Department of Mechanical Engineering, Colorado State University, Fort Collins, Colorado 80523, United States.
Aerodyne Research Inc., Billerica, Massachusetts 01821, United States.
Environ Sci Technol. 2022 May 17;56(10):6262-6273. doi: 10.1021/acs.est.1c08520. Epub 2022 May 3.
Secondary organic aerosol (SOA) data gathered in environmental chambers (ECs) have been used extensively to develop parameters to represent SOA formation and evolution. The EC-based parameters are usually constrained to less than one day of photochemical aging but extrapolated to predict SOA aging over much longer timescales in atmospheric models. Recently, SOA has been increasingly studied in oxidation flow reactors (OFRs) over aging timescales of one to multiple days. However, these OFR data have been rarely used to validate or update the EC-based parameters. The simultaneous use of EC and OFR data is challenging because the processes relevant to SOA formation and evolution proceed over very different timescales, and both reactor types exhibit distinct experimental artifacts. In this work, we show that a kinetic SOA chemistry and microphysics model that accounts for various processes, including wall losses, aerosol phase state, heterogeneous oxidation, oligomerization, and new particle formation, can simultaneously explain SOA evolution in EC and OFR experiments, using a single consistent set of SOA parameters. With α-pinene as an example, we first developed parameters by fitting the model output to the measured SOA mass concentration and oxygen-to-carbon (O:C) ratio from an EC experiment (<1 day of aging). We then used these parameters to simulate SOA formation in OFR experiments and found that the model overestimated SOA formation (by a factor of 3-16) over photochemical ages ranging from 0.4 to 13 days, when excluding the abovementioned processes. By comprehensively accounting for these processes, the model was able to explain the observed evolution in SOA mass, composition (i.e., O:C), and size distribution in the OFR experiments. This work suggests that EC and OFR SOA data can be modeled consistently, and a synergistic use of EC and OFR data can aid in developing more refined SOA parameters for use in atmospheric models.
二次有机气溶胶(SOA)数据在环境舱(EC)中收集,已被广泛用于开发参数来表示 SOA 的形成和演化。基于 EC 的参数通常限制在不到一天的光化学老化,但外推到大气模型中预测 SOA 的老化时间要长得多。最近,SOA 在氧化流动反应器(OFR)中越来越多地进行了研究,老化时间尺度为 1 至数天。然而,这些 OFR 数据很少被用于验证或更新基于 EC 的参数。同时使用 EC 和 OFR 数据具有挑战性,因为与 SOA 形成和演化相关的过程在非常不同的时间尺度上进行,并且这两种反应器类型都表现出明显的实验假象。在这项工作中,我们表明,一种动力学 SOA 化学和微物理模型,该模型考虑了各种过程,包括壁损失、气溶胶相态、异相氧化、低聚物形成和新粒子形成,能够同时解释 EC 和 OFR 实验中的 SOA 演化,使用一组单一的一致的 SOA 参数。以α-蒎烯为例,我们首先通过将模型输出拟合到 EC 实验中测量的 SOA 质量浓度和氧-碳(O:C)比(<1 天的老化)来开发参数。然后,我们使用这些参数模拟 OFR 实验中的 SOA 形成,发现当排除上述过程时,模型高估了 SOA 形成(3-16 倍)在光化学年龄从 0.4 到 13 天的范围内。通过全面考虑这些过程,该模型能够解释 OFR 实验中观察到的 SOA 质量、组成(即 O:C)和粒径分布的演化。这项工作表明,EC 和 OFR 的 SOA 数据可以一致地建模,并且 EC 和 OFR 数据的协同使用可以有助于开发更精细的大气模型中使用的 SOA 参数。