In addition to strong emission reductions, Carbon Dioxide Removal (CDR) strategies are critical to avoid exceeding the temperature limits of the Paris Agreement. At the same time, large-scale CDR deployment might be in conflict with reaching the Sustainable Development Goals (SDG), e.g. massive expansion of bioenergy production conflicts with SDG 2 “zero hunger”, and sustainability considerations are increasingly seen as vital for the success of CDR strategies. CDR approaches, including afforestation and reforestation, bioenergy with carbon capture and storage (BECCS), ocean alkalinity enhancement (OAE), and direct air capture with CCS (DACCS), must scale to remove up to several hundreds of Gt of CO2 in order to reach net-zero as fast as possible. Robust and optimised monitoring, reporting, and verification (MRV) systems are essential in order to enable reliable carbon accounting and guarantee the capacity to continuously and consistently detect the early emergence of CDR-related signals and potential side-effects.
In this session, we invite modelling or observation based contributions on the detection of climatic and biogeochemical signals and their attribution to CDR deployment at different timescales. For example, changes in features of variability, such as, long-term trends, seasonal or diurnal cycles of carbon cycle components but also of variables that could reveal CDR-related side effects (e.g. ocean oxygen, nutrient availability, soil moisture, land-surface properties, etc.).
We welcome studies employing marine mesocosm CDR experiments, pilot CDR field sites, or modelling of novel CDR scenarios and CDR practices. We also welcome studies that use observational networks - including innovative use of existing monitoring networks, such as Argo floats, established land and ocean time series or ICOS data, that can provide insights into CDR potential and impacts. Implementation of machine learning algorithms, optimal fingerprinting or innovative time-of-emergence analysis for MRV are particularly encouraged.
The objective of this session is to gather an understanding of emerging monitoring practices with potential to advance the scientific foundations for robust MRV, and to explore opportunities and challenges for responsible, large-scale implementation of CDR.