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Published on Climate Planning (http://www.climateplanning.org) CLIMATE PLANNING Climate Compatible Development Tools: A guide for national planning McKinsey GHG abatement cost curve Identifying options for climate change mitigation and calculation of mitigation costs POLICY STAGES: 1. Awareness raising, 2. Problem Definition, 3. Identification of options Assessment of mitigation / resource potential Assess broad mitigation options such as CO2 emissions reduction and renewable energy resource potentials such McKinsey & Company’s GHG abatement cost curve tool provides as wind energy. information on the abatement potential, cost and required investment of over 200 mitigation options with the possibility of various levels of granularity. The cost curve presents the technical potential of emissions abatement per specific mitigation option and the associated cost per tCO2e saved, taking into account the required up-front investments and associated operating costs of each option. A national or regional cost curve is developed in a project with McKinsey with the involvement of a high number of local stakeholders and experts. Each project includes substantial awareness raising and capacity building on mitigation. McKinsey’s Climate Desk is a web-based subscription service for the global GHG abatement cost curve. Over 100 academics and other experts have been granted a free license to the tool. AREA OF FOCUS Published by: Requirements McKinsey & Company [email protected] http://www.mckinsey.com Training: Special training is required that will take 8 days or more. USD$2000+ Location: Costs: Using the tool: USD$2000+ Time needed: 2-4 months Accessing the tool For global use Availablility: Online: Global Assessment: Online via Climate Desk; national GHG project only via McKinsey Languages: English Contact: Sebastian Schienle http://solutions.mckinsey.com/climatedesk . This guide was commissioned by the Climate and Development Knowldge Network (CDKN). Content is jointly managed and developed by Ecofys and IDS Read more Take our user survey