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全球大气研究排放数据库中的高时间分辨率时间剖面。

High resolution temporal profiles in the Emissions Database for Global Atmospheric Research.

机构信息

European Commission, Joint Research Centre (JRC), Ispra, Italy.

Institute of Energy Economics and Rational Energy Use (IER), Universität Stuttgart, Hessbruehlstr. 49a, 70565, Stuttgart, Germany.

出版信息

Sci Data. 2020 Apr 17;7(1):121. doi: 10.1038/s41597-020-0462-2.

Abstract

Emissions into the atmosphere from human activities show marked temporal variations, from inter-annual to hourly levels. The consolidated practice of calculating yearly emissions follows the same temporal allocation of the underlying annual statistics. However, yearly emissions might not reflect heavy pollution episodes, seasonal trends, or any time-dependant atmospheric process. This study develops high-time resolution profiles for air pollutants and greenhouse gases co- emitted by anthropogenic sources in support of atmospheric modelling, Earth observation communities and decision makers. The key novelties of the Emissions Database for Global Atmospheric Research (EDGAR) temporal profiles are the development of (i) country/region- and sector- specific yearly profiles for all sources, (ii) time dependent yearly profiles for sources with inter-annual variability of their seasonal pattern, (iii) country- specific weekly and daily profiles to represent hourly emissions, (iv) a flexible system to compute hourly emissions including input from different users. This work creates a harmonized emission temporal distribution to be applied to any emission database as input for atmospheric models, thus promoting homogeneity in inter-comparison exercises.

摘要

人类活动向大气排放的污染物具有明显的时间变化特征,从年际变化到小时变化。计算年排放量的惯例是按照基础年度统计数据的时间分配进行的。然而,年排放量可能无法反映重污染事件、季节性趋势或任何依赖时间的大气过程。本研究开发了高时间分辨率的大气污染物和温室气体排放清单,以支持大气模式、地球观测社区和决策者的工作。全球大气研究排放数据库(EDGAR)时间序列的主要创新之处在于:(i)为所有源开发了针对国家/地区和部门的年度特定时间序列;(ii)对于季节性模式具有年际变化的源,开发了随时间变化的年度时间序列;(iii)针对国家/地区,开发了每周和每日时间序列,以代表小时排放量;(iv)开发了灵活的系统来计算小时排放量,包括来自不同用户的输入。这项工作创建了一个协调一致的排放时间分布,可作为大气模型的输入应用于任何排放数据库,从而促进了比较研究中的一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55b6/7165169/34789ea99013/41597_2020_462_Fig1_HTML.jpg

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