The relative role of Amazonian and non-Amazonian fires in building up the aerosol optical depth in South America: A five year study (2005–2009)

2013 ◽  
Vol 122 ◽  
pp. 298-309 ◽  
Author(s):  
Fernando Castro Videla ◽  
Francesca Barnaba ◽  
Federico Angelini ◽  
Pablo Cremades ◽  
Gian Paolo Gobbi
2021 ◽  
Vol 13 (11) ◽  
pp. 2231
Author(s):  
Débora Souza Alvim ◽  
Júlio Barboza Chiquetto ◽  
Monica Tais Siqueira D’Amelio ◽  
Bushra Khalid ◽  
Dirceu Luis Herdies ◽  
...  

The scope of this work was to evaluate simulated carbon monoxide (CO) and aerosol optical depth (AOD) from the CAM-chem model against observed satellite data and additionally explore the empirical relationship of CO, AOD and fire radiative power (FRP). The simulated seasonal global concentrations of CO and AOD were compared, respectively, with the Measurements of Pollution in the Troposphere (MOPITT) and the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products for the period 2010–2014. The CAM-chem simulations were performed with two configurations: (A) tropospheric-only; and (B) tropospheric with stratospheric chemistry. Our results show that the spatial and seasonal distributions of CO and AOD were reasonably reproduced in both model configurations, except over central China, central Africa and equatorial regions of the Atlantic and Western Pacific, where CO was overestimated by 10–50 ppb. In configuration B, the positive CO bias was significantly reduced due to the inclusion of dry deposition, which was not present in the model configuration A. There was greater CO loss due to the chemical reactions, and shorter lifetime of the species with stratospheric chemistry. In summary, the model has difficulty in capturing the exact location of the maxima of the seasonal AOD distributions in both configurations. The AOD was overestimated by 0.1 to 0.25 over desert regions of Africa, the Middle East and Asia in both configurations, but the positive bias was even higher in the version with added stratospheric chemistry. By contrast, the AOD was underestimated over regions associated with anthropogenic activity, such as eastern China and northern India. Concerning the correlations between CO, AOD and FRP, high CO is found during March–April–May (MAM) in the Northern Hemisphere, mainly in China. In the Southern Hemisphere, high CO, AOD, and FRP values were found during August–September–October (ASO) due to fires, mostly in South America and South Africa. In South America, high AOD levels were observed over subtropical Brazil, Paraguay and Bolivia. Sparsely urbanized regions showed higher correlations between CO and FRP (0.7–0.9), particularly in tropical areas, such as the western Amazon region. There was a high correlation between CO and aerosols from biomass burning at the transition between the forest and savanna environments over eastern and central Africa. It was also possible to observe the transport of these pollutants from the African continent to the Brazilian coast. High correlations between CO and AOD were found over southeastern Asian countries, and correlations between FRP and AOD (0.5–0.8) were found over higher latitude regions such as Canada and Siberia as well as in tropical areas. Higher correlations between CO and FRP are observed in Savanna and Tropical forests (South America, Central America, Africa, Australia, and Southeast Asia) than FRP x AOD. In contrast, boreal forests in Russia, particularly in Siberia, show a higher FRP x AOD correlation than FRP x CO. In tropical forests, CO production is likely favored over aerosol, while in temperate forests, aerosol production is more than CO compared to tropical forests. On the east coast of the United States, the eastern border of the USA with Canada, eastern China, on the border between China, Russia, and Mongolia, and the border between North India and China, there is a high correlation of CO x AOD and a low correlation between FRP with both CO and AOD. Therefore, such emissions in these regions are not generated by forest fires but by industries and vehicular emissions since these are densely populated regions.


2016 ◽  
Vol 16 (23) ◽  
pp. 15097-15117 ◽  
Author(s):  
David A. Ridley ◽  
Colette L. Heald ◽  
Jasper F. Kok ◽  
Chun Zhao

Abstract. The role of mineral dust in climate and ecosystems has been largely quantified using global climate and chemistry model simulations of dust emission, transport, and deposition. However, differences between these model simulations are substantial, with estimates of global dust aerosol optical depth (AOD) that vary by over a factor of 5. Here we develop an observationally based estimate of the global dust AOD, using multiple satellite platforms, in situ AOD observations and four state-of-the-science global models over 2004–2008. We estimate that the global dust AOD at 550 nm is 0.030 ± 0.005 (1σ), higher than the AeroCom model median (0.023) and substantially narrowing the uncertainty. The methodology used provides regional, seasonal dust AOD and the associated statistical uncertainty for key dust regions around the globe with which model dust schemes can be evaluated. Exploring the regional and seasonal differences in dust AOD between our observationally based estimate and the four models in this study, we find that emissions in Africa are often overrepresented at the expense of Asian and Middle Eastern emissions and that dust removal appears to be too rapid in most models.


2012 ◽  
Vol 12 (7) ◽  
pp. 17465-17501 ◽  
Author(s):  
N. E. Rosário ◽  
K. M. Longo ◽  
S. R. Freitas ◽  
M. A. Yamasoe ◽  
R. M. Fonseca

Abstract. Intra-seasonal variability of smoke aerosol optical depth (AOD) and downwelling solar irradiance at the surface during the 2002 biomass burning season in South America was modeled using the Coupled Chemistry-Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS). Measurements of AOD from the AErosol RObotic NETwork (AERONET) and solar irradiance at the surface from the Solar Radiation Network (SolRad-NET) were used to evaluate model results. In general, the major features associated with AOD evolution over the southern part of the Amazon Basin and cerrado ecosystem are captured by the model. The main discrepancies were found for high aerosol loading events. In the northeastern portion of the Amazon Basin the model systematically underestimated AOD. This is likely due to the cloudy nature of the region, preventing accurate detection of the fire spots used in the emission model. Moreover, measured AOD were very often close to background conditions and emissions other than smoke were not considered in the simulation. Therefore, under the background scenario, one would expect the model to underestimate AOD. The issue of high aerosol loading events in the southern part of the Amazon and cerrado is also discussed in the context of emission shortcomings. The Cuiabá cerrado site was the only one where the highest quality AERONET data were unavailable. Thus, lower quality data were used. Root-mean-square-error (RMSE) between the model and observations decreased from 0.48 to 0.17 when extreme AOD events (AOD550 nm ≥ 1.0) and Cuiabá were excluded from analysis. Downward surface solar irradiance comparisons also followed similar trends when extremes AOD were excluded. This highlights the need to improve the modelling of the regional smoke plume in order to enhance the accuracy of the radiative energy budget. Aerosol optical model based on the mean intensive properties of smoke from the southern part of the Amazon Basin produced a radiative forcing efficiency (RFE) of −158 W m−2/AOD550 nm at noon. This value is in between −154 W m−2/AOD550 nm and −187 W m−2/AOD550 nm, the range obtained when spatial varying optical models were considered. The average 24 h surface forcing over the biomass burning season varied from −55 W m−2 close to smoke sources in the southern part of the Amazon Basin and cerrado to −10 W m−2 in remote regions of the Southeast Brazilian coast.


2017 ◽  
Vol 17 (6) ◽  
pp. 1623-1636 ◽  
Author(s):  
Bethania L. Lanzaco ◽  
Luis E. Olcese ◽  
Gustavo G. Palancar ◽  
Beatriz M. Toselli

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