Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling

We present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for th...

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Autores: Guevara Vilardell, Marc|||0000-0001-9727-8583, Jorba Casellas, Oriol|||0000-0001-5872-0244, Tena, Carles|||0000-0002-5768-6758, Gon, Hugo Denier van der, Kuenen, Jeroen, Elguindi, Nellie, Darras, Sabine, Granier, Claire, Pérez García-Pando, Carlos|||0000-0002-4456-0697
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/342462
Acceso en línea:https://hdl.handle.net/2117/342462
https://dx.doi.org/10.5194/essd-13-367-2021
Access Level:acceso abierto
Palabra clave:Atmospheric chemistry
Air pollutants
Data sets
Air quality
Ammonia emissions
Air-pollution
Anthropogenic emissions
Gridded emissions
Transport model
Data product
Bottom-up
Fuel use
Inventory
China
Química atmosfèrica
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
id ES_95edf23b00ba95cbc9d22eba4e66948c
oai_identifier_str oai:upcommons.upc.edu:2117/342462
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
title Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
spellingShingle Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
Guevara Vilardell, Marc|||0000-0001-9727-8583
Atmospheric chemistry
Air pollutants
Data sets
Air quality
Ammonia emissions
Air-pollution
Anthropogenic emissions
Gridded emissions
Transport model
Data product
Bottom-up
Fuel use
Inventory
China
Química atmosfèrica
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
title_short Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
title_full Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
title_fullStr Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
title_full_unstemmed Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
title_sort Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
dc.creator.none.fl_str_mv Guevara Vilardell, Marc|||0000-0001-9727-8583
Jorba Casellas, Oriol|||0000-0001-5872-0244
Tena, Carles|||0000-0002-5768-6758
Gon, Hugo Denier van der
Kuenen, Jeroen
Elguindi, Nellie
Darras, Sabine
Granier, Claire
Pérez García-Pando, Carlos|||0000-0002-4456-0697
author Guevara Vilardell, Marc|||0000-0001-9727-8583
author_facet Guevara Vilardell, Marc|||0000-0001-9727-8583
Jorba Casellas, Oriol|||0000-0001-5872-0244
Tena, Carles|||0000-0002-5768-6758
Gon, Hugo Denier van der
Kuenen, Jeroen
Elguindi, Nellie
Darras, Sabine
Granier, Claire
Pérez García-Pando, Carlos|||0000-0002-4456-0697
author_role author
author2 Jorba Casellas, Oriol|||0000-0001-5872-0244
Tena, Carles|||0000-0002-5768-6758
Gon, Hugo Denier van der
Kuenen, Jeroen
Elguindi, Nellie
Darras, Sabine
Granier, Claire
Pérez García-Pando, Carlos|||0000-0002-4456-0697
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Atmospheric chemistry
Air pollutants
Data sets
Air quality
Ammonia emissions
Air-pollution
Anthropogenic emissions
Gridded emissions
Transport model
Data product
Bottom-up
Fuel use
Inventory
China
Química atmosfèrica
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
topic Atmospheric chemistry
Air pollutants
Data sets
Air quality
Ammonia emissions
Air-pollution
Anthropogenic emissions
Gridded emissions
Transport model
Data product
Bottom-up
Fuel use
Inventory
China
Química atmosfèrica
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
description We present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for the priority air pollutants (NOx ; SOx ; NMVOC, non-methane volatile organic compound; NH3; CO; PM10; and PM2.5) and the greenhouse gases (CO2 and CH4) for each of the following anthropogenic source categories: energy industry (power plants), residential combustion, manufacturing industry, transport (road traffic and air traffic in airports) and agricultural activities (fertilizer use and livestock). The profiles are computed on a global 0.1 x 0.1 degrees and regional European 0.1 x 0.05 degrees grid following the domain and sector classification descriptions of the global and regional emission inventories developed under the CAMS programme. The profiles account for the variability of the main emission drivers of each sector. Statistical information linked to emission variability (e.g. electricity production and traffic counts) at national and local levels were collected and combined with existing meteorology-dependent parametrizations to account for the influences of sociodemographic factors and climatological conditions. Depending on the sector and the temporal resolution (i.e. monthly, weekly, daily and hourly) the resulting profiles are pollutant-dependent, year-dependent (i.e. time series from 2010 to 2017) and/or spatially dependent (i.e. the temporal weights vary per country or region). We provide a complete description of the data and methods used to build the CAMS- TEMPO profiles, and whenever possible, we evaluate the representativeness of the proxies used to compute the temporal weights against existing observational data. We find important discrepancies when comparing the obtained temporal weights with other currently used datasets. The CAMS-TEMPO data product including the global (CAMS-GLOB-TEMPOv2.1, https://doi.org/10.24380/ks45-9147, Guevara et al., 2020a) and regional European (CAMS-REG-TEMPOv2.1, https://doi.org/10.24380/1cx4-zy68, Guevara et al., 2020b) temporal profiles are distributed from the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: February 2021).
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-02-01
2021
2021-03-25
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/342462
https://dx.doi.org/10.5194/essd-13-367-2021
url https://hdl.handle.net/2117/342462
https://dx.doi.org/10.5194/essd-13-367-2021
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 773051 FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
Attribution 3.0 Spain
https://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Copernicus
publisher.none.fl_str_mv Copernicus
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modellingGuevara Vilardell, Marc|||0000-0001-9727-8583Jorba Casellas, Oriol|||0000-0001-5872-0244Tena, Carles|||0000-0002-5768-6758Gon, Hugo Denier van derKuenen, JeroenElguindi, NellieDarras, SabineGranier, ClairePérez García-Pando, Carlos|||0000-0002-4456-0697Atmospheric chemistryAir pollutantsData setsAir qualityAmmonia emissionsAir-pollutionAnthropogenic emissionsGridded emissionsTransport modelData productBottom-upFuel useInventoryChinaQuímica atmosfèricaÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèricaWe present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for the priority air pollutants (NOx ; SOx ; NMVOC, non-methane volatile organic compound; NH3; CO; PM10; and PM2.5) and the greenhouse gases (CO2 and CH4) for each of the following anthropogenic source categories: energy industry (power plants), residential combustion, manufacturing industry, transport (road traffic and air traffic in airports) and agricultural activities (fertilizer use and livestock). The profiles are computed on a global 0.1 x 0.1 degrees and regional European 0.1 x 0.05 degrees grid following the domain and sector classification descriptions of the global and regional emission inventories developed under the CAMS programme. The profiles account for the variability of the main emission drivers of each sector. Statistical information linked to emission variability (e.g. electricity production and traffic counts) at national and local levels were collected and combined with existing meteorology-dependent parametrizations to account for the influences of sociodemographic factors and climatological conditions. Depending on the sector and the temporal resolution (i.e. monthly, weekly, daily and hourly) the resulting profiles are pollutant-dependent, year-dependent (i.e. time series from 2010 to 2017) and/or spatially dependent (i.e. the temporal weights vary per country or region). We provide a complete description of the data and methods used to build the CAMS- TEMPO profiles, and whenever possible, we evaluate the representativeness of the proxies used to compute the temporal weights against existing observational data. We find important discrepancies when comparing the obtained temporal weights with other currently used datasets. The CAMS-TEMPO data product including the global (CAMS-GLOB-TEMPOv2.1, https://doi.org/10.24380/ks45-9147, Guevara et al., 2020a) and regional European (CAMS-REG-TEMPOv2.1, https://doi.org/10.24380/1cx4-zy68, Guevara et al., 2020b) temporal profiles are distributed from the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: February 2021).The present work was funded through the CAMS_81 (CAMS global and regional emissions) contract, coordinated by the Centre National de la Recherche Scientifique (CNRS, Claire Granier). The Copernicus Atmosphere Monitoring Service (CAMS, https://atmosphere.copernicus.eu/) is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme. The study has also received support from the Ministerio de Ciencia, Innovación y Universidades (MICINN) as part of the BROWNING project (grant no. RTI2018-099894-B-I00) and NUTRIENT project (grant no. CGL2017-88911-R) and from the Agencia Estatal de Investigación (AEI) as part of the VITALISE project (grant no. PID2019-108086RA-I00 / AEI / 10.13039/501100011033). Carlos Pérez García-Pando acknowledges the European Research Council (grant no. 773051, FRAGMENT), the long-term support from the AXA Research Fund, and the support received through the Ramón y Cajal programme (grant no. RYC-2015-18690) of the MICINN. The authors acknowledge PRACE and RES for awarding access to MareNostrum at Barcelona Supercomputing Center. The authors are thankful to the Spanish Research Centre for Energy, Environment and Technology (CIEMAT) for sharing the databases of power plant emissions.Peer ReviewedCopernicus20212021-02-0120212021-03-25journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/342462https://dx.doi.org/10.5194/essd-13-367-2021reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 773051 FRontiers in dust minerAloGical coMposition and its Effects upoN climaTeopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/Attribution 3.0 Spainhttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3424622026-05-27T15:37:01Z
score 15.300724

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