Details

The UK and Global Bioenergy Resource Model (2024), the background worksheets, user guide, and accompanying brief report, allow the user to estimate the potential bioenergy resource that the UK could access from both domestic and international sources in the period up to 2050 that meets user-set criteria for the feedstocks' upstream GHG requirements. 

In 2011, in preparation for the 2012 Bioenergy Strategy, a study by AEA Technology plc for DECC was published: the DECC: UK and Global Bioenergy Resource and Prices. This study used a model to estimate the potential bioenergy resource available to the UK from domestically sourced and imported feedstocks from 2010 to 2030. 

In 2017, BEIS (now DESNZ) commissioned Ricardo Energy & Environment to update, expand, and improve the UK and Global Bioenergy Resource Model. The model was restructured to improve user clarity for publication. A brief accompanying report documented the changes that were made to the model during this update compared to the 2011 version and explored the differences in results.   

In 2022, DESNZ commissioned a further revision from Ricardo Energy & Environment, to include: updated input data, new feedstocks, regional spatial availability within the UK, and estimates of carbon available for capture from combustion of the feedstocks.

Accompanying the UK and Global Bioenergy Resource Model, there is:

• a methodology report, which gives a description of the updated model, and how it functions to enable users to understand factors that affect the estimated quantity of bioenergy feedstocks available to the UK within the model.
• a user guide, which is more focused on the operation of the model.
• an external peer review, which was carried out on a draft version of the model by 3 independent academics. Those recommendations that were within scope are included in the published version. The report from the peer review process is included for context.
• a set of workbooks, provided as spreadsheets in a zip file, which offer supporting information on the underlying assumptions in the model.

Already have an account? Login