Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China
Authors: Campbell Steven J. , Wolfer Kate , Utinger Battist , Westwood Joe , Zhang Zhi-Hui , Bukowiecki Nicolas , Steimer Sarah S. , Vu Tuan V. , Xu Jingsha , Straw Nicholas , Thomson Steven , Elzein Atallah , Sun Yele , Liu Di , Li Linjie , Fu Pingqing , Lewis Alastair C. , Harrison Roy M. , Bloss William J. , Loh Miranda , Miller Mark R. , Shi Zongbo , Kalberer Markus 
Published: April 2021

Abstract. Epidemiological studies have consistently linked exposure
to PM2.5 with adverse health effects. The oxidative potential (OP) of
aerosol particles has been widely suggested as a measure of their potential
toxicity. Several acellular chemical assays are now readily employed to
measure OP; however, uncertainty remains regarding the atmospheric
conditions and specific chemical components of PM2.5 that drive OP. A
limited number of studies have simultaneously utilised multiple OP assays
with a wide range of concurrent measurements and investigated the
seasonality of PM2.5 OP. In this work, filter samples were collected
in winter 2016 and summer 2017 during the atmospheric pollution and human
health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP
was analysed using four acellular methods: ascorbic acid (AA),
dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and
electron paramagnetic resonance spectroscopy (EPR). Each assay reflects
different oxidising properties of PM2.5, including particle-bound reactive oxygen species
(DCFH), superoxide radical production (EPR) and catalytic redox chemistry
(DTT/AA), and a combination of these four assays provided a detailed overall
picture of the oxidising properties of PM2.5 at a central site in
Beijing. Positive correlations of OP (normalised per volume of
air) of all four assays with overall PM2.5 mass were observed, with
stronger correlations in winter compared to summer. In contrast, when OP
assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µg m−3) were found to have lower
mass-normalised OP values as measured by AA and DTT. This finding supports
that total PM2.5 mass concentrations alone may not always be the best
indicator for particle toxicity. Univariate analysis of OP values and an
extensive range of additional measurements, 107 in total, including
PM2.5 composition, gas-phase composition and meteorological data,
provided detailed insight into the chemical components and atmospheric
processes that determine PM2.5 OP variability. Multivariate
statistical analyses highlighted associations of OP assay responses with
varying chemical components in PM2.5 for both mass- and
volume-normalised data. AA and DTT assays were well predicted by a small set
of measurements in multiple linear regression (MLR) models and indicated
fossil fuel combustion, vehicle emissions and biogenic secondary organic
aerosol (SOA) as influential particle sources in the assay response. Mass
MLR models of OP associated with compositional source profiles predicted OP
almost as well as volume MLR models, illustrating the influence of mass
composition on both particle-level OP and total volume OP. Univariate and
multivariate analysis showed that different assays cover different chemical
spaces, and through comparison of mass- and volume-normalised data we
demonstrate that mass-normalised OP provides a more nuanced picture of
compositional drivers and sources of OP compared to volume-normalised
analysis. This study constitutes one of the most extensive and comprehensive
composition datasets currently available and provides a unique opportunity
to explore chemical variations in PM2.5 and how they affect both
PM2.5 OP and the concentrations of particle-bound reactive oxygen species.