Abstract
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.
Highlights
Volatile Organic Compounds (VOCs) play a significant role in local, regional, and global air pollution
volatile organic compounds (VOCs) are harmful to humans, ecosystems, and the atmosphere because of their role in the formation of ozone and peroxy-acetyl nitrate (PAN) [1,2,3,4]
In order to make the choice of the number of factors as less arbitrarily as possible, we developed a multiple-indicator approach based on the values of three different statistical indicators for positive matrix factorization (PMF) model performance: (i) the correlation coefficients between observed and model reconstructed concentrations for a single VOC; (ii) an overall correlation coefficient for all the VOCs considered in PMF runs; and (iii) the normalized absolute error between observed and reconstructed concentrations for the entire
Summary
Volatile Organic Compounds (VOCs) play a significant role in local, regional, and global air pollution. VOCs are harmful to humans, ecosystems, and the atmosphere because of their role in the formation of ozone and peroxy-acetyl nitrate (PAN) [1,2,3,4]. Atmosphere 2018, 9, 390 and urbanization, megacities and city clusters in China are suffering from severe photochemical pollution [7]. Concern about VOC concentrations in China caused the central government to start controlling VOCs, during the 12th five-year period (2011–2015), in key regions as well as the launch of VOCs monitoring programs and pilot projects [8]. There are extensive offline and online observations performed to investigate the current ambient status of VOCs in main populated cluster areas of
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