کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4429968 | 1619840 | 2011 | 8 صفحه PDF | دانلود رایگان |

In this work Positive Matrix Factorization (PMF) was applied to 4-hour resolved PM10 data collected in Milan (Italy) during summer and winter 2006. PM10 characterisation included elements (Mg–Pb), main inorganic ions (NH4+, NO3−, SO42−), levoglucosan and its isomers (mannosan and galactosan), and organic and elemental carbon (OC and EC).PMF resolved seven factors that were assigned to construction works, re-suspended dust, secondary sulphate, traffic, industry, secondary nitrate, and wood burning. Multi Linear Regression was applied to obtain the PM10 source apportionment. The 4-hour temporal resolution allowed the estimation of the factor contributions during peculiar episodes, which would have not been detected with the traditional 24-hour sampling strategy.
► PMF analysis on Milan data: contribution estimation of sources affecting the area.
► Levoglucosan and isomers amongst tracers: estimation of wood burning contribution.
► Source apportionment on 4-hour resolved data: analysis of peculiar episodes.
Journal: Science of The Total Environment - Volume 409, Issue 22, 15 October 2011, Pages 4788–4795