Embed Size (px)
Citation preview
Current situation in greenhouse gas inventory and reporting on policies, measures and projections to UNFCCC and European Commission in the Baltic States and Baltic Sea Region States
Mārtiņš Knite
Janis Brizga
Green Liberty, NGO
2017
2
Contents Abbreviations ............................................................................................................................ 3
Introduction ............................................................................................................................... 5
General description of GHG reporting covered by this report .............................................. 5
1. General comparison of the reporting to EC and UNFCCC in the Baltic States .................. 7
1.2. Annual GHG inventory ............................................................................................... 7
1.3. The 6th National Communication ............................................................................. 10
1.4. 2nd Biennial report ................................................................................................... 14
2. Comparative analysis of specific reporting questions ..................................................... 18
2.2. National reporting system ....................................................................................... 18
2.2.1. National inventory reporting ........................................................................... 18
2.1.2. National System for reporting on policies, measures, and projections .......... 28
2.3. GHG inventory data sources .................................................................................... 31
2.3.1. Uncertainties ................................................................................................... 32
2.3.2. Activity data ..................................................................................................... 34
2.3.3. Confidentiality ................................................................................................. 37
2.3.4. Emission factors ............................................................................................... 37
2.4. Methods for inventory ............................................................................................ 41
2.5. Methods, emission factors and uncertainties for key categories ........................... 43
2.6. Methods for projections .......................................................................................... 45
2.6.1. Structure and contents of reporting ............................................................... 45
2.6.2. Models and methods used .............................................................................. 46
2.6.3. Table of projections ......................................................................................... 51
2.6.4. Table of parameters ........................................................................................ 52
2.7. Approach for PAMs selection and evaluation ......................................................... 54
3. Final conclusions and recommendations ........................................................................ 58
References ............................................................................................................................... 60
ANNEX 1. Emission factors ...................................................................................................... 61
ANNEX 2. NIR methods ............................................................................................................ 66
ANNEX 3. Comparison of Projections items ............................................................................ 72
ANNEX 4. Comparison of projection models reported to EC .................................................. 87
ANNEX 5. Comparison of projection parameters reported to EC ........................................... 90
3
Abbreviations
BENGGI - Baltic Expert Network for Greenhouse Gas Inventory, Projections and PaMs Reporting
BR - Biennial report
COP - Conference of the Parties
CRF - Common Reporting Format
CS - Country Specific
CSB - Central Statistical Bureau
CTF - Common tabular format
D - IPCC default
EC - European Commission
ECE - Economic Commission for Europe
EE - Estonia
EEA - European Economic Area
EERC - Estonian Environmental Research Centre
EF - Emission Factor
EMEP - European Monitoring and Evaluation Programme
EMHI - Estonian Meteorological and Hydrological Institute
EPA - Environmental Protection Agency
EtEA - Estonian Environment Agency
ETSAP - Energy Technology Systems Analysis Programme
EU - European Union
EUA - European Union emission trading allowances
GDP - Gross Domestic Product
GHG - Greenhouse Gas
IPCC - Intergovernmental Panel on Climate Change
IPPU - Industrial Processes and Product Use
KP - Kyoto Protocol
kt - kiloton
LEAP - Long-range Energy Alternatives Planning System
LEGMC - Latvian Environment, Geology and Meteorology Centre
LT - Lithuania
LULUCF - Land Use, Land-Use Change and Forestry
LV – Latvia
M - Model
MEPRD - Ministry of Environmental Protection and Regional Development
MMR - Monitoring Mechanism Regulation
MoA - Ministry of Agriculture
MoEc - Ministry of the Economy
MoEn - Ministry of the Environment
MEPRD - Ministry of Environmental Protection and Regional Development
NC - National Communication
NIR - National Inventory Report
OTH – Other factors
PaMs - Policies and Measures
PS - Plant Specific
RA - Reference Approach
QA/QC - Quality Assurance and Quality Control
SE - Statistics Estonia
SFS - State Forest Service
T1 - IPCC Tier 1
T2 - IPCC Tier 2
T3 - IPCC Tier 3
UN - United Nations
UNFCCC - United Nations Framework Convention on Climate Change
URL - Uniform Resource Locator
WAM - with additional measures
WEM - with existing measures
WOM - without measures
4
Chemicals
CH4 - Methane
CO2 - Carbon dioxide
F-gases - Fluorinated gasses
HFC - hydrofluorocarbon
N - Nitrogen
N2O - Nitrous oxide
NF3 - Nitrogen trifluoride
PFC - Perfluorocarbon
SF6 - Sulphur hexafluoride
SO2 - Sulphur dioxide
5
Introduction This report aims to provide the insight into greenhouse gas (GHG) emission/removal and
policies, measures and projections reporting of the three Baltic States: Estonia (EE), Latvia
(LV) and Lithuania (LT). The report has been prepared by the NGO "Green Liberty" as part of
the project ‘’Baltic Expert Network for Greenhouse Gas Inventory, Projections and PaMs
Reporting” (BENGGI) carried out by the Ministry of Environmental Protection and Regional
Development (MEPRD) of Latvia and funded by the Seed Money Facility.
The report is based on desk research of relevant documents and interviews with experts
from the three the Baltic States as well as the two international workshops (25.10.2016. and
22.02.2017.) conducted as part of the BENGGI project.
The report consists of two main parts. First, we compare general compliance of the regular
reports on GHG emissions prepared by the three Baltic States with the EC and UNFCCC
regulation and guidelines. In the second part of the report, we examine the national
institutional systems for preparation of the reports, data sources, methods used for
inventory and projections and approach for PAMs selection and evaluation.
General description of GHG reporting covered by this report All three Baltic States are the European Union (EU) member-states and parties to the United
Nations Framework Convention on Climate Change (UNFCCC), therefore, they shall regularly
report their GHG emissions according to following requirements:
report to the EU according to Monitoring Mechanism Regulation (MMR)1 and the
Commission Implementing Regulation 749/2014;
annually prepare national GHG inventories consisting of Common Reporting Format
(CRF) tables and National Inventory Report (NIR)2;3
,4 according to UNFCCC;
submit Biennial Reports (BR)5 every 2 years to the UNFCCC;
submit National Communications (NC)6 every 4 years to the UNFCCC.
The requirements for GHG inventory reporting are set out in several documents. The Baltic
States as part of the EU are also required to monitor their emissions under the EU's GHG
monitoring mechanism, which was established in 1993 and revised two times, in 2004 and
in 2013, as part of the EU's preparations for meeting its Kyoto Protocol (KP) emissions
target. The latest revision concerns the new MMR which entered into force on 8 July 2013
(EC, 2013). This mechanism now provides the legal basis to implement revised domestic
commitments set out in the 2009 climate and energy package (20-20-20 commitments), as
well as to ensure timely and accurate monitoring of the progress in the implementation of
these commitments.
1 http://ec.europa.eu/clima/policies/strategies/progress/monitoring/index_en.htm; http://cdr.eionet.europa.eu/ 2http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/9492.php 3http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/9477.php 4 Annual European Union greenhouse gas inventory 1990-2014 and inventory report 2016 5 http://unfccc.int/national_reports/biennial_reports_and_iar/submitted_biennial_reports/items/7550.php 6 http://unfccc.int/national_reports/annex_i_natcom_/items/1095.php
6
The requirement to submit National Inventories to the UN is set out in the UNFCCC,
requiring all Parties to prepare, periodically update, and submit national inventories of GHG
emissions and sinks and to report a national GHG inventory — a general description of steps
that the Party has taken or envisages to implement the Convention and any other
information that the Party considers relevant to the achievement of the objective of the
Convention. The Convention itself does not establish a frequency for submission of national
communications but leaves this to decisions of the Conference of Parties.
The national communication reporting covers:
emissions of 7 greenhouse gasses from all sectors: energy, industrial processes and
product use, land use, land use change & forestry (LULUCF), agriculture and waste;
projections, policies & measures to fulfill GHG emission reduction targets;
national measures to adapt to climate change;
low-carbon development strategies;
financial & technical support for developing countries, and similar commitments
under the 2009 Copenhagen Accord and 2010 Cancún Agreements;
Conference of the Parties (COP) Decision 24/CP.19 Revision of the UNFCCC reporting
guidelines sets out the reporting requirements on annual national inventories for Parties
included in Annex I to the Convention7 (UNFCCC reporting guidelines). The Guidelines were
adopted at Conference of the Parties at its 19th session. According to the guidelines the
period covered by the inventories starts in the base year (mostly 1990) and runs up until 2
years before the current year (i.e. in 2016 the inventories cover emissions up to 2014).
UN Intergovernmental Panel on Climate Change (IPCC) Guidelines for the preparation of NCs
were adopted at COP 2 in Geneva in 1996 and revised several times. Consultative Group of
Experts on National Communications from non-Annex I Parties made major contributions to
the review of the guidelines. At COP 8 (New Delhi, 2002) Parties adopted revised guidelines8.
COP 17 adopted the guidelines for the preparation of biennial reports contained in annex III
of decision 2/CP.179.
There are three ‘Tiers’ of complexity in the calculations. In IPCC terminology, the lowest
ranking or simplest method is Tier 1 (default emission factors (EF) and the most basic, and
least disaggregated, activity data). The Tier 2 calculations generally disaggregate the activity
data and use various emission factors that reflect regional and temporal differences. Tier 3
methods use models that are more complex and highly disaggregated activity data sources.
7 http://unfccc.int/resource/docs/2013/cop19/eng/10a03.pdf#page=2 8 http://unfccc.int/resource/docs/cop8/07a02.pdf 9 http://unfccc.int/resource/docs/2011/cop17/eng/09a01.pdf#page=39 http://unfccc.int/resource/docs/2011/cop17/eng/09a01.pdf#page=39
7
1. General comparison of the reporting to EC and UNFCCC
in the Baltic States To compare general compliance of the three Baltic States (Estonia, Latvia, and Lithuania) with the reporting guidelines of the UNFCCC the summaries of the technical review were compared for each of the reports assessed:
National GHG inventory report (NIR201610) - in accordance with the “Guidelines for
review under Article 8 of the Kyoto Protocol” (decision 22/CMP.1);
National Communication (NC611) - in accordance with the “Guidelines for the
technical review of information reported under the Convention related to
greenhouse gas inventories, biennial reports and national communications by
Parties included in Annex I to the Convention” and the “Guidelines for review under
Article 8 of the Kyoto Protocol”.;
Biennial report (BR212) - in accordance with the “Guidelines for the technical review
of information reported under the Convention related to greenhouse gas
inventories, biennial reports and national communications by Parties included in
Annex I to the Convention”.
Paragraphs with recommendations were assessed for each country. The focus of research
was on recommendations and observations of comparison within this research requiring
conceptual improvements or more efforts assuming that some recommendations are
relatively easy to solve or already solved by countries. Overall representation level of reports
was also assessed to provide a clear contribution towards the goals and the main questions
of the reports.
General comparison of reporting to EC was made by assessment of reported list for the EC
requirements on reporting items for the MMR. No substantial differences or missing items
were found in this comparison. Therefore, it is not described in detail in this chapter. But the
more detailed assessment of relevant sections from reporting to EC is explored in section 2
describing specific aspects of comparison.
1.2. Annual GHG inventory Comparison of summaries from the technical reviews of annual GHG inventories in 201613 is
presented in Table 1.1.a and b below. It can be observed that there are three sections where
technical reviews identified the need for improvements for all the Baltic States:
- Selection and use of methodologies and assumptions;
- Collection and selection of activity data;
- Missing categories/completeness.
Latvia has received the most of the comments in “Selection and use of methodologies and
assumptions” and “Missing categories/completeness”, but Lithuania – in “Collection and
selection of activity data”. (Table 1.1.b.). Comparison of the items and problems identified
10 http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/9492.php 11 http://unfccc.int/national_reports/annex_i_natcom/submitted_natcom/items/7742.php 12 http://unfccc.int/national_reports/biennial_reports_and_iar/submitted_biennial_reports/items/7550.php 13 http://unfccc.int/national_reports/annex_i_ghg_inventories/inventory_review_reports/items/8452.php
8
suggests that they are country specific and there is no direct opportunity for common
solving the specific problems.
Latvia and Estonia have received a list of issues in the section “Development and selection of
emission factors”.
Table 1.1.a Summary and general assessment of the 2016 annual submission - “Table 2” of
the Report on the individual review
Assessment Assessment questions LV EE** LT
Application of the requirements of the UNFCCC Annex I inventory reporting guidelines and Wetlands Supplement (if applicable)
Have any issues been identified in the following areas:
1. Identification of key categories No No No
2. Selection and use of methodologies and assumptions Yes Yes Yes
3. Development and selection of emission factors Yes Yes No
4. Collection and selection of activity data Yes Yes Yes
5. Reporting of recalculations Yes No No
6. Reporting of a consistent time series Yes No No
7. Reporting of uncertainties, including methodologies Yes No No
8. QA/QC procedures were assessed in the context of the national system (see below)
9. Missing categories/completeness Yes Yes Yes
10. Application of corrections to the inventory No No No
Significance threshold
For categories reported as insignificant, has the Party provided sufficient information showing that the likely level of emissions meets the criteria in paragraph 37(b) of the UNFCCC Annex I inventory reporting guidelines?
Yes * *
Description of trends Did the ERT conclude that the description in the NIR of the trends for the different gases and sectors is reasonable?
Yes Yes Yes
Supplementary information under the Kyoto Protocol
Have any issues been identified in the following areas:
1. National system:
(a) The overall organization of the national system, including the effectiveness and reliability of the institutional, procedural and legal arrangements
No No No
(b) Performance of the national system functions No No No
2. National registry:
(a) Overall functioning of the national registry No No No
(b) Performance of the functions of the national registry and the technical standards for data exchange
No No No
3. ERUs, CERs, AAUs and RMUs and on information on discrepancies reported in accordance with decision 15/CMP.1, annex, chapter I.E, taking into consideration any findings or recommendations contained in the SIAR
Yes No Yes
4. Matters related to Article 3, paragraph 14, of the Kyoto Protocol, specifically problems related to the transparency, completeness or timeliness of reporting on the Party’s activities related to the priority actions listed in decision 15/CMP.1, annex, paragraph 24, including any changes since the previous annual submission
No No No
5. LULUCF activities under Article 3, paragraphs 3 and 4, of the Kyoto Protocol:
(a) Reporting in accordance with the requirements of decision 2/CMP.8, annex II, paragraphs 1–5
No Yes No
9
Assessment Assessment questions LV EE** LT
(b) The Party has demonstrated methodological consistency between the reference level and reporting on forest management in accordance with decision 2/CMP.7, annex, paragraph 14
Yes Yes No
(c) The Party has reported information in accordance with decision 6/CMP.9
No No No
(d) Country-specific information has been reported to support provisions for natural disturbances, in accordance with decision 2/CMP.7, annex, paragraphs 33 and 34
NA Yes NA
(e) Other issues No Yes No
CPR Was the CPR reported in accordance with the annex to decision 18/CP.7, the annex to decision 11/CMP.1 and decision 1/CMP.8, paragraph 18?
Yes Yes Yes
Adjustments
Has the ERT applied an adjustment under Article 5, paragraph 2, of the Kyoto Protocol?
No No No
The ERT accepts that the revised estimate submitted by Lithuania in its 2016 submission can replace a previously applied adjustment in the compilation and accounting database
NA
Response from the Party during the review
Has the Party provided the ERT with responses to the questions raised, including the data and information necessary for the assessment of conformity with the UNFCCC Annex I inventory reporting guidelines and any further guidance adopted by the Conference of the Parties?
Yes Yes Yes
Recommendation for an exceptional in-country review
On the basis of the issues identified, does the ERT recommend that the next review be conducted as an in-country review?
No No No
Question of implementation
Did the ERT list a question of implementation? No No No
*The Party did not report “NE” for any insignificant categories ** Report on the individual review of the annual submission of Estonia submitted in 2016 used is a draft version – not officially approved14 Source: Compiled by Green Liberty from the technical reviews of GHG inventory reports in 201615
Note: Blue marked are the sections where an issue or a problem is identified.
Table 1.1.b. Items with issues or problems of the 2016 annual submission - selection from
the Table 2 of the Report on the individual review (Issue or problem ID #(s) in tables 3
and/or 5a of the Report are identified)
Assessment Assessment questions LV EE** LT
Application of the requirements of the UNFCCC Annex I inventory reporting guidelines and Wetlands Supplement (if applicable)
Have any issues been identified in the following areas:
2. Selection and use of methodologies and assumptions E.14, I.13, I.14, A.4
E.7 L.5
3. Development and selection of emission factors
E.5, E.14, A.8, A.9, L.14, L.15, L.21, KL.8, KL.13
E.4, E.11, E.16, A.1, W.1
14 http://unfccc.int/national_reports/annex_i_ghg_inventories/inventory_review_reports/items/9916.php 15 http://unfccc.int/national_reports/annex_i_ghg_inventories/inventory_review_reports/items/8452.php
10
Assessment Assessment questions LV EE** LT
4. Collection and selection of activity data I.15
E.3, E.9, I.10, A.3, A.4, L.3, W.6, W.7
L.6
5. Reporting of recalculations A.6
6. Reporting of a consistent time series I.1, E.17, A.5
7. Reporting of uncertainties, including methodologies KL.2
9. Missing categories/completenessb I.9, L.16, L.20, L.23
A.4, W.9 L.7
Significance threshold
For categories reported as insignificant, has the Party provided sufficient information showing that the likely level of emissions meets the criteria in paragraph 37(b) of the UNFCCC Annex I inventory reporting guidelines?
Yes * *
Supplementary information under the Kyoto Protocol
3. ERUs, CERs, AAUs and RMUs and on information on discrepancies reported in accordance with decision 15/CMP.1, annex, chapter I.E, taking into consideration any findings or recommendations contained in the SIAR
G.13 G.9
(a) Reporting in accordance with the requirements of decision 2/CMP.8, annex II, paragraphs 1–5
KL.5, KL.8, KL.9
(b) The Party has demonstrated methodological consistency between the reference level and reporting on forest management in accordance with decision 2/CMP.7, annex, paragraph 14
KL.12 KL.6, KL.10
(d) Country-specific information has been reported to support provisions for natural disturbances, in accordance with decision 2/CMP.7, annex, paragraphs 33 and 34
KL.4, KL.5, KL.6
(e) Other issues KL.7, KL.11
*The Party did not report “NE” for any insignificant categories ** Report on the individual review of the annual submission of Estonia submitted in 2016 used is a draft version – not officially approved Source: Compiled by Green Liberty from the technical reviews of GHG inventory reports in 201616
Note: Blue marked are the sections where an issue or a problem is identified.
1.3. The 6th National Communication Comparison of summaries from the technical reviews of the 6th National Communication is
presented in Table 1.2. below. The reports for each of the Baltic States present the results of
the technical review of the 6th National Communication and supplementary information
under the Kyoto Protocol conducted by an expert review team in accordance with the
“Guidelines for the technical review of information reported under the Convention related
to greenhouse gas inventories, biennial reports and national communications by Parties
included in Annex I to the Convention” and the “Guidelines for review under Article 8 of the
Kyoto Protocol”.17
Technical reviews include assessments in two categories:
16 http://unfccc.int/national_reports/annex_i_ghg_inventories/inventory_review_reports/items/8452.php 17 http://unfccc.int/national_reports/annex_i_natcom/idr_reports/items/2711.php
11
Sections of national communication;
Supplementary information under the Kyoto Protocol.
In both categories, Completeness and Transparency were assessed.
Table 1.2. Comparison of summaries from the technical reviews of the 6th National
Communication for the three Baltic States
12
Source: Compiled by Green Liberty from the technical reviews of the 6th National Communication reports.
Note: Blue marked are the sections that are identified as not sufficient or complete according to the technical
reviews.
All the Baltic States in both assessment categories have sections that were assessed as not
fully complete and transparent. There are several common problems identified:
Category “Sections of national communication”
Completeness
Projections and total effects of PaMs indicates the need for improvements in all
Baltic States;
Vulnerability assessment, climate change impacts, and adaptation measures
indicates a common problem for Latvia and Lithuania;
Research and systematic observation indicate a common problem for Latvia and
Lithuania
Transparency
Policies and Measures (PaMs) indicated as a common problem for Estonia and
Lithuania;
Projections and total effects of PaMs indicates a common problem for Estonia and
Latvia
13
Category “Supplementary information under the Kyoto Protocol”
Completeness
PaMs in accordance with Article 2 indicates the need for improvements in all Baltic
States;
National system indicates a common problem for Latvia and Lithuania;
Transparency
PaMs in accordance with Article 2 indicates a common problem for Estonia and
Lithuania;
Domestic and regional programmes and/or arrangements and procedures indicates
a common problem for Estonia and Latvia
Detailed comparison for category “Sections of national communication”
There are nine sections of NC subject to technical review. Two-thirds of 19 articles with
recommendations (for all three the Baltic States together) were related to the section
“Projections and total effects of PaMs” (seven paragraphs in Estonia, three in Latvia and one
in Lithuania).
Comparison of the contents of the 6th National Communication for each of the Baltic States
and recommendations from the technical reviews led to several notes for the future
improvements in reporting:
- A clear representation of the effects of PaMs should be improved. Lithuania and Estonia
were recommended to include additional detailed information (total effect of PaMs by
gas for Lithuania and a missing year for Estonia). Recommendation for Latvia states that
“estimate of the total effect of its PaMs, in accordance with the ‘with measures’
definition, compared with a situation without such PaMs”. Concerning a clear
representation of the effects Lithuania has the highest rating according to this research –
a summary graph representing total emission projections for all three scenarios –
without measures (WOM), with existing measures (WEM) and with additional measures
(WAM). Estonia has represented two aggregated tables including the total effect of
implemented and adopted PaMs in one table and planned PaMs in other. Latvia has
included comparison graphs for WAM and WEM scenarios (total emissions in one graph
and reduction share as an effect in other). Latvia has not included the total effect of
WEM (but it is represented in the biennial report). To improve a clear representation of
the effects of PaMs it is recommended within this research to display graphs of total
emissions for all three scenarios (WEM, WAM, WOM) in one picture representing
historical data together with projections similar to the report of Lithuania. The effect for
WEM and WAM should be represented in tabular format as in the case of Estonia or
precentral decrease (or physical units as in the biennial report) of emissions as in Latvia
or both. These are the contents of the report section “Assessment of the aggregate
effect of policies and measures”. For a better representation, it is recommended to
supplement the comparison mentioned above with the split of emissions by sectors and
by gases for each of scenarios – WEM, WAM, WOM. That could be done in tabular
format as in the Latvia report. Despite possible duplication with the sectoral chapters,
this information should provide a comprehensive overview of effects of all PaMs
scenarios.
14
- Another general note is related to transparency. Despite country-specific
recommendations of the technical reviews (QC improvement for consistency of data
with the biennial report in Latvia, transparency of specific methods and assumptions in
Estonia and others) comparison of the 6th National Communication reports within this
research resulted in observation related to the methodologies of projections used. The
general impression could be reflected as follows. Lithuania that uses its own excel based
tools for the projections has explained all assumptions and calculation steps in detail
thus providing an impression of good transparency. Estonia (and to some extend also
Latvia) is using ready-made calculation tools (LEAP - Long-range Energy Alternatives
Planning System and MARKAL models); thus referring to “reliable black box” that gives
appropriate results in the energy sector.
1.4. 2nd Biennial report Comparison of summaries from the technical reviews of the 2nd Biennial report is presented
in Table 1.3. below. The reports for each of the Baltic States presents the results of the
technical review of the 2nd BR, conducted by an expert review team in accordance with the
“Guidelines for the technical review of information reported under the Convention related
to greenhouse gas inventories, biennial reports and national communications by Parties
included in Annex I to the Convention”18.
Technical reviews indicate common fields of improvements for Latvia and Lithuania:
Transparency in Assumptions, conditions, and methodologies related to the
attainment of the quantified economy-wide emission reduction target;
Completeness in Progress in the achievement of targets.
Section “Assumptions, conditions and methodologies related to the attainment of the
quantified economy-wide emission reduction target” contain one country specific
recommendation for Latvia (reporting base year for F-gases) and one for Lithuania
(information on the possible scale of contributions from market-based mechanisms).
18 http://unfccc.int/national_reports/biennial_reports_and_iar/technical_reviews/items/9534.php
15
Table 1.3. Comparison of summaries from the technical reviews of the 2nd Biennial report
for the three the Baltic States
Source: Compiled by Green Liberty from the technical reviews of the 2nd Biennial report reports
Note: Blue marked are the sections that are identified as not sufficient or complete according to the technical
reviews.
80% of paragraphs with recommendations for all three Baltic States together refer to section
“Progress in achievement of targets”.
Comparison of the contents of the 2nd Biennial report for each of the Baltic States and
recommendations from the technical reviews led to several notes for the attention to
ensure the future improvements in reporting:
1. Latvia and Lithuania received recommendations to improve the completeness of reporting
changes in its domestic institutional arrangements.
2. To improve transparency, the Expert Review Team recommends that Latvia and Lithuania
report separately, to the extent possible, its emission projections related to fuel sold to ships
and aircraft engaged in international transport in its next BR.
3. All the three Baltic States have received recommendations related to CTF Table 3
“Progress in achievement of the quantified economy-wide emission reduction target:
information on mitigation actions and their effects”. Latvia is recommended to include the
corresponding year of the mitigation impact of PaMs and other information required by the
UNFCCC reporting guidelines as well as explaining the use of the notation keys “NE” and
“IE”, and consistently allocating PaMs to the relevant sector. Estonia is recommended to
provide quantitative estimates of the impacts of the remaining PaMs or, if this is not
possible, provide the relevant explanations. Lithuania has got a recommendation in relation
to the table 3 - to “improve the transparency of its reporting by organizing, to the
appropriate extent, the reporting of its mitigation actions by gas in its next BR, as is currently
done in CTF table 3”. Comparison of the 2nd Biennial reports from all three Baltic States
within this research leads to the conclusion that the style of organizing and structuring
16
information on progress in the achievement of the quantified economy-wide emission
reduction target has differences both – in the description part and in the CTF Table 3.
Comparison of the 2nd Biennial reports and the technical review reports led to the conclusion
that recommendations for one country could to some extent be relevant also to other
countries. This means that other experts in the next technical reviews of the Biennial reports
could outline also other aspects for improvement.
3.1. There are differences in how the PaMs are presented in the text of the report and CTF
Table 3. For example, Lithuania has indicated two mitigation actions in Table 3 for the
transport sector, but four main legal documents and five main mitigation measures are
described in the report text. That indicates to the attempt to describe groups of PaMs in
Table 3. Latvia and Estonia have included a long list in Table 3. Latvia clearly refers only to
new PaMs in the text that was not included in the previous BR.
3.2. There are differences of detail – what is defined as PaM or group of PaMs. The previous
note indicates the need to formulate more clearly of what is included in the CTF and text and
if PAMs of the PAM group are described also separately from the group.
3.3. Estonia has developed a way to include changes over time in the definition of PaMs.
Instructions for Table 3 stipulates that “*” should be used to indicate that PaM is included in
WEM. For continuous groups of PaMs in the next periods, Estonia uses “additional” in the
definition to reflect contents of WAM. For example, “Additional improvement of the traffic
system”.
4. Other comments in the technical reviews referred to discrepancies between the values
presented in the BR2 and in the CTF table (Latvia), discrepancies for NF3 gas in different
places (Estonia) and lack of contribution from LULUCF reported in CTF Table 4 (Lithuania).
In the context of potential cooperation between the Baltic States in improving the reporting
process, notes 1 and 4 should be assumed as country specific (except reporting on a
contribution from LULUCF in Lithuania) where experience in Latvia and Lithuania should be
examined in detail if assumed for use as good practice. Rather it should be assumed as
individual work for each country.
Note 2 indicates on potential cooperation in finding solutions for Latvia and Lithuania in
reporting on projections related to fuel sold to ships and aircraft.
Note 3 indicates that detailed common assessment within three the Baltic States on types of
PaMs and styles of reporting would be favorable to improve a clear representation of the
progress and a role of PaMs and to reduce the risk of new recommendations from the
technical reviews in the future.
The level of detail in formulating PaMs should be checked for possible change. The
observation within this research indicates that combining PaMs in the groups of PaMs could
reduce transparency but increase completeness if not described in much detail.
Another observation leads to the conclusion that ambiguity and difficulties in calculation of
effects occur mainly due to the inclusion of PaMs with indirect impacts on reduction of GHG
emissions. For example – “Systematic inspection of the technical conditions” for vehicles in
the transport sector in Latvia. Theoretically, such measure could be included in the list of
other countries as well. Moreover, there is a list of similar PaMs listed by all the countries.
The recommendation within this research is to explore a comparison on lists of PaMs for the
17
Baltic States and other countries and to organize a separate discussion among the
representatives of all three Baltic States on improving the way of selecting and structuring
PaMs.
Another recommendation is to improve structuring by clear defining and presenting of direct
and indirect PaMs and applying different approaches for assessing the effect of them as well
as clearly structuring descriptions for PaMs and groups of PaMs.
Description of effects of PAMs is clearly divided in Estonia 2nd Biennial report; outline of
assumptions on dynamics of projection parameters is detailed in Lithuania 2nd Biennial
report.
18
2. Comparative analysis of specific reporting questions
2.2. National reporting system This chapter examines the national institutional systems for the GHG reporting. Institutions
and their responsibilities, data gathering and reporting processes and financing mechanisms
are compared to the three Baltic States.
2.2.1. National inventory reporting The main information on institutions and their responsibilities, data gathering and reporting
processes and financing mechanisms in Latvia, Estonia and Lithuania are presented in the
following sections using citations from the 2016 NIRs. Then the comparison is made and the
main differences and similarities identified.
Latvia
The organizational structure of Latvia’s national inventory reporting is presented in Figure
2.1. According to information presented in the NIR2016 overall coordination of GHG
inventory process, coordinating the work between the involved institutions, preparation of
legal basis for maintaining the National System and other general functions are under the
responsibility of Ministry of Environmental Protection and Regional Development (MEPRD)
Climate Change Department.
Figure 2.1. Organizational structure of Latvia’s national inventory reporting
Source: Latvia’s National GHG inventory report 1990 – 2014.
Latvian Environment, Geology and Meteorology Centre (LEGMC) is a governmental limited
liability company and is responsible for collecting of activity data and preparation of the
emission estimates for the Energy (excluding Transport), Industrial Processes and Product
19
Use and Waste sectors. Besides it has also important management functions - quality
manager from LEGMC Air and Climate division performs the overall QA/QC procedures for
all sectors according to the QA/QC plan and LEGMC is the National Emissions Trading
Authority in Latvia and prepare relevant information for GHG inventory from the registry.
Calculations of removals and emissions for the LULUCF sector is done by Latvian State Forest
Research Institute "Silava" in collaboration with Ministry of Agriculture (MoA).
Institute of Physical Energetic calculates emissions for the Transport sector.
Emission calculations from Agriculture sector are done by Latvia University of Agriculture in
collaboration with MoA.
A full list of responsibilities for MEPRD and LEGMC according to NIR 2016 is listed below:
1. The MEPRD Climate Change Department is responsible for:
Preparation of legal basis for maintaining the National System;
Informing the inventory compilers about requirements of the national system;
Overall coordination of GHG inventory process;
Final checking and approving of the GHG inventory before official submission to the
EC and UNFCCC;
Formal agreements with inventory experts and for third party experts that evaluate
quality assurance process;
Coordinating the work between the involved institutions, experts, European
Commission and UNFCCC (including coordination of the UNFCCC inventory reviews);
Timely submission of GHG inventory to the UNFCCC and European Commission;
Keeping of archive of official submissions to UNFCCC and European Commission.
2. LEGMC is responsible for:
Collecting of activity data for Energy, Industrial Processes and Product Use (IPPU)
and Waste sectors (activity data are mainly collected from other institutions and
LEGMC (Air and Climate division, Chemicals and Hazardous Waste division, Inland
Waters division) use them to calculate emissions);
Preparation of the emission estimates for the Energy, Industrial Processes and
Product Use and Waste sectors;
Preparation of QC procedures for relevant categories and documentation and
archiving of used materials for emission calculation;
LEGMC Air and Climate Division compile the final NIR using information from all
involved institutions as well as summarized emission data in CRF Reporter;
Quality manager from LEGMC Air and Climate division perform the overall QA/QC
procedures for all sectors according to the QA/QC plan;
LEGMC is the National Emissions Trading Authority in Latvia and prepare relevant
information for GHG inventory from registry – on emission reduction units, certified
emission reductions, temporary certified emission reductions, long-term certified
emission reductions and assigned amount units for annual inventory submissions in
accordance with guidelines for preparation of information under Article 7 of the
Kyoto Protocol (a standard electronic format tables).
20
Estonia
According to information presented in the NIR201619 “single national entity with overall
responsibility for the Estonian GHG inventory is the Estonian Ministry of the Environment
(MoEn). Financial resources are partly planned in the State Budget and partly applied from
Environmental Investment Centre. Practical work is done mostly on the basis of contracts.
Starting from 2014inventories were produced in collaboration between the MoEn, Estonian
Environment Agency (EtEA) and Estonian Environmental Research Centre (EERC),
responsibilities between different institutions are shown in Figure 2.2.
Figure 2.2. Organizational structure of Estonia’s national inventory reporting
Source: Estonia’s National GHG Inventory Report 1990 – 2014.
19 http://unfccc.int/files/national_reports/annex_i_ghg_inventories/national_inventories_submissions/application/zip/est-2016-nir-15jun16.zip
21
The MoE is responsible for:
coordinating the inventory preparation process as a whole;
approving the inventory before official submission to the UNFCCC;
reporting the greenhouse gas inventory to the UNFCCC, including the National
Inventory Report and CRF tables;
entering into formal agreements with inventory compilers (EERC);
coordinating cooperation between the inventory compilers and UNFCCC Secretariat;
informing the inventory compilers of the requirements of the national system and
ensuring that existing information in national institutions is considered and used in
the inventory where appropriate;
informing the inventory compilers of new or revised guidelines; and
coordinating the UNFCCC inventory reviews and communication with the expert
review team, including responses to the review findings.
The EERC, as the inventory coordinator, is responsible for:
compiling the National Inventory Report according to the parts submitted by the
inventory compilers;
coordinating the implementation of the QA/QC plan;
coordinating the inventory process; and
the overall archiving system.
Lithuania
According to information presented in the NIR201620, until the year 2011, GHG inventory
preparation process was performed by contracting GHG compilers on the annual basis.
Aiming to increase institutional capacity for inventory preparation and continuity of the
inventory preparation process in compliance with Guidelines for National systems under
Article 5 paragraph 1 of the Kyoto Protocol (decision 19/CMP.1) the Government of
Lithuania and the Minister of Environment have issued a number of key regulatory legal acts
and assigned responsible institutions for GHG inventory preparation. The main entities
participating in GHG inventory preparation process are:
Ministry of Environment
Environmental Protection Agency (EPA)
State Forest Service
National Climate Change Committee
Permanent GHG inventory working group
Data providers
External consultants
The principle scheme showing institutions responsibility in the preparation of the GHG
inventory in Lithuania and their interaction is shown in Figure 2.3.
20 http://unfccc.int/files/national_reports/annex_i_ghg_inventories/national_inventories_submissions/application/zip/ltu-2016-nir-17jun16.zip
22
Figure 2.3. Organizational structure of Lithuania's national inventory reporting
Source: Lithuania’s National GHG Inventory Report 1990 – 2014
Ministry of Environment
Ministry of Environment of the Republic of Lithuania is a National Focal Point to the UNFCCC.
The Ministry of Environment is designated as single national entity responsible for the national
GHG inventory. It has overall responsibility for the national system of GHG inventory and is in
charge of the legal, institutional and procedural arrangements for the national system and the
strategic development of the national inventory.
Environmental Protection Agency Lithuanian Environmental Protection Agency under the Ministry of Environment starting
from 2011 was nominated as an entity responsible for GHG inventory preparation. At
present EPA collects data on the use of water resources, discharges of wastewater, waste
generation and treatment, pollution of ambient air and surface water, chemicals and
fluorinated gasses; manages the available registers, e.g. the Ambient Air Quality, the
European Pollutants Releases and Transfer Register and various databases. In 2012, Climate
change division for GHG inventory preparation was established within the EPA.
Since 2014 submission personnel of EPA is also responsible for the calculation of emissions
and preparation of NIR part of the industrial processes and products use sector and
agriculture soils part of the agriculture sector.
Permanent GHG Inventory preparation working group
In Lithuania, Permanent GHG Inventory preparation working group is established by the
Governmental Resolution according to which, a working group (Commission) for the
preparation of a GHG inventory report consists of representatives from:
Ministry of Environment (Chairman of the Commission);
Environmental Protection Agency (Deputy Chairman of the Commission);
Institute of Physics of the Centre for Physical Sciences and Technology (energy,
transport);
Lithuanian Energy Institute (energy, except transport);
Institute of Animal Science of the Lithuanian University of Health Sciences
(agriculture);
23
Aleksandras Stulginskis University (LULUCF, except forestry);
State Forest Service (LULUCF, forestry; KP-LULUCF);
Public body Centre for Environmental Policy (waste).
State Forest Service (SFS)
The State Forest Service compiles the National Forest Inventory and the forest information
system, carries out monitoring of the status of the Lithuanian forests, collects and manages
statistical data etc. The Service functions under the Ministry of Environment.
Since 2010, SFS in the GHG inventory preparation process is responsible for calculations of
emissions and removals of LULUCF sector.
Data collection and CRF Reporter
The main organizational characteristics of data collection and filling in CRF Reporter are
outlined below to describe the data flow during the NIR 2016 preparation process.
Latvia
Each emission sector has an assigned at least one responsible sectoral expert who is
responsible for the selection of appropriate data sources and activity data collection,
processing and updating of data.
For the Energy (excluding Transport), IPPU and Waste – data collection and emission
estimation are done by LEGMC experts from Air and Climate Division, Chemicals and
Hazardous Waste Division and Inland Waters Division.
For transport activity data is collected and emissions are calculated by the expert from
Institute of Physical Energetics.
For Agriculture, data collection and emission estimations are done by the Latvia University of
Agriculture in collaboration with Ministry of Agriculture.
LULUCF and KP-LULUCF data are collected and emissions/removals are calculated in Latvian
State Forest Research Institute "Silava" in collaboration with Ministry of Agriculture and
Latvia University of Agriculture.
According to Inventory preparation plan in NIR 2016, there are few more organizations
responsible for providing data (besides operators and National statistics), e.g. gas provider
“Latvijas Gāze”, Ministry of Health collaborating with State Agency of Medicines, State
Firefighting & Rescue Service.
All responsible experts collect and process particular sector activity data, emission factors
and do the emission calculations and data import into CRF Reporter software. LEGMC Air
and Climate Division compiles the final NIR using information from all involved institutions as
well as summarizes emission data in CRF Reporter. The sectoral experts upload data in CRF
Reporter software either manually or by importing Microsoft Excel spreadsheets.
Sectoral experts check the data in the CRF Reporter for consistency and quality assurance
(e.g. to check whether the sum adds up to 100%, to check the year to year changes between
values reported etc.).
24
Estonia
The sectoral experts from EERC and EtEA are collecting data and preparing the estimates for
the national inventory. The main sources of data are official Estonian statistics (Statistics
Estonia, Estonian Animal Recording Center) and company’s annual emission reports.
MoEn has a bilateral agreement with Statistics Estonia (SE). SE collects statistical data based
on the Official Statistics Act §3(2), taking into consideration the official statistical surveys
approved by the Government.
The data collection from other institutions and private companies is done by sectoral experts
that have personal contacts in order to receive the data.
Sectoral experts collect activity data, estimate emissions and/or removals, implement QC
procedures and record the results, fill in sectoral data to the CRF Reporter and prepare the
sectoral parts of the NIR. Responsible experts export empty excel tables from the CRF
reporter and fill them manually after what the prefilled tables are imported back to the CRF
reporter. These experts are also responsible for archiving activity data, estimates and all
other relevant information according to the archiving system. After experts are done with
the data import, the EERC coordinator conducts consistency and completeness checks in the
CRF reporter.
Lithuania
All necessary data for GHG inventory preparation is collected either by the sectoral experts
from Permanent GHG inventory working group, State Forest Service or it is requested from
data providers by official letters from Environmental Protection Agency (EPA). The main
sources of data are Statistics Lithuania (energy balance, agriculture statistics), EPA (waste,
wastewater, F-gases databases), private industrial companies, databases of State Forest
Service, EU ETS reports etc.
EPA compiles the final NIR using information provided from all involved experts and is
responsible for crosscutting issues such as general uncertainty assessment, key category
analysis, QA/QC procedures implementation.
The sectoral experts upload data to CRF Reporter mainly by importing MS Excel
spreadsheets.
Comparison
Distribution of the main sectoral responsibilities for preparation of NIR is compared in Table
2.1. below.
Table 2.1. Comparison of the main responsibilities of the Baltic States
Latvia Estonia Lithuania
Energy Latvian Environment,
Geology and
Meteorology Centre
Estonian
Environmental
Research Centre
Permanent GHG
Inventory working
group (representative
from Lithuanian Energy
Institute)
25
Latvia Estonia Lithuania
IPPU Latvian Environment,
Geology and
Meteorology Centre
Estonian
Environmental
Research Centre
Environmental
Protection Agency
Transport Institute of Physical
Energetic
Estonian
Environmental
Research Centre
Permanent GHG
Inventory working
group (representative
from Institute of
Physics)
Agriculture Latvia University of
Agriculture and
Ministry of
Agriculture
Estonian
Environmental
Research Centre
Environmental
Protection Agency,
Permanent GHG
Inventory working
group (representative
from Institute of Animal
Science)
LULUCF Latvian State Forest
Research Institute
"Silava" and Ministry
of Agriculture
Estonian
Environment
Agency
State Forest Service,
Permanent GHG
Inventory working
group (representative
from Aleksandras
Stulginskis University)
Waste Latvian Environment,
Geology and
Meteorology Centre
Estonian
Environmental
Research Centre
Permanent GHG
Inventory working
group (representative
from Center for
Environmental Policy)
QA/QC Latvian Environment,
Geology and
Meteorology Centre
Estonian
Environmental
Research Centre
Environmental
Protection Agency
Main responsibility of GHG inventory
Ministry of
Environmental
Protection and
Regional
Development
Ministry of
Environment
Ministry of Environment
Uncertainties Each expert is
responsible for
activity data and
emission factor
uncertainty
evaluation in his
sector. LEGMC GHG
inventory compiler is
Each expert is
responsible for
activity data and
emission factor
uncertainty
evaluation in their
sectors. EERC
coordinator is
Uncertainty is mainly
evaluated by sectoral
experts. Some activity
data providers evaluate
uncertainty of their
initial data. Total
26
Latvia Estonia Lithuania
responsible for the
total uncertainty
estimates.
responsible for the
total uncertainty
estimates.
In many cases
uncertainty values
have been assigned
based on default
uncertainty
estimates according
to IPCC guidelines or
expert judgement.
uncertainty is assessed
by Environmental
Protection Agency
CRF Reporter Sectoral experts and
LEGMC Air and
Climate Division
Sectoral experts and
EERC coordinator
Sectoral experts (EPA,
Permanent GHG
Inventory group, State
Forest Service)
KP-LULUCF State Fire and Rescue
Service of Latvia,
State forest service of
Latvia, National
Forest monitoring
program, National
studies and expert
judgment – for
Activity data. Latvian
State Forest Research
Institute "Silava" – for
calculations
Estonian
Environment
Agency
State Forest Service
Accounting of Kyoto units
LEGMC Ministry of the
Environment
Lithuanian Environment
Investment Fund
Changes in national system
LEGMC EERC coordinator Ministry of Environment
Changes in national registry
LEGMC Ministry of the
Environment
Lithuanian Environment
Investment Fund
Minimization of adverse impacts
MEPRD Ministry of the
Environment
Ministry of Environment
The main funding sources
State budget and
specific projects (e.g.
State budget and
Estonian
State budget and
Climate Change Special
Programme
27
Latvia Estonia Lithuania
EEA Financial
mechanism)
Environment
Investment Centre
The main similarities:
General functions and supervision are under Ministry that is responsible for
environment and climate issues in each country;
“National environmental agencies” have a significant role in the preparation of NIR in all
the countries. In Latvia, it is LEGMC, but in Lithuania EPA. In Estonia its EtEA, which was
set up in 2013 after the merging of the Estonian Meteorological and Hydrological
Institute (EMHI) and the Estonian Environment Information Centre. Lithuanian
Environmental Protection Agency (EPA) is a state authority functioning under the
Ministry of Environment similar to Latvia and Estonia. Similarities in the basic functions
and historical background of those organizations indicate parallels in approach within
NIR process and the potential for collaboration and data exchange. However, there are
significant differences in sectors of NIR prepared by those organizations that are
described below.
The main differences:
QC/QA. The coordinators from the MoEn and EERC have an overall responsibility for QC
of the emission inventory data in Estonia, but in Latvia and Lithuania, the cross-sectoral
QC/QA procedures are under the responsibility of the “environmental agencies” -
Latvian Environment, Geology and Meteorology Centre and Environmental Protection
Agency in Lithuania.
The role of “Environmental agencies”. “Environmental agencies” in Latvia and Lithuania
have a list of responsibility areas for NIR sectors. However, in Estonia, only LULUCF
reporting is the direct responsibility of Estonian Environment Agency.
The main contribution to the preparation of NIR. In each country, there is an institution
where concentrates most of the effort for the NIR preparation (besides the MoEn).
However, the status and organizational structure differs – in Latvia LEGMC together
with contractors performs majority of NIR preparation; in Estonia - Estonian
Environmental Research Centre (EERC) has the compiler functions; in Lithuania
Environmental Protection Agency is GHG inventory compiler and together with
permanent GHG Inventory preparation working group, and experts from State Forest
Service prepares GHG inventory.
CRF reporter. CRF reporter is filled by:
o sectoral experts and compiled by LEGMC in Latvia;
o sectoral experts from Permanent GHG inventory working group, EPA and SFS in
Lithuania;
o sectoral experts in Estonia.
Recommendations
For reporting: Table “Institutions responsible for activity data and calculating emissions”
in the Latvia NIR is proposed to be helpful for the clear understanding of
28
responsibilities, activity data gathering, and calculations. For improvement of
cooperation, other countries are suggested to use the same format.
For institutional development: Latvia is recommended to check if the creation of
Permanent GHG Inventory preparation working group, based on the existing pool of
experts, as in Lithuania could help to homogenize the NIR preparation process among
different contractors.
2.1.2. National System for reporting on policies, measures, and projections Comparison of “National System for reporting on policies, measures and projections under
Article 13 (1) (a) of Regulation (EU) No. 525/2013 and Article 20 of implementing Regulation
(EU) No. 749/2014” was performed to assess the National System for reporting on policies,
measures, and projections.
Latvia
According to Latvia report on a national system for policies and measures and projections to
EC, 201521, the main institutions and their responsibilities are listed below:
1. Ministry of the Environmental Protection and Regional Development ensures the
submission of the GHG emission/removals projections to the relevant international
institutions (UNFCCC, EC/EIONET, CLRTAP etc.) and monitors the co-operation of the
authorities involved.
2. Ministry of Economy (MoEc) - every second year, until 1st of August, MoEc shall
prepare the macroeconomic, energy, industrial manufacturing, construction and
agricultural sectors activity data projections.
3. Latvian Environment, Geology and Meteorology Centre (LEGMC) - Every second year
until 1st of March LEGMC collects, calculates, coordinates and harmonizes the
different sectors (energy, transport, agriculture, industrial processes and other
product use, land use, land-use change and forestry, waste management) GHG
emissions and air pollutants and CO2 removal projections and prepares the
descriptive part on 2015., 2020., 2025., 2030., 2035. - 2050. year in accordance with
the requirements set out, on the basis of the projections delivered by the
institutions involved in the development of the sectoral projections. The information
shall be coordinated with the institutions involved and shall submit to the MEPRD. In
addition, LEGMC shall prepare projections in industrial processes, wastewater
treatment, and waste management sector, as well as is responsible for preparation
of QC procedures for relevant categories and documentation and archiving of
materials of emission calculations.
4. Ministry of Agriculture (MoA) - every second year until 1st of August MoA prepares
activity data projections for agriculture and LULUCF sectors.
5. Latvian State Forest Research Institute "Silava" in collaboration with MoA is
responsible for preparation of GHG emission/removals projection from LULUCF
sector.
6. The Institute of Physical Energetics carries out emission calculation from Energy and
Transport sectors according to the agreement with MEPRD.
21 Reporting on a national system for policies and measures and projections under article 13(1)(a) of regulation (EU) No 525/2013 and article 20 of implementing regulation (EU) No 749/2014, Latvia.
29
7. Latvia University of Agriculture in collaboration with Ministry of Agriculture is
responsible for GHG emission projection preparation from the agriculture sector.
Data suppliers:
Central Statistical Bureau – main data supplier of historical statistical data;
State Agency of Medicines of Latvia;
Electricity suppliers provide data on SF6 consumption;
MoEc provides data on macroeconomic projections;
Enterprises (information from databases “2-Gaiss”, “3-Atkritumi”, “2-ūdens” etc.);
ETS operators.
Estonia
According to Estonia report on a national system for policies and measures and projections
to EC, 201522, the main institutions and their responsibilities are listed below:
1. Ministry of Environment is responsible for preparing Estonian national GHG
emissions related reports pursuant to the MMR and submitting the reports to
the European Commission.
2. Estonian Environmental Research Centre - Climate Department of Estonian
Environmental Research Centre (EERC) and Climate and Radiation Department of
the Ministry of the Environment coordinates the compilation of the report on
policies and measures and projections. EERC is responsible for the overall collection
of the data and compilation of the policies and measures and projections report.
Each subsector in the report has its own expert (from EERC) who is responsible for
the compilation of the projections.
3. Sectoral ministries - Before submitting the relevant report on policies, measures and
projections several meetings with experts from Ministry of Economic Affairs and
Communications, Ministry of Rural Affairs, Waste Department of the Ministry of the
Environment and Forest Department of the Ministry of the Environment are held to
ensure the quality, accuracy and timeliness of the projections.
Responsibilities regarding sectors:
Ministry of Economic Affairs and Communications - industry, trade, energy, housing,
building, transport and traffic management;
Ministry of Rural Affairs - agriculture;
Ministry of the Environment - waste, LULUCF, F-gases, industrial processes
The compilation of the policies and measures and projections report is funded by the
Environmental Investment Centre.
Lithuania
The main institutions involved in the preparation of the Policies & Measures and GHG
emission projections and responsible for the process of submission are:
• Ministry of Environment;
• Environmental Protection Agency;
• State Forest Service;
22 National System for reporting on policies, measures and projections under Article 13 (1) (a) of Regulation (EU) No. 525/2013 and Article 20 of implementing Regulation (EU) No. 749/2014 Estonia.
30
• Data providers.
Figure 1-1. The scheme of the main responsible institutions involved in the preparation
of PaMs and GHG emission projections in Lithuania.
According to Lithuania report on a national system for policies and measures and projections
to EC, 201523, the main institutions and their responsibilities are listed below:
1. Ministry of Environment is the main responsible and coordinating institution for the
development of climate change policy and its implementation in Lithuania. The
Ministry of Environment provides information on the waste sector, wastewater and
sludge treatment development and strategic plans. The additional projected data on
waste management was collected from the EPA under the Ministry of Environment
and Regional waste management centers.
2. Environmental Protection Agency is responsible for the calculation of GHG emissions
based on activity data received from data providers and the preparation of part of
GHG emission projections of the report. EPA has the following functions and
responsibilities:
o Analysis of key categories and identification of specific information, activity
data, and emission factors used to calculate GHG emission projections;
o Analysis of activity data received from data providers, preparation of
assumptions and calculation of GHG projections;
o Performing the sensitivity analysis of GHG projections;
o Filling the MMR Article 23 Reporting on projections template and providing to
the Ministry of Environment;
o Archiving the supplied and used activity data for GHG projections calculations,
calculation files of GHG projections and used materials;
o Evaluating requirements for new activity data, based on internal and external
reviews;
o Implementation of QC procedures for GHG projections estimates.
23 Policies & Measures and Projections of GHG Emissions in Lithuania report, 2015
31
3. The State Forest Service (SFS) compiles the National Forest Inventory (NFI) and the
forest information system, carries out monitoring of the status of the Lithuanian
forests, collects and manages forestry statistical data etc.
4. The Ministry of Energy provides the projected activity data on energy sector
development. The provided data was based on the results of the study made by the
Lithuanian Energy institute (contracted by the Ministry of Energy in 2014). This
analysis of different scenarios in energy sector development until 2030 was made
with an optimization model (MESSAGE).
5. The Ministry of Transport and Communication and its subordinated institutions
provide projected information on transport sector’s development. The projected
activity data was based on an expert judgment by the competent experts and newly
adopted the National transport and communication development programme for
2014-2022.
6. The Ministry of Agriculture provides information on projected animal number based
on the projected agriculture sector economic development, and the information on
planned use of synthetic fertilizers and capacities of biogas production. The
projection of development of agriculture sector is made by the Lithuanian Institute
of Agrarian Economics.
The largest Lithuania’s industry companies provide information on their planned production
capacities.
Conclusions The general organizational characteristics are:
All three Baltic States involve mostly the same organizations as in the NIR preparation;
Involvement of the sectoral ministries is higher compared to NIR reporting –ministries
mostly provide sectoral activity data projections that are compiled by the same
organizations that organize compilation of NIR reports.
2.3. GHG inventory data sources There is no one single approach to collect activity data and emission factors for inventories
and projections. Different methods can be used to estimate emissions or removals from
most source and sink categories as well as to project emissions in the future. However, they
have to be in line with the 2006 IPCC Guidelines24. The selection of a particular method
depends on the desired degree of estimation detail, the availability of activity data and
emission factors, and the financial and human resources available to complete the
inventory.
As regard to the LULUCF, each country applies its own definitions and methods to estimate
GHG emissions (Blujdea et al., 2015). There are also significant uncertainties with regard to
the GHG emission calculations. The lack of data and poor emission factors may cause
uncertainties of up to a factor of ten (Nowak et al., 2012), especially in the data-poor
regions.
24 http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/1_Volume1/V1_2_Ch2_DataCollection.pdf
32
These uncertainties can be reduced both by use of the higher-tier calculation method and by
improving the accuracy of the parameters, including the use of more geographically explicit
emission factors, employed in the emissions calculations (Ometto et al., 2014).
Therefore all the countries are investing to improve calculation methods and data used for
the calculations, e.g. by organizing meetings between sectoral experts in order to discuss
problems and possible improvements in GHG inventory as well as to ensure consistency
between activity data used by experts in emission estimation for different sectors, or
carrying out studies – according to the NIR, during the years 2012-2013 Lithuania has done 6
studies aiming to improve the quality of the activity data, process information and emission
factors in 5 sectors and in 2015-2017 had implemented Norway Grants partnership project,
during which several studies in LULUCF sector and energy sector were performed. Latvia has
also done several studies and is implementing 2009 – 2014 EEA (European Economic Area)
Grants Programme National Climate Policy, including the project “Development of the
national system for greenhouse gas inventory and reporting on policies, measures and
projections” as well as preparing and annually updating instruction for GHG inventory as
well as instructions on estimations and methodologies for each sector.
To analyze the available activity data and emission factors we used National Inventory
Reports and Common Reporting Format available at UNFCCC GHG emission database25. We
used the latest data available (2014). For Latvia, it was Inventory Submission 2016 v3, for
Lithuania Inventory Submission 2016 v2, for Estonia Inventory Submission 2016 v1.5.
However, it should be noted that Estonia has requested not to publish their latest CRF tables
on the UNFCCC secretariat webpage due to ongoing issues with the CRF reporter.
2.3.1. Uncertainties As in most of the models, also GHG emission estimates are uncertain. The main causes of
uncertainty are uncertainties in emission factors, activity data (typically estimated from
sample surveys and these estimates will be uncertain unless the whole population is
surveyed accurately), and methods used (so far, UNFCCC methods are the most reasonable)
(Milne et al., 2014, Lesiv et al., 2014). However, the reason for changes in reported
uncertainties can be due to the structural changes in emissions or “learning’ - increased
knowledge about inventory processes (Lesiv et al., 2014).
These uncertainties exist in all the sectors. In the EU the uncertainty of GHG emissions from
fossil fuel burning is still considerable (up to 10%) (Ometto et al., 2014) and influences the
results of GHG inventories. Other sectors’ emission sources, such as industrial processes,
agriculture, forestry and other land uses, and waste, cause lower emissions of certain kinds
but could have much higher uncertainty. For some countries, the uncertainties in GHG
emissions in these categories can be less than 25% or more than 100% due to the
insufficient accuracy of input data and models (Ometto et al., 2014).
25 http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/9492.php#fn6 http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/9492.php#fn6
33
Table 2.2. demonstrates that there are also significant uncertainties in the emission
calculation for the Baltic States. The highest uncertainty for the total 2014 inventory is in
Lithuania (±53.5%) and the lowest uncertainty in Estonia (±4.13%). The highest uncertainty
in Latvia and Lithuania arises in LULUCF, however in Estonia results are the most precise
excluding LULUCF. Uncertainties in national total emissions without LULUCF are generally in
the range between 3 and 8% (Pulles, 2017) - making the Baltic States at the highest level of
uncertainty (see table 2.2.).
Table 2.2. Uncertainties of 2016 submission
Uncertainty in total inventory % Trend uncertainty %
EE LV LT EE LV LT
With LULUCF 4.1 16 53.5 1.8 11 10.4
Without LULUCF 7.2 8 9.3 9 2 2
We have looked only at some of the sectors and gasses to see the level of uncertainty and
differences among countries. Lithuania list all the uncertainties related to the total
inventory, activity data and emission factors in tabular format in the NIR Annex. Estonia and
Latvia provide tables with all the uncertainties listed within the NIR. We have combined the
uncertainty calculations of the CO2 emissions related to the fuel combustion in Table 2.3.,
which shows that countries refer to significantly different levels of uncertainty in activity
data and emission factors used.
Research (Marland, 2008) in other countries show, that the estimates of CO2 emissions from
fossil fuels consumption are the most accurate for comparison with other source categories
(uncertainties are estimated in the range of ±5%). Uncertainties in other sectors could be
higher.
Table 2.3. Estimated relative uncertainties of CO2 emission due to Fuel combustion in 2014
GHG Categories
Uncertainty of activity data, % Uncertainty of emission factor, %
Countries EE LV LT EE LV LT
Liquid Fuels 1.7 2 2 1.8 10 2.5
Solid Fuels 3.3 2 2 38.9* 20 7
Gaseous Fuels
1.4 2 2 3.6 5 PS (natural gas)
2.5
Other Fuels* 5 2 2 60 20
Peat 2 2 10 CS (peat) 7
Biomass 5 30 50 50
*The uncertainty of the emission factors of the solid fuels category 1.A.1a is significantly
lower – 2.39%.
34
Differences among the three Baltic States in uncertainties of emission factors are also seen
in other sectors and for other gasses, e.g. there are significant differences in uncertainties of
emission factors in the case of CH4 and N2O26:
In Latvia uncertainty for most of the sectors both for CH4 and N2O emissions factors
of 50% was assigned;
In Lithuania uncertainty both for CH4 and N2O emissions factors of 150% was
assigned;
In Estonia, uncertainty for emissions factors for CH4 was 50% and for N2O - 60%.
These differences in uncertainties arise from the differences in the activity data and
emission factors used for calculations of GHG emissions.
Uncertainties in the inventory are assessed by the experts, but the overall uncertainty of the
inventory is evaluated by the national environmental protection agencies – EERC in the case
of Estonia, the Climate Change Division at the Environmental Protection Agency in Lithuania
and Latvian Environment, Geology and Meteorology Centre.
2.3.2. Activity data For most of the data used in the calculations, countries are using national statistics.
However, in some cases also other databases and data from specific plants are used.
Improvements in the quality of the activity data is an ongoing process performed by all the
countries.
Experts at the BENGGI project meeting (25.10.2016.) specifically highlighted problems
related to the F-gases activity data:
F-gas activity data reported by operators (completeness and correctness problem);
Several assumptions within this sector (develop common approach regarding used
assumptions between Baltic states);
How to avoid possible double counting (data by services and operators in one
database).
However, similar problems with activity data also exist in other sectors, e.g. agriculture,
IPPU, energy, LULUCF, waste sectors. Below you will find some of the examples of activity
data mentioned in the latest NIRs.
Estonia
Activity data used in calculations in carbon balances are collected from private companies
and are therefore considered confidential. Activity data on oil shale, shale oil, and oil shale
gasses production by oil companies and calculations of carbon balances are not part of the
national inventory report and are allocated into the archive. The data can be made available
during the review process for the review team.
26 For more details on uncertainties of the activity data and emission factors look in the “Annex 2: Assessment of Uncertainty” of the National Inventory reports.
35
Activity data on lubricants and bitumen consumption is received from IEA statistics; the
national statistics does not publish this data. Data on natural gas use for non-energy use are
taken from national energy balance sheet.
Forest activity data and growing stocks are obtained from the National Forest Inventory
(updated annually). The entire time series of activity data is annually recalculated for all
areas of land categories and land-use conversions since new data about land-use transitions
are collected every year and new estimates will be integrated into overall activity data.The
activity data for estimating N2O from advanced centralized wastewater treatment plants is
kept under consideration and the emission calculation will be included as soon as activity
data is available.
Latvia
Main activity data provider for Latvia’s GHG inventory is Central Statistical Bureau (CSB),
which has established Quality Guidelines27 - an informative document describing stages,
methods and organizational principles of producing the national statistics, the policy of data
protection and dissemination. The purpose of the Guidelines is to ensure higher quality to a
maximum extent from both ethical and professional aspect, national statistics similarly to
the Community statistics must follow the principles of impartiality, reliability, relevance,
cost-effectiveness, statistical confidentiality, and transparency.
In its NIR Latvia is providing a table (Table 1.3. Main data sources for activity data and
emission values) describing the main sources of activity data used for the calculations and
high transparency. The main sources are:
For the Energy (excluding Transport) – data collection and emission estimation are
done by LEGMC experts:
o Energy balance from Latvian Central Statistical Bureau;
o IEA/ OECD – EUROSTAT – UN Economic Commission for Europe (ECE) Annual
questionnaires;
o LEGMC “2-AIR” database;
o Researches of experts.
For the IPPU – data collection and emission estimation are done by LEGMC experts:
o National production and sales statistics;
o Direct information from enterprises operating with pollutants;
o Central Statistical Bureau;
o Chemicals Database;
o Assumptions by experts;
o State Agency of Medicines;
o Researches by experts;
o LEGMC “2-AIR” database
For Transport activity data is collected and emissions are calculated by an expert
from Institute of Physical Energetics:
o Energy balance from Central Statistical Bureau;
o IEA/AIE – EUROSTAT – UN ECE Annual questionnaires;
o Data of Road Traffic safety Directorate;
27 Central Statistical Bureau Quality Guidelines (http://www.csb.gov.lv/en/dokumenti/quality-guidelines-30868.html).
36
o Researches of experts.
For Agriculture, data collection and emission estimations are done by the Latvia
University of Agriculture in collaboration with Ministry of Agriculture:
o National agricultural statistics obtained from CSB;
o National studies.
LULUCF data and KP- LULUCF data are collected and emissions/removals are
calculated in Latvian State Forest Research Institute "Silava" in collaboration with
Ministry of Agriculture and Latvia University of Agriculture.
o National forest inventory
o State forest service
o Ministry of Agriculture
o Central Statistical Bureau
o State Firefighting & Rescue Service
o National studies and expert judgments
For the Waste – data collection and emission estimation are done by LEGMC
experts:
o LVGMC “3-Waste” and “2-Water” databases;
o Methane recovery installations;
o CSB.
All experts responsible for data collection and processing in a particular sector are preparing
their data (activity data, emission factors) for import into CRF Reporter software.
Lithuania
Table 2.4. summarizes the most important data sources used in Lithuania’s GHG inventory. Table 2.4. Main data sources used in Lithuania’s GHG inventory
Sector Main data sources
1.A Energy: Fuel
Combustion
Energy Statistics database (Statistics Lithuania)
EU ETS emission data
1.B Energy: Fugitive
Emissions
Energy Statistics database (Statistics Lithuania)
Lithuanian Geological Service
Individual companies
2. Industrial Processes
and Product Use
Individual production plants
EU ETS emission data
Industrial statistics database (Statistics Lithuania)
F-gases database (EPA)
Published literature
3. Agriculture The Register of Agricultural Information and Rural Business
Centre of Ministry of Agriculture
Agricultural Statistics database (Statistics Lithuania)
Published literature
International fertilizer association (IFA)
4. LULUCF NFI (National Forest Inventory)
State Forest inventory
Lithuanian Statistical Yearbook of Forestry
Published literature
5. Waste Waste database (EPA)
37
Water and wastewater database (EPA)
Regional Waste Management Centres
2.3.3. Confidentiality Some of the data used in the compilation of the inventories are confidential and cannot be
published in print or electronic format. Due to a small market of the Baltic States, some
activity data can be considered confidential.
Lithuania in its NIR does not report major confidentiality issues. However, in most of the
Industrial processes categories in Estonia, there is only one major manufacturer. Therefore,
due to reasons of confidentiality, only aggregate figures are provided in the CRF. Also,
activity data on oil shale, shale oil, and oil shale gasses production by oil companies and
calculations of carbon balances are not part of the national inventory report and are
allocated into the archive.
For Latvia’s GHG Inventory mainly confidentiality is related to activity data provided by CSB.
The data then cannot be reported further but can be used for emission estimation. To deal
with this issue in Latvia LEGMC has an interdepartmental agreement with CSB to receive
confidential information for the emission estimation but these activity data has to be
reported as confidential in CRF Tables and in NIR. If the data that could be considered as
confidential is provided to LEGMC by production plan or another enterprise then the data is
not considered as confidential and can be reported within GHG Inventory.
Although this requirement impairs the transparency of the inventory, all confidential data
nevertheless can be made available to the official review process of the UNFCCC.
2.3.4. Emission factors In the Baltic States, the main sources for emission factors are national studies for country
specific parameters (e.g. CO2 emission factors, aspects influencing SO2 emission factors,
distribution of animal waste management systems, average N excretion rates, etc.) and
plant-specific parameters, as well as following guidelines:
2006 IPCC Guidelines;
2013 Supplement to the 2006 IPCC Guidelines for National GHG Inventories:
Wetlands (IPCC Wetlands Supplement);
2013 Revised Supplementary Methods and Good Practice Guidance Arising from the
Kyoto Protocol (IPCC KP Supplement);
EMEP (European Monitoring and Evaluation Programme) /CORINAIR Guidebook
2007 and EMEP/EEA 2009;
EMEP/EEA air pollutant emission inventory guidebook 2013.
The comparison of the emission factors used by three Baltic States in their national
inventories was realized in this study (Annex 2.3). The following notation keys were used to
specify different emission factors:
D (IPCC default)
CR (CORINAIR)
CS (Country Specific)
38
PS (Plant Specific)
OTH (Other)
M (model)
From the summary Table 2.5. it can be seen that the most common emission factors used by
all the Baltic States and for all the gasses are the default IPCC factors (D)28. In Estonia's
inventory D factors have been used 57 times (27 times as the only factor), in Latvia 65 times
(33 times as the only factor), but in Lithuania 74 times (29 times as the only factor).
However, the use of country-specific emission factors rather than IPCC default values is
increasing in all the Baltic States. The use of country-specific emission factors ensures
greater accuracy and lower uncertainty of GHG inventory (Konstantinaviciute and Bobinaite,
2015). However, in many cases, it is sufficient to use default emission factors in the
inventory. Generally, development of country specific emission factors requires more
resources and it may be not feasible to use more rigorous factors for every category of
emissions and removals in the development of GHG inventory. Inventory compilers should
prioritize their efforts and identify its national key categories in a systematic and objective
manner and use the results of key category analysis as a basis for methodological choice and
country specific emission factors development.
Table 2.5. Emission factors used in the Baltic States.
Type of emission factor Latvia Lithuania Estonia
D (IPCC default) 65 (33) 74 (29) 57 (27)
CR (CORINAIR) 8 8 0
CS (Country Specific) 28 (3) 43 (5) 35 (9)
PS (Plant Specific) 7 15 (4) 6
OTH (Other) 15 4 7 (2)
M (model) 0 0 0
Note: number in the brackets means how many times particular emission factor has been
used as the single factor.
In LULUCF generally, default IPCC emission factors are used (with a few exceptions; e.g.,
Sweden uses its own subsidence data for cropland or belowground litter input and
heterotrophic respiration for grasslands) (Blujdea et al., 2015). However, analyses
demonstrate that in the Baltic States countries are also using country specific, CORINAIR and
other factors.
Second most utilized emission factors are country specific (CS) factors which are used in 28
(3) cases in Latvia, 43 (5) times in Lithuania and 35 (9) times in Estonia. Use of the country-
specific emission factors rather than IPCC default values is increasing and this is improving
the accuracy of GHG inventories (decreasing uncertainty).
Lithuania and Latvia are also using emission factors from CORINAIR database (CR) to
calculate emission in the fuel combustion and metal industry sectors (in the case of Latvia)
28 Data on the Defalt emission factors can be found at the IPCC emissions factor database (www.ipcc-nggip.iges.or.jp/EFDB/).
39
and non-energy products from fuels and solvent use (in the case of Lithuania) (8 times each,
but always in combination with other factors).
In the case of CO2 emissions in fuel combustion and industrial processes countries are also
using plant specific (PS) emission factors: in 7 cases in Latvia, 15 (4) times in Lithuania and 6
(2) times in Estonia. Lithuania PS emission factors are also using as regards to emissions of
other gasses (N2O, HFCs, and SF6).
In some cases countries are also using other emission factors. The use of notation OTH is
explained in detail in the NIRs. Latvia is using other factors more than others are (in the
sectors of transport and mineral industries). All the countries are using other factors for the
calculation of CH4 emissions from the enteric fermentation.
Refining emission factors and incorporating mitigation into national inventories is both
difficult and expensive, with many countries lacking either the scientific or the financial
resources to develop their own higher Tier factors that would allow for the incorporation
and exploitation of additional mitigation options.
According to the IPCC Guidelines for NI, if an activity is a key emission category for a country,
it is a good practice to develop and to apply a country specific emission factor for that
activity. However, all the Baltic states still utilize Default emission factors for some of the
categories with the highest national emissions, e.g.
In Latvia D factors in combination with the country specific factors are used for the
following categories: 4.B.1 Cropland remaining Cropland Drained organic soil, 4.C.2
Land converted to grassland - net carbon stock change in mineral soils and 5.D.1
Wetlands remaining Wetlands\Peatland - organic soils managed for peat extraction;
In Estonia Default factors are used for the following categories: the 1.A.1.a Energy
Industries/Public Electricity and Heat Production - Solid Fuels, 1.A.3.b
Transport/Road Transportation - Liquid Fuels, 4.B.1 Cropland remaining Cropland
Drained organic soil, 4.B.1 Cropland remaining Cropland - organic soils, 5.D.1
Wetlands remaining Wetlands\Peatland - organic soils managed for peat extraction;
In Lithuania, Default factors are used for the following categories: 4.A.1 Forest land
remaining forest land - carbon stock change in biomass; 4.B.2 Land converted to
cropland - net carbon stock change in mineral soils.
Estonia
Estonia is using CS and PS carbon emission factors for most of the fossil fuels and has a well-
developed methodology for the emissions from Oil Shale. However, at the same time uses
Default approach for biomass. Calculations of CH4 and N2O emissions from fuels (except for
Oil Shale where CS emission factors are used) are based on the Default approach as well.
For industrial processes and product use Estonia is using a mixture of emission factors. For
Mineral industry, mostly PS emission factors are used, for Chemical industry, D factors
dominate, but for Product use and Other products, CS emission factors exist.
For methane emission from Agriculture sector mixture of D and CS emission factors but for
N2O only Default factors are used in Estonia, e.g. CH4 emission factors, recommended by the
2006 IPCC Guidelines for developed countries, were used to estimate emissions from Enteric
fermentation of sheep, goats, and horses, but emission factors for fur animals were provided
by a Finnish expert.
40
Estonia does not have CS emission factors for soils and litter for most of the land use
categories. As an interim approach, carbon stock change estimates of these pools are based
on emission factors from the Sweden National Inventory Report 2015. CS emission factors
were implemented for wetland/peatland emissions. Dead wood is estimated with the Tier 3
method based on Estonia’s own emission factors by Köster et al. (2015).
Due to the lack of national research, Estonia is employing only Default emission factors in
estimations of GHG emissions from each sub-sector of the Waste sector.
Latvia
Where data of bottom-up method were available and plants had reported estimated data
using plant-specific emission factors and estimation methodologies for the Energy sector,
these data were used in the submission. If these data were not available, Tier 1 method
from 2006 IPCC Guidelines was used to estimate emissions. Emissions from the whole
country fuel consumption were estimated by adding up fuel consumption of individual
sectors multiplied by appropriate emission factors.
Emissions from Road Transport sector were estimated by using COPERT IV model for 1990–
2014 (Tier-2 method). Emissions for other transport sub-sectors were estimated according
to IPCC Tier 1 and Tier 2 methodologies (Tier 2 method for diesel oil CO2 emission calculation
in railway and navigation and Tier 2 method for jet kerosene emission calculation in aviation
(civil and international). Rest of emissions have been calculated by Tier 1 method).
Emissions from Industrial Processes and Product Use were estimated according to 2006 IPCC
Guidelines, EMEP/CORINAIR 2007 Guidebook, EMEP/EEA 2009, EMEP/EEA air pollutant
emission inventory guidebook 2013 as well as using expert research and judgment about
activity data and emission factors.
Emissions from Agriculture sector were estimated according to methodologies from 2006
IPCC Guidelines; IPCC Wetlands Supplement additionally using local researchers related
some parameters.
2006 IPCC Guidelines, IPCC KP Supplement, and IPCC Wetlands Supplement for CO2, CH4 and
N2O emissions from drained and rewetted soils were used to estimate emissions from
LULUCF and KP-LULUCF sector.
2006 IPCC Guidelines were used to estimate emissions from the Waste sector.
Lithuania
Lithuania is using CS CO2 emission factors for most of the fuels. These emission factors were
developed in study "Update of country specific GHG emission factors for energy sector"
performed by Lithuanian Energy Institute in 2016. CH4 and N2O emissions from combustion
of fuels are estimated using emission factors recommended in 2006 IPCC Guidelines except
for stationary combustion of biomass in other sectors (1.A.4.a.i, 1.A.4.b.i, 1.A.4.c.i) where CS
emission factors are used. In addition to this, CS factor is used for fugitive emissions of
natural gas.
For most of key categories in IPPU sector Lithuania is using CS or PS emission factors:
cement, other process use of carbonates, nitric acid, ammonia, electronics industry
emissions. Emissions of cast iron production, F-gases, non-energy products from fuels and
solvent use are estimated using mostly D emission factors.
41
For CH4 emission from Agriculture sector mixture of D and CS emission factors are used. CS
emission factors are mostly used for key sources: emissions from cattle, sheep and swine
and D emission factors are used for less significant emissions from remaining livestock
species. For N2O emissions from agricultural soils only D factors are used in Lithuania.
Lithuania lacks several emission factors or carbon stock change factors in LULUCF sector.
Currently default value of carbon stock change in forest litter from IPCC 2006 Guidelines is
used. In the next submissions Lithuania is planning to implement national values obtained
during the study of carbon stocks changes in litter and soil carried out during the partnership
project with Norwegian Environment Agency. Lithuania is using default emission factors to
estimate emissions from drained organic soils in forest land, cropland and grassland
categories as well as emissions from peat extraction sites. Lithuania is planning to
implement national initial carbon stock (SOCREF) values for cropland and grassland,
obtained during the above mentioned partnership project, to estimate carbon stock changes
in the event of conversion between those categories while at the moment default values
calculated by Joint research Centre (JRC) are used.
In waste sector, Lithuania is using D emission factors in estimations of GHG emissions from
each sub-sector.
2.4. Methods for inventory Analysis of inventory methods was performed using data provided by the Baltic States in the
CRF reporter reporting excel that was compared between countries. 10 methodological
options are proposed in reporting for selection:
D (IPCC default)
RA (Reference Approach)
T1 (IPCC Tier 1)
T1a, T1b, T1c (IPCC Tier 1a, Tier 1b and Tier 1c, respectively)
T2 (IPCC Tier 2)
T3 (IPCC Tier 3)
CR (CORINAIR)
CS (Country Specific)
OTH (Other)
M (model)
Comparison of methods used for three Baltic States is displayed in the Tables 2.6., 2.7. and
2.8. below by general categories for each gas. The more detailed comparison table is added
in Annex 2. Latvia and Lithuania are presented using 2016 NIR tables submitted, but for
Estonia 2017 submission was available.
For CO2 emissions mostly T1, T2, T3 are used. For industrial processes, Latvia indicates also
country specific and IPCC default methods, Estonia - IPCC default, but Lithuania also country
specific and CORINAIR. For LULUCF Estonia indicates also T3 compared to other states. In
waste sector, Latvia indicates IPCC default, but Estonia also T2 additional to T1.
42
For CH4 also mostly T1, T2 are used, but Latvia and Estonia have used also IPCC default
methods. Estonia and Lithuania have used T3 for Energy sector.
Table 2.6. Use of the calculation methods (CO2 and CH4)
Sectors LV EE LT
CO2
1. Energy T1,T2,T3 T1,T2,T3 T1,T2,T3
2. Industrial processes CS,D,T1,T2,T3 D,T1,T2,T3 CR,CS,T1,T2,T3
3. Agriculture T1 D,T1 T1
4. LULUCF T1,T2 IE,T1,T2,T3 T1,T2
5. Waste D T1,T2 T1
CH4
1. Energy T1,T2 T1,T2,T3 T1,T2,T3
2. Industrial processes T1 NA NA
3. Agriculture T1,T2 D,T1,T2 T1,T2
4. LULUCF D,T1,T2 T2 T1,T2
5. Waste D,T2 T1,T2 T1,T2
For N2O also mostly T1, T2 are used. Estonia and Lithuania have used T3 for Energy sector.
For industrial processes, each country has different methods. In agriculture Estonia has used
also country specific and IPCC default methods.
Table 2.7. Use of the calculation methods (N2O)
GREENHOUSE GAS SOURCE AND SINK LV EE LT
CATEGORIES N2O
1. Energy T1,T2 T1,T2,T3 T1,T2,T3
2. Industrial processes CS T2 D,T1,T3
3. Agriculture T1,T2 CS,D,T1,T2 T1,T2
4. LULUCF D,T1,T2 T1,T2 T1,T2
5. Waste D T1,T2 T1
Other gasses refer to industrial processes. For HFCs, T2 is used, but Lithuania has used also
T1a and T1b. For SF6 Estonia and Lithuania have used T3, but Latvia T1. For NF3 only
Lithuania has indicated a method used – T2.
Table 2.8. Use of the calculation methods (other gasses)
GHG SOURCE AND SINK LV EE LT LV EE LT LV EE LT LV EE LT LV EE LT
CATEGORIES HFCs PFCs SF6
Unsp. mix of HFCs and
PFCs NF3
2. Industrial processes
NO, T1a, T2 T2
T1a, T1b, T2
NO NA NA T1 T3 T3
NO NA NA
NO NA T2
43
In general, T1 and T2 are the most frequently used methods in all Baltic States, but also IPCC
default methods are used in at least two countries for gasses CO2, CH4, and N2O.
2.5. Methods, emission factors and uncertainties for key categories A detailed comparison of methods, emission factors and uncertainties for key categories was
prepared. For each of the Baltic States, the most important key categories were selected
representing cumulative 50% of total emissions. Approach 1 level assessment with LULUCF
tables from the 2016 NIR (2017 NIR for Lithuania) reports were used for selection of the
most important key categories. For each of the selected categories methods, emission
factors and uncertainties were identified for all three Baltic States to assess if there is a
potential to learn from each other in how to move to the higher tier level for the main key
categories. The methods, emission factors, and uncertainties were identified in the NIR for
each country. Where the data was not clearly defined in the NIR the most likely assessment
was made according to the description of the method. Therefore this comparison should be
assumed as indicative and may be corrected with more precise data by sectoral experts. The
results are presented in Table 2.9.
Table 2.9. Comparison of methods, emission factors and uncertainties for the most
important key categories (top cumulative 50% from Approach 1 level assessment with
LULUCF) Note: gray areas indicate the country in which the category is within top 50% of key
categories)
METHODOLOGY
UNCERTAINTY
Method
Emission factor
Activity data uncertainty
Emission factor / estimation parameter
uncertainty
IPCC category/Group Gas LV EE LT
LV EE LT
LV EE LT LV EE LT
1.A.1.a Public Electricity and Heat Production - Gaseous Fuels
CO2 T2 T2, T3
T2
CS CS, PS
CS
2% 1% 2% 5% 4% 2%
1.A.1.a Energy Industries/Public Electricity and Heat Production - Solid Fuels
CO2 T2 T2, T3
T2
CS, PS
CS
2%
3% 2%
20%
2% 5%
1.A.1.c Energy Industries/Manufacture of Solid Fuels and Other Energy Industries - Solid Fuels
CO2 T2 T2, T3
T2
CS, PS
CS
2%
3% 2%
20%
39% 5%
1.A.3.b Road transportation
CO2 T2 T1, T2
CS D,
CS
2% 2%
1.A.3.b Transport/Road Transportation - Liquid Fuels
CO2 T2 T2 T1, T2
CS D D,
CS
2% 2% 2% 2%
1.A.3.b Road Transportation - Diesel Oil
CO2 T2 T2
CS CS
2% 2% 2% 2%
2.B.1 Ammonia Production
CO2 T3 T3
PS PS
1% 2% 4% 3%
3.D.1.1 Direct Soil Emissions - Inorganic N Fertilizers
N2O T1* T3 T1
CS CS D
10% 15% 200% 135%
44
3.D.2.2 Indirect Emissions - Nitrogen Leaching and Run-off
N2O T1 T2 T1
D CS D
18% 20% 287% 163%
4.A.1 Forest Land remaining Forest Land Drained organic soil
CO2 T2 T2 T1
CS CS (SE)
D
5% 3% 4%* 25%
40% 36%*
4.A.1 Forest Land remaining Forest Land Carbon stock change, dead wood
CO2 T2 T3 T1*
CS CS D*
2% 2% 4%* 5% 20% 36%*
4.A.1 Forest land remaining forest land - carbon stock change in biomass
CO2 T2 T2 (M2)
T1 (M2)
CS CS D*
4%* 36%*
4.A.1. Forest Land remaining Forest Land- mineral soils
CO2 T2 T2 T1
CS CS (SE)
D
1% 4%* 60% 36%*
4.A.2.2. Grassland converted to Forest Land - living biomass
CO2 T2 T2 T2*
CS CS*
31% 3%* 47% 75%*
4.B.2 Land converted to cropland - net carbon stock change in mineral soils
CO2
T2 T1
CS D
2%* 67%*
4.B.1 Cropland remaining Cropland Drained organic soil
CO2 T1; T2
T1 T1
CS, D
D D
114% 74% 2%* 18%
90% 67%*
4.C.2 Land converted to grassland - net carbon stock change in mineral soils
CO2 T1; T2
T1
CS, D
CS
3%* 75%*
4.G. Harvested wood products
CO2 T2 T1
CS D
15% 15% 0% 59%
4.G. Wood panels and sawnwood
CO2 T1 T1
D
63% 15%* 80% 59%*
5.D.1 Wetlands remaining Wetlands\Peatland - organic soils managed for peat extraction
CO2 T1; T2
T2 T1
CS, D
CS D
21% 6%* 50% 204%*
* data or provided for group of categories or should be checked for more precise identification of
methodological level
Source: Green Liberty
Comparison of the most important key categories suggest that is a group of categories
where is recommended to compare the methodologies among countries in detail to find if
the best practice could be changed:
- All listed LULUCF categories. There are indications that there are differences in the level
of approaches among countries. However, the description of methodologies in the NIR
reports did not allow making a strong conclusion about best approaches. Therefore, it is
recommended to explore more detailed comparison among sectoral experts in the
categories:
o 4.A.1 Forest Land remaining Forest Land Drained organic soil
o 4.A.1 Forest Land remaining Forest Land Carbon stock change, dead wood
o 4.A.1 Forest land remaining forest land - carbon stock change in biomass
o 4.A.1. Forest Land remaining Forest Land- mineral soils
o 4.A.2.2. Grassland converted to Forest Land - living biomass
o 4.B.2 Land converted to cropland - net carbon stock change in mineral soils
o 4.B.1 Cropland remaining Cropland Drained organic soil
o 4.C.2 Land converted to grassland - net carbon stock change in mineral soils
45
o 4.G. Harvested wood products
o 5.D.1 Wetlands remaining Wetlands\Peatland - organic soils managed for peat
extraction
2.6. Methods for projections
2.6.1. Structure and contents of reporting Analysis of methods for projections was based on an assessment of five documents for each
of the Baltic State:
The 6th national communication under the UNFCCC (2013);
2nd Biennial report under the UNFCCC (2015);
Reporting on policies and measures under article 13 and on projections under article
14 of regulation (EU) No 525/2013 of the European parliament and of the council
(2015);
Reporting on parameters for projections used – with the reporting template Table 3
under the Article 23 of regulation (EU) No 525/2013 of the European parliament and
of the council (2015);
Model Factsheet - with the reporting template Table 4 under the Article 23 of
regulation (EU) No 525/2013 of the European parliament and of the council (2015).
The last two - Model Factsheet and Reporting on parameters for projections used – are excel
spreadsheets providing most comparable data on the methodology of projections. All the
Baltic States have completed the templates. The general differences refer to the nature of
models used. Latvia and Estonia have indicated models for energy sector modeling. Estonia
also uses model for waste sector. However, Lithuania indicated that they do not use specific
models and make individual projection calculations. Therefore, they have not fulfilled the
Model factsheet (Annex 4).
Description of methodologies for projections are included in all three reports – the 6th
National communication and the 2nd Biennial report under the UNFCCC as well as reporting
on policies and measures to the European Parliament and the Council. There is some
overlapping observable and lack of clear distinction between information provided in each
of three reporting documents.
There were differences among the Baltic States on the type and detail of information
provided in the National communication and BR.
Latvia provided more detailed information on energy model in the 6th National
communication, but no information on methodology in the other sectors. The 2nd Biennial
report included information on the other sectors, but the total amount of detail was
decreased. However, annex with the Summary of key variables and assumptions used in the
projections analysis (same as in the table of parameters) is included in the report. The
general macroeconomic assumptions were included in the methodology description in the
6th national communication, but main assumptions for modeling were included in the
descriptions for projected emissions per sector in both reports.
Reporting document on policies and measures under article 13 and on projections under
article 14 of regulation (EU) No 525/2013 of the European parliament and of the council
46
includes the same method (model) description as in the 6th national communication, but
with less detail on assumptions.
Estonia provided information on methodology in all the sectors both in the 6th National
Communication and the 2nd Biennial report. The Biennial report includes a more detailed
explanation on other sectors but energy. Both documents include separate sub-section for
the main assumptions. Reporting to the European Parliament and the Council includes
slightly shorter but comprehensive description than in the 2nd Biennial report.
Lithuania provided more detail on the assumptions for each sector in the 6th National
communication as no specific pre-defined model was used. The Biennial report includes
more detailed information on assumptions including specific assumptions on effects for
separate PaMs. Reporting to the European Parliament and the Council is structured in a
different manner compared to UNFCCC reports or reports provided by Latvia and Estonia.
Description of each sector includes three subsections: Overview of the sector,
Methodologies and key assumptions, Projections of GHG Emissions.
The main comparison tips and conclusions for reporting contents and structure Latvia,
Estonia, and Lithuania:
- Estonia and Lithuania provided more detailed information on methodology in the 2nd
Biennial report compared to the 6th National communication. Latvia – wider, but less
detailed information.
- Estonia and Latvia provided basically the same information to the European Parliament
and the Council as in the UNFCCC reports. Lithuania incorporated methodology in the
description of the sector projections.
- Latvia and Estonia use ready-made models for the energy sector, but Lithuania-not. That
should be the main reason for Lithuania to include a very detailed description of
assumptions for improving transparency.
- As many assumptions are not clearly separated in the text for Latvia, the presented
format could create diffuse perception effect for completeness. Therefore, it would be
recommended to describe the assumptions separately or summarize them. It would be
also recommended for Latvia to add details of methodology for sectors other than
energy to reduce the effect of non-proportional description.
- There are preferences for the perception of the text if the methods and assumptions are
united in logical text within the description of projections based on clear WEM and
WAM contents and scenarios.
2.6.2. Models and methods used In recent decades, several models (e.g. bottom–up, top–down, and hybrid models) have
seen a rapid improvement in the possibility to analyze the interaction between the economy
and GHG emissions on global, national, and sectoral levels. These range from bottom-up
accounting models for the economic sector to top-down models of the whole economy, e.g.
for the energy sector, the most common models include accounting frameworks (LEAP and
STAIR), optimization models (MARKAL and ETO), and an iterative equilibrium model (ENPEP)
(Sathaye and Meyers, 2013).
Each of these models may be used for integrated assessment of demand and supply
although the approach and method vary among them. Independently developed bottom–up
47
and top–down models are combined together through soft-linked (e.g. MARKAL-MACRO
energy system model) and hard linked (e.g. the WITCH (World Induced Technical Change
Hybrid model), GAINS-AIM/CGE, and GAINS-ECSC) (Zhang et al., 2015).
Sathaye and Meyers (2013) in their book “Greenhouse gas mitigation assessment: a
guidebook” have analyzed these analytical tools for mitigation assessments and classified
them in the way described in Table 2.10.
Table 2.10. Examples of Analytical Tools Available for Mitigation Assessments
Topic Analytical Tools
Energy Sector
Accounting Models LEAP, STAIR
Optimization Models MARKAL, ETO
Iterative Equilibrium Model ENPEP
Decision Analysis Framework Analytical Hierarchy Process (AHP)
Energy-Economy Interaction LBL-CGE, MARKAL-MACRO
Non-Energy Sectors
Forestry COPATH, COMAP
Agriculture EPIC, CENTURY
Rangelands CENTURY
Waste Management Landfill Gas Model
Source: Sathaye and Meyers, 2013
Some of these models have been used also in the Baltic States. Latvia has reported using one
model for energy sector – MARKAL, but Estonia – two: LEAP for the energy sector and IPCC
Waste Model 2006 for waste sector. Lithuania has reported that no specific models have
been used for the projections of GHG emissions. They have done calculations based on 2006
IPCC guidelines using Microsoft Office Excel. Annex 4 of this report provides more
information on the models used by Latvia and Estonia. Observation under this research
suggests that the general difference in reporting is in the level of detail – Estonia provided
only minimal information referring to URL (Uniform Resource Locator) instead of
descriptions.
A general comparison of models and methods is described below for each sector separately.
Energy sector
Methods for projections and style of reporting on methods differs for all three Baltic states.
Lithuania uses its own calculations based on 2006 IPCC guidelines. Estonia and Latvia use
more comprehensive models that allow modeling of energy demand and supply. Latvia uses
adopted MARKAL model (version - 5.9g. Latvia database version - 14.0), but Estonia is using
energy accounting model - LEAP.
48
According to the information reported by Lithuania, projections were carried out by
determining the consumption of fuel in every subsector up to the year 2030. Since the GHG
emissions are directly linked to the final fuel consumption the calculation of GHG emissions
could be performed by linearly interpolating them according to changes in the final fuel
consumption.
According to the information reported by Latvia, calculation principles of the MARKAL model
include projection on prices of energy resources, as well as useful energy demand (energy
service demand) or other secondary parameters, like the area of heated premises of
buildings or mileage of cars that reflects the required amount of energy are needed as the
input data in MARKAL model.
According to the information on the webpage29 of the models, MARKAL was developed in a
cooperative multinational project over a period of almost two decades by the Energy
Technology Systems Analysis Programme (ETSAP) of the International Energy Agency. It is
the predecessor to system TIMES. 77 institutions in 37 countries are presented as users.
LEAP model used by Estonia is spreadsheet based energy accounting model that calculates
the GHG reduction potentials in accordance with various scenarios regarding an energy
system. LEAP model was developed at the Stockholm Environment Institute, Boston.
According to company data, at least 32 countries used LEAP to create energy and emissions
scenarios that were the basis for their Intended Nationally Determined Contributions on
Climate Change.
Although LEAP includes a built-in technology and environmental database (emission factors),
country-specific information has to be inserted separately. Because it is possible in the LEAP
model to adjust the components and variables for the energy sector, it bears an advantage
in conducting simulations across various scenarios (Hong et al., 2016).
When comparing both models (see table 2.11.) we can see that LEAP model has the simplest
framework which can be used for mitigation assessment with the minimum of non-energy
data. However, even in this case, if a mitigation assessment requires the evaluation of costs,
then data on the cost of individual options is needed. Most countries have energy balances,
but a mitigation assessment will need data well beyond these, and an analyst needs to bear
this fact in mind before attempting a detailed mitigation assessment.
The bottom-up models MARKAL (but also ETO and ENPEP) used by Latvia require
increasingly more sophisticated data sets. Since the optimization models rank options on the
basis of their costs of providing energy services, reliable estimates of costs become crucial to
the least-cost selection of technology options (Sathaye and Meyers, 2013).
Table 2.11. Characteristics of LEAP and MARKAL models
Model Characteristics LEAP MARKAL
Model Type Energy Accounting Engineering Optimization
Energy Supply
Representation
Process Analysis Process Analysis
29 http://iea-etsap.org/index.php/etsap-tools/model-generators/markal
49
Energy Demand
Representation
Exogenous Exogenous
Multi-Period No Yes
Consumer/Producer
Foresight
Not Applicable Perfect or Myopic
Solution Algorithm Accounting Linear Programming
Data Requirements Moderate Moderate
Software Requirements Spreadsheet GAMS-MINOS
Ease of Modifying source
code
Harder Moderate
Ease of Modifying data Easy Easy
Ease of including Non-
Market Factors
Not Applicable Harder
Source: Sathaye and Meyers, 2013
IPPU sector
In Latvia, the combined method of time series and impact of macroeconomic indices was
applied for projection of emissions from Industrial Processes and Product Use. Correlations
of amounts of the output of every subsection are formed in the form of “correction of
errors”, which comply with the model of error correction. The obtained timelines were
corrected in compliance with the known and forecasted technologies changes in every
subsection (according to the description in the 2nd Biennial report).
In Estonia the GHG emissions from industrial processes under categories mineral and
chemical industry are projected considering the integrated environmental permits that are
issued to the relevant industries (as required by The Industrial Emissions Act) and also the
plant operators plans on production volumes and on implementation of new technologies
(according to the description in the Biennial report).
In Lithuania, the GHG emissions projections were provided for the main emitters in this sector:
the clinker, lime, ammonia and nitric acid producing companies. The projections of CO2
emissions from clinker and lime production were based on the projections of activity data
provided by company’s authorities. It is assumed that clinker production will increase in the
period 2015–2020. From 2020 clinker production volume will remain stable. The lime
production volume will remain stable in the period 2015–2030. The projections of N2O and
CO2 were based on data provided by the main manufacturer in Lithuania. The projection of
consumption of NF3 gases was based on activity data provided by company’s authorities and
it was assumed that consumption of NF3 gases will increase until 2020, and after 2020 remain
stable until 2035 as the company’s maximum production/use capacity will remain unchanged
Emissions of the other fluorinated gases are projected to be equal to 2012 level during the
period 2015–2030. Also, projections were provided for consumption of NF3 gases.
50
Agriculture
In Latvia activity data for projections of GHG emissions from agriculture sector have been
calculated using an approach based on combined results of linear and non-linear multiple
regression analysis and corrections of results by agriculture experts within statistical forecast
confidence limits. Factors used in the regression analysis include population data, agriculture
products consumption indicators, and the share of agriculture in Gross Domestic Product
(GDP) and global trading data of agriculture products (according to the description in the 2nd
Biennial report).
In Estonia, emissions under the agricultural sector are calculated with the corresponding
methodology used in the Estonian GHG Inventory. A more detailed description can be found
in the Estonian National Inventory Report 2015. Projections of GHG emissions from
agricultural sector are based on projected animal population, milk yield, crops production,
consumption of synthetic fertilizers and the share of anaerobic digestion in manure
management. Expert estimation by the Estonian Ministry of Rural Affairs on projected
livestock numbers is used (according to the description in the 2nd Biennial report).
In Lithuania Projections of GHG emissions from agriculture sector with existing measures
(WEM) are based on forecasted livestock population, milk yield, harvested crops,
consumption of synthetic N fertilizers, consumption of limestone and data on planned
extension projects of biogas power plants. Forecast of the main data is provided by the
Ministry of Agriculture, Agricultural Information and Rural Business Centre and Institute of
Animal Science.
LULUCF sector
In Estonia projections in LULUCF are calculated using land use data from 1990–2013 and
emissions/removals reported in the National Inventory Report 2015 and CRF tables.30
Projections of CO2 are calculated as an average of:
linear forecasts over the time series of 1990– 2013,
an average of time series of 1990–2013,
an average of time series of 2000–2013,
estimation of the reference year (according to the description in the Biennial
report).
In Latvia, there is no detailed description included in the text of the report, however, using
Tier 1 method according to the IPCC 2006 is mentioned (according to the description in the
EC report).
In Lithuania NIR there is a poor description of the methodology: future emissions and
removals projections have been compiled using data from and taking into account measures
determined in the national strategies and plans (according to the description in the EC
report). However, more detailed information is provided in the chapter 4.2.5. of 2nd BR31.
30 The years here are relevant only for the projections presented in 2015. For every next projectons the latest inevntory data available are used 31 http://www.am.lt/VI/files/File/Klimato%20kaita/aTASKAITA/Final_2nd_BR_LT_v2.pdf
51
Waste sector
In Estonia projections in the subcategory, solid waste disposal on land is based on the 2006
IPCC Waste Model. Calculating the amount of municipal waste, human population projection
from Statistics Estonia and the annual real GDP growth rate from EC recommended
parameters for reporting on GHG projections in 2015 is used. The composition of municipal
solid waste is projected based on values from Mixed Municipal Solid Waste Composition
Study carried out in 2013 and the decrease percentage of biodegradable waste in the total
amount by weight of municipal waste deposited in landfills by 2020 (according to the
description in the Biennial report).
In Latvia, the calculation of the activity data and emission projections was done on the basis
of the following main assumptions and the existing policies and plans:
- Projections of the country’s population and macroeconomic factors prepared by the
Ministry of Economics;
- The requirements set in the Landfill Directive (1999/31/EC) on the volume of the
disposed of biodegradable waste are met;
- The requirements set for 2020 in the Waste Framework Directive (2008/98/EC) on
recycling of municipal waste are met (according to the description in the EC report).
In Lithuania, projections of GHG emissions from the waste sector with existing measures are
based on the National Waste Management Plan for period 2014-2020, data provided by the
Waste Department of Ministry of Environment, the Environmental Protection Agency and The
Association of the Regional Waste Management Centres. Projections in the subcategory solid
waste disposal on land is based on the 2006 IPCC Waste Model. More detailed information is
provided in the chapter 4.2.6. of 2nd BR32.
2.6.3. Table of projections Article 23 of MMR “Reporting on projections” stipulates that the Member States shall report
the information on projections of anthropogenic greenhouse gases emissions by sources and
removals by sinks referred to in Article 14 of Regulation (EU) No 525/2013 in accordance
with the tabular formats set out in Annex XII to this Regulation, using the reporting template
provided and the submission process introduced by the Commission.
All three Baltic States have filled in the projection tables, but there are slight differences that
indicate differences in the calculation methods used by the countries (in Annex 3 missing
fields are identified and colored if compared to at least one of the Baltic States).
All three Baltic States have calculated scenarios “With existing measures” and “With
additional measures”. However, none have calculated voluntary scenario “Without
measures”.
Comparison of details in sectors is listed below.
32 http://www.am.lt/VI/files/File/Klimato%20kaita/aTASKAITA/Final_2nd_BR_LT_v2.pdf
52
1. Energy sector
- Latvia and Estonia have not indicated emission projections in the section 1.A.1.b.
Petroleum refining compared to Lithuania, but it should not be assumed as missing, as
there is no such industry in Estonia or Latvia.
- Latvia has not indicated emission projections in the section 1.A.1.c. Manufacturer of
solid fuels and other energy industries compared to Lithuania.
- Latvia and Estonia have not indicated emission projections in the section 1.B. Fugitive
emissions from fuels refining compared to Lithuania.
- Latvia and Estonia have not indicated emission projections in the section 1.B.2. Oil and
natural gas and other emissions from energy production compared to Lithuania.
- Lithuania has indicated values also in sections other and other transportation compared
to Latvia and Estonia.
All mentioned differences refer to CO2, N2O, and CH4.
2. Industrial processes
- Latvia and Estonia have not indicated NF3 (kt CO2e) emission projections compared to
Lithuania, but it should not be assumed as missing as there is no such industry in Estonia
or Latvia. Latvia has not indicated CO2, N2O emission projections in the section 2.B.
Chemical industry compared to Lithuania, but Estonia – not in CO2.
- Lithuania has reported on SF6 and NF3 projections in 2.E. Electronics industry compared
to Latvia and Estonia, but it should not be assumed as missing as there is no such
industry in Estonia or Latvia.
3. Agriculture
- All three Baltic countries reported on the same type of projections in the agriculture
sector.
4. Land Use, Land-Use Change, and Forestry
- The minor sectoral difference is that Lithuania in its 2015 report has not filled-in
projection section on LULUCF. However, it was displayed separately.33
- Estonia has not reported on N2O and CH4 in 4.E. Settlements and CH4 in 4.B. Cropland
compared to Latvia.
5. Waste
- Latvia has not reported on CH4 in 5.C. Incineration and open burning of waste compared
to Lithuania and Estonia.
2.6.4. Table of parameters Article 23 of Regulation (EU) No 525/2013 “Reporting on projections” stipulates that
1.Member States shall report the information on projections of anthropogenic greenhouse
gases emissions by sources and removals by sinks referred to in Article 14 of Regulation (EU)
No 525/2013 in accordance with the tabular formats set out in Annex XII (Table 3) of the
33 The projections for LULUCF were reported by LT: http://www.am.lt/VI/files/File/Klimato%20kaita/aTASKAITA/Final_2nd_BR_LT_v2.pdf
53
Commission Implementing Regulation No 749/2014, using the reporting template provided
and the submission process introduced by the Commission.
All three Baltic States have filled-in the projection table, but there are slight differences that
indicate on the contents of the calculation methodology (in Annex 5 missing fields are
identified and colored if compared to at least one of the Baltic States).
There are some structural differences in all sectors except waste. Most of the parameters
are country specific. EU ETS carbon price is outstanding with significantly different
projections in 2035 among the three Baltic States (LV-46.54 EUR/EUA; EE- 30; LT- 6.37).
General parameters
Compared to Latvia, Estonia and Lithuania have indicated the use of fewer parameters.
Estonia has indicated (see Annex 5) that it does not use indicators EU ETS carbon price and
International (wholesale) fuel import prices for calculation of:
- 1.A.3 Transport (excl. 1.A.3.a domestic aviation);
- 1.A.4.a Commercial / institutional;
- 1.A.4.b Residential;
- 1B Fugitive emissions from fuels
- International Aviation in the EU ETS + 1.A.3.a Domestic aviation
Estonia has indicated that it does not use indicators International (wholesale) fuel import
prices: Crude Oil and Natural gas for calculation of International Aviation in the EU ETS +
1.A.3.a Domestic aviation.
Lithuania has not indicated any use and values for indicators International (wholesale) fuel
import prices:
- Electricity Coal, International (wholesale) fuel import prices:
- Crude Oil, International (wholesale) fuel import prices:
- Natural gas.
Energy parameters
- Estonia and Lithuania have not indicated the use of Gross electricity production
parameters in sectors 1.A.2 Manufacturing industries and construction, 1.A.3
Transport (excl. 1.A.3.a domestic aviation), 1.A.4.a Commercial / institutional,
1.A.4.b Residential, 1B Fugitive emissions from fuels, but Latvia has indicated.
- For indicators, Final energy consumption Estonia and Lithuania has indicated
selective use according to the energy sub-sector, but Latvia has indicated the use of
all indicators in all sub-sectors.
- Latvia has indicated the use of the Number of heating degree-days (HDD) compared
to Estonia and Lithuania.
Transport parameters
- For all three transport parameters Latvia has indicated use in all energy sub-sectors,
but Estonia and Lithuania only in 1.A.3 Transport (excl. 1.A.3.a domestic aviation).
Buildings parameters
54
- For both of building parameters (Number of households, Household size) Latvia has
indicated use all energy sub-sectors, Estonia – in 1.A.1 Energy industries, but
Lithuania – in none.
Agriculture parameters
- Use of Agriculture parameters match in Latvia and Estonia, but Lithuania has not
indicated the use of any indicator.
Waste parameters
- Use of waste parameters match to all three countries, but Estonia has indicated also
additional indicators - Biodegradable waste composted, Amount of municipal solid
waste open burned.
The main comparison tips and conclusions for methods, models, and assumptions in
Latvia, Estonia and Lithuania:
- Latvia and Estonia use sophisticated models for the energy sector, but Lithuania uses
more simplified projections and external sources.
- Lithuania has reported projections on more subcategories compared to Estonia and
Latvia except for LULUCF (regarding information in the reporting table). Possibly, it
can be related to more elastic projection methodology compared to ready-made
models.
- If purchase or replacement of the model is assumed then LEAP is assumed newer
and more elastic for selection and modeling of the measures according to the initial
assessment.
- Estonia has reported on the use of model also in the waste sector - IPCC Waste
Model 2006.
- In other sectors, projections are mainly based on the corresponding methodology
used for the GHG Inventory, external sources (sectoral ministries, policy plans, major
enterprises and others), linear and non-linear extrapolation and expert assessments.
- There is a list of indicators that one country is using, but others -not. Therefore it is
recommended to share experience for potential of using appropriate indicators for
calculations of projections
2.7. Approach for PAMs selection and evaluation Selection of PAMs can be observed from the perspective of responsibility – those that are to
be realized within the authority of MoEn directly and those to be realized by other
ministries. Methods for selection and cooperation are rather different. Description of the
responsible authorities for describing PAMs and projections were presented above and
indicates the substantial involvement of other ministries. Observation within this research
indicates that only 20% of PAMs in Latvia and Estonia refer to direct responsibility of MoEn.
Ex-ante, Ex-post and cost estimates
Therefore, evaluation of ex-ante, ex-post and cost assessments is proposed to be the crucial
factor for improving the selection process of PAMs in intersectoral policy competition.
55
Research34 on EU countries succeeding to prepare ex-ante and ex-post assessments
indicates that Estonia has the highest amount of ex-ante assessments among the Baltic
States. Ex-post assessments are very rare- prepared only by few countries in EU, but Latvia –
the lowest.
An evaluation prepared in the current research suggests that the latest reports indicate
much better situation with 41% of PAMs with ex-ante assessments in Latvia and 65% in
Estonia.
Figure 2.4. PAMs with ex-ante and ex-post assessments
Source: Magdalena Jóźwicka, Overview of reported PaMs information EU-28, 2015, EEA
Latvia is currently implementing 2009 – 2014 EEA Grants Programme “National Climate
Policy” project “Development of the national system for greenhouse gas (GHG) inventory
and reporting on policies, measures and projections”, which aims to improve national
system of policies and measures and projections. One of the main outcomes of the project is
improved quality of ex-ante and ex-post evaluation of climate change policy measures and
development of a model system for climate change mitigation policy evaluation, including
guidelines for cost assessment of different policy measures and ex-ante and ex-post policy
assessment.35
34 Magdalena Jóźwicka, Overview of reported PaMs information EU-28, 2015, EEA 35 Reporting on A National System for Policies And Measures and Projections Under Article 13(1)(A) of Regulation (EU) No 525/2013 and Article 20 Of Implementing Regulation (EU) No 749/2014, Latvia
56
Cost estimates for PAMs show quite similar situation. Research36 on a comparison of PAMs
with estimated costs in EU countries indicates that Estonia has quite a high level with 38 cost
estimates prepared.
Table 2.12. Number of PAMs with cost estimates, 2015
Source: Magdalena Jóźwicka, Overview of reported PaMs information EU-28, 2015, EEA
An evaluation prepared in the current research suggests that the latest reports indicate on
the slightly different situation with 34 cost estimates or 54% in Estonia. Latvia has indicated
14 or 23% PAMs with cost estimates (Table 2.13).
Table 2.13. Comparison of common tabular format for PAMs reporting
Only those columns of the common tabular format are listed that have differences between
countries (x-reported; blank - not reported)
Missing/reported items LV EE LT
Indicators used to monitor and evaluate progress over time (ex-post or ex-ante) x x
Reference to assessments and underpinning technical reports x x
General Comments x x
Ex-ante assessment: x x x
Ex-post assessment:
Year for which reduction applies
Average emission reduction
Explanation of the basis for the mitigation estimates x x
Factors affected by PaM
Documentation/ Source of estimation if available
Projected costs and benefits
Costs in EUR per tonne CO2eq reduced/ sequestered
Absolute costs per year in EUR x
Year(s) for which cost has been calculated x
Benefits in EUR per ton CO2eq reduced/ sequestered
Absolute benefit per year in EUR
Net costs in EUR per tonne CO2eq reduced/ sequestered x
Net Cost per year in EUR x
Realised costs and benefits
36 Magdalena Jóźwicka, Overview of reported PaMs information EU-28, 2015, EEA
57
Costs in EUR per tonne CO2eq reduced/ sequestered
Absolute costs per year in EUR x
Year(s) for which cost has been calculated x
Price reference year x
Benefits in EUR per ton CO2eq reduced/ sequestered
Absolute benefit per year in EUR
Net costs in EUR per tonne CO2eq reduced/ sequestered
Net Cost per year in EUR x
Description of cost estimates (basis for cost estimate, what type of costs are included in the estimate, methodology)
x
Documentation/ Source of cost estimation
Evaluation
Article 23 Reporting on projections states that Member States shall report the information
on projections of anthropogenic greenhouse gases emissions by sources and removals by
sinks referred to in Article 14 of Regulation (EU) No 525/2013 in accordance with the tabular
formats set out in Annex XII. Table 2 refers to Indicators to monitor and evaluate projected
progress of policies and measures. None of the Baltic States has filled it in.
Conclusions
There is potential for improving ex-ante and cost estimates for more grounded PAM
selection and evaluation process. Currently, Estonia has the widest experience and it is
recommended to share between Latvia and Estonia.
Latvia and Estonia are recommended to assess possibilities for using energy sector models
for the process of modeling alternatives and PAM selection.
58
3. Final conclusions and recommendations
Comparison of reporting led to several recommendations on the different level of detail and
topics.
Preparation of technical reviews
- Comparison of the 2nd Biennial reports and the technical review reports led to the
conclusion that recommendations for one country could to some extent be relevant also
to other countries. This means that other experts in the next technical reviews of the
Biennial reports could outline also other aspects for improvement. Therefore sharing of
experience among the Baltic States in dealing with recommendations of the technical
reviews is expected to be effective.
General comparison of the 6th National Communication and 2nd Biennial reports
- To improve a clear representation of the effects of PaMs it is recommended to display
graphs of total emissions for all three scenarios (WEM, WAM) in one picture
representing historical data together with projections similar to the report of Lithuania.
The effect for WEM and WAM should be represented in tabular format as in the case of
Estonia or precentral decrease (or physical units as in the biennial report) of emissions
as in Latvia or both. These are the contents of the report section “Assessment of the
aggregate effect of policies and measures”. For a better representation, it is
recommended to supplement the comparison mentioned above with the split of
emissions by sectors and by gases for each of scenarios – WEM, WAM. That could be
done in tabular format as in the Latvia report. Despite possible duplication with the
sectoral chapters, this information should provide a comprehensive overview of effects
of all PaMs scenarios.
- The recommendation is to explore a comparison on lists of PaMs for the Baltic States
and other countries and to organize a separate discussion among the representatives of
all three Baltic States on improving the way of structuring and defining PaMs.
- Another recommendation is to improve structuring by clear defining and presenting of
direct and indirect PaMs and applying different approaches for assessing the effect of
them as well as clearly structuring descriptions for PaMs and groups of PaMs.
- Description of effects of PAMs is clearly divided in Estonia 2nd Biennial report; outline of
assumptions on dynamics of projection parameters is detailed in Lithuania 2nd Biennial
report. That could be used as good practice if appropriate.
- Estonia has developed a way to include changes over time in the definition of PaMs
adding “additional” to the name of PAM. This approach could be used by other countries
in defining changes of existing PAMs over time.
- As observed from reporting to EC there is a list of PAM indicators that one country is
using, but others -not. Therefore, it is recommended to share experience for the
potential of using more appropriate indicators for calculations of projections.
Institutional development
- Latvia is recommended to check if the creation of Permanent GHG Inventory preparation
working groups as in Lithuania could help to homogenize the NIR preparation process
among different contractors.
59
- Table “Institutions responsible for activity data and calculating emissions” in the Latvia
NIR is proposed to be helpful for the clear understanding of responsibilities, activity data
gathering, and calculations. For improvement of cooperation, other countries are
suggested to use the same format.
GHG Inventory data
- Countries are using different aggregation levels when reporting their emission
uncertainties. Uncertainties can be also reduced by moving to more detailed sectoral
breakdown, using high uncertainty emission factors only in categories where this
applies.
- Countries have to evaluate if country specific emission factors are necessary for the key
emission categories. Countries have to conduct a sensitivity analysis to identify the most
important mechanisms and identify new insights on parameterisation and/or updated
emission factors.
Methods for projections
- There is a list of parameters that one country is using, but others -not. Therefore, it is
recommended to share experience for the potential of using appropriate indicators for
calculations of projections.
- There are preferences for the perception of the text and transparency if the main
methods and assumptions are united in logical text within the description of projections
based on clear WEM and WAM contents and scenarios (additionally to separate
methodological description).
Approach for PAMs selection and evaluation
- There is potential for improving ex-ante and cost estimates for more grounded PAM
selection process. Currently, Estonia has the widest experience and it is recommended
to share among Latvia and Lithuania Latvia and Estonia are recommended to assess
possibilities for using energy sector models for modeling in the process of PAM
selection.
In general, it can be concluded that there is a vast list of conceptual, technical and
representative aspects where one of the Baltic States has better experience to share and
there is a list of common problems that can be solved in cooperation. Regular and structured
cooperation among the Baltic States is recommended for reporting management
representatives and sectoral experts.
There is potential for improving ex-ante and cost estimates for more grounded PAM
selection process. Currently, Estonia has the widest experience and it is recommended to
share between Latvia and Lithuania.
60
References BLUJDEA, V. N., VIÑAS, R. A., FEDERICI, S. & GRASSI, G. 2015. The EU greenhouse gas inventory
for the LULUCF sector: I. Overview and comparative analysis of methods used by EU member states. Carbon Management, 6, 247-259.
EC 2013. Regulation (EU) No 525/2013 of the European parliament and of the Council on mechanisms for monitoring and reporting greenhouse gas emissions and for reporting other information at national and Union level relevant to climate change and repealing Decision No 280/2004/EC.
HONG, S., CHUNG, Y., KIM, J. & CHUN, D. 2016. Analysis on the level of contribution to the national greenhouse gas reduction target in Korean transportation sector using LEAP model. Renewable and Sustainable Energy Reviews, 60, 549-559.
KONSTANTINAVICIUTE, I. & BOBINAITE, V. 2015. Comparative analysis of carbon dioxide emission factors for energy industries in European Union countries. Renewable and Sustainable Energy Reviews, 51, 603-612.
LESIV, M., BUN, A. & JONAS, M. 2014. Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15. Climatic change, 124, 505-518.
MARLAND, G. 2008. Uncertainties in accounting for CO2 from fossil fuels. Journal of Industrial Ecology, 12, 136.
MILNE, A. E., GLENDINING, M. J., BELLAMY, P., MISSELBROOK, T., GILHESPY, S., CASADO, M. R., HULIN, A., VAN OIJEN, M. & WHITMORE, A. P. 2014. Analysis of uncertainties in the estimates of nitrous oxide and methane emissions in the UK's greenhouse gas inventory for agriculture. Atmospheric Environment, 82, 94-105.
NOWAK, J., NEUMAN, J., BAHREINI, R., MIDDLEBROOK, A., HOLLOWAY, J., MCKEEN, S., PARRISH, D., RYERSON, T. & TRAINER, M. 2012. Ammonia sources in the California South Coast Air Basin and their impact on ammonium nitrate formation. Geophysical Research Letters, 39.
OMETTO, J. P., BUN, R., JONAS, M., NAHORSKI, Z. & GUSTI, M. I. 2014. Uncertainties in greenhouse gases inventories–expanding our perspective. Springer.
PULLES, T. 2017. Did the UNFCCC review process improve the national GHG inventory submissions? Carbon Management, 1-13.
SATHAYE, J. A. & MEYERS, S. 2013. Greenhouse gas mitigation assessment: a guidebook, Springer Science & Business Media.
ZHANG, S., WORRELL, E. & CRIJNS-GRAUS, W. 2015. Synergy of air pollutants and greenhouse gas emissions of Chinese industries: A critical assessment of energy models. Energy, 93, Part 2, 2436-2450.
61
ANNEX 1. Emission factors GREENHOUSE GAS SOURCE AND SINK CO2
CATEGORIES Emission factor
LV LT EE
1. Energy CS,D,NO,OTH,PS CS,D,PS CS,D,PS
A. Fuel combustion CS,D,OTH,PS CS,D,PS CS,D,PS
1. Energy industries CS,D CS,D,PS CS,D,PS
2. Manufacturing industries and construction CS,D,PS CS CS,D,PS
3. Transport CS,D,OTH CS,D CS,D
4. Other sectors CS,D CS CS,D
5. Other D CS CS
B. Fugitive emissions from fuels CS,NO CS,D D
1. Solid fuels NA NA NA
2. Oil and natural gas CS,NO CS,D D
C. CO2 transport and storage NO NA NA
2. Industrial processes D,NO,OTH,PS CR,CS,D,PS D,PS
A. Mineral industry D,OTH,PS CS,D,PS D,PS
B. Chemical industry NO CS NA
C. Metal industry D,NO,PS D NA
D. Non-energy products from fuels and solvent use D,PS CR,D D
E. Electronic industry
F. Product uses as ODS substitutes
G. Other product manufacture and use NA NA NA
H. Other NO D NA
3. Agriculture D D
A. Enteric fermentation
B. Manure management
C. Rice cultivation
D. Agricultural soils(3)
E. Prescribed burning of savannas
F. Field burning of agricultural residues
G. Liming D D D
H. Urea application D D NA
I. Other carbon-containing fertilizers NA NA NA
J. Other NA NA
4. Land use, land-use change and forestry CS,D,NA CS,D CS,D,OTH
A. Forest land CS,D,NA CS,D D,OTH
B. Cropland CS,NA CS,D D
C. Grassland CS,D,NA CS,D D,OTH
D. Wetlands CS,D,NA D CS,D
E. Settlements CS,NA CS,D OTH
F. Other land NA CS,D OTH
G. Harvested wood products CS,NA D CS,D
H. Other NA NA NA
5. Waste D,NA D D
A. Solid waste disposal NA NA NA
B. Biological treatment of solid waste
C. Incineration and open burning of waste D,NA D D
D. Waste water treatment and discharge
E. Other NA NA
6. Other (as specified in summary 1.A) NA NA NA
62
GREENHOUSE GAS SOURCE AND SINK CH4
CATEGORIES Emission factor
LV LT EE
1. Energy CR,CS,D,NO,OTH CR,CS,D CS,D
A. Fuel combustion CR,CS,D,OTH CR,CS,D CS,D
1. Energy industries D CS,D CS,D
2. Manufacturing industries and construction D CS,D D
3. Transport CR,D,OTH CR,D CS,D
4. Other sectors CS,D CS,D CS,D
5. Other D D D
B. Fugitive emissions from fuels CS,NO CS,D D
1. Solid fuels NA NA NA
2. Oil and natural gas CS,NO CS,D D
C. CO2 transport and storage
2. Industrial processes CR,NO NA NA
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry CR,NO NA NA
D. Non-energy products from fuels and solvent use NA NA NA
E. Electronic industry
F. Product uses as ODS substitutes
G. Other product manufacture and use NA NA NA
H. Other NO NA NA
3. Agriculture CS,D,OTH CS,D,NO,OTH CS,D,OTH
A. Enteric fermentation CS,D,OTH CS,D,OTH CS,D,OTH
B. Manure management CS,D CS,D CS,D
C. Rice cultivation NA NA NA
D. Agricultural soils(3)
E. Prescribed burning of savannas NA NO NA
F. Field burning of agricultural residues NA NA NA
G. Liming
H. Urea application
I. Other carbon-containing fertilizers
J. Other NA NA NA
4. Land use, land-use change and forestry D,NA CS,D CS,D
A. Forest land D,NA D NA
B. Cropland NA CS,D NA
C. Grassland NA CS,D D
D. Wetlands NA NA CS
E. Settlements NA NA
F. Other land NA NA
G. Harvested wood products
H. Other NA NA NA
5. Waste CS,D,NA D D
A. Solid waste disposal CS,D D D
B. Biological treatment of solid waste D,NA D D
C. Incineration and open burning of waste NA D D
D. Waste water treatment and discharge CS,NA D D
E. Other NA NA
6. Other (as specified in summary 1.A) NA NA NA
63
GREENHOUSE GAS SOURCE AND SINK N2O
CATEGORIES Emission factor
LV LT EE
1. Energy CR,D,NO,OTH CR,CS,D CS,D
A. Fuel combustion CR,D,OTH CR,CS,D CS,D
1. Energy industries D CS,D CS,D
2. Manufacturing industries and construction D CS,D D
3. Transport CR,D,OTH CR,D CS,D
4. Other sectors D CS,D CS,D
5. Other D D D
B. Fugitive emissions from fuels NO D NA
1. Solid fuels NA NA NA
2. Oil and natural gas NO D NA
C. CO2 transport and storage
2. Industrial processes D,NO D,OTH,PS CS
A. Mineral industry
B. Chemical industry NO PS NA
C. Metal industry NO NA
D. Non-energy products from fuels and solvent use NA NA NA
E. Electronic industry
F. Product uses as ODS substitutes
G. Other product manufacture and use D,NO D,OTH CS
H. Other NO NA NA
3. Agriculture D D,NO CS,D
A. Enteric fermentation
B. Manure management D D CS,D
C. Rice cultivation
D. Agricultural soils(3) D D D
E. Prescribed burning of savannas NA NO NA
F. Field burning of agricultural residues NA NA NA
G. Liming
H. Urea application
I. Other carbon-containing fertilizers
J. Other NA NA NA
4. Land use, land-use change and forestry D,NA CS,D CS,D
A. Forest land D,NA D NA
B. Cropland D,NA CS,D D
C. Grassland NA CS,D D
D. Wetlands NA D CS
E. Settlements D D NA
F. Other land D NA
G. Harvested wood products
H. Other NA NA NA
5. Waste D,NA D D
A. Solid waste disposal
B. Biological treatment of solid waste D,NA D D
C. Incineration and open burning of waste D,NA D D
D. Waste water treatment and discharge D,NA D D
E. Other NA NA
6. Other (as specified in summary 1.A) NA NA NA
64
GREENHOUSE GAS SOURCE AND SINK HFCs
CATEGORIES Emission factor
LV LT EE
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes CS,D,NO,OTH CS,D,PS CS
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA
D. Non-energy products from fuels and solvent use
E. Electronic industry NA NA NA
F. Product uses as ODS substitutes CS,D,NO,OTH CS,D,PS CS
G. Other product manufacture and use NA NA NA
H. Other NA NA NA
GREENHOUSE GAS SOURCE AND SINK PFCs
CATEGORIES Emission factor
LV LT EE
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO NA NA
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA NA
D. Non-energy products from fuels and solvent use
E. Electronic industry NA NA NA
F. Product uses as ODS substitutes NO NA NA
G. Other product manufacture and use NA NA NA
H. Other NA NA NA
65
GREENHOUSE GAS SOURCE AND SINK SF6
CATEGORIES Emission factor
LV LT EE
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes D,NO CS,PS CS
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA NA
D. Non-energy products from fuels and solvent use
E. Electronic industry NA PS NA
F. Product uses as ODS substitutes NO NA NA
G. Other product manufacture and use D CS CS
H. Other NA NA NA
GREENHOUSE GAS SOURCE AND SINK Unspecified mix of
HFCs and PFCs NF3
CATEGORIES Emission factor Emission factor
LV LT EE LV LT EE
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO NA NA NO PS NA
A. Mineral industry
B. Chemical industry NO NA NA NO NA NA
C. Metal industry NO NA NO NA
D. Non-energy products from fuels and solvent use
E. Electronic industry NA NA NA NA PS NA
F. Product uses as ODS substitutes NO NA NA NO NA NA
G. Other product manufacture and use NA NA NA NA NA NA
H. Other NA NA NA NA NA NA
66
ANNEX 2. NIR methods
GREENHOUSE GAS SOURCE AND SINK Latvia 2016
Estonia 2017
Lithuania 2016
CATEGORIES CO2
1. Energy NO,T1,T2,T3 T1,T2,T3 T1,T2,T3
A. Fuel combustion T1,T2,T3 T1,T2,T3 T1,T2,T3
1. Energy industries T1,T2 T1,T2,T3 T1,T2,T3
2. Manufacturing industries and
construction T1,T2,T3 T1,T2,T3 T2
3. Transport T1,T2 T1,T2 T1,T2
4. Other sectors T1,T2 T1,T2 T2
5. Other T1 T2 T2
B. Fugitive emissions from fuels NO,T2 T1 T1,T2
1. Solid fuels NA NA NA
2. Oil and natural gas NO,T2 T1 T1,T2
C. CO2 transport and storage NO NA NA
2. Industrial processes CS,D,NO,T1,T2,T3 D,T1,T2,T3 CR,CS,T1,T2,T3
A. Mineral industry T1,T2,T3 T1,T2,T3 CS,T1,T2
B. Chemical industry NO NA T3
C. Metal industry NO,T2 NA T2
D. Non-energy products from fuels and solvent
use CS,D,T1,T2 D,T1,T2 CR,T1,T3
E. Electronic industry
F. Product uses as ODS substitutes
G. Other product manufacture and use NA NA NA
H. Other NO NA T1
3. Agriculture T1 D,T1 T1
A. Enteric fermentation
B. Manure management
C. Rice cultivation
D. Agricultural soils(3)
E. Prescribed burning of savannas
F. Field burning of agricultural residues
G. Liming T1 D,T1 T1
H. Urea application T1 NA T1
I. Other carbon-containing fertilizers NA NA NA
J. Other NA NA NA
4. Land use, land-use change and forestry T1,T2 IE,T1,T2,T3 T1,T2
A. Forest land T1,T2 IE,T1,T2,T3 T1,T2
B. Cropland T1,T2 T1,T2 T1,T2
C. Grassland T1,T2 T1,T2,T3 T1,T2
D. Wetlands T1,T2 T2 T1
E. Settlements T2 T2 T1,T2
F. Other land NA T2 T1,T2
67
G. Harvested wood products T2 T2,T3 T1
H. Other NA NA NA
5. Waste D T1,T2 T1
A. Solid waste disposal NA NA NA
B. Biological treatment of solid waste
C. Incineration and open burning of waste D T1,T2 T1
D. Waste water treatment and discharge
E. Other NA NA
6. Other (as specified in summary 1.A) NA NA NA
CH4
1. Energy NO,T1,T2 T1,T2,T3 T1,T2,T3
A. Fuel combustion T1,T2 T1,T2,T3 T1,T2,T3
1. Energy industries T1 T1,T2 T1,T2
2. Manufacturing industries and
construction T1 T1 T1,T2
3. Transport T1,T2 T1,T2,T3 T1,T2,T3
4. Other sectors T1,T2 T1,T2 T1,T2
5. Other T1 T1 T1
B. Fugitive emissions from fuels NO,T2 T1 T1,T2
1. Solid fuels NA NA NA
2. Oil and natural gas NO,T2 T1 T1,T2
C. CO2 transport and storage
2. Industrial processes NO,T1 NA NA
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO,T1 NA NA
D. Non-energy products from fuels and solvent
use NA NA NA
E. Electronic industry
F. Product uses as ODS substitutes
G. Other product manufacture and use NA NA NA
H. Other NO NA NA
3. Agriculture T1,T2 D,T1,T2 NO,T1,T2
A. Enteric fermentation T1,T2 D,T1,T2 T1,T2
B. Manure management T1,T2 D,T1,T2 T1,T2
C. Rice cultivation NA NA NA
D. Agricultural soils(3)
E. Prescribed burning of savannas NA NA NO
F. Field burning of agricultural residues NA NA NA
G. Liming
H. Urea application
I. Other carbon-containing fertilizers
J. Other NA NA NA
4. Land use, land-use change and forestry D,T1,T2 T2 T1,T2
A. Forest land T1,T2 T2 T1,T2
68
B. Cropland T1 NA T1,T2
C. Grassland D,T1 T2 T1,T2
D. Wetlands T1 T2 NA
E. Settlements NA NA NA
F. Other land NA NA NA
G. Harvested wood products
H. Other NA NA NA
5. Waste D,T2 T1,T2 T1,T2
A. Solid waste disposal T2 T2 T2
B. Biological treatment of solid waste D T1 T1
C. Incineration and open burning of waste NA T1 T1
D. Waste water treatment and discharge D T1 T1
E. Other NA NA
6. Other (as specified in summary 1.A) NA NA NA
N2O
1. Energy NO,T1,T2 T1,T2,T3 T1,T2,T3
A. Fuel combustion T1,T2 T1,T2,T3 T1,T2,T3
1. Energy industries T1 T1,T2 T1,T2
2. Manufacturing industries and
construction T1 T1 T1,T2
3. Transport T1,T2 T1,T2,T3 T1,T2,T3
4. Other sectors T1 T1,T2 T1,T2
5. Other T1 T1 T1
B. Fugitive emissions from fuels NO NA T1
1. Solid fuels NA NA NA
2. Oil and natural gas NO NA T1
C. CO2 transport and storage
2. Industrial processes CS,NO T2 D,T1,T3
A. Mineral industry
B. Chemical industry NO NA T3
C. Metal industry NO NA
D. Non-energy products from fuels and solvent
use NA NA NA
E. Electronic industry
F. Product uses as ODS substitutes
G. Other product manufacture and use CS,NO T2 D,T1
H. Other NO NA NA
3. Agriculture T1,T2 CS,D,T1,T2 NO,T1,T2
A. Enteric fermentation
B. Manure management T1,T2 T1,T2 T1,T2
C. Rice cultivation
D. Agricultural soils(3) T1 CS,D,T1,T2 T1
E. Prescribed burning of savannas NA NA NO
F. Field burning of agricultural residues NA NA NA
G. Liming
69
H. Urea application
I. Other carbon-containing fertilizers
J. Other NA NA NA
4. Land use, land-use change and forestry D,T1,T2 T1,T2 T1,T2
A. Forest land T1,T2 T2 T1,T2
B. Cropland T1 T1 T1,T2
C. Grassland D T2 T1,T2
D. Wetlands T1 T2 T1
E. Settlements T1 NA T1,T2
F. Other land NA NA T1,T2
G. Harvested wood products
H. Other NA NA NA
5. Waste D T1 T1
A. Solid waste disposal
B. Biological treatment of solid waste D T1 T1
C. Incineration and open burning of waste D T1 T1
D. Waste water treatment and discharge D T1 T1
E. Other NA NA
6. Other (as specified in summary 1.A) NA NA NA
HFCs
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and
construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO,T1a,T2 T2 T1a,T1b,T2
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA
D. Non-energy products from fuels and solvent
use
E. Electronic industry NA NA NA
F. Product uses as ODS substitutes NO,T1a,T2 T2 T1a,T1b,T2
G. Other product manufacture and use NA NA NA
H. Other NA NA NA
PFCs
1. Energy
70
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and
construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO NA NA
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA NA
D. Non-energy products from fuels and solvent
use
E. Electronic industry NA NA NA
F. Product uses as ODS substitutes NO NA NA
G. Other product manufacture and use NA NA NA
H. Other NA NA NA
SF6
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and
construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO,T1 T3 T3
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA NA
D. Non-energy products from fuels and solvent
use
E. Electronic industry NA NA T3
F. Product uses as ODS substitutes NO NA NA
G. Other product manufacture and use T1 T3 T3
H. Other NA NA NA
Unspecified mix of HFCs and PFCs
71
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and
construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO NA NA
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA
D. Non-energy products from fuels and solvent
use
E. Electronic industry NA NA NA
F. Product uses as ODS substitutes NO NA NA
G. Other product manufacture and use NA NA NA
H. Other NA NA NA
NF3
1. Energy
A. Fuel combustion
1. Energy industries
2. Manufacturing industries and
construction
3. Transport
4. Other sectors
5. Other
B. Fugitive emissions from fuels
1. Solid fuels
2. Oil and natural gas
C. CO2 transport and storage
2. Industrial processes NO NA T2
A. Mineral industry
B. Chemical industry NO NA NA
C. Metal industry NO NA
D. Non-energy products from fuels and solvent
use
E. Electronic industry NA NA T2
F. Product uses as ODS substitutes NO NA NA
G. Other product manufacture and use NA NA NA
H. Other NA NA NA
72
ANNEX 3. Comparison of Projections items Comparison of reporting on projections (Regulation (EU) No 525/2013 in accordance with the tabular formats set out in Annex XII)
Colored items indicate on projection that is not evaluated in the observed country but is evaluated in at least one of the other Baltic States
Submission Year 2015
MS Latvia
Category (1,3)
Scenario
(WEM,
WAM,
WOM)
CO2 (kt) N2O
(kt) CH4 (kt)
HFC (kt
CO2e)
PFC (kt
CO2e)
SF6 (kt
CO2e)
NF3 (kt
CO2e)
Total
GHGs (kt
CO2e)
Total
ETS
GHGs
(kt
CO2e)
Total
ESD
GHGs (kt
CO2e)
2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00
Total excluding LULUCF WEM 9871.24 6.70 77.78 277.58 NA,NO 17.71 NA,NO 14593.77 4413.51 10180.26
Total including LULUCF WEM 17067.05 8.82 92.04 277.58 NA,NO 17.71 NA,NO 22778.84 4413.51 10180.26
1. Energy WEM 8918.52 0.45 6.82 NA NA NA NA 9222.66 3589.86 5632.80
1.A. Fuel combustion WEM 8918.52 0.45 4.93 NA NA NA NA 9175.56 3589.86 5585.70
1.A.1. Energy industries WEM 2504.51 0.15 1.05 NA NA NA NA 2575.36 2096.02 479.33
1.A.1.a. Public electricity
and heat production WEM 2504.51 0.15 1.05 NA NA NA NA 2575.36 2096.02 479.33
1.A.1.b. Petroleum refining WEM NO NO NO NA NA NA NA NO NO NO
1.A.1.c. Manufacture of
solid fuels and other energy
industries
WEM IE IE IE NA NA NA NA IE 0.00 IE
1.A.2. Manufacturing
industries and construction WEM 2681.77 0.07 0.51 NA NA NA NA 2714.36 1454.32 1260.03
1.A.3. Transport WEM 2987.65 0.17 0.21 NA NA NA NA 3044.83 0.00 3044.83
1.A.3.a. Domestic aviation WEM 4.58 0.00 0.00 NA NA NA NA 4.64 0.00 4.64
1.A.3.b. Road transportation WEM 2746.19 0.08 0.19 NA NA NA NA 2774.68 0.00 2774.68
1.A.3.c. Railways WEM 219.79 0.09 0.01 NA NA NA NA 246.33 0.00 246.33
1.A.3.d. Domestic navigation WEM 17.09 0.01 0.00 NA NA NA NA 19.17 0.00 19.17
1.A.3.e. Other
transportation WEM IE IE IE NA NA NA NA IE 0.00 IE
1.A.4. Other sectors WEM 744.59 0.06 3.17 NA NA NA NA 841.03 39.51 801.51
1.A.4.a.
Commercial/Institutional WEM 136.83 0.01 0.65 NA NA NA NA 156.12 16.28 139.84
1.A.4.b. Residential WEM 132.69 0.03 2.27 NA NA NA NA 198.27 0.00 198.27
1.A.4.c.
Agriculture/Forestry/Fishing WEM 475.07 0.02 0.25 NA NA NA NA 486.64 23.23 463.41
73
1.A.5. Other WEM IE IE IE NA NA NA NA 0.00 0.00 0.00
1.B. Fugitive emissions from
fuels WEM 0.00 NO,NA 1.88 NA NA NA NA 47.10 0.00 47.10
1.B.1. Solid fuels WEM NO NO,NA NO NA NA NA NA NO,NA NO,NA NO,NA
1.B.2. Oil and natural gas
and other emissions from
energy production
WEM 0.00 NO 1.88 NA NA NA NA 47.10 0.00 47.10
1.C. CO2 transport and
storage WEM NO NO NO NA NA NA NA NO NO NO
2. Industrial processes WEM 926.87 4.21 277.58 17.71 1327.47 823.65 503.82
2.A. Mineral Industry WEM 822.15 NA NA NA NA NA NA 822.15 822.15 0.00
2.A. of which cement
production WEM 800.78 NA NA NA NA NA NA 800.78 800.78 0.00
2.A. of which other non
cement production WEM 21.37 NA NA NA NA NA NA 21.37 21.37 0.00
2.B. Chemical industry WEM NO NO NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO
2.C. Metal industry WEM 1.50 NO 4.21 NO NO NO NO 106.81 1.50 105.32
2.C. of which Iron and steel
production WEM 1.50 NO 0.00 NO NO NO NO 1.59 1.50 0.09
2.C. of which other non Iron
and steel production WEM NO NO 4.21 NO NO NO NO 105.23 0.00 105.23
2.D. Non-energy products
from fuels and solvent use WEM 103.21 NO,NA NO,NA NA NA NA NA 103.21 NA 103.21
2.E. Electronics industry WEM NO NO NO NO NO NO NO NO NO NO
2.F. Product uses as
substitutes for ODS(2) WEM NO NO NO 277.58 NO NO NO 277.58 NA 277.58
2.G. Other product
manufacture and use WEM 0.00 NO NO NO NO 17.71 NO 17.71 NA 17.71
2.H. Other (please specify) WEM NO NO NO NA NA NA NA NO,NA NA NA
3. Agriculture WEM 25.53 6.23 66.75 3551.87 NA 3551.87
3.A. Enteric fermentation WEM NA NA 57.31 NA NA NA NA 1432.70 NA 1432.70
3.B. Manure management WEM NA 0.55 9.44 NA NA NA NA 399.94 NA 399.94
3.C. Rice cultivation WEM NO NO NO NO NO NO NO NO NA NO
3.D. Agricultural soils WEM NA 5.68 NA NA NA NA NA 1693.69 NA 1693.69
3.E. Prescribed burning of
savannahs WEM NO NO NO NO NO NO NO NO NA NO
3.F. Field burning of
agricultural residues WEM NO NO NO NO NO NO NO NO NA NO
3.G. Liming WEM 19.66 NA NA NA NA NA NA 19.66 NA 19.66
3.H. Urea application WEM 5.87 NA NA NA NA NA NA 5.87 NA 5.87
3.I. Other carbon-containing
fertilizers WEM NO NO NO NO NO NO NO NO NA NO
74
3.J. Other (please specify) WEM NO NO NO NO NO NO NO NO NA NO
4. Land Use, Land-Use
Change and Forestry WEM 7195.82 2.12 14.26 8185.07 NA
4.A. Forest land WEM 991.65 1.93 2.81 1637.61 NA
4.B. Cropland WEM 2902.82 0.11 5.09 3063.64 NA
4.C. Grassland WEM 722.69 0.00 2.65 788.99 NA
4.D. Wetlands WEM 1779.30 0.01 3.28 1865.12 NA
4.E. Settlements WEM 1982.12 0.07 0.42 2012.48 NA
4.F. Other Land WEM NA
4.G. Harvested wood
products WEM -1182.76 -1182.76 NA
4.H. Other WEM NA
5. Waste WEM 0.32 0.02 491.77 0.00 491.77
5.A. Solid Waste Disposal WEM NA NA 13.30 332.55 0.00 332.55
5.B. Biological treatment of
solid waste WEM NA 0.01 0.16 7.64 0.00 7.64
5.C. Incineration and open
burning of waste WEM 0.32 0.00 NA 0.33 0.00 0.33
5.D. Wastewater treatment
and discharge WEM NA 0.01 5.98 151.25 0.00 151.25
5.E. Other (please specify) WEM NA NA NA NA
Memo items WEM NA
M.International bunkers WEM 1350.10 0.15 0.06 NA NA NA NA 1395.23 442.55 NA
M.IB.Aviation WEM 442.55 0.01 0.00 NA NA NA NA 447.06 442.55 4.51
M.IB.Navigation WEM 907.55 0.13 0.06 NA NA NA NA 948.17 NA NA
M.CO2 emissions from
biomass WEM 5283.39 NA NA NA NA NA NA 5283.39 NA NA
M.CO2 captured WEM NO NO NO NA NA NA NA NA NA NA
M.Long-term storage of C in
waste disposal sites WEM NA
M.Indirect N2O WEM NA
M.International aviation in
the EU ETS WEM 442.55 NA NA NA NA NA NA NA NA NA
Total excluding LULUCF WAM 8205.53 6.20 81.32 277.58 NA,NO 17.71 NA,NO 12380.68 3402.09 8978.92
Total including LULUCF WAM 15401.34 8.32 95.58 277.58 NA,NO 17.71 NA,NO 20565.75 3402.09 8978.92
1. Energy WAM 7252.81 0.43 7.02 NA NA NA NA 7555.27 2578.45 4976.82
1.A. Fuel combustion WAM 7252.81 0.43 5.20 NA NA NA NA 7509.74 2578.45 4931.30
1.A.1. Energy industries WAM 1815.15 0.16 1.17 NA NA NA NA 1891.79 1519.10 372.69
75
1.A.1.a. Public electricity
and heat production WAM 1815.15 0.16 1.17 NA NA NA NA 1891.79 1519.10 372.69
1.A.1.b. Petroleum refining WAM NO NO NO NA NA NA NA NO NO NO
1.A.1.c. Manufacture of
solid fuels and other energy
industries
WAM IE IE IE NA NA NA NA IE 0.00 IE
1.A.2. Manufacturing
industries and construction WAM 1878.97 0.09 0.67 NA NA NA NA 1922.03 1018.97 903.06
1.A.3. Transport WAM 2798.39 0.12 0.20 NA NA NA NA 2839.32 0.00 2839.32
1.A.3.a. Domestic aviation WAM 4.57 0.00 0.00 NA NA NA NA 4.63 0.00 4.63
1.A.3.b. Road transportation WAM 2698.69 0.08 0.19 NA NA NA NA 2726.94 0.00 2726.94
1.A.3.c. Railways WAM 78.06 0.03 0.01 NA NA NA NA 88.60 0.00 88.60
1.A.3.d. Domestic navigation WAM 17.07 0.01 0.00 NA NA NA NA 19.15 0.00 19.15
1.A.3.e. Other
transportation WAM IE IE IE NA NA NA NA IE 0.00 IE
1.A.4. Other sectors WAM 760.30 0.06 3.16 NA NA NA NA 856.60 40.38 816.22
1.A.4.a.
Commercial/Institutional WAM 138.23 0.01 0.64 NA NA NA NA 157.34 16.45 140.89
1.A.4.b. Residential WAM 132.67 0.03 2.26 NA NA NA NA 198.12 0.00 198.12
1.A.4.c.
Agriculture/Forestry/Fishing WAM 489.40 0.02 0.25 NA NA NA NA 501.14 23.93 477.21
1.A.5. Other WAM IE IE IE NA NA NA NA 0.00 0.00 0.00
1.B. Fugitive emissions from
fuels WAM 0.00 NO,NA 1.82 NA NA NA NA 45.53 0.00 45.53
1.B.1. Solid fuels WAM NO NO,NA NO NA NA NA NA NO,NA NO,NA NO,NA
1.B.2. Oil and natural gas
and other emissions from
energy production
WAM 0.00 NO 1.82 NA NA NA NA 45.53 0.00 45.53
1.C. CO2 transport and
storage WAM NO NO NO NA NA NA NA NO NO NO
2. Industrial processes WAM 926.87 NA 4.21 277.58 17.71 1327.47 823.65 503.82
2.A. Mineral Industry WAM 822.15 NA 822.15 822.15 0.00
2.A. of which cement
production WAM 800.78 NA 800.78 800.78 0.00
2.A. of which other non
cement production WAM 21.37 NA 21.37 21.37 0.00
2.B. Chemical industry WAM NA NA 0.00 0.00 0.00
2.C. Metal industry WAM 1.50 NA 4.21 106.81 1.50 105.32
2.C. of which Iron and steel
production WAM 1.50 NA 0.00 1.59 1.50 0.09
2.C. of which other non Iron
and steel production WAM NO NO 4.21 NO NO NO NO 105.23 0.00 105.23
76
2.D. Non-energy products
from fuels and solvent use WAM 103.21 NO NO NA NA NA NA 103.21 0.00 103.21
2.E. Electronics industry WAM NO NO NO NO NO NO NO 0.00
2.F. Product uses as
substitutes for ODS(2) WAM NO NO NO 277.58 NO NO NO 277.58 0.00 277.58
2.G. Other product
manufacture and use WAM 0.00 NO NO NO NO 17.71 NO 17.71 0.00 17.71
2.H. Other (please specify) WAM NA
3. Agriculture WAM 25.53 5.74 54.36 3096.42 NA 3096.42
3.A. Enteric fermentation WAM NA NA 47.74 NA NA NA NA 1193.40 NA 1193.40
3.B. Manure management WAM NA 0.44 6.62 NA NA NA NA 296.21 NA 296.21
3.C. Rice cultivation WAM NO NO NO NO NO NO NO NO NA NO
3.D. Agricultural soils WAM NA 5.31 NA NA NA NA NA 1581.27 NA 1581.27
3.E. Prescribed burning of
savannahs WAM NO NO NO NO NO NO NO NO NA NO
3.F. Field burning of
agricultural residues WAM NO NO NO NO NO NO NO NO NA NO
3.G. Liming WAM 19.66 NA NA NA NA NA NA 19.66 NA 19.66
3.H. Urea application WAM 5.87 NA NA NA NA NA NA 5.87 NA 5.87
3.I. Other carbon-containing
fertilizers WAM NO NO NO NO NO NO NO NO NA NO
3.J. Other (please specify) WAM NO NO NO NO NO NO NO NO NA NO
4. Land Use, Land-Use
Change and Forestry WAM 7195.82 2.12 14.26 8185.07 NA
4.A. Forest land WAM 991.65 1.93 2.81 1637.61 NA
4.B. Cropland WAM 2902.82 0.11 5.09 3063.64 NA
4.C. Grassland WAM 722.69 0.00 2.65 788.99 NA
4.D. Wetlands WAM 1779.30 0.01 3.28 1865.12 NA
4.E. Settlements WAM 1982.12 0.07 0.42 2012.48 NA
4.F. Other Land WAM NA
4.G. Harvested wood
products WAM -1182.76 -1182.76 NA
4.H. Other WAM NA
5. Waste WAM 0.32 0.03 15.73 401.53 NA 401.87
5.A. Solid Waste Disposal WAM NA NA 9.45 236.37 NA 236.37
5.B. Biological treatment of
solid waste WAM NA 0.02 0.29 13.91 NA 13.91
5.C. Incineration and open
burning of waste WAM 0.32 0.00 NA 0.33 NA 0.33
5.D. Wastewater treatment
and discharge WAM NA 0.01 5.98 151.25 NA 151.25
77
5.E. Other (please specify) WAM NA NA NA NA 0.00
Memo items WAM NA
M.International bunkers WAM 1349.00 0.15 0.06 NA NA NA NA 1394.10 441.45 NA
M.IB.Aviation WAM 441.45 0.01 0.00 NA NA NA NA 445.93 441.45 4.48
M.IB.Navigation WAM 907.55 0.13 0.06 NA NA NA NA 948.17 NA NA
M.CO2 emissions from
biomass WAM 6826.03 NA NA NA NA NA NA 6826.03 NA NA
M.CO2 captured WAM NO NO NO NA NA NA NA NA NA NA
M.Long-term storage of C in
waste disposal sites WAM NA NA
M.Indirect N2O WAM NA NA
M.International aviation in
the EU ETS WAM 441.45 NA NA NA NA NA NA NA NA NA
Comparison of reporting on projections (Regulation (EU) No 525/2013 in accordance with the tabular formats set out in Annex XII)
Colored items indicate on projection that is not evaluated in the observed country but is evaluated in at least one of the other Baltic States
Submission Year 2015
MS Estonia
Category (1,3) Scenario (WEM,
WAM, WOM) CO2 (kt)
N2O
(kt) CH4 (kt)
HFC (kt
CO2e)
PFC (kt
CO2e)
SF6 (kt
CO2e)
NF3 (kt
CO2e)
Total
GHGs (kt
CO2e)
Total ETS
GHGs (kt
CO2e)
Total
ESD
GHGs
(kt
CO2e)
2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00
Total excluding LULUCF WEM 15080.12 2.94 43.37 107.04 NO 4.23 NO 17150.28 11836.68 5311.49
Total including LULUCF WEM 13737.09 2.96 43.37 107.04 NO 4.23 NO 15814.43 11836.68 5311.49
1. Energy WEM 13977.76 0.48 11.33 NO NO NO NO 14405.35 10765.65 3637.36
1.A. Fuel combustion WEM 13977.76 0.48 7.88 NO NO NO NO 14319.21 10765.65 3551.22
1.A.1. Energy industries WEM 10351.04 0.29 2.03 NO NO NO NO 10487.23 10138.89 348.35
1.A.1.a. Public electricity
and heat production WEM 6194.80 0.27 1.84 NO NO NO NO 6320.87 5982.65 338.22
1.A.1.b. Petroleum refining WEM NO NO NO NO NO NO NO NO NO NO
1.A.1.c. Manufacture of
solid fuels and other energy
industries WEM 4156.24 0.02 0.18 NO NO NO NO 4166.36 4156.24 10.12
1.A.2. Manufacturing
industries and construction WEM 837.97 0.02 0.11 NO NO NO NO 845.59 603.83 241.76
1.A.3. Transport WEM 2229.66 0.11 0.42 NO NO NO NO 2271.64 NO 2269.30
78
1.A.3.a. Domestic aviation WEM 2.31 0.00 0.00 NO NO NO NO 2.34 NO NO
1.A.3.b. Road
transportation WEM 2072.23 0.06 0.36 NO NO NO NO 2100.10 NO 2100.10
1.A.3.c. Railways WEM 134.55 0.04 0.06 NO NO NO NO 148.54 NO 148.54
1.A.3.d. Domestic
navigation WEM 20.57 0.00 0.00 NO NO NO NO 20.66 NO 20.66
1.A.3.e. Other
transportation WEM NO NO NO NO NO NO NO NO NO NO
1.A.4. Other sectors WEM 545.28 0.07 5.33 NO NO NO NO 700.68 22.93 677.75
1.A.4.a.
Commercial/Institutional WEM 57.92 0.00 0.04 NO NO NO NO 58.99 22.93 36.05
1.A.4.b. Residential WEM 198.66 0.07 5.23 NO NO NO NO 350.68 NO 350.68
1.A.4.c.
Agriculture/Forestry/Fishing WEM 288.70 0.00 0.06 NO NO NO NO 291.02 NO 291.02
1.A.5. Other WEM 13.82 0.00 0.00 NO NO NO NO 14.07 NO 14.07
1.B. Fugitive emissions from
fuels WEM NO NO 3.45 NO NO NO NO 86.13 NO 86.13
1.B.1. Solid fuels WEM NO NO NO NO NO NO NO NO NO NO
1.B.2. Oil and natural gas
and other emissions from
energy production WEM NO NO 3.45 NO NO NO NO 86.13 NO 86.13
1.C. CO2 transport and
storage WEM NO NO NO NO NO NO NO NO NO NO
2. Industrial processes WEM 1092.14 0.01 NO 107.04 NO 4.23 NO 1207.34 1071.03 136.54
2.A. Mineral Industry WEM 811.91 NO NO NO NO NO NO 811.91 811.68 0.23
2.A. of which cement
production WEM 633.04 NO NO NO NO NO NO 633.04 633.04 NO
2.A. of which other non
cement production WEM 178.87 NO NO NO NO NO NO 178.87 178.64 0.23
2.B. Chemical industry WEM 259.35 NO NO NO NO NO NO 259.35 259.35 NO
2.C. Metal industry WEM NO NO NO NO NO NO NO NO NO NO
2.C. of which Iron and steel
production WEM NO NO NO NO NO NO NO NO NO NO
2.C. of which other non Iron
and steel production WEM NO NO NO NO NO NO NO NO NO NO
2.D. Non-energy products
from fuels and solvent use WEM 20.88 NO NO NO NO NO NO 20.88 NO 20.88
2.E. Electronics industry WEM NO NO NO NO NO NO NO NO NO NO
2.F. Product uses as
substitutes for ODS(2) WEM NO NO NO NO NO NO NO 107.04 NO 107.04
2.G. Other product
manufacture and use WEM NO 0.01 NO 107.04 NO 4.23 NO 8.16 NO 8.16
2.H. Other (please specify) WEM NO NO NO NO NO NO NO NO NO NO
79
3. Agriculture WEM 10.18 2.26 27.86 NO NO NO NO 1379.01 NO 1379.01
3.A. Enteric fermentation WEM NO NO 25.18 NO NO NO NO 629.48 NO 629.48
3.B. Manure management WEM NO 0.22 2.68 NO NO NO NO 133.07 NO 133.07
3.C. Rice cultivation WEM NO NO NO NO NO NO NO NO NO NO
3.D. Agricultural soils WEM NO 2.03 NO NO NO NO NO 606.28 NO 606.28
3.E. Prescribed burning of
savannahs WEM NO NO NO NO NO NO NO NO NO NO
3.F. Field burning of
agricultural residues WEM NO NO NO NO NO NO NO NO NO NO
3.G. Liming WEM 9.02 NO NO NO NO NO NO 9.02 NO 9.02
3.H. Urea application WEM 1.16 NO NO NO NO NO NO 1.16 NO 1.16
3.I. Other carbon-
containing fertilizers WEM NO NO NO NO NO NO NO NO NO NO
3.J. Other (please specify) WEM NO NO NO NO NO NO NO NO NO NO
4. Land Use, Land-Use
Change and Forestry WEM -1343.03 0.02 0.01 NO NO NO NO -1335.85 NO NO
4.A. Forest land WEM -1454.17 0.00 0.00 NO NO NO NO -1454.04 NO NO
4.B. Cropland WEM 169.75 0.02 NO NO NO NO NO 175.11 NO NO
4.C. Grassland WEM 218.77 0.00 0.00 NO NO NO NO 218.77 NO NO
4.D. Wetlands WEM 177.77 0.01 0.00 NO NO NO NO 179.46 NO NO
4.E. Settlements WEM 379.42 NO NO NO NO NO NO 379.42 NO NO
4.F. Other Land WEM 47.74 NO NO NO NO NO NO 47.74 NO NO
4.G. Harvested wood
products WEM -882.30 NO IE NO NO NO NO -882.30 NO NO
4.H. Other WEM NO NO NO NO NO NO NO NO NO NO
5. Waste WEM 0.03 0.18 4.18 NO NO NO NO 158.58 NO 158.58
5.A. Solid Waste Disposal WEM NO NO 1.56 NO NO NO NO 39.04 NO 39.04
5.B. Biological treatment of
solid waste WEM NO 0.09 1.17 NO NO NO NO 55.26 NO 55.26
5.C. Incineration and open
burning of waste WEM 0.03 0.00 0.00 NO NO NO NO 0.04 NO 0.04
5.D. Wastewater treatment
and discharge WEM NO 0.09 1.45 NO NO NO NO 64.24 NO 64.24
5.E. Other (please specify) WEM NO NO NO NO NO NO NO NO NO NO
Memo items WEM 13019.67 0.53 0.08 NO NO NO NO 13179.10 NO NO
M.International bunkers WEM 1340.83 0.01 0.08 NO NO NO NO 1345.76 NO NO
M.IB.Aviation WEM 104.92 0.00 0.00 NO NO NO NO 104.92 NO NO
M.IB.Navigation WEM 1235.91 0.01 0.08 NO NO NO NO 1240.84 NO NO
M.CO2 emissions from
biomass WEM 8079.96 NO NO NO NO NO NO 8079.96 NO NO
80
M.CO2 captured WEM NO NO NO NO NO NO NO NO NO NO
M.Long-term storage of C in
waste disposal sites WEM 3598.88 NO NO NO NO NO NO 3598.88 NO NO
M.Indirect N2O WEM NO 0.52 NO NO NO NO NO 154.51 NO NO
M.International aviation in
the EU ETS WEM NO NO NO NO NO NO NO NO NO NO
Total excluding LULUCF WAM 13183.72 2.84 40.09 107.04 NO 4.23 NO 15144.59 11067.62 4074.62
Total including LULUCF WAM 11840.68 2.87 40.10 107.04 NO 4.23 NO 13808.74 11067.62 4074.62
1. Energy WAM 12081.36 0.39 8.05 NO NO NO NO 12399.65 9996.59 2400.72
1.A. Fuel combustion WAM 12081.36 0.39 5.91 NO NO NO NO 12346.21 9996.59 2347.28
1.A.1. Energy industries WAM 9557.37 0.26 1.88 NO NO NO NO 9683.37 9372.40 310.97
1.A.1.a. Public electricity
and heat production WAM 5401.13 0.25 1.70 NO NO NO NO 5517.01 5216.16 300.85
1.A.1.b. Petroleum refining WAM NO NO NO NO NO NO NO NO NO NO
1.A.1.c. Manufacture of
solid fuels and other energy
industries WAM 4156.24 0.02 0.18 NO NO NO NO 4166.36 4156.24 10.12
1.A.2. Manufacturing
industries and construction WAM 837.97 0.02 0.11 NO NO NO NO 845.59 603.83 241.76
1.A.3. Transport WAM 1193.70 0.06 0.31 NO NO NO NO 1219.07 NO 1216.73
1.A.3.a. Domestic aviation WAM 2.31 0.00 0.00 NO NO NO NO 2.34 NO NO
1.A.3.b. Road
transportation WAM 1094.25 0.04 0.25 NO NO NO NO 1110.97 NO 1110.97
1.A.3.c. Railways WAM 88.72 0.02 0.06 NO NO NO NO 97.31 NO 97.31
1.A.3.d. Domestic
navigation WAM 8.42 0.00 0.00 NO NO NO NO 8.45 NO 8.45
1.A.3.e. Other
transportation WAM NO NO NO NO NO NO NO NO NO NO
1.A.4. Other sectors WAM 478.50 0.05 3.61 NO NO NO NO 584.11 20.36 563.75
1.A.4.a.
Commercial/Institutional WAM 51.43 0.00 0.03 NO NO NO NO 52.38 20.36 32.02
1.A.4.b. Residential WAM 138.37 0.05 3.51 NO NO NO NO 240.72 NO 240.72
1.A.4.c.
Agriculture/Forestry/Fishing WAM 288.70 0.00 0.06 NO NO NO NO 291.02 NO 291.02
1.A.5. Other WAM 13.82 0.00 0.00 NO NO NO NO 14.07 NO 14.07
1.B. Fugitive emissions from
fuels WAM NO NO 2.14 NO NO NO NO 53.44 NO 53.44
1.B.1. Solid fuels WAM NO NO NO NO NO NO NO NO NO NO
81
1.B.2. Oil and natural gas
and other emissions from
energy production WAM NO NO 2.14 NO NO NO NO 53.44 NO 53.44
1.C. CO2 transport and
storage WAM NO NO NO NO NO NO NO NO NO NO
2. Industrial processes WAM 1092.14 0.01 NO 107.04 NO 4.23 NO 1207.34 1071.03 136.31
2.A. Mineral Industry WAM 811.91 NO NO NO NO NO NO 811.91 811.68 0.23
2.A. of which cement
production WAM 633.04 NO NO NO NO NO NO 633.04 633.04 NO
2.A. of which other non
cement production WAM 178.87 NO NO NO NO NO NO 178.87 178.64 0.23
2.B. Chemical industry WAM 259.35 NO NO NO NO NO NO 259.35 259.35 NO
2.C. Metal industry WAM NO NO NO NO NO NO NO NO NO NO
2.C. of which Iron and steel
production WAM NO NO NO NO NO NO NO NO NO NO
2.C. of which other non Iron
and steel production WAM NO NO NO NO NO NO NO NO NO NO
2.D. Non-energy products
from fuels and solvent use WAM 20.88 NO NO NO NO NO NO 20.88 NO 20.88
2.E. Electronics industry WAM NO NO NO NO NO NO NO NO NO NO
2.F. Product uses as
substitutes for ODS(2) WAM NO NO NO NO NO NO NO 107.04 NO 107.04
2.G. Other product
manufacture and use WAM NO 0.01 NO 107.04 NO 4.23 NO 8.16 NO 8.16
2.H. Other (please specify) WAM NO NO NO NO NO NO NO NO NO NO
3. Agriculture WAM 10.18 2.26 27.86 NO NO NO NO 1379.01 NO 1379.01
3.A. Enteric fermentation WAM NO NO 25.18 NO NO NO NO 629.48 NO 629.48
3.B. Manure management WAM NO 0.22 2.68 NO NO NO NO 133.07 NO 133.07
3.C. Rice cultivation WAM NO NO NO NO NO NO NO NO NO NO
3.D. Agricultural soils WAM NO 2.03 NO NO NO NO NO 606.28 NO 606.28
3.E. Prescribed burning of
savannahs WAM NO NO NO NO NO NO NO NO NO NO
3.F. Field burning of
agricultural residues WAM NO NO NO NO NO NO NO NO NO NO
3.G. Liming WAM 9.02 NO NO NO NO NO NO 9.02 NO 9.02
3.H. Urea application WAM 1.16 NO NO NO NO NO NO 1.16 NO 1.16
3.I. Other carbon-
containing fertilizers WAM NO NO NO NO NO NO NO NO NO NO
3.J. Other (please specify) WAM NO NO NO NO NO NO NO NO NO NO
4. Land Use, Land-Use
Change and Forestry WAM -1343.03 0.02 0.01 NO NO NO NO -1335.85 NO NO
4.A. Forest land WAM -1454.17 0.00 0.00 NO NO NO NO -1454.04 NO NO
82
4.B. Cropland WAM 169.75 0.02 NO NO NO NO NO 175.11 NO NO
4.C. Grassland WAM 218.77 0.00 0.00 NO NO NO NO 218.77 NO NO
4.D. Wetlands WAM 177.77 0.01 0.00 NO NO NO NO 179.46 NO NO
4.E. Settlements WAM 379.42 NO NO NO NO NO NO 379.42 NO NO
4.F. Other Land WAM 47.74 NO NO NO NO NO NO 47.74 NO NO
4.G. Harvested wood
products WAM -882.30 NO IE NO NO NO NO -882.30 NO NO
4.H. Other WAM NO NO NO NO NO NO NO NO NO NO
5. Waste WAM 0.03 0.18 4.18 NO NO NO NO 158.58 NO 158.58
5.A. Solid Waste Disposal WAM NO NO 1.56 NO NO NO NO 39.04 NO 39.04
5.B. Biological treatment of
solid waste WAM NO 0.09 1.17 NO NO NO NO 55.26 NO 55.26
5.C. Incineration and open
burning of waste WAM 0.03 0.00 0.00 NO NO NO NO 0.04 NO 0.04
5.D. Wastewater treatment
and discharge WAM NO 0.09 1.45 NO NO NO NO 64.24 NO 64.24
5.E. Other (please specify) WAM NO NO NO NO NO NO NO NO NO NO
Memo items WAM 13255.10 0.53 0.08 NO NO NO NO 5099.15 NO NO
M.International bunkers WAM 1340.83 0.01 0.08 NO NO NO NO 1345.76 NO NO
M.IB.Aviation WAM 104.92 0.00 0.00 NO NO NO NO 104.92 NO NO
M.IB.Navigation WAM 1235.91 0.01 0.08 NO NO NO NO 1240.84 NO NO
M.CO2 emissions from
biomass WAM 7079.48 NO NO NO NO NO NO 7079.48 NO NO
M.CO2 captured WAM NO NO NO NO NO NO NO NO NO NO
M.Long-term storage of C in
waste disposal sites WAM 3598.88 NO NO NO NO NO NO 3598.88 NO NO
M.Indirect N2O WAM NO 0.52 NO NO NO NO NO 154.51 NO NO
M.International aviation in
the EU ETS WAM NO NO NO NO NO NO NO NO NO NO
Comparison of reporting on projections (Regulation (EU) No 525/2013 in accordance with the tabular formats set out in Annex XII)
Coloured items indicate on projection that is not evaluated in the observed country but is evaluated in at least one of the other Baltic States
Submission Year 2015
MS Lithuania
Category (1,3)
Scenario (WEM, WAM, WOM)
CO2 (kt) N2O (kt)
CH4 (kt) HFC (kt CO2e)
PFC (kt CO2e)
SF6 (kt CO2e)
NF3 (kt CO2e)
Total GHGs (kt CO2e)
Total ETS GHGs (kt CO2e)
Total ESD GHGs (kt CO2e)
2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00 2035.00
Total excluding LULUCF WEM 18463.40 11.97 114.39 284.11 0.00 3.99 2.68 25181.88 11236.87 14024.86
Total including LULUCF WEM 18463.40 11.97 114.39 284.11 0.00 3.99 2.68 15270.00 11236.87 14024.86
83
1. Energy WEM 15819.89 0.47 20.76 NO NO NO NO 16477.58 7994.63 8482.96
1.A. Fuel combustion WEM 15814.89 0.46 8.61 NO NO NO NO 16168.73 7994.63 8174.10
1.A.1. Energy industries WEM 6836.92 0.10 0.77 NO NO NO NO 6887.30 6851.37 35.93
1.A.1.a. Public electricity and heat production WEM 4591.50 0.09 0.71 NO NO NO NO 4637.56 4637.56
1.A.1.b. Petroleum refining WEM 2215.93 0.01 0.06 NO NO NO NO 2220.15 2213.81 6.34
1.A.1.c. Manufacture of solid fuels and other energy industries WEM 29.49 0.00 0.00 NO NO NO NO 29.59 NO 29.59
1.A.2. Manufacturing industries and construction WEM 1554.35 0.03 0.22 NO NO NO NO 1568.78 1139.19 429.59
1.A.3. Transport WEM 6237.21 0.23 0.66 NO NO NO NO 6321.37 3.91 6317.47
1.A.3.a. Domestic aviation WEM 3.88 0.00 0.00 NO NO NO NO 3.91 3.91
1.A.3.b. Road transportation WEM 5663.19 0.10 0.63 NO NO NO NO 5708.73 5708.73
1.A.3.c. Railways WEM 193.81 0.08 0.01 NO NO NO NO 216.75 216.75
1.A.3.d. Domestic navigation WEM 11.99 0.00 0.00 NO NO NO NO 12.06 12.06
1.A.3.e. Other transportation WEM 364.34 0.05 0.02 NO NO NO NO 379.93 379.93
1.A.4. Other sectors WEM 1177.46 0.10 6.96 NO NO NO NO 1382.24 0.16 1382.09
1.A.4.a. Commercial/Institutional WEM 399.45 0.01 0.47 NO NO NO NO 414.34 414.34
1.A.4.b. Residential WEM 678.48 0.09 6.35 NO NO NO NO 864.06 864.06
1.A.4.c. Agriculture/Forestry/Fishing WEM 99.52 0.00 0.14 NO NO NO NO 103.85 0.16 103.70
1.A.5. Other WEM 8.96 0.00 0.00 NO NO NO NO 9.03 9.03
1.B. Fugitive emissions from fuels WEM 5.00 0.00 12.15 NO NO NO NO 308.85 308.85
1.B.1. Solid fuels WEM NO NO NO NO NO NO NO NO NO
1.B.2. Oil and natural gas and other emissions from energy production WEM 5.00 0.00 12.15 NO NO NO NO 308.85 308.85
1.C. CO2 transport and storage WEM NO NO NO NO NO NO NO NO NO NO
2. Industrial processes WEM 2607.55 2.17 0.00 284.11 NO 3.99 2.68 3544.99 3162.39 382.60
2.A. Mineral Industry WEM 893.02 0.00 0.00 0.00 NO 0.00 0.00 893.02 893.02
2.A. of which cement production WEM 806.31 NO NO NO NO NO NO 806.31 806.31
2.A. of which other non cement production WEM 86.71 NO NO NO NO NO NO 86.71 86.71
2.B. Chemical industry WEM 1625.22 2.16 NO NO NO NO NO 2269.37 2269.37
2.C. Metal industry WEM 3.27 0.00 0.00 0.00 NO 0.00 0.00 3.27 3.27
2.C. of which Iron and steel production WEM 3.27 NO NO NO NO NO NO 3.27 3.27
2.C. of which other non Iron and steel production WEM NO NO NO NO NO NO NO NO NO
2.D. Non-energy products from fuels and solvent use WEM 72.87 NO NO NO NO NO NO 72.87 72.87
2.E. Electronics industry WEM NO NO NO NO NO 3.56 2.68 6.24 6.24
2.F. Product uses as substitutes for ODS(2) WEM NO NO NO 284.11 NO NO NO 284.11 284.11
2.G. Other product manufacture and use WEM NO 0.01 NO NO NO 0.44 NO 2.94 2.94
2.H. Other (please specify) WEM 13.16 NO NO NO NO NO NO 13.16 13.16
3. Agriculture WEM 24.59 9.13 77.66 NO NO NO NO 4687.33 4687.33
3.A. Enteric fermentation WEM NO NO 70.41 NO NO NO NO 1760.34 1760.34
84
3.B. Manure management WEM NO 0.77 7.25 NO NO NO NO 411.06 411.06
3.C. Rice cultivation WEM NO NO NO NO NO NO NO NO NO
3.D. Agricultural soils WEM NO 8.36 NO NO NO NO NO 2491.34 2491.34
3.E. Prescribed burning of savannahs WEM NO NO NO NO NO NO NO NO NO
3.F. Field burning of agricultural residues WEM NO NO NO NO NO NO NO NO NO
3.G. Liming WEM 8.08 NO NO NO NO NO NO 8.08 8.08
3.H. Urea application WEM 16.51 NO NO NO NO NO NO 16.51 16.51
3.I. Other carbon-containing fertilizers WEM NO NO NO NO NO NO NO NO NO
3.J. Other (please specify) WEM NO NO NO NO NO NO NO NO NO
4. Land Use, Land-Use Change and Forestry WEM NO NO NO NO -9911.88
4.A. Forest land WEM NO NO NO NO
4.B. Cropland WEM NO NO NO NO
4.C. Grassland WEM NO NO NO NO
4.D. Wetlands WEM NO NO NO NO
4.E. Settlements WEM NO NO NO NO
4.F. Other Land WEM NO NO NO NO
4.G. Harvested wood products WEM NO NO NO NO
4.H. Other WEM NO NO NO NO
5. Waste WEM 11.37 0.21 15.96 0.00 NO NO NO 471.97 471.97
5.A. Solid Waste Disposal WEM NO NO 15.25 NO NO NO NO 381.34 381.34
5.B. Biological treatment of solid waste WEM NO 0.05 0.63 NO NO NO NO 29.65 29.65
5.C. Incineration and open burning of waste WEM 11.37 0.00 0.00 NO NO NO NO 11.73 11.73
5.D. Wastewater treatment and discharge WEM NO 0.16 0.08 NO NO NO NO 49.26 49.26
5.E. Other (please specify) WEM NO NO NO NO NO NO NO NO NO
Memo items WEM
M.International bunkers WEM 737.47 0.01 0.02 NO NO NO NO 741.68
M.IB.Aviation WEM 428.88 0.01 0.00 NO NO NO NO 431.55
M.IB.Navigation WEM 308.58 0.00 0.01 NO NO NO NO 310.13
M.CO2 emissions from biomass WEM 5791.83
M.CO2 captured WEM NO NO NO NO NO NO NO NO
M.Long-term storage of C in waste disposal sites WEM NO NO NO NO NO NO NO NO
M.Indirect N2O WEM
M.International aviation in the EU ETS WEM 79.85 NO NO NO NO NO NO 79.85 79.85
Total excluding LULUCF WAM 15328.00 11.92 112.99 284.11 NO 3.99 2.68 21995.23 9320.90 12754.06
Total including LULUCF WAM 15328.00 11.92 112.99 284.11 NO 3.99 2.68 7543.60 9320.90 12754.06
1. Energy WAM 12684.49 0.41 19.37 NO NO NO NO 13290.94 6078.66 7212.16
1.A. Fuel combustion WAM 12679.49 0.41 7.22 NO NO NO NO 12982.08 6078.66 6903.31
1.A.1. Energy industries WAM 4905.36 0.07 0.53 NO NO NO NO 4939.88 4910.88 29.00
1.A.1.a. Public electricity and heat production WAM 3093.07 0.06 0.48 NO NO NO NO 3124.09 3124.09
1.A.1.b. Petroleum refining WAM 1788.50 0.01 0.05 NO NO NO NO 1791.90 1786.79 5.11
1.A.1.c. Manufacture of solid fuels and other energy industries WAM 23.80 0.00 0.00 NO NO NO NO 23.89 23.89
85
1.A.2. Manufacturing industries and construction WAM 1250.23 0.02 0.17 NO NO NO NO 1261.72 1163.71 98.00
1.A.3. Transport WAM 5523.06 0.23 0.66 0.00 0.00 0.00 0.00 5607.22 3.91 5603.31
1.A.3.a. Domestic aviation WAM 3.88 0.00 0.00 NO NO NO NO 3.91 3.91
1.A.3.b. Road transportation WAM 4949.03 0.10 0.63 NO NO NO NO 4994.58 4994.58
1.A.3.c. Railways WAM 193.81 0.08 0.01 NO NO NO NO 216.75 216.75
1.A.3.d. Domestic navigation WEM 11.99 0.00 0.00 NO NO NO NO 12.06 NA 12.06
1.A.3.e. Other transportation WAM 364.34 0.05 0.02 NO NO NO NO 379.93 379.93
1.A.4. Other sectors WAM 991.89 0.09 5.86 NO NO NO NO 1164.12 0.16 1163.96
1.A.4.a. Commercial/Institutional WAM 322.40 0.01 0.38 NO NO NO NO 334.41 334.41
1.A.4.b. Residential WAM 569.96 0.08 5.33 NO NO NO NO 725.85 725.85
1.A.4.c. Agriculture/Forestry/Fishing WAM 99.52 0.00 0.14 NO NO NO NO 103.85 0.16 103.70
1.A.5. Other WAM 8.96 0.00 0.00 NO NO NO NO 9.03 9.03
1.B. Fugitive emissions from fuels WAM 5.00 0.00 12.15 NO NO NO NO 308.85 308.85
1.B.1. Solid fuels WAM NO NO NO NO NO NO NO NO NO
1.B.2. Oil and natural gas and other emissions from energy production WAM 5.00 0.00 12.15 NO NO NO NO 308.85 308.85
1.C. CO2 transport and storage WAM NO NO NO NO NO NO NO NO NO NO
2. Industrial processes WAM 2607.55 2.17 0.00 284.11 NO 3.99 2.68 3544.99 3162.39 382.60
2.A. Mineral Industry WAM 893.02 0.00 0.00 0.00 NO 0.00 0.00 893.02 893.02
2.A. of which cement production WAM 806.31 NO NO NO NO NO NO 806.31 806.31
2.A. of which other non cement production WAM 86.71 NO NO NO NO NO NO 86.71 86.71
2.B. Chemical industry WAM 1625.22 2.16 NO NO NO NO NO 2269.37 2269.37
2.C. Metal industry WAM 3.27 0.00 0.00 0.00 NO 0.00 0.00 3.27 3.27
2.C. of which Iron and steel production WAM 3.27 NO NO NO NO NO NO 3.27 3.27
2.C. of which other non Iron and steel production WAM NO NO NO NO NO NO NO NO NO
2.D. Non-energy products from fuels and solvent use WAM 72.87 NO NO NO NO NO NO 72.87 72.87
2.E. Electronics industry WAM NO NO NO NO NO 3.56 2.68 6.24 6.24
2.F. Product uses as substitutes for ODS(2) WAM NO NO NO 284.11 NO NO NO 284.11 284.11
2.G. Other product manufacture and use WAM NO 0.01 NO NO NO 0.44 NO 2.94 2.94
2.H. Other (please specify) WAM 13.16 NO NO NO NO NO NO 13.16 13.16
3. Agriculture WAM 24.59 9.13 77.66 NO NO NO NO 4687.33 4687.33
3.A. Enteric fermentation WAM NO NO 70.41 NO NO NO NO 1760.34 1760.34
3.B. Manure management WAM NO 0.77 7.25 NO NO NO NO 411.06 411.06
3.C. Rice cultivation WAM NO NO NO NO NO NO NO NO NO
3.D. Agricultural soils WAM NO 8.36 NO NO NO NO NO 2491.34 2491.34
3.E. Prescribed burning of savannahs WAM NO NO NO NO NO NO NO NO NO
3.F. Field burning of agricultural residues WAM NO NO NO NO NO NO NO NO NO
3.G. Liming WAM 8.08 NO NO NO NO NO NO 8.08 8.08
3.H. Urea application WAM 16.51 NO NO NO NO NO NO 16.51 16.51
86
3.I. Other carbon-containing fertilizers WAM NO NO NO NO NO NO NO NO NO
3.J. Other (please specify) WAM NO NO NO NO NO NO NO NO NO
4. Land Use, Land-Use Change and Forestry WAM NO NO NO NO
-14451.63
4.A. Forest land WAM NO NO NO NO
4.B. Cropland WAM NO NO NO NO
4.C. Grassland WAM NO NO NO NO
4.D. Wetlands WAM NO NO NO NO
4.E. Settlements WAM NO NO NO NO
4.F. Other Land WAM NO NO NO NO
4.G. Harvested wood products WAM NO NO NO NO
4.H. Other WAM NO NO NO NO
5. Waste WAM 11.37 0.21 15.96 NO NO NO NO 471.97 471.97
5.A. Solid Waste Disposal WAM NO NO 15.25 NO NO NO NO 381.34 381.34
5.B. Biological treatment of solid waste WAM NO 0.05 0.63 NO NO NO NO 29.65 29.65
5.C. Incineration and open burning of waste WAM 11.37 0.00 0.00 NO NO NO NO 11.73 11.73
5.D. Wastewater treatment and discharge WAM NO 0.16 0.08 NO NO NO NO 49.26 49.26
5.E. Other (please specify) WAM NO NO NO NO NO NO NO NO NO
Memo items WAM
M.International bunkers WAM 737.47 0.01 0.02 NO NO NO NO 741.68
M.IB.Aviation WAM 428.88 0.01 0.00 NO NO NO NO 431.55
M.IB.Navigation WAM 308.58 0.00 0.01 NO NO NO NO 310.13
M.CO2 emissions from biomass WAM 7806.38
M.CO2 captured WAM NO NO NO NO NO NO NO NO
M.Long-term storage of C in waste disposal sites WAM NO NO NO NO NO NO NO NO
M.Indirect N2O WAM
M.International aviation in the EU ETS WAM 79.85 NO NO NO NO NO NO 79.85 79.85
87
ANNEX 4. Comparison of projection models reported to EC Comparison of model descriptions (Regulation (EU) No 525/2013)
Table 1: Model Factsheet37 Country Latvia Estonia
Model name MARKAL LEAP
Full model name MARKAL-Latvia
Long-range Energy Alternatives Planning system
Model version and status Model generators code version - 5.9g. Latvia data base version - 10.1.
Version 2014.0.1.20
Latest date of revision Latvia data base updated in May 2015
2/28/2015
URL to model description
http://www.iea-etsap.org/web/Documentation.asp
http://energycommunity.org/default.asp?action=47
Model type
A bottom-up optimization technology model of the energy & environment system
Accounting type and optimization type
Model description
The basic components in a MARKAL model are specific types of energy or emission control technology. Each is represented quantitatively by a set of performance and cost characteristics. A menu of both existing and future technologies is input to the model. Both the supply and demand sides are integrated, so that one side responds automatically to changes in the other. The model selects that combination of technologies that minimizes total energy system cost
See "URL to model description"
Summary
MARKAL is a demand driven model, integrating the supply and end-use sectors of economy, and lay emphasis on the description of energy related sub-sectors and on the minimization of the long term discounted cost of all the modelled energy-environmental system.
See "URL to model description"
Intended field of application
Energy system evolution Tool for energy policy analysis and climate change mitigation assessment
Description of main input data categories and data sources
Energy balance; techno economic parameters for technologies and energy carriers; useful energy demand projections which are linked with macroeconomics forecast; emission factors; fuel
Fuel consumption in different subsectors of the energy sector
37 Lithuania has indicated not using specific models.
88
prices projection; energy taxes and subsidies
Validation and evaluation
MARKAL-Latvia is continuously developed since 1995. Years 2000, 2005 and 2010 are calibrated according to the published energy balance
-
Output quantities
Optimal technology and fuel mix; energy consumption and production; emission levels; technologies costs, capacity levels
User defined
GHG covered CO2, N2O, CH4 All GHGs
Sectoral coverage 1. Energy Energy Sector
Geographical coverage Latvia User defined
Temporal coverage,(e.g. time steps, time span)
Modelled horizon covers 1998 to 2052 divided in 11 periods of 5 years each centered in 2000, 2005, 2010 ... etc.
User defined
Interface with other models
Soft link with COPERT -
Input from other models
Average consumptions and emission factors for road transport technologies
-
Model structure(if diagram please add to the template)
The structural boundaries of the RES (Reference Energy System) consist of the energy services and the energy sources, both of which are specified not as fixed assumptions, but as supply curves (for energy sources) and demand curves (for energy services). Timewise, the boundaries are the initial period (when the initially existing system is described), and the end of the horizon (when the remaining capacities are valued).
-
Model name IPCC Waste Model 2006
Full model name -
Model version and status -
Latest date of revision -
URL to model description
www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/5_Volume5/IPCC_Waste_Model.xls
Model type First order decay method
89
Model description
See "URL to model description"
Summary
http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/5_Volume5/V5_3_Ch3_SWDS.pdf
Intended field of application
To estimate emissions of methane from SWDS and stored carbon in the SWDS
Description of main input data categories and data sources
Amount of waste generated and deposited in SWDS
Validation and evaluation IPCC
Output quantities Gigagrams
GHG covered CH4
Sectoral coverage Waste sector
Geographical coverage User defined
Temporal coverage,(e.g. time steps, time span)
User defined
Interface with other models
-
Input from other models -
Model structure(if diagram please add to the template)
spreadsheet model
Member States may reproduce this table to allow them to report details of individual sub-models which have been used to create GHG projections
90
ANNEX 5. Comparison of projection parameters reported to
EC
Comparison of parameters for projections (Regulation (EU) No 525/2013 in accordance with the tabular formats set out in Annex XII, Regulation (EU) No 749/2014) Table 3: Reporting on parameters for projections used
Coloured items indicate on projection that is not evaluated in the observed country but is evaluated in at least one of the other Baltic States Section "Parameter used(4) ('without measures' scenario)" was not filled by any of the Baltic states. Therefore not included in the table below. For comparison of the parameters calculated only column for 2035 projections is used
Description of columns:
1.A.1 Energy industries
1.A.2 Manufacturing industries and construction
1.A.3 Transport (excl 1.A.3.a domestic aviation)
1.A.4.a Commercial / institutional
1.A.4.b Residential
1B Fugitive emissions from fuels
2 Industrial Processes and product use
3 Agriculture
4 LULUCF
5 Waste
IA- International Aviation in the EU ETS + 1.A.3.a Domestic aviation
Submission Year 2015
MS Latvia
Sectoral projections for which the parameter is used
Parameter used(4) ('with existing measures' scenario)
2035 Data source
Year of publication of data source
1.A.1
1.A.2
1.A.3
1.A.4.a
1.A.4.b
1B 2 3 4 5 IA
Population 1924.48 Yes Yes Yes Yes Yes
Gross domestic product (GDP):-Real growth rate
2.46263 Ministry of Economics
2015
Gross domestic product (GDP):-Constant prices
44385.6 Ministry of Economics
2015 Yes Yes Yes Yes
Gross value added (GVA) total industry
7127.73 Ministry of Economics
2015 Yes Yes
Exchange rates EURO (for non-EURO countries), if applicable
Exchange rates US DOLLAR, if applicable
EU ETS carbon price 46.5434 Primes 2013
2013 Yes Yes Yes Yes Yes Yes No No No No Yes
International (wholesale) fuel import prices:-Electricity Coal
4.56 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
International (wholesale) fuel import prices:-Crude Oil
16.2914 IEA 2014 Yes Yes Yes Yes Yes Yes No No No No Yes
International (wholesale) fuel
8.92 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
91
import prices:-Natural gas
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
National retail fuel prices (with taxes included):-Coal, households
National retail fuel prices (with taxes included):-Heating oil, industry
National retail fuel prices (with taxes included):-Heating oil, households
National retail fuel prices (with taxes included):-Transport, gasoline
Yes
National retail fuel prices (with taxes included):-Transport, diesel
Yes
National retail fuel prices (with taxes included):-Natural gas, industry
National retail fuel prices (with taxes included):-Natural gas, households
National retail electricity prices (with taxes included):-Industry
National retail electricity prices (with taxes included):-Households
Gross inland (primary energy) consumption:-Coal
38105 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Oil
62194 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Natural gas
33615 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Renewables
64981 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Nuclear
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Other
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Total
198895 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
92
Gross electricity production:-Coal
1.65456 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Oil
0.0006 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Natural gas
2.04348 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Renewables
4.14235 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Nuclear
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Other
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Total
7.84099 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Total net electricity imports
2.5 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross final energy consumption
186586 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Industry
50142 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Transport
49247 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Residential
44554 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Agriculture/Forestry
8247 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Services
25108 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Other
IE MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Total
177298 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Number of heating degree days (HDD)
4092 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Number of cooling degree days (CDD)
Transport parameters
Number of passenger-kilometres (all modes)
10439.2 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Freight transport tonnes-kilometres (all modes)
43122.8 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Final energy demand for road transport
38788 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Buildings parameters
Number of households
864.386 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Household size 2.22641 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Agriculture parameters
Livestock:-Dairy cattle
250.25 Yes
Livestock:-Non-dairy cattle
351 Yes
93
Livestock:-Sheep 186.75 Yes
Livestock:-Pig 452 Yes
Livestock:-Poultry 8385 Yes
Nitrogen input from application of synthetic fertilizers
113.75 Yes
Nitrogen input from application of manure
27.1593 Yes
Nitrogen fixed by N-fixing crops
NA
Nitrogen in crop residues returned to soils
33.645 Yes
Area of cultivated organic soils
132895 Yes
Waste parameters
Municipal solid waste (MSW) generation
2746926 Expert judgment
2015 Yes
Municipal solid waste (MSW) going to landfills
322000 Expert judgment
2015 Yes
Share of CH4 recovery in total CH4 generation from landfills
46.0159 Expert judgment
2015 Yes
Other parameters
Biodegradable waste composted
Amount of municipal solid waste open burned
Add rows for other relevant parameters(1)
Parameter used(4) ('with additional measures' scenario)
Population 1924.48 Yes Yes Yes Yes Yes
Gross domestic product (GDP):-Real growth rate
2.46263 Ministry of Economics
2015
Gross domestic product (GDP):-Constant prices
44385.6 Ministry of Economics
2015 Yes Yes Yes Yes
Gross value added (GVA) total industry
7127.73 Ministry of Economics
2015 Yes Yes
Exchange rates EURO (for non-EURO countries), if applicable
Exchange rates US DOLLAR, if applicable
EU ETS carbon price 46.5434 Primes 2013
2013 Yes Yes Yes Yes Yes Yes No No No No Yes
International (wholesale) fuel import prices:-Electricity Coal
4.56 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
International (wholesale) fuel import prices:-Crude Oil
16.2914 IEA 2014 Yes Yes Yes Yes Yes Yes No No No No Yes
International (wholesale) fuel
8.92 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
94
import prices:-Natural gas
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
National retail fuel prices (with taxes included):-Coal, households
National retail fuel prices (with taxes included):-Heating oil, industry
National retail fuel prices (with taxes included):-Heating oil, households
National retail fuel prices (with taxes included):-Transport, gasoline
Yes
National retail fuel prices (with taxes included):-Transport, diesel
Yes
National retail fuel prices (with taxes included):-Natural gas, industry
National retail fuel prices (with taxes included):-Natural gas, households
National retail electricity prices (with taxes included):-Industry
National retail electricity prices (with taxes included):-Households
Gross inland (primary energy) consumption:-Coal
22525 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Oil
59883 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Natural gas
32488 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Renewables
82602 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Nuclear
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Other
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross inland (primary energy) consumption:-Total
197498 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
95
Gross electricity production:-Coal
0.63968 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Oil
0.00057 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Natural gas
1.91993 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Renewables
5.28425 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Nuclear
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Other
NO MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross electricity production:-Total
7.84443 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Total net electricity imports
2.5 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Gross final energy consumption
185815 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Industry
49761 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Transport
48861 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Residential
44466 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Agriculture/Forestry
8437 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Services
25078 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Other
IE MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Final energy consumption:-Total
176603 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Number of heating degree days (HDD)
4092 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Number of cooling degree days (CDD)
Transport parameters
Number of passenger-kilometres (all modes)
10439.2 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Freight transport tonnes-kilometres (all modes)
43122.8 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Final energy demand for road transport
38444 MARKAL 2015 YES YES YES YES YES YES NO NO NO NO YES
Buildings parameters
Number of households
864.386 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Household size 2.22641 MARKAL 2015 Yes Yes Yes Yes Yes Yes No No No No Yes
Agriculture parameters
Livestock:-Dairy cattle
250.25 Yes
Livestock:-Non-dairy cattle
351 Yes
96
Livestock:-Sheep 186.75 Yes
Livestock:-Pig 452 Yes
Livestock:-Poultry 8385 Yes
Nitrogen input from application of synthetic fertilizers
113.75 Yes
Nitrogen input from application of manure
27.1593 Yes
Nitrogen fixed by N-fixing crops
NA
Nitrogen in crop residues returned to soils
33.645 Yes
Area of cultivated organic soils
132895 Yes
Waste parameters
Municipal solid waste (MSW) generation
2746926 Expert judgment
2015 Yes
Municipal solid waste (MSW) going to landfills
322000 Expert judgment
2015 Yes
Share of CH4 recovery in total CH4 generation from landfills
46.0159 Expert judgment
2015 Yes
Other parameters
Biodegradable waste composted
Amount of municipal solid waste open burned
Add rows for other relevant parameters(1)
Submission Year 2015
MS Estonia
Parameter used(4) ('with existing measures' scenario)
2035 Year of publication of data source
1.A.1 1.A.2 1.A.3
1.A.4.a
1.A.4.b
1B 2 3 4 5 IA
Population 1178674 2014 No No Yes Yes Yes No No No No Yes Yes
Gross domestic product (GDP):-Real growth rate
2.1 2014 Yes Yes Yes Yes Yes Yes No No No Yes Yes
Gross domestic product (GDP):-Constant prices
29499 2014 Yes Yes Yes Yes Yes Yes No No No Yes yes
Gross value added (GVA) total industry
NA NA No No No No No No No No No No No
Exchange rates EURO (for non-EURO countries), if applicable
NA NA No No No No No No No No No No No
Exchange rates US DOLLAR, if applicable
NA NA No No No No No No No No No No No
EU ETS carbon price 30 2014 Yes Yes No No No No Yes No No No No
International (wholesale) fuel import prices:-Electricity Coal
3.44 2014 Yes Yes No No No No Yes No No No No
International (wholesale) fuel
15.8 2014 Yes Yes Yes Yes Yes No Yes No No No No
97
import prices:-Crude Oil
International (wholesale) fuel import prices:-Natural gas
10.9 2014 Yes Yes Yes Yes Yes Yes Yes No No No No
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Coal, households
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Heating oil, industry
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Heating oil, households
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Transport, gasoline
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Transport, diesel
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Natural gas, industry
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Natural gas, households
NA NA No No No No No No No No No No No
National retail electricity prices (with taxes included):-Industry
NA NA No No No No No No No No No No No
National retail electricity prices (with taxes included):-Households
NA NA No No No No No No No No No No No
Gross inland (primary energy) consumption:-Coal
18238866 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Oil
37117830 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Natural gas
23710967 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Renewables
79573660 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Nuclear
NO NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Other
2.67E+08 NA Yes Yes Yes Yes Yes Yes No No No No No
98
Gross inland (primary energy) consumption:-Total
4.25E+08 NA Yes Yes Yes Yes Yes Yes No No No No
Gross electricity production:-Coal
1.42 NA Yes No No No No No No No No No No
Gross electricity production:-Oil
NO NA Yes No No No No No No No No No No
Gross electricity production:-Natural gas
0.082 NA Yes No No No No No No No No No No
Gross electricity production:-Renewables
2.335 NA Yes No No No No No No No No No No
Gross electricity production:-Nuclear
NO NA Yes No No No No No No No No No No
Gross electricity production:-Other
5.58 NA Yes No No No No No No No No No No
Gross electricity production:-Total
9.417 NA Yes No No No No No No No No No No
Total net electricity imports
1.546 NA Yes No No No No No No No No No No
Gross final energy consumption
37.768 NA Yes Yes Yes Yes Yes Yes Yes No No No Yes
Final energy consumption:-Industry
31466000 NA No Yes No No No Yes Yes No No No No
Final energy consumption:-Transport
38040000 NA No No Yes No No Yes No No No No Yes
Final energy consumption:-Residential
43629000 NA No No No No Yes Yes No No No No No
Final energy consumption:-Agriculture/Forestry
5595000 NA No No No No No Yes No No No No No
Final energy consumption:-Services
17046000 NA No No No Yes No Yes No No No No No
Final energy consumption:-Other
189000 NA No No No No No Yes No No No No No
Final energy consumption:-Total
1.36E+08 NA Yes Yes Yes Yes Yes Yes Yes No No No Yes
Number of heating degree days (HDD)
NA NA No No No No No No Yes No No No No
Number of cooling degree days (CDD)
NA NA No No No No No No Yes No No No No
Transport parameters
Number of passenger-kilometres (all modes)
7415.108 2014 No No Yes No No No No No No No Yes
Freight transport tonnes-kilometres (all modes)
15112.61 2015 No No Yes No No No No No No No Yes
Final energy demand for road transport
35070000 2016 No No Yes No No No No No No No No
Buildings parameters
No No No
Number of households
NA NA Yes No No No No No No No No No No
Household size NA NA No No No No No No No No No No No
Agriculture parameters
Livestock:-Dairy cattle
115 NA No No No No No No No Yes No No No
99
Livestock:-Non-dairy cattle
160.9 NA No No No No No No No Yes No No No
Livestock:-Sheep 97.6 NA No No No No No No No Yes No No No
Livestock:-Pig 379 NA No No No No No No No Yes No No No
Livestock:-Poultry 2241.231 NA No No No No No No No Yes No No No
Nitrogen input from application of synthetic fertilizers
35.75 NA No No No No No No No Yes No No No
Nitrogen input from application of manure
11.58791 NA No No No No No No No Yes No No No
Nitrogen fixed by N-fixing crops
NA NA No No No No No No No No No No No
Nitrogen in crop residues returned to soils
13.38744 2010 No No No No No No No Yes No No No
Area of cultivated organic soils
22619.38 NA No No No No No No No Yes No No No
Waste parameters
Municipal solid waste (MSW) generation
454617 NA No No No No No No No No No Yes No
Municipal solid waste (MSW) going to landfills
33283.49 NA No No No No No No No No No Yes No
Share of CH4 recovery in total CH4 generation from landfills
46.76262 NA No No No No No No No No No Yes No
Other parameters
Biodegradable waste composted
291772.4 NA No No No No No No No No No Yes No
Amount of municipal solid waste open burned
0 NA No No No No No No No No No Yes No
Add rows for other relevant parameters(1)
Parameter used(4) ('with additional measures' scenario)
Population 1178674 2014 No No Yes Yes Yes No No No No Yes Yes
Gross domestic product (GDP):-Real growth rate
2.1 2014 Yes Yes Yes Yes Yes Yes No No No Yes Yes
Gross domestic product (GDP):-Constant prices
29499 2014 Yes Yes Yes Yes Yes Yes No No No Yes yes
Gross value added (GVA) total industry
NA NA No No No No No No No No No No No
Exchange rates EURO (for non-EURO countries), if applicable
NA NA No No No No No No No No No No No
Exchange rates US DOLLAR, if applicable
NA NA No No No No No No No No No No No
EU ETS carbon price 30 2014 Yes Yes No No No No Yes No No No No
International (wholesale) fuel import prices:-Electricity Coal
3.44 2014 Yes Yes No No No No Yes No No No No
International (wholesale) fuel import prices:-Crude Oil
15.8 2014 Yes Yes Yes Yes Yes No Yes No No No No
International (wholesale) fuel
10.9 2014 Yes Yes Yes Yes Yes Yes Yes No No No No
100
import prices:-Natural gas
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Coal, households
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Heating oil, industry
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Heating oil, households
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Transport, gasoline
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Transport, diesel
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Natural gas, industry
NA NA No No No No No No No No No No No
National retail fuel prices (with taxes included):-Natural gas, households
NA NA No No No No No No No No No No No
National retail electricity prices (with taxes included):-Industry
NA NA No No No No No No No No No No No
National retail electricity prices (with taxes included):-Households
NA NA No No No No No No No No No No No
Gross inland (primary energy) consumption:-Coal
16440930 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Oil
21133000 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Natural gas
15498028 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Renewables
70549050 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Nuclear
NO NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Other
2.66E+08 NA Yes Yes Yes Yes Yes Yes No No No No No
Gross inland (primary energy) consumption:-Total
3.89E+08 NA Yes Yes Yes Yes Yes Yes No No No No
101
Gross electricity production:-Coal
1.4 NA Yes No No No No No No No No No No
Gross electricity production:-Oil
NO NA Yes No No No No No No No No No No
Gross electricity production:-Natural gas
0.082 NA Yes No No No No No No No No No No
Gross electricity production:-Renewables
2.374 NA Yes No No No No No No No No No No
Gross electricity production:-Nuclear
NO NA Yes No No No No No No No No No No
Gross electricity production:-Other
5.58 NA Yes No No No No No No No No No No
Gross electricity production:-Total
9.436 NA Yes No No No No No No No No No No
Total net electricity imports
1.546 NA Yes No No No No No No No No No No
Gross final energy consumption
30.556 NA Yes Yes Yes Yes Yes Yes Yes No No No Yes
Final energy consumption:-Industry
31466000 NA No Yes No No No Yes Yes No No No No
Final energy consumption:-Transport
25162000 NA No No Yes No No Yes No No No No Yes
Final energy consumption:-Residential
31784000 NA No No No No Yes Yes No No No No No
Final energy consumption:-Agriculture/Forestry
5595000 NA No No No No No Yes No No No No No
Final energy consumption:-Services
15804000 NA No No No Yes No Yes No No No No No
Final energy consumption:-Other
189000 NA No No No No No Yes No No No No No
Final energy consumption:-Total
1.1E+08 NA Yes Yes Yes Yes Yes Yes Yes No No No Yes
Number of heating degree days (HDD)
NA NA No No No No No No Yes No No No No
Number of cooling degree days (CDD)
NA NA No No No No No No Yes No No No No
Transport parameters
Number of passenger-kilometres (all modes)
6456.999 2014 No No Yes No No No No No No No Yes
Freight transport tonnes-kilometres (all modes)
13764.57 2015 No No Yes No No No No No No No Yes
Final energy demand for road transport
22390000 2016 No No Yes No No No No No No No No
Buildings parameters
No No No
Number of households
NA NA Yes No No No No No No No No No No
Household size NA NA No No No No No No No No No No No
Agriculture parameters
Livestock:-Dairy cattle
115 NA No No No No No No No Yes No No No
Livestock:-Non-dairy cattle
160.9 NA No No No No No No No Yes No No No
Livestock:-Sheep 97.6 NA No No No No No No No Yes No No No
Livestock:-Pig 379 NA No No No No No No No Yes No No No
102
Livestock:-Poultry 2241.231 NA No No No No No No No Yes No No No
Nitrogen input from application of synthetic fertilizers
35.75 NA No No No No No No No Yes No No No
Nitrogen input from application of manure
11.58791 NA No No No No No No No Yes No No No
Nitrogen fixed by N-fixing crops
NA NA No No No No No No No No No No No
Nitrogen in crop residues returned to soils
13.38744 2010 No No No No No No No Yes No No No
Area of cultivated organic soils
22619.38 NA No No No No No No No Yes No No No
Waste parameters
Municipal solid waste (MSW) generation
454617 NA No No No No No No No No No Yes No
Municipal solid waste (MSW) going to landfills
33283.49 NA No No No No No No No No No Yes No
Share of CH4 recovery in total CH4 generation from landfills
46.76262 NA No No No No No No No No No Yes No
Other parameters
Biodegradable waste composted
291772.4 NA No No No No No No No No No Yes No
Amount of municipal solid waste open burned
0 NA No No No No No No No No No Yes No
Add rows for other relevant parameters(1)
103
Estonia – data sources (For Latvia it was included in the table)
Submission Year 2015
MS Estonia
Parameter used(4) ('with existing measures' scenario)
Data source
Population "Recommended parameters for reporting on GHG projections in 2015"
Gross domestic product (GDP):-Real growth rate
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Gross domestic product (GDP):-Constant prices
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Gross value added (GVA) total industry NA
Exchange rates EURO (for non-EURO countries), if applicable
NA
Exchange rates US DOLLAR, if applicable NA
EU ETS carbon price Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
International (wholesale) fuel import prices:-Electricity Coal
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
International (wholesale) fuel import prices:-Crude Oil
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
International (wholesale) fuel import prices:-Natural gas
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
NA
National retail fuel prices (with taxes included):-Coal, households
NA
National retail fuel prices (with taxes included):-Heating oil, industry
NA
National retail fuel prices (with taxes included):-Heating oil, households
NA
National retail fuel prices (with taxes included):-Transport, gasoline
NA
National retail fuel prices (with taxes included):-Transport, diesel
NA
National retail fuel prices (with taxes included):-Natural gas, industry
NA
National retail fuel prices (with taxes included):-Natural gas, households
NA
National retail electricity prices (with taxes included):-Industry
NA
National retail electricity prices (with taxes included):-Households
NA
Gross inland (primary energy) consumption:-Coal
LEAP model results
Gross inland (primary energy) consumption:-Oil
LEAP model results
Gross inland (primary energy) consumption:-Natural gas
LEAP model results
Gross inland (primary energy) consumption:-Renewables
LEAP model results
Gross inland (primary energy) consumption:-Nuclear
NA
Gross inland (primary energy) consumption:-Other
LEAP model results
Gross inland (primary energy) consumption:-Total
LEAP model results
Gross electricity production:-Coal LEAP model results
Gross electricity production:-Oil LEAP model results
104
Gross electricity production:-Natural gas LEAP model results
Gross electricity production:-Renewables
LEAP model results
Gross electricity production:-Nuclear NA
Gross electricity production:-Other LEAP model results
Gross electricity production:-Total LEAP model results
Total net electricity imports LEAP model results
Gross final energy consumption LEAP model results
Final energy consumption:-Industry LEAP model results
Final energy consumption:-Transport LEAP model results
Final energy consumption:-Residential LEAP model results
Final energy consumption:-Agriculture/Forestry
LEAP model results
Final energy consumption:-Services LEAP model results
Final energy consumption:-Other LEAP model results
Final energy consumption:-Total LEAP model results
Number of heating degree days (HDD) NA
Number of cooling degree days (CDD) NA
Transport parameters
Number of passenger-kilometers (all modes)
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Freight transport tonnes-kilometers (all modes)
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Final energy demand for road transport Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Buildings parameters
Number of households NA
Household size NA
Agriculture parameters
Livestock:-Dairy cattle Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Non-dairy cattle Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Sheep Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Pig Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Poultry Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Nitrogen input from application of synthetic fertilizers
Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Nitrogen input from application of manure
Projection based on the number of livestock, milk yield and allocation of manure management systems
Nitrogen fixed by N-fixing crops NA
Nitrogen in crop residues returned to soils
Data on crops production originate from the report Analysis of the systematic development measures and the respective EU policy future directions of Estonian agriculture, forestry and conservancy compiled by the Estonian University of Life Sciences.
Area of cultivated organic soils Value of 2013 was used for the whole projected time-series and Estonian Environment Agency
Waste parameters
Municipal solid waste (MSW) generation Projection based on population, base year and GDP growth rate
Municipal solid waste (MSW) going to landfills
Projection based on increase of recycled waste and the amount of waste projected to burn in Iru CHP waste incineration plant
Share of CH4 recovery in total CH4 generation from landfills
Projection based on the average amount of CH4 recovered and applied to the total CH4 generation from landfills
Other parameters
Biodegradable waste composted Projection based on increase of recycled waste , base year and GDP growth rate
Amount of municipal solid waste open burned
Projection based on the decrease of open burning and total amount of waste generated
Add rows for other relevant parameters(1)
Parameter used(4) ('with additional measures' scenario)
Population "Recommended parameters for reporting on GHG projections in 2015"
105
Gross domestic product (GDP):-Real growth rate
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Gross domestic product (GDP):-Constant prices
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Gross value added (GVA) total industry NA
Exchange rates EURO (for non-EURO countries), if applicable
NA
Exchange rates US DOLLAR, if applicable NA
EU ETS carbon price Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
International (wholesale) fuel import prices:-Electricity Coal
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
International (wholesale) fuel import prices:-Crude Oil
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
International (wholesale) fuel import prices:-Natural gas
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
NA
National retail fuel prices (with taxes included):-Coal, households
NA
National retail fuel prices (with taxes included):-Heating oil, industry
NA
National retail fuel prices (with taxes included):-Heating oil, households
NA
National retail fuel prices (with taxes included):-Transport, gasoline
NA
National retail fuel prices (with taxes included):-Transport, diesel
NA
National retail fuel prices (with taxes included):-Natural gas, industry
NA
National retail fuel prices (with taxes included):-Natural gas, households
NA
National retail electricity prices (with taxes included):-Industry
NA
National retail electricity prices (with taxes included):-Households
NA
Gross inland (primary energy) consumption:-Coal
LEAP model results
Gross inland (primary energy) consumption:-Oil
LEAP model results
Gross inland (primary energy) consumption:-Natural gas
LEAP model results
Gross inland (primary energy) consumption:-Renewables
LEAP model results
Gross inland (primary energy) consumption:-Nuclear
NA
Gross inland (primary energy) consumption:-Other
LEAP model results
Gross inland (primary energy) consumption:-Total
LEAP model results
Gross electricity production:-Coal LEAP model results
Gross electricity production:-Oil LEAP model results
Gross electricity production:-Natural gas LEAP model results
Gross electricity production:-Renewables
LEAP model results
Gross electricity production:-Nuclear NA
Gross electricity production:-Other LEAP model results
Gross electricity production:-Total LEAP model results
Total net electricity imports LEAP model results
106
Gross final energy consumption LEAP model results
Final energy consumption:-Industry LEAP model results
Final energy consumption:-Transport LEAP model results
Final energy consumption:-Residential LEAP model results
Final energy consumption:-Agriculture/Forestry
LEAP model results
Final energy consumption:-Services LEAP model results
Final energy consumption:-Other LEAP model results
Final energy consumption:-Total LEAP model results
Number of heating degree days (HDD) NA
Number of cooling degree days (CDD) NA
Transport parameters
Number of passenger-kilometres (all modes)
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Freight transport tonnes-kilometres (all modes)
Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Final energy demand for road transport Analysis and projections regarding "Energy Sector Development Plan 2030+". All relevant information available at http://www.energiatalgud.ee
Buildings parameters
Number of households NA
Household size NA
Agriculture parameters
Livestock:-Dairy cattle Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Non-dairy cattle Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Sheep Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Pig Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Livestock:-Poultry Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Nitrogen input from application of synthetic fertilizers
Projection based on an expert opinion by the Estonian Ministry of Agriculture and Statistics Estonia
Nitrogen input from application of manure
Projection based on the number of livestock, milk yield and allocation of manure management systems
Nitrogen fixed by N-fixing crops NA
Nitrogen in crop residues returned to soils
Data on crops production originate from the report Analysis of the systematic development measures and the respective EU policy future directions of Estonian agriculture, forestry and conservancy compiled by the Estonian University of Life Sciences.
Area of cultivated organic soils Value of 2013 was used for the whole projected time-series and Estonian Environment Agency
Waste parameters
Municipal solid waste (MSW) generation Projection based on population, base year and GDP growth rate
Municipal solid waste (MSW) going to landfills
Projection based on increase of recycled waste and the amount of waste projected to burn in Iru CHP waste incineration plant
Share of CH4 recovery in total CH4 generation from landfills
Projection based on the avarege amount of CH4 recovered and applied to the total CH4 generation from landfills
Other parameters
Biodegradable waste composted Projection based on increase of recycled waste , base year and GDP growth rate
Amount of municipal solid waste open burned
Projection based on the decrease of open burning and total amount of waste generated
Add rows for other relevant parameters(1)
107
Submission Year 2015
MS Lithuania
Sectoral projections for which the parameter is used(2)
Parameter used(4) ('with existing measures' scenario)
Year of publication of data source
1.A.1
1.A.2
1.A.3
1.A.4.a
1.A.4.b
1B
2 3 4 5 IA
Population 2057227 2014 Yes
Gross domestic product (GDP):-Real growth rate
2.2 2014 Yes Yes Yes Yes Yes
Gross domestic product (GDP):-Constant prices
2015
Gross value added (GVA) total industry
Exchange rates EURO (for non-EURO countries), if applicable
Exchange rates US DOLLAR, if applicable
EU ETS carbon price 6.37 Yes Yes Yes Yes Yes Yes
International (wholesale) fuel import prices:-Electricity Coal
International (wholesale) fuel import prices:-Crude Oil
International (wholesale) fuel import prices:-Natural gas
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
National retail fuel prices (with taxes included):-Coal, households
National retail fuel prices (with taxes included):-Heating oil, industry
National retail fuel prices (with taxes included):-Heating oil, households
National retail fuel prices (with taxes included):-Transport, gasoline
National retail fuel prices (with taxes included):-Transport, diesel
National retail fuel prices (with taxes included):-Natural gas, industry
National retail fuel prices (with taxes included):-Natural gas, households
National retail electricity prices (with taxes included):-Industry
National retail electricity prices (with taxes included):-Households
Gross inland (primary energy) consumption:-Coal
2015
Gross inland (primary energy) consumption:-Oil
2015
Gross inland (primary energy) consumption:-Natural gas
2015
Gross inland (primary energy) consumption:-Renewables
2015
108
Gross inland (primary energy) consumption:-Nuclear
2015
Gross inland (primary energy) consumption:-Other
2015
Gross inland (primary energy) consumption:-Total
2015
Gross electricity production:-Coal
Gross electricity production:-Oil
Gross electricity production:-Natural gas
Gross electricity production:-Renewables
Gross electricity production:-Nuclear
Gross electricity production:-Other
Gross electricity production:-Total
Total net electricity imports 2015
Gross final energy consumption
Final energy consumption:-Industry
2.6E+07 2014 x Yes
Final energy consumption:-Transport
9.3E+07 2014 x Yes Yes
Final energy consumption:-Residential
3.1E+07 2014 x Yes
Final energy consumption:-Agriculture/Forestry
3764000 2014 x
Final energy consumption:-Services
7491070 2014 x Yes
Final energy consumption:-Other
1586650 2014 x
Final energy consumption:-Total
1.6E+08 2014 x
Number of heating degree days (HDD)
Number of cooling degree days (CDD)
Transport parameters
Number of passenger-kilometres (all modes)
Yes
Freight transport tonnes-kilometres (all modes)
Yes
Final energy demand for road transport
Buildings parameters
Number of households
Household size
Agriculture parameters
Livestock:-Dairy cattle 338.333
Livestock:-Non-dairy cattle 510.029
Livestock:-Sheep 168.162
Livestock:-Pig 931.944
Livestock:-Poultry 10099.6
Nitrogen input from application of synthetic fertilizers
159.129
109
Nitrogen input from application of manure (including sewage sludge and compost)
30.7948
Nitrogen fixed by N-fixing crops
Nitrogen in crop residues returned to soils (including N-fixing crops)
74.3379
Area of cultivated organic soils (same as in 2012)
175.713
Waste parameters
Municipal solid waste (MSW) generation
1472.24 2014 Yes
Municipal solid waste (MSW) going to landfills
441.672 2014 Yes
Share of CH4 recovery in total CH4 generation from landfills
34.4619 2015 Yes
Other parameters
Add rows for other relevant parameters(1)
Parameter used(4) ('with additional measures' scenario)
Population
Gross domestic product (GDP):-Real growth rate
Gross domestic product (GDP):-Constant prices
Gross value added (GVA) total industry
Exchange rates EURO (for non-EURO countries), if applicable
Exchange rates US DOLLAR, if applicable
EU ETS carbon price
International (wholesale) fuel import prices:-Electricity Coal
International (wholesale) fuel import prices:-Crude Oil
International (wholesale) fuel import prices:-Natural gas
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
National retail fuel prices (with taxes included):-Coal, households
National retail fuel prices (with taxes included):-Heating oil, industry
National retail fuel prices (with taxes included):-Heating oil, households
National retail fuel prices (with taxes included):-Transport, gasoline
National retail fuel prices (with taxes included):-Transport, diesel
110
National retail fuel prices (with taxes included):-Natural gas, industry
National retail fuel prices (with taxes included):-Natural gas, households
National retail electricity prices (with taxes included):-Industry
National retail electricity prices (with taxes included):-Households
Gross inland (primary energy) consumption:-Coal
Gross inland (primary energy) consumption:-Oil
Gross inland (primary energy) consumption:-Natural gas
Gross inland (primary energy) consumption:-Renewables
Gross inland (primary energy) consumption:-Nuclear
Gross inland (primary energy) consumption:-Other
Gross inland (primary energy) consumption:-Total
Gross electricity production:-Coal
Gross electricity production:-Oil
Gross electricity production:-Natural gas
Gross electricity production:-Renewables
Gross electricity production:-Nuclear
Gross electricity production:-Other
Gross electricity production:-Total
Total net electricity imports
Gross final energy consumption
Final energy consumption:-Industry
2.1E+07 2014 Yes
Final energy consumption:-Transport
7.5E+07 2014 Yes Yes
Final energy consumption:-Residential
2.6E+07 2014 Yes
Final energy consumption:-Agriculture/Forestry
3682000 2014
Final energy consumption:-Services
6046118 2014 Yes
Final energy consumption:-Other
82000 2014
Final energy consumption:-Total
1.3E+08 2014
Number of heating degree days (HDD)
Number of cooling degree days (CDD)
Transport parameters
111
Number of passenger-kilometres (all modes)
Freight transport tonnes-kilometres (all modes)
Final energy demand for road transport
Buildings parameters
Number of households
Household size
Agriculture parameters
Livestock:-Dairy cattle
Livestock:-Non-dairy cattle
Livestock:-Sheep
Livestock:-Pig
Livestock:-Poultry
Nitrogen input from application of synthetic fertilizers
Nitrogen input from application of manure
Nitrogen fixed by N-fixing crops
Nitrogen in crop residues returned to soils
Area of cultivated organic soils
Waste parameters
Municipal solid waste (MSW) generation
Municipal solid waste (MSW) going to landfills
Share of CH4 recovery in total CH4 generation from landfills
Other parameters
Add rows for other relevant parameters(1)
Lithuania – data sources
Submission Year 2015
MS Lithuania
Parameter used(4) ('with existing measures' scenario)
Data source
Population Commission recommended parameters for reporting on GHG projections in 2015
Gross domestic product (GDP):-Real growth rate
Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Gross domestic product (GDP):-Constant prices
Lithuania statistics department. Data updated at: 2015-05-29 (GDP, at constant prices (chain-linking method) | EUR million)
Gross value added (GVA) total industry
Exchange rates EURO (for non-EURO countries), if applicable
Exchange rates US DOLLAR, if applicable
EU ETS carbon price Constant price (EEX Emissionsmarkt / EUA Primary Market Auction)
International (wholesale) fuel import prices:-Electricity Coal
International (wholesale) fuel import prices:-Crude Oil
International (wholesale) fuel import prices:-Natural gas
112
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
National retail fuel prices (with taxes included):-Coal, households
National retail fuel prices (with taxes included):-Heating oil, industry
National retail fuel prices (with taxes included):-Heating oil, households
National retail fuel prices (with taxes included):-Transport, gasoline
National retail fuel prices (with taxes included):-Transport, diesel
National retail fuel prices (with taxes included):-Natural gas, industry
National retail fuel prices (with taxes included):-Natural gas, households
National retail electricity prices (with taxes included):-Industry
National retail electricity prices (with taxes included):-Households
Gross inland (primary energy) consumption:-Coal
Eurostat online database table nrg_100a, last update 2015-04-27
Gross inland (primary energy) consumption:-Oil
Eurostat online database table nrg_100a, last update 2015-04-27
Gross inland (primary energy) consumption:-Natural gas
Eurostat online database table nrg_100a, last update 2015-04-27
Gross inland (primary energy) consumption:-Renewables
Eurostat online database table nrg_100a, last update 2015-04-27
Gross inland (primary energy) consumption:-Nuclear
Eurostat online database table nrg_100a, last update 2015-04-27
Gross inland (primary energy) consumption:-Other
Eurostat online database table nrg_100a, last update 2015-04-27
Gross inland (primary energy) consumption:-Total
Eurostat online database table nrg_100a, last update 2015-04-27
Gross electricity production:-Coal
Gross electricity production:-Oil
Gross electricity production:-Natural gas
Gross electricity production:-Renewables
Gross electricity production:-Nuclear
Gross electricity production:-Other
Gross electricity production:-Total
Total net electricity imports Lithuania statistics department. (23,828 TJ According to Eurostat nrg_100a, last update 2015-04-27)
Gross final energy consumption
Final energy consumption:-Industry calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Transport calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Residential calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Agriculture/Forestry
calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Services calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Other calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Total calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Number of heating degree days (HDD)
113
Number of cooling degree days (CDD)
Transport parameters
Number of passenger-kilometres (all modes)
Data recieved from Ministry of transport and comunication
Freight transport tonnes-kilometres (all modes)
Data recieved from Ministry of transport and comunication
Final energy demand for road transport
Buildings parameters
Number of households
Household size
Agriculture parameters
Livestock:-Dairy cattle Institute of animal science
Livestock:-Non-dairy cattle Institute of animal science
Livestock:-Sheep Institute of animal science
Livestock:-Pig Institute of animal science
Livestock:-Poultry Institute of animal science
Nitrogen input from application of synthetic fertilizers
Ministry of Agriculture (MoA)
Nitrogen input from application of manure (including sewage sludge and compost)
Institute of animal science/MoA
Nitrogen fixed by N-fixing crops
Nitrogen in crop residues returned to soils (including N-fixing crops)
Ministry of Agriculture (MoA)
Area of cultivated organic soils (same as in 2012)
Waste parameters
Municipal solid waste (MSW) generation National Plan of Waste Management
Municipal solid waste (MSW) going to landfills
National Plan of Waste Management
Share of CH4 recovery in total CH4 generation from landfills
Association of the Regional Waste Management Centers
Other parameters
Add rows for other relevant parameters(1)
Parameter used(4) ('with additional measures' scenario)
Population
Gross domestic product (GDP):-Real growth rate
Gross domestic product (GDP):-Constant prices
Gross value added (GVA) total industry
Exchange rates EURO (for non-EURO countries), if applicable
Exchange rates US DOLLAR, if applicable
EU ETS carbon price
International (wholesale) fuel import prices:-Electricity Coal
International (wholesale) fuel import prices:-Crude Oil
International (wholesale) fuel import prices:-Natural gas
Energy parameters
National retail fuel prices (with taxes included):-Coal, industry
National retail fuel prices (with taxes included):-Coal, households
National retail fuel prices (with taxes included):-Heating oil, industry
114
National retail fuel prices (with taxes included):-Heating oil, households
National retail fuel prices (with taxes included):-Transport, gasoline
National retail fuel prices (with taxes included):-Transport, diesel
National retail fuel prices (with taxes included):-Natural gas, industry
National retail fuel prices (with taxes included):-Natural gas, households
National retail electricity prices (with taxes included):-Industry
National retail electricity prices (with taxes included):-Households
Gross inland (primary energy) consumption:-Coal
Gross inland (primary energy) consumption:-Oil
Gross inland (primary energy) consumption:-Natural gas
Gross inland (primary energy) consumption:-Renewables
Gross inland (primary energy) consumption:-Nuclear
Gross inland (primary energy) consumption:-Other
Gross inland (primary energy) consumption:-Total
Gross electricity production:-Coal
Gross electricity production:-Oil
Gross electricity production:-Natural gas
Gross electricity production:-Renewables
Gross electricity production:-Nuclear
Gross electricity production:-Other
Gross electricity production:-Total
Total net electricity imports
Gross final energy consumption
Final energy consumption:-Industry calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Transport calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Residential calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Agriculture/Forestry
calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Services calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Other calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Final energy consumption:-Total calculated according to Lithuanian energy sector development outlook analysis in relation to the EU’s strategic energy initiatives
Number of heating degree days (HDD)
Number of cooling degree days (CDD)
Transport parameters
Number of passenger-kilometres (all modes)
Freight transport tonnes-kilometres (all modes)
Final energy demand for road transport
Buildings parameters
115
Number of households
Household size
Agriculture parameters
Livestock:-Dairy cattle
Livestock:-Non-dairy cattle
Livestock:-Sheep
Livestock:-Pig
Livestock:-Poultry
Nitrogen input from application of synthetic fertilizers
Nitrogen input from application of manure
Nitrogen fixed by N-fixing crops
Nitrogen in crop residues returned to soils
Area of cultivated organic soils
Waste parameters
Municipal solid waste (MSW) generation
Municipal solid waste (MSW) going to landfills
Share of CH4 recovery in total CH4 generation from landfills
Other parameters
Add rows for other relevant parameters(1)
