Articles | Volume 15, issue 14
https://doi.org/10.5194/acp-15-8539-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-8539-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Jul 2015
Research article |
| 30 Jul 2015
Using SEVIRI fire observations to drive smoke plumes in the CMAQ air quality model: a case study over Antalya in 2008
G. Baldassarre
CORRESPONDING AUTHOR
Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
L. Pozzoli
Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
C. C. Schmidt
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, Madison, WI, USA
A. Unal
Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
T. Kindap
Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
W. P. Menzel
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, Madison, WI, USA
S. Whitburn
Spectroscopie de l'Atmosphère, Service de Chimie Quantique et de Photophysique, Université Libre de Bruxelles (U.L.B), Brussels, Belgium
P.-F. Coheur
Spectroscopie de l'Atmosphère, Service de Chimie Quantique et de Photophysique, Université Libre de Bruxelles (U.L.B), Brussels, Belgium
A. Kavgaci
Southwest Anatolia Forest Research Institute, Antalya, Turkey
J. W. Kaiser
King's College, London, UK
European Center for Medium-Range Weather Forecasts, Reading, UK
Max Planck Institute for Chemistry, Mainz, Germany
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- Calibrating R-LINE model results with observational data to develop annual mobile source air pollutant fields at fine spatial resolution: Application in Atlanta X. Zhai et al. 10.1016/j.atmosenv.2016.10.015
- Improvements in high-temporal resolution active fire detection and FRP retrieval over the Americas using GOES-16 ABI with the geostationary Fire Thermal Anomaly (FTA) algorithm W. Xu et al. 10.1016/j.srs.2021.100016
- Assessment of global and regional PM10 CAMSRA data: comparison to observed data in Morocco I. Sekmoudi et al. 10.1007/s11356-021-12783-3
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- LSA SAF Meteosat FRP products – Part 2: Evaluation and demonstration for use in the Copernicus Atmosphere Monitoring Service (CAMS) G. Roberts et al. 10.5194/acp-15-13241-2015
- Development of an infrared pollution index to identify ground-level compositional, particle size, and humidity changes using Himawari-8 M. Sowden et al. 10.1016/j.atmosenv.2020.117435
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- Geostationary active fire products validation: GOES-17 ABI, GOES-16 ABI, and Himawari AHI J. Hall et al. 10.1080/01431161.2023.2217983
- Global impact of landscape fire emissions on surface level PM2.5 concentrations, air quality exposure and population mortality G. Roberts & M. Wooster 10.1016/j.atmosenv.2021.118210
- Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data H. Nguyen & M. Wooster 10.1016/j.rse.2020.111971
- An evaluation of empirical and statistically based smoke plume injection height parametrisations used within air quality models J. Wilkins et al. 10.1071/WF20140
- Review of surface particulate monitoring of dust events using geostationary satellite remote sensing M. Sowden et al. 10.1016/j.atmosenv.2018.04.020
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- Assessment of fire emission inventories during the South American Biomass Burning Analysis (SAMBBA) experiment G. Pereira et al. 10.5194/acp-16-6961-2016
- Evaluation of impact of residential heating on air quality of megacity Istanbul by CMAQ M. Baykara et al. 10.1016/j.scitotenv.2018.10.091
2 citations as recorded by crossref.
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Latest update: 13 Dec 2024
Short summary
We investigate the quality of fire emission estimates derived from SEVIRI FRP for air quality simulations with the Community Multiscale Air Quality (CMAQ) model, by comparing them with available MODIS FRP-based ones.
We demonstrate that geostationary observations allow for refining biomass burning emissions, which can subsequently be used in regional scale air quality models in order to improve the prediction of chemical composition of the atmosphere in presence of large fire episodes.
We investigate the quality of fire emission estimates derived from SEVIRI FRP for air quality...
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