A review of receptor modelling of industrially emitted particulate matter

Adewale M. Taiwo, Roy M. Harrison, Zongbo Shi

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Abstract

This review summarizes the different receptor models that have been adopted at industrial and urban sites to apportion the sources of particulate matter (PM) from industries. Industrial processes and those associated with industry (such as transportation) are an important source of airborne PM which includes trace elements, organic and elemental carbon, and PAHs. Industry also emits gaseous pollutants which form secondary aerosol in the atmosphere. Most published studies have employed chemical mass balance (CMB), positive matrix factorization (PMF) and/or principal component analysis (PCA) models as source apportionment tools. These receptor models were mostly applied to fine particulate matter (PM2.5) and PM10 compositional data, particularly the inorganic constituents. Some studies have combined two or more of these receptor models, which provides useful information on the uncertainties associated with different models. Industry has been reported to contribute from 0 to 70% of PM mass at industrial sites. It appears that some studies are unsuccessful in apportioning PM from industry, e.g., unable to distinguish industrial emissions from other sources. A critical evaluation of the literature data also showed that the choice of appropriate tracers for industry, both generically and for specific industries, varies between different PM source apportionment studies. This is not surprising considering the significant difference in source profiles of PM from different types of industry, which may compromise source apportionment of industrial emissions using CMB with non-local source profiles. It may also affect the attribution of industrial emissions in multivariate statistical models (e.g. PMF and PCA). It is concluded that a general classification of the source “industry” is rarely appropriate for PM source apportionment. Indeed, such studies may even need to consider the different processes within a particular industry, such as a steelworks, which emit PM with significantly different chemical signatures. It is suggested that future source apportionment studies should make every effort to measure source profiles of PM from different industrial processes, and where possible, use multiple models in order to more accurately apportion the source emissions from industry.
Original languageEnglish
Pages (from-to)109-120
JournalAtmospheric Environment
Volume97
Early online date1 Aug 2014
DOIs
Publication statusPublished - Nov 2014

Keywords

  • Source apportionment
  • Industrial emissions
  • Receptor modelling
  • Metals
  • Particulate matter
  • Steel industry

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