Source Apportionment of Volatile Organic Compounds (VOCs) by Positive Matrix Factorization (PMF) supported by Model Simulation and Source Markers - Using Petrochemical Emissions as a Showcase. (November 2019)
- Record Type:
- Journal Article
- Title:
- Source Apportionment of Volatile Organic Compounds (VOCs) by Positive Matrix Factorization (PMF) supported by Model Simulation and Source Markers - Using Petrochemical Emissions as a Showcase. (November 2019)
- Main Title:
- Source Apportionment of Volatile Organic Compounds (VOCs) by Positive Matrix Factorization (PMF) supported by Model Simulation and Source Markers - Using Petrochemical Emissions as a Showcase
- Authors:
- Su, Yuan-Chang
Chen, Wei-Hao
Fan, Chen-Lun
Tong, Yu-Huei
Weng, Tzu-Hsiang
Chen, Sheng-Po
Kuo, Cheng-Pin
Wang, Jia-Lin
Chang, Julius S. - Abstract:
- Abstract: This study demonstrates the use of positive matrix factorization (PMF) in a region with a major Petrochemical Complex, a prominent source of volatile organic compounds (VOCs), as a showcase of PMF applications. The PMF analysis fully exploited the quality and quantity of the observation data, sufficed by a cluster of 9 monitoring sites within a 20 km radius of the petro-complex. Each site provided continuous data of 54 speciated VOCs and meteorological variables. Wind characteristics were highly seasonal and played a decisive role in the source-receptor relationship, hence the dataset was divided into three sub-sets in accordance with the prevailing wind flows. A full year of real-time data were analyzed by PMF to resolve into various distinct source types including petrochemical, urban, evaporative, long-range air parcels, etc., with some sites receiving more petro-influence than others. To minimize subjectivity in the assignment of the PMF source factors, as commonly seen in some PMF works, this study attempted to solidify PMF results by supporting with two tools of spatially/temporally resolved air-quality model simulations and observation data. By exploiting the two supporting tools, the dynamic process of individual sources to a receptor were rationalized. Percent contributions from these sources to the receptor sites were calculated by summing over the occurrence of different source types. Interestingly, although the Petro-complex is the single largest localAbstract: This study demonstrates the use of positive matrix factorization (PMF) in a region with a major Petrochemical Complex, a prominent source of volatile organic compounds (VOCs), as a showcase of PMF applications. The PMF analysis fully exploited the quality and quantity of the observation data, sufficed by a cluster of 9 monitoring sites within a 20 km radius of the petro-complex. Each site provided continuous data of 54 speciated VOCs and meteorological variables. Wind characteristics were highly seasonal and played a decisive role in the source-receptor relationship, hence the dataset was divided into three sub-sets in accordance with the prevailing wind flows. A full year of real-time data were analyzed by PMF to resolve into various distinct source types including petrochemical, urban, evaporative, long-range air parcels, etc., with some sites receiving more petro-influence than others. To minimize subjectivity in the assignment of the PMF source factors, as commonly seen in some PMF works, this study attempted to solidify PMF results by supporting with two tools of spatially/temporally resolved air-quality model simulations and observation data. By exploiting the two supporting tools, the dynamic process of individual sources to a receptor were rationalized. Percent contributions from these sources to the receptor sites were calculated by summing over the occurrence of different source types. Interestingly, although the Petro-complex is the single largest local VOC source in the 20 km radius study domain, all monitoring sites in the region received far less influence from the Petro-complex than from other emission types within or outside the region, which together add up to more than 70% of the total VOC abundance. Graphical abstract: Image 1 Highlights: Meteorology controlled plume transport despite proximity to a major source. PAMS network allowed PMF to equip with temporal resolution of source apportionment. Simulations provided pictorial views of plume transport to support PMF results. … (more)
- Is Part Of:
- Environmental pollution. Volume 254(2019)Part A
- Journal:
- Environmental pollution
- Issue:
- Volume 254(2019)Part A
- Issue Display:
- Volume 254, Issue 1 (2019)
- Year:
- 2019
- Volume:
- 254
- Issue:
- 1
- Issue Sort Value:
- 2019-0254-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-11
- Subjects:
- Source-receptor -- Petrochemical complex -- Photochemical assessment measurement stations (PAMS)
Pollution -- Periodicals
Pollution -- Environmental aspects -- Periodicals
Environmental Pollution -- Periodicals
Pollution -- Périodiques
Pollution -- Aspect de l'environnement -- Périodiques
Pollution -- Effets physiologiques -- Périodiques
Pollution
Pollution -- Environmental aspects
Periodicals
Electronic journals
363.73 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02697491 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envpol.2019.07.016 ↗
- Languages:
- English
- ISSNs:
- 0269-7491
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.539000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16695.xml