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

Yao, Liquan; Kong, Shaofei; Nemitz, Eiko ORCID: https://orcid.org/0000-0002-1765-6298; Vieno, Massimo ORCID: https://orcid.org/0000-0001-7741-9377; Cheng, Yi; Zheng, Huang; Wang, Yuanlin; Chen, Nan; Hu, Yao; Liu, Dantong; Zhao, Tianliang; Bai, Yongqing; Qi, Shihua. 2024 Improving below‐cloud scavenging coefficients of sulfate, nitrate, and ammonium in PM2.5 and implications for numerical simulation and air pollution control. Journal of Geophysical Research: Atmospheres, 129 (2), e2023JD039487. 23, pp. https://doi.org/10.1029/2023JD039487

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Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2023JD039487
UKCEH and CEH Sections/Science Areas:	Atmospheric Chemistry and Effects (Science Area 2017-)
ISSN:	2169-897X
NORA Subject Terms:	Atmospheric Sciences
Related URLs:	Dataset Other
Date made live:	19 Jan 2024 15:04 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/536719

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