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Evaluating the impact of new observational constraints on P-S/IVOC emissions, multi-generation oxidation, and chamber wall losses on SOA modeling for Los Angeles, CA

机译:在加利福尼亚州洛杉矶评估新的观测约束对P-S / IVOC排放,多代氧化和室壁损失对SOA建模的影响

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摘要

Secondary organic aerosol (SOA) is an important contributor to fineparticulate matter (PM) mass in polluted regions, and its modeling remains poorly constrained. A box model is developed that uses recently publishedliterature parameterizations and data sets to better constrain andevaluate the formation pathways and precursors of urban SOA duringthe CalNex 2010 campaign in Los Angeles. When using the measurementsof intermediate-volatility organic compounds (IVOCs) reported in Zhao et al. (2014) and of semi-volatile organic compounds (SVOCs) reported inWorton et al. (2014) the model is biased high at longerphotochemical ages, whereas at shorter photochemical ages it isbiased low, if the yields for VOC oxidation are not updated. Theparameterizations using an updated version of the yields, whichtakes into account the effect of gas-phase wall losses inenvironmental chambers, show model–measurement agreement at longerphotochemical ages, even though some low bias at short photochemicalages still remains. Furthermore, the fossil and non-fossil carbon splitof urban SOA simulated by the model is consistent with measurementsat the Pasadena ground site.Multi-generation oxidation mechanisms are often employed in SOAmodels to increase the SOA yields derived from environmental chamberexperiments in order to obtain better model–measurementagreement. However, there are many uncertainties associated withthese aging mechanisms. Thus, SOA formation in the model iscompared to data from an oxidation flow reactor (OFR) in orderto constrain SOA formation at longer photochemical ages thanobserved in urban air. The model predicts similar SOA mass at shortto moderate photochemical ages when the aging mechanisms or theupdated version of the yields for VOC oxidation are implemented. Thelatter case has SOA formation rates that are more consistentwith observations from the OFR though. Aging mechanisms may still play animportant role in SOA chemistry, but the additional mass formed byfunctionalization reactions during aging would need to be offset bygas-phase fragmentation of SVOCs.All the model cases evaluated in this work show a large majority ofthe urban SOA (70–83 %) at Pasadena coming from the oxidationof primary SVOCs (P-SVOCs) and primary IVOCs (P-IVOCs). The importance of these two types of precursors is further supported by analyzing the percentage of SOAformed at long photochemical ages (1.5 days) as a function of theprecursor rate constant. The P-SVOCs and P-IVOCs have rate constantsthat are similar to highly reactive VOCs that have been previouslyfound to strongly correlate with SOA formation potential measured bythe OFR.Finally, the volatility distribution of the total organic mass (gasand particle phase) in the model is compared againstmeasurements. The total SVOC mass simulated is similar to themeasurements, but there are important differences in the measuredand modeled volatility distributions. A likely reason for thedifference is the lack of particle-phase reactions in the model thatcan oligomerize and/or continue to oxidize organic compounds evenafter they partition to the particle phase.
机译:二次有机气溶胶(SOA)是污染区域中细颗粒物(PM)质量的重要贡献者,其建模仍然受约束较弱。开发了一个框模型,该框模型使用最近发布的文献参数化和数据集来更好地约束和评估洛杉矶CalNex 2010活动期间城市SOA的形成途径和前兆。当使用中挥发性有机化合物(IVOC)的测量方法时,Zhao等报道了。 (2014)和沃顿(Worton)等人报道的半挥发性有机化合物(SVOC)。 (2014年),如果不更新VOC氧化的产量,该模型在较长的光化学年龄下会偏高,而在较短的光化学年龄下会偏低。考虑到环境室中气相壁损失的影响,使用产量的更新版本进行的参数化显示了在更长的光化学年龄下的模型-测量一致性,尽管在短光化学寿命下仍然存在一些低偏差。此外,该模型模拟的城市SOA的化石和非化石碳分解与帕萨迪纳地面站点的测量结果一致.SOA模型中经常采用多代氧化机制来增加环境试验获得的SOA产量,以获得更好的模型–测量协议。但是,与这些老化机制相关的不确定因素很多。因此,将模型中的SOA形成与来自氧化流反应器(OFR)的数据进行比较,以便在比城市空气中观察到的更长的光化学年龄上限制SOA的形成。当实施了老化机制或VOC氧化收率的更新版本时,该模型预测了在短至中等光化学年龄下的相似SOA质量。但是,其他情况下的SOA形成速率与OFR的观察结果更加一致。老化机制可能仍在SOA化学中起着重要作用,但是在老化过程中由官能化反应形成的额外质量将需要通过SVOC的气相裂解来抵消。这项工作中评估的所有模型案例均显示,绝大多数城市SOA(70-帕萨迪纳的83%(%)来自主要SVOC(P-SVOC)和主要IVOC(P-IVOC)的氧化。通过分析在长光化学年龄(1.5天)时形成的SOA的百分比作为前体速率常数的函数,进一步支持了这两种类型的前体的重要性。 P-SVOC和P-IVOC的速率常数与高反应性VOC相似,后者以前与OFR测得的SOA形成潜力密切相关。最后,模型中总有机物(气相和颗粒相)的挥发性分布与测量进行比较。模拟的SVOC总质量与测量值相似,但是在测量和建模的波动率分布中存在重要差异。造成这种差异的一个可能原因是模型中缺乏粒子相反应,即使它们分配到粒子相后,它们仍可能低聚和/或继续氧化有机化合物。

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