Dynamic monitoring, reporting and verification for implementing negative emission strategies in managed ecosystems (RETINA)

Carbon sequestration in soil is one of the most promising biological negative emission (BNE) technologies to mitigate climate change. Soil carbon sequestration relies on the adoption of best management practices to increase the amount of carbon stored in soil. An advantage of soil carbon sequestration in agriculture is that carbon stocks are most depleted in cropland systems, so there is great potential to capture atmospheric carbon without land use conversion and competition for land resources. The successful implementation of land based negative emission technologies will require continuous monitoring, reporting and verification of soil storage changes and greenhouse gas (GHG) emissions to estimate net carbon sequestration in soils. Currently, a lack of cost effective, robust, consistent, transparent and accurate methods limits large-scale implementation of these technologies. Monitoring, reporting and verification of carbon sequestration and GHG emissions from soils could be achieved by combining information from novel cost-effective technological developments in field-based sensors, remote sensing, and/or smartphone apps and integration of models on cloud platforms to confirm management practice effectiveness. The process of detecting and inferring soil carbon changes and GHG emissions is extremely data intensive. In order to understand the variability in soil carbon and GHG emissions there is a need to combine information from diverse sensor networks in different environments and to accurately model soil carbon changes and GHG emissions from various management practices. Here we propose a cloud-based platform that combines new development in sensor-based technologies with cloud-based model simulations to overcome major obstacles for implementing a monitoring, reporting and verification (MRV) system for land based negative emission technologies. To operationalize the MRV system, we will collect and process sensor information from the field, land scape level sensors and national scale (Satellite data) and harmonize data feeds to cloud-based models. This setup allows near time simulations on carbon changes and GHG emissions on the cloud without the need for individual user inputs. This project offers the quality data and confidence required for visualising a future, rising to the demands of a net zero carbon UK by 2050. This project will undertake transdisciplinary research to harness recent advances in digital technology combined with novel approaches in stakeholder engagement to make a step change in delivering integrated management options, co-produced with stakeholders, which can help to mitigate climate change. There are several groups who will benefit from the outcomes of this research. We identify various stakeholders and interested groups; UK Farmers will benefit from a freely available mobile-App to help plan various management options to increase/maintain soil organic matter in soil while also accounting for GHG emissions from soil. For policy makers, web-based decision support tool developed in this project will forecast regional estimates of net soil carbon sequestration and GHG emissions. This project could help in designing strategies to monitor and improve environmental quality and reduce GHG emissions from managed ecosystems to meet net zero Britain by 2050. We anticipate wide interest from academia in the GHG budgets and various environmental data sources this project will generate.
Keywords: Climate change, soils, carbon sequestration, Greenhouse gas emissions, cloud-based modelling

Apart from benefits outlined for the main stakeholders there are several extended benefits like capacity building, academic engagement and bring several technological advancements are likely from this project:
Capacity building: Currently, the UK reports GHG emissions from agriculture using tier 2 emission methodologies. IPCC tier 3 GHG estimation methods are most complex in terms of required input data, understanding of biophysical processes, monitoring of changes in spatially explicit manner. Output from this project will provide GHG emissions using tier 3 methods which can be reported to the UNFCCC as part if the national GHG inventory. This output will provide capacity and capabilities to the UK. We will approach reporting authorities and engage with them for possible tier 3 reporting based on the outcome of this project.

Global academic/scientific community: We anticipate wide interest in the GHG budgets and various environmental data sources this project will generate. The proposed iterative near-term net carbon sequestration and GHG emissions forecasting framework and data generated from this project will be of long-lasting value to those in the global greenhouse gas modelling and atmospheric science communities.

Technological advancements proposed using developing technologies like aerial photography and mobile app-based soil characteristic estimations will pave the way to digitize farm level information bringing automation into their processes which is an important step forward smart farming technology. The approaches proposed are applicable globally and successful demonstration of our approach will allow uptake internationally, particularly as key data that we will exploit are collected in existing global monitoring programmes.

International outreach: The PI and Co-PI's of this project are very well connected with several international networks. JY and PS are actively involved in Global Research Alliance Agriculture Greenhouse Gas Emissions network and the international initiative "4 per 1000". PS is a lead authors in IPCC and numerous international networks. The research outcome will be presented to these networks to maximize the impact.

Public engagement: We will also disseminate and engage with general public trough social media accounts e.g. twitter, institute blogs etc., A project page on Research Gate, a social media forum for researchers, will be developed and updated regularly with project information, activities and outcomes.