Nitrous oxide emission factors from fertilizer use in Brazilian agricultural systems: meta-analytical insights for soil management, climate, and land-use policies

Mineral fertilizers account for 18% of Brazil's agricultural greenhouse gas (GHG) emissions, as reported in the Fourth National Inventory. Initial estimates relied on IPCC Tier I factors, but recent methodologies have advanced toward Tier II and III approaches, incorporating fertilizer type and regional conditions. This study aimed to refine direct N₂O emission estimates by proposing specific emission factors (EFs) for organic, mineral, and combined fertilizers across sugarcane, grain, and pasture systems. These factors considered environmental conditions, agricultural practices, and excreta inputs to improve national representativeness. A systematic review of 56 articles from Web of Science, Scopus, and SciELO yielded 325 trials. Variables analyzed included climate, biome, soil type, irrigation, management, nitrogen sources and rates, pH, texture, and soil carbon, nitrogen, and organic matter. Statistical analyses included boxplots, Kruskal-Wallis tests, and meta-analysis with bootstrapping, all performed in R. Higher N₂O emission factors were generally observed in pasture systems under Cwa climatic conditions, in grain systems under subtropical climates (Cfb and Cfa), and in sugarcane systems under tropical and subtropical climates (Am and Cfa), with elevated values frequently observed in the Cerrado and Atlantic Forest biomes. Weighted EFs ranged from 0.14 to 1.63%, while national average EFs were 0.66 for sugarcane, 0.69 for grains, and 0.64 for pastures, all within the uncertainty range of IPCC default values. These results demonstrate the potential of Tier II factors to improve N₂O emission estimates in Brazil, while highlighting important limitations related to data availability, methodological heterogeneity, and uneven geographic coverage. Continued efforts to expand regionally representative datasets and advance toward Tier III approaches are essential to reduce uncertainties and support more robust GHG inventories, life cycle assessments, and mitigation strategies.