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Evaluating the influence of constant source profile presumption on PMF analysis of PM2.5 by comparing long- and short-term hourly observation-based modeling.
Xie, Mingjie; Lu, Xinyu; Ding, Feng; Cui, Wangnan; Zhang, Yuanyuan; Feng, Wei.
  • Xie M; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanj
  • Lu X; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanj
  • Ding F; Nanjing Environmental Monitoring Center of Jiangsu Province, 175 Huju Road, Nanjing, 210013, China.
  • Cui W; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanj
  • Zhang Y; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanj
  • Feng W; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanj
Environ Pollut ; 314: 120273, 2022 Dec 01.
Article in English | MEDLINE | ID: covidwho-2041734
ABSTRACT
Hourly PM2.5 speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM2.5 components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM2.5 water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMFwhole). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMFwhole solution. After removing event data, PMF modeling was conducted for individual months (PMFmonth) and the 4-year period (PMF4-year), respectively. PMFmonth solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF4-year solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Environ Pollut Journal subject: Environmental Health Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Environ Pollut Journal subject: Environmental Health Year: 2022 Document Type: Article