An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan
The positive matrix factorization (PMF) model is widely used for source apportionment of volatile organic compounds (VOCs). The question about how to select the proper number of factors, however, is rarely studied. In this study, an integrated method to determine the most appropriate number of sourc...
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MDPI AG
2018-10-01
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| Series: | Atmosphere |
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| Online Access: | http://www.mdpi.com/2073-4433/9/10/390 |
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| author | Fenjuan Wang Zhenyi Zhang Costanza Acciai Zhangxiong Zhong Zhaokai Huang Giovanni Lonati |
| author_facet | Fenjuan Wang Zhenyi Zhang Costanza Acciai Zhangxiong Zhong Zhaokai Huang Giovanni Lonati |
| author_sort | Fenjuan Wang |
| collection | DOAJ |
| description | The positive matrix factorization (PMF) model is widely used for source apportionment of volatile organic compounds (VOCs). The question about how to select the proper number of factors, however, is rarely studied. In this study, an integrated method to determine the most appropriate number of sources was developed and its application was demonstrated by case study in Wuhan. The concentrations of 103 ambient volatile organic compounds (VOCs) were measured intensively using online gas chromatography/mass spectrometry (GC/MS) during spring 2014 in an urban residential area of Wuhan, China. During the measurement period, the average temperature was approximately 25 °C with very little domestic heating and cooling. The concentrations of the most abundant VOCs (ethane, ethylene, propane, acetylene, n-butane, benzene, and toluene) in Wuhan were comparable to other studies in urban areas in China and other countries. The newly developed integrated method to determine the most appropriate number of sources is in combination of a fixed minimum threshold value for the correlation coefficient, the average weighted correlation coefficient of each species, and the normalized minimum error. Seven sources were identified by using the integrated method, and they were vehicular emissions (45.4%), industrial emissions (22.5%), combustion of coal (14.7%), liquefied petroleum gas (LPG) (9.7%), industrial solvents (4.4%), and pesticides (3.3%) and refrigerants. The orientations of emission sources have been characterized taking into account the frequency of wind directions and contributions of sources in each wind direction for the measurement period. It has been concluded that the vehicle exhaust contribution is greater than 40% distributed in all directions, whereas industrial emissions are mainly attributed to the west southwest and south southwest. |
| first_indexed | 2024-12-13T11:40:53Z |
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| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-12-13T11:40:53Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-33e638c98b1241f5be0ca5a6ac344ca42022-12-21T23:47:38ZengMDPI AGAtmosphere2073-44332018-10-0191039010.3390/atmos9100390atmos9100390An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in WuhanFenjuan Wang0Zhenyi Zhang1Costanza Acciai2Zhangxiong Zhong3Zhaokai Huang4Giovanni Lonati5National Climate Center, China Meteorological Administration, Beijing 100081, ChinaNational Institute for Environmental Studies, Ibaraki 305-8506, JapanDepartment of Civil and Environmental Engineering, Politecnico di Milano, Milan 20133, ItalyWuhan Municipality Environmental Monitoring Center, Wuhan 430015, ChinaShanghai BAIF Technology Co., LTD, Shanghai 201202, ChinaDepartment of Civil and Environmental Engineering, Politecnico di Milano, Milan 20133, ItalyThe positive matrix factorization (PMF) model is widely used for source apportionment of volatile organic compounds (VOCs). The question about how to select the proper number of factors, however, is rarely studied. In this study, an integrated method to determine the most appropriate number of sources was developed and its application was demonstrated by case study in Wuhan. The concentrations of 103 ambient volatile organic compounds (VOCs) were measured intensively using online gas chromatography/mass spectrometry (GC/MS) during spring 2014 in an urban residential area of Wuhan, China. During the measurement period, the average temperature was approximately 25 °C with very little domestic heating and cooling. The concentrations of the most abundant VOCs (ethane, ethylene, propane, acetylene, n-butane, benzene, and toluene) in Wuhan were comparable to other studies in urban areas in China and other countries. The newly developed integrated method to determine the most appropriate number of sources is in combination of a fixed minimum threshold value for the correlation coefficient, the average weighted correlation coefficient of each species, and the normalized minimum error. Seven sources were identified by using the integrated method, and they were vehicular emissions (45.4%), industrial emissions (22.5%), combustion of coal (14.7%), liquefied petroleum gas (LPG) (9.7%), industrial solvents (4.4%), and pesticides (3.3%) and refrigerants. The orientations of emission sources have been characterized taking into account the frequency of wind directions and contributions of sources in each wind direction for the measurement period. It has been concluded that the vehicle exhaust contribution is greater than 40% distributed in all directions, whereas industrial emissions are mainly attributed to the west southwest and south southwest.http://www.mdpi.com/2073-4433/9/10/390PMFfactor number selectionvolatile organic compoundssource apportionmentcentral China |
| spellingShingle | Fenjuan Wang Zhenyi Zhang Costanza Acciai Zhangxiong Zhong Zhaokai Huang Giovanni Lonati An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan Atmosphere PMF factor number selection volatile organic compounds source apportionment central China |
| title | An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan |
| title_full | An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan |
| title_fullStr | An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan |
| title_full_unstemmed | An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan |
| title_short | An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan |
| title_sort | integrated method for factor number selection of pmf model case study on source apportionment of ambient volatile organic compounds in wuhan |
| topic | PMF factor number selection volatile organic compounds source apportionment central China |
| url | http://www.mdpi.com/2073-4433/9/10/390 |
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