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Title: Simulations of Sulfate-Nitrate-Ammonium (SNA) aerosols during the extreme haze events over Northern China in 2014

Journal Article · · Atmospheric Chemistry and Physics (Online)

Extreme haze events have occurred frequently over China in recent years. Although many studies have investigated the formation mechanisms associated with PM2.5 for heavily polluted regions in China based on observational data, adequately predicting peak PM2.5 concentrations is still challenging for regional air quality models. In this study, we evaluate the performance of one configuration of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and use the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during four extreme haze episodes in October 2014 over the North China Plain. The highest observed PM2.5 concentration of 469 μg m-3 occurred in Beijing. Comparisons with observations show that the model reproduced the temporal variability in PM2.5 with the highest PM2.5 values on polluted days (defined as days in which observed PM2.5 is greater than 75 μg m-3), but predictions of sulfate, nitrate, and ammonium were too low on days with the highest observed concentrations. Observational data indicate that the sulfur/nitric oxidation rates are strongly correlated with relative humidity during periods of peak PM2.5; however, the model failed to reproduce the highest PM2.5 concentrations due to missing heterogeneous reactions. As the parameterizations of those reactions is not well established yet, estimates of SO2-to-H2SO4 and NO2/NO3-to-HNO3 reaction rates that depend on relative humidity were applied which improved the simulation of sulfate, nitrate, and ammonium enhancement on polluted days in terms of both concentrations and partitioning among those species. Sensitivity simulations showed that the extremely high heterogeneous reaction rates and also higher emission rates than those reported in the emission inventory

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1322494
Report Number(s):
PNNL-SA-116728; KP1701000
Journal Information:
Atmospheric Chemistry and Physics (Online), Vol. 16, Issue 16; ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English

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