Direct Validated Improvement of Atmospheric Aerosol Property Prediction Using Laboratory Measurements

气溶胶粒子通过太阳辐射的散射和吸收直接影响气候(直接影响)，并通过其作为云凝结核的作用间接影响气候(间接影响)，后者的影响构成气候变化中最大的不确定性。同样，气溶胶颗粒对空气质量也有很大影响。不幸的是，有许多不确定因素阻碍了我们对气溶胶粒子行为进行建模，从而评估它们可能产生的影响的能力。这些不确定性在很大程度上是由于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，随后与无机化合物耦合。虽然物种形成很困难，但我们知道某些化合物存在于这一组分中，但缺乏侧重于特定参数的详细实验室/理论研究。如果不改进对基本数据的了解，就不可能预测效果，也不可能以任何程度的确定性简化和/或参数化气溶胶属性。然而，例如，旨在评估气溶胶对气候影响的大型模式的开发在很大程度上依赖于这样的参数化。因此，目前无法获得的数据传播到气溶胶影响中的不确定性。最重要的不确定因素是决定气溶胶水分含量和气体/气溶胶分配的参数。前者对于预测直接和间接的气候影响是必要的；后者决定了气溶胶的化学成分的演变，因此对于预测气溶胶的含量和组成是必要的，这对空气质量的考虑也很重要。为了确定100%相对湿度以下对吸水率的影响，需要通过测量/预测被称为水活度的量来研究水的热力学，水活度表示有效浓度。对于100%相对湿度以上的水吸收的预测，溶液表面张力是预测云激活的关键参数。在描述气溶胶颗粒组成的变化时，重要的是要知道化合物在气相和颗粒相之间分配的难易程度。这里有两个重要的参数。溶质活度系数是衡量溶液中发生的化学作用的一个指标，它描述了化合物在水气溶胶中的舒适程度，因此对冷凝模型很重要。同样，低蒸汽压的化合物有更高的分配到气溶胶颗粒的倾向，因此是一个重要的参数，但仍然高度不确定。这项建议寻求利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最先进的多组分气溶胶行为模型的预测能力。因此，实验室方案的基础模式和预测技术的改进将直接促进气候预测和空气质量评估的改进。

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.