Receptor modelling of both particle composition and size distribution from a background site in London, UK - a two step approach

Research output: Contribution to journalArticlepeer-review

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  • Department of Environmental Sciences / Center of Excellence in Environmental Studies, King Abdulaziz University, PO Box 80203, Jeddah, 21589, Saudi Arabia


Some air pollution datasets contain multiple variables with a range of measurement units, and combined analysis using positive matrix factorization (PMF) can be problematic but can offer benefits through the greater information content. In this work, a novel method is devised and the source apportionment of a mixed unit dataset (PM 10 mass and number size distribution, NSD) is achieved using a novel two-step approach to PMF. In the first step the PM 10 data are PMF-analysed using a source apportionment approach in order to provide a solution which best describes the environment and conditions considered. The time series G values (and errors) of the PM 10 solution are then taken forward into the second step, where they are combined with the NSD data and analysed in a second PMF analysis. This results in NSD data associated with the apportioned PM 10 factors. We exemplify this approach using data reported in the study of Beddows et al. (2015), producing one solution which unifies the two separate solutions for PM 10 and NSD data datasets together. We also show how regression of the NSD size bins and the G time series can be used to elaborate the solution by identifying NSD factors (such as nucleation) not influencing the PM 10 mass.


Original languageEnglish
Pages (from-to)4863-4876
Number of pages14
JournalAtmospheric Chemistry and Physics
Issue number7
Publication statusPublished - 11 Apr 2019


  • PM10, London, PMF, source apportionment, receptor modelling