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
世界上只有少数几个国家,欧洲只有两个国家(英国和瑞士,通过我们的团队),经常使用自下而上(清单)和自上而下(基于大气数据)的方法一起报告他们的排放量。《巴黎协定》的中心目标是大大提高对这种联合排放评估方法的采用。我们的目标研究领域已经显示,通过我们以前的成功,是高价值的库存编译器,或只是部分探索在以前的项目。为了让清单小组尽早参与项目,我们重点关注氟化气体(f -气体)的新排放估计,这些气体的来源分布相对简单,但对其量级的了解很少。我们将在欧洲的八个国家推广我们行之有效的方法,即使用自顶向下的约束来评估库存含氟气体模型。对于来源更为复杂的温室气体(甲烷和二氧化碳),巴黎协定的研究侧重于将通量归属于特定的来源和汇。我们将推进世界领先的同位素测量和基于示踪剂的分析方法,为库存团队提供针对不确定区域的新信息。对于一氧化二氮这种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温室气体,将推进两个过程级模型,以产生时间和空间分辨率的估算,并将根据同位素数据进行评估。对于重要但复杂的气候因素,有机物质气溶胶和黑碳,我们将通过开发源分配方法,采取下一步必要的措施,实现强有力的自上而下的排放推断。为了产生最大的影响,我们将以《巴黎协定》八个重点国家国家清单报告年度附件草案的形式综合这些进展。如果被采纳,这将意味着全球将自上而下的排放估算纳入近红外光谱的国家数量几乎翻了两番。
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: