کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4416066 1307767 2006 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identification of PM sources by principal component analysis (PCA) coupled with wind direction data
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم محیط زیست شیمی زیست محیطی
پیش نمایش صفحه اول مقاله
Identification of PM sources by principal component analysis (PCA) coupled with wind direction data
چکیده انگلیسی

The effectiveness of combining principal component analysis (PCA) with multi-linear regression (MLRA) and wind direction data was demonstrated in this study. PM data from three grain-size fractions from a highly industrialised area in Northern Spain were analysed. Seven independent PM sources were identified by PCA: steel (Pb, Zn, Cd, Mn) and pigment (Cr, Mo, Ni) manufacture, road dust (Fe, Ba, Cd), traffic exhaust (P, OC + EC), regional-scale transport (NH4+, SO42-, V), crustal contributions (Al2O3, Sr, K) and sea spray (Na, Cl). The spatial distribution of the sources was obtained by coupling PCA with wind direction data, which helped identify regional drainage flows as the main source of crustal material. The same analysis showed that the contribution of motorway traffic to PM10 levels is 4–5 μg m−3 higher than that of local traffic. The coupling of PCA-MLRA with wind direction data proved thus to be useful in extracting further information on source contributions and locations. Correct identification and characterisation of PM sources is essential for the design and application of effective abatement strategies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemosphere - Volume 65, Issue 11, December 2006, Pages 2411–2418
نویسندگان
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