Develop BAU

From Open Energy Information

Stage 3

Previous Step Next Step

3a Analytical Decision Making - Developing a Business as Usual (BAU) Scenario
3a.1 Develop common vision of "no action" scenario through 2050

 
Good Practices for BAU Projections

  • Economy-wide and sectoral BAU projections developed to at least 2030
  • Sensitivity analyses performed for BAU projections
  • Detailed enough to inform evaluation of LED options
  • Credible enough to serve as basis for investment and offset projects
  • Documentation of data sources and modeling assumptions provided
  • Can be validated by third party
  • Publicly available for comment
  • Process for incorporating comments and iteration

At this stage the technical team and stakeholder group can develop a "no action" scenario incorporating the data and projections for economy and development, energy demand and supply, land use, GHG emissions and future climate conditions collected in the previous Module 2.

  • Ideally, as a starting point, the country will have a GHG emission inventory from which to develop a "no action" scenario for GHG emissions. Where sufficient GHG inventory data do not exist, capacity building may be necessary to develop these data before projections can be made. The tools in the Stage 2 GHG Inventory Development Toolkit can be used to support the development of a GHG emissions inventory.

 
Questions

What datasets and tools might be helpful for calculating my country’s baseline projections for the economy and development, energy, land-use, emissions, and climate conditions?

Lessons Learned and Good Practice Resources

Click here to view resources

Data Resources for BAU Projection

Click here to view resources

Software Tools

Click here to view resources

All Resources

Click here to view resources


3a.2.1. Review existing scenarios and data used

Land-use sectors

The stakeholder group can establish one or more baseline reference scenarios for landscapes to describe the emissions expected in the absence of a low-emissions development strategy. This business-as-usual should be based on historic landscape-based emissions, adjusted, as appropriate, to include projections to 2050 for the economy, development (e.g., income, access to improved water sources), land use, forest cover change, agricultural expansion and carbon emissions. Reference scenarios for landscapes require information on land cover change and the carbon content of different land cover and land uses.

It may not be possible to definitively choose one reference scenario in the absence of UNFCCC-negotiated guidelines and processes. Until that is clarified, it may be necessary to create a set of different scenarios that vary depending on assumptions related to the projected effect of existing policy reforms and on which future reforms would or would not have happened in absence of LEDS. Different assumptions of future market demand will also strongly affect the reference scenario, as will the base year(s) chosen.

Reliable estimates of land cover change and carbon inventories of different land uses and land cover types require in-depth studies and are not available in many countries. As a result, many countries will not have the data necessary to establish credible reference scenarios. Countries that have already initiated REDD+ readiness activities will have begun work to determine a reference scenario for emissions from deforestation and forest degradation. The scoping and planning step of this framework will determine how far along a county is in developing a reference scenario and if the necessary data exists. In the absence of robust data on landscape-based emissions, coarse estimates of historic land cover change can be approximated by widely available remote sensing data coupled with default carbon stock factors. In these cases, improving the carbon inventory and land cover data will be part of the LEDS plan, and the reference scenario will be continually refined as better data is available.

As with many steps in this framework, determining a reference scenario requires integrating technical assistance into a political process and highlighting the need for stakeholder buy-in, especially by national leaders.

3a.2.2. Create and refine new BAU pathway(s) out to 2050
3a.2.3. Document assumptions and data used in models
3a.2.4. Share results with stakeholder groups for information and feedback