Improving below‐cloud scavenging coefficients of sulfate, nitrate, and ammonium in PM2.5 and implications for numerical simulation and air pollution control

Below-cloud scavenging (BS) is often underestimated in chemical transport models (CTMs) due to inaccurate parameterizations of BS coefficient for fine particle (Λ) caused by a shortage of high-time resolution field observations. Rainfall ions and related air pollutants were measured hourly in Central China (CC) during 2019. BS contributed to 37%–68% of wet deposition for SO2-4, NO3, and NH4+(SNA). By a bulk method coupled with brute-force search, the Λ (10−2–10 hr−1) was parameterized for SNA in PM2.5, which was 1–3 orders of magnitudes higher than theoretical calculations in CTMs. These chemical-specific Λ parameterizations were validated by EMEP model. Compared to baselines, updated simulations for annual SNA wet deposition increased by 3.3%–20.4% and for mean PM2.5 SNA concentrations reduced by 1.2%–40%, capturing measurements better. The contributions of scavenged gases to wet deposition below cloud were calculated as 9%–73%, exhibiting discrepancies (2%–17% for HNO3 and 19%–90% for SO2) with previous modeling results as different Λ schemes adopted in CTMs. The nonlinearity between Λ and precipitation intensity causes frequency exerting stronger impact on aerosol burden than intensity and duration. Periodic light rain with a precipitation amount of 1–10 mm per event can eliminate 60% of SNA in PM2.5 and is suggested as a routine procedure to improve local air quality. Analyzing a typical washout process after a haze event in CC, BS could reduce PM2.5 SNA concentrations by 44%–54% derived from improved parameterizations.