Non‐Ideal Treatment of Organic Aerosol Reveals Its Missing Sources and Improves PM 2.5 Prediction

Abstract Organic aerosols (OAs) exhibit non‐ideal behaviors that challenge conventional models assuming ideal equilibrium partitioning. This study integrates a unified kinetic framework into WRF‐Chem model to handle non‐ideal evolution of OAs with considering kinetic mass transfer process with multidirectional interactions (particle surface area, volume, molecular weight) governed by Fick's second law. Simulations in winter of the North China Plain (NCP) reveal that non‐ideal treatment enhances condensation of organics species and water vapor, amplifies interactions between OA, aerosol liquid water content (ALWC), and secondary inorganic aerosols (SIA, pSO 4 2− , pNO 3 − and pNH 4 + ). The revised framework reduces mean bias in OA and SIA predictions from normalized mean bias (NMB) of −18.4% to −2.9%, −33.4% to −23.0%, −2.0% to −0.3%, and −35.4% to −30.2%, respectively, achieves better performance in reproducing ALWC with better correlation (from 0.81 to 0.88), and improves PM 2.5 modeling accuracy (NMB from −18.0% to −9.5%) in “2 + 26” city cluster among the NCP. The framework enhances predictions without modifying chemical mechanisms and suggests a potential reductions in direct radiative forcing estimation (−0.77 W/m 2 among the NCP). The findings advocate urgent integrating non‐ideal behavior of OA into air quality models to advance aerosol prediction.