Articles | Volume 20, issue 22
Atmos. Chem. Phys., 20, 13801–13815, 2020
https://doi.org/10.5194/acp-20-13801-2020
Atmos. Chem. Phys., 20, 13801–13815, 2020
https://doi.org/10.5194/acp-20-13801-2020

Research article 17 Nov 2020

Research article | 17 Nov 2020

Evaluating trends and seasonality in modeled PM2.5 concentrations using empirical mode decomposition

Huiying Luo et al.

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Marina Astitha on behalf of the Authors (31 Jul 2020)  Author's response    Manuscript
ED: Publish as is (23 Sep 2020) by Min Shao
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Short summary
A new method is introduced to evaluate nonlinear, nonstationary modeled PM2.5 time series by decomposing decadal PM2.5 concentrations and its species onto various timescales. It does not require preselection of temporal scales and assumptions of linearity and stationarity. It provides a unique opportunity to assess the influence of each species on total PM2.5. The results reveal a phase shift in modeled EC/OC concentrations, indicating the need for improved model treatment of organic aerosols.
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