EnerFuture MACCs - Marginal Abatement Cost Curves

What is the future CO2 emissions reduction potentials and what are their costs across economic sectors?  Leveraging Enerdata’s 30 year expertise in this field and the globally recognised POLES forecasting model, Enerdata provides a unique online service offering instantaneous access to long-term MAC Curves. Download brochure 12-month subscription service in web access

The Marginal Abatement Cost Curves (MACCs) provide for a given year, a given country and a given sector the different levels of emissions reductions that can be reached for different carbon price levels. They are derived from a fully explicit baseline scenario.

The MACCs are a very powerful tool that is used by policy makers, researchers, business analysts to assess climate policies, evaluate their cost and their efficiency, simulate carbon markets such as the EU ETS … On a MAC Curve, the x-axis represents the emissions reduction, the y-axis the associated carbon value and the area under the curve the total abatement cost. The MACCs in the Enerfuture Service are generated with the POLES-Enerdata model, they are available for 6 years (2015, 2020, 2025, 2030, 2040 and 2050), 65 countries/regions, 31 sectors and two contrasted baseline scenarios.

• Long-term Marginal Abatement Cost Curves (2015, 2020, 2025, 2030, 2040 and 2050)
• Output data: projected CO2 reduction according to carbon value
• 65 countries & regions covered
• CO2 emissions by large sector: power, industry, transport, residential-services, total CO2
• Sector breakdown available (optional): energy, industry combustion, industry process, residential-services, transport
• Other GHGs – energy and industry sources (optional): CH4, N2O, SF6, HFC, PFC
• A set of 2 scenarios: Recovery & Depression
• MACCs generated by the globally recognised POLES-Enerdata energy forecasting model

• Unique! Access MACCs instantaneously in a couple of clicks
• Get data and insight from one of the only recognised MACCs experts worldwide
• Benefit from the robust and reliable POLES model

• 24/7 online access
• Interface in English language
• Modelling methodology made explicit
• Communication of the set of assumptions by scenario
• Bi-annual updates
• Access to Enerdata experts for data support

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