Improvement of model simulation for summer PM and O through coupling with two new potential HONO sources in the North China Plain.

A large fraction of fine particulate matter (PM) and ozone (O) in the troposphere originates from secondary formation through photochemical processes, which remarkably contributes to the deterioration of regional air quality in China. The photochemical reactions initiated by hydroxyl radicals (OH) play vital roles in secondary PM and O formation. In contrast, the OH levels in polluted areas are underestimated by current chemical transport models (CTMs) because of the strongly unknown daytime sources of tropospheric nitric acid (HONO), which has been recognized as the dominant source of primary OH in polluted areas of China. In this study, the atmospheric HONO levels at two urban sites were found to be significantly underestimated by the WRF-Chem model based on available information on HONO sources. The HONO levels could be well reproduced by the WRF-Chem model after incorporating two new potential HONO sources from the photochemical reactions of NO, as proposed in our previous study based on chamber experiment results. Comparing the simulations with available information of HONO sources, the simulated levels of atmospheric OH, secondary inorganic and organic aerosols (SIA and SOA), PM and daily maximum 8-h average (MDA8) O were evidently elevated or were closer to the observations over the North China Plain (NCP), with elevation percentages of 0.48-20.1 %, and a decrement percentage of -5.79 % for pNO. Additionally, the compensating errors in modeling PM and the gap in MDA8 O levels between observation and simulation in 2 + 26 cities became evidently smaller. The results of this study indicated that the empirical parameterization of two new potential HONO sources through photochemical reactions of NO improved the model performance in modeling PM and O by narrowing the gap in daytime HONO levels between simulation and observation, although their detailed chemical mechanisms are still unknown and should be further investigated and explicitly parameterized.