Greenhouse Gas Removal
Calculating how to optimise siting bioenergy with carbon capture and storage facilities. Manchester experts have created a model to calculate the full-chain transportation carbon costs of operating carbon capture and storage (BECCS) at any location in the UK.
BECCS has the potential to deliver cost-effective greenhouse gas removal at scale and could be crucial to helping the UK meet net zero targets.
The UK is rich in a wide array of biomass sources ranging from forestry, agricultural residues and industrial wastes. However, until now, there has been no clear picture of where these potential sources lie and how to measure the economic and environmental impact of the transportation and storage process.
Understanding biomass’s potential in the UK
Manchester experts, Dr Muir Freer, Dr Amanda Lea-Langton, Dr Andrew Welfle and Dr Clair Gough, have created a tool that enables policymakers and industry to calculate this and aid decision-making, by providing – for the first time – the end-toend carbon costs of the transport involved in BECCS supply chains.
Manchester experts worked on two key elements:
Firstly, they undertook high spatial resolution biomass mapping to identify the UK’s entire biomass resource distributions from waste and residue products. With competition for land fierce, making growing biomass-specific crops expensive, the team documented everything from food waste to wood residues and animal by-products along with the volumes available, and presented in user-friendly 3D spike maps, enabling users to quickly locate the areas rich in abundant and more affordable biomass.
Secondly, the team created a digital twin model that maps all the transportation networks across the BECCS supply chain (including biomass, CO2 and any energy output), acting as a virtual version of the UK’s transport network, called the Carbon Navigation System (CNS) model.
From this, the high spatial resolution biomass data is plugged into the CNS model, which allows the simulation of entire BECCS supply chains anywhere in the UK. The model then routes the biomass feedstocks, as well as how the CO2 is transported to offshore storage sites and all the energy outputs produced at the facility to its end-users (electricity, biofuels and hydrogen).
From this modelling of the supply chains, the model can optimise the carbon emissions associated with the transportation aspects of the supply chains by automatically switching between trucks, rail, shipping and pipelines to minimise emissions, and find the optimal siting location for specific supply chains.
Strengthening the UK’s leadership in BECCS delivery
Looking ahead, the UK could be at the forefront of BECCS delivery.
Manchester’s innovative modelling allows the UK to strengthen this advantage by giving users – for the first time – the information to make evidence-based decisions. The sophisticated tool allows policymakers and industry to accurately understand where biomass sources are and the volume that exists, how best to transport the energy, store resulting CO2 while incurring minimum emissions and which supply chains perform better in which areas.
The research team has already begun to show industrial clusters how the model can maximise profitability and sustainability. A recent partnership with Glass Futures revealed the economies of scale created by local glass producers coming together to use BECCS to power their furnaces.
Alongside, the team is working to decarbonise carbon-intensive industries and provide more sustainable long-term revenue streams. For example, the model was used as the basis of a three-month secondment to help Uniper Energy build a roadmap to convert a fossil-fuel facility into a BECCS facility.
Additionally, through collaborative engagement with BEIS (six meetings to date), the team is influencing net zero policy, demonstrating the full-chain benefits of BECCS and its alignment with the UK strategy of cluster collaboration.
Finally, the full-chain transportation CNS modelling tool can handle any energy output, it identifies where potential energy demand is, and carbon optimally sends the energy to end users. The sophistication of the tool means it has the option of multiple applications and can be repurposed to simulate any technology or supply chain.