New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies

9 pags., 5 figs. 1 tab. Oceans are the largest source of biogenic emissions to the atmosphere, including aerosol precursors like marine halocarbons and dimethyl sulfide (DMS). During the last decade, the CAMS-GLOB-OCE dataset has developed an analysis of daily emissions of tribromomethane (CHBr3), d...

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Published in:Air Quality, Atmosphere & Health
Main Authors: Pino-Cortés, Ernesto, Gómez, Katherine, González Taboada, Fernando, Fu, Joshua S., Saiz-Lopez, A., Höfer, Juan
Other Authors: Comisión Nacional de Investigación Científica y Tecnológica (Chile), German Research Foundation, Fondo Nacional de Desarrollo Científico y Tecnológico (Chile)
Format: Article in Journal/Newspaper
Language:English
Published: Springer 2022
Subjects:
Online Access:http://hdl.handle.net/10261/295975
https://doi.org/10.1007/s11869-022-01301-0
https://doi.org/10.13039/501100001659
https://doi.org/10.13039/501100002848
https://doi.org/10.13039/501100002850
https://api.elsevier.com/content/abstract/scopus_id/85145211744
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spelling ftcsic:oai:digital.csic.es:10261/295975 2024-06-23T07:45:43+00:00 New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies Pino-Cortés, Ernesto Gómez, Katherine González Taboada, Fernando Fu, Joshua S. Saiz-Lopez, A. Höfer, Juan Comisión Nacional de Investigación Científica y Tecnológica (Chile) German Research Foundation Fondo Nacional de Desarrollo Científico y Tecnológico (Chile) Pino-Cortés, Ernesto González Taboada, Fernando Fu, Joshua S. Saiz-Lopez, A. Höfer, Juan 2022-12-30 http://hdl.handle.net/10261/295975 https://doi.org/10.1007/s11869-022-01301-0 https://doi.org/10.13039/501100001659 https://doi.org/10.13039/501100002848 https://doi.org/10.13039/501100002850 https://api.elsevier.com/content/abstract/scopus_id/85145211744 en eng Springer Air Quality, Atmosphere and Health Postprint https://doi.org/10.1007/s11869-022-01301-0 Sí Air Quality Atmosphere and Health (2022) 1873-9318 http://hdl.handle.net/10261/295975 doi:10.1007/s11869-022-01301-0 http://dx.doi.org/10.13039/501100001659 http://dx.doi.org/10.13039/501100002848 http://dx.doi.org/10.13039/501100002850 2-s2.0-85145211744 https://api.elsevier.com/content/abstract/scopus_id/85145211744 open CAMS-GLOB-OCE CMAQ Marine emissions NetCDF Command Operator SMOKE artículo http://purl.org/coar/resource_type/c_6501 2022 ftcsic https://doi.org/10.1007/s11869-022-01301-010.13039/50110000165910.13039/50110000284810.13039/501100002850 2024-05-29T00:01:24Z 9 pags., 5 figs. 1 tab. Oceans are the largest source of biogenic emissions to the atmosphere, including aerosol precursors like marine halocarbons and dimethyl sulfide (DMS). During the last decade, the CAMS-GLOB-OCE dataset has developed an analysis of daily emissions of tribromomethane (CHBr3), dibromomethane (CH2Br2), iodomethane (CH3I), and DMS, due to its increasingly recognized role on tropospheric chemistry and climate dynamics. The potential impacts of these compounds on air quality modeling remain, however, largely unexplored. The lack of a reliable and easy methodology to incorporate these marine emissions into air quality models is probably one of the reasons behind this knowledge gap. Therefore, this study describes a methodology to adapt the CAMS-GLOB-OCE dataset to be used as an input of the preprocessor software Sparse Matrix Operator Kernel Emissions (SMOKE). The method involves nine steps to update file attribute properties and to bilinearly interpolate compound emission fields. The procedure was tested using halocarbon and DMS emissions fields available within the CAMS-GLOB-OCE database for the Southern Ocean around Antarctica. We expect that this methodology will allow more studies to include the marine emissions of halocarbons and DMS in air quality studies. This work was supported by CONICYT-PIA-FONDEQUIP-FUNDACIÓN ALEMANA PARA LA INVESTIGACIÓN D.F.G (DFG190001), FONDECYT-REGULAR 1211338, and the supercomputing infrastructure at NLHPC (ECM-02). Peer reviewed Article in Journal/Newspaper Antarc* Antarctica Southern Ocean Digital.CSIC (Spanish National Research Council) Southern Ocean Air Quality, Atmosphere & Health
institution Open Polar
collection Digital.CSIC (Spanish National Research Council)
op_collection_id ftcsic
language English
topic CAMS-GLOB-OCE
CMAQ
Marine emissions
NetCDF Command Operator
SMOKE
spellingShingle CAMS-GLOB-OCE
CMAQ
Marine emissions
NetCDF Command Operator
SMOKE
Pino-Cortés, Ernesto
Gómez, Katherine
González Taboada, Fernando
Fu, Joshua S.
Saiz-Lopez, A.
Höfer, Juan
New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies
topic_facet CAMS-GLOB-OCE
CMAQ
Marine emissions
NetCDF Command Operator
SMOKE
description 9 pags., 5 figs. 1 tab. Oceans are the largest source of biogenic emissions to the atmosphere, including aerosol precursors like marine halocarbons and dimethyl sulfide (DMS). During the last decade, the CAMS-GLOB-OCE dataset has developed an analysis of daily emissions of tribromomethane (CHBr3), dibromomethane (CH2Br2), iodomethane (CH3I), and DMS, due to its increasingly recognized role on tropospheric chemistry and climate dynamics. The potential impacts of these compounds on air quality modeling remain, however, largely unexplored. The lack of a reliable and easy methodology to incorporate these marine emissions into air quality models is probably one of the reasons behind this knowledge gap. Therefore, this study describes a methodology to adapt the CAMS-GLOB-OCE dataset to be used as an input of the preprocessor software Sparse Matrix Operator Kernel Emissions (SMOKE). The method involves nine steps to update file attribute properties and to bilinearly interpolate compound emission fields. The procedure was tested using halocarbon and DMS emissions fields available within the CAMS-GLOB-OCE database for the Southern Ocean around Antarctica. We expect that this methodology will allow more studies to include the marine emissions of halocarbons and DMS in air quality studies. This work was supported by CONICYT-PIA-FONDEQUIP-FUNDACIÓN ALEMANA PARA LA INVESTIGACIÓN D.F.G (DFG190001), FONDECYT-REGULAR 1211338, and the supercomputing infrastructure at NLHPC (ECM-02). Peer reviewed
author2 Comisión Nacional de Investigación Científica y Tecnológica (Chile)
German Research Foundation
Fondo Nacional de Desarrollo Científico y Tecnológico (Chile)
Pino-Cortés, Ernesto
González Taboada, Fernando
Fu, Joshua S.
Saiz-Lopez, A.
Höfer, Juan
format Article in Journal/Newspaper
author Pino-Cortés, Ernesto
Gómez, Katherine
González Taboada, Fernando
Fu, Joshua S.
Saiz-Lopez, A.
Höfer, Juan
author_facet Pino-Cortés, Ernesto
Gómez, Katherine
González Taboada, Fernando
Fu, Joshua S.
Saiz-Lopez, A.
Höfer, Juan
author_sort Pino-Cortés, Ernesto
title New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies
title_short New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies
title_full New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies
title_fullStr New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies
title_full_unstemmed New processing methodology to incorporate marine halocarbons and dimethyl sulfide (DMS) emissions from the CAMS-GLOB-OCE dataset in air quality modeling studies
title_sort new processing methodology to incorporate marine halocarbons and dimethyl sulfide (dms) emissions from the cams-glob-oce dataset in air quality modeling studies
publisher Springer
publishDate 2022
url http://hdl.handle.net/10261/295975
https://doi.org/10.1007/s11869-022-01301-0
https://doi.org/10.13039/501100001659
https://doi.org/10.13039/501100002848
https://doi.org/10.13039/501100002850
https://api.elsevier.com/content/abstract/scopus_id/85145211744
geographic Southern Ocean
geographic_facet Southern Ocean
genre Antarc*
Antarctica
Southern Ocean
genre_facet Antarc*
Antarctica
Southern Ocean
op_relation Air Quality, Atmosphere and Health
Postprint
https://doi.org/10.1007/s11869-022-01301-0

Air Quality Atmosphere and Health (2022)
1873-9318
http://hdl.handle.net/10261/295975
doi:10.1007/s11869-022-01301-0
http://dx.doi.org/10.13039/501100001659
http://dx.doi.org/10.13039/501100002848
http://dx.doi.org/10.13039/501100002850
2-s2.0-85145211744
https://api.elsevier.com/content/abstract/scopus_id/85145211744
op_rights open
op_doi https://doi.org/10.1007/s11869-022-01301-010.13039/50110000165910.13039/50110000284810.13039/501100002850
container_title Air Quality, Atmosphere & Health
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