Processes driving the regional sensitivities of summertime PM_2.5 to temperature across the US: new insights from model simulations

<p>The temperature sensitivity of fine particulate matter (PM<span class="inline-formula">_2.5</span>) critically influences air quality and human health under a warming climate, yet models struggle to accurately reproduce observed sensitivities. This study improves the representation of PM<span class="inline-formula">_2.5</span>-temperature relationships in the chemical transport model GEOS-Chem through targeted improvements and analyses of the underlying drivers based on simulations across the contiguous US (2000–2022). Our simulations reveal that chemical production processes, particularly isoprene secondary organic aerosol (SOA) and sulfate formation, determine the magnitude of PM<span class="inline-formula">_2.5</span> sensitivity in the eastern US. In the western US, primary emissions drive the increasing PM<span class="inline-formula">_2.5</span>-temperature sensitivity. Transport processes contribute to interannual variability in PM<span class="inline-formula">_2.5</span> sensitivity across all regions. We quantified the contributions from individual temperature-sensitive processes for the first time. Sulfate concentration plays a pivotal role in modulating the sensitivity of isoprene SOA due to its direct influence on isoprene SOA formation. Furthermore, the increased SO<span class="inline-formula">₂</span> emissions on warm days dictates both the magnitude and variability of sulfate sensitivity in the eastern and central US. In the western US, however, sulfate sensitivity is primarily controlled by the temperature response of hydroxyl radicals (<span class="inline-formula">^{<span class="Radical">⚫</span>}</span>OH). These findings highlight the impact of anthropogenic emission reductions on declining PM<span class="inline-formula">_2.5</span>–temperature sensitivity in the eastern US, improve our understanding of climate-driven air quality changes, and underscore the importance of accurately representing temperature-dependent processes in future air quality projections.</p>