GHG emissions - outlook from MNP
Justification for indicator selection
There is growing evidence that emissions of greenhouse gases are causing global and European surface air temperatures to increase, resulting in climate change (IPCC, 2001). The potential consequences at the global level include rising sea levels, increasing frequency and intensity of floods and droughts, changes in biota and food productivity and increases in diseases. Efforts to reduce or limit the effects of climate change are focused on limiting the emissions of all greenhouse gases covered by the Kyoto Protocol.
This outlook supports assessment of progress in reducing GHG emissions in the pan-European level to achieve the Kyoto Protocol targets and relevant EU commitments. It also helps to identify appropriate policy response options.
- No rationale references available
This indicator illustrates the projected trends in anthropogenic greenhouse gas emissions in relation to the EU and Member State targets, using existing policies and measures and/or additional policies and/or use of Kyoto mechanisms. The greenhouse gases are those covered by the Kyoto Protocol (CO2, CH4, N2O, SF6, HFCs and PFCs), weighed by their respective global warming potential, aggregated and presented in CO2-equivalent units.
The indicator also provides information on emissions from the main greenhouse gas emitting sectors: energy supply and use (including energy industry, fugitive emissions, energy use by industry and by other sectors); transport; industry (processes); agriculture; waste and other (non-energy).
Model used: IMAGE
Ownership: Netherlands Environmental Assessment Agency (MNP)
Temporal coverage: 1990 - 2100
Geographical coverage: OECD Europe: Andorra, Austria, Belgium, Denmark, Faeroe Islands, Finland, France, Germany, Gibraltar, Greece, Holy See, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Svalbard and Jan Mayen; Eastern Europe: Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, Macedonia, Poland, Romania, Slovakia, Slovenia, Yugoslavia; Former USSR: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan; South Asia: Afganistan, Bangladesh, Bhutan, British Indian Ocean Territory, India, Maldives, Nepal, Pakistan, Sri Lanka; East Asia: China, Hong Kong, Democratic People's Republic of Korea, Republic of Korea, Macau, Mongolia, Taiwan; Canada, USA
UnitsMillion tonnes in CO2-equivalent or Gt in CO2-equivalent
Policy context and targets
Over a decade ago, most countries joined an international treaty -- the(UNFCCC) -- to begin to consider what can be done to reduce global warming and to cope with whatever temperature increases are inevitable. Recently, a number of nations have approved an addition to the treaty: the . The Kyoto Protocol, an international and legally binding agreement to reduce greenhouse gases emissions world wide, entered into force on February 16th 2005. The 1997 Kyoto Protocol shares the Convention's objective, principles and institutions, but significantly strengthens the Convention by committing Annex I Parties to individual, legally-binding targets to limit or reduce their greenhouse gas emissions.
To date most countries in the Pan-European region ratified the Kyoto Protocol, notably: Annex I: Belarus, Croatia, Russian Federation, Ukraine, EU 27, Norway, Iceland, Liechtenstien, Switzerland. Non-Annex I countries: Albania, Armenia, Azerbaijan, Bosnia and Herzegovina, Georgia, Kyrgyzstan, Kazhakhstan, Former Yugoslavian Republic Macedonia, Montenegro, Republic of Moldova, Serbia, Tajikistan, Turkey, Turkmenistan, and Uzbekistan.
31 countries and the EEC are required to reduce greenhouse gas emissions below levels specified for each of them in the treaty. Thefor Annex I Parties are listed in the Kyoto Protocol's Annex B. These add up to a total cut in greenhouse-gas emissions of at least 5% from 1990 levels in the commitment period 2008-2012.
The EU Commission's Progress Report towards achieving the Kyoto objectives in the EU and the individual Member States is required under the EU Greenhouse Gas Monitoring Mechanism (Council Decision 280/2004/EC concerning a mechanism for monitoring Community GHG emissions and for implementing the Kyoto Protocol).
Pan European level
The majority of the countries in the Pan European region and the EEC are required to reduce greenhouse gas emissions below levels specified for each of them in the Kyoto Protocol. The for Annex I Parties are listed in the Kyoto Protocol's Annex B. These should add up to a total cut in greenhouse-gas emissions of at least 5% from 1990 levels in the commitment period 2008-2012.
For the EU-15 Member States, the targets are those set out in Council Decision 2002/358EC in which Member States agreed that some countries would be allowed to increase their emissions, within limits, provided these are offset by reductions in others.
The EU-15 Kyoto Protocol target for 2008-2012 is a reduction of 8 % from 1990 levels for the basket of six greenhouse gases. For the new Member States, the candidate countries, other EEA member countries, and other Annex 1 countries the targets are included in the Kyoto Protocol.
Overview of national Kyoto targets (reduction from base year levels):
|Iceland||-10.0%||15 old EU Member |
Non-Annex I countries are not bound to such commitments and do not expect reduction of the GHG emissions.
The post 2012 climate regime will look different compared to Kyoto. In March 2007, the Council of the European Union decided that the EU would make a firm independent commitment to achieving at least a 20 % reduction of greenhouse gas emissions by 2020 compared to 1990. On 23 January 2008 the European Commission put forward a package of proposals that will deliver on the European Union's ambitious commitments to fight climate change and promote renewable energy up to 2020 and beyond. In December 2008 the European Parliament and Council reached an agreement on the package that will help transform Europe into a low-carbon economy and increase its energy security. The Package sets a number of targets for EU member states with the ambition to achieve the goal of limiting the rise in global average temperature to 2 degrees Celsius compared to pre-industrial times including: GHG reduction of 20% compared to 1990 by 2020 (under a satisfactory global climate agreement this could be scaled up to a 30% reduction); 20% reduction in energy consumption through improved energy efficiency, an increase in renewable energy's share to 20% and a 10% share for sustainably produced biofuels and other renewable fuels in transport.
Other related goals and targets:
- max global temperature rise of 2o (EC 6EAP and Councils), meaning global concentrations of less than 450 ppm CO2 equivalent
- for developed countries: 60 to 80% reductions in greenhouse gas emissions (2004 Environment Council)
- global CO2 emissions should decline after 2025, by as much as 50% of 1990 levels (EC 2006 Green paper on energy)
Related policy documents
- Climate and Energy package 2009
Council Decision (2002/358/EC) of 25 April 2002
Council Decision (2002/358/EC) of 25 April 2002 concerning the approval, on behalf of the European Community, of the Kyoto Protocol to the United Nations Framework Convention on Climate Change and the joint fulfilment of commitments thereunder.
Greenhouse gas monitoring mechanism
Decision No 280/2004/EC of the European Parliament and of the Council of 11 February 2004 concerning a mechanism for monitoring Community greenhouse gas emissions and for implementing the Kyoto Protocol
Kyoto Protocol to the UN Framework Convention on Climate Change
Kyoto Protocol to the United Nations Framework Convention on Climate Change; adopted at COP3 in Kyoto, Japan, on 11 December 1997
UN Framework Convention on Climate Change
United Nations Framework Convention on Climate Change
Methodology for indicator calculation
Projections of GHG emissions are produced can be calculated using the IMAGE Scenarios Model
Overview of the IMAGE Scenarios Model
The Integrated Model to Assess the Global Environment (IMAGE) developed by the National Institute for Public Health and the Environment (RIVM), is a dynamic integrated assessment modelling framework for global change. The main objectives of IMAGE are to contribute to scientific understanding and support decision-making by quantifying the relative importance of major processes and interactions in the society-biosphere-climate system. To accomplish this, IMAGE provides:
- dynamic and long-term perspectives on the systemic consequences of global change
- insights into the impacts of global change
- a quantitative basis for analyzing the relative effectiveness of various policy options to address global change.
Components of IMAGE 2.2
In the IMAGE 2.2 framework the general equilibrium economy model, WorldScan, and the population model, PHOENIX, feed the basic information on economic and demographic developments for 17 world regions into three linked subsystems:
- The Energy-Industry System (EIS), which calculates regional energy consumption, energy efficiency improvements, fuel substitution, supply and trade of fossil fuels and renewable energy technologies. On the basis of energy use and industrial production, EIS computes emissions of greenhouse gases (GHG), ozone precursors and acidifying compounds.
- The Terrestrial Environment System (TES), which computes land-use changes on the basis of regional consumption, production and trading of food, animal feed, fodder, grass and timber, with consideration of local climatic and terrain properties. TES computes emissions from land-use changes, natural ecosystems and agricultural production systems, and the exchange of CO2 between terrestrial ecosystems and the atmosphere.
- The Atmospheric Ocean System (AOS) calculates changes in atmospheric composition using the emissions and other factors in the EIS and TES, and by taking oceanic CO2 uptake and atmospheric chemistry into consideration. Subsequently, AOS computes changes in climatic properties by resolving the changes in radiative forcing caused by greenhouse gases, aerosols and oceanic heat transport.
Modelling approach of IMAGE 2.2
Historical data for the 1765-1995 period are used to initialise the carbon cycle and climate system. IMAGE 2.2 simulations cover the 1970-2100 period. Data for 1970-1995 are used to calibrate EIS and TES. Simulations up to the year 2100 are made on the basis of scenario assumptions on, for example, demography, food and energy consumption and technology and trade. Although IMAGE 2.2 is global in application, it performs many of its calculations either on a high-resolution terrestrial 0.5 by 0.5 degree grid (land use and land cover) or for 17 world regions (energy, trade and emissions).
Use of Scenarious
The objective of the IMAGE 2.2 model is to explore the long-term dynamics of global environmental change, in particular, dynamics related to climate change. This requires an image of how the world system could evolve. Future greenhouse gas emissions, for instance, are the result of complex interacting demographic, techno-economic, socio-cultural and political forces. Scenarios are alternative images of how the future might unfold. They form an appropriate tool in analyzing how driving forces may influence future emissions and in assessing the associated uncertainties.
Recently, the Intergovernmental Panel on Climate Change (IPCC) published a set of new scenarios in the Special Report on Emissions Scenarios (SRES) (IPCC, 2000). These scenarios are based on a thorough review of the literature, the development of narrative 'storylines' and the quantification of these storylines using six different integrated models from different countries.
This CD-ROM represents the IMAGE 2.2 elaboration of the SRES storylines. Contrary to the original SRES scenarios, the scenarios on this CD-ROM do not focus solely on emissions, but also describe the possible environmental impacts of these scenarios . It should, however, be clear that the scenarios on this CD-ROM represent only one of the many possible elaborations of the SRES scenarios. In this respect, they reflect the authors' interpretations and valuation of only a part of past and present events, behaviours and structures. So-called 'disaster' scenarios are not included and none of the scenarios include new explicit climate policies.
Summary of the scenarious presented in the table below:
Stabilizing population (9 billion in 2050)
Stabilizing population (9 billion in 2050)
Growing population (13.5 billion in 2100); slowdown in fertility decline with lower income
rowing population (10.5 billion in 2100); in some regions slowdown in fertility decline with lower income
lobalization, very high-growth high-tech
Globalization, high-growth high-tech
Focus on regional [cultural] identity; environment low-priority
Focus on regional [cultural] identity; local/regional environment high-priority; non-effective in global environmental issues
Market-based capital and labour allocation
Balanced government and market in [economic] development
Orientation on profits and [technological] opportunities
Orientation on non-material quality of life aspects.
No convergence in regional income and slow diffusion of technology; trade barriers
Orientation on non-material quality of life aspects. Varied regional economic and technology developments
Energy system dynamics
Decline in energy-intensity due to innovations and high capital turnover rate
Strong focus on energy efficiency and sufficiency, service economy.
Low rate of energy efficiency innovations, due to trade barriers and capital scarcity
Focus on energy efficiency and sufficiency, service economy.
Preference for clean fuels and fast depletion cause fossil fuel prices to rise. This enables efficiency and zero-carbon options to penetrate, accelerated by learning-by-doing
Large preference for clean fuels and depletion cause fossil fuel prices to rise. This further accelerates efficiency and zero-carbon options to penetrate, accelerated by learning-by-doing
Coal use rises in many regions: seen as cheapest available fuel as oil and gas become more expensive/ unavailable. initially capital-intensive zero-carbon options penetrate in most regions only slowly
Preference for clean fuels and depletion cause fossil fuel prices to rise in some regions, inducing efficiency and zero-carbon options to penetrate, accelerated by learning-by-doing
Food system dynamics
Fast increase in the volume of trade in food and feed
Fast increase in the volume of trade in food and feed
Moderate increase in the volume of trade in food and feed
Moderate increase in the volume of trade in food and feed
Fast increase in food and livestock productivity
Fast increase in food and livestock productivity with high efficiency of fertilizer use
Slow increase in crop and livestock productivity
Moderate increase in food and livestock productivity
Fast increase in per capita consumption of livestock products as a result of GDP increase
Per capita consumption of livestock products is 10% lower than in A1 scenario in 2050 and 20% lower than in A1 in 2100
Slow increase in per capita consumption of livestock products as a result of GDP increase
Moderate increase in per capita consumption of livestock products as a result of GDP increase
The IMAGE 2.2 elaboration of the SRES scenario narratives and assumptions described in detail by IPCC (2000) is found on the main disc.
Methodology for gap filling
Historical data for the 1765-1995 period are used to initialise the carbon cycle and climate system. IMAGE 2.2 simulations cover the 1970-2100 period. Data for 1970-1995 are used to calibrate EIS and TES. Simulations up to the year 2100 are made on the basis of scenario assumptions on, for example, demography, food and energy consumption and technology and trade. Models are used for projections and gap fillings.
No methodology references available.
EEA data references
- No datasets have been specified here.
External data references
- Input data to IMAGE 2.2. Scenarios - use of primary and secondary energy carriers and feedstock - output from TIMER model
- Input data to IMAGE 2.2. Scenarios - production of energy carriers - output from TIMER model
- Input data from IMAGE 2.2. Scenarios - Demand for modern and traditional biofuels - output of TIMER Model
- Output data from INAGE 2.2. Scenarios - Energy-related and industrial emissions of greenhouse gases and atmospheric pollutants - output from TIMER Emissions Module
- Input data to IMAGE 2.2. Scenarios - population - output of PHONEX model
- Input data to IMAGE 2.2. Scenarios - economic growth - output from WorldScan Model
- Input data to IMAGE 2.2. Scenarios - the potential distribution of natural vegetation and crops on the basis of climate conditions - output from TVM model
- Input data to IMAGE 2.2. Scenarios - demand for agricultural products (basic products, affluent products, feed products, wood products) - output from the Agricultural Economy Model (AEM
- Input data to IMAGE 2.2. Scenarios - updated land cover map (0.5 by 0.5 degree grid) - output from the Land-Cover Model (LCM)
Data sources in latest figures
Many unknowns and uncertainties in the climate system are not reflected in the IMAGE scenarios. Some of the major uncertainties in the causal chain are the climate sensitivity and regional climate-change patterns. The direct effects of a changed climate are changes in carbon uptake by the biosphere and oceans and in the distribution and productivity of crops, as well as shifts in ecosystems. Indirectly, many other processes are influenced, which can lead to the concentrations of greenhouse gases in the atmosphere being built up differently and to different land-use patterns. IMAGE simulates the consequences of these changes in an integrated fashion, accounting for interactions and feedbacks. The outcome is thus not necessarily a linear function of climate sensitivity.
These climate uncertainties were addressed by providing additional simulations to illustrate the uncertainty in the climate sensitivity and in the regional climate-change patterns.
Climate sensitivity refers to long-term (equilibrium) change in global mean surface temperature following a doubling of the atmospheric concentration in CO2 equivalents. According to IPCC, this climate sensitivity is between 1.5oC and 4.5oC. In earlier versions of IMAGE, the climate sensitivity generated by the climate model was 2.4oC. Due to the rigid structure of these earlier versions, we were unable to change this and assess the consequences of such a change.
In IMAGE 2.2 a simpler climate model MAGICC (see Upwelling-Diffusion Climate Model) is incorporated, allowing to define the climate sensitivity. The default value for IMAGE runs is 2.5, which is the median value of the IPCC range (median differs from mean because the range is logarithmic).
To test the uncertainty related to the climate sensitivity, runs with respectively a low (1.5oC) and high (4.5oC) climate sensitivity were created. A pattern-scaling procedure is used to obtain regional and seasonal climate-change patterns using the calculated increase in global mean temperature.
Runs with changed climate sensitivity are provided for the A1F (A1F low, A1F high) and B1 (B1 low, B1 high) scenarios on the main disc (IMAGE team 2001a). These scenarios span the full range of the SRES emission scenarios and therefore adequately illustrate the uncertainty of different climate sensitivities.
Regional climate-change patterns
Climate-change patterns are not simulated explicitly in IMAGE. The global mean temperature increase, as calculated by IMAGE, is linked with the climate patterns generated by a general circulation model (GCM) for the atmosphere and oceans. This linking takes place using the standardized IPCC pattern-scaling approach (Carter et al., 1994) and additional pattern-scaling for the climate response to sulphate aerosols forcing (Schlesinger et al., 2000; see Geographical Pattern Scaling, GPS). GCMs are currently the best tools available for simulating the physical processes that determine global climate dynamics and regional climate patterns.
GCMs simulate climate over a continuous global grid with a spatial resolution of a few hundred kilometres and a temporal resolution of less than an hour.
Most GCMs agree on the global patterns of climate change:
- temperature increases above land are faster than above the oceans
- high latitudes warm up more sharply than low latitudes
- winter warms up more sharply than summers
- total precipitation increases with increasing temperature
- maritime regions generally get wetter
- continental regions could get dryer.
Regionally, however, there are large differences between the different GCMs, especially in precipitation-change patterns.
IMAGE 2.2 runs with five different climate-change patterns are provided on the supplementary disc (IMAGE team 2001b, RIVM CD-ROM publication 481508019) for the A1F, B1 and A2 scenarios. The aim of this material is to illustrate the uncertainties in SRES climate-change scenarios resulting from these differences in GCMs. The first two scenarios span the full range of the SRES emission scenarios, the latter being based on a highly different narrative with different demographic and socio-economic assumptions. The three scenarios therefore adequately illustrate the uncertainty of different climate patterns. Differences in the runs for each scenario indicate some of the uncertainty caused by regional variation in climate-change patterns (not the global mean).
The scenarios for five different GCM runs from the IPCC data centre were implemented, which comprised:
- ECHAM4 of the Deutsches Klimarechenzentrum DKRZ in Germany
- CGCM1 of the Canadian Centre for Climate Modelling and Analysis in Canada
- GFDL-LR15-a of the Geophysical Fluid Dynamics Laboratory in the USA
- HADCM2 of the Hadley Centre for Climate Prediction and Research in the UK
- CSIRO-MK2 of Commonwealth Scientific and Industrial Research Organisation in Australia
Data sets uncertaintyDescription of the date sets uncertainties is not found in the reference documentation.
In common with all attempts to describe future trends, the energy projections and GHG projections in the Outlook are subject to a wide range of uncertainties. The reliability of projections depends both on how well the model represents reality and on the validity of the assumptions it works under.
Short term work
Work specified here requires to be completed within 1 year from now.
Long term work
Work specified here will require more than 1 year (from now) to be completed.
Responsibility and ownership
EEA Contact InfoAnita Pirc Velkavrh
Typology: Performance indicator (Type B - Does it matter?)
For references, please go to www.eea.europa.eu/soer or scan the QR code.
This briefing is part of the EEA's report The European Environment - State and Outlook 2015. The EEA is an official agency of the EU, tasked with providing information on Europe’s environment.
PDF generated on 01 Dec 2015, 10:52 PM