Temperature-dependent composition of summertime PM_2.5 in observations and model predictions across the Eastern U.S

Throughout the U.S., summertime fine particulate matter (PM_2.5) exhibits a strong temperature (T) dependence. Reducing the PM_2.5 enhancement with T could reduce the public health burden of PM_2.5 now and in a warmer future. Atmospheric models are a critical tool for probing the processes and components driving observed behaviors. In this work, we describe how observed and modeled aerosol abundance and composition varies with T in the present-day Eastern U.S. with specific attention to the two major PM_2.5 components: sulfate (SO₄ ^2-) and organic carbon (OC). Observations in the Eastern U.S. show an average measured summertime PM_2.5-T sensitivity of 0.67 microg/m³/K, with CMAQ v5.4 regional model predictions closely matching this value. Observed SO₄ ^2- and OC also increase with T; however, the model has component-specific discrepancies with observations. Specifically, the model underestimates SO₄ ^2- concentrations and their increase with T while overestimating OC concentrations and their increase with T. Here, we explore a series of model interventions aimed at correcting these deviations. We conclude that the PM_2.5-T relationship is driven by inorganic and organic systems that are highly coupled, and it is possible to design model interventions to simultaneously address biases in PM_2.5 component concentrations as well as their response to T.