PARIS: Process Attribution of Regional Emissions
PARIS: Process Attribution of Regional Emissions
批准号:
10040943
负责人:
金额:
$19.28万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
全世界只有少数几个国家,欧洲只有两个国家(英国和瑞士,通过我们的团队),他们经常使用自下而上(清单)和自上而下(基于大气数据)的方法来报告他们的排放量。巴黎的中心目标是大幅度提高对排放评估这一联合办法的接受程度。我们的目标研究领域,已被证明,通过我们以前的成功,是高价值的库存编译器,或已在以前的项目中仅部分探讨。为了让清单团队在项目早期参与进来,我们专注于氟化气体(F-gases)的新排放估计,这些气体的源分布相对简单,但对数量了解甚少。我们将在欧洲的八个国家推广我们成熟的方法,使用自上而下的约束来评估库存含氟气体模型。对于甲烷和二氧化碳这两种来源混合较为复杂的温室气体,巴黎的研究侧重于将通量归因于特定的源和汇。我们将推进我们世界领先的同位素测量和基于示踪剂的分析方法,为库存团队提供新的信息,以瞄准不确定领域。对于大多数欧洲清单依赖高度简化和不确定的自下而上方法的一氧化二氮温室气体,将提出两个过程级模型,以产生时间和空间分辨的估计数,并将根据同位素数据进行评估。对于重要但复杂的气候强迫因子,有机物气溶胶和炭黑,我们将采取下一步措施,通过开发源解析方法来实现强大的自上而下的排放推断。为了产生最大的影响,我们将以国家清单报告(NIR)年度附件草案的形式综合这些进展,其中包括八个巴黎重点国家。如果获得通过,这将使全球在国家清单报告中列入自上而下的排放量估计数的国家数量增加近四倍。
英文摘要
There are only a few countries worldwide, and only two in Europe (the UK and Switzerland, via our team), who routinely report their emissions using bottom-up (inventory) and top-down (atmospheric data-based) methods together. The central aim of PARIS is to significantly increase the uptake of this joint approach to emissions evaluation. We target research areas that have been shown, through our previous successes, to be of high value to inventory compilers, or have been only partly explored in previous projects. To engage inventory teams early in the project, we focus on new emissions estimates for fluorinated gases (F-gases), which have relatively simple source distributions, but poorly understood magnitudes. We will extend to eight countries across Europe our proven approach in using top down constraints to evaluate inventory F-gas models. For greenhouse gases (GHGs) with a more complex mixture of sources, methane and carbon dioxide, research in PARIS focuses on the attribution of fluxes to particular sources and sinks. We will advance our world leading isotopologue measurements and tracer-based analysis methods, providing inventory teams with new information to target areas of uncertainty. For nitrous oxide, a GHG for which most European inventories rely on highly simplified and uncertain bottom-up methods, two process-level models will be advanced to produce time- and space-resolved estimates that will be evaluated against isotopic data. For the important, but complex, climate forcers, organic matter aerosol and black carbon, we will take the next steps required towards robust top-down emissions inference by developing source apportionment methods. To generate maximum impact, we will synthesise these advances in the form of draft annual Annexes to National Inventory Reports (NIRs) for eight PARIS focus countries. If adopted, this will represent almost a quadrupling of the number of countries globally that include top-down emissions estimates in their NIRs.
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国内基金
海外基金
Neural Process模型的多样化高保真技术研究
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批准号:62306326
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项目类别:青年科学基金项目
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资助金额:30万元
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批准年份:2023
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负责人:王琦
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依托单位:
磁转动超新星爆发中weak r-process的关键核反应
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批准号:12375145
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项目类别:面上项目
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资助金额:52.00万元
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批准年份:2023
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负责人:金仕纶
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依托单位:
多臂Bandit process中的Bayes非参数方法
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批准号:71771089
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项目类别:面上项目
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资助金额:48.0万元
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批准年份:2017
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负责人:吴贤毅
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依托单位: