Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)3201-3212
Journal / PublicationAtmospheric Environment
Volume33
Issue number19
Publication statusPublished - Aug 1999
Externally publishedYes

Abstract

An advanced algorithm called positive matrix factorization (PMF) in receptor modeling was used to identify the sources of respirable suspended particulates (RSP) in Hong Kong. The compositional data obtained from the Hong Kong Environmental Protection Department from 1992 to 1994 were analyzed. The species analyzed in this study are Al, Ca, Mg, Pb, Na+, V, Cl-, NH4 +, SO4 2-, Br-, Mn, Fe, Ni, Zn, Cd, K+, Ba, Cu, and As. Unlike the conventional receptor modeling algorithm, factor analysis PMF only generates non-negative source profiles. To eliminate sulfate from such factors where it is not physically plausible, special penalty terms were included in the model so that sulfate concentrations could be selectively decreased in specified factors. A 9-factor model containing non-zero sulfate concentrations in three factors gives the most satisfactory source profiles. Ammonium sulfate, chloride depleted marine aerosols and crustal aerosols are the three non-zero sulfate sources. Other factors are marine aerosols, non-ferrous smelters, particulate copper, fuel oil burning, vehicular emission and bromide/road dust. The last two sources can be combined as a single source of vehicle/road dust. The compositional profiles of these factors were also developed. The mass profiles obtained can be improved by further refinement of distribution of sulfate in the sources.

Research Area(s)

  • Hong Kong, Positive matrix factorization, Receptor modeling, Respirable suspended particulates, Source apportionment