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Disparities in precipitation effects on PM2.5 mass concentrations and chemical compositions: Insights from online monitoring data in Chengdu

Authors: Yi Li,Li Zhou,Hefan Liu,Song Liu,Miao Feng,Danlin Song,Qinwen Tan,Hongbin Jiang,Sophia Zuoqiu,Fumo Yang
Journal: Journal of Environmental Sciences
Publisher: Elsevier BV
Publish date: 2025-10
ISSN: 1001-0742 DOI: 10.1016/j.jes.2024.08.015
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The authors define SR as SR = ΔC / Cseason × 100%, where Cseason is the seasonal mean concentration. This normalization choice is problematic. The scavenging effect of a single rain event should be evaluated against its immediate pre-event conditions, not a long-term seasonal average.

This raises two key questions:

How can a rain event’s efficiency be meaningfully assessed using a baseline (seasonal mean) that may be heavily influenced by many other rain events and long-term pollution trends?
Doesn’t this formula artificially inflate the SR in seasons with low background pollution (e.g., summer) and suppress it in high-pollution seasons (e.g., winter), making cross-seasonal comparisons invalid?
This methodological flaw could significantly skew the reported disparities in scavenging rates for different PM2.5​ components, rainfall intensities, and seasons.

A more robust and physically meaningful calculation of the scavenging rate should normalize the concentration change by the pre-rain concentration. The following adjusted formula is recommended:

Recommended Scavenging Rate (SR’):

SR’ = (Cb – Ca) / Cb × 100%

Cb = Average concentration in the 3 hours before the precipitation event.
Ca = Average concentration in the 3 hours after the precipitation event.

 

Formula with Diurnal Adjustment:
SR’ = (Ćb – Ća) / Ćb × 100%

Where Ćb and Ća are the diurnally-adjusted values as defined in the paper. This would isolate the precipitation’s effect from the normal daily cycle while maintaining a physically sound normalization.

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