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Using GECKO-A to derive mechanistic understanding of secondary organic aerosol formation from the ubiquitous but understudied camphene

机译:使用Gecko-A从普遍但被覆盖物中的二次有机气溶胶形成的机械理解

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Camphene, a dominant monoterpene emitted from both biogenic and pyrogenic sources, has been significantly understudied, particularly in regard to secondary organic aerosol (SOA) formation. When camphene represents a significant fraction of emissions, the lack of model parameterizations for camphene can result in inadequate representation of gas-phase chemistry and underprediction of SOA formation. In this work, the first mechanistic study of SOA formation from camphene was performed using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). GECKO-A was used to generate gas-phase chemical mechanisms for camphene and two well-studied monoterpenes, α -pinene and limonene, as well as to predict SOA mass formation and composition based on gas/particle partitioning theory. The model simulations represented observed trends in published gas-phase reaction pathways and SOA yields well under chamber-relevant photooxidation and dark ozonolysis conditions. For photooxidation conditions, 70?% of the simulated α -pinene oxidation products remained in the gas phase compared to 50?% for limonene, supporting model predictions and observations of limonene having higher SOA yields than α -pinene under equivalent conditions. The top 10 simulated particle-phase products in the α -pinene and limonene simulations represented 37?%–50?% of the SOA mass formed and 6?%–27?% of the hydrocarbon mass reacted. To facilitate comparison of camphene with α -pinene and limonene, model simulations were run under idealized atmospheric conditions, wherein the gas-phase oxidant levels were controlled, and peroxy radicals reacted equally with HO 2 and NO. Metrics for comparison included gas-phase reactivity profiles, time-evolution of SOA mass and yields, and physicochemical property distributions of gas- and particle-phase products. The controlled-reactivity simulations demonstrated that?(1) in the early stages of oxidation, camphene is predicted to form very low-volatility products, lower than α -pinene and limonene, which condense at low mass loadings; and (2) the final simulated SOA yield for camphene (46?%) was relatively high, in between α -pinene (25?%) and limonene (74?%). A 50?% α -pinene? + ?50?% limonene mixture was then used as a surrogate to represent SOA formation from camphene; while simulated SOA mass and yield were well represented, the volatility distribution of the particle-phase products was not. To demonstrate the potential importance of including a parameterized representation of SOA formation by camphene in air quality models, SOA mass and yield were predicted for three wildland fire fuels based on measured monoterpene distributions and published SOA parameterizations for α -pinene and limonene. Using the 50 / 50 surrogate mixture to represent camphene increased predicted SOA mass by 43?%–50?% for black spruce and by 56?%–108?% for Douglas fir. This first detailed modeling study of the gas-phase oxidation of camphene and subsequent SOA formation highlights opportunities for future measurement–model comparisons and lays a foundation for developing chemical mechanisms and SOA parameterizations for camphene that are suitable for air quality modeling.
机译:樟烯是一种从生物和热原子源发出的主要单分体,已经得到了显着的描述,特别是关于二次有机气溶胶(SOA)形成。当樟烯代表大量排放时,樟树的模型参数缺乏可能导致气相化学的表示和SOA形成的潜在欠鉴定。在这项工作中,使用发电机在大气中的明确化学和有机动力学(Gecko-A)中的明确化学和动力学进行了来自樟树的第一机制研究。 Gecko-A用于为Camphene和两种研究的单萜,α-戊烯和柠檬烯产生气相化学机制,以及基于气体/粒子分配理论预测SOA批量形成和组成。模拟模拟代表出现出版的气相反应途径和SOA在腔室相关光氧化和暗臭臭氧条件下产生的趋势。对于光氧化条件,70〜%的模拟α-丁烯氧化产物保持在气相中,与50μl的柠檬烯相比,支持模型预测和柠檬烯的观察,其在等同条件下具有比α-烯烯更高的SOA产率。 α-烯烃和柠檬烯模拟中的前10个模拟粒子相产物表示为形成的SOA质量的37〜%-50?%,6μm-27?%的烃质量反应。为了便于蛋白与α-丁烯和柠檬烯的比较,在理想化大气条件下运行模型模拟,其中控制气相氧化水平,并且过氧自由基与HO 2同样反应。用于比较的度量包括气相反应性谱,SOA质量和产量的时间演变,以及气体和颗粒产物的物理化学性质分布。受控反应性模拟证明?(1)在氧化的早期阶段,预计樟树形成非常低挥发性产物,低于α-烯烃和柠檬烯,在低质量载荷下冷凝。 (2)α-己烯(25μm)和柠檬烯(74〜%)之间的最终模拟SOA产量相对较高,在α-己烯烯(25μl)和柠檬烯之间相对较高。一个50?%α-己烯烯?然后使用+ +(50μl%的柠檬烯混合物用作替代物,以表示樟烯的SOA形成;虽然模拟SOA质量和产量很好地表示,但颗粒相产品的挥发性分布不是。为了证明包括樟树在空气质量模型中包括SOA形成的参数化表示的潜在重要性,基于测量的单萜分布和出版的SOA参数化,为α-丁烯和柠檬烯的SOA参数化预测SOA质量和产量。使用50/50替代混合物代表Camphene将预测的SOA质量增加了43〜50-%的黑色云杉,Douglas FIR的56〜108倍。这首先详细建模研究樟树和随后的SOA形成凸显了未来测量模型比较的机会,为开发适用于空气质量建模的樟树的化学机制和SOA参数提供了基础。

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