Practical Implementation of Novel Analysis Protocols for the Separation of Complex Environmental Mixtures

对成分的测量-即在某一特定区域中存在哪些化学物种、丰度如何-是许多环境科学的基础，从对自然过程的基本了解到对人为污染的来源和影响的评估。这种分析的一个关键要求是它们是具体的-可以识别和独立量化各个物种。这是一项具有挑战性的任务，因为大多数环境混合物（如水，空气）在痕量物种水平上是高度复杂的。我们专注于大气测量，开发了一种新的方法，使用质谱技术来分离复杂环境混合物中的化学物种。我们的方法的基础是故意使目标分子在仪器内以可控和物种依赖的方式片段化或分解，并使用所得的片段化模式来识别通常无法彼此区分的物种。这项工作得到了当前NERC CASE博士研究生项目的支持，该项目由丹尼尔·布兰克霍恩先生（拟议的实习生候选人）与Kore Technology Ltd作为工业合作伙伴联合举办。我们在CASE研究生项目中的工作已经证明了这种方法在理论和控制场景中的潜力。在这个创新实习项目中，我们寻求在此基础上，通过在Kore为Blenkhorn先生提供六个月的职位，在PTR-MS系统中实现方法的实际实施。我们将以用户友好的格式（电子表格模板）实现我们的分离算法，并开发必要的数据收集方法（仪器参数空间扫描），供NERC社区的仪器最终用户应用，使用真实世界的数据集展示其性能，并使由此产生的新工具免费在线提供。因此，实习将增强NERC科学在环境数据优先领域的影响。实习机会还将在商业研发环境中为Blenkhorn先生提供宝贵的技能培训，并为未来使用环境数据提供新的方法。

Measurements of composition - i.e. which chemical species are present, at what abundance, in a given compartment - underpins much environmental science, ranging from fundamental understanding of natural processes through to assessment of the sources and impacts of man-made pollution. A key requirement for such analyses is that they are specific - that individual species can be identified and independently quantified. This can be a challenging task as most environmental mixtures (e.g. water, air) are highly complex at the trace species level.With a focus upon atmospheric measurements, we have developed a new approach to use mass spectrometry techniques to separate chemical species in complex environmental mixtures. The basis of our approach is to deliberately cause target molecules to fragment or break-up within the instrument, in a controllable and species-dependent way, and use the resulting fragmentation pattern to identify species which are not usually distinguishable from each other. This work has been supported by a current NERC CASE PhD studentship, held by Mr Daniel Blenkhorn (proposed intern candidate) in association with Kore Technology Ltd as industrial partner.Our work within the CASE studentship has demonstrated the potential for this approach, in theory and in controlled scenarios. Within this Innovation Internship project, we seek to build upon this to achieve a practical implementation of the methodology within PTR-MS systems, through a six-month placement for Mr Blenkhorn at Kore. We will implement our separation algorithms in a user-friendly format (spreadsheet template), and develop approaches for the necessary data collection (instrument parameter space scanning) for application by instrument end-users across the NERC community, demonstrate their performance using real-world data sets, and make the resulting new tools freely available online. The internship will thus enhance the impact of NERC science in the priority area of Environmental Data. The intern opportunity will also provide valuable skills training in a commercial R&D environment for Mr Blenkhorn, and lead to new approaches to the use of environmental data in future.