Aerosol mixing state is one of the most important factors determining the impacts of aerosol particles on aerosol-cloud-climate interactions and human health. The size, composition, and morphology of about 32,000 single particles are analyzed using transmission electron microscopy (TEM) to evaluate per-particle mixing state. Based on the TEM analysis, we quantify aerosol mixing state and examine the impacts of per-particle mixing state on cloud condensation nuclei (CCN) properties and particle deposition efficiency along the human respiratory tract. Assuming homogeneous chemical composition across the aerosol population, a common practice in many global and regional models to various extents, we show that such simplification of mixing state representation could potentially lead to remarkable errors, a maximum of about 90% and 35%, in CCN concentrations and deposition efficiency calculations respectively. Our results from ambient per-particle observations highlight the importance of considering aerosol mixing state in both air quality models and climate models.

气溶胶混合状态是决定气溶胶颗粒对气溶胶-云-气候相互作用和人类健康影响的最重要因素之一。使用透射电子显微镜（TEM）分析了大约32,000个单个颗粒的大小，组成和形态，以评估每个颗粒的混合状态。在TEM分析的基础上，我们量化了气溶胶的混合状态，并检查了每颗粒混合状态对沿人类呼吸道的云凝结核（CCN）性质和颗粒沉积效率的影响。假设整个气溶胶种群中的化学成分均一，这是许多全球和区域模型在不同程度上的普遍做法，那么我们表明，这种简化的混合状态表示法可能会导致显着的误差，最大误差约为90％和35％，分别计算CCN浓度和沉积效率。我们从环境每颗粒观测得到的结果凸显了在空气质量模型和气候模型中考虑气溶胶混合状态的重要性。