Application of Positive Matrix Factorization in the Identification of the Sources of PM_2.5 in Taipei City

Fine particulate matter (PM_2.5) has a small particle size, which allows it to directly enter the respiratory mucosa and reach the alveoli and even the blood. Many countries are already aware of the adverse effects of PM_2.5, and determination of the sources of PM_2.5 is a critical step in reducing its concentration to protect public health. This study monitored PM_2.5 in the summer (during the southwest monsoon season) of 2017. Three online monitoring systems were used to continuously collect hourly concentrations of key chemical components of PM_2.5, including anions, cations, carbon, heavy metals, and precursor gases, for 24 h per day. The sum of the concentrations of each compound obtained from the online monitoring systems is similar to the actual PM_2.5 concentration (98.75%). This result suggests that the on-line monitoring system of this study covers relatively complete chemical compounds. Positive matrix factorization (PMF) was adopted to explore and examine the proportion of each source that contributed to the total PM_2.5 concentration. According to the source contribution analysis, 55% of PM_2.5 can be attributed to local pollutant sources, and the remaining 45% can be attributed to pollutants emitted outside Taipei City. During the high-PM_2.5-concentration (episode) period, the pollutant conversion rates were higher than usual due to the occurrence of vigorous photochemical reactions. Moreover, once pollutants are emitted by external stationary pollutant sources, they move with pollution air masses and undergo photochemical reactions, resulting in increases in the secondary pollutant concentrations of PM_2.5. The vertical monitoring data indicate that there is a significant increase in PM_2.5 concentration at high altitudes. High-altitude PM_2.5 will descend to the ground and thereby affect the ground-level PM_2.5 concentration.