Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model
<p>Vegetation fires emit large quantities of aerosol into the atmosphere, impacting regional air quality and climate. Previous work has used comparisons of simulated and observed aerosol optical depth (AOD) in regions heavily impacted by fires to suggest that emissions of aerosol particles fro...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-07-01
|
| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/19/9125/2019/acp-19-9125-2019.pdf |
| _version_ | 1798045077449211904 |
|---|---|
| author | C. L. Reddington W. T. Morgan E. Darbyshire J. Brito J. Brito H. Coe P. Artaxo C. E. Scott J. Marsham D. V. Spracklen |
| author_facet | C. L. Reddington W. T. Morgan E. Darbyshire J. Brito J. Brito H. Coe P. Artaxo C. E. Scott J. Marsham D. V. Spracklen |
| author_sort | C. L. Reddington |
| collection | DOAJ |
| description | <p>Vegetation fires emit large quantities of aerosol into the
atmosphere, impacting regional air quality and climate. Previous work has
used comparisons of simulated and observed aerosol optical depth (AOD) in
regions heavily impacted by fires to suggest that emissions of aerosol particles
from fires may be underestimated by a factor of 2–5. Here we use surface,
aircraft and satellite observations made over the Amazon during September
2012, along with a global aerosol model to improve understanding of aerosol
emissions from vegetation fires. We apply three different satellite-derived
fire emission datasets (FINN, GFED, GFAS) in the model. Daily mean aerosol
emissions in these datasets vary by up to a factor of 3.7 over the Amazon
during this period, highlighting the considerable uncertainty in emissions.
We find variable agreement between the model and observed aerosol mass
concentrations. The model reproduces observed aerosol concentrations
over deforestation fires well in the western Amazon during dry season conditions
with FINN or GFED emissions and during dry–wet transition season conditions
with GFAS emissions. In contrast, the model underestimates aerosol
concentrations over savanna fires in the Cerrado environment east of the
Amazon Basin with all three fire emission datasets. The model generally
underestimates AOD compared to satellite and ground stations, even when the
model reproduces the observed vertical profile of aerosol mass
concentration. We suggest it is likely caused by uncertainties in the
calculation of AOD, which are as large as <span class="inline-formula">∼90</span> %, with the
largest sensitivities due to uncertainties in water uptake and relative
humidity. Overall, we do not find evidence that particulate emissions from
fires are systematically underestimated in the Amazon region and we caution
against using comparison with AOD to constrain particulate emissions from
fires.</p> |
| first_indexed | 2024-04-11T23:14:47Z |
| format | Article |
| id | doaj.art-e30cadfccab241bb9666ca10358ce272 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-11T23:14:47Z |
| publishDate | 2019-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-e30cadfccab241bb9666ca10358ce2722022-12-22T03:57:40ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242019-07-01199125915210.5194/acp-19-9125-2019Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol modelC. L. Reddington0W. T. Morgan1E. Darbyshire2J. Brito3J. Brito4H. Coe5P. Artaxo6C. E. Scott7J. Marsham8D. V. Spracklen9School of Earth and Environment, University of Leeds, Leeds, UKCentre of Atmospheric Sciences, School of Earth and Environmental Science, University of Manchester, Manchester, UKCentre of Atmospheric Sciences, School of Earth and Environmental Science, University of Manchester, Manchester, UKPhysics Institute, University of São Paulo, São Paulo, Brazilnow at: Laboratoire de Météorologie Physique, Université Clermont Auvergne, Aubière, FranceCentre of Atmospheric Sciences, School of Earth and Environmental Science, University of Manchester, Manchester, UKPhysics Institute, University of São Paulo, São Paulo, BrazilSchool of Earth and Environment, University of Leeds, Leeds, UKSchool of Earth and Environment, University of Leeds, Leeds, UKSchool of Earth and Environment, University of Leeds, Leeds, UK<p>Vegetation fires emit large quantities of aerosol into the atmosphere, impacting regional air quality and climate. Previous work has used comparisons of simulated and observed aerosol optical depth (AOD) in regions heavily impacted by fires to suggest that emissions of aerosol particles from fires may be underestimated by a factor of 2–5. Here we use surface, aircraft and satellite observations made over the Amazon during September 2012, along with a global aerosol model to improve understanding of aerosol emissions from vegetation fires. We apply three different satellite-derived fire emission datasets (FINN, GFED, GFAS) in the model. Daily mean aerosol emissions in these datasets vary by up to a factor of 3.7 over the Amazon during this period, highlighting the considerable uncertainty in emissions. We find variable agreement between the model and observed aerosol mass concentrations. The model reproduces observed aerosol concentrations over deforestation fires well in the western Amazon during dry season conditions with FINN or GFED emissions and during dry–wet transition season conditions with GFAS emissions. In contrast, the model underestimates aerosol concentrations over savanna fires in the Cerrado environment east of the Amazon Basin with all three fire emission datasets. The model generally underestimates AOD compared to satellite and ground stations, even when the model reproduces the observed vertical profile of aerosol mass concentration. We suggest it is likely caused by uncertainties in the calculation of AOD, which are as large as <span class="inline-formula">∼90</span> %, with the largest sensitivities due to uncertainties in water uptake and relative humidity. Overall, we do not find evidence that particulate emissions from fires are systematically underestimated in the Amazon region and we caution against using comparison with AOD to constrain particulate emissions from fires.</p>https://www.atmos-chem-phys.net/19/9125/2019/acp-19-9125-2019.pdf |
| spellingShingle | C. L. Reddington W. T. Morgan E. Darbyshire J. Brito J. Brito H. Coe P. Artaxo C. E. Scott J. Marsham D. V. Spracklen Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model Atmospheric Chemistry and Physics |
| title | Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model |
| title_full | Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model |
| title_fullStr | Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model |
| title_full_unstemmed | Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model |
| title_short | Biomass burning aerosol over the Amazon: analysis of aircraft, surface and satellite observations using a global aerosol model |
| title_sort | biomass burning aerosol over the amazon analysis of aircraft surface and satellite observations using a global aerosol model |
| url | https://www.atmos-chem-phys.net/19/9125/2019/acp-19-9125-2019.pdf |
| work_keys_str_mv | AT clreddington biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT wtmorgan biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT edarbyshire biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT jbrito biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT jbrito biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT hcoe biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT partaxo biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT cescott biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT jmarsham biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel AT dvspracklen biomassburningaerosolovertheamazonanalysisofaircraftsurfaceandsatelliteobservationsusingaglobalaerosolmodel |