Nitrogen (N) deposition is one of the major inputs to cropland and consequently important for the estimation of N Use Efficiency (NUE) for crop production. However, the estimates for N deposition carry large uncertainty, and existing assessments of N budgets and NUE on agricultural land use different estimates of N deposition. To evaluate the uncertainties in existing methods for national scale N deposition estimation and assess their impacts on the resulting NUE estimation for countries around the world, we 1) reviewed existing methods and related data sources for quantifying N deposition inputs to crop production on a national scale; 2) identified the most up–to–date data sources and designed methods to quantify N deposition input to crop production on a national scale; 3) collected N deposition data from observation sites in major countries (e.g., UK, US, and China) to validate the estimated N deposition input; and 4) conducted sensitivity analysis to evaluate how the uncertainties in N deposition affect crop NUE assessment. As a result, we established four estimates for N deposition inputs on cropland for 251 countries around the world during 1961–2020 as combinations of two sets of N deposition maps (ACCMIP¹ and Wang et al.^2-4) and two sets of cropland maps (HYDE⁵ and LUH2⁶). The four products (1. AH: ACCMIP and HYDE, 2. AL: ACCMIP and LUH2, 3. WH: Wang et al. and HYDE, and 4. WL: Wang et al. and LUH2) show good agreement in N deposition estimates for the majority of countries, but have large differences in several Asian countries (e.g., China, India, and Pakistan), and the differences are mostly caused by the use of different N deposition maps. According to the comparison with the observation records in China, the deposition estimates based on Wang et al. show a better agreement with the observations. Hence, the authors recommend using product #4 WL (Wang et al. and LUH2) as the reference dataset for N deposition in the global assessments of N budgets by countries. 

References:

1. Lamarque, J. F. et al. Multi-model mean nitrogen and sulfur deposition from the atmospheric chemistry and climate model intercomparison project (ACCMIP): Evaluation of historical and projected future changes. Atmos. Chem. Phys. 13, 7997–8018 (2013).
2. Shang, Z. et al. Weakened growth of cropland-N2O emissions in China associated with nationwide policy interventions. Glob. Chang. Biol. 25, 3706–3719 (2019).
3. Wang, Q. et al. Data-driven estimates of global nitrous oxide emissions from croplands. Natl. Sci. Rev. 7, 441–452 (2020).
4. Wang, R. et al. Global forest carbon uptake due to nitrogen and phosphorus deposition from 1850 to 2100. Glob. Chang. Biol. 23, 4854–4872 (2017).
5. Goldewijk, K. K., Beusen, A., Doelman, J. & Stehfest, E. Anthropogenic land use estimates for the Holocene - HYDE 3.2. Earth Syst. Sci. Data 9, 927–953 (2017).
6. Hurtt, G. C. et al. Harmonization of global land use change and management for the period 850-2100 (LUH2) for CMIP6. Geoscientific Model Development 13, (2020).

Changes after Oct 5, 2022: The WH and WL data products are extended to 2022 while AL and AH are until 2020. 

Previously, we used Wang et al. as N deposition map for FAO dataset, and croplands include LUH2 and HYDE3.2 maps. As a final dataset in the previous version, LUH2 and Wang et al combination was preferred because *“(1) the Wang et al. estimates are closer to the remaining existing datasets for the majority of regions, particularly Asian countries, whereas the estimates obtained using ACCMIP are on the lower side of the distribution of N deposition compared to other datasets, with minimal change after 2005, (2) the LUH2 cropland map is available at an annual time scale, which serves the purpose of this study, while the HYDE map is only available at a decadal scale until 2000, and annually from 2000–2017, and (3) the WL product was within the range of ground estimates of N deposition from the station networks in multiple countries (i.e., China, the UK, the USA, and East Asia).” * Vishwakarma et al. (2023). Recently, HYDE data was updated with version 3.3 at annual scale until 2022 removing the limitations that existed in HYDE3.2 (Table 1). Hence, in this year’s update Wang et al and HYDE 3.3 products are also developed and compared with products with LUH2.