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This form is used for the policy intervention part of a model component. The infobox from the introduction page will be displayed here, with exception of the references. The page starts with a description of the baseline plus figure, followed by a table with policy interventions. The page ends with examples of policy interventions, text plus figures. The 'policy interventions' themselves must be entered separately via the Form:PolicyInterventionForm.
Description. Baseline and Policy intervention examples:
<div class="page_standard"> ==Baseline developments== In a baseline scenario, most greenhouse gas ({{abbrTemplate|GHG}}) emissions tend to increase, driven by an increase in underlying activity levels (This is shown in the figure below for a baseline scenario for the [[Roads from Rio+20 (2012) project|Rio+20]] study ([[PBL, 2012]]). Without climate policy, all non-CO<sub>2</sub> {{abbrTemplate|GHG}}s emissions are expected to increase towards the end of the century ([[Lucas et al., 2007]], Harmsen et al., [[Harmsen et al., 2019a|2019a]], [[Harmsen et al., 2019c|2019c]]). For air pollutants, the pattern also depends strongly on the assumptions on air pollution control. In most baseline scenarios, air pollutant emissions tend to decrease, or at least stabilize, in the coming decades as a result of more stringent environmental standards in high and middle income countries. {{DisplayPolicyInterventionFigureTemplate|{{#titleparts: {{PAGENAME}}|1}}|Baseline figure}} ==Policy interventions== A large variety of mitigation options exist or could be developed to abate emissions from each of the main non-CO<sub>2</sub> {{abbrTemplate|GHG}} emission sources. Lucas et al. (2007) followed by Harmsen et al. (2019c) described the development and application of sets of long-term non-CO<sub>2</sub> marginal abatement cost ({{abbrTemplate|MAC}}) curves of all major non-CO<sub>2</sub> GHG sources. These curves represent the mitigation potentials and costs of region- and source-specific mitigation measures. As such, they are used in the [[FAIR model|FAIR]] model to determine strategies and costs of comprehensive {{abbrTemplate|GHG}} mitigation strategies. The {{abbrTemplate|MAC}} curves have been developed using existing short-term {{abbrTemplate|MAC}} datasets as well as recent literature on emission source-specific mitigation measures. The new {{abbrTemplate|MAC}} curves include estimates of future technology development and removal of implementation barriers to capture long-term dynamics. The maximum reduction potential (MRP) of all non-CO<sub>2</sub> {{abbrTemplate|GHG}} measures is estimated at 71% in the year 2100. The MRP is the highest for F-gases ({{abbrTemplate|HFCs}}, {{abbrTemplate|PFCs}}, {{abbrTemplate|SF6}}), followed by followed by methane (CH<sub>4</sub>)(68%) and nitrous oxide (N<sub>2</sub>O)(62%)([[Harmsen et al., 2019c]]). Mitigation costs for most non-CO<sub>2</sub> {{abbrTemplate|GHG}} sources are lower than are lower than those of CO<sub>2</sub> mitigation, on average, but costs vary considerably by source. Note, however, that the mitigation potential of non-CO<sub>2</sub> measures is limited and that further mitigation would be far more costly and/or likely not possible. Mitigation of HFCs and CH<sub>4</sub> from fossil fuel sources can be considered very attractive, due to a large (in absolute terms), but relatively low-cost reduction potential. Policy scenarios present several ways to influence emission of air pollutants ([[Braspenning Radu et al., 2016]]): * Introduction of climate policy, which leads to systemic changes in the energy system (less combustion) and thus, indirectly to reduced emissions of air pollutants ([[Van Vuuren et al., 2006]]). * Policy interventions can be mimicked by introducing an alternative formulation of emission factors to the standard formulations ({{abbrTemplate|EKC}}, {{abbrTemplate|CLE}}). For instance, emission factors can be used to deliberately include maximum feasible reduction measures. * Policies may influence emission levels for several sources, for instance, by reducing consumption of meat products. By improving the efficiency of fertiliser use, emissions of N<sub>2</sub>O, NO and NH<sub>3</sub> can be decreased ([[Van Vuuren et al., 2011b]]). By increasing the amount of feed crops in the cattle rations, CH<sub>4</sub> emissions can be reduced. Production of crop types has a significant influence on emission levels of N<sub>2</sub>O, NO<sub>x</sub> and NH<sub>3</sub> from spreading manure and fertilisers. * Assumptions related to soil and nutrient management. The major factors are fertiliser type and mode of manure and fertiliser application. Some fertilisers cause higher emissions of N<sub>2</sub>O and NH<sub>3</sub> than others. Incorporating manure into soil lowers emissions compared to broadcasting. The impacts of more ambitious control policies ({{abbrTemplate|CLE}} versus {{abbrTemplate|EKC}}) on SO<sub>2</sub> and NO<sub>x</sub>, emissions, and the influence of climate policy are presented in the figure below. Where climate policy is particularly effective in reducing SO<sub>2</sub> emissions, air pollution control policies are effective in reducing NO<sub>x</sub> emissions. See also the Policy interventions Table below. {{DisplayPolicyInterventionFigureTemplate|{{#titleparts: {{PAGENAME}}|1}}|Policy intervention figure}} {{PIEffectOnComponentTemplate }} </div>
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