Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China
Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and...
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Elsevier
2022
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oai:doaj.org-article:732a290172894f449911689fe77046c72021-11-18T04:43:20ZMultiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China0160-412010.1016/j.envint.2021.106979https://doaj.org/article/732a290172894f449911689fe77046c72022-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S0160412021006048https://doaj.org/toc/0160-4120Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and total solar radiation or oxidants to reduce the effects of dispersion and chemical loss. These methods were applied to hourly speciated VOC data from November 2019 to March 2020 including during the COVID-19 shutdown. Various comparisons were made to assess the influences of these fluctuation drivers by time of day. Dispersion normalized PMF (DN-PMF) reduced the dispersion variations. Dispersion-radiation normalized PMF (DRN-PMF) reduced the impact of chemical loss, especially at night, which was better than Dispersion-Ox normalized PMF (DON-PMF). The conditional bivariate probability function (CBPF) plots of DRN-PMF results were consist with actual source locations. The DN-PMF, DRN-PMF, and DON-PMF results were consistent between 10:00 and 15:00, suggesting dispersion was significantly more influential than photochemical reactions during these times. The DRN-PMF results indicated that the highest VOC contributors during the COVID-19 shutdown were liquefied petroleum gas (LPG) (28.8%), natural gas (25.2%), and pulverized coal boilers emissions (19.6%). Except for petrochemical-related enterprises and LPG, the contribution concentrations of all other sources decreased substantially during the COVID-19 shutdown, by 94.7%, 90.6%, and 86.8% for vehicle emissions, gasoline evaporation, and the mixed source of diesel evaporation and solvent use, respectively. Controlling the use of motor vehicles and related volatilization of diesel fuel and gasoline can be effective in controlling VOCs in the future.Yao GuBaoshuang LiuQili DaiYufen ZhangMing ZhouYinchang FengPhilip K. HopkeElsevierarticleCOVID-19Volatile organic compoundsSource apportionmentImproved PMFEnvironmental sciencesGE1-350ENEnvironment International, Vol 158, Iss , Pp 106979- (2022) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
COVID-19 Volatile organic compounds Source apportionment Improved PMF Environmental sciences GE1-350 |
| spellingShingle |
COVID-19 Volatile organic compounds Source apportionment Improved PMF Environmental sciences GE1-350 Yao Gu Baoshuang Liu Qili Dai Yufen Zhang Ming Zhou Yinchang Feng Philip K. Hopke Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China |
| description |
Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and total solar radiation or oxidants to reduce the effects of dispersion and chemical loss. These methods were applied to hourly speciated VOC data from November 2019 to March 2020 including during the COVID-19 shutdown. Various comparisons were made to assess the influences of these fluctuation drivers by time of day. Dispersion normalized PMF (DN-PMF) reduced the dispersion variations. Dispersion-radiation normalized PMF (DRN-PMF) reduced the impact of chemical loss, especially at night, which was better than Dispersion-Ox normalized PMF (DON-PMF). The conditional bivariate probability function (CBPF) plots of DRN-PMF results were consist with actual source locations. The DN-PMF, DRN-PMF, and DON-PMF results were consistent between 10:00 and 15:00, suggesting dispersion was significantly more influential than photochemical reactions during these times. The DRN-PMF results indicated that the highest VOC contributors during the COVID-19 shutdown were liquefied petroleum gas (LPG) (28.8%), natural gas (25.2%), and pulverized coal boilers emissions (19.6%). Except for petrochemical-related enterprises and LPG, the contribution concentrations of all other sources decreased substantially during the COVID-19 shutdown, by 94.7%, 90.6%, and 86.8% for vehicle emissions, gasoline evaporation, and the mixed source of diesel evaporation and solvent use, respectively. Controlling the use of motor vehicles and related volatilization of diesel fuel and gasoline can be effective in controlling VOCs in the future. |
| format |
article |
| author |
Yao Gu Baoshuang Liu Qili Dai Yufen Zhang Ming Zhou Yinchang Feng Philip K. Hopke |
| author_facet |
Yao Gu Baoshuang Liu Qili Dai Yufen Zhang Ming Zhou Yinchang Feng Philip K. Hopke |
| author_sort |
Yao Gu |
| title |
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China |
| title_short |
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China |
| title_full |
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China |
| title_fullStr |
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China |
| title_full_unstemmed |
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China |
| title_sort |
multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the covid-19 shutdown in tianjin, china |
| publisher |
Elsevier |
| publishDate |
2022 |
| url |
https://doaj.org/article/732a290172894f449911689fe77046c7 |
| work_keys_str_mv |
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