Daniele Mosso

The Agriculture, Forestry, and Other Land Use sectors account for approximately 20% of global greenhouse gas emissions, highlighting their critical role in achieving decarbonization targets. Despite their importance, these sectors remain inadequately represented in traditional energy-environment-economy modeling frameworks used to design emission reduction pathways. This study investigates how integrating AFOLU systems into energy system optimization models affects the assessment of net-zero pathways and land-energy nexus. In doing so, the paper proposes a best practice to include and link land use sectors within energy models. By modeling the consumption of natural resources, such as land and water, the framework captures the inherent competition between processes. Furthermore, the techno-economic characterization of land-based mitigation options-including detailed manure management, biogas & biomass production, and afforestation-strengthens the nexus representation across sectors. Using Sweden as a case study, it is demonstrated that adding land use sectors to energy models enhances their accuracy by capturing additional positive and negative emissions without distorting global outcomes. Eighteen scenarios, tested under various sensitivities and policy drivers, reveal that emissions related to land use could be reduced by over 45% by 2050. Specifically, more than 30% of this reduction is attributed to organic farming and over 15% results from livestock management.

This chapter highlights the significance of open-source energy system optimization models in enhancing the transparency and accessibility of energy system studies for policymakers. It provides a detailed example of the creation of a robust modeling framework. This includes guidance on selecting appropriate inputs, interpreting results, and connecting them to policy-relevant objectives such as the Sustainable Development Goals (SDGs), particularly SDGs 6 (water), 7 (energy), 8 (work and economic growth), 9 (industry), 13 (climate) and 15 (land). The focus is on the energy system optimization model TEMOA-Italy, a case study for Italy developed within the open-source framework TEMOA. The presented results explore the impact of possible future scenarios and energy policies on the power sector’s sustainability, showing that low emissions scenarios perform better than a base scenario concerning environmental aspects, but worse in terms of land use and social aspects like the quality of labor. Import dependence is also affected by the renewables’ penetration, due to the criticality of renewable technologies imports. The exclusion of carbon capture from the set of available new technologies improves geopolitical stability and reduces volume shortage risk.

In the context of the energy transition, the integration of land use considerations into energy planning can provide significant improvements. In energy system optimization models (ESOMs), land use aspects can be integrated at the cost of a finer spatial resolution and a more detailed characterization of land, tailored to regional constraints and specificities. Additionally, an assessment of trade-offs with alternative land uses is necessary. Nevertheless, they are commonly neglected. This study addresses the challenge of incorporating land use aspects into ESOMs, with a focus on the unique context of Pantelleria Island. It aims to bridge the gap in methodologies for renewable energy potential assessment and model integration, considering the critical role of land pricing and availability. It combines geospatial data aggregation with model adaptation to include detailed land use aspects. The findings highlight the substantial impact of land costs on renewable energy planning, with land pricing significantly altering model outcomes. This research offers key insights for sustainable energy planning and underscores the importance of considering land use in energy transition strategies.

In the context of the energy transition, the integration of land use considerations into energy planning is increasingly vital, especially in scenarios where land availability is a constraint. This study addresses the challenge of incorporating land-use aspects into Energy System Optimization Models (ESOMs), with a focus on the unique context of Pantelleria Island. It aims to bridge the gap in methodologies for renewable energy potential assessment and model integration, considering the critical role of land pricing and availability. It combines geospatial data aggregation with model adaptation to include detailed land use aspects. Findings highlight the substantial impact of land costs on renewable energy planning, with land pricing significantly altering model outcomes. This research offers key insights for sustainable energy planning and underscores the importance of considering land use in energy transition strategies.