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Air pollution causes over 8 million premature deaths annually, yet global PM 2.5 concentrations persistently exceed WHO guidelines while ground level O 3 increases—highlighting an insufficient understanding of coordinated control. Peroxyacetyl nitrate (PAN) plays a pivotal role in influencing these two pollutants. Despite the inclusion of its fundamental chemistry in chemical transport models (CTMs), uncertainties in key parameters (temperature) lead to persistent discrepancies in simulations. Through a machine learning and causal inference framework applied to four decades of global observations, we identified a critical thermal threshold (287 ± 3.7K) that governs the transition in PAN's chemical regime. Below this threshold, PAN exhibits net accumulation, coinciding with PM 2.5 dominated pollution; above it, PAN undergoes net loss, shifting to a regime of active O 3 formation. This finding is directly relevant to PAN chemistry in the surface and near‐surface environment and provides a valuable reference for evaluating and refining PAN‐related parameterizations in CTMs.
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Shen et al. (2026) studied this question.
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