scholarly journals Determinação e modelagem da taxa de consumo de biomassa queimada

2012 ◽  
Vol 27 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Gabriel Pereira ◽  
Francielle da Silva Cardozo ◽  
Fabrício Brito Silva ◽  
Elisabete Caria Moraes ◽  
Nelson Jesus Ferreira ◽  
...  

O presente trabalho avalia o emprego da energia radiativa do fogo (ERF) para estimar as emissões de material particulado com diâmetro menor que 2,5µm (PM2,5µm), a partir da obtenção do coeficiente multiplicativo, que relaciona o consumo de biomassa com a ERF liberada. Para isto, foram utilizados dados provenientes dos produtos do MODIS (Moderate Resolution Imaging Spectroradiometer) e do produto derivado do satélite GOES (Geostationary Operational Environmental Satellite), para calcular o total de aerossóis emitidos para a atmosfera. O CCATT-BRAMS (Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modelling System) foi utilizado para estimar a concentração de PM2,5µm provenientes da queima de biomassa. Estes dados foram comparados com os dados de campo obtidos nos experimentos do LBA (Large Scale Biosphere-Atmosphere) SMOCC (Smoke, Aerosols, Clouds, rainfall, and Climate) e RaCCI (Radiation, Cloud, and Climate Interactions). A estimativa da emissão de PM2,5µm (µg.m-3) apresentou uma correlação com os dados do SMOCC/RaCCI superiores a 92%. Ainda, constatou-se que o consumo máximo diário pode exceder 5 Tg (milhões de toneladas), com uma média diária de 2,1 Tg. O método resultante das análises de laboratório permitiu estimar a biomassa consumida em 0,28 ± 0,01 Pg (10(15) g) para a América do Sul, entre Julho e Novembro de 2002.

Author(s):  
Eiji Nunohiro ◽  
◽  
Kei Katayama ◽  
Kenneth J. Mackin ◽  
Jong Geol Park ◽  
...  

Tokyo University of Information Sciences receives MODIS (Moderate Resolution Imaging Spectroradiometer) data from NASA’s Terra and Aqua satellites, and provides the processed data to universities and research institutes as part of the academic frontier project. This paper considers the utilization of MODIS data for a system to search for fire regions in forests and fields. For the search system to be effective, the system must be able to extract the location, range and distribution of fires in forests and fields from a large scale image database quickly with high accuracy. In order to achieve high search response time and to improve the accuracy of the analysis, we propose a forest and field fire search system which implements a) a parallel distributed system configuration using multiple PC clusters, and b) MOD02, MOD03 and MOD09 process levels of MODIS data for input data which provide higher resolution and more accurate readings than the standard MOD14 process level data.


2020 ◽  
Author(s):  
Chuyong Lin ◽  
Jason Cohen

<p>A simple variance-maximization approach, based on 19 years of weekly Moderate Resolution Imaging spectroradiometer (MOPITT) CO vertical measurements, was employed to quantify the spatial distribution of the global seasonal biomass burning region. Results demonstrate there are a few large-scale and typical biomass burning regions responsible for most of the biomass burning emissions throughout the world, with the largest of these such regions located in Amazonian South America, Western Africa, Indonesia, and Northern Southeast Asia (Eastern India, Northern Myanmar, Laos, Vietnam and Eastern Bangladesh), which are highly associated with the results of Global Fire Emission Database(GFED). The CO is primarily lofted to and spreads downwind at 800mb or 700mb with three exceptions: The Maritime Continent and South America where there is significant spread at 300mb consistent with known deep- and pyro-convection; and Southern Africa where there is significant spread at 600mb. The total mass of CO lofted into the free troposphere ranges from 46% over Central Africa to 92% over Australia.</p>


2019 ◽  
Vol 11 (3) ◽  
pp. 314 ◽  
Author(s):  
Rita Condé ◽  
Jean-Michel Martinez ◽  
Marco Pessotto ◽  
Raúl Villar ◽  
Gérard Cochonneau ◽  
...  

In this study, we used moderate resolution imaging spectroradiometer (MODIS) satellite images to quantify the sedimentation processes in a cascade of six hydropower dams along a 700-km transect in the Paranapanema River in Brazil. Turbidity field measurement acquired over 10 years were used to calibrate a turbidity retrieval algorithm based on MODIS surface reflectance products. An independent field dataset was used to validate the remote sensing estimates showing fine accuracy (RMSE of 9.5 NTU, r = 0.75, N = 138). By processing 13 years of MODIS images since 2000, we showed that satellite data can provide robust turbidity monitoring over the entire transect and can identify extreme sediment discharge events occurring on daily to annual scales. We retrieved the decrease in the water turbidity as a function of distance within each reservoir that is related to sedimentation processes. The remote sensing-retrieved turbidity decrease within the reservoirs ranged from 2 to 62% making possible to infer the reservoir type and operation (storage versus run-of-river reservoirs). The reduction in turbidity assessed from space presented a good relationship with conventional sediment trapping efficiency calculations, demonstrating the potential use of this technology for monitoring the intensity of sedimentation processes within reservoirs and at large scale.


2010 ◽  
Vol 49 (3) ◽  
pp. 463-477 ◽  
Author(s):  
David Painemal ◽  
René Garreaud ◽  
José Rutllant ◽  
Paquita Zuidema

Abstract Stratocumulus cloud cover patterns and their relationship to drizzle were characterized at San Felix Island (SFI; 26.5°S, 80°W) in the southeast Pacific Ocean. Small closed, large closed, and open cells were identified in about 65% of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images during 2003. The MODIS imagery was combined with ceilometer and surface meteorological measurements, human observations of cloud types and drizzle, and large-scale meteorological analyses for January through June. The authors identified two drizzle regimes: a synoptically quiescent summer (January–March) regime characterized by a strong anticyclone, large closed cells, and frequent drizzle, and an autumn (April–June) regime characterized by a weaker anticyclone, small closed cells and open cells, and precipitation that was mainly associated with synoptic activity. The large closed cells had higher mean cloud bases and tops than the small closed cells and accounted for 45% of the cumulus-under-stratocumulus reports and 29% of the total drizzle and rain reports. Large closed cells occupied more intermittently coupled boundary layers than did the small closed cells. Open cells also occurred in more decoupled conditions but only accounted for 18% of the total reports of drizzle and rain. The atmospheric stability of large and small closed cells was similar, but large closed cells were more commonly associated with a strong anticyclone, and small closed cells with wave activity superimposed upon a weakened anticyclone. The increased drizzle and occurrence of cumulus-under-stratocumulus in the summer rather than autumn is consistent with higher nighttime liquid water paths. A contribution of this study is the documentation of the ways in which synoptic activity can affect stratocumulus decks.


2021 ◽  
Vol 13 (6) ◽  
pp. 1151
Author(s):  
Tamás Várnai ◽  
Alexander Marshak

This paper examines cloud-related variations of atmospheric aerosols that occur in partly cloudy regions containing low-altitude clouds. The goal is to better understand aerosol behaviors and to help better represent the radiative effects of aerosols on climate. For this, the paper presents a statistical analysis of a multi-month global dataset that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instruments with data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis. Among other findings, the results reveal that near-cloud enhancements in lidar backscatter (closely related to aerosol optical depth) are larger (1) over land than ocean by 35%, (2) near optically thicker clouds by substantial amounts, (3) for sea salt than for other aerosol types, with the difference from dust reaching 50%. Finally, the study found that mean lidar backscatter is higher near clouds not because of large-scale variations in meteorological conditions, but because of local processes associated with individual clouds. The results help improve our understanding of aerosol-cloud-radiation interactions and our ability to represent them in climate models and other atmospheric models.


2016 ◽  
Author(s):  
Antigoni Panagiotopoulou ◽  
Panagiotis Charalambidis ◽  
Christos Fountoukis ◽  
Christodoulos Pilinis ◽  
Spyros N. Pandis

Abstract. The ability of the chemical transport model (CTM) PMCAMx to reproduce aerosol optical depth (AOD) measurements by the Aerosol Robotic Network (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) over Europe during a photochemically active period is evaluated. Periods with high dust levels are excluded so the analysis focuses on the ability of the model to simulate the mostly secondary aerosol and its interactions with water. PMCAMx reproduces the monthly mean MODIS and AERONET AOD values over the Iberian Peninsula, the British Isles, central Europe, and Russia with fractional bias less than 15 % and fractional error less than 30 %. However, the model overestimates the AOD over northern Europe probably due to an overestimation of organic aerosol and sulfates. On the other end, PMCAMx underestimates the monthly mean MODIS AOD over the Balkans, the Mediterranean, and the South Atlantic. These errors are probably due to an underestimation of sulfates. Sensitivity tests indicate that the evaluation results of the monthly mean AODs are quite sensitive to the relative humidity (RH) fields used by PMCAMx, but are not sensitive to the simulated size distribution and the black carbon mixing state.


2020 ◽  
Vol 41 (5supl1) ◽  
pp. 2419-2428
Author(s):  
Willyan Ronaldo Becker ◽  
Jonathan Richetti ◽  
Erivelto Mercante ◽  
Júlio César Dalla Mora Esquerdo ◽  
Carlos Antonio da Silva Junior ◽  
...  

Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the SD, the difference in the maturation cycles of the cultivars, and regional climatic variation, the HD of soybean varied greatly during the studied crop years, ranging from mid-February to late March. The SD of corn is before that of soybean, and mainly occurs in late September to mid-October. The DMVD mainly occurs during December, and the HD is distributed throughout January to March in Paraná. When comparing the estimated dates with observed dates the mean error (ME) varied from 0.2 days earlier to 3.3 days after the observed date for soybean with root mean square error (RMSE) from 1.93 to 14.73 days. For corn, the ME varied from 10.3 days to 18.5 days after the observed date with RMSE from 18.02 to 27.82 days.


Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.


2021 ◽  
Vol 13 (15) ◽  
pp. 2895
Author(s):  
Maria Gavrouzou ◽  
Nikolaos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Christos J. Lolis ◽  
Nikolaos Mihalopoulos

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.


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