DOI: 10.1016/j.atmosenv.2020.117364
论文题名: PM2.5 source apportionment during severe haze episodes in a Chinese megacity based on a 5-month period by using hourly species measurements: Explore how to better conduct PMF during haze episodes
作者: Tian Y. ; Zhang Y. ; Liang Y. ; Niu Z. ; Xue Q. ; Feng Y.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 224 语种: 英语
英文关键词: Explosives
; Factorization
; Organic carbon
; Sensitivity analysis
; Uncertainty analysis
; Coefficients of variations
; Haze
; Particulate Matter
; Physico-chemical changes
; Positive Matrix Factorization
; Secondary organic carbons (SOC)
; Source apportionment
; Uncertainty
; Coal combustion
; coal
; ion
; organic carbon
; coal combustion
; displacement
; heating
; megacity
; organic carbon
; source apportionment
; uncertainty analysis
; air pollution
; Article
; bootstrapping
; China
; city
; combustion
; concentration (parameter)
; environmental aspects and related phenomena
; haze
; heating
; measurement
; particulate matter
; physical chemistry
; positive matrix factorization
; priority journal
; China
; Tianjin
学科: Haze
; Particulate matter
; PMF
; Source apportionment
; Uncertainty
中文摘要: To understand rapid physicochemical changes and to explore how to better conduct PMF for source apportionment during haze episodes, EPA Positive Matrix Factorization (PMF) 5.0, including an assessment of uncertainties, was performed based on hourly measurements of PM2.5-bound species during a heating period in 2017–2018 in the Chinese megacity of Tianjin. Five haze episodes were the focus of this study. PMF was conducted using two modes (whole-based mode for the entire sampling period and episode-based mode for each episode), and some indicators, including bootstrap (BS), displacement of factor elements (DISP), E/M (ratios of estimated and measured concentrations), were then used to evaluate PMF performance. The contributions of secondary ions and secondary organic carbon (SOC) for episodes I and III were greater than 50% (which were defined as SPE: episodes strongly influenced by secondary particles). The coal combustion contribution in episode II (defined as coal combustion episode: CCE) was greater than in the other episodes, and fireworks burning were extracted in episode IV (defined as fireworks burning episode: FBE). The PMF solutions were poor for the regional transport episode (RTE), during which episode the species showed weak variations (low coefficients of variation) and similar patterns (high correlations). During SPE, E/M were 0.71–1.00 for episode-based mode and 0.65–1.28 for whole-based mode, indicating good performance for both modes; while during CCE and FBE, E/M were 0.53–0.99 for episode-based mode and 0.10–1.06 for whole-based mode, showing that estimation of some important markers were poor for the whole-based mode. Sensitivity tests were then conducted to systematically investigate the influence of heavy-pollution types on PMF and showed that PMF was insensitive to contribution variations but was strongly sensitive to variations in source profiles. Overall, episode-based mode of PMF is better for episodes with strong variations of primary sources (CCE and FBE), whereas whole-based mode can be used for SPE and RTE. This work will help us to accurately assess hourly source variations. © 2020 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160903
Appears in Collections: 气候变化与战略
There are no files associated with this item.
作者单位: The State Environmental Protection Key Laboratory of Urban Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China; College of Intelligence and Computing, Tianjin University, 135 Yaguan Rd, Tianjin, China
Recommended Citation:
Tian Y.,Zhang Y.,Liang Y.,et al. PM2.5 source apportionment during severe haze episodes in a Chinese megacity based on a 5-month period by using hourly species measurements: Explore how to better conduct PMF during haze episodes[J]. Atmospheric Environment,2020-01-01,224