the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A Preliminary Assessment of the Impacts of Multiple Temporal-scale Variations in Particulate Matter on its Source Apportionment
Abstract. Time series of pollutant concentrations consist of variations at different time scales that are attributable to many processes/sources (data noise, source intensities, meteorological conditions, climate, etc.). Improving the knowledge of the impact of multiple temporal-scale components on pollutant variations and pollution levels can provide useful information for suitable mitigation strategies for pollutant control during a high pollution episode. To investigate the source factors driving these variations, the Kolmogorov-Zurbenko (KZ) filter was used to decompose the time series of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and chemical species into intra-day, diurnal, synoptic, and baseline temporal-scale components (TS components). The synoptic TS component has the largest amplitude and relative contributions (about 50 %) to the total variance of SO42−, NH4+, and OC concentrations. The diurnal TS component has the largest relative contributions to the total variance of PM2.5, NO3−, EC, Ca, and Fe concentrations, ranging from 32 % to 47 %. To investigate the source impacts on PM2.5 from different TS components, four datasets RI (intra-day removed), RD (diurnal removed), RS (synoptic removed), and RBL (baseline removed) were created by respectively removing the intra-day, diurnal, synoptic, and baseline TS component from the original datasets. Multilinear Engine 2 (ME-2) and/or principal component analysis was applied to these four datasets as well as the original datasets for source apportionment. ME-2 solutions using the original and RI dataset identify crustal dust contributions. For the solutions from original, RI, RD, and RS datasets, the total primary source impacts are close, ranging from 35.1 to 40.4 μg m−3 during the entire sampling period. For the secondary source impacts, solutions from the original, RI and RD dataset give similar source impacts (about 30 μg m−3), which were higher than the impacts derived from the RS datasets (21.2 μg m−3).
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Preprint
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Supplement
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This preprint has been withdrawn.
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Interactive discussion
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RC1: 'Referee comment', Anonymous Referee #3, 09 Jun 2018
- AC1: 'Response to RC1', Guoliang Shi, 05 Sep 2018
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RC2: 'Comment', Anonymous Referee #4, 24 Jul 2018
- AC2: 'Response to RC2', Guoliang Shi, 05 Sep 2018
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RC3: 'Reviewer 5', Anonymous Referee #5, 27 Jul 2018
- AC3: 'Response to RC3', Guoliang Shi, 05 Sep 2018
- AC1: 'Response to RC1', Guoliang Shi, 05 Sep 2018
Interactive discussion
-
RC1: 'Referee comment', Anonymous Referee #3, 09 Jun 2018
- AC1: 'Response to RC1', Guoliang Shi, 05 Sep 2018
-
RC2: 'Comment', Anonymous Referee #4, 24 Jul 2018
- AC2: 'Response to RC2', Guoliang Shi, 05 Sep 2018
-
RC3: 'Reviewer 5', Anonymous Referee #5, 27 Jul 2018
- AC3: 'Response to RC3', Guoliang Shi, 05 Sep 2018
- AC1: 'Response to RC1', Guoliang Shi, 05 Sep 2018
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Xing Peng
Jian Gao
Guoliang Shi
Xurong Shi
Yanqi Huangfu
Jiayuan Liu
Yuechong Zhang
Yinchang Feng
Ruoyu Ma
Cesunica E. Ivey
Yi Deng
This preprint has been withdrawn.
- Preprint
(818 KB) - Metadata XML
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Supplement
(3945 KB) - BibTeX
- EndNote