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Indicator Assessment
Under the IPCC scenarios the overall concentration of the six Kyoto gasses is projected to increase up to 638-1360 ppm CO2-equivalent by 2100, whereas the concentration of all GHGs may increase up to 608-1535 ppm CO2-equivalent. The global atmospheric GHG concentration of 450 ppm CO2-equivalent may be exceeded between 2015 and 2030.
The IPCC (2001, 2007a) showed various projected future greenhouse gas concentrations for the 21st century, varying due to a range of scenarios of socio-economic, technological and demographic developments (see Table 1). These scenarios assume no implementation of specific climate-driven policy measures. Under these scenarios, the overall concentration of the six Kyoto gasses is projected to increase up to 638-1360 ppm CO2-equivalent by 2100, whereas the concentration of all GHGs (incl. aerosols) may increase up to 608-1535 ppm CO2-equivalent by 2100.
The IPCC projections show that a global atmospheric GHG concentration of 450 ppm may exceeded between 2010-2015 (in case of Kyoto gasses only) or between 2020-2030 (all GHGs). A level of 550 ppm CO2-equivalent may become exceeded a decade later (Figure: on the figure are presented only baseline scenario and low emissions scenario). Substantial global emission reductions are therefore needed to remain below these targets or return back to these levels after an overshoot.
Table: Projected changes in atmospheric GHG concentration (considering either Kyoto gasses only or all GHGs)
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| A1B | A1T | A1FI | A2 | B1 | B2 |
Kyoto only | 2020 | 489 | 478 | 484 | 484 | 475 | 470 |
| 2050 | 645 | 613 | 707 | 653 | 571 | 575 |
| 2100 | 877 | 722 | 1360 | 1196 | 638 | 800 |
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all GHGs | 2020 | 416 | 442 | 417 | 407 | 416 | 432 |
| 2050 | 605 | 622 | 686 | 575 | 515 | 555 |
| 2100 | 861 | 717 | 1535 | 1256 | 608 | 808 |
Source: IPCC, 2001, 2007a
1Defined as >95% probability (IPCC, 2007)
22008 concentration levels are yet not available for the other greenhouse gasses.
Definition: The indicator shows the measured trends and projections of greenhouse gas concentrations. The various greenhouse gases have been grouped in three different ways. In all cases the effect of greenhouse gas concentrations on the enhanced greenhouse effect is presented as CO2-equivalent concentration. Global annual averages are considered.
Model used: IMAGE
Ownership: European Environment Agency
Temporal coverage: 2000 - 2100
Geographical coverage: global
Over a decade ago, most countries joined an international treaty -- the United Nations Framework Convention on Climate Change (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 Kyoto Protocol. 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.
The indicator is aimed at supporting assessment of progress towards the EU long-term target to limit global temperature increase to below 2 degrees C above pre-industrial levels, and, derived from this, stabilisation of GHG concentrations at well below 450 ppm CO2-equivalent (
EECCA policy context
There are no specific policies concerning atmospheric greenhouse gas concentrations in this region. However, in EECCA Environmental Strategy reduction of GHGs are defined as one of the aims.
no targets were set at this subregional level
The concentrations are calculated in the Atmospheric Chemistry Model (ACM) of IMAGE 2.2 on the basis of the emissions generated by the TIMER emissions model (TEM) and Land Use Emissions Model (LUEM). The global mean concentrations are used as input of the Upwelling-Diffusion Climate Model (UDCM) of IMAGE 2.2. The AEA technology approach was used for methane.
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 modeling 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:
More detailed description of the IMAGE model can be found here.
The IMAGE model has a range of submodels which calculate different parameters for the model. Therefore, GHG's concentrations are included in the Atmospheric Chemistry Model (ACM).
Thus the change in concentrations depends on the change in both emissions and the atmospheric removal, determined by its atmospheric lifetime. However, for N2O, CCl3, the CFCs, bromocarbons and PFCs, the chemical lifetime is assumed constant, as adopted in most simple climate models currently used ( Harvey et al., 1997). The calculation of the CO concentration is slightly modified from the approach used in IMAGE 2.0 (Krol and Van der Woerd, 1994). On the basis of recent literature, the CO yield factor for NMVOC emissions is 0.4; the lifetime of CO due to soil uptake and stratospheric loss is 1.10 year ( M?and Brasseur, 1995).
ACM covers such kinds of emissions and their further concentrations as:
to be included
Baseline scenario
The baseline scenario follows a conventional definition and expands on current expectations regarding macro-economic, sectoral, technological and societal developments, as well as including those policies that have been implemented and/or adopted, which typically refer to pieces of legislation such as EU directives or political agreements.
EEA's outlooks across the various sectors and themes use a common reference set of assumptions for the key driving forces to ensure consistency across the board and facilitate cross-cutting analysis. This reference set builds on the socio-economic assumptions developed for the DG TREN baseline projections 'European energy and transport trends to 2030', which are also being used within the Clean Air for Europe (CAFE, DG ENV) programme. Within this framework, assumptions have been developed as a consistent set and cover the following key driving forces:
Population:
The European population is expected to stabilize, but gradually to become an ageing society. Main demographical trends are presented in the Table 1.
Population (millions) | ||||
Year | EEA - 31 | EU - 25 | EU - 15 | New - 10 |
1990 | 540 | 441 | 366 | 75 |
2000 | 563 | 453 | 379 | 75 |
2010 | 586 | 461 | 388 | 73 |
2020 | 586 | 462 | 390 | 72 |
2030 | 587 | 458 | 389 | 69 |
Average annual growth rates (%) | ||||
1990 -2000 | 0.4 | 0.3 | 0.3 | -0.1 |
1990 -2030 | 0.2 | 0.1 | 0.2 | -0.2 |
The age distribution in the EU is a growing concern, particularlyin connection with pension and health expenditure and working life-time. While the accession of the 10 new Member States in 2004 has somewhat rejuvenated the EU population, it failed to reserve the trend of increasing old age dependency from 30% in the 1960s to 39% today in the EU-25.
This trend is expected to continue over the 2000-2030 period, with the share of people of 65 years and older in the total population increasing from 15% to 25% in the EU-15, and from 10% to 22% in the New-10.
The macro-economic assumptions.
The macro-economic assumptions for Europe are moderately optimisticand entail challengingtrade-offs in light of achieving sustainableeconomic development. Average annual economic growth in the EU is expected to be 2.4% and 3.5% in the New-10.
GDP assumptions are presented in the table 2.
GDP per capita (1000 Euro, year 2000) | ||||
Year | EEA - 31 | EU - 25 | EU - 15 | New - 10 |
2000 | 17.1 | 19.7 | 22.6 | 5.3 |
2010 | 21.3 | 24.8 | 28.0 | 7.8 |
2020 | 26.9 | 31.3 | 34.9 | 11.5 |
2030 | 33.7 | 39.3 | 43.5 | 15.9 |
Average annual growth rates (%) | ||||
2000-2010 | 2.5 | 2.5 | 2.4 | 3.8 |
2010-2020 | 2.5 | 2.4 | 2.3 | 3.6 |
2020-2030 | 2.3 | 2.2 | 2.2 | 3.0 |
2000-2030 | 2.4 | 2.4 | 2.3 | 3.5 |
Technological developments:
Technological progress is moderate but essential in key area such as energy, agriculture and water, but no technological breakthroughs are assumed.
More detailed information concerning technology can be found in the European Environment Outlook N4/2005 (pp. 22-23).
Sectoral developments
The service sector is expectedto retain its predominance in the European economy and be instrumental insustaing economic growth. The baseline scenario uses specific technological assumptions at the sectoral level, which directly affect most of European environmental concerns. The explanationsof such asumptions are available in the European Environment Outlook N4/2005 (pp. 23-24).
The scenario has been developed as an alternative scenario, which aims at identifying the implications of the EU's long term sustainable objective as stated in the 6th EAP for future GHG patterns, sectoral developments and the costs of policies. The scenario bears similarities with current initiatives, studies and political debate across the EU for far-reaching climate change policies.
One of the main assumptions are shifts induced by the low GHG emissions scenario. It is concerning the power generation sector in terms of fuel inputs. In particular, the share of solids is significantly reduced, and there is a greater deployment of renewables.
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.
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
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:
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:
Atmospheric concentrations of greenhouse gases are a well-established indicator of changes in atmospheric composition, which causes changes of the global climate system. To answer the key question of the indicator (will GHG concentrations stay within sustainable limits) it is not enough to know only current concentration trends - projection techniques should be applied to warn on early stages how the situation is developing.
For references, please go to https://www.eea.europa.eu/data-and-maps/indicators/ghg-concentrations-outlook-from-mnp/ghg-concentrations-outlook-from-mnp or scan the QR code.
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