Title: | Source apportionment of urban air pollutants using constrained receptor models with a priori profile information |
Author(s): | Liao HT; Yau YC; Huang CS; Chen N; Chow JC; Watson JG; Tsai SW; Chou CC; Wu CF; |
Address: | "Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Taipei, Taiwan. Institute of Environmental Health, National Taiwan University, Taipei, Taiwan. Division of Atmospheric Sciences, Desert Research Institute, Reno, NV, USA. Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan. Electronic address: ckchou@rcec.sinica.edu.tw. Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Taipei, Taiwan; Institute of Environmental Health, National Taiwan University, Taipei, Taiwan; Department of Public Health, National Taiwan University, Taipei, Taiwan. Electronic address: changfu@ntu.edu.tw" |
DOI: | 10.1016/j.envpol.2017.04.071 |
ISSN/ISBN: | 1873-6424 (Electronic) 0269-7491 (Linking) |
Abstract: | "Exposure to air pollutants such as volatile organic compounds (VOCs) and fine particulate matter (PM(2.5)) are associated with adverse health effects. This study applied multiple time resolution data of hourly VOCs and 24-h PM(2.5) to a constrained Positive Matrix Factorization (PMF) model for source apportionment in Taipei, Taiwan. Ninety-two daily PM(2.5) samples and 2208 hourly VOC measurements were collected during four seasons in 2014 and 2015. With some a priori information, we used different procedures to constrain retrieved factors toward realistic sources. A total of nine source factors were identified as: natural gas/liquefied petroleum gas (LPG) leakage, solvent use/industrial process, contaminated marine aerosol, secondary aerosol/long-range transport, oil combustion, traffic related, evaporative gasoline emission, gasoline exhaust, and soil dust. Results showed that solvent use/industrial process was the largest contributor (19%) to VOCs while the largest contributor to PM(2.5) mass was secondary aerosol/long-range transport (57%). A robust regression analysis showed that secondary aerosol was mostly contributed by regional transport related factor (25%)" |
Keywords: | "Aerosols/analysis Air Pollutants/*analysis Air Pollution/*statistics & numerical data Dust/analysis Environmental Monitoring/*methods Gasoline/analysis *Models, Chemical Models, Theoretical Particulate Matter/analysis Regression Analysis Seasons Taiwan Vo;" |
Notes: | "MedlineLiao, Ho-Tang Yau, Yu-Chen Huang, Chun-Sheng Chen, Nathan Chow, Judith C Watson, John G Tsai, Shih-Wei Chou, Charles C-K Wu, Chang-Fu eng England 2017/05/10 Environ Pollut. 2017 Aug; 227:323-333. doi: 10.1016/j.envpol.2017.04.071. Epub 2017 May 4" |