Multispectral remote sensing of biomass burning in West Africa

Ricardo, Jesús Estupiñán; França, A. De; Brustet, J. M.; Fontan, J.

doi:10.1007/bf00708183

Cited by 26 publications

(2 citation statements)

References 36 publications

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“…Many studies show that remote sensing is the most practical means of measuring energy release from large-scale open-air biomass burning (Ricardo et al, 1995;PalaciosOrueta et al, 2004;Lee et al, 2005;Bradley and Millington, 2006) because satellite observations may detect unknown global or regional patterns, daily variations and seasonality that are not reproduced by models (Hoelzemann et al, 2009). Initiatives such as the ESA's Climate Change Initiative (CCI) and Global Burnt Area 2000 Project (GBA2000) attempt to evaluate burnt areas using different sensors.…”

Section: Introductionmentioning

confidence: 99%

Integration of remote sensing data and surface observations to estimate the impact of the Russian wildfires over Europe and Asia during August 2010

et al. 2011

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Abstract.A series of wildfires broke out in Western Russia starting in late July of 2010. Harmful particulates and gases released into the local Russian atmosphere have been reported, as have possible negative consequences for the global atmosphere. In this study, an extremely hazy area and its transport trajectory on Russian wildfires were analysed using aerosol optical depth (AOD) images retrieved via the synergy method from Moderate Resolution Imaging Spectroradiometer (MODIS) data. In addition, we used trace gases (NO 2 and SO 2 ) and CO 2 products measured using Ozone Monitoring Instrument (OMI) data, vertical distribution of AOD data retrieved from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the mass trajectory analyses, synoptic maps from a HYSPLIT model simulation and ground-based data, including AERONET (both AOD andÅngström exponent) data and PM 2.5 . First, an Optimal Smoothing (OS) scheme was used to develop more precise and reliable AOD data based on multiple competing predictions made using several AOD retrieval models; then, integrated AOD and PM 2.5 data were related using a chemical Correspondence to: Y. Xue (yxue@irsa.ac.cn) transport model (GEOS-Chem), and the integrated AOD and visibility data were related using the 6S radiative transfer code. The results show that the PM 2.5 concentration is enhanced by a factor of 3-5 as determined from both satellite and in situ observations with peak daily mean concentrations of approximately 500 µg m 3 . Also, the visibility in many parts of Russia, for instance in Moscow, was less than 100 m; in some areas, the visibility was less than 50 m. Additionally, the possible impact on neighbouring countries due to long-transport was analysed for 31 July and 15 August 2010.

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Section: Introductionmentioning

confidence: 99%

Integration of remote sensing data and surface observations to estimate the impact of the Russian wildfires over Europe and Asia during August 2010

et al. 2011

View full text Add to dashboard Cite

show abstract

“…Many studies show that remote sensing is the most practical means of measuring energy release from large-scale open-air biomass burning (Ricardo et al, 1995;Palacios-Orueta et al, 2004;Lee et al, 2005;Bradley and Millington, 2006) because satellite observations may detect unknown global or regional patterns, daily variations and seasonality that are not reproduced by models (Hoelzemann et al, 2009). Initiatives such as the ESA's Climate Change Initiative (CCI) and Global Burnt Area 2000 Project (GBA2000) attempt to evaluate burnt areas using different sensors.…”

Section: Introductionmentioning

confidence: 99%

Integration of remote sensing data and surface observations to estimate the impact of the russian wildfires over Europe and Asia during August 2010

Mei¹,

Xue²,

Leeuw³

et al. 2011

Preprint

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A series of wildfires broke out in western Russia starting in late July of 2010. Harmful particulates and gases released into the local Russian atmosphere have been reported, as have possible negative consequences for the global atmosphere. In this study, an extremely hazy area and its transport trajectory on Russian wildfires were analysed using aerosol optical depth (AOD) images retrieved via the synergy method from Moderate Resolution Imaging Spectroradiometer (MODIS) data. In addition, we used trace gases (NO2 and SO2) and CO2 products measured using Ozone Monitoring Instrument (OMI) data, vertical distribution of AOD data retrieved from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the mass trajectory analyses, synoptic maps from a HYSPLIT model simulation and ground-based data, including AERONET (both AOD and Ångström exponent) data and PM2.5. First, an Optimal Smoothing (OS) scheme was used to develop more precise and reliable AOD data based on multiple competing predictions made using several AOD retrieval models; then, integrated AOD and PM2.5 data were related using a chemical transport model (GEOS-Chem), and the integrated AOD and visibility data were related using a 6S model. The results show that the PM2.5 concentration is 3–5 times the normal amount based on both satellite data and in situ values with peak daily mean concentrations of approximately 500 μg m−3. Also, the visibility of many parts of Russia, even Moscow, was less than 100 m; in some areas, the visibility was less than 50 m. Additionally, the possible impact on neighbouring countries due to the long-transport effect was also analysed during 31 July and 15 August 2010. A comparison of the satellite aerosol products and ground observations from the neighbouring countries suggests that wildfires in western Russian have had little impact on most European and Asian countries, the exceptions being Finland, Estonia, Ukraine and Kyrgyzstan. However, a possible impact on the Arctic region was also identified; such an effect would have a serious influence on the polar atmospheric environment and on animals such as polar bears

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Mesoscale modeling and satellite observation of transport and mixing of smoke and dust particles over northern sub‐Saharan African region

et al. 2013

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The transport and vertical distribution of smoke and dust aerosols over the northern sub‐Saharan African region are simulated in the Weather Research and Forecasting model with Chemistry (WRF‐Chem), which uses hourly dynamic smoke emissions from the Fire Locating and Modeling of Burning Emissions database derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) fire products. Model performance for February 2008 is evaluated using MODIS true color images, aerosol optical depth (AOD) measurements from the Aerosol Robotic Network, MODIS AOD retrievals, and the Cloud‐Aerosol Lidar data with Orthogonal Polarization (CALIOP) atmospheric backscattering and extinction products. Specification of smoke injection height of 650 m in WRF‐Chem yields aerosol vertical profiles that are most consistent with CALIOP observations of aerosol layer height. Between the equator and 10°N, Saharan dust is often mixed with smoke near the surface, and their transport patterns manifest the interplay of trade winds, subtropical highs, precipitation associated with the Intertropical Convergence Zone, and the high mountains located near the Great Rift Valley region. At the 700 hPa level and above, smoke layers spread farther to the north and south and are often above the dust layers over the Sahel region. In some cases, transported smoke can also be mixed with dust over the Saharan region. Statistically, 5% of the CALIOP valid measurements in February 2007–2011 show aerosol layers either above or between the clouds, reinforcing the importance of the aerosol vertical distribution for quantifying aerosol impact on climate in the Sahel region.

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Multispectral remote sensing of biomass burning in West Africa

Cited by 26 publications

References 36 publications

Integration of remote sensing data and surface observations to estimate the impact of the Russian wildfires over Europe and Asia during August 2010

Integration of remote sensing data and surface observations to estimate the impact of the Russian wildfires over Europe and Asia during August 2010

Integration of remote sensing data and surface observations to estimate the impact of the russian wildfires over Europe and Asia during August 2010

Mesoscale modeling and satellite observation of transport and mixing of smoke and dust particles over northern sub‐Saharan African region

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