sources: NIR, Table 6.5
In case of emission from manure management the following manure management systems
were considered:

Liquid slurry

Sold storage

Pasture, range, paddock
172

Other

Pit storage < one month

Pit storage > one month
The amount of manure managed in these systems was estimated for each year in the period of
2010-2025. This constitutes the second most important input data in this calculation.
In the next step the emission factors characteristic of the different livestock were calculated,
which was based on the data form NIR, too. These results are summarised in the Appendix.
The country and livestock specific emission factors multiplied by the number of livestock in
the actual year and given in Gg31 mean the CH4 emissions from enteric fermentation. The
equation 4.17 from IPCC-GPG32 was applied.
The calculation of N2O emission was also based on livestock numbers and share of manure
managed in each manure management system. However, manure from grazing was separately
calculated. The main determining factors were the N2O-N emissions of the manure
management systems (EF3), and species with specific N excretion (Nex). These factors are
summarised in the Appendix.
Emission from rice cultivation was based on the area of cultivation in the country, type of
cultivation and the given emission factors in IPCC-GPG using equation 4.42. The specific
emission for the country was 20 g CH4/m2, which was multiplied by the cultivated area and
transformed to a Gg/year format.
Emissions from soil were split to direct and indirect emission as given in the IPCC-GPG.
Direct soil emissions consist of nitrogen synthetic fertilisers applied to soil use (FSN), manure
N applied to soil (FAM), nitrogen fixed by N-fixing crops (FBN), and amount of N in crop
residues returned to soil (FCR). Emission from synthetic fertiliser use was calculated by
equation 4.22 in IPCC-GPG. Here the amount of applied N fertiliser was multiplied by the
volatilisation factor (FracGASF), which defines the share of ammonia and nitrogen volatilised
from the applied fertiliser. The volatilisation factor was set to 0.1 according to NIR.
Emissions form manure applications to the soil (equation IPCC-GPG 4.24 in IPCC-GPG)
were calculated by multiplying excreted manure N with the volatilisation factor (Frac GASM).
This was set to 0.2 based on NIR. Manure from grazing was considered here, too. Generally,
it was finally assumed that all manure produced in the country sooner or later will be applied
to soil, since there is no manure burning in the country.
31
Gg = gigagramm = kt
32
IPCC „Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories‖
(abbreviation: IPCC-GPG )
173
N2O emissions from N-fixing crops were estimated by calculating the amount of annual crops
multiplied by the volatilisation factor FracNCBRF (equation 4.26 IPCC-GPG). Factors are given
in the Appendix. Emissions from crop residues were estimated according to their share of Ncontent left on site (equation 4.28 IPCC-GPG). Direct soil emission was estimated by
summing up the N input to the environment from the above sources and multiplied this
amount by the share of N forming N2O. This factor (EF1) was taken from NIR and set to
1.25%.
Indirect N2O emissions were calculated from mineral fertiliser use and manure from grazing
leached and deposited to the soil. In case of deposition the factor of N 2O emissions from
fertiliser and manure was determined by EF4=0,01 (equation 4.31 IPCC-GPG). Emissions
from leaching were determined by the amount of N excreted and the emission factors
FracLEACH = 0,3 and EF5 = 0,025 were taken from NIR.
III.5.2. Land use and land use change
Emissions from this part are also calculated by the IPCC-GPG. Here the following land use
categories were taken into consideration:

Forest

Cropland

Grassland

Wetland

Settlement

Other
Emissions from land use emerge only by the emissions stemming from land use change on
managed land that is extended. That is why a complete land use change matrix is needed. The
matrix used in our calculations is given below.
174
Table 59 Land use change matrix
Forest Land Cropland SA-Cropland Grassland SA-Grassland Wetland Settlements Other Land
Forest Land
Cropland
SA-Cropland
Grassland
SA-Grassland
Wetland
Settlements
Other Land
33
Red cells in the table indicate conversions that are considered in our calculations, forest flux
is calculated in forestry. Emissions from different sinks were calculated in a 20-year horizon.
Carbon storages in case of different land uses and biomass coverage are taken from average
values based on NIR 2010. These changes are summarised in Table 60.
Table 60 Carbon storage changes in biomass and soil, tC/ha
Biomass changes
Grassland converted to cropland
1.88
Cropland converted to grassland
-1.87
Cropland converted to settlement
-5.00
Grassland converted to settlement
-3.13
Soil carbon storage changes
Cropland
Cropland remaining cropland
0.20
Set aside cropland converted to
cropland
-6.75
Cropland converted to set aside
cropland
6.70
Grassland converted to cropland
-13.36
Grassland
Grassland remaining grassland
-2.27
Grassland converted to set aside
grassland
-2.29
Cropland converted to grassland
11.29
Settlements
Cropland converted to settlement
-7.65
Grassland converted to settlement
-9.89
Additionally, perennials - vineyards and orchards - also have to be considered. An
accumulation rate (2.1 tC/ha) in case of an increase in the area of perennials and a biomass
33
SA: Set aside
175
carbon loss (63 tC/ha) in case of area losses of perennials are important factors here. These
together with the values in the table above are then multiplied by the changes in land use
giving the net changes of total carbon stored in biomass and soil. These calculations only
consider CO2 emissions, since other pollutants are accounted in the sphere of agriculture and
because on-site burning is prohibited in Hungary. Emissions from management changes,
however, were not considered in our model.
III.5.3. Forestry
Concerning emissions and sequestration of carbon dioxide in forests a couple of important
factors are elaborated that mainly influence these fluxes. First, the forest area is one of the
most important determinants. Changes in the area can induce considerable changes on both
sides: emissions or sequestrations. The other important factor is the composition of forest by
different tree species, since some species are advantageous in increasing biomass
sequestration while others are less beneficial. The age of forests is also a very important
factor: an old forest has a very limited potential of carbon uptake, while young forests are able
to grow at a much higher pace. Local environmental conditions also highly influence the
growth of forests and thus carbon uptake. Last but not least, human influences like harvest
and different management practices also distort the carbon balance of forests.
Forest harvest was considered in a way that harvested wood is immediately oxidised. For
modelling carbon fluxes in forestry the CASMOFOR model34 was used.
III.5.4. Driving factors
In this section the main input data used for the calculation models will be introduced
according to the anticipated scenarios. There were three scenarios undertaken:

Without measure (WOM) – there are no changes in the policy, thus regulations stay
unchanged from 2009 till end of the period 2025.

With existing measure (WEM) – Policy changes between 2009 and 2010 are
considered, where a shift towards greener alternatives is anticipated. This would result
in applying more environmentally friendly solutions in agriculture.

With additional measures (WAM) – Additional policy changes are considered
including regulations after 2010, too. Here even more radical changes in greening
agricultural production are expected.
III.5.4.1. Driving factors in agriculture
The main driving factors of the calculations are the input data used for the model. These are
the following:
34
http://www.scientia.hu/casmofor
176

Number of livestock between 2010 and 2025

Share of manure managed in the different manure management systems between 2010
and 2025

Area and amount of crop produced between 2010 and 2025

Area of rice production between 2010 and 2025

Amount of applied N fertilisers between 2010 and 2025
Applied amount of N fertilisers in WOM is expected to grow by 16% of the level in 2009 till
the end of the period and will reach 320 kg/year active ingredients. In WAM nitrogen
fertilisers will drop by 9% based on the level of 2009. The need for fertilisers will be more or
less substituted by manure in the growing share of organic agriculture. In the WEM scenario a
middle of these extremes were taken.
The most important agricultural crops will take 3.9 million ha in 2020 according to the WOM
scenario. This area will be only 3.6 million ha in the WAM, i.e. about 300,000 will be
available for alternative uses. The area of cereals is expected to grow by 50,000 ha in WOM
and decrease by 200,000 ha in WAM. Yields are expected to grow more in WOM than in
WAM due to more extensive cultivation technologies in WAM.
Industrial crops will increase in all scenarios, however, at a different pace. WOM will have
the highest increase, whereas WAM is going to show only a moderate growth. This positive
trend is charged to the bill of biofuels mainly.
The decrease in area and yield in the cereal sector is compensated by vegetables in WAM,
thus the yearly amount of these products will moderately increase. On the contrary, the yearly
yields of vegetable production will slightly decline in WOM.
Orchards and vineyards will be more prosperous in WAM than in WOM, so their area and
yield will be slightly increased. Shrinkage will be experienced in the WOM, while in WEM
area and yield can be maintained.
In general, the number of livestock shows a steady downward slope, where exceptions are
only temporal or refer to small husbandry sectors. The most intensive depletion of stock is
anticipated in the dairy sector. This intensity is the most moderate in the WAM scenario.
Although milk production is expected to drop, beef production will develop with similar
intensity in all scenarios.
Sheep livestock will shrink till the end of the period in WOM, while in WAM livestock
number will be stabilised from the middle of the period. WEM scenario is positioned in the
middle. Swine production is expected to drop in all scenarios too, mainly due to high fodder
prices.
177
Poultry production, as an industry-like system, is much less exposed to agricultural policy.
However, animal welfare regulations might hinder the sector in their quick development.
Thus, in all scenarios the numbers are expected to stagnate.
Manure management is estimated by using the statistics of IPPC-authorised big animal
husbandry farms. In this statistics, however, biogas related data are not incorporated. These
data are estimated from the national roadmap of renewable energy production that anticipates
a capacity of 100 MW from biogas in 2020.
Table 61 Summary of expected changes in the input data
Driving factor/input
data
WOM
WEM
WAM
Increase by 16% till
Increase by 7% till
Decrease by 9% till
Fertiliser use
2020 on the basis of
2009
2009
2009
Area of cereals
50.000 ha increment
150.000 ha shrinkage
200.000 ha shrinkage
Yield of industrial
crops
Substantial
development
Average
development
Moderate
development
Yield of vegetables
Moderate decrease
Stagnation
Moderate increase
Yield of pulses
Stagnation
Average
development
Intensive
development
Area of perennials
Steady decrease
Stagnation
Slight rise
Stock of dairy cow
Drastic drop
Average drop
Moderate drop
Beef production
Moderate increase
Middle increase
Intensive
development
Sheep stock
Decrease
After moderate drop
stagnation
After moderate drop
stagnation
Swine stock
Intensive drop
Average shrinkage
Moderate drop
Stock of poultry
N/A
N/A
N/A
Manure management
Moderate increase in
biogas production
Average increase in
biogas production
Ambitious increase
in biogas production
III.5.4.2. Driving factors in land use change
In the land use change calculations the most important factors are the changes of the different
land use over time with regard to the sources of the conversions, too. This was summarised in
the table below.
In WOM arable land is supposed to decrease by 8%, which will be converted to forest and
settlement. 24% of grassland will be converted to set aside grassland, forest and arable land.
178
Table 62 Land use change in the WOM scenario
2009
2020
Change, %
Change, ha
Forest Land
2 039 347
2 172 416
7%
133 069
Cropland
4 776 114
4 399 980
-8%
-376 135
SA-Cropland
457 876
715 223
56%
257 347
Grassland
791 460
602 109
-24%
-189 351
SA-Grassland
406 233
559 605
38%
153 372
Wetland
263 035
268 656
2%
5 621
Settlements
566 751
582 821
3%
16 070
Other land
2 451
2 456
0%
5
Total
9 303 266
9 303 266
0%
0
Table 63 Land use change matrix in the WOM scenario, 2010-2020, ha
Forest
SASASettlement
Cropland
Grassland
Wetland
Land
Cropland
Grassland
s
Forest land
2 039 347
-106 456
Cropland
106 456
4 776 114
SA26 614
SAGrassland
-26 614
-3 738
16 070
3 738
791 460
153 372
-257 347
-153 372
406 233
Wetland
-5 621
Settlements
5 621
5
263 035
-16 070
566 751
Other land
TOTAL
Land
457 876
Cropland
Grassland
257 347
Other
-5
2 172 417
4 399 979
715 223
602 110
2 451
559 605
268 656
582 821
2 456
In the WEM scenario forest area grows by 8%, while cropland does not change. Grassland
decreases by 24%, and set aside grassland grows by 1%.
179
Table 64 Land use change in the WEM scenario
2009
2020
Change, %
Change, ha
Forest Land
2 039 347
2 202 494
8%
163 148
Cropland
4 776 114
4 776 114
0%
0
SA-Cropland
457 876
457 876
0%
0
Grassland
791 460
601 510
-24%
-189 950
SA-Grassland
406 233
410 772
1%
4 540
Wetland
263 035
268 295
2%
5 261
Settlements
566 751
583 753
3%
17 003
Other land
2 451
2 451
0%
0
TOTAL
9 303 266
9 303 266
0%
0
Forest
Land
Forest land
Table 65 Land use change matrix in the WEM scenario
SASACropland
Grassland
Wetland
Cropland
Grassland
2 039 347
Cropland
0
Other
s
Land
-163 148
4 776 114
SA-
457 876
Cropland
Grassland
Settlement
163 148
SAGrassland
17 003
791 460
4 540
-4 540
406 233
Wetland
-5 261
Settlements
-17 003
5 261
5
263 035
566 751
Other land
TOTAL
2 451
2 202 495
4 776 114
457 876
601 508
410 773
268 296
583 754
2 456
The WAM scenario anticipates 11% growth in forest and 4% drop in cropland. Grassland also
decreases by 24%, while set aside grassland, settlement and wetland increases.
Table 66 Land use change in the WAM scenario
2009
2020
Change, %
Change, ha
Forest Land
2 039 347
2 263 675
11%
224 328
Cropland
4 776 114
4 585 070
-4%
-191 045
SA-Cropland
457 876
457 876
0%
0
Grassland
791 460
601 510
-24%
-189 950
SAGrassland
406 233
540 637
33%
134 404
Wetland
263 035
268 295
2%
5 261
Settlements
566 751
583 753
3%
17 003
Other land
2 451
2 451
0%
0
TOTAL
9 303 266
9 303 266
0%
0
180
Forest
Land
Table 67 Land use change matrix in the EXT scenario
SASACropland
Grassland
Wetland
Cropland
Grassland
Forest land
2 039 347
-179 462
Cropland
179 462
4 776 114
SACropland
Grassland
0
-44 866
457 876
11 582
44 866
SA-
-11 582
Grassland
134 404
-134 404
406 233
-5 261
Settlements
-17 003
5 261
263 035
566 751
Other land
TOTAL
Other
Land
17 003
791 460
Wetland
Settlement
s
2 451
2 263 675
4 585 070
457 876
601 508
540 637
268 296
583 754
2 451
III.5.4.3. Driving factors in forestry
In the forestry sector area, the age and harvest of forest were taken into consideration. These
data were taken from the statistics of Official Forestry Service and from the management
plans.
Forest harvest was set to be stable in the WOM scenario and changed in WEM and WAM.
Age composition of Hungarian forests was kept stable over the period of 2010-2020.
Areal changes are set differently in the scenarios, however, the loss of forest area converted to
settlements with a yearly rate of 500 ha was the same. Afforestation was estimated in the
reference scenario to grow by 15,000 ha yearly and in the extended scenario by 20,000 ha
yearly. Wood production was assumed to grow in the reference scenario from 7 mcm to 7.5
mcm and 8 mcm till 2020.
III.5.5. Results
The WOM scenario has the most stable line, while the WEM and WAM scenario has a
steeper downward trend till 2015, a slight increase afterwards and a drop in the last two years
of the decade. Although scenarios were defined in extremes, their results do not differ
substantially from each other. This is because background processes compensate for the
effects of extreme tendencies.
Land use change decreased substantially in this period, where WEM and WAM have similar
results, while WOM shows a less steep drop. In forestry sequestration tends to lessen but
stays more or less stable over the period. Agricultural emissions are slightly but continuously
shrinking in every scenario, although the magnitude of changes differs from scenario to
scenario: WAM will have the smallest values at the end.
181
Figure 77 GHG emissions in the agriculture sector in different scenarios, 2008-2025
10 000
9 000
8 000
7 000
5 234
kt CO2eq
6 000
4 834
4 820
4 820
4 764
4 778
4 913
4 835
5 193
4 579
5 348
4 838
4 467
5 000
Agricultural Soils
Rice Cultivation
Manure Management
Enteric Fermentation
4 000
21
11
11
11
12
12
12
12
12
3 000
1 709
1 709
1 709
2 028
1 471
1 394
1 548
12
1 415
1 313
1 517
2 046
2 046
2 046
1 637
1 771
1 897
2 022
WOM
WEM
WAM
1 379
1 331
2 000
1 000
12
12
1 640
1 778
1 915
WOM
WEM
WAM
12
1 424
1 529
1 656
1 782
WOM
WEM
WAM
0
WOM
2008
WEM
WAM
2010
2015
2020
2025
Figure 78 GHG emissions in the land use, land use change (LULUC) and Forestry in different scenarios,
2008-2020
2008
2010
2015
WAM
WEM
WOM
243
237
240
-2 483
-2 494
-2 505
2020
WAM
WEM
WOM
-2 412
-2 490
-2 578
WAM
WEM
WOM
500
0
152
-500
-1 000
-2 402
-2 545
-2 708
kt CO2eq
-1 500
-2 000
-2 500
LULUC
Forestry
-4 145
-184
-94
-177
-47
-92
-78
-3 000
-3 500
-4 000
-4 500
182
III.6. Waste
III.6.1. Solid waste
This section is to present an estimation of greenhouse gas emissions of the Hungarian solid
waste management sector. Carbon dioxide and methane are produced in the course of the
treatment of waste, and their share from the total global emission is not significant but cannot
be neglected. From the global anthropogenic methane emission 3-19% can be ascribed to the
biogas from landfills. (US EPA, 1994)
III.6.1.1. Waste management policies defining greenhouse gas emission
The quantity of the waste production and the proportions of different waste management
methods (landfill, incineration, recycling and prevention) may be influenced fundamentally
by the following policies until 2025:

Prevention will be a more stressed priority. Hungary's waste management policy tries
to emphasize the importance of this device.

Recycling will be growing in several areas. The European Union's new waste
management framework directive35 set a mandatory target level of 50% for recycling
of glass, metals, paper and plastics of MSW by 2020.

From the point of view of GHG emissions it is important to increase recycling of
biodegradable waste.

EU accession results in a quick closing process of old landfill sites without state-ofthe-art environmental technologies. Modern regional landfills equipped with leachate
control and biogas utilisation technologies took their place.
According to estimates some 1.4 billion cubic meter biogas is produced annually in Hungary.
A previous study estimates (COWI, 2009) a 175 mcm/years (12.5%) exploitable landfill gas.
However, practice shows that biogas utilisation investments rapidly spread in the country.
III.6.1.2. Waste management data and trends
III.6.1.2.1 Non hazardous waste from production
Decrease in the amount of non-hazardous waste from production is a European and domestic
tendency. The source of this trend in Hungary is the political and economic transition, and
that the most waste intensive sectors like mining and metallurgy have lost their economic
weight. 40% decrease was caused by closing up of old firms born in the centrally planned
35
Directive 2008/98/EC of the European Parliament and of the Council of 19 November 2008 on waste and
repealing certain Directives
183
economy. Additional modernisation of the production technologies would be a driving force
in the next decades.
Figure 79 Amount of non-hazardous wastes from production
30
27.5
25
24.5
22.7
20.5
Mt
20
20.2
20.0
15
10
5
0
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: COWI, 2009
Industrial non-hazardous waste was 27.5 million tonnes in 2000, and only 20 million tonnes
in 2008. A considerable part of this quantity is mining waste, slag from power generation and
metallurgical technologies, and mud of sewage treatment.
The typical manner of treatment of these wastes is disposal (with a proportion of 60%).
Recycling (rate is at 29%), incineration (1-2%) and other treatments (9-10%) have a minor
role.
184
Figure 80 Resource productivity in Hungary, EU-15 and EU-27 countries, €/kg, 2000-2007
EU15
EU27
Hungary
Source: GKI, 2010 - Eurostat based
It is clear from the above figure, that Hungarian economy has a potential for minimising
waste production via increasing resources productivity. The prevention of waste output can be
achieved by applying more effective production technologies.
Forecast until 2025: The production of non-hazardous solid waste will decrease in the future,
but at a slower rate than in the period of 1990-2010. In every five years, non-hazardous waste
production may decrease with about 1 million tonnes.
In waste management incineration will be marginal, landfilling could decrease slightly, and
recycling has to come nearer to the EU average level.
III.6.1.2.2 Hazardous wastes
The First National Waste Management Plan (OHT-I) of the government forecast 1.3 million
tonnes of hazardous waste production by 2008. According to the waste management
information system (HIR) the produced quantity exceeded this level in 2006, as 1.37 million
tons of hazardous waste were reported.
The extremely low data of 2008 reflected the industrial production recession after the
outbreak of the global economic crisis.
185
Figure 81 Quantity of the hazardous waste
4.0
3.5
3.4
3.0
Mt
2.5
2.0
1.5
1.4
1.2
1.0
1.1
1.0
0.7
0.5
0.0
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: KvVM, 2010
Forecast until 2025: The quantity of hazardous waste will decrease moderately. No essential
change is expected in the treatment structure.
III.6.1.2.3 Municipal solid waste (MSW)
The quantity of the MSW fluctuated greatly in the past two decades, stagnated or decreased at
the end of the 90‘s, and from 2000 it grew mildly. The following figure depicts the
development of the quantity of MSW between 2000 and 2008.
186
Figure 82 MSW quantities, kt
5.0
4.9
4.8
4.7
4.7
4.7
4.6
4.6
4.6
Mt
4.6
4.5
4.5
4.6
4.6
4.5
4.4
4.3
4.2
4.1
4.0
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: COWI, 2009 and KvVM, 2010
It is important to note that in Hungary the production of MSW per capita is smaller than the
average of the EU15 or even the EU27, as the following figure demonstrates.
Figure 83: The production of MSW per capita, kg/person
EU15
EU27
Hungary
Source: GKI, 2010 - Eurostat based
187
COWI made a forecast for the treatment of MSW in 2009. These figures are depicted in the
following table.
Table 68 Forecast for the treatment of MSW with existing measures until 2014, kt
2009
2010
2011
2012
2013
2014
Recycling
748
896
972
1 037
1 082
1 126
Composting
205
317
347
347
347
347
Other recycling
543
579
625
690
735
779
Paper, plastic, metal, glass
recycling
142
159
184
208
242
276
Other recycling and reuse
489
498
545
541
559
560
All recycling
1 237
1 394
1 517
1 578
1 641
1 685
Landfilled
3 240
3 036
2 853
2 835
2 809
2 808
Landfilled organic
1 303
1 175
1 065
1 032
981
953
Source: COWI, 2009
Forecast until 2025: The quantity of wastes may increase or may stagnate because of the
proportion of two contrary effects. The increasing income of the population and increasing
consumption being connected to the former case, while the effect of the prevention measures
and recycling to the latter one.
It is not apparent which scenario will take place. The former government planned an increase
in incineration, the existing government is calculating with a constant share of 9-10% for
incineration in waste management. Prevention and recycling will be a more preferable waste
management method in the future.
III.6.1.3. Waste management scenarios
The following table shows the main assumptions in the various scenarios.
Table 69 Main assumptions in the different scenarios
Proportion of landfill and
Waste production
Tendencies of recycling
incineration
WOM
Production: mild decrease
according to the trend of the
past decade; MSW: mild
increase
Disposal: a decisive share,
burning capacity does not
expand
Disposal decreases significantly,
Production: more vigorous
in favour of incineration and
recycling
decrease; MSW: becomes
Disposal decreases mildly
stable or decrease slightly in
2020-2025
following prevention and
recycling
WEM
WAM
Incineration stays at a constant
level
Is growing mildly, with small late
compared to the EU regulations
Accomplishes the EU regulations
fully
Recycling is growing (but at a
lower rate than in the WEM
scenario)
Prevention is in the focus
188
The highlighted data for waste are the following in the WOM, WEM and WAM scenarios.
Figure 84 Different types of solid waste productions in the various scenarios, mt
30
Municipal solid waste
Hazardous
Industrial non hazardous
25
4.6
4.5
4.5
4.5
4.6
20
0.7
0.6
0.6
4.6
4.6
4.6
4.5
0.6
0.6
0.6
0.6
4.5
4.4
0.4
0.4
16.2
16.0
WEM
WAM
0.5
0.5
mt
4.7
4.5
0.5
0.5
15
10
20.0
19.8
19.8
19.8
19.0
18.7
18.5
18.2
17.2
16.8
17.5
5
0
WOM
2008
WEM
WAM
WOM
2010
WEM
WAM
WOM
2015
WEM
WAM
WOM
2020
2025
Figure 85 Share of solid waste management tools in total waste production, %
100
Landfilled MSW
90
Incinerated
hazardous waste
80
70
%
60
50
76.0
74.0
74.0
74.0
71.0
71.0
71.0
65.0
60.0
65.0
62.0
52.0
62.0
40
30
20
10
11.0
12.0
12.0
12.0
12.0
WOM
WEM
WAM
WOM
15.0
12.0
15.0
21.0
18.0
12.0
15.0
15.0
0
2008
2010
WEM
2015
WAM
WOM
WEM
2020
WAM
WOM
WEM
WAM
2025
The GHG emission data based on the above-mentioned waste management scenarios are the
following.
189
III.6.1.4. CO2 from incineration
Because of the energy utilisation of the burning process, GHG emissions from the Municipal
Waste Incinerator of Budapest (this is the one and only municipal solid waste incinerator in
Hungary) are calculated by the Hungarian Inventory of GHG emissions in the section of
„Energy‖ instead of chapter „Waste‖. Here only the emissions of non-municipal hazardous
waste incinerator plans were accounted for.
Table 70 Carbon dioxide emission from solid waste incineration in million tons, 2008-2025
2008
2010
2015
2020
2025
Without measures
0.1276
0.1176
0.1176
0.1225
0.1225
With existing measures
0.1276
0.1176
0.1470
0.1470
0.1372
With additional measures
0.1276
0.1176
0.1176
0.0980
0.0980
III.6.1.5. CH4 from landfills
The table below shows the methane emission from landfills till 2025.
Table 71 Methane emission from landfills in million tons CO 2eq, 2008-2025
2008
2010
2015
2020
2025
Without measures
2.9024
2.7601
2.2885
1.8113
1.7232
With existing measures
2.9024
2.7601
2.2811
1.6538
1.4071
With additional measures
2.9024
2.7601
2.2762
1.7527
1.5149
III.6.2. GHG emission pathways for wastewater management
III.6.2.1. Sources of wastewater related GHG emissions
According to the sectoral classification of the UNFCCC wastewater, collection and treatment
– together with solid waste management - belongs to the waste sector. Within wastewater
management there are three main sources of GHG emissions:

CH4 emissions from household sewage and industrial wastewater released into public
sewers. The volume of methane is determined primarily by the pollution load of the
wastewater as measured by its biological oxygen demand (BOD) and the technology
of wastewater collection and treatment, especially its aerobic / anaerobic attributes.
The volume of methane that actually gets emitted is determined by the methane
conversion factor (MCF) specific to each technology, and the share of collected and
utilized (combusted) methane, which is to be subtracted.

N2O may be released during nitrification and denitrification, to a small extent from the
wastewater treatment technology, and to a larger extent after wastewater is discharged
into recipient water bodies.

Methane may also be released from industrial wastewater discharged directly into
water bodies. Emissions can be computed based on the chemical oxygen demand
190
(COD) of the wastewater. The key polluting industries are those, where the discharged
wastewater has high organic content, such as food industry and pulp and paper
production.
Secondary (or more advanced) treatment of wastewater will result in residual sewage sludge,
which – without proper treatment – will release methane into the atmosphere. This emission is
to be calculated with an MCF of 0.8 to 1, implying that this is the most potent source of
sewage related GHG emission. Since wastewater sludge is generally taken over by the solid
waste sector and the agricultural sector, most of the methane emissions from untreated sludge
are emitted there. If the sludge is anaerobically treated within the wastewater sector and the
generated methane is combusted to produce energy then the methane emissions from the
wastewater sector will not be impacted, while emissions from sludge disposal in other sectors
should decrease. Moreover, the biogas based energy will replace some fossil fuel based
generation therefore the GHG emissions of the energy sector should also decline36.
III.6.2.2. Baseline emissions in Hungary in 2008
According to the National Inventory Report, the following baseline GHG emissions were
registered in the wastewater sector in 2008:

526.63 GgCO2eq CH4, of which 466 GgCO2eq originates from households (sewage
released to the sewer and sewage treated on site in latrines and septic tanks) and 60.5
GgCO2eq of emissions are of industrial sources;

199.58 GgCO2e of N2O emissions.
An additional 140 GgCO2eq of methane was flared or combusted to generate energy. The
source for this emission is not indicated but it likely stands for sludge based biogas utilization.
The above data is characterised by significant uncertainty as detailed information necessary
for more precise calculations is not available on technologies and pollutants in effluents.
According to the UNFCCC methodology the GHG emissions originating from household
wastewater and industrial wastewater released to public sewers are driven primarily by the
following factors:

Number of inhabitants (more inhabitants mean more pollution, since a uniform BOD
content of 60 g/day/person is used for Hungary based on UNFCCC documentation);
36
Unless the methane is simply flared without energy generation, which is not uncommon at wastewater
facilities, especially during the summer when the energy need of the facilities is below their sludge based energy
producing capacity (electricity sales to the grid are characterized by water utility managers as difficult to
impossible).
191

Ratio of households on the sewer (higher ratio means lower pollution as on-site
treatment has a higher MCF – in fact, an increase in sewer penetration is the most
effective method of GHG abatement in the wastewater sector);

Wastewater treatment technology (untreated or mechanically treated wastewater has
an MCF of 0 while advanced treatment – a mix of aerobic and anaerobic technologies
in Hungary - was given an MCF of 0.15 within the NIR);

Collection of methane from the wastewater treatment technology (while anaerobic
treatment has a higher MCF, the resulting methane is more likely to be collected as the
technology is in a closed system, and methane poses a danger of explosion);

Sludge treatment technology and sludge disposal (use of sludge for biogas generation
will offset GHG emissions elsewhere, while sludge disposed in other sectors will
generate GHG emissions).
Hungarian estimates for N2O emissions from wastewater have traditionally been driven by the
protein consumption of the population with little impact from changes in the wastewater
treatment technologies.
III.6.2.3. Key attributes of GHG emission scenarios until 2025
Using the detailed Hungarian implementation plans of the Water Framework Directive
(WFD) of the EU and the estimated GHG emission abatement costs within the wastewater
sector three scenarios have been created: WOM, WEM and WAM.
Under WOM it is assumed that the implementation of the WFD will progress sub-optimally,
which can be translated into less progress in wastewater collection and treatment,
corresponding to - on balance - higher GHG emissions. No targeted GHG reduction
measures37 are implemented.
Under WEM the WFD is smoothly implemented, resulting in lower GHG levels than under
WOM. Emission reductions are achieved due to large infrastructural changes driven by the
river basin management planning process of the WFD, without consideration of GHG
impacts. Therefore the associated costs of the large scale investments are not accounted for as
GHG abatement costs - GHG abatement is a side-impact of implementing the water
regulations.
The table below provides a summary of the key attributes of the three scenarios. The baseline
is the starting point of the projections, representing year 2008 conditions. The figures for
WOM, WEM and WAM represent year 2015 conditions, assuming that there is gradual
37
Measures the sole purpose of which GHG is abatement.
192
change between 2008 and 2015. It is also presumed that the key attributes of large water
infrastructure do not further change between 2015 and 2025.
Table 72 Key assumptions of the scenarios
Feature
1. Household BOD emissions
Baseline
WOM
WEM
WAM
60
60
60
60
g/person/day g/person/day g/person/day g/person/day
2. Ratio of households connected
to the sewer
70%
84%
89%
89%
3. Ratio of collected sewage that
is not treated or treated only
mechanically before release to
water bodies
30%
0%
0%
0%
4. N effluents from municipal
wastewater treatment plants
(thousand tons/year)
24
34.6
24
24
5. COD content of industrial
effluents (units)
100
100
60
60
III.6.2.4. GHG emission pathways
The GHG emissions of the scenarios have been estimated based on key sectoral changes. The
resulting emissions pathways are in the figure below.
193
Figure 86 Projected GHG emissions by scenarios (kt CO2e/year)
800
750
WOM
GHG emssission, kt CO2eq
700
650
WEM
600
550
500
WAM
450
400
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
350
The emission estimates by source and gas are provided in Table 73. The reduced emissions of
the WAM scenario have been allocated to sources and gases in proportion to the distribution
of emissions among sources and gases under WEM.
Table 73 CH4 emission estimates by gas for key years, ktCO2eq
1. Industrial Wastewater
Without measures
With existing
measure
2. Domestic and Commercial
Waste Water
2010
2015
2020
2025
60.50
60.50
60.50
60.50
452.95 420.31 420.31 420.31
3. Other
0
0
0
0
53.59
36.30
36.30
36.30
Waste Water
439.89 374.63 374.63 374.63
3. Other
0
0
0
0
53.59
36.30
30.25
24.20
With additional
measures
Waste Water
3. Other
439.89 374.63 312.19 249.75
0.00
0.00
0.00
0.00
194
Table 74 N2O emission estimates by gas for key years, ktCO 2eq
Without measures
With existing
measure
With additional
measures
Waste Water
2010
2015
2020
2025
0
0
0
0
224.77 287.73 287.73 287.73
3. Other
0
0
0
0
0
0
0
0
Waste Water
199.58 199.58 199.58 199.58
3. Other
0
0
0
0
0
0
0
0
Waste Water
3. Other
199.58 199.58 166.32 133.05
0
0
0
0
III.7. ETS non-ETS split
By comparing the figures of Hungarian GHG inventory and the company level figures of the
ETS inventory between 2006 and 2009, the share of the ETS for all the sectors and gases can
be calculated. The result – which is the basis of our forecast - is shown in the following table.
195
Table 75 The average share of the ETS coverage in the various sectors and GHG gases between 2006 and
2009
CO2
CH4
N2O
HFCs
PFCs
SF6
Public Electricity and Heat production
98%
0%
0%
0%
0%
0%
Petroleum Refining
100%
0%
0%
0%
0%
0%
Manufacture of Solid Fuels and Other
Energy Industries
90%
0%
0%
0%
0%
0%
Manufacturing Industries and
Construction
95%
0%
0%
0%
0%
0%
Transport
0%
0%
0%
0%
0%
0%
Other combustion sectors
11%
0%
0%
0%
0%
0%
Fugitive emissions form fuels
0%
0%
0%
0%
0%
0%
Industrial Processes except chemical
industry and other
90%
0%
0%
0%
0%
0%
Chemical industry
90%
0%
100%*
0%
0%
0%
Industrial Processes - other
0%
0%
0%
0%
0%
0%
Solvents and other product use
0%
0%
0%
0%
0%
0%
Agriculture
0%
0%
0%
0%
0%
0%
LULUCF
0%
0%
0%
0%
0%
0%
Waste
0%
0%
0%
0%
0%
0%
* Only in the WEM and WAM scenario
Source: Hungarian GHG Inventory and CITL
196
IV. Measures
Relevant
To
Community
Legislation
and
Commitments Under The Kyoto Protocol
(a) information on measures being taken or planned for the implementation of relevant
Community legislation and policies, and information on legal and institutional steps to
prepare to implement commitments under the Kyoto Protocol and information on
arrangements for, and national implementation of, compliance and enforcement
procedures;
Community legislation, policies
2004/101/EC
Kyoto Protocol
project
mechanisms
1996/61/EC
and
2008/1/EC
Integrated
Pollution
Prevention And
Control Directive
2003/66/EC
Labelling
Directive
2005/32/EC
Eco-design
framework
directive
Implementation in Hungary
Implemented by the following legislation:
 Act LX of 2007 on the implementation framework
for the implementation of the UN Framework
Convention on Climate Change and of the Kyoto
Protocol
 Govt. Decree 323/2007 (XII. 11.) Korm. On the
implementation rules of Act LX of 2007
 Act XV of 2005 on the trading with emission units
of GHG
 Govt. Decree 13/2008 (I.30.) Korm. on National
Allocation Plan for 2008-2013 and the detailed rules
of allocation of emission units
 Act LIII of 1995 on general rules of environmental
protection
 Govt. Decree 314/2005. (XII. 25.) Korm. on
procedures of environmental impact survey as and
IPPC licensing
Partly implemented by the following legislation:
 Decree 4/2002.GM (effective since 2003, amended
in 2004) on information provision about the energy
consumption of household light sources
 5/2002.GM (effective since 2003) on energy
efficiency criteria of refrigerators and freezers and
their certification:
 6/2002.GM (effective since 2002) ) on information
provision about the energy consumption of
combined washing machine/driers:
 6/2002.GM (effective since 2002) ) on information
provision about the energy consumption of
dishwashers
Planned measures:
 Labelling of household boilers, air-conditioning
equipment, water heaters
 Govt. decree 217/2007. (VIII. 15.) Korm. on the
ecodesign requirements for energy-using products
and on the general conditions of trade and
compatibility certification
 All decrees that set minimum energy requirements
197
1991/676/EEC
Nitrate Directive
()
1999/31/EC
Landfill Directive,
2000/60/EC
Water Framework
Directive
2001/80/EC
Large Combustion
Plant directive
2001/81/EC
Directive on
national
emissions' ceilings
for certain
pollutants
2002/91/EC
2003/30/EC
Buildings
Directive
Biofuels directive
for equipment or appliance (see previous points)
 Govt. decree 27/2006. (II. 7.) Korm. on the
protection of waters against nitrate pollution of
agricultural origin. (earlier: 49/2001.Korm)
 Decree 59/2008. (IV. 29.) FVM on the detailed rules
of implementing 27/2006. (II. 7.) Korm.
 Decree 43/2007. (VI. 1.) FVM on the publication of
nitrate-sensitive areas according to MePAR
 2nd Nitrate action programme 2008-2011
 Act XLIII of 2000 on Waste Management
 Decree 20/2006. (IV. 5.) KvVM on the rules and
conditions for landfilling wastes and landfills
 Act LVII of 1995 on Waste Management
 Act LIII of 1995 on the General Rules of
Environmental Protection
 Govt. decree 219/2004 (VII.21) Korm. on the rules
of protecting the quality of underground waters
of protecting the quality of surface waters
water catchment area management
 Decree 5/2009. (IV. 14.) KvVM on water
management councils
 Several other pieces of legislation on testing and
quality control of waters, data supply, registries, etc.
 Decree 10/2003. (VII. 11.) KvVM on the conditions
of operating combustion equipment larger than
50 MW input capacity and their emission limits.
 Govt. decree 306/2010 (VII.21) Korm. on the
protection of air
 Decree 7/2003. (V. 16.) KvVM-GKM on the limits
of total emission of certain pollutants
 Govt. decree 306/2010 (VII.21) Korm. on the
protection of air
 Govt. Decree 7/2006. (V. 24. TNM), update in
progress (see II.3.7.1)
 Govt. Decree 176/2008. (VI. 30.) Korm. on the
certification of the energy performance of buildings
 Govt. Decree 2058/2006. (III. 27.) Korm. on the
development of production of biofuels and the
promotion of their use in transport.
 Govt. Decree 2233/2004. (IX. 22.) Korm. on the
national targets for biofuels and other renewables in
198
transport.
Govt. Decree 343/2010. (XII. 28.) Korm. on the
requirements and certification of sustainable biofuel
production.
 Act LX of 2007 on the implementation framework
for the implementation of the UN Framework
Convention on Climate Change and of the Kyoto
Protocol
 Govt. Decree 323/2007 (XII. 11.) Korm. On the
implementation rules of Act LX of 2007
 Act XV of 2005 on the trading with emission units
of GHG
 Govt. Decree 13/2008 (I.30.) Korm. on National
Allocation Plan for 2008-2013 and the detailed rules
of allocation of emission units
 Act LXXXVIII. of 2003 on energy tax
 Act CXXVII. of 2003 on excise tax
 Act LXXXVI of 2007 on electric power
 Govt. Decree 389/2007 (XII.23.) Korm. on
compulsory take-over and feed-in price of electric
power from renewable, waste or cogeneration
 Act LVI of 1995 on environmental levy and the
environmental levy of certain products

2003/87/EC
EU ETS directive
as amended by
Directive
2008/101/EC and
Directive
2009/29/EC
2003/96/EC
Energy Taxation
Directive
2004/8/EC
Cogeneration
Directive
2006/12/EC
Waste Directive
Common
Agricultural
2006/144/EC
Policy (CAP)
Reform, as
modified by
2009/61/EC
2006/32/EC
Directive on enduse energy
efficiency and
energy services
2006/40/EC
Directive relating
to emissions for
air conditioning
Taken into account in preparing the rural development
programmes
Used as basis in preparing the Energy Strategy and the
Energy Efficiency Action Plan.
 Govt. decree 64/2009. (III. 31.) Korm. on the
modification of Governmental Decrees affecting
energy efficiency and energy services (this affects
the implementation decrees of all basic energy
related Acts, [electric power, gas, district heating])
 288/2009. (XII. 15.) Korm on data collection for the
National Statistical System
 Governmental Resolution 1076/2010. (III. 31.)
Korm. on the Updated Energy Efficiency Action
Plan
 Decree 6/1990. (IV. 12.) KöHÉM on operation road
vehicles
 Decree 5/1990. (IV. 12.) KöHÉM on the inspection
199
systems of motor
vehicles
2006/842/EC
F-gas Regulation
()
2008/98/EC
Waste
Management
Framework
Directive
2009/28/EC
RES directive
of road vehicles
 Govt. Decree 310/2008. (XII. 20.) on certain
activities related to F gases and ozone depletion
substances.
Not yet codified and legally implemented, but taken into
account in preparing the NWMP 2009-14.
Not yet codified and legally implemented, but taken into
account in preparing the NCsT, and the sustainability criteria
are already included in the support systems for biofuels.
200
V. Glossary
CFL
Compact Fluorescent Lighting
CHP
Combined heat and power
DH
District heating
DHW
Domestic hot water
EE
Energy efficiency
EHA
Energy Efficiency Credit Fund
EKFS
Unified Transport Development Strategy
ESCO
Energy Service Company
ETS
Emission Trading Scheme
EUME
European Size Unit - unit to describe the potential profitability of
an agricultural enterprise
GHG
Greenhouse gas
GIS
Green Investment Scheme
ha
hectare, unit of area defined as 10000 square metres
HUF
Hungarian Forint (the Hungarian currency)
KÁT
Subsidy provided through the feed-in tariff of electric power
generated from renewables, wastes or cogeneration
M
(as prefix in units
such as in M HUF)
Million
MAVIR
Hungarian Transmission System Operator Company Ltd.
MEH
Hungarian Energy Office
MGSzH
Central Agricultural Office
MND
Ministry of National Development
MSW
Municipal Solid Waste
NCsT
Renewable Action Plan (Hungary‘s Action Plan for the Utilisation
of Renewable Energies 2010-2020)
NEEAP
National Energy Efficiency Action Plan
NÉS
National Climate Change Strategy
NGO
Non-Governmental Organisation
NKP
National Environmental Protection Programme
NSDS
National Sustainable Development Strategy
NWMP
National Waste Management Plan
ROP
Regional Operative Programme
SAPS
Single Area Payment Scheme
SME
Small and medium enterprise(s)
201
SPS
Single Payment Scheme
TAP
Thematic Action Programme
TEN-T
Trans-European Transport Network
TEU
Twenty-foot Equivalent Unit (a measure used for capacity in
container transportation)
TOC
Total Organic Carbon
ÚSZT
New Széchenyi Plan
VET
Act on Electricity
ZBR
Green Investment Scheme
202
VI. References

96/2009 (XII. 9) OGY határozat a 2009-2014 közötti időszakra szóló Nemzeti
Környezetvédelmi Programról [96/2009 (XII. 9) Decree of the Parliament on the
National Environmental Protection Program for the period 2009-2014]

A kapcsolt energiatermelés jelenlegi és lehetséges jövőbeni helyzete Magyarországon
(Current and possible future situation of combined heat and power generation in
Hungary) by KPMG, 2010.

Amann, Markus et. al. (2008) . Methane scenarios for non-CO2 greenhouse gases in
the EU-27. Mitigation potentials and costs in 2020. IIASA.

Amann, Markus. (2009) Methane Emissions Reduction Potentials and Costs.
Presentation. IIASA.

Bartus. G: (2010): Database on the Hungarian waste disposal sites from the fugitive
gas utilisation point of view (manuscript) REKK. (in Hungarian)

Biennial Report 280/2004/EC Hungary, 2009

Cambridge Climate Strategies (2007): M. Sato, M. Grubb, J. Cust, K. Chan, A.
Korpoo: Differentiation and dynamics of competitiveness impacts from the EU ETS;
Working Paper, Faculty of Economics, University of Cambridge; letöltés: 2011.
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
Cló, S. (2010): Grandfathering, auctioning and Carbon Leakage: Assessing the
inconsistencies of the new ETS Directive, Energy Policy 38., pp 2420 - 2430

COM 265/2010: Communication from Commission: Analysis of options to move
beyond 20% greenhouse gas emission reductions and assessing the risk of carbon
leakage
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COWI, 2009: Országos Hulladékgazdálkodási Terv 2009-2014, Megalapozó
tanulmány [Background Study for National Waste Management Plan 2009-2014],
Manuscript, Budapest.

Criqui, P (editor). (2002) Greenhouse Gas Emission Control Strategies. GECS −
Research Project N° EVK2-CT-1999-00010 Thematic Programme: Environment and
Sustainable Development of the DG Research Fifth Framework Programme.
November 2002.

Databases: KSH, Eurostat, Enerdata
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DG TREN (2009a) : TRENDS TO 2030 — UPDATE 2009, PRIMES modell
203

DG TREN (2009b): Study on the Energy Savings Potentials in EU Member States,
Candidate Countries and EEA Countries Final Report EC Service Contract Number
TREN/D1/239-2006/S07.66640

Ecofys (2009a): GHG mitigation scenarios for Hungary up to 2025 Final report
(HUNMIT report)

Ecofys (2009b) Study on European Energy-Intensive Industries – The Usefulness of
Estimating
Sectoral
Price
Elasticities;
download:
http://ec.europa.eu/enterprise/policies/sustainable-business/climate-change/energyintensive-industries/carbon-leakage/files/cl_executive_summary_en.pdf

Envincent Kft (2011): Background calculations to the Hungarian Energy Efficiency
Strategy (non published results)
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for the year 2009 (http://airclimate.eionet.europa.eu/docs/ETCACC_TP_2010_4_EU_GHG_Inv2009.pdf)

EU Commission Decision (2010/2/EU) determining, pursuant to Directive
2003/87/EC of the European Parliament and of the Council, a list of sectors and
subsectors which are deemed to be exposed to a significant risk of carbon leakage;
http://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:001:0010:0018:EN:PDF

EU Commission Impact Assessment (2009) Draft Document accompanying the
Commission Decision determining a list of sectors and subsectors which are deemed
to be exposed to a significant risk of carbon leakage pursuant to Article 10a (13) of
Directive
2003/87/EC;
download:;
http://ec.europa.eu/clima/documentation/ets/docs/exec_summ_ia_leakage_list4_9.pdf

EU Commission Impact Assessment (2010) Accompanying document to the
Commission Decision on determining transitional Union-wide rules for harmonised
free allocation pursuant to Article 10a of Directive 2003/87/EC; download: DG
CLIMATE;
http://ec.europa.eu/clima/documentation/ets/docs/ia_free_allocation_final.pdf

EU Draft Commission Decision (2010) of […]determining transitional Union-wide
rules for the harmonised free allocation of emission allowances pursuant to Article 10a
of
Directive
2003/87/EC;
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DG
CLIMATE;
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pdf
204

FVM, KVVM (2010): Report on the state of municipal waste water treatment
according to the 91/271/EC directive, and its National Implementation Programme. (in
Hungarian)

GKI, 2010: Fenntartható fejlődés évkönyv 2010 [Sustainable development almanac
2010] (ed by Péter Bíró), Budapest: GKI Gazdaságkutató - Tisza Vegyi Kombinát
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Gómez Antonio, Javier Zubizarreta, Marcos Rodrigues, César Dopazo, Norberto
Fueyo (2010): Potential and cost of electricity generation from human and animal
waste in Spain. Renewable Energy, Volume 35, Issue 2, 498-505.
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Grassi, G. (2011): Forest Management projections for EU MS. Elaboration of JRC
based on modeling work of IIASA and EFI. EG LULUCF meeting, Brussels, 7
February 2011.
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Hogg, D., (2001): Costs for Municipal Waste Management in the EU, Final Report to
DG Environment. Eunomia Research and Consulting
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Hourcade, J.C., Neuhoff, K., et. al. (2007): Differentiation and dynamics of EU ETS
industrial competitiveness impacts, Climate Strategies; download; www.climatestrategies.org,

IPCC, 2006: IPCC Guidelines for National Greenhouse Gas Inventories, Volume 5:
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Kohlheb N. – Pataki Gy. – Porteleki A. – Szabó B. (2010): Employment impacts of
the use of renawable energies. Background study to the Hungarian Natioanal
Renewable Action Plan ESSRG Kft. Budapest (in Hungarian)
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KSH (2010): Energy consumption of housholds, 2008(in Hungarian)

KSH Statinfo (2010): KSh internet database,.
http://portal.ksh.hu (in Hungarian)
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KvVM, 2010: Hazánk környezeti állapota 2010 [The environmental state of Hungary
2010], Budapest: Ministry for Environment and Water Management.
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MOL Nyrt (2009): Annual Report; downloaded: 2011. március
http://www.mol.hu/hu/a_molrol/befektetoknek/jelentesek/eves_jelentes/
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NIR, 2010: National Inventory Report of Hungary. URL: http://www.unfccc.int
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Nitrogénművek Annual report (2008):
http://www.nitrogen.hu/index.php?option=com_rokdownloads&view=folder&Itemid=
38&id=173:%C3%A9ves-jelent%C3%A9sek
http://statinfo.ksh.hu/Statinfo;
27.
(in
205

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Hungarian Houshold sector. KVVM (in Hungarian)
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sector; CEU dissertation
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OECD (2004): Addressing the Economics of Waste, Organisation for Economic Cooperation and Development, Paris.
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areas KEOP-2.5.0. projeckt (TED [2008/S 169-226955]). 2009. (in Hungarian)

Pettus, Ashley. (2009) Methane: Tapping the Untapped Potential. Clean Air Task
Force.
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utilization of biogas in Germany. Renewable and Sustainable Energy Reviews Volume
14, 1782–1797.

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levels by Hungary. A UNFCCC számára készített jelentés, Budapest. URL:
http://www.unfccc.int

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Johann Heinrich von Thünen-Institute, Hamburg. Draft working paper, pp. 74.
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
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
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decision for sustainable utility energy management. Water Science and Technology:
Water Supply Vol. 10. Number 5, 2010. p. 721

Szajkó et. al. (2009): Woody biomass for energy use from forestry and energy
plantation in Hungary; Budapest Corvinus University, Regionális Energiagazdasági
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
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206
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
US EPA (2006): Global Mitigation of Non-CO2 Greenhouse Gases.
207
VII. Apendix A: The HUNMIT model: energy consumption and
CO2 emission
Upon the request of the Ministry of Environmental Protection and Rural Development
(KvVM), the HUNMIT model was created in 2009 by a consortium led by consulting
company Ecofys (2009)38. HUNMIT, created for Hungarian specialties, is a model which
gives an estimate of greenhouse gas emissions and emissions abatement potentials until 2025
in the following six sectors:

residential buildings

services/institutional buildings

industry

transport

energy supply and

waste.
The model gives almost 700 methods of emissions abatement, which can be used one by one.
In addition to the already existing technologies, the model takes into account such state-ofthe-art technologies which are not yet in use, however, likely to become mature till 2025. The
model sets a reference scenario for emissions abatement potential and costs between 2005 and
2025. Besides taking into account autonomous efficiency improvements due to stock
turnover, the reference scenario uses detailed energy intensities calculated for subsectors and
applies them for estimated future levels of activity.
The HUNMIT model defines three possible future scenarios of gross residential energy
consumption. Firstly, the reference scenario is called ‘frozen baseline‘, as it excludes
autonomous energy efficiency improvement except for capital stock turnover meaning
household devices and buildings in this context. Therefore, in this case energy saving could
originate from the change of devices at the end of their technical lifespan. The second
scenario is called the ‘actual baseline‘ as it includes the actual energy policy rules in place as
well as the autonomous energy efficiency improvement. The third scenario is called ‘max
reduction‘ in which all economically efficient (estimations based on the model) energy saving
options are included to the highest possible potentials. In addition, an ‘original baseline‘ was
projected which differs from the ‘frozen baseline‘ in that it includes gross energy
consumption, for the sake of comparison. These scenarios were not harmonised with the ones
required by this reporting task, so they had to be redefined and also some modification to the
38
Ecofys 2009: GHG mitigation scenarios for Hungary up to 2025 Final report (HUNMIT report)
208
model was carried out during this application, as they are shown in the respective sectors
(residential and commercial/institutional buildings sector, transport, industry).
Agriculture including forestry was excluded from the HUNMIT model. For this report a
separate agricultural model was applied, that is introduced at the agricultural chapter.
209
VIII. APPENDIX B: Description of the regional power model
VIII.1. Analyzed countries
The figure below shows the countries included in the model divided into two groups: in
countries with yellow background prices are derived from the demand-supply balance. In
countries with blue background exogenous prices are assumed.
Figure 87 Analyzed countries
VIII.2. Demand data
Within each year, the market equilibrium in 24 separate demand periods is modelled. The
total consumption in the analyzed 15 countries for every hour in 2007 is summed up and the
hours are grouped into 24 separate demand periods. The first group represents the lowest load
hours, while the 24th represents the highest load hours.
After classifying the hours into separate demand groups, the individual country observations
for each hour are taken and their average in a given period are calculated. Finally, the average
load for all of the analyzed countries in 2007 is determined and also the ratio of the given load
210
of the demand period to the average load is calculated, which ratio is different country-bycountry.
VIII.3. Supply data
Supply input data consist of production costs and capacities. These will be detailed in the
current subsection. Since short term competition is being modelled, the only relevant costs to
calculate with are variable costs, i.e. those that quickly respond to changes in the level of
output.
As mentioned before, the optimal short run production decision of a power plant depends on
how its marginal (or incremental) production costs compare to the prevailing market price.
The marginal production cost of a given unit is composed of three main components: CO2
emissions cost, fuel cost and variable OPEX.
Figure 88 Marginal cost estimation methodology in the market simulation
EUA (CO2)
price
Fuel type and
price
Generation technology
Estimated heat
rate
CO2 emissions
cost
+
Fuel cost
Estimated selfconsumption
+
Variable OPEX
Marginal production
cost
The fuel cost in each generation unit depends on the type and price of fuel, and the overall
efficiency of electricity generation, which is the product of two factors: the amount of
electricity generated from 1 MWh of primary fuel burnt (fuel efficiency), and the amount of
electricity fed into the network from 1 MWh of electricity generated. The latter factor differs
from unity by the proportional self-consumption of a generation unit. An energy tax element
is also added to the fossil fuel price for EU member countries.
VIII.3.1. Availability and fuel efficiency
The following two tables list the assumed efficiency and availability parameters (based on the
literature and empirical observation) for various power plant types and commissioning dates.
211
Table 76 Gross fuel conversion efficiency factors
Fuel conversion efficiency
Year of
commissioning
Gas/Oil ST
Coal ST/Biomass
1960
37%
35%
1970
39%
37%
1980
41%
39%
1990
43%
41%
50%
2000
45%
43%
55%
2010
47%
45%
58%
2020 (assumed)
49%
47%
60%
CCGT
Source: KEMA (2005)
Table 77 Self-consumption and expected availability of power plants
Plant type
Self-consumption
Availability
Gas/oil-fired steam turbine
5%
90%
Coal/biomass-fired steam turbine
13%
85%
CCGT
5%
90%
Nuclear
6%
95%
Wind
-
20%
The table above also shows the assumed average availability of a unit, i.e. the percentage of
days when it is not under maintenance. For wind turbines, the availability parameter equals
the average utilization rate, since wind generation is a weather-dependent technology.
Since nuclear units are always in base load operation and they are hardly ever the price setting
producers, modelling their fuel costs with a bottom-up approach starting with fuel efficiency
is an unnecessary complication. Instead, a fuel cycle cost estimate of 10 €/MWh is used as the
upper limit of figures cited in the literature. Regarding wind and hydro producers, their short
run marginal costs are assumed to be 0 €/MWh.
VIII.3.2. Secondary reserve
In case of Hungary reserves are taken into consideration, too, but only secondary reserves.
Primary reserves can be provided by most of the participants and the quantity of primary
reserve is quite small, only 10-20 MW per year. While in the case of tertiary reserves power
plants have enough time to react, and it is not only gas-fired power plants that can provide this
type of reserve.
It is assumed that secondary reserves are fully provided by spinning, gas-fired power plants: it
is necessary to be able to decrease the production, which is only possible if the power plants
are spinning, while only gas-fired power plants have as fast reaction time as is required by the
TSO. In the following the amount of necessary secondary reserve is determined.
212
However, to provide a given amount of reserves to the system, power plants must run at an
excess capacity because of minimum utilization requirements. As a result, the minimum
presence of gas-fired capacity in the system is estimated, which turned out to be 441 MW in
the summer of 2009. This value is taken to be the necessary spinning reserve requirement.
VIII.3.3. Fuel-prices
There are three types of fossil fuels to calculate with:

Solid: hard coal, lignite

Liquid: light and heavy fuel oil

Gaseous: natural gas
Liquid fuels are refined oil products. Since the refining process operates with fixed
proportions of output to input, it is reasonable to expect close co-movement between crude oil
and fuel oil prices.
The figure below shows the price assumptions, which are based on DG Clima calculations.
Table 78 Fuel prices, in 2008 real terms
Gas,
€c/GJ
Hard coal,
€C/GJ
Lignite,
€C/GJ
Crude oil,
$/bbl
2010
537.6
226.7
181.3
77.5
2015
602.0
274.9
219.9
94.5
2020
810.2
352.3
281.8
108.1
2025
973.3
390.1
312.1
117.6
Source: DG Climate and REKK calculations
VIII.3.4. Cost of CO2 emission
CO2 emissions costs arise in case of fossil fuelled units (coal-, gas- or oil-fired) in countries
that participate in the EU‘s Emission Trading Scheme (ETS). Burning fossil fuels produces
CO2 emissions for which power plants must possess a corresponding number of EU
Allowance Units (EUA‘s). The number of EUA‘s needed to produce 1 MWh of electricity
depends on the type of fuel used and the efficiency of fuel energy conversion into electricity
(unit heat rate and self-consumption). The table below shows the CO2 emissions of various
fossil fuels. According to the data, a gas-fired unit produces about half as much CO2 as a
lignite plant with the same efficiency.
213
Table 79 CO2 emissions by fuel type
Fuel type
CO2 emissions
[kg/GJ]
Hard coal
93.7
Lignite
112.1
Natural gas
55.8
Heavy fuel oil
77.0
Light fuel oil
73.7
Source: UNFCC
One of the main components of the CO2 cost is the EUA price, which differs in the scenarios,
as it was demonstrated in the main text.
VIII.3.5. OPEX
The final element of marginal cost estimation is the inclusion of the variable part of operating
expenditures. An approximation of these for the potentially price-setting (marginal)
technologies is shown in 0.
Figure 89 Estimated variable operating expenditures by technology and year of build
8
7
Coal /
biomass
6
EUR/MWh
5
Gas / oil steam
turbine, OCGT
4
3
CCGT
2
1
0
1960
1970
1980
1990
2000
2010
2020
Source: Data collection by MOL Hungary
VIII.3.6. Installed capacities in the future
Projected installed capacities are calculated based on Platts Energy in East Europe
publication, which publish detailed lists of the new and expected power plants developments.
Renewable based electricity generation is equal with the figure demonstrated in the NREAPs.
Decommissioning of power plants was more problematic, because it is dependent on not only
age of the power generator, but also hang on the market environment. Sometimes it is worth
to refurbish a power generator, even it is very old. In general, information about the expected
date of decommissioning in a specific power plant is not known, only in some cases. Where
214
no clear information on the date of decommissioning is known, a power plant will be closed
after its lifetime, but at least it will operate till 2012. In coal (or lignite)-fired power plants a
lifetime of 50 years, in the case of OCGT 40 years are assumed, while a 30 years long lifetime
for CCGT is assumed.
VIII.4. Cross-border interconnections
The capacities available for cross-border trade in the model are shown in the following figure.
Figure 90 Existing capacities for cross-border trade (below 1000 MW)
1,000
Default
direction
800
600
400
MW
200
0
-200
-400
-600
-800
Reverse
direction
AL-GR
AL-ME
AL-RS
AT-CH
AT-CZ
AT-DE
AT-HU
AT-IT_N
AT-SI
BA-HR
BA-ME
BA-RS
BG-GR
BG-RO
BG-RS
CZ-DE
CZ-PL
CZ-SK
HR-HU
HR-RS
HR-SI
HU-RO
HU-RS
HU-SK
HU-UA_W
ME-RS
MK-GR
MK-RS
PL-DE
PL-SE
PL-SK
RO-RS
RO-UA_W
SI-IT_N
SK-UA_W
GR-IT_S
HU-Sl
BG-MK
RO-MD
-1,000
Source: ENTSO-E
VIII.5. Neighbouring market prices
Market prices for large Western European markets, such as Germany or Italy are linked to the
crude oil and CO2 prices, as well as the demand period. Smaller outside markets, such as
Moldova or Ukraine, are taken into account as low price import sources for the region.
215
IX. Appendix C: Methane emission factors from manure management
Typical
animal
mass
(average)
VS daily
excretion
(average)
CH4
producing
potential (Bo)
(average)
3
MCF, %
Pasture,
EF
Pit
Pit
storage
<1
month
storage
>1
month
Livestock
(kg)
(kg
dm/head/day)
(m CH4/kg
VS)
Liquid,
slurry
Solid
storage
Dairy cow
650.00
5.24
0.24
0.39
0.01
0.01
7.66
Non-dairy cattle
430.65
2.92
0.17
0.39
0.01
0.01
2.05
Bulls
430.65
2.92
0.17
0.39
0.01
0.01
4.11
Young cattle
430.65
2.92
0.17
0.39
0.01
0.01
0.00
Buffalo
380.00
3.90
0.10
0.01
0.01
0.95
Sheep
NA
0.40
0.19
0.01
0.01
0.25
0.01
0.01
Goats
NA
0.28
0.17
Camel and lamas
NO
NO
NO
0.39
range,
paddock
Other
0.01
kg
CH4/db/év
0.12
0.00
Horses
NA
1.72
0.33
0.01
0.01
1.39
Donkey and
mules
NA
0.94
0.33
0.01
0.01
0.76
Saw
63.83
0.50
0.45
0.39
0.01
0.00
0.39
10.87
Boars
63.83
0.50
0.45
0.39
0.01
0.00
0.39
10.87
Piglets
63.83
0.50
0.45
0.39
0.01
0.00
0.39
10.87
Poultry
NA
0.02
0.32
0.39
0.01
10.87
0.01
0.16
Rabbits
216
X. Appendix D: N2O emission factors of animal manure
management
EF3(S), kg N2O-N/kg N in manure managements system
Livestock
NEX [kg
N/head/yr]
Liquid, Solid Pasture,
slurry storage paddock
Pit
Other
Pit
storage
storage
<1 month >1 month
Dairy cow
131.8
0.001
0.020
0.020
0.005
Non-dairy
cattle
48.3
0.001
0.020
0.020
0.005
Bulls
48.3
0.001
0.020
0.020
0.005
Young cattle
48.3
0.001
0.020
0.020
0.005
Buffalo
70.0
0.001
0.020
0.020
0.005
Sheep
20.0
0.001
0.020
0.020
0.005
Goats
18.0
0.001
0.020
0.020
0.005
Camel and
lamas
0.0
0.001
0.020
0.020
0.005
Horses
60.0
0.001
0.020
0.020
0.005
Donkey and
mules
25.0
0.001
0.020
0.020
0.005
Saw
8.1
0.001
0.020
0.020
0.005
0.001
0.001
Boars
8.1
0.001
0.020
0.020
0.005
0.001
0.001
Piglets
8.1
0.001
0.020
0.020
0.005
0.001
0.001
Poultry
0.6
0.001
0.020
0.020
0.005
Rabbits
4.1
0.001
0.020
0.020
0.005
217
XI. Appendix E: Factors of N2O from plant production
Plant production Res/Crop 1+Res/Crop FracDM FracNCRO/FracNCRBF
Wheat
1.3
2.3
0.850
0.0028
Barley
1.2
2.2
0.850
0.0043
Maize
1.0
2.0
0.780
0.0081
Oat
1.3
2.3
0.920
0.0070
Rye
1.6
2.6
0.900
0.0048
Rice
1.6
2.6
0.850
0.0067
Triticale
1.3
2.3
0.850
0.0028
Other cereals
1.3
2.3
0.850
0.0028
Dry beans
2.1
3.1
0.855
0.0230
Peas
1.5
2.5
0.870
0.0142
Soya
2.1
3.1
0.865
0.0230
Lentils
1.5
2.5
0.870
0.0142
Horse beans
2.1
3.1
0.855
0.0230
Alfalfa seed
1.5
2.5
0.870
0.0142
Forage
0.0
1.0
0.850
0.0142
Potato
0.4
1.4
0.850
0.0110
Other vegetables
0.4
1.4
0.850
0.0110
Sugarbeet
0.3
1.3
0.850
0.0228
Sunflower
1.0
2.0
0.850
0.0150
Rape seed, other
seeds
1.0
2.0
0.850
0.0150
218
XII. Acknowledgment
The Ministry of National Development would like to acknowledge the work of the Regional
Centre for Energy Policy Research and its experts (in alphabetic order: András Kis, András
Mezősi, Zsuzsanna Pató, and László Szabó) in the compilation and development of this
report, as well as the work of the other experts involved (in alphabetic order): Gábor Bartus,
Norbert Kohlheb, and István Kovacsics.
219

III. Projections of Greenhouse Gas Emissions

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