Monitoring the transport of biomass burning emissions in South America

Freitas, Saulo R.; Longo, Karla M.; Dias, Maria A. F. Silva; Dias, Pedro; Chatfield, R. B.; Prins, E. M.; Artaxo, Paulo; Grell, Georg; Recuero, Fernando S.

doi:10.1007/s10652-005-0243-7

Cited by 271 publications

(259 citation statements)

References 45 publications

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“…Methodologies currently do not consider the fire type explicitly and typically model emissions on the basis of the dominant land cover or vegetation type where active fires are detected (Freitas et al 2005;van der Werf et al 2008;Ichoku and Ellison 2013;Castellanos, Boersma, and Van Der Werf 2014;Mitchard et al 2014). The spatial distribution of the classified fire types may help provide more reliable parameterization of the biomass loading, combustion completeness, and emission factors that differ among the fire types.…”

Section: Discussionmentioning

confidence: 99%

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

Roy

Kumar

2016

International Journal of Digital Earth

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The Brazilian Tropical Moist Forest Biome (BTMFB) spans almost 4 million km 2 and is subject to extensive annual fires that have been categorized into deforestation, maintenance, and forest fire types. Information on fire types is important as they have different atmospheric emissions and ecological impacts. A supervised classification methodology is presented to classify the fire type of MODerate resolution Imaging Spectroradiometer (MODIS) active fire detections using training data defined by consideration of Brazilian government forest monitoring program annual land cover maps, and using predictor variables concerned with fuel flammability, fuel load, fire behavior, fire seasonality, fire annual frequency, proximity to surface transportation, and local temperature. The fire seasonality, local temperature, and fuel flammability were the most influential on the classification. Classified fire type results for all 1.6 million MODIS Terra and Aqua BTMFB active fire detections over eight years (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) are presented with an overall fire type classification accuracy of 90.9% (kappa 0.824). The fire type user's and producer's classification accuracies were respectively 92.4% and 94.4% (maintenance fires), 88.4% and 87.5% (forest fires), and, 88.7% and 75.0% (deforestation fires). The spatial and temporal distribution of the classified fire types are presented and are similar to patterns reported in the available recent literature. ARTICLE HISTORY

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Section: Discussionmentioning

confidence: 99%

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

Roy

Kumar

2016

International Journal of Digital Earth

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“…Although the seasonal variability in the average convective available potential energy (CAPE) is small, the tail of the CAPE seasonal distribution (computed as the surface parcel) exhibits relatively higher values during the dry to wet season transition than during the wet season (Williams et al, 2002). During the dry season, the aerosols produced by biomass burning in central South America impact a larger area, reaching the tropical Pacific, subtropical South America, and the South Atlantic Freitas et al, 2005Freitas et al, , 2017Camponogara et al, 2014).…”

Section: The Amazon Forest Climatementioning

confidence: 99%

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

et al. 2018

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Abstract. This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the massweighted mean diameter) were quantified over both seasons.The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only durPublished by Copernicus Publications on behalf of the European Geosciences Union. L. A. T. Machado et al.: Overview: Precipitation characteristics and sensitivities to environmental conditionsing the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

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“…Black carbon aerosols over the south-western part of the Atlantic Ocean are mostly due to the biomass burning in South America (Freitas et al, 2005;Evangelista et al, 2007). ABB is known to emit lots of aerosols, especially BBA and gaseous particles (Xue et al, 2012).…”

Section: Agriculture Biomass Burningmentioning

confidence: 99%

A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data

Mukai

Nakata

Yasumoto

et al. 2015

Front. Environ. Sci.

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Aerosol distributions in East Asia are complicated owing to both natural factors and human activities. In recent years, influence of yellow sand and biomass burning aerosols generated by agricultural biomass burning (ABB) has been noted upon the severe air pollution episodes. This work intends to make the retrieval algorithm more efficient and to make the aerosol model more tractable as far as heavy air pollution caused by ABB is concerned. Aerosol retrieval in the hazy atmosphere is achieved based on radiation simulation method of successive order of scattering (MSOS) for the moderate resolution imaging spectroradiometer (MODIS) on AQUA data. The retrieved aerosol properties agree well with the ground measurements and numerical model simulations. Multi-angle observations with the polarization and directionality of the Earth's reflectances (POLDER) on the polarization & anisotropy of reflectances for atmospheric sciences coupled with observations from a lidar (PARASOL) are available for aerosol retrieval from a mixture of cloud and haze, and many potential applications of MSOS involving polarization information are expected to be available for cloud as well as aerosol episodes.

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Monitoring the transport of biomass burning emissions in South America

Cited by 271 publications

References 45 publications

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data

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