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Improvement of composition and property prediction techniques for for Secondary Organic Aerosol (SOA)

二次有机气溶胶（SOA）成分和性质预测技术的改进

基本信息

批准号：
NE/J009202/1
负责人：
David Topping
金额：
$ 44.06万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2012
资助国家：
英国
起止时间：
2012 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FJ009202%2F1
关键词：
Improvement composition property prediction techniques

项目摘要

Aerosol particles remain highly uncertain contributors to climate change, influencing climate directly by the scattering and absorption of solar radiation and indirectly through their role as cloud condensation nuclei. Atmospheric loading of particulate matter also has serious implications for urban air quality. Historically, it was assumed that aerosol particles were composed only of inorganic material. However, it has been found that organic components may constitute a substantial fraction of the aerosol composition, ranging from 20-60% of the fine particulate matter depending on the location. Condensed organic material is either directly emitted (primary) or formed in-situ by condensation and transformation of low-volatility and semi-volatile products derived from photo-oxidation of anthropogenic and biogenic volatile organic compounds (secondary organic aerosol:SOA). Gas-to-aerosol partitioning, or creation of SOA, is key to determining the chemical composition and loading of aerosol particles. A detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. However, organic material can comprise many thousands, as yet largely unidentified, compounds with a vast range of properties. As a consequence, the chemical and physical processes associated with secondary organic aerosol (SOA) formation are complex and varied, and a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science!Key uncertainties associated with our understanding of SOA formation have been identified. A compound will partition to the particulate phase if its equilibrium vapour pressure is low enough. This is dependent on the pure component vapour pressure, which can further decrease if the compound undergoes condensed phase reactions in the aerosol phase, enhancing gas/particle partitioning. Unfortunately, uncertainties associated with pure component vapour pressures and effective volatility of mixtures are enough to cause uncertainties in aerosol mass spanning up to 4 orders of magnitude. Vapour pressure predictive techniques are largely based on atmospherically irrelevant compounds used within industrial engineering and there is a large gap concerning the rates and importance of postulated relevant condensed phase reactions which we cannot even elucidate on using current analytical laboratory techniques.In this proposal we aim to address these fundamental uncertainties via 1) Measurement of pure component vapour pressures using our well-established and validated method of Knudsen Effusion Mass Spectrometry. The resulting data will be assimilated into the Dortmund Databank (DDB) and new model revisions will be carried out by our industrial partner.2) Directly link chemical composition to volatility within mixtures for the first time3) Assess the complexity required to truly capture the SOA formation in atmospheric models.

气溶胶粒子对气候变化的影响仍然非常不确定，它们通过散射和吸收太阳辐射直接影响气候，并通过其作为云凝结核的作用间接影响气候。大气中颗粒物的含量也对城市空气质量产生严重影响。历史上，人们认为气溶胶粒子仅由无机材料组成。然而，已经发现，有机组分可以构成气溶胶组合物的相当大的部分，取决于位置，范围为细颗粒物质的20-60%。凝结的有机物质要么直接排放（一次），要么是人为和生物挥发性有机化合物光氧化产生的低挥发性和半挥发性产品凝结和转化就地形成的（二次有机气溶胶：SOA）。气-气溶胶分离或SOA的产生是确定气溶胶颗粒的化学成分和负载的关键。因此，需要详细了解SOA的形成、性质和转化，以评估其对大气过程、气候和人类健康的影响。然而，有机材料可以包括成千上万的，但在很大程度上尚未确定的，具有广泛性质的化合物。因此，与二次有机气溶胶（SOA）形成相关的化学和物理过程是复杂和多样的，并且不存在对SOA形成的定量和预测性理解，因此代表了大气科学的主要研究挑战！与我们对SOA形成的理解相关的关键不确定性已经被确定。如果一种化合物的平衡蒸气压足够低，它将分配到颗粒相。这取决于纯组分的蒸气压，如果化合物在气溶胶相中经历冷凝相反应，则蒸气压可进一步降低，从而增强气体/颗粒分配。遗憾的是，与纯组分蒸汽压力和混合物有效挥发性相关的不确定性足以导致气溶胶质量的不确定性跨越4个数量级。蒸汽压预测技术在很大程度上是基于工业工程中使用的与大气无关的化合物，并且关于假定的相关凝聚相反应的速率和重要性存在很大的差距，我们甚至无法使用当前的分析实验室技术来阐明。在本提案中，我们的目标是通过以下方式解决这些基本不确定性：1）使用我们的井测量纯组分蒸汽压;建立并验证了努森效应质谱法。由此产生的数据将被吸收到多特蒙德数据库（DDB）中，我们的工业合作伙伴将进行新的模型修订。2）首次将混合物中的化学成分与挥发性直接联系起来3）评估在大气模型中真正捕获SOA形成所需的复杂性。