Sequential Compound Extremes in an Inverse-Seasonal City: A Multi-Reanalysis Framework for Heat–Air Quality Risk Assessment in Ahmedabad, India

Compound heat–pollution extremes (HPE) are conventionally defined as simultaneous high-temperature and high-PM₂.₅ days, a definition that fails for cities with inverse seasonality, where PM₂.₅ peaks in winter and heat peaks in summer. We propose a Sequential Compound Extreme (SCE) framework and apply it to Ahmedabad, India (2019), using daily PM₂.₅ (CAMS, MERRA-2), daily maximum temperature (ERA5), and 1-km monthly PM₂.₅ (Washington University) for chronic exposure assessment. Using matched absolute 90th-percentile thresholds (PM₂.₅ >127.8 µg m⁻³; Tmax >40.7 °C), conventional HPE identified zero simultaneous extreme days. Of 14 winter (Nov–Feb) high-PM₂.₅ episodes, 8 occurred in January–February and were each followed by a summer extreme-heat day (lead time 58–93 days, mean 76); the remaining 6 November–December episodes could not be evaluated against a subsequent summer within the single-year window. Annual chronic PM₂.₅-attributable mortality, estimated via the Integrated Exposure–Response model, was 1,907 excess deaths (IHD 827, stroke 529, COPD 242, lung cancer 78, LRI 232); this reflects annual mean exposure and is not attributed to SCE events. Independent extreme-heat mortality was 313 deaths (37 extreme-heat days), consistent with observed heat-mortality risk escalation in Indian populations (Mazdiyasni et al., 2017). The synergistic mortality fraction from sequential exposure requires distributed lag non-linear models and daily mortality records, identified as essential future work. Spatial analysis revealed stronger PM₂.₅–mortality associations in western industrial corridors, with confounding caveats acknowledged. We propose a three-tier winter-PM preparedness protocol integrated with Ahmedabad's existing Heat Action Plan, providing 58–93 days of preparedness lead time ahead of the climatologically certain hot season. Findings are presented as a case study and transferable analytical approach; cross-city validation in other inverse-seasonal South Asian cities is required.

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