Abstract. In recent years, nitrate aerosols have become a dominant component of atmospheric composition, surpassing sulfate in both concentration and climatic impact. However, accurately simulating nitrate remains a major challenge for global models due to complex formation mechanisms and strong regional variability. This study investigates key factors influencing nitrate aerosol formation to improve simulation accuracy in polluted regions. Using the EMAC climate–chemistry model and the ISORROPIA II thermodynamic module, we assess the effects of grid resolution, emission inventories, chemical kinetics, thermodynamic assumptions, and aerosol scavenging processes. Model predictions are evaluated against PM2.5 and PM1 nitrate observations from filter networks and aerosol mass spectrometer campaigns across Europe, North America, East Asia, and India. Results show that PM2.5 nitrate is generally overestimated, especially in East Asia (up to a factor of three), while PM1 nitrate is underestimated, particularly at urban-downwind sites. Higher grid resolution, adjusted N2O5 uptake, and updated emissions (e.g., CMIP6) improve PM2.5 predictions but do not consistently enhance PM1 accuracy. Seasonal and diurnal biases are most pronounced in Europe, where the model fails to capture observed nitrate variability. Sensitivity tests show limited impact on the total tropospheric nitrate burden (within 25 %). A combined configuration using high grid resolution, reduced N2O5 uptake, and the HTAPv3 emission inventory improves PM2.5 predictions in low-concentration periods and U.S. networks, but PM1 biases persist regionally. These findings highlight the difficulty of achieving consistent improvements across aerosol size modes and diverse geographic regions.
Milousis et al. (Tue,) studied this question.
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