Atmospheric composition and climate/Policy issues

Component is implemented in:

MAGICC model (version IMAGE-MAGICC 6.3) Components: Atmospheric composition and climate

Related IMAGE components

Air pollution and energy policies Carbon cycle and natural vegetation Climate policy Crops and grass Emissions Human development Land and biodiversity policies Nutrients Water

Projects/Applications

Representative Concentration Pathways - RCP (2009)

Models/Databases

AR4 (IPCC) database LPJmL model

Key publications

Meinshausen et al., 2011b Müller et al., 2016b Van Vuuren and Stehfest, 2013

References

Overmars et al., 2014 Shindell et al., 2012 Van Vuuren and Stehfest, 2013

Flowchart Atmospheric composition and climate. See also the Input/Output Table on the introduction page.

Baseline developments

In baseline scenarios, emissions and greenhouse gas concentrations increase substantially. The increase in emissions depends on socio-economic factors, such as population growth, economic growth, technology development and lifestyle. Most medium baseline scenarios in IMAGE result in a rise in global mean temperature of about 3 to 5 °C above pre-industrial levels by 2100 (the figure below).

In the policy scenarios, emissions decrease strongly after 2020, while concentration levels only decrease or stabilise after 2050. Global mean temperature, due to inertia in the climate system, will not stabilise until the end of this century under the most ambitious climate policy scenario (2.6 W/m²).

Policy interventions

Policy interventions that affect future climate range from policy on energy and agricultural systems, air pollution measures, and land-use policies to direct management of radiative forcing. For instance, the IMAGE system can be used to analyse energy efficiency, use of low-carbon fuels, reduction in non-CO₂ greenhouse gas emissions and reduction of deforestation (Overmars et al., accepted). Interventions related to policies on climate, air pollution and land use are described in Componens Climate policy, Air pollution and energy policies and Land and biodiversity policies, respectively. These measures lead to a change in emissions, and then to the expected reduction in radiative forcing and climate change.

The slow temporal dynamics of the climate system play an important role in climate policy assessments. IMAGE calculations show considerable time lag between policy introduction and impacts on climate change. Even if emissions were substantially reduced from 2020 and onwards, several decades would elapse before stabilization in temperature in the global climate system is observed (the figure above). In addition to these standard climate measures, a range of policy interventions may play a role in the temporal dynamics of the climate system, and may be analysed using the IMAGE system:

• Mitigation in short-lived versus long-lived greenhouse gas emissions, and co-benefits with air pollution measures (Shindell et al., 2012). Short-term benefits in air quality and climate mitigation may be achieved by reducing black carbon emissions and ozone precursors.
• Non-mitigation management of global radiative forcing, such as by means of geo-engineering as shown in the figure below (Van Vuuren and Stehfest, 2013).

In addition to ‘conventional’ climate policy, there may be situations where urgent action on climate change is required, either via rapid mitigation, or via Solar Radiation Management (SRM) (e.g. sulphur emissions to the stratosphere). Radiative forcing is immediately stabilised at the intended level by SRM, and also temperatures are adjusted immediately (though not yet at the equilibrium level), and even faster under extreme SRM than would be possible through strong mitigation. However, substantial uncertainties and risks are related to such drastic manipulations of the radiation balance.