Dynamic Modeling of Ammonia Emissions and Nitrogen Deposition via Online Coupling of WRF‐Chem and Noah‐MP‐CN

Abstract Ammonia (NH 3 ) is an important alkaline gas, mainly emitted from agricultural activities, playing an important role in global nitrogen cycle and surface ecosystems. Chemical transport models and emission inventories are widely used to study the emission, transport, and chemical transformation of NH 3 . However, traditional static inventories consider emissions as unidirectional, overlooking interactions between NH 3 emissions and other ecosystems, especially land surface processes linked to emissions. In this study, we achieved bidirectional NH 3 exchange between land surface and atmospheric chemistry models by developing WRF‐CN‐Chem, a model integrating the Noah‐MP land surface model with carbon‐nitrogen dynamics (Noah‐MP‐CN) and the Weather Research and Forecasting model with atmospheric chemistry (WRF‐Chem). Compared with the static Multi‐resolution Emission Inventory for China, the dynamic bidirectional model exhibits higher spatiotemporal resolution and demonstrated a stronger temporal correlation with satellite observations. WRF‐CN‐Chem model estimated 7.88 TgN NH 3 emission in year 2020 in eastern China. Additionally, we incorporated the atmospheric nitrogen deposition, simulated by the “Online” experiment, into the soil ammonium pool. Our findings revealed an increase of 2.25 TgC yr −1 in land net primary productivity (NPP) in eastern China attributable to the increased nitrogen deposition. By incorporating bidirectional NH 3 exchange between land surface and atmosphere chemistry models, this study enhances the simulation of dynamic ammonia emissions and improves understanding of atmospheric nitrogen deposition processes. Furthermore, linking these processes to land NPP provides valuable insights for sustainable land management and pollution mitigation strategies, helping address the environmental impacts of excessive fertilization.