From Crops to Carbon Sequestration: A Technology-Explicit AFOLU Module for Energy Models

The Paris Agreement commits 197 countries to stabilizing global average surface temperatures at less than 2 °C above pre-industrial levels. Many industrialized nations, including Italy, aim for climate neutrality by 2050 through “net zero” greenhouse gas (GHG) emissions policies, aimed at decarbonizing all the energy intensive sector. In this context, the role of agriculture, forestry, and other land use (AFOLU) sector play an ambiguous role. Challenges include balancing GHG mitigation with food security, addressing synergies with the energy sector (e.g., bio commodities), and leveraging AFOLU as a net sink to offset emissions from other sectors.

Energy system optimization models (ESOMs), as widely used to design cost-optimal decarbonization policies, can be used to determine effective AFOLU management strategies at a national level. Nevertheless, their focus on energy-intensive processes had previously limited detailed AFOLU representation, despite its prominent role in emission mitigation. ESOMs often lack the integration of natural capital constraints, such as land and water availability, as well as the ability to model specific AFOLU commodities like crops, livestock, and forest products. To address this gap, we introduce a novel AFOLU module designed to couple with ESOMs, enabling the formulation of national decarbonization scenarios incorporating a technology-explicit AFOLU representation, biophysical constraints and the possibility to evaluate climate change impacts on the sector.

The AFOLU module tracks GHG emissions from livestock, crops, and bioenergy production while optimizing sectoral contributions to national decarbonization goals. Additionally, it projects the evolution of AFOLU commodities, including shifts in crop types, livestock production, and forest management strategies in response to climate and policy drivers. Finally, it can account for biophysical constraints such as land use limitations, crop yield sensitivity to fertilizer and climate change, and forest absorption potential. The module is designed to be directly fed by the Global Agro-Ecological Zones (GAEZ) database from FAO, allowing for the automatized creation of national instances based on up-to-date geospatial datasets.

To demonstrate the utility of the module, we integrate it with the open-source energy system optimization model TEMOA, which has been validated in Italian case studies and shown coherence with established models like TIMES, and similar in structure to other ESOMs like MESSAGE, and OSeMOSYS. The integrated model evaluates Italy’s national climate mitigation plans, focusing on the interplay between energy and AFOLU sectors, including land competition for bio crop production.

Key outputs of the model include detailed accounting and optimization of AFOLU emissions, land and water use, and cost-effective decarbonization pathways for all the energy intensive sectors. For instance, scenarios explore the potential of organic farming to reduce crop-related emissions, the role of manure management in mitigating livestock emissions, and the benefits of afforestation for carbon sequestration. Preliminary results from the Italian case study reveal critical trade-offs and synergies, such as the tension between bioenergy production and food security, while identifying least-cost pathways to achieve climate neutrality.

This research bridges a critical gap in decarbonization modeling by integrating a flexible AFOLU module with energy systems, offering a reproducible framework for other national applications.