A novel approach to assessing the commercial opportunities for greenhouse gas removal technology value chains: Developing the case for a negative emissions credit in the UK

In the UK the development of greenhouse gas removal (GGR) technologies at scale by 2050 is seen as an increasingly urgent imperative; necessary to ensure alignment of the UK's carbon targets with international efforts to limit the global temperature increase to 2 °C or less. As such, GGR is an increasingly critical topic for UK climate policy. So far, GGR research has focused on top-down assessment of techno-environmental potential and carbon abatement costs - an approach which aids integrated assessment modelling but does not provide the commercially relevant analysis necessary to understand potential routes to market for this sector. This research reduces this knowledge gap by employing a novel bottom-up perspective to determine the financial opportunities available to GGR business models in Biomass heavy UK energy scenarios. This delivers results relevant to national and sectorial policy and decision making, by quantifying revenue opportunities from future GGR value chains, as well as business model performance. It also informs the innovation, policy, and regulatory environment required to ensure market development and resilience of different revenue streams. The work concludes that energy market policy - specifically access to a carbon credit mechanism - has by far the greatest near term opportunity to drive the negative emissions technologies we assess. This is because the values in this market far outweigh those in related supply chains such as: enhanced oil recovery, afforestation payments, biochar markets, and industry and commercial uses of captured carbon. This data shows that negative emissions technologies in the UK, should not be led by agricultural and land use policy, but should be integrated with energy policy. To do this, the development of a carbon storage credit mechanism analogous to the existing carbon price floor is key. As a proof of concept for a novel method to generate commercially relevant insights for GGR scale up, the research clearly demonstrates that the value pool method provides critical insights to assist GGR development and could form the basis of further work

The Use of Lidar Data and VHR Imagery to Estimate the Effects of Tree Roots on Shallow Landslides Assessment

The study of geo-hazards has been benefited from the technological advances in the field of Remote Sensing (RS) techniques as the ALS (Airborne Laser Scanners) Systems with Very High Resolution (VHR) cameras. Recently, the LiDAR (Light Detection and Ranging) is an active sensor technique used for a variety of geoscientific applications including slope monitoring to retrieve ground surface displacements at high spatial resolution. Additionally, LiDAR has been widely used in order to collect high-resolution information on forests structure for the determination and characterization of vegetation cover due its ability to capture multiple returns and to reach the ground, even in forested areas, allowing the generation of Digital Terrain Models (DTMs) for the estimation of forest variables. In this paper, a LiDAR dataset and VHR imagery from aerial survey was used in the southwest zone of Medellín City-Colombia where the most frequent landslides are shallow and triggered by rainfall. Slopes with gradients up to 30% on residual soils characterize the study area, having about of 30% of forest cover consisting predominantly of Eucalyptus and Coniferous forests. For the estimation of the tree roots effects on the shallow landslides assessment on a natural slope, interpolation processes were developed from the LiDAR 3D point cloud, obtaining DTMs of 1 m-pixel. Additionally, orthophotos with the same spatial resolution were acquired in the aerial campaign. The proposed workflow was implemented on a GIS platform, and considers the extraction of the tree heights by generating a Canopy Height Model (CHM), while for the delineation of the tree crown a process of image segmentation was developed. Once the vegetation has been characterized using LiDAR products and dendrometric relationships, the Limit Equilibrium Method (LEM) was used to evaluate slope stability considering the effect of vegetation (trees). The results indicate that the proposed workflow allows to obtain adequate stability indicators for the estimation of tree roots contribution and additionally, this RS technique allows saving resources in this kind of analysis. © Published under licence by IOP Publishing Ltd