EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol
The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-ar...
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| Autor*in: |
Mihaela Mircea [verfasserIn] Bertrand Bessagnet [verfasserIn] Massimo D'Isidoro [verfasserIn] Guido Pirovano [verfasserIn] Sebnem Aksoyoglu [verfasserIn] Giancarlo Ciarelli [verfasserIn] Svetlana Tsyro [verfasserIn] Astrid Manders [verfasserIn] Johannes Bieser [verfasserIn] Rainer Stern [verfasserIn] Marta García Vivanco [verfasserIn] Cornelius Cuvelier [verfasserIn] Wenche Aas [verfasserIn] André S.H. Prévôt [verfasserIn] Armin Aulinger [verfasserIn] Gino Briganti [verfasserIn] Giuseppe Calori [verfasserIn] Andrea Cappelletti [verfasserIn] Augustin Colette [verfasserIn] Florian Couvidat [verfasserIn] Hilde Fagerli [verfasserIn] Sandro Finardi [verfasserIn] Richard Kranenburg [verfasserIn] Laurence Rouïl [verfasserIn] Camillo Silibello [verfasserIn] Gerald Spindler [verfasserIn] Laurent Poulain [verfasserIn] Hartmut Herrmann [verfasserIn] Jose L. Jimenez [verfasserIn] Douglas A. Day [verfasserIn] Petri Tiitta [verfasserIn] Samara Carbone [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Übergeordnetes Werk: |
In: Atmospheric Environment: X - Elsevier, 2019, 2(2019), Seite - |
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| Übergeordnetes Werk: |
volume:2 ; year:2019 ; pages:- |
| Links: |
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| DOI / URN: |
10.1016/j.aeaoa.2019.100018 |
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| Katalog-ID: |
DOAJ006236502 |
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| 245 | 1 | 0 | |a EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol |
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| 520 | |a The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison | ||
| 653 | 0 | |a Environmental pollution | |
| 653 | 0 | |a Meteorology. Climatology | |
| 700 | 0 | |a Bertrand Bessagnet |e verfasserin |4 aut | |
| 700 | 0 | |a Massimo D'Isidoro |e verfasserin |4 aut | |
| 700 | 0 | |a Guido Pirovano |e verfasserin |4 aut | |
| 700 | 0 | |a Sebnem Aksoyoglu |e verfasserin |4 aut | |
| 700 | 0 | |a Giancarlo Ciarelli |e verfasserin |4 aut | |
| 700 | 0 | |a Svetlana Tsyro |e verfasserin |4 aut | |
| 700 | 0 | |a Astrid Manders |e verfasserin |4 aut | |
| 700 | 0 | |a Johannes Bieser |e verfasserin |4 aut | |
| 700 | 0 | |a Rainer Stern |e verfasserin |4 aut | |
| 700 | 0 | |a Marta García Vivanco |e verfasserin |4 aut | |
| 700 | 0 | |a Cornelius Cuvelier |e verfasserin |4 aut | |
| 700 | 0 | |a Wenche Aas |e verfasserin |4 aut | |
| 700 | 0 | |a André S.H. Prévôt |e verfasserin |4 aut | |
| 700 | 0 | |a Armin Aulinger |e verfasserin |4 aut | |
| 700 | 0 | |a Gino Briganti |e verfasserin |4 aut | |
| 700 | 0 | |a Giuseppe Calori |e verfasserin |4 aut | |
| 700 | 0 | |a Andrea Cappelletti |e verfasserin |4 aut | |
| 700 | 0 | |a Augustin Colette |e verfasserin |4 aut | |
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| 700 | 0 | |a Hilde Fagerli |e verfasserin |4 aut | |
| 700 | 0 | |a Sandro Finardi |e verfasserin |4 aut | |
| 700 | 0 | |a Richard Kranenburg |e verfasserin |4 aut | |
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| 700 | 0 | |a Petri Tiitta |e verfasserin |4 aut | |
| 700 | 0 | |a Samara Carbone |e verfasserin |4 aut | |
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10.1016/j.aeaoa.2019.100018 doi (DE-627)DOAJ006236502 (DE-599)DOAJ7d7b1e930bfe4176ac54701e7c2693ee DE-627 ger DE-627 rakwb eng TD172-193.5 QC851-999 Mihaela Mircea verfasserin aut EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison Environmental pollution Meteorology. Climatology Bertrand Bessagnet verfasserin aut Massimo D'Isidoro verfasserin aut Guido Pirovano verfasserin aut Sebnem Aksoyoglu verfasserin aut Giancarlo Ciarelli verfasserin aut Svetlana Tsyro verfasserin aut Astrid Manders verfasserin aut Johannes Bieser verfasserin aut Rainer Stern verfasserin aut Marta García Vivanco verfasserin aut Cornelius Cuvelier verfasserin aut Wenche Aas verfasserin aut André S.H. Prévôt verfasserin aut Armin Aulinger verfasserin aut Gino Briganti verfasserin aut Giuseppe Calori verfasserin aut Andrea Cappelletti verfasserin aut Augustin Colette verfasserin aut Florian Couvidat verfasserin aut Hilde Fagerli verfasserin aut Sandro Finardi verfasserin aut Richard Kranenburg verfasserin aut Laurence Rouïl verfasserin aut Camillo Silibello verfasserin aut Gerald Spindler verfasserin aut Laurent Poulain verfasserin aut Hartmut Herrmann verfasserin aut Jose L. Jimenez verfasserin aut Douglas A. Day verfasserin aut Petri Tiitta verfasserin aut Samara Carbone verfasserin aut In Atmospheric Environment: X Elsevier, 2019 2(2019), Seite - (DE-627)1662576919 25901621 nnns volume:2 year:2019 pages:- https://doi.org/10.1016/j.aeaoa.2019.100018 kostenfrei https://doaj.org/article/7d7b1e930bfe4176ac54701e7c2693ee kostenfrei http://www.sciencedirect.com/science/article/pii/S2590162119300218 kostenfrei https://doaj.org/toc/2590-1621 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 2 2019 - |
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10.1016/j.aeaoa.2019.100018 doi (DE-627)DOAJ006236502 (DE-599)DOAJ7d7b1e930bfe4176ac54701e7c2693ee DE-627 ger DE-627 rakwb eng TD172-193.5 QC851-999 Mihaela Mircea verfasserin aut EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison Environmental pollution Meteorology. Climatology Bertrand Bessagnet verfasserin aut Massimo D'Isidoro verfasserin aut Guido Pirovano verfasserin aut Sebnem Aksoyoglu verfasserin aut Giancarlo Ciarelli verfasserin aut Svetlana Tsyro verfasserin aut Astrid Manders verfasserin aut Johannes Bieser verfasserin aut Rainer Stern verfasserin aut Marta García Vivanco verfasserin aut Cornelius Cuvelier verfasserin aut Wenche Aas verfasserin aut André S.H. Prévôt verfasserin aut Armin Aulinger verfasserin aut Gino Briganti verfasserin aut Giuseppe Calori verfasserin aut Andrea Cappelletti verfasserin aut Augustin Colette verfasserin aut Florian Couvidat verfasserin aut Hilde Fagerli verfasserin aut Sandro Finardi verfasserin aut Richard Kranenburg verfasserin aut Laurence Rouïl verfasserin aut Camillo Silibello verfasserin aut Gerald Spindler verfasserin aut Laurent Poulain verfasserin aut Hartmut Herrmann verfasserin aut Jose L. Jimenez verfasserin aut Douglas A. Day verfasserin aut Petri Tiitta verfasserin aut Samara Carbone verfasserin aut In Atmospheric Environment: X Elsevier, 2019 2(2019), Seite - (DE-627)1662576919 25901621 nnns volume:2 year:2019 pages:- https://doi.org/10.1016/j.aeaoa.2019.100018 kostenfrei https://doaj.org/article/7d7b1e930bfe4176ac54701e7c2693ee kostenfrei http://www.sciencedirect.com/science/article/pii/S2590162119300218 kostenfrei https://doaj.org/toc/2590-1621 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 2 2019 - |
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10.1016/j.aeaoa.2019.100018 doi (DE-627)DOAJ006236502 (DE-599)DOAJ7d7b1e930bfe4176ac54701e7c2693ee DE-627 ger DE-627 rakwb eng TD172-193.5 QC851-999 Mihaela Mircea verfasserin aut EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison Environmental pollution Meteorology. Climatology Bertrand Bessagnet verfasserin aut Massimo D'Isidoro verfasserin aut Guido Pirovano verfasserin aut Sebnem Aksoyoglu verfasserin aut Giancarlo Ciarelli verfasserin aut Svetlana Tsyro verfasserin aut Astrid Manders verfasserin aut Johannes Bieser verfasserin aut Rainer Stern verfasserin aut Marta García Vivanco verfasserin aut Cornelius Cuvelier verfasserin aut Wenche Aas verfasserin aut André S.H. Prévôt verfasserin aut Armin Aulinger verfasserin aut Gino Briganti verfasserin aut Giuseppe Calori verfasserin aut Andrea Cappelletti verfasserin aut Augustin Colette verfasserin aut Florian Couvidat verfasserin aut Hilde Fagerli verfasserin aut Sandro Finardi verfasserin aut Richard Kranenburg verfasserin aut Laurence Rouïl verfasserin aut Camillo Silibello verfasserin aut Gerald Spindler verfasserin aut Laurent Poulain verfasserin aut Hartmut Herrmann verfasserin aut Jose L. Jimenez verfasserin aut Douglas A. Day verfasserin aut Petri Tiitta verfasserin aut Samara Carbone verfasserin aut In Atmospheric Environment: X Elsevier, 2019 2(2019), Seite - (DE-627)1662576919 25901621 nnns volume:2 year:2019 pages:- https://doi.org/10.1016/j.aeaoa.2019.100018 kostenfrei https://doaj.org/article/7d7b1e930bfe4176ac54701e7c2693ee kostenfrei http://www.sciencedirect.com/science/article/pii/S2590162119300218 kostenfrei https://doaj.org/toc/2590-1621 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 2 2019 - |
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10.1016/j.aeaoa.2019.100018 doi (DE-627)DOAJ006236502 (DE-599)DOAJ7d7b1e930bfe4176ac54701e7c2693ee DE-627 ger DE-627 rakwb eng TD172-193.5 QC851-999 Mihaela Mircea verfasserin aut EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison Environmental pollution Meteorology. Climatology Bertrand Bessagnet verfasserin aut Massimo D'Isidoro verfasserin aut Guido Pirovano verfasserin aut Sebnem Aksoyoglu verfasserin aut Giancarlo Ciarelli verfasserin aut Svetlana Tsyro verfasserin aut Astrid Manders verfasserin aut Johannes Bieser verfasserin aut Rainer Stern verfasserin aut Marta García Vivanco verfasserin aut Cornelius Cuvelier verfasserin aut Wenche Aas verfasserin aut André S.H. Prévôt verfasserin aut Armin Aulinger verfasserin aut Gino Briganti verfasserin aut Giuseppe Calori verfasserin aut Andrea Cappelletti verfasserin aut Augustin Colette verfasserin aut Florian Couvidat verfasserin aut Hilde Fagerli verfasserin aut Sandro Finardi verfasserin aut Richard Kranenburg verfasserin aut Laurence Rouïl verfasserin aut Camillo Silibello verfasserin aut Gerald Spindler verfasserin aut Laurent Poulain verfasserin aut Hartmut Herrmann verfasserin aut Jose L. Jimenez verfasserin aut Douglas A. Day verfasserin aut Petri Tiitta verfasserin aut Samara Carbone verfasserin aut In Atmospheric Environment: X Elsevier, 2019 2(2019), Seite - (DE-627)1662576919 25901621 nnns volume:2 year:2019 pages:- https://doi.org/10.1016/j.aeaoa.2019.100018 kostenfrei https://doaj.org/article/7d7b1e930bfe4176ac54701e7c2693ee kostenfrei http://www.sciencedirect.com/science/article/pii/S2590162119300218 kostenfrei https://doaj.org/toc/2590-1621 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 2 2019 - |
| allfieldsSound |
10.1016/j.aeaoa.2019.100018 doi (DE-627)DOAJ006236502 (DE-599)DOAJ7d7b1e930bfe4176ac54701e7c2693ee DE-627 ger DE-627 rakwb eng TD172-193.5 QC851-999 Mihaela Mircea verfasserin aut EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison Environmental pollution Meteorology. Climatology Bertrand Bessagnet verfasserin aut Massimo D'Isidoro verfasserin aut Guido Pirovano verfasserin aut Sebnem Aksoyoglu verfasserin aut Giancarlo Ciarelli verfasserin aut Svetlana Tsyro verfasserin aut Astrid Manders verfasserin aut Johannes Bieser verfasserin aut Rainer Stern verfasserin aut Marta García Vivanco verfasserin aut Cornelius Cuvelier verfasserin aut Wenche Aas verfasserin aut André S.H. Prévôt verfasserin aut Armin Aulinger verfasserin aut Gino Briganti verfasserin aut Giuseppe Calori verfasserin aut Andrea Cappelletti verfasserin aut Augustin Colette verfasserin aut Florian Couvidat verfasserin aut Hilde Fagerli verfasserin aut Sandro Finardi verfasserin aut Richard Kranenburg verfasserin aut Laurence Rouïl verfasserin aut Camillo Silibello verfasserin aut Gerald Spindler verfasserin aut Laurent Poulain verfasserin aut Hartmut Herrmann verfasserin aut Jose L. Jimenez verfasserin aut Douglas A. Day verfasserin aut Petri Tiitta verfasserin aut Samara Carbone verfasserin aut In Atmospheric Environment: X Elsevier, 2019 2(2019), Seite - (DE-627)1662576919 25901621 nnns volume:2 year:2019 pages:- https://doi.org/10.1016/j.aeaoa.2019.100018 kostenfrei https://doaj.org/article/7d7b1e930bfe4176ac54701e7c2693ee kostenfrei http://www.sciencedirect.com/science/article/pii/S2590162119300218 kostenfrei https://doaj.org/toc/2590-1621 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 2 2019 - |
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Mihaela Mircea @@aut@@ Bertrand Bessagnet @@aut@@ Massimo D'Isidoro @@aut@@ Guido Pirovano @@aut@@ Sebnem Aksoyoglu @@aut@@ Giancarlo Ciarelli @@aut@@ Svetlana Tsyro @@aut@@ Astrid Manders @@aut@@ Johannes Bieser @@aut@@ Rainer Stern @@aut@@ Marta García Vivanco @@aut@@ Cornelius Cuvelier @@aut@@ Wenche Aas @@aut@@ André S.H. Prévôt @@aut@@ Armin Aulinger @@aut@@ Gino Briganti @@aut@@ Giuseppe Calori @@aut@@ Andrea Cappelletti @@aut@@ Augustin Colette @@aut@@ Florian Couvidat @@aut@@ Hilde Fagerli @@aut@@ Sandro Finardi @@aut@@ Richard Kranenburg @@aut@@ Laurence Rouïl @@aut@@ Camillo Silibello @@aut@@ Gerald Spindler @@aut@@ Laurent Poulain @@aut@@ Hartmut Herrmann @@aut@@ Jose L. Jimenez @@aut@@ Douglas A. Day @@aut@@ Petri Tiitta @@aut@@ Samara Carbone @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ006236502</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309200859.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.aeaoa.2019.100018</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ006236502</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ7d7b1e930bfe4176ac54701e7c2693ee</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TD172-193.5</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QC851-999</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Mihaela Mircea</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Environmental pollution</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Meteorology. 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Elektronische Aufsätze |
| author-letter |
Mihaela Mircea |
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10.1016/j.aeaoa.2019.100018 |
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verfasserin |
| title_sort |
eurodelta iii exercise: an evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol |
| callnumber |
TD172-193.5 |
| title_auth |
EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol |
| abstract |
The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison |
| abstractGer |
The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison |
| abstract_unstemmed |
The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. Keywords: Elemental carbon, Organic aerosol, Secondary organic aerosol, Model validation, Model inter-comparison |
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| title_short |
EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol |
| url |
https://doi.org/10.1016/j.aeaoa.2019.100018 https://doaj.org/article/7d7b1e930bfe4176ac54701e7c2693ee http://www.sciencedirect.com/science/article/pii/S2590162119300218 https://doaj.org/toc/2590-1621 |
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Bertrand Bessagnet Massimo D'Isidoro Guido Pirovano Sebnem Aksoyoglu Giancarlo Ciarelli Svetlana Tsyro Astrid Manders Johannes Bieser Rainer Stern Marta García Vivanco Cornelius Cuvelier Wenche Aas André S.H. Prévôt Armin Aulinger Gino Briganti Giuseppe Calori Andrea Cappelletti Augustin Colette Florian Couvidat Hilde Fagerli Sandro Finardi Richard Kranenburg Laurence Rouïl Camillo Silibello Gerald Spindler Laurent Poulain Hartmut Herrmann Jose L. Jimenez Douglas A. Day Petri Tiitta Samara Carbone |
| author2Str |
Bertrand Bessagnet Massimo D'Isidoro Guido Pirovano Sebnem Aksoyoglu Giancarlo Ciarelli Svetlana Tsyro Astrid Manders Johannes Bieser Rainer Stern Marta García Vivanco Cornelius Cuvelier Wenche Aas André S.H. Prévôt Armin Aulinger Gino Briganti Giuseppe Calori Andrea Cappelletti Augustin Colette Florian Couvidat Hilde Fagerli Sandro Finardi Richard Kranenburg Laurence Rouïl Camillo Silibello Gerald Spindler Laurent Poulain Hartmut Herrmann Jose L. Jimenez Douglas A. Day Petri Tiitta Samara Carbone |
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TD - Environmental Technology |
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2024-07-03T19:46:21.499Z |
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| score |
7.402128 |