Multi-Index Attribution of Extreme Winter Air Quality in Beijing, China

High-impact poor air quality events, such as Beijing's so-called “Airpocalypse” in January 2013, demonstrate that short-lived poor air quality events can have significant effects on health and economic vitality. Poor air quality events result from the combination of the emission of pollutants and meteorological conditions favorable to their accumulation, which include limited scavenging, dispersion, and ventilation. The unprecedented nature of events such as the 2013 Airpocalypse, in conjunction with our nonstationary climate, motivate an assessment of whether climate change has altered the meteorological conditions conducive to poor winter air quality in Beijing. Using three indices designed to quantify the meteorological conditions that support poor air quality and drawing on the attribution methods of Diffenbaugh et al. (2017, https://doi.org/10.1073/pnas.1618082114), we assess (i) the contribution of observed trends to the magnitude of events, (ii) the contribution of observed trends to the probability of events, (iii) the return interval of events in the observational record, preindustrial model-simulated climate and historical model-simulated climate, (iv) the probability of the observed trend in the preindustrial and historical model-simulated climates, and (v) the relative influences of anthropogenic forcing and natural variability on the observed trend. We find that anthropogenic influence has had a small effect on the probability of the January 2013 event in all three indices but has increased the probability of a long-term positive trend in two out of three indices. This work provides a framework for both further understanding the role of climate change in air quality and expanding the scope of event attribution.