GSTDTAP  > 地球科学
DOI10.5194/acp-17-15271-2017
Source attribution using FLEXPART and carbon monoxide emission inventories: SOFT-IO version 1.0
Sauvage, Bastien1; Fontaine, Alain1; Eckhardt, Sabine3; Auby, Antoine4; Boulanger, Damien2; Petetin, Herve1; Paugam, Ronan5; Athier, Gilles1; Cousin, Jean-Marc1; Darras, Sabine3; Nedelec, Philippe1; Stohl, Andreas3; Turquety, Solene6; Cammas, Jean-Pierre7,8; Thouret, Valerie1
2017-12-22
发表期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN1680-7316
EISSN1680-7324
出版年2017
卷号17期号:24
文章类型Article
语种英语
国家France; Norway; England
英文摘要

Since 1994, the In-service Aircraft for a Global Observing System (IAGOS) program has produced in situ measurements of the atmospheric composition during more than 51 000 commercial flights. In order to help analyze these observations and understand the processes driving the observed concentration distribution and variability, we developed the SOFT-IO tool to quantify source-receptor links for all measured data. Based on the FLEXPART particle dispersion model (Stohl et al., 2005), SOFT-IO simulates the contributions of anthropogenic and biomass burning emissions from the ECCAD emission inventory database for all locations and times corresponding to the measured carbon monoxide mixing ratios along each IAGOS flight. Contributions are simulated from emissions occurring during the last 20 days before an observation, separating individual contributions from the different source regions. The main goal is to supply added-value products to the IAGOS database by evincing the geographical origin and emission sources driving the CO enhancements observed in the troposphere and lower stratosphere. This requires a good match between observed and modeled CO enhancements. Indeed, SOFT-IO detects more than 95% of the observed CO anomalies over most of the regions sampled by IAGOS in the troposphere. In the majority of cases, SOFT-IO simulates CO pollution plumes with biases lower than 10-15 ppbv. Differences between the model and observations are larger for very low or very high observed CO values. The added-value products will help in the understanding of the trace-gas distribution and seasonal variability. They are available in the IAGOS database via http://www.iagos.org. The SOFT-IO tool could also be applied to similar data sets of CO observations (e.g., ground-based measurements, satellite observations). SOFT-IO could also be used for statistical validation as well as for intercomparisons of emission inventories using large amounts of data.


领域地球科学
收录类别SCI-E
WOS记录号WOS:000418683300002
WOS关键词PARTICLE DISPERSION MODEL ; TROPOSPHERIC OZONE ; BLACK CARBON ; INTERANNUAL VARIABILITY ; POLLUTION TRANSPORT ; LOWER STRATOSPHERE ; MOZAIC PROGRAM ; FIRE EMISSIONS ; AIR-POLLUTION ; GLOBAL-SCALE
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/30856
专题地球科学
作者单位1.Univ Toulouse, CNRS, UPS, Lab Aerol, Toulouse, France;
2.Observ Midipyrenees, Toulouse, France;
3.Norwegian Inst Air Res, NILU, Kjeller, Norway;
4.CAP HPI, Leeds, W Yorkshire, England;
5.Kings Coll London, Dept Geog, London, England;
6.UPMC Univ Paris 6, Lab Meteorol Dynam IPSL, Paris, France;
7.Univ Reunion, Observ Sci Univers Reunion UMS 3365, St Denis, La Reunion, France;
8.Univ Reunion, Lab Atmosphere & Cyclones UMR 8105, St Denis, La Reunion, France
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GB/T 7714
Sauvage, Bastien,Fontaine, Alain,Eckhardt, Sabine,et al. Source attribution using FLEXPART and carbon monoxide emission inventories: SOFT-IO version 1.0[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2017,17(24).
APA Sauvage, Bastien.,Fontaine, Alain.,Eckhardt, Sabine.,Auby, Antoine.,Boulanger, Damien.,...&Thouret, Valerie.(2017).Source attribution using FLEXPART and carbon monoxide emission inventories: SOFT-IO version 1.0.ATMOSPHERIC CHEMISTRY AND PHYSICS,17(24).
MLA Sauvage, Bastien,et al."Source attribution using FLEXPART and carbon monoxide emission inventories: SOFT-IO version 1.0".ATMOSPHERIC CHEMISTRY AND PHYSICS 17.24(2017).
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