International network for coordinating work on the physicochemical properties of molecules and mixtures important for atmospheric particulate matter

协调对大气颗粒物重要的分子和混合物的物理化学性质工作的国际网络

• 批准号: NE/N013794/1
• 负责人: David Topping
• 金额: $ 15.06万
• 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: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FN013794%2F1
• 关键词: International; network; coordinating; work; physicochemical

Predicting the impact of atmospheric aerosols, through their evolving size and chemical composition, relies on using mechanistic models that attempt to predict the partitioning of potentially millions of such compounds between the gas phase and condensed phase. Uncertainties in the physicochemical properties of pure components and condensed phase mixtures affect our ability to accurately predict and resolve this partitioning. How do we tackle such uncertainties? In 2 ongoing NERC grants, a range of fundamental properties of pure components and mixtures (vapour pressures, viscosities and diffusion constants), are being measured with the objective of improving predictions for atmospheric functionalities. Given the urgency of making such measurements, complementary instruments and expertise exists across the EU and North America that is not available through existing NERC projects. Similarly, the laboratory facilities and expertise enabled by the referenced NERC projects are not accessible to such international programmes. Why is the lack of coherence in methodology and expertise a problem? Recent reviews by the international community highlight significant discrepancies between experimental methods. Despite this, there is no coordinated effort to reconcile these differences or to start compiling appropriate data, with appropriate screening, to improve the predictive techniques essential for improving atmospheric aerosol models. Current compiled data are extremely sparse. On top of this, there are no recommended standards to establish accepted criteria for future measurements or an agreed set of modelling tools to determine how accurate the data has to be to predict evolving aerosol properties. Ultimately, we do not know what level of accuracy in properties might be attainable and acceptable. This is a unique opportunity to address these issues internationally whilst directly benefiting existing and future NERC driven programmes. This IOF will catalyse exploitation of data from ongoing NERC grants, consolidating it into new databases built with measurements and expertise from partner organisation, adding value by expanding flexibility and accuracy of predictive techniques. We have identified 3 ongoing and 2 completed NERC grants as detailed in the case for support. Each partner will provide access to their existing measurement and modelling programmes, involvement in evaluation committee meetings, writing publications, hosting researchers to take part in intercomparisons (see letters of support) and supporting engagement with the wider community once the network matures. Whilst we identify activities to take place over a 2-year period, it is crucial to ensure project sustainability. As such, we will not only create new databanks and an agreed set of open source community modelling facilities, but an agreed set of standards for accepting future measurements will be established. We will engage with the global community through open workshops and meetings. The network comprises researchers from: The University of Manchester [lead], University of Bristol [UK-CoI], ETH [Switzerland], Aarhus University [Denmark], Stockholm University [Sweden], Lawrence Berkeley Laboratory [US], Pacific Northwest National Lab [US] and University of British Columbia [Canada].

通过其不断变化的大小和化学成分预测大气气溶胶的影响，依赖于使用机械模型，试图预测潜在的数百万种此类化合物在气相和冷凝相之间的分配。纯组分和凝聚相混合物的物理化学性质的不确定性影响我们准确预测和解决这种分配的能力。我们如何应对这种不确定性？在正在进行的两项NERC赠款中，正在测量纯成分和混合物的一系列基本特性（蒸汽压、粘度和扩散常数），目的是改进对大气功能的预测。鉴于进行此类测量的紧迫性，欧盟和北美存在补充工具和专业知识，而这些工具和专业知识是现有NERC项目无法提供的。同样，这些国际方案也无法利用所提到的NERC项目所提供的实验室设施和专门知识。为什么方法和专门知识缺乏一致性是一个问题？国际社会最近的审查突出了实验方法之间的重大差异。尽管如此，没有协调一致的努力来调和这些差异，或开始汇编适当的数据，进行适当的筛选，以改进对改进大气气溶胶模型至关重要的预测技术。目前汇编的数据极为稀少。除此之外，没有建议的标准来为未来的测量建立可接受的标准，也没有商定的一套建模工具来确定数据的准确性，以预测不断变化的气溶胶特性。最终，我们不知道什么样的精度水平的属性可能是可达到和可接受的。这是一个独特的机会，在国际上解决这些问题，同时直接受益于现有和未来的NERC驱动的计划。该IOF将促进利用来自正在进行的NERC赠款的数据，将其整合到利用合作伙伴组织的测量和专业知识构建的新数据库中，通过扩大预测技术的灵活性和准确性来增加价值。我们已经确定了3个正在进行的和2个已完成的NERC赠款，详见支持案例。每个伙伴都将提供其现有的计量和建模方案，参与评价委员会会议，编写出版物，接待研究人员参加相互比较（见支持函），并在网络成熟后支持与更广泛的社区接触。虽然我们确定了在2年内开展的活动，但确保项目的可持续性至关重要。因此，我们不仅将创建新的数据库和一套商定的开源社区建模设施，还将建立一套商定的标准，用于接受未来的测量。我们将通过公开研讨会和会议与国际社会接触。该网络的研究人员来自：曼彻斯特大学[牵头]、布里斯托大学[UK-CoI]、ETH [瑞士]、奥胡斯大学[丹麦]、斯德哥尔摩大学[瑞典]、劳伦斯伯克利实验室[美国]、太平洋西北国家实验室[美国]和不列颠哥伦比亚省大学[加拿大]。

项目成果

Response to Comment on "Measured Saturation Vapor Pressures of Phenolic and Nitro-Aromatic Compounds".

对“酚类和硝基芳香族化合物的饱和蒸气压测量”评论的回应。

• DOI: 10.1021/acs.est.7b02681
• 发表时间: 2017
• 期刊: Environmental science & technology
• 影响因子: 11.4
• 作者: Topping D

A method for extracting calibrated volatility information from the FIGAERO-HR-ToF-CIMS and its application to chamber and field studies

从 FigAERO-HR-ToF-CIMS 中提取校准挥发性信息的方法及其在腔室和现场研究中的应用

• DOI: 10.5194/amt-2018-255
• 发表时间: 2018
• 作者: Bannan T

An efficient approach for treating composition-dependent diffusion within organic particles

处理有机颗粒内成分依赖性扩散的有效方法

• DOI: 10.5194/acp-2016-1052
• 发表时间: 2017
• 作者: O'Meara S

Measured Saturation Vapor Pressures of Phenolic and Nitro-aromatic Compounds.

• DOI: 10.1021/acs.est.6b06364
• 发表时间: 2017-03
• 期刊: Environmental science & technology
• 影响因子: 11.4
• 作者: T. Bannan;A. M. Booth;Benjamin T. Jones;S. O'Meara;M. Barley;I. Riipinen;Carl J. Percival;D. Topping

A reference data set for validating vapor pressure measurement techniques: Homologous series of polyethylene glycols

用于验证蒸气压测量技术的参考数据集：聚乙二醇同系物

• DOI: 10.5194/amt-2017-224
• 发表时间: 2017
• 作者: Krieger U