Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China.

Steven Campbell ,Miranda Loh,Di Liu,Zongbo Shi,Jingsha Xu,Yele Sun,Kate Wolfer,Atallah Elzein,Joe Westwood,Roy M Harrison,Sarah S Steimer,William J Bloss,Nicholas Straw,Pingqing Fu,Tuan V Vu,Battist Utinger,Mark R Miller,Alastair C Lewis,Markus Kalberer,Nicolas Bukowiecki,Steven J Thomson ,Zhi‐Hui Zhang

doi:10.5194/acp-21-5549-2021

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 (μgm−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.

Highlights

Large-scale epidemiological studies have consistently linked the exposure of airborne particulate matter (PM) with a range of adverse human health effects (Hart et al, 2015; Laden et al, 2006; Lepeule et al, 2012)
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 oxidative potential (OP) provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis
Particle-bound reactive oxygen species (ROS) is exogenously delivered into the lung through PM inhalation or can be produced in vivo via redox chemistry initiated by certain particle components, in addition to baseline tissue ROS produced by metabolic processes (Dellinger et al, 2001)

Summary

Introduction

Large-scale epidemiological studies have consistently linked the exposure of airborne particulate matter (PM) with a range of adverse human health effects (Hart et al, 2015; Laden et al, 2006; Lepeule et al, 2012). Large uncertainty remains regarding the physical and chemical characteristics of PM that result in adverse health outcomes upon exposure (Bates et al, 2019). Studies have suggested that oxidative stress promoted by PM components in vivo could be a key mechanism that results in adverse health outcomes (Donaldson and Tran, 2002; Knaapen et al, 2004; Øvrevik et al, 2015). Oxidative stress occurs when excess concentrations of reactive oxygen species (ROS) overwhelm cellular anti-oxidant defences, resulting in an imbalance of the oxidant–antioxidant ratio in favour of the former, which can subsequently lead to inflammation and disease (Knaapen et al, 2004; Li et al, 2003, 2008). The capability of PM to produce ROS with subsequent depletion of anti-oxidants upon inhalation is defined as oxidative potential (OP) (Bates et al, 2019)

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Results