Direct Validated Improvement of Atmospheric Aerosol Property Prediction Using Laboratory Measurements

使用实验室测量直接验证改进大气气溶胶特性预测

• 批准号: NE/E018181/1
• 负责人: David Topping
• 金额: $ 44.35万
• 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: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FE018181%2F1
• 关键词: Direct; Validated; Improvement; Atmospheric; Aerosol

Aerosol particles influence climate directly by the scattering and absorption of solar radiation (direct effect) and indirectly through their role as cloud condensation nuclei (indirect effect), the latter effect comprising the largest uncertainty in climate change. Similarly, aerosol particles have a large impact on air quality. Unfortunately, there are many uncertainties which hinder our ability to model the behaviour of aerosol particles and thus asses the impacts they can have. These uncertainties are largely caused by the complexity of organic compounds, which represent a significant fraction of the chemical composition, and subsequent coupling with inorganic compounds. Whilst speciation is difficult we know certain compounds reside in this fraction yet detailed laboratory/theoretical studies focusing on specific parameters are lacking. Without an improved knowledge of basic data it is not possible to predict effects or simplify and / or parameterise aerosol properties with any degree of certainty. However, development of large scale models which aim to assess the effect of aerosols on climate, for example, rely heavily on such parameterisations. Thus, current unavailability of data propagates through to uncertainty in the aerosol impact. The most important uncertainties are in those parameters which dictate the aerosol water content and gas / aerosol partitioning. The former is necessary for predicting the direct and indirect climatic effect; the latter determines the evolving chemical composition of the aerosol and hence is necessary for predicting aerosol loading and composition which is also important for air quality considerations. To determine effects on water uptake below 100% relative humidity, investigations of aqueous thermodynamics are required through measurements / predictions of a quantity known as the water activity, which represents an 'effective' concentration. For predictions of water uptake above 100%RH, the solution surface tension is a crucial parameter for predictions of cloud activation. In describing the changing composition of aerosol particles, it is important to know how readily a compound will partition between the gas and particulate phase. Two parameters are important here. Solute activity coefficients, a measure of chemical interactions taking place in solution, describes how 'comfortable' a compound is in the aqueous aerosol, and is thus important for modelling condensation. Similarly, compounds with low vapour pressure have higher tendency to partition to aerosol particle and is thus an important parameter yet remains highly uncertain. This proposal seeks to conduct a range of detailed laboratory measurements, using well-established techniques, on key parameters which at the present time critically compromise the predictive capability of state of the art models of multicomponent aerosol behaviour. Improvement in the base models and predictive techniques from the laboratory programme will thus find its way directly to improved climate predictions and assesment of air quality.

气溶胶颗粒通过太阳辐射的散射和吸收直接影响气候（直接效应），并通过其作为云凝结核的作用间接影响气候（间接效应），后者影响气候变化的最大不确定性。同样，气溶胶颗粒对空气质量也有很大影响。不幸的是，有许多不确定性阻碍了我们对气溶胶颗粒行为进行建模并评估其影响的能力。这些不确定性很大程度上是由有机化合物的复杂性造成的，有机化合物占化学成分的很大一部分，以及随后与无机化合物的耦合。虽然形态形成很困难，但我们知道某些化合物存在于该部分中，但缺乏针对特定参数的详细实验室/理论研究。如果不加深对基本数据的了解，就不可能以任何程度的确定性来预测效果或简化和/或参数化气溶胶特性。然而，旨在评估气溶胶对气候影响的大型模型的开发在很大程度上依赖于此类参数化。因此，当前数据的不可用会导致气溶胶影响的不确定性。最重要的不确定性在于那些决定气溶胶含水量和气体/气溶胶分配的参数。前者对于预测直接和间接气候影响是必要的；后者决定了气溶胶不断变化的化学成分，因此对于预测气溶胶负荷和成分是必要的，这对于空气质量考虑也很重要。为了确定低于 100% 相对湿度对水吸收的影响，需要通过测量/预测水活度（代表“有效”浓度）的量来研究水热力学。对于 100%RH 以上的吸水量预测，溶液表面张力是预测云激活的关键参数。在描述气溶胶颗粒的成分变化时，了解化合物在气相和颗粒相之间分配的容易程度非常重要。这里有两个参数很重要。溶质活度系数是溶液中发生的化学相互作用的量度，描述了化合物在水性气溶胶中的“舒适度”，因此对于冷凝建模非常重要。类似地，低蒸气压的化合物更容易分离成气溶胶颗粒，因此是一个重要的参数，但仍然高度不确定。该提案旨在使用成熟的技术对关键参数进行一系列详细的实验室测量，这些参数目前严重损害了多组分气溶胶行为的最先进模型的预测能力。因此，实验室项目对基础模型和预测技术的改进将直接改善气候预测和空气质量评估。

项目成果

The sensitivity of secondary organic aerosol component partitioning to the predictions of component properties - Part 1: A systematic evaluation of some available estimation techniques

二次有机气溶胶成分分配对成分特性预测的敏感性 - 第 1 部分：对一些可用估计技术的系统评估

• DOI: http://dx.10.5194/acp-10-10255-2010
• 发表时间: 2010
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: McFiggans G

Surfactant effects in global simulations of cloud droplet activation

云滴激活全局模拟中的表面活性剂效应

• DOI: http://dx.10.1029/2011gl050467
• 发表时间: 2012
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Prisle N

Solid state and sub-cooled liquid vapour pressures of substituted dicarboxylic acids using Knudsen Effusion Mass Spectrometry (KEMS) and Differential Scanning Calorimetry

使用克努森流出质谱 (KEMS) 和差示扫描量热法测定取代二羧酸的固态和过冷液体蒸气压

• DOI: 10.5194/acp-10-4879-2010
• 发表时间: 2010-05-26
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: A. M. Booth;M. Barley;D. Topping;G. Mcfiggans;A. Garforth;C. Percival
• 通讯作者: C. Percival

The Kelvin versus the Raoult Term in the Köhler Equation

科勒方程中的开尔文项与拉乌尔项

• DOI: http://dx.10.1175/2008jas2720.1
• 发表时间: 2008
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Stratmann F

Surface tension of mixed inorganic and dicarboxylic acid aqueous solutions at 298.15 K and their importance for cloud activation predictions.

298.15 K 下混合无机和二羧酸水溶液的表面张力及其对云激活预测的重要性。

• DOI: 10.1039/b906849j
• 发表时间: 2009-09-02
• 期刊: Physical chemistry chemical physics : PCCP
• 作者: A. M. Booth;D. Topping;G. Mcfiggans;C. Percival
• 通讯作者: C. Percival