Project description
Understanding N2O emissions from agricultural soils
Agricultural soils represent the primary source of human-induced atmospheric nitrous oxide (N2O) emissions, which pose a threat to the ozone layer. However, the precise magnitude and critical influencing factors of these emissions remain uncertain. The MSCA-funded COLOSSAL project seeks to develop a model-driven framework aimed at enhancing the global quantification and understanding of N2O emissions from agricultural soils. The project will involve the creation of comprehensive databases encompassing N2O emissions and crop productivity, quantify global N2O emissions using an advanced terrestrial biosphere model, and use interpretable machine learning models to identify the primary drivers of N2O emissions. COLOSSAL will also incorporate climate change projections and mitigation practices to forecast future N2O emission scenarios.
Objective
Agricultural soils are the primary human-induced source of atmospheric nitrous oxide (N2O) emissions, a potent greenhouse gas and the most significant damaging substance of the ozone layer. Climate change and the projected increases in food demand, agricultural land area, and fertilizer use are expected to increase N2O emissions over the coming decades. However, the actual magnitude and the key-influencing factors remain highly uncertain. COLOSSAL will develop an innovative models-driven framework to improve global quantification and understanding of N2O emissions from agricultural soils. First, I will produce comprehensive databases of N2O emissions and crop productivity at site- and regional-scale, establishing the foundation for subsequent steps. Second, I will use an advanced terrestrial biosphere model for a mechanistic-based quantification of global N2O emissions from agricultural soils, covering historical and current time periods. Third, I will implement interpretable machine-learning models to unravel the key drivers and estimate N2O emissions globally, including plant-soil-atmosphere interactions and management practices. Finally, I will unfold future N2O emission scenarios by incorporating climate change projections and mitigation practices into the terrestrial biosphere model informed by interpretable machine-learning models. COLOSSAL, stemming from 3 leading multi-disciplinary research groups, will take place during the 2-year outgoing phase at the Massachusetts Institute of Technology including an 8-month secondment at Boston College (USA), and 1-year return phase at Aarhus University (Denmark). Overall, COLOSSAL will advance our understanding of N2O emissions from global agricultural soils, contributing decisively to the design of more effective strategies for mitigating worldwide greenhouse gas emissions in the future.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdatabases
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorologybiosphera
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
You need to log in or register to use this function
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global FellowshipsCoordinator
8000 Aarhus C
Denmark