To what extent can the below-cloud washout effect influence the PM2.5? A combined observational and modeling study

Lu, Xingcheng; Chan, Siu Chung; Fung, Jimmy C.H.; Lau, Alexis K.H.

To what extent can the below-cloud washout effect influence the PM2.5? A combined observational and modeling study

2019

Lu, Xingcheng | Chan, Siu Chung | Fung, Jimmy C.H. | Lau, Alexis K.H.

The below-cloud washout (BCW) effect on PM₂.₅ concentration during periods of rain is still a subject of debate. Existing BCW schemes for PM₂.₅ 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 PM₂.₅ 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 PM₂.₅ simulation during rainy days. The BCW effect can clean around 10–40% of the PM₂.₅ over our study region, which can help to reduce the PM₂.₅ exposure level for residents, and the health burdens caused by this pollutant can thus be reduced. Rainmaking is a potential way to decrease PM₂.₅ concentration, but it cannot be the key method to reduce the PM₂.₅ level to the standard during episodic cases (e.g., >200 μg/m³).

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