To what extent can the below-cloud washout effect influence the PM_2.5? A combined observational and modeling study

The below-cloud washout (BCW) effect on PM_2.5 concentration during periods of rain is still a subject of debate. Existing BCW schemes for PM_2.5 have large deficiencies that influence its simulation in 3D chemical transport models (CTMs). In this study, a 7-year dataset with high temporal resolution (in minutes) sampled from a pristine rural site is used to calculate the BCW coefficient during the rain events. The data used for the BCW coefficient calculation cover a wide range of rain intensity from 2 mm h^-1 to 60 mm h^-1. The BCW coefficient linearly correlates with the rain intensity, with a correlation coefficient of 0.82. The coefficient has a magnitude of 10^-5 to 10^-4 s^-1 when the rain intensity ranges from 1 to 40 mm h^-1. After implementing the updated BCW scheme into the Comprehensive Air Quality Model with Extensions (CAMx) model, the performance of PM_2.5 simulation improves for the two months of heavy rain. Apart from the CAMx model, our scheme can be easily implemented into other 3D CTMs to improve PM_2.5 simulation during rainy days. The BCW effect can clean around 10-40% of the PM_2.5 over our study region, which can help to reduce the PM_2.5 exposure level for residents, and the health burdens caused by this pollutant can thus be reduced. Rainmaking is a potential way to decrease PM_2.5 concentration, but it cannot be the key method to reduce the PM_2.5 level to the standard during episodic cases (e.g., >200 μg/m³).