Cite this article: Cao, Z., Zhou, X., Ma, Y., Wang, L., Wu, R., Chen, B. and Wang, W. (2017). The Concentrations, Formations, Relationships and Modeling of Sulfate, Nitrate and Ammonium (SNA) Aerosols over China.
Aerosol Air Qual. Res.
17: 84-97. https://doi.org/10.4209/aaqr.2016.01.0020
SO42–, NO3– and NH4+ are characterized in China based on published observation data.
SO42–, NO3– and NH4+ occupy 34.2 ± 10.9% of PM2.5 and 28.2 ± 8.5% of PM10.
Stationary source emissions of coal combustion are still dominated in China.
(NH4)2SO4 and NH4NO3 are the main existing forms of SO42–, NO3– and NH4+ in aerosols.
Sulfate levels simulated have an obvious underestimation in winter in northern China.
Sulfate, nitrate and ammonium (SNA) are the dominant composition of secondary aerosols in the atmosphere and have a significant impact on public health, atmospheric chemistry process and climate. In this study, to evaluate SNA pollution in China, a first nationwide investigation derived from almost all published data in the field measurement before 2012 was carried out. The results show that SNA levels in China are about 3–5 times higher than those in USA and Europe. SNA account for 34.2 ± 10.9% in PM2.5 and 28.2 ± 8.5% in PM10. The highest SNA concentrations occur in urban areas of northern China. SNA all have peaks in winter, but the nadirs are in spring for sulfate and ammonium and in summer for nitrate. SOR (sulfur oxidation ratio) and NOR (nitrogen oxidation ratio) values show that the formations of sulfate and nitrate are distinct in different regions and seasons. The low average NO3–/SO42– ratio (0.43 ± 0.26) indicates that the stationary emissions from coal combustion remain the main sources. There is a good relationship between (2[SO42–] + [NO3–]) and [NH4+] with near 1 slope, signifying that (NH4)2SO4 and NH4NO3 are the predominant forms which SNA exist in particles in China. Based on the comprehensive observational data in China, the simulation for SNA aerosols by GISS in CMIP5 were evaluated.
Keywords: SNA; Field measurement; Model simulation; China