Regenerative practices reduce global warming impact and intensity of maize systems in north-central Italy

Agriculture significantly contributes to global climate warming, accounting for up to one-third of anthropogenic greenhouse gas (GHG) emissions. One of the key strategies to mitigate these emissions is through adopting regenerative agricultural practices. This study quantified the global warming impact (GWI) and its intensity (GWI-I) associated with conventional and regenerative maize production systems in Emilia Romagna in the center of the Po Valley region, Italy. Using detailed field-level producer data and a hybrid quantification framework that combines process-based crop modeling with carbon footprint analysis, we compared a business-as-usual (BAU) management scenario—characterized by intensive tillage, frequent irrigation, and high agrochemical inputs—with six regenerative strategies. Results from the 16 measured sites over four years (2019–2022) showed an average GWI of 5594 kg CO 2 -eq ha −1 yr −1 under BAU, primarily driven by GHG emissions from soil organic carbon (SOC) loss and synthetic nitrogen (N) fertilizer inputs. When scaled regionally, regenerative practices substantially reduced GWI and GWI-I, with reductions ranging from 35 % to 87 % compared to BAU. The most climate mitigating management scenario involved a combination of no-tillage, diversified crop rotation, and N rate reduction. These practices enhanced SOC gain by 0.38 Mg C ha −1 yr −1 , reduced nitrous oxide (N 2 O) emissions by 35 %, while maintaining crop yields. Our findings highlight that adopting regenerative agricultural practices offers climate mitigation potential without sacrificing productivity. Agriculture is a major contributor to climate change, responsible for up to one-third of global anthropogenic greenhouse gas (GHG) emissions. There is an urgent need to identify scalable strategies that mitigate these emissions without compromising productivity. Regenerative agriculture has emerged as a promising solution, but field-scale data combined with robust modeling approaches are needed to assess its effectiveness. To quantify the global warming impact (GWI) and its intensity (GWI-I) of conventional (business-as-usual, BAU) versus regenerative maize management practices in the Emilia Romagna region of northern Italy, while identifying the best scenarios that offer the greatest climate mitigation potential without reducing crop yield. We applied a hybrid quantification framework that integrated field-level measurements, carbon footprint (CF) life cycle assessment (LCA) based, and process-based crop modeling (CSM) to evaluate GWI and GWI-I under BAU and six regenerative management scenarios. Data from 16 maize fields over four years (2019–2022) were collected and regionally upscaled to 3509 maize fields using soil datasets. Scenarios included variations in tillage, crop rotation, cover cropping, and nitrogen fertilizer application. GHG emissions were estimated from both off-site and on-site sources, including soil organic carbon (SOC) change. Under BAU, the average GWI was 5594 kg CO 2 -eq ha −1 yr −1 , primarily due to SOC loss (47 % of GWI) and synthetic nitrogen use. Regenerative scenarios reduced GWI by 35–87 %, with the most effective involving no-till, diversified rotation with soybean and rye cover crops, and a 25 % nitrogen rate reduction. This scenario increased SOC by 0.38 Mg C ha −1 yr −1 , reduced N 2 O emissions by 35 %, and maintained yields, resulting in near carbon-neutral or even negative GWI-I values. SOC accrual and lower N 2 O emissions were the primary drivers of reduced climate impact. This study demonstrates that regenerative maize systems can significantly reduce agricultural GHG emissions while sustaining productivity. The hybrid CF-CSM approach provides a replicable, high-resolution framework for evaluating and scaling regenerative agricultural practices. The findings offer actionable insights for policy and land management strategies to meet climate neutrality targets. • BAU maize practices emit 5.6 Mg CO₂-eq ha −1 yr −1 , due to SOC loss and N fertilizers. • Regenerative management reduces GWI by up to 87 % compared to conventional BAU. • Combining no-till, crop rotation, and lower N rate leads to a near C neutral GWI. • The N 2 O contribution from crop residues, roots and SOM mineralized N was determined. • Hybrid LCA dynamic modeling and regional emission factors used to scale GHG impacts.