Articles | Volume 20, issue 22
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, Marina Astitha, Christian Hogrefe, Rohit Mathur, and S. Trivikrama Rao


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

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
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.
Final-revised paper