Linking the chemical composition and optical properties of biomass burning aerosols in Amazonia

Ponczek, Milena; Franco, Marco Aurélio; Carbone, Samara; Rizzo, L. V.; Santos, Djacinto Monteiro dos; Morais, Fernando; Duarte, Alejandro Fonseca; Barbosa, H. M.; Artaxo, Paulo

doi:10.1039/d1ea00055a

Cited by 16 publications

(12 citation statements)

References 102 publications

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“…BrC exhibits a broad range of optical properties due to its diverse sources and dynamic transformations during atmospheric aging. − Recent studies have begun revealing the relationship between BrC’s optical properties and its chemical composition. − Accordingly, BrC is classified into four optically based groups: very weakly (VW), weakly (W), moderately (M), or strongly (S)absorbing BrC . The VW group portrays BrC formed in secondary organic aerosols, while the W and M groups represent BrC originating from primary BB emissions. − The S group delineates highly viscous particles that have undergone significant transformations, such as refractory carbonaceous spheres (tar balls). , Chemical analysis of BrC materials representing these groups has revealed distinct physicochemical properties, including unique wavelength absorption spectra, molecular weight, elemental and structural composition, oxidation state, volatility, aqueous solubility, and more. ,,,, These characteristics serve as metrics for comparing and apportioning BrC observed in real-world studies within the proposed optically based classification framework.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Light Absorption and Elevated Viscosity of Atmospheric Brown Carbon through Evaporation of Volatile Components

Calderon-Arrieta,

Morales,

Hettiyadura

et al. 2024

Environ. Sci. Technol.

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Samples of brown carbon (BrC) material were collected from smoke emissions originating from wood pyrolysis experiments, serving as a proxy for BrC representative of biomass burning emissions. The acquired samples, referred to as "pyrolysis oil (PO 1 )," underwent subsequent processing by thermal evaporation of their volatile compounds, resulting in a set of three additional samples with volume reduction factors of 1.33, 2, and 3, denoted as PO 1.33 , PO 2 , and PO 3 . The chemical compositions of these PO x samples and their BrC chromophore features were analyzed using a high-performance liquid chromatography instrument coupled with a photodiode array detector and a high-resolution mass spectrometer. The investigation revealed a noteworthy twofold enhancement of BrC light absorption observed for the progression of PO 1 to PO 3 samples, assessed across the spectral range of 300−500 nm. Concurrently, a decrease in the absorption Ångstrom exponent (AAE) from 11 to 7 was observed, indicating a weaker spectral dependence. The relative enhancement of BrC absorption at longer wavelengths was more significant, as exemplified by the increased mass absorption coefficient (MAC) measured at 405 nm from 0.1 to 0.5 m 2 /g. Molecular characterization further supports this darkening trend, manifesting as a depletion of small oxygenated, less absorbing monoaromatic compounds and the retention of relatively large, less polar, more absorbing constituents. Noteworthy alterations of the PO 1 to PO 3 mixtures included a reduction in the saturation vapor pressure of their components and an increase in viscosity. These changes were quantified by the mean values shifting from approximately 1.8 × 10 3 μg/m 3 to 2.3 μg/m 3 and from ∼10 3 Pa•s to ∼10 6 Pa•s, respectively. These results provide quantitative insights into the extent of BrC aerosol darkening during atmospheric aging through nonreactive evaporation. This new understanding will inform the refinement of atmospheric and chemical transport models.

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Section: Introductionmentioning

confidence: 99%

Enhanced Light Absorption and Elevated Viscosity of Atmospheric Brown Carbon through Evaporation of Volatile Components

Calderon-Arrieta,

Morales,

Hettiyadura

et al. 2024

Environ. Sci. Technol.

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“…3,9,10 Analysis of the spatial distribution of FB is fundamental to understanding the structural changes in the vegetation composition and supporting definition of measures for biodiversity conservation and forest management. 1,3,11,12 The FB can be estimated using direct and indirect methodological approaches. To apply direct methods, the biomass measurement is conducted based on destructive methods, which requires cutting down the trees of interest.…”

Section: Introductionmentioning

confidence: 99%

“…FB has been studied for a variety of purposes, including nutrient cycling, energy use, and evaluation of arboreal species growth 3 , 9 , 10 . Analysis of the spatial distribution of FB is fundamental to understanding the structural changes in the vegetation composition and supporting definition of measures for biodiversity conservation and forest management 1 , 3 , 11 , 12 …”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence tools and vegetation indices combined to estimate aboveground biomass in tropical forests

Costa

Pinto

Miguel

et al. 2023

J. Appl. Rem. Sens.

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Measurement of forest biomass is a time-, money-, and labor-consuming activity.Developing methodological approaches for quantifying biomass in natural ecosystems has motivated countless investigations in several vegetation types worldwide. In this study, we developed a model to estimate the above-ground biomass (AGB) in a study site spatially located in Western Pará state, Brazilian Amazon. We applied artificial neural networks and remotely sensed data for adjusting our model based on forest inventory data. We tested four vegetation indices retrieved from a Landsat-5 thematic mapper scene and assessed their correlations with the field measured AGB. We trained 286 artificial neural networks using the vegetation stratus (two phytophysiognomies: dense lowland ombrophilous forest and dense submontane ombrophilous forest) and the normalized difference vegetation index (NDVI) and aerosol-free vegetation index as predictors variables of the AGB. We selected the artificial neural network model showing higher correlation coefficient and concentration of residuals in the center classes, which indicates higher predictive capabilities of biomass estimation. The generated model architecture (4-13-1) was composed by 4 predictor neurons in the input layer, 13 neurons in the hidden layer, activated by logistic functions, and a single neuron (the AGB in ton • ha −1 ) in the output layer, activated by an identity function. We observed that the NDVI and aerosol free vegetation index showed the best performance to estimate the AGB in the study area. Using artificial neural network and a Landsat-5 image combined, we were able to accurately predict (estimation error of ∼20%) AGB in tropical forest. This is a promising methodological approach that can be applied to assess ecosystem services related to carbon stock in tropical regions.

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“…It is essential to understand the optical properties of aerosol particles, as total aerosol optical depth (AOD), single-scattering albedo (SSA), the Ångström exponent (AE), and their chemical composition, to evaluate their influence on the radiation balance and resolve uncertainties regarding their impact on the climate [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Chemical Characterization and Optical Properties of the Aerosol in São Paulo, Brazil

Vieira,

do Rosario,

Yamasoe

et al. 2023

Atmosphere

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Air pollution in the Metropolitan Area of São Paulo (MASP), Brazil, is a serious problem and is strongly affected by local sources. However, atmosphere column composition in MASP is also affected by biomass burning aerosol (BB). Understanding the impacts of aerosol particles, from both vehicles and BB, on the air quality and climate depends on in-depth research with knowledge of some parameters such as the optical properties of particles and their chemical composition. This study characterized fine particulate matter (PM2.5) from July 2019 to August 2020 in the eastern part of the MASP, relating the chemical composition data obtained at the surface and columnar optical parameters, such as aerosol optical depth (AOD), Ångström Exponent (AE), and single-scattering albedo (SSA). According to the analyzed data, the mean PM2.5 concentration was 18.0 ± 12.5 µg/m3; however, daily events exceeded 75 times the air quality standard of the World Health Organization (15 µg/m3). The mean black carbon concentration was 1.8 ± 1.5 µg/m3 in the sampling period. Positive matrix factorization (PMF) identified four main sources of aerosol: heavy vehicles (42%), followed by soil dust plus local sources (38.7%), light vehicles (9.9%), and local sources (8.6%). AOD and AE presented the highest values in the dry period, during which biomass burning events are more frequent, suggesting smaller particles in the atmosphere. SSA values at 440 nm were between 0.86 and 0.94, with lower values in the winter months, indicating the presence of more absorbing aerosol.

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Linking the chemical composition and optical properties of biomass burning aerosols in Amazonia

Abstract: Biomass burning emissions in Amazonia changes the atmospheric composition and aerosol properties during the dry season. We investigated fine-mode aerosol chemical composition and optical properties at an intensive field experiment...

Cited by 16 publications

References 102 publications

Enhanced Light Absorption and Elevated Viscosity of Atmospheric Brown Carbon through Evaporation of Volatile Components

Enhanced Light Absorption and Elevated Viscosity of Atmospheric Brown Carbon through Evaporation of Volatile Components

Artificial intelligence tools and vegetation indices combined to estimate aboveground biomass in tropical forests

Chemical Characterization and Optical Properties of the Aerosol in São Paulo, Brazil

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