Beneficial or impactful management? Life Cycle Assessment and i-Tree Canopy to evaluate the net environmental benefits of Mediterranean urban forests

Abstract

Several tree-planting initiatives have been launched globally to face challenges related to air pollution and climate change in urban areas. However, different management activities could potentially increase emissions and hence reduce net benefits provided by urban forests, and research on this is still scarce in the literature. This study aims to evaluate the net environmental benefits of different management and planting strategies of an urban forest, comparing the Ecosystem Services (ES) supply assessed by i-Tree Canopy tool and potential implementation impacts assessed by Life-Cycle Assessment (LCA). The main assumption is that the higher the Tree Canopy Cover (TCC), the higher the ES supply, particularly in terms of air pollutants removal (PM_2.5 and SO₂) and CO₂eq sequestration. The urban forest implementation and growth over time were simulated on a 1-hectare plot, proposing three Mediterranean oak species plantations. Three alternative scenarios were designed, reflecting three strategies to achieve 100 %TCC across three-time targets (i.e., 2030, 2050, 2100) increasing the intensity of management. Findings evidenced how CO₂ net balance values are mainly affected by plant density contrary to the net balance for pollutants, strongly influenced by management activities. Accordingly, high management intensity is not sustainable in terms of pollutants, especially to reach short-term targets. The combination of the LCA-ES model supports the planning and management of new urban forests, maximizing net benefits and integrating time growth as a crucial variable. This methodological approach can help model the contribution of single and multiple trees to offset pollutants and CO₂ emissions in different urban and climatic contexts. The study stands as an innovative attempt to optimize the net environmental benefits of alternative management strategies according to policy goals over time targets.