Novel informatic software for automated aerosol component property predictions and ensemble predictions for direct model - measurement comparison

大气气溶胶粒子，或悬浮在大气中的颗粒物质，是地球气候系统中非常重要但又高度不确定的组成部分，也是空气质量的关键决定因素。决定这些高度不确定的影响的性质在最基本的层面上与可能存在于粒子中的化学成分有关。无机和有机材料都可以在气相和颗粒相之间转移。无机物只限于几种为人熟知的化合物。然而，有机材料可以包含成千上万的化合物，这些化合物大部分尚未被识别，具有广泛的特性。由于大气气溶胶成分的复杂性和多样性，量化决定其高度不确定的气候和人类健康影响的特性需要开发和应用新的技术应用，例如这里提出的信息软件。首先，我们必须能够预测微粒物质中可以存在多少个成分。具体地说，预测气溶胶的演变需要计算气相和颗粒相之间所有成分的分布，这反过来又需要了解所有成分的蒸汽压力和其他热力学性质。此外，气溶胶的物理性质决定其气候影响，需要详细了解所有成分的基本性质。成千上万的单个气溶胶成分确保了对这些特性进行明确的人工计算是费力、耗时的，而且往往是不可能的。因此，自动化是必要的。其次，为了确定关键成分并解决其对环境的影响，我们必须能够复制在真实/模拟大气中测量到的化学特性。目前还没有对大气气溶胶的单个有机成分进行全面的实验测定，导致对混合物的“化学特征”进行间接测量。通过组分性质估计的自动化，结合气体/气溶胶转移模型，这些由最先进的大气采样仪器确定的“化学特征”将得到预测。这将通过计算仪器响应函数与所有组件的预测丰度来实现。同样，由于涉及的数量庞大，每个单独组件的仪器响应函数的预测（和组合）适合自动化。信息学套件将使用灵活的高级可移植编程语言和开源化学信息学包构建，旨在为每种属性估计方法提取适当的亚分子信息。

Atmospheric aerosol particles, or particulate matter suspended in the atmosphere, are highly important yet highly uncertain components of the earths climate system and key determinants of air quality. Properties which determine these highly uncertain impacts are linked at the most fundamental level to the chemical components which may reside in the particle. Both inorganic and organic material can transfer between the gas and particle phase. Inorganic material is restricted to a few well-understood compounds. However, organic material can comprise many thousands, as yet largely unidentified, compounds with a vast range of properties. Owing to the complexity and diversity of atmospheric aerosol components, quantification of the properties that determine their highly uncertain climatic and human health impacts requires the development and application of novel technological applications such as the informatic software proposed here. Firstly, we must be able to predict how ever many thousands of components can exist in particulate matter. Specifically, predicting the evolution of aerosol requires calculation of the distribution of all components between the gas and particle phases which in turn requires knowledge of all component vapour pressures and other thermodynamic properties. Furthermore, the physical properties of the aerosol determining their climatic impacts require detailed knowledge of fundamental properties of all components. The many thousands of individual aerosol components ensure that explicit manual calculation of these properties is laborious, time-consuming and often impossible. Thus, automation is necessary. Secondly, to identify key components and resolve their environmental impacts we must be able to replicate chemical characteristics measured in real/simulated atmospheres. A comprehensive experimental determination of individual organic components of atmospheric aerosols is not available, leading to indirect measurements on 'chemical signatures' of mixtures. Through automation of component property estimation, combined with a gas/aerosol transfer model, these 'chemical sigmatures' as determined by state-of-the-science atmospheric sampling instrumentation will be predicted. This will be achieved by calculating instrument response functions with the predicted abundance of all components. Again, the prediction (and combination) of instrument response functions for each individual component lends itself to automation due to the vast numbers involved. The informatics suite will be built using a flexible high-level portable programming language and an open source chemical informatics package that is designed to allow extraction of appropriate sub-molecular information relevant for each property estimation method.