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Source apportionment of synchronously size segregated fine and coarse particulate matter, using an improved three-way factor analysis model.
Shi, Guo-Liang; Tian, Ying-Ze; Ye, Si; Peng, Xing; Xu, Jiao; Wang, Wei; Han, Bo; Feng, Yin-Chang.
Affiliation
  • Shi GL; State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China. Electronic address: nksgl@hotmail.com.
  • Tian YZ; State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China. Electronic address: tianyingze@hotmail.com.
  • Ye S; College of Software, Nankai University, No. 94 Weijin Road, Tianjin 300071, China.
  • Peng X; State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
  • Xu J; State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
  • Wang W; College of Software, Nankai University, No. 94 Weijin Road, Tianjin 300071, China.
  • Han B; Tianjin Key Laboratory for Air Traffic Operation Planning and Safety Technology, Civil Aviation University of China, Tianjin 300300, China.
  • Feng YC; State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China. Electronic address: fengyc@nankai.edu.cn.
Sci Total Environ ; 505: 1182-90, 2015 Feb 01.
Article in En | MEDLINE | ID: mdl-25461116
Samples of PM10 and PM2.5 were synchronously collected from a megacity in China (Chengdu) during the 2011 sampling campaign and then analyzed by an improved three-way factor analysis method based on ME2 (multilinear engine 2), to investigate the contributions and size distributions of the source categories for size segregated particulate matter (PM). Firstly, the synthetic test was performed to evaluate the accuracy of the improved three-way model. The same five source categories with slightly different source profiles were caught. The low AAE (average absolute error) values between the estimated and the synthetic source contributions (<15%) and the approachable estimated PM2.5/PM10 ratios with the simulated ratios might indicate that the results of the improved three-way factor analysis might be satisfactory. Then, for the ambient PM samples, the mean levels were 206.65 ± 69.90 µg/m(3) (PM10) and 130.47 ± 43.67 µg/m(3) (PM2.5). The average ratio of PM2.5/PM10 was 0.63. PM10 and PM2.5 in Chengdu were influenced by the same source categories and their percentage contributions were in the same order: crustal dust & coal combustion presented the highest percentage contributions, accounting for 58.20% (PM10) and 53.73% (PM2.5); followed by vehicle exhaust & secondary organic carbon (18.45% for PM10 and 21.63% for PM2.5), secondary sulfate and nitrate (17.06% for PM10 and 20.91% for PM2.5) and cement dust (6.30% for PM10 and 3.73% for PM2.5). The source profiles and contributions presented slightly different distributions for PM10 and PM2.5, which could better reflect the actual situation. The findings based on the improved three-way factor analysis method may provide clear and deep insights into the sources of synchronously size-resolved PM.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Environmental Monitoring / Factor Analysis, Statistical / Air Pollutants / Particulate Matter / Models, Theoretical Type of study: Prognostic_studies Country/Region as subject: Asia Language: En Journal: Sci Total Environ Year: 2015 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Environmental Monitoring / Factor Analysis, Statistical / Air Pollutants / Particulate Matter / Models, Theoretical Type of study: Prognostic_studies Country/Region as subject: Asia Language: En Journal: Sci Total Environ Year: 2015 Type: Article