Climate policy/Policy issues

2019-03-05T14:33:25Z

Hofa:

Climate policy/Policy issues

2019-03-05T14:31:51Z

Hofa:

{{ComponentPolicyIssueTemplate
|Reference=Den Elzen et al., 2007; Den Elzen and van Vuuren, 2007; Van Vuuren et al., 2011a; Van Vuuren et al., 2012; European Commission, 2010; Den Elzen et al., 2012b; Den Elzen et al., 2011b; UNEP, 2012; Hof et al., 2013; Höhne et al., 2012; Roelfsema et al., 2013; Roelfsema et al., 2014; Den Elzen and Höhne, 2010; Den Elzen et al., 2012a; Hof et al., 2012; Mendoza Beltrán et al., 2011; Hof et al., 2011; Hof et al., 2008; Hof et al., 2010; Den Elzen et al., 2012c; Van Vliet et al., 2012; Admiraal et al., 2016; Van den Berg et al., 2015; Harmsen et al. (2016); UNEP (2016); Rogelj et al., 2016; Den Elzen et al., 2015a; Kuramochi et al., 2016; Hof et al., 2016;
}}

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==Policy analyses==
[[FAIR model|FAIR]] can be used to analyse baseline developments, such as expected climate change damage. However, more often baseline developments are explored using the larger IMAGE framework, and the FAIR model receives this information as input for policy analysis.

As part of the IMAGE framework, FAIR can be used to evaluate a range of policies and strategies, including:

* Long-term mitigation strategies such as emission reductions over time ([[Van Vliet et al., 2012]]);

* Evaluation of current reduction proposals by countries and policy options until 2030 ([[Den Elzen et al., 2016]]; [[Den Elzen et al., 2019]]);

* Evaluation of domestic climate and energy policies up to 2030 ([[Kuramochi et al., 2016]]; [[Kuramochi et al., 2018]]; [[Roelfsema et al., 2018]]);

* Evaluation of burden sharing or effort sharing regimes ([[Den Elzen et al., 2012a]]; [[Hof et al., 2012]]; [[Hof et al., 2016]]; [[Van den Berg, 2019]]);

* Analysis of regional abatement costs and emission trading ([[Den Elzen et al., 2008]]; [[Den Elzen et al., 2011a]]; [[Mendoza Beltrán et al., 2011]]; [[Hof et al., 2017]]);

* Evaluation of proposals for financing climate policies ([[Hof et al., 2009]]; [[Hof et al., 2011|2011]]);

* Evaluation of trade-offs between mitigation costs, adaptation costs and the benefits of reduced climate damage ([[Hof et al., 2008]]; [[Hof et al., 2009|2009]]; [[Hof et al., 2010|2010]]; [[Admiraal et al., 2016]]);

* Assessment of the policy costs, emission profiles and climate effects resulting from the use of different climate metrics such as the {{abbrTemplate|GWP}} ([[Van den Berg et al., 2015]]; [[Harmsen et al. (2016)]]);

==Policy interventions==

[!CHANGE]The Global Pathfinder module FAIR-SiMCaP was used to determine what the pledges for 2020 and the {{abbrTemplate|INDC}} targets (mainly for 2030) imply for global emission pathways consistent with meeting the 2 °C target ([[Hof et al., 2016]]; [[Van Vliet et al., 2012]]). The mitigation costs module has been applied to compare the mitigation costs for 2030 resulting from implementation of the NDCs with reductions required for achieving the climate targets of the Paris Agreement ([[Hof et al., 2017]]). The main findings of these studies were as follows (see also the figure below):
* The global 2030 emission level resulting from implementation of the NDCs exceeds those of least-cost pathways that achieve a 2 °C target;
* Slightly postponing mitigation action compared to the least-cost scenario seems technically feasible but at higher cumulative discounted mitigation costs;
*A delay in emission reductions limits the flexibility in the portfolio of emission reduction options. Such delayed scenarios rely more on the use of bioenergy with carbon capture and storage ({{abbrTemplate|BECCS}}), an option with uncertain prospects for large-scale implementation.
*Abatement costs are very sensitive to socioeconomic developments: with slow economic growth rapid population growth, and high inequality, mitigation costs of achieving all unconditional NDCs are estimated at USD 135 billion in 2030 - which is more than twice the level as under more sustainable socioeconomic developments.
*Allowing emission trading could decrease the global costs of achieving the NDC targets considerably by about 50%.
*The required effort in terms of mitigation costs of achieving 2030 emission levels consistent with 2°C pathways is about three times higher than the costs of achieving the conditional NDCs.

{{DisplayFigureTemplate|002g ind16_CP}}[[File:002g ind16.png|thumb|Regional and global abatement costs for NDCs]]

[!CHANGE]

{{PIEffectOnComponentTemplate }}
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2019-03-05T09:49:33Z

Hofa:

{{ComponentTemplate2
|IMAGEComponent=Drivers; Emissions; Energy supply; Energy conversion; Energy supply and demand; Carbon, vegetation, agriculture and water; Atmospheric composition and climate;
|Model-Database=MAGICC model; AD RICE model; TIMER model; POLES model; Enerdata Global Energy & CO2 Data; IIASA database;
|KeyReference=Den Elzen et al., 2011a; Den Elzen et al., 2008; Hof et al., 2009; Van Vliet et al., 2009;
|Reference=UNFCCC (2015); UNFCCC (2015b); UNEP (2016); Rogelj et al., 2016; Den Elzen et al., 2015a; Kuramochi et al., 2016; Hof et al., 2016;
|InputVar=Population; GDP per capita; CO2 emission from energy and industry; CO and NMVOC emissions; Non-CO2 GHG emissions (CH4, N2O and Halocarbons); Marginal abatement cost; Climate target; Domestic climate policy; Marginal abatement costs; BC, OC and NOx emissions; SO2 emissions; Land-use CO2 emissions - grid; Equity principles; Adaptation level; Investment and Capital Stock
|Parameter=Other energy and land-use models;
|OutputVar=Carbon price; Emission abatement; Global emission pathways; Mitigation costs; Emission trading; Consumption loss; Adaptation costs; Residual damage;
|ComponentCode=CP
|FrameworkElementType=response component
|AggregatedComponent=Policy responses
}}
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==Introduction==
With the 2015 Paris Agreement, all Parties to the United Nations Framework Convention on Climate Change (UNFCCC) have agreed to limit global warming to 2 °C compared to pre-industrial levels and to pursue efforts to further limit this increase to a maximum of 1.5 °C [[UNFCCC (2015b)]].

To achieve this goal, countries have proposed short- and long-term reduction targets in the {{abbrTemplate|UNFCCC}} climate negotiating process and in domestic policies. To support climate policymakers, the IMAGE model is used in conjunction with the climate policy model [[FAIR model|FAIR]]. FAIR is a decision support tool to analyse the costs, benefits, and climate effects of mitigation regimes, emission reduction commitments, and climate policies.

FAIR can work in stand-alone mode using exogenous data, but in recent applications it interacts with several IMAGE components. For instance, mitigation cost curves for the energy sector are derived from the [[Energy supply and demand|Energy Supply and Demand model TIMER]] and land-use mitigation options from [[Agriculture and land use|Agriculture and Land Use]]. Data from FAIR on marginal abatement costs and reduction efforts per sector and greenhouse gases are used as input for IMAGE to evaluate the impacts under different assumptions for climate mitigation.

FAIR in combination with IMAGE can analyse the interaction between long-term climate targets and short-term regional emission targets. Regional targets are based on effort-sharing approaches and/or national emission reduction proposals, taking into account decisions on accounting rules as agreed under the {{abbrTemplate|UNFCCC}}. The central purposes of the model are the calculation of mitigation costs and trade in emission allowances, and the net mitigation costs of a region to achieve its mitigation target. FAIR enables evaluation of proposed effort-sharing regimes, including differentiated timing and participation of a limited number of parties to the climate convention. Furthermore, FAIR analyses the trade-offs between costs and benefits of mitigation and adaptation policy.

{{InputOutputParameterTemplate}}
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Investment and Capital Stock

2019-03-05T09:45:30Z

Hofa: Investment and Capital Stock database as input for cost-benefit module FAIR

{{VariableTemplate
|Label=IMF Investment and Capital Stock
|Dimension=time, region
|Unit=2005 international dollars
|VariableType=external parameter
|Source2=IMF
|BasedOn2=IMF database
|Reference2=http://data.imf.org/?sk=1CE8A55F-CFA7-4BC0-BCE2-256EE65AC0E4
}}