Seasonal Variation of Aerosol Oxidative Potential in Beijing, China during the APHH Campaign

Abstract

<p>The negative effects of air pollution on human health has been subject to a number of epidemiological studies that consistently link respiratory and cardiovascular diseases to exposure to particulate matter (PM) (Englert, 2004). It is estimated that up to 0.3 million premature deaths per year in Europe and 2.1 million deaths worldwide are the result of exposure to particles with an aerodynamic diameter less than 2.5 μm (PM<sub>2.5</sub>) (Andersson, 2009). However, identifying the specific particle properties responsible for these health effects, such as their physical and physicochemical characteristics, as well as their chemical composition, remains a challenge.</p> <p>One of the leading hypotheses for how particles cause harm is by inducing oxidative stress and inflammation, which can subsequently lead to disease (Øvrevik, 2015). In particular, reactive oxygen species (ROS), which typically refer to a range of species including hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) possibly including organic peroxides, the hydroxyl radical (<sup>.</sup>OH) and superoxide radical (O<sub>2</sub><sup>.-</sup>), may substantially contribute to the oxidative potential (OP) of PM and hence influence their toxicity. An excess of ROS in the lung, introduced or generated via particle exposure, leads to an imbalance of the oxidant-antioxidant ratio in favour of the former, which can subsequently promote oxidative stress. There are a number of acellular methods used routinely to measure aerosol OP, including the dithiothreitol assay (DTT), ascorbic acid assay (AA), 2,7-dichlorofluoroscein/hydrogen peroxidase assay (DCFH/HRP), and electron paramagnetic resonance (EPR) spectroscopy.</p> <p>In this work, the OP of aerosol collected in Beijing, China, in the winter 2016 and summer 2017 during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH) campaign is quantified, with 30 24-hr aerosol filter samples analysed for each season. We use the four aforementioned methods to measure OP<sub>AA</sub>, OP<sub>DTT</sub>, OP<sub>DCFH </sub>and OP<sub>EPR, </sub> and to extensively characterise the seasonal variation of aerosol OP in a megacity. All OP measurements show a significantly stronger correlation with PM<sub>2.5</sub> mass in the winter compared to summer. Furthermore, the OP<sub>AA</sub>, OP<sub>DTT</sub>, OP<sub>DCFH</sub> and OP<sub>EPR</sub> were correlated using univariate and multivariate analysis with a variety of other measurements such as meteorological data, trace gas measurements and aerosol composition measurements including organic aerosol components and x-ray fluorescence elemental analysis.  </p> <p>These results emphasise that the four OP methods applied in this study capture different aspects of aerosol OP between the seasons. As an example, OP<sub>AA</sub> normalised to account for aerosol mass show that aerosol OP<sub>AA</sub> in the winter is higher on average and more variable compared to the summer, whereas OP<sub>DCFH</sub> is more consistent between the winter and summer seasons. OP<sub>AA </sub>also showed a strong correlation with PM<sub>2.5 </sub>mass in the winter (r<sup>2</sup> = 0.91) but correlated poorly in the summer months (r<sup>2</sup> = 0.09), suggesting different aerosol components affect OP<sub>AA </sub>in summer and winter.</p> <p>Englert, N. Toxicol. Lett. <strong>149,</strong> 235–242 (2004).</p> <p>Andersson, C., et al., Atmos. Environ. <strong>43,</strong> 3614–3620 (2009).</p> <p>Øvrevik, J., et al., Biomolecules <strong>5,</strong> 1399–1440 (2015).</p>