HaNi-Crop: A Harmonized and Gridded Global Dataset of Crop-Specific Nitrogen Inputs from Nitrogen Fertilizer and Manure

Abstract. Crop-specific dataset on nitrogen (N) inputs from synthetic fertilizer and manure are critical for assessing crop productivity, nutrient use efficiency, and environmental impacts, as crops differ substantially in their N demands and utilization. However, existing datasets remain limited in their simultaneous coverage of crop-group specificity, spatial resolution, long-term temporal coverage, and fertilizer-form differentiation. These limitations have constrained comprehensive global and regional assessments of crop-specific greenhouse gas emissions, N use efficiency, N budgets, and agrifood-system resilience. Based upon the History of Anthropogenic Nitrogen Inputs (HaNi) data infrastructure (Tian et al., 2022), we present HaNi-Crop, a harmonized global dataset of crop-specific N inputs from synthetic fertilizer and manure for 21 major crop groups at a spatial resolution of 0.1° × 0.1°, spanning the period of 1961–2023. This dataset integrates national and sub-national fertilizer and manure statistics, crop harvested-area maps, fertilizer product information, and spatial allocation procedures to generate annual gridded estimates of crop-specific N application rates differentiated by NH4+-N and NO3--N forms. Globally, synthetic fertilizer N inputs to cropland increased sharply from 11 Tg N yr-1 in the early 1960s to more than 100 Tg N yr-1 by 2023, while manure N inputs increased from 14 to 23 Tg N yr-1. Throughout 1961–2023, three major cereal crops–wheat, maize, and rice, consistently accounted for approximately half of global synthetic fertilizer N inputs. Among N fertilizer forms, NH4+-N inputs increased from 8 to nearly 90 Tg N yr-1, while the inputs for NO3--N fertilizers only increased from 3 to about 12 Tg N yr-1. Overall, the HaNi-Crop dataset provides a critical foundation for crop-specific greenhouse gas accounting, Earth system and agroecosystem modeling, and N budget analyses to enhance food security, environmental sustainability, and climate mitigation. The dataset is publicly available at https://doi.org/10.5281/zenodo.21364978 (Hao et al., 2026).