A hybrid source apportionment strategy using positive matrix factorization (PMF) and molecular marker chemical mass balance (MM-CMB) models

Lu, Zhaojie; Liu, Qingyang; Xiong, Ying; Huang, Fan; Zhou, Jiabin; Schauer, James J.

A hybrid source apportionment strategy using positive matrix factorization (PMF) and molecular marker chemical mass balance (MM-CMB) models

2018

The molecular marker-based chemical mass balance (MM-CMB) method performs well in the source apportionment of organic carbon (OC) but has some difficulty with contributions from primary sources to inorganic secondary ions when apportioning PM2.5 (particles with aerodynamic diameter of 2.5 μm or less) sources. Positive matrix factorization (PMF) with the input of inorganic and organic tracers can properly estimate the contributions of primary and secondary sources to inorganic secondary ions; however, PMF is unable to apportion several PM2.5 sources with large fractions of organic carbon and few elemental compositions. In this study regarding data collected in 2011 and 2012 at three sites in Wuhan, China, the MM-CMB model was used to apportion OC in the PM2.5, and the PMF model was used to apportion the inorganic ions (sulfate, nitrate, and ammonia), dust, and EC. The source contributions of PM2.5 were estimated by reconstructing masses of bulk chemical components that had been apportioned to real-world sources using suitable source apportionment methods. Good performance of this hybrid source apportionment strategy was observed with ten resolved factors, explaining 70–80% of measured PM2.5 mass on average. The hybrid strategy takes the advantages of both models in PM2.5 source apportionment and yields unique source apportionment results for PM2.5 bulk chemical components, which could provide new information for optimizing air quality regulations for the emission abatement of target PM mass and compositions for countries around the world.

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