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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== The model shows that under a typical baseline scenario such as the one of the [[Roads from Rio+20 (2012) project|Rio+20]] study, energy demand is projected to grow significantly during the 21st century. Most growth will be driven by an increase in energy use in low-income countries. Per capita use in high-income countries is projected to remain more or less constant, consistent with recent historical trends. The increase in energy demand in the first half of the century will be mostly met by fossil fuels and electricity. In this model simulation, hydrogen becomes competitive in the transport sector in the second half of the century, as a result of increasing oil prices and the assumed progress in hydrogen technologies. An alternative assumption could result in a similar role for electricity. {{DisplayPolicyInterventionFigureTemplate|{{#titleparts: {{PAGENAME}}|1}}|Baseline figure}} ==Policy interventions== Various policy interventions can be implemented in the energy demand submodules in different ways (see also the Policy interventions Table below): * Energy tax and carbon tax. This changes the prices for the energy carriers influences the choice of technology. * Discount rate/payback time. In the residential submodule , the perceived costs of capital (discount rate) influence the extent of energy efficiency improvement (PIEEI) and the choice of fuel and/or technology in the residential submodule. * Preferences. Fuel choice can be influenced by correction factors, representing aspects that influence fuel choice but are not incorporated in the price, such as fuel characteristics (e.g., cleanliness, availability), comfort and speed considerations, and infrastructure. * Efficiency standards. Such improvements can be introduced for the submodules that focus on specific technologies, for example, in transport, heavy industry and households. * Enforced market shares of fuel types. Such an analysis could, for instance, provide insight into the implications in the model of increasing the use of biofuels, electricity or hydrogen ([[Van Ruijven et al., 2007]]). {{PIEffectOnComponentTemplate }} </div>
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