Source apportionment of PM2.5 size distribution and composition data from multiple stationary sites using a mobile platform

Ho Tang Liao; Charles C.K. Chou; Sheng Hsiu Huang; Chia Jung Lu; Chih Chieh Chen; Philip K. Hopke; Chang Fu Wu

doi:10.1016/j.atmosres.2017.02.008

Source apportionment of PM_2.5 size distribution and composition data from multiple stationary sites using a mobile platform

Ho Tang Liao, Charles C.K. Chou, Sheng Hsiu Huang, Chia Jung Lu, Chih Chieh Chen, Philip K. Hopke, Chang Fu Wu^*

^*Corresponding author for this work

Department of Chemistry

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

Several source apportionment studies considering multiple sites showed spatial variability of source contributions. However, setting up multiple fixed sites to collect comprehensive chemical speciation data is resource demanding. In this study, field campaigns were conducted at multiple receptor sites in the Mailiao and Taishi townships in Yunlin County using a mobile platform to demonstrate the feasibility of receptor modeling with particle size distribution and PM_2.5 speciation data. Sources of air pollutants to all of the monitoring sites were identified and quantified using a modified positive matrix factorization (PMF) model. Modeling results indicated that a mixed source dominated by secondary aerosol was the largest contributor to PM_2.5 at most sites. Adding VOC measurements with high time resolution helped to improve the source separation. Different patterns of source contributions among sites and seasons were observed showing both spatial heterogeneity and seasonal variation.

Original language	English
Pages (from-to)	21-28
Number of pages	8
Journal	Atmospheric Research
Volume	190
DOIs	https://doi.org/10.1016/j.atmosres.2017.02.008
Publication status	Published - 2017 Jul 1

Keywords

Mobile platform
Multiple time resolution
Positive matrix factorization (PMF)
Source apportionment
Spatial variation

ASJC Scopus subject areas

Atmospheric Science

Access to Document

10.1016/j.atmosres.2017.02.008

Cite this

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title = "Source apportionment of PM2.5 size distribution and composition data from multiple stationary sites using a mobile platform",

abstract = "Several source apportionment studies considering multiple sites showed spatial variability of source contributions. However, setting up multiple fixed sites to collect comprehensive chemical speciation data is resource demanding. In this study, field campaigns were conducted at multiple receptor sites in the Mailiao and Taishi townships in Yunlin County using a mobile platform to demonstrate the feasibility of receptor modeling with particle size distribution and PM2.5 speciation data. Sources of air pollutants to all of the monitoring sites were identified and quantified using a modified positive matrix factorization (PMF) model. Modeling results indicated that a mixed source dominated by secondary aerosol was the largest contributor to PM2.5 at most sites. Adding VOC measurements with high time resolution helped to improve the source separation. Different patterns of source contributions among sites and seasons were observed showing both spatial heterogeneity and seasonal variation.",

keywords = "Mobile platform, Multiple time resolution, Positive matrix factorization (PMF), Source apportionment, Spatial variation",

author = "Liao, {Ho Tang} and Chou, {Charles C.K.} and Huang, {Sheng Hsiu} and Lu, {Chia Jung} and Chen, {Chih Chieh} and Hopke, {Philip K.} and Wu, {Chang Fu}",

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AU - Liao, Ho Tang

AU - Chou, Charles C.K.

AU - Huang, Sheng Hsiu

AU - Lu, Chia Jung

AU - Chen, Chih Chieh

AU - Hopke, Philip K.

AU - Wu, Chang Fu

PY - 2017/7/1

Y1 - 2017/7/1

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AB - Several source apportionment studies considering multiple sites showed spatial variability of source contributions. However, setting up multiple fixed sites to collect comprehensive chemical speciation data is resource demanding. In this study, field campaigns were conducted at multiple receptor sites in the Mailiao and Taishi townships in Yunlin County using a mobile platform to demonstrate the feasibility of receptor modeling with particle size distribution and PM2.5 speciation data. Sources of air pollutants to all of the monitoring sites were identified and quantified using a modified positive matrix factorization (PMF) model. Modeling results indicated that a mixed source dominated by secondary aerosol was the largest contributor to PM2.5 at most sites. Adding VOC measurements with high time resolution helped to improve the source separation. Different patterns of source contributions among sites and seasons were observed showing both spatial heterogeneity and seasonal variation.

KW - Mobile platform

KW - Multiple time resolution

KW - Positive matrix factorization (PMF)

KW - Source apportionment

KW - Spatial variation

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