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• W2408589067 abstract "Abstract With real time resolved data of Particulate matter (PM) and chemical species, understanding the source patterns and chemical characteristics is critical to establish controlling of PM. In this work, PM2.5 and chemical species were measured by corresponding online instruments with 1-h time resolution in Beijing. Multilinear Engine 2 (ME2) model was applied to explore the sources, and four sources (vehicle emission, crustal dust, secondary formation and coal combustion) were identified. To investigate the sensitivity of time resolution on the source contributions and chemical characteristics, ME2 was conducted with four time resolution runs (1-h, 2-h, 4-h, and 8-h). Crustal dust and coal combustion display large variation in the four time resolutions runs, with their contributions ranging from 6.7 to 10.4 μg m−3 and from 6.4 to 12.2 μg m−3, respectively. The contributions of vehicle emission and secondary formation range from 7.5 to 10.5 and from 14.7 to 16.7 μg m−3, respectively. The sensitivity analyses were conducted by principal component analysis-plot (PCA-plot), coefficient of divergence (CD), average absolute error (AAE) and correlation coefficients. For the four time resolution runs, the source contributions and profiles of crustal dust and coal combustion were more unstable than other source categories, possibly due to the lack of key markers of crustal dust and coal combustion (e.g. Si, Al). On the other hand, vehicle emission and crustal dust were more sensitive to time series of source contributions at different time resolutions. Findings in this study can improve our knowledge of source contributions and chemical characteristics at different time solutions." @default.
• W2408589067 created "2016-06-24" @default.
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• W2408589067 date "2016-08-01" @default.
• W2408589067 modified "2023-10-14" @default.
• W2408589067 title "Characteristics and sensitivity analysis of multiple-time-resolved source patterns of PM2.5 with real time data using Multilinear Engine 2" @default.
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• W2408589067 doi "https://doi.org/10.1016/j.atmosenv.2016.05.032" @default.
• W2408589067 hasPublicationYear "2016" @default.
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