OpenGHG: A community platform for greenhouse gas data science

OpenGHG：温室气体数据科学社区平台

• 批准号: NE/V002996/1
• 负责人: Matthew Rigby
• 金额: $ 70.48万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV002996%2F1
• 关键词: OpenGHG; community; platform; greenhouse; gas

With numerous governments, cities, and organisations declaring climate emergencies and net-zero emissions targets, greenhouse gases (GHGs) are now the focus of international geopolitics and UK domestic policies. Furthermore, with the recent identification of violations of the Montreal Protocol, ozone depleting substances (ODS), are receiving renewed attention. It is therefore critically important to be able to analyse GHG and ODS emissions trends, examine spatial patterns, estimate future trajectories, and explore mitigation options in an open, transparent and publicly accessible way. Our proposed project will enable this, using state-of-the-art computing technology to create a platform, "OpenGHG".The estimation of GHG and ODS emissions requires close collaboration between a diverse group of scientists and stakeholders: "bottom-up" methods rely on statistical information collected by governments and industries, combined with scientific studies of the emissions intensity of particular activities, or the development of computer models that describe how human or natural processes produce or absorb GHGs. Complementary "top-down" techniques rely on instruments developed by spectroscopists and analytical chemists, the data from which are analysed along with outputs from meteorological models using advanced statistical methods. The data that is being generated by these diverse research and stakeholder communities is growing rapidly. However, the development of computational tools to help researchers aggregate data from such a wide range of sources and carry out and share analyses has not kept pace. Furthermore, given the sensitive nature of, for example, the inference of national GHG or ODS emissions, these communities must urgently take steps to make their analyses more transparent and reproducible.OpenGHG meets these needs, by providing an open, cloud-based, platform for researchers to share data and analysis methods and publish workflows. Furthermore, we have co-designed with our stakeholders, a range of tools that will facilitate the sharing of research outputs with governments, private companies and the public. The OpenGHG platform will:- Continuously incorporate and standardise up to date GHG and ODS measurements, bottom-up emission estimates, and a range of ancillary information related to GHG and ODS emissions. This data will be pulled automatically, or on demand, from a range of public archives, or pushed to the platform by data providers seeking to analyse or share their own data - Provide a wide range of analysis options, including the ability to design, publish and share custom workflows- Allow production of new top-down and bottom-up emissions estimates by accessing pre-existing and newly developed models and methods incorporated into the platform- Provide users with lower levels of computational expertise an easy-to-use interface for the most useful data analysis and visualisation. This will include comparisons of top-down and bottom-up estimates of emissions from different sectors of the economy, and potential future warming from different emissions scenarios.

随着众多政府、城市和组织宣布气候紧急情况和净零排放目标，温室气体 (GHG) 现在成为国际地缘政治和英国国内政策的焦点。此外，随着最近发现违反《蒙特利尔议定书》的行为，消耗臭氧层物质（ODS）再次受到关注。因此，能够以开放、透明和公开的方式分析温室气体和消耗臭氧层物质排放趋势、检查空间模式、估计未来轨迹并探索缓解方案至关重要。我们提出的项目将利用最先进的计算技术创建一个平台“OpenGHG”来实现这一目标。温室气体和消耗臭氧层物质排放量的估算需要不同的科学家和利益相关者群体之间的密切合作：“自下而上”这些方法依赖于政府和行业收集的统计信息，结合对特定活动排放强度的科学研究，或开发描述人类或自然过程如何产生或吸收温室气体的计算机模型。互补的“自上而下”技术依赖于光谱学家和分析化学家开发的仪器，使用先进的统计方法对仪器中的数据以及气象模型的输出进行分析。这些不同的研究和利益相关者社区生成的数据正在迅速增长。然而，帮助研究人员从如此广泛的来源汇总数据并进行和共享分析的计算工具的发展却没有跟上步伐。此外，考虑到国家温室气体或消耗臭氧层物质排放推断等的敏感性，这些社区必须紧急采取措施，使其分析更加透明和可重复。OpenGHG 通过提供一个开放的、基于云的平台来满足这些需求供研究人员共享数据和分析方法并发布工作流程。此外，我们与利益相关者共同设计了一系列工具，以促进与政府、私营公司和公众分享研究成果。 OpenGHG 平台将： - 持续整合最新的温室气体和消耗臭氧层物质测量、自下而上的排放估算以及一系列与温室气体和消耗臭氧层物质排放相关的辅助信息并使其标准化。这些数据将自动或按需从一系列公共档案中提取，或由寻求分析或共享自己数据的数据提供商推送到平台 - 提供广泛的分析选项，包括设计、发布的能力并共享自定义工作流程 - 通过访问平台中现有的和新开发的模型和方法，允许生成新的自上而下和自下而上的排放估算 - 为计算专业知识水平较低的用户提供易于使用的界面最有用的数据分析和可视化。这将包括对不同经济部门排放量的自上而下和自下而上估计的比较，以及不同排放情景下未来潜在的变暖。

项目成果

A machine learning emulator for Lagrangian particle dispersion model footprints: a case study using NAME

用于拉格朗日粒子分散模型足迹的机器学习模拟器：使用 NAME 的案例研究

• DOI: http://dx.10.5194/egusphere-2022-1174
• 发表时间: 2022
• 作者: Fillola E

Joint inference of CFC lifetimes and banks suggests previously unidentified emissions.

对 CFC 寿命和库存的联合推断表明了先前未确定的排放量。

• DOI: http://dx.10.1038/s41467-021-23229-2
• 发表时间: 2021
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Lickley M

Global emissions of perfluorocyclobutane (PFC-318, c-C4F8) resulting from the use of hydrochlorofluorocarbon-22 (HCFC-22) feedstock to produce polytetrafluoroethylene (PTFE) and related fluorochemicals

全氟环丁烷的全球排放量（PFC-318、

• DOI: http://dx.10.5194/acp-22-3371-2022
• 发表时间: 2022
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: Mühle J

Global Emissions of Perfluorocyclobutane (PFC-318, c-C4F8) Resulting from the Use of Hydrochlorofluorocarbon-22 (HCFC-22) Feedstock to Produce Polytetrafluoroethylene (PTFE) and related Fluorochemicals

全氟环丁烷 (PFC-318, c-C) 的全球排放量

• DOI: http://dx.10.5194/acp-2021-857
• 发表时间: 2021
• 作者: Mühle J

Western European emission estimates of CFC-11, CFC-12 and CCl 4 derived from atmospheric measurements from 2008 to 2021

根据 2008 年至 2021 年大气测量得出的西欧 CFC-11、CFC-12 和 CCl 4 排放估算

• DOI: http://dx.10.5194/acp-23-7383-2023
• 发表时间: 2023
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: Redington A