Abstract

Chemical mass balance (CMB) is one of the most popular methods to apportion the sources of PM2.5. However, the source apportionment results are dependent on the choices of measured chemical species and the source profiles. Here, we explore the sensitivity of CMB results to source profiles by comparing CMB modeling based on organic markers only (OM-CMB) with a combination of organic and inorganic markers (IOM-CMB), using organic and inorganic markers in PM2.5 samples collected in the Chinese megacity of Chengdu. OM-CMB results show that gasoline vehicles, diesel vehicles, industrial coal combustion, resuspended dust, biomass burning, cooking, vegetation detritus, SOA, sulphate, and nitrate contributed to 4 %, 10 %, 15 %, 12 %, 5 %, 3 %, 4 %, 9 %, 10 %, and 20 %, in comparison to 4 %, 11 %, 15 %, 17 %, 6 %, 2 %, 5 %, 10 %, 7 %, and 18 % from IOM-CMB modelling. The temporal variations of PM2.5 contributions from sulphate, nitrate, SOA, gasoline vehicles, and biomass burning, characterized by unique markers and low collinearity, were in good agreement between the OM-CMB and IOM-CMB results. However, resuspended dust estimates from OM-CMB had a poor correlation with that from IOM-CMB, due to the different tracers used. When replacing the source profile for industrial coal combustion with that for from residential sources, the contributions of resuspended dust and residential coal combustion were overestimated because the residential coal combustion profile contained a higher concentration of OC and organic compounds but lower crustal elements. Different source profiles for gasoline vehicles were also evaluated. Our results confirm the superiority of combining inorganic and organic tracers and using up-to-date locally-relevant source profiles in source apportionment of PM.

Highlights

  • IntroductionAtmospheric fine particles (PM2.5) have long been shown to have pronounced effects on human health (Bell et al, 2014; Yang et al, 2019; Hong et al.,2021; Li et al, 2022; Wen et al, 2022)

  • The chemical mass balance (CMB) model approach has been used for source apportionment of PM at many locations, worldwide (Zheng et al, 2002; Perrone et al, 2012; Yin et al, 2015; Chen et al.,2015; Lu et al, 2018; Wu et al, 2020; Wong et al, 2021)

  • The temporal variations of PM2.5 contributions from sulphate, nitrate, SOA, gasoline vehicles, and biomass burning were in good agreement between the organic matter (OM)-CMB and inorganic and organic marker-based CMB (IOM-CMB) results

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Summary

Introduction

Atmospheric fine particles (PM2.5) have long been shown to have pronounced effects on human health (Bell et al, 2014; Yang et al, 2019; Hong et al.,2021; Li et al, 2022; Wen et al, 2022). The chemical mass balance (CMB) model approach has been used for source apportionment of PM at many locations, worldwide (Zheng et al, 2002; Perrone et al, 2012; Yin et al, 2015; Chen et al.,2015; Lu et al, 2018; Wu et al, 2020; Wong et al, 2021). This model has some underlying challenges posed by possible collinearity of source profiles, and relevance of source profiles

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