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Preprints
https://doi.org/10.5194/acp-2020-1024
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-1024
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Oct 2020

13 Oct 2020

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This preprint is currently under review for the journal ACP.

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

Steven J. Campbell1,2,, Kate Wolfer1,, Battist Utinger1, Joe Westwood2, Zhi-hui Zhang1,2, Nicolas Bukiowiecki1, Sarah S. Steimer2,a, Tuan V. Vu3,b, Jingsha Xu3, Nicholas Straw4, Steven Thomson3, Atallah Elzein5, Yele Sun6, Di Liu3,6, Linjie Li6, Pingqing Fu8, Alastair C. Lewis5,7, Roy M. Harrison3,10, William J. Bloss3, Miranda Loh9, Mark R. Miller4, Zongbo Shi3, and Markus Kalberer1,2 Steven J. Campbell et al.
  • 1Department of Environmental Sciences, University of Basel, Basel, Switzerland
  • 2Department of Chemistry, University of Cambridge, Cambridge, UK
  • 3School of Geography Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
  • 4Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK
  • 5Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, UK
  • 6State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 7National Centre for Atmospheric Science, University of York, York, UK
  • 8Institute of Surface Earth System Science, Tianjin University, Tianjin, China
  • 9Institute of Occupational Medicine, Edinburgh, UK
  • 10Department of Environmental Sciences/Center of Excellence in Environmental Studies, King Abdulaziz University, PO Box 80203, Jeddah, 21589, Saudi Arabia
  • anow at: Department of Environmental Science, Stockholm University, Stockholm, Sweden
  • bnow at: School of Public Health, Imperial College London, London, UK
  • These authors contributed equally to this work.

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 (APHH-Beijing) campaign, and PM2.5 OP was analysed using four acellular methods; ascorbic acid (AA), dithiothreitol (DTT), 2-7-dichlorofluoroscin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Positive correlations of OP normalised per volume of air of all four assays with overall PM2.5 mass was observed, with stronger correlations in the winter compared to the 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 intrinsic mass-normalised OP values as measured by AA and DTT. This indicates that total PM2.5 mass concentrations alone might 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, provides detailed insight into chemical components or 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. Variable selection was used to produce subsets of measurements indicative of PM2.5 sources, and used to model OP response; AA and DTT assays were well predicted by small panels of measurements, and indicated fossil fuel combustion processes, vehicle emissions and biogenic SOA as most influential in the assay response. Through comparative analysis of both mass- and volume-normalised data we demonstrate the importance of also considering mass-normalised OP when correlating with particle composition measurements, which provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis, and which may be more useful in temporal and site comparative contexts.

Steven J. Campbell et al.

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Short summary
Despite vast epidemiological evidence, uncertainty remains regarding the mechanisms of action of aerosol particle toxicity upon exposure. Here, we quantify PM2.5 oxidative potential (OP), a metric widely suggested as a potential measure of particle toxicity, in Beijing, using four acellular assays. We correlate particle OP with a wide range of additional measurements, and using multivariate statistical analysis, highlight specific particle components and sources that influence OP variability.
Despite vast epidemiological evidence, uncertainty remains regarding the mechanisms of action of...
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