This article constructed a 1km agricultural NH3 emission inventory for China for the year 2017. Through several agricultural NUE increasing scenarios, they investigated the implications for NH3 emissions and provincial PM2.5 air pollution mitigation. The authors did an in-depth analyses of benefits for various seasons and provinces. The research highlighted the prioritized provinces and crop types for NUE improvements and associated air quality benefits. I recommend its acceptance upon addressing the following comments through minor revision.

1. It's not easy to construct a such high geographical resolution NH3 inventory all based on solid data about activity levels and emission factors, particularly since we do not know below county level the nitrogen fertilizer use situation and manure management information. Although the authors have stated that ‘It is assumed that all other crops are distributed uniformly throughout the croplands of each province.’  ‘The gridded livestock population map at 1 km, including cattle, sheep, goat, pork, and poultry was obtained from Cheng et al. (2023) ‘. They should disclose more information to what extent current simplification or treatment might affect the NH3 mitigation and PM2.5 mitigation assessment. NH3-contributed PM2.5 may provide a particularly large health impact for populated areas. If the cropland are assumed to be distributed uniformly within one provinces for other major crops, that may lead to large biases in the air pollution impact assessments. It is the same for manure, what is the assumption Cheng et al. 2023 used for allocating livestock population to 1km scale? That assumption would be critical for understanding the validity of livestock NH3 geographical distribution estimated. Also please clarify the EFs, including the geographical resolution and parameterization. 

2. It is relatively easy to use NUE to construct scenarios for crop and livestock management rather than specific technological bundles, however, how realistic are these NUE scenarios? Are technologies available to achieve NUE defined here? Less is known about the potential of improving fruits and vegetables NUE compared to other crops. Furthermore, calculations for crop NUE itself can involve substantial uncertainties and data problems, see Zhang, X., Zou, T., Lassaletta, L. et al. Quantification of global and national nitrogen budgets for crop production. Nat Food 2, 529–540 (2021). https://doi.org/10.1038/s43016-021-00318-5. For livestock, could CHANS model represent flow of TAN across various manure handling stages? Since your emission inventory represent flow of TAN - but I suspect CHANS's representation for manure N would not be as sophisticated. How would the CHANS calculated livestock NUE in China compared to other nitrogen budgets research methods? It still is worthy of conducting a more detailed literature search to understand the uncertainties and give some paraphrases in the Discussion section. 

3. The GCHP simulation is done for one year for China in quite high resolution. I wonder what is the computing resources and time taken for completing the baseline simulation? 

4. Atmospheric background emissions, which affect contribution of NH3 to PM2.5, have changed a lot between 2017 and the present. Could the authors comment on the implications for the effectiveness of these NUE-increasing scenarios? 

This study develops a high-resolution NH3 emission inventory for Chinese agriculture and integrates it with nitrogen flow and air quality models to assess mitigation potentials. Results show that cropland NUE improvements and organic fertilizer use offer greater NH3 reduction than livestock measures, with distinct regional effectiveness. Specifically, organic fertilizers are found to be most effective in grain-producing regions, while NUE enhancement benefits southern coastal areas. The analysis particularly highlights severe over-fertilization in vegetable/fruit production as a critical mitigation target. These findings provide scientific support for China's emerging agricultural NH3 control policies while revealing data gaps for future refinement, demonstrating how optimized nitrogen management can simultaneously address air pollution and sustainable development goals.

The study is well organized and conducted. Below are some moderate comments for further clarification of the manuscript.

Specific comments:

1) The agricultural crop-related NH₃ emissions in this study are significantly higher than those in other emission inventories. Could this be attributed not only to the use of localized emission factors for China but also to other potential reasons? Was the total nitrogen application amount constrained in the calculations? Additionally, the assumption that crops other than the major ones are uniformly distributed across provincial croplands—what is the basis for this method, and how does it impact the subsequent NH3 mitigation potential analysis?

2) In the NUE-C and OUR mitigation scenarios, the proposed measures may also alter the corresponding emission factors (EFs). Did the study only consider reductions in nitrogen input (activity data)? Could you further explain how the mitigation measures were integrated with the emission inventory? (Page 9)

3) It is generally believed that poultry contributes significantly to livestock-related agricultural NH3 emissions, yet in this study, poultry accounts for a relatively small proportion (17.6%). What might explain this discrepancy? (Page 10)

4) Does the HHH region include Hebei or Hubei? Spatially, Hebei (Beijing-Tianjin-Hebei region) has long been considered a hotspot for NH3 emissions. Why does this inventory instead show Jiangsu Province as having higher emissions? (Page 13)

5) Although the emission inventory in this study achieves a 1 km resolution, the meteorological reanalysis data likely do not match this resolution. Could you provide more details on the data processing methods?

6) When comparing model results with observations, could seasonal comparisons be included for a more comprehensive evaluation?