Figure 4
From: Compound climate-pollution extremes in Santiago de Chile

The rise in the mortality risk associated with heat-ozone compound extremes is larger in affluent communities than in deprived communities in Santiago. (a) Progress of daily excess deaths in adults (aged ≥ 65 years, all socioeconomic strata; upper red line), daily maximum temperature anomalies (dotted red line), and the anomalies of daily maximum 8-h mean ozone concentration at Las Condes station (black line) and at Pudahuel station (gray line). For detrend purposes, daily anomalies and daily excess deaths were computed using the summer average of each year as a reference. Then, daily anomalies and daily excess deaths were averaged over the 30-day warmest period (20 Dec–18 Jan) of the year. The correlation coefficients (R) between the temperature anomaly and the excess deaths (as well as the ozone concentration anomalies) are shown in the plot. (b) Progress of the daily mortality rate in adults (aged ≥ 65 years, all socioeconomic strata; upper red line), the daily maximum temperature (dotted red line), and the daily maximum 8-h mean ozone concentration at Las Condes station (black line) and at Pudahuel station (gray line), over the period 17 Jan 2019 and 30 Jan 2019. The correlation coefficients (R) between the temperature and the mortality rate (as well as the ozone concentration) are shown in the plot. Santiago hit its all-time heat record (38.3 °C) on 26 Jan 2019. (c) Heat-mortality associations for two age strata (upper plot) and for two socioeconomic strata (lower plot). Mortality from all causes was used in this study. Exposure–response associations are estimated as best linear unbiased predictions (see “Methods”) and reported as Relative Risks. Bold lines represent the risks (shading indicates 95% confidence intervals) of exposure to a daily maximum temperature, relative to the risk corresponding to the temperature of minimum mortality (which in Santiago is about 27 °C). In Santiago, the 99th percentile of the daily maximum temperature (summer) is 35 °C. Plots were generated using Python’s Matplotlib library50.