Toward Sustainable Agriculture Through Carbon Farming

The European Green Deal and the new CAP call for a rapid transition of agricultural systems. In this context, carbon farming — agricultural practices that enhance soil carbon sequestration — is a key tool for mitigating climate change and supporting more sustainable food systems, especially in intensively farmed regions such as the Po Valley.

The Project Data Science Approach for Carbon Farming Scenarios (DaSACaF) answers to the call Data Science for Climate and Agriculture – 2023 by Cariplo Foundation. The project develops an innovative model to assess how different farming practices and policy scenarios affect carbon sequestration, enabling informed and sustainable decision-making. The project brings together multidisciplinary expertise and integrates data, advanced methods, and local knowledge through four main pillars.

Integrated Data Lake

We collect and harmonize climatic, agronomic, socio-economic, and remote-sensing data to enable accurate and robust carbon farming assessments.

Advanced Modelling

We design a predictive framework combining data science, deep learning, crop modelling, and statistical methods to estimate soil carbon sequestration potential across different regions and scenarios.

Scenario Analysis

Together with farmers and stakeholders, we co-develop realistic scenarios that combine crop management, policy options, and climate change. The model translates complex interactions into clear, actionable recommendations for sustainable transitions.

Multi-dimensional Assessment

We evaluate economic, social, and environmental impacts of alternative strategies — from cost-effectiveness and carbon credits to community well-being, biodiversity, ecosystem health, and climate resilience.

DaSACaF focuses on representative case studies in Lombardy, Novara, and Verbano-Cusio-Ossola to demonstrate the validity and future scalability of the approach across Europe.

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