Key concepts

There are four concepts important for understanding of the essence of the Tool:

MRV - Measurable, Reportable & Verifiable parameters under which the mitigation actions should be 
undertaken. For the first time this concept was introduced in 2007 Bali Action Plan. 

Tool is a platform to structure, organize and analyze data taking into account a certain analytical goal 

Baseline is an imaginary line, standard of value, which is used for measurement or comparison 

‘Futureline’ is an expected or supposed sequence of events in the future under certain (defined) 
While the baseline aims at presenting the current state, the futureline aims at depicting one of the possible futures. Both baselines & futurelines depend on certain assumptions and input data. This way multiple baselines & futurelines can become possible. Therefore, it is necessary to develop (and agree on) a common methodology, which can be used for the baseline assessment under different settings. Such settings can include national level, regional level or city activities.


The CCM2.0 can be used for estimating energy use and related GHG emissions for the building sector of any region, country, city, as well as for a smaller portfolio of similar buildings.
The tool covers five end-uses: space heating, space cooling, water heating, lighting and appliances. Main focus will however be on space heating, water heating and space cooling as lighting and appliances.

Different end-uses have different opportunities for splitting energy use and emissions estimations by types of the buildings and/or equipment, depending on the user’s priorities and/or data availability. 
For example, for space heating, cooling and water heating it is possible to distinguish among different levels of building energy performance, new and existing buildings, climate zones (CCM2.0 uses the Koppen Classification System), residential and commercial buildings, as well as various building sub-categories. For lighting it is possible to take into account a number of lamps types, which can be used in different types of building.

Calculation Methodology

The CCM2.0 uses a three step approach to establishing building energy use and associated GHG emissions base-lines and mitigation scenarios.
Step 1: Establish baselines
Step 2: Develop future line scenarios
Step 3: Analyze and compare results

Assuming you have all required data assembled, an assessment using the CCM2.0 should take no longer than one hour to complete. Where no measured data exists, please provide an estimate for all required data fields, noting these data as estimates in the Data Source column. Please do not leave fields blank or enter zero (0) in any required fields.

Step 1: Establish Baselines

The tool is based on a calculation methodology that conforms to ‘measurable, reportable and verifiable (MRV)’ data standards. It offers three ways of generating energy use and GHG emissions base lines for a stock of buildings (top-down, bottom-up and hybrid).

This approach is useful if you only have access to aggregated building energy use data such as national, regional or municipal statistics on residential and/or non-residential energy-use.  This approach requires information on the total building stock, total energy use and shares of different building types in the total energy use of the building sector. This approach is mostly useful, when the assessment has to be done on a large scale (e.g. country) and there is a lack of detailed data on that level. The tool guides you through a simple step-by-step process to disaggregate this data to generate MRV emissions base line by building type.

This approach is useful if you have more detailed measured energy use data from a representative sample of buildings in your building stock. You will be able to build-up an MRV baseline by entering more detailed energy data from individual buildings in different categories of building types – such as single or multi-family residential, commercial, hospitals etc.  This approach focuses on (one or several) individual buildings and requires information on floor area 
and, total energy consumption in kWh and fuel mix for each particular building. Bottom-up approach can be applied as well, if all required data can be found for representative case studies, typical buildings or assumed averages. It also allows for utilizing experts' judgments (e.g. regarding specific energy consumption values) in case measured data are impossible to obtain.

The Bottom-up approach is very useful for a certain (limited) group of buildings and/or for a concrete mitigation project, but can be less useful for establishment of a national baseline or Business as Usual (BAU). 

Hybrid Approach:
This approach requires information on total floor area and, most importantly, specific energy consumption in kWh/m2, which allows for calculating total energy use for different end-uses, building types, climate zones, etc. at the level of a region, country or city. The Hybrid approach can be use on a smaller scale, when it is important to analyze different influences on energy use and GHG emissions (e.g. in different building types or climate zones), or in cases where there is a lack of data and need for detailed assessment on larger scales (country, region, etc.) 

Step 2: Establish ‘Future line’ Scenarios

‘Futureline’ analysis follows the same steps to make estimations for the first (‘base’) year, however, as future-line analysis also includes estimations for the future, it requires data for more parameters such as renovation rates, changes in occupancy, new construction rates, and includes additional calculations to enable projection of future energy demand and emissions.

The CCM2.0 Tool will guide you through the input date required in the futurelines sections. The data requirements for futurelines change depending on whether you are working in top-down, bottom-up or hybrid modes. You must calculate a baseline before you can begin working on futurelines for a particular project or jurisdiction.

Step 3: Analyse and Compare

Once you have established a baseline, you can generate comparisons of base-line and futureline scenarios and generate results in graphic or table formats. These outputs can be used to support policy recommendations, roadmaps and applications for climate finance.