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Modelling non-equilibrium secondary organic aerosol formation and evaporation with the aerosol dynamics, gas- and particle-phase chemistry kinetic multilayer model ADCHAM

机译:使用气溶胶动力学,气体和粒子相化学的非平衡二次有机气溶胶形成和蒸发。

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We have developed the novel Aerosol Dynamics, gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM). The model combines the detailed gas-phase Master Chemical Mechanism version 3.2 (MCMv3.2), an aerosol dynamics and particle-phase chemistry module (which considers acid-catalysed oligomerization, heterogeneous oxidation reactions in the particle phase and non-ideal interactions between organic compounds, water and inorganic ions) and a kinetic multilayer module for diffusion-limited transport of compounds between the gas phase, particle surface and particle bulk phase. In this article we describe and use ADCHAM to study (1) the evaporation of liquid dioctyl phthalate (DOP) particles, (2) the slow and almost particle-size-independent evaporation of α-pinene ozonolysis secondary organic aerosol (SOA) particles, (3) the mass-transfer-limited uptake of ammonia (NH3) and formation of organic salts between ammonium (NH4+) and carboxylic acids (RCOOH), and (4) the influence of chamber wall effects on the observed SOA formation in smog chambers. ADCHAM is able to capture the observed α-pinene SOA mass increase in the presence of NH3(g). Organic salts of ammonium and carboxylic acids predominantly form during the early stage of SOA formation. In the smog chamber experiments, these salts contribute substantially to the initial growth of the homogeneously nucleated particles. The model simulations of evaporating α-pinene SOA particles support the recent experimental findings that these particles have a semi-solid tar-like amorphous-phase state. ADCHAM is able to reproduce the main features of the observed slow evaporation rates if the concentration of low-volatility and viscous oligomerized SOA material at the particle surface increases upon evaporation. The evaporation rate is mainly governed by the reversible decomposition of oligomers back to monomers. Finally, we demonstrate that the mass-transfer-limited uptake of condensable organic compounds onto wall-deposited particles or directly onto the Teflon chamber walls of smog chambers can have a profound influence on the observed SOA formation. During the early stage of the SOA formation the wall-deposited particles and walls themselves serve as an SOA sink from the air to the walls. However, at the end of smog chamber experiments the semi-volatile SOA material may start to evaporate from the chamber walls. With these four model applications, we demonstrate that several poorly quantified processes (i.e. mass transport limitations within the particle phase, oligomerization, heterogeneous oxidation, organic salt formation, and chamber wall effects) can have a substantial influence on the SOA formation, lifetime, chemical and physical particle properties, and their evolution. In order to constrain the uncertainties related to these processes, future experiments are needed in which as many of the influential variables as possible are varied. ADCHAM can be a valuable model tool in the design and analysis of such experiments.
机译:我们开发了用于实验室研究(AdCham)的新型气溶胶动力学,气体和粒子相化学模型。该模型结合了详细的气相母材化学机制3.2版(MCMV3.2),气溶胶动力学和颗粒相化学模块(其考虑酸催化的低聚,非均相氧化反应,在颗粒相中和有机物之间的非理想相互作用化合物,水和无机离子)和动力学多层模块,用于扩散限制的化合物在气相,颗粒表面和颗粒体相之间的化合物。在本文中,我们描述和使用AdCham学习(1)邻苯二甲酸盐(DOP)颗粒的蒸发蒸发,(2)α-Pine臭氧臭氧溶解二次有机气溶胶(SOA)颗粒的缓慢和几乎粒径无关蒸发, (3)氨(NH3)的质量转移限制吸收和铵(NH4 +)和羧酸(RCOOH)之间的有机盐的形成,以及(4)腔室壁效应对烟雾室中观察到的SOA形成的影响。 AdCham能够在NH 3(G)存在下观察到的α-Pinene SOA质量增加。铵和羧酸的有机盐主要在SOA形成的早期阶段形成。在烟雾室实验中,这些盐基本上有助于均匀核颗粒的初始生长。蒸发α-脊烯SOA颗粒的模型模拟支持最近这些颗粒具有半固体焦油类非晶相状态的实验结果。如果在蒸发时颗粒表面的低挥发性和粘性低聚的SOA材料的浓度增加,则AdCham能够再现观察到的缓慢蒸发速率的主要特征。蒸发速率主要由低聚物恢复单体的可逆分解。最后,我们证明了可冷凝有机化合物在壁沉积的颗粒上或直接在烟雾室的Teflon室壁上的质量转移限制的吸收可以对观察到的SOA形成产生深远的影响。在SOA形成的早期阶段,壁沉积的颗粒和壁本身用作从空气到墙壁的SOA下沉。然而,在烟雾室实验结束时,半挥发性SOA材料可以开始从腔室壁蒸发。通过这四种模型应用,我们证明了几种量化的方法(即颗粒相,低聚,非均相氧化,有机盐形成和室壁效应的大规模运输限制)可对SOA形成,寿命,化学物质产生重大影响和物理颗粒特性及其进化。为了限制与这些过程相关的不确定性,需要未来的实验,其中尽可能多地改变许多有影响力的变量。 AdCham可以成为这些实验的设计和分析中的有价值的模型工具。

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