scholarly journals Global top-down smoke aerosol emissions estimation using satellite fire radiative power measurements

2013 ◽  
Vol 13 (10) ◽  
pp. 27327-27386 ◽  
Author(s):  
C. Ichoku ◽  
L. Ellison

Abstract. Biomass burning occurs seasonally in most vegetated parts of the world, consuming large amounts of biomass fuel, generating intense heat energy, and emitting corresponding amounts of smoke plumes that comprise different species of aerosols and trace gases. Accurate estimates of these emissions are required as model inputs to evaluate and forecast smoke plume transport and impacts on air quality, human health, clouds, weather, radiation, and climate. Emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. Fortunately, a series of recent studies have revealed that both the rate of biomass consumption and the rate of emission of aerosol particulate matter (PM) by open biomass burning are directly proportional to the rate of release of fire radiative energy (FRE), which is fire radiative power (FRP) that is measurable from satellite. This direct relationship enables the determination of coefficients of emission (Ce), which can be used to convert FRP or FRE to smoke aerosol emissions in the same manner as emission factors (EFs) are used to convert burned biomass to emissions. We have leveraged this relationship to generate the first global 1° × 1° gridded Ce product for smoke aerosol or total particulate matter (TPM) emissions using coincident measurements of FRP and aerosol optical thickness (AOT) from the Moderate-resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce product has now been released to the community and can be obtained from http://feer.gsfc.nasa.gov/, along with the corresponding 1-to-1 mapping of their quality assurance (QA) flags that will enable the Ce values to be filtered by quality for use in various applications. The regional averages of Ce values for different ecosystem types were found to be in the ranges of: 16–21 g MJ−1 for savanna and grasslands, 15–32 g MJ−1 for tropical forest, 9–12 g MJ−1 for North American boreal forest, about ~24 g MJ−1 for Russian boreal forest, and 18–26 g MJ−1 for Russian croplands and natural vegetation. The FEER.v1 Ce product was multiplied with FRP data to generate smoke TPM emissions, which were compared with equivalent emissions products from three existing inventories. The smoke TPM emissions results from FEER.v1 showed higher and more reasonable estimates than those of two other emissions inventories that are based on bottom up approaches and already reported in the literature to be too low, but portrayed an overall reasonable agreement with those of another inventory based on a hybrid method that includes the top-down approach, thereby suggesting that top-down approaches may hold better promise and need to be further developed to accelerate the reduction of uncertainty associated with fire emissions estimation in air-quality and climate research and applications. Based on analysis of data covering the period of 2004–2011, FEER.v1 results show that ~65–85 Tg yr−1 of TPM is emitted globally from open biomass burning, with a generally decreasing trend over this short time period. The FEER.v1 Ce product is the first global gridded product in the family of "emission factors", that is based essentially on satellite measurements, and requires only direct satellite FRP measurements of an actively burning fire anywhere to evaluate its emission rate in near real time, which is essential for operational activities, such as the monitoring and forecasting of smoke emission impacts on air quality.

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7075
Author(s):  
Daniel Fisher ◽  
Martin J. Wooster ◽  
Weidong Xu ◽  
Gareth Thomas ◽  
Puji Lestari

Extreme fires in the peatlands of South East (SE) Asia are arguably the world’s greatest biomass burning events, resulting in some of the worst ambient air pollution ever recorded (PM10 > 3000 µg·m−3). The worst of these fires coincide with El Niño related droughts, and include huge areas of smouldering combustion that can persist for months. However, areas of flaming surface vegetation combustion atop peat are also seen, and we show that the largest of these latter fires appear to be the most radiant and intensely smoke-emitting areas of combustion present in such extreme fire episodes. Fire emissions inventories and early warning of the air quality impacts of landscape fire are increasingly based on the fire radiative power (FRP) approach to fire emissions estimation, including for these SE Asia peatland fires. “Top-down” methods estimate total particulate matter emissions directly from FRP observations using so-called “smoke emission coefficients” [Ce; g·MJ−1], but currently no discrimination is made between fire types during such calculations. We show that for a subset of some of the most thermally radiant peatland fires seen during the 2015 El Niño, the most appropriate Ce is around a factor of three lower than currently assumed (~16.8 ± 1.6 g·MJ−1 vs. 52.4 g·MJ−1). Analysis indicates that this difference stems from these highly radiant fires containing areas of substantial flaming combustion, which changes the amount of particulate matter emitted per unit of observable fire radiative heat release in comparison to more smouldering dominated events. We also show that even a single one of these most radiant fires is responsible for almost 10% of the overall particulate matter released during the 2015 fire event, highlighting the importance of this fire type to overall emission totals. Discriminating these different fires types in ways demonstrated herein should thus ultimately improve the accuracy of SE Asian fire emissions estimates derived using the FRP approach, and the air quality modelling which they support.


2012 ◽  
Vol 9 (1) ◽  
pp. 527-554 ◽  
Author(s):  
J. W. Kaiser ◽  
A. Heil ◽  
M. O. Andreae ◽  
A. Benedetti ◽  
N. Chubarova ◽  
...  

Abstract. The Global Fire Assimilation System (GFASv1.0) calculates biomass burning emissions by assimilating Fire Radiative Power (FRP) observations from the MODIS instruments onboard the Terra and Aqua satellites. It corrects for gaps in the observations, which are mostly due to cloud cover, and filters spurious FRP observations of volcanoes, gas flares and other industrial activity. The combustion rate is subsequently calculated with land cover-specific conversion factors. Emission factors for 40 gas-phase and aerosol trace species have been compiled from a literature survey. The corresponding daily emissions have been calculated on a global 0.5° × 0.5° grid from 2003 to the present. General consistency with the Global Fire Emission Database version 3.1 (GFED3.1) within its accuracy is achieved while maintaining the advantages of an FRP-based approach: GFASv1.0 makes use of the quantitative information on the combustion rate that is contained in the FRP observations, and it detects fires in real time at high spatial and temporal resolution. GFASv1.0 indicates omission errors in GFED3.1 due to undetected small fires. It also exhibits slightly longer fire seasons in South America and North Africa and a slightly shorter fire season in Southeast Asia. GFASv1.0 has already been used for atmospheric reactive gas simulations in an independent study, which found good agreement with atmospheric observations. We have performed simulations of the atmospheric aerosol distribution with and without the assimilation of MODIS aerosol optical depth (AOD). They indicate that the emissions of particulate matter need to be boosted by a factor of 2–4 to reproduce the global distribution of organic matter and black carbon. This discrepancy is also evident in the comparison of previously published top-down and bottom-up estimates. For the time being, a global enhancement of the particulate matter emissions by 3.4 is recommended. Validation with independent AOD and PM10 observations recorded during the Russian fires in summer 2010 show that the global Monitoring Atmospheric Composition and Change (MACC) aerosol model with GFASv1.0 aerosol emissions captures the smoke plume evolution well when organic matter and black carbon are enhanced by the recommended factor. In conjunction with the assimilation of MODIS AOD, the use of GFASv1.0 with enhanced emission factors quantitatively improves the forecast of the aerosol load near the surface sufficiently to allow air quality warnings with a lead time of up to four days.


2011 ◽  
Vol 8 (4) ◽  
pp. 7339-7398 ◽  
Author(s):  
J. W. Kaiser ◽  
A. Heil ◽  
M. O. Andreae ◽  
A. Benedetti ◽  
N. Chubarova ◽  
...  

Abstract. The Global Fire Assimilation System (GFASv1.0) calculates biomass burning emissions by assimilating Fire Radiative Power (FRP) observations from the MODIS instruments onboard the Terra and Aqua satellites. It corrects for gaps in the observations, which are mostly due to cloud cover, and filters spurious FRP observations of volcanoes, gas flares and other industrial activity. The combustion rate is subsequently calculated with land cover-specific conversion factors. Emission factors for 40 gas-phase and aerosol trace species have been compiled from a literature survey. The corresponding daily emissions have been calculated on a global 0.5° × 0.5° grid from 2003 to the present. General consistency with the Global Fire Emission Database version 3.1 (GFED3.1) within its accuracy is achieved while maintaining the advantages of an FRP-based approach: GFASv1.0 makes use of the quantitative information on the combustion rate that is contained in the observations, and it detects fires in real time at high spatial and temporal resolution. GFASv1.0 indicates omission errors in GFED3.1 due to undetected small fires. It also exhibits slightly longer fire seasons in South America and North Africa and a slightly shorter fire season in Southeast Asia. GFASv1.0 has already been used for atmospheric reactive gas simulations in an independent study, which found good agreement with atmospheric observations. We have performed simulations of the atmospheric aerosol distribution with and without the assimilation of MODIS aerosol optical depth (AOD). They indicate that the emissions of particulate matter need to be boosted with a factor of 2–4 to reproduce the global distribution of organic matter and black carbon. This discrepancy is also evident in the comparison of previously published top-down and bottom-up estimates. For the time being, a global enhancement of the particulate matter emissions by 3.4 is recommended. Validation with independent AOD and PM10 observations recorded during the Russian fires in summer 2010 show that the global Monitoring Atmospheric Composition and Change (MACC) aerosol model with GFASv1.0 aerosol emissions captures the smoke plume evolution well when organic matter and black carbon are enhanced by the recommended factor. In conjunction with the assimilation of MODIS AOD, the use of GFASv1.0 with enhanced emission factors quantitatively improves the forecast of the aerosol load near the surface sufficiently to allow air quality warnings with a lead time of up to four days.


2014 ◽  
Vol 14 (13) ◽  
pp. 6643-6667 ◽  
Author(s):  
C. Ichoku ◽  
L. Ellison

Abstract. Fire emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. We present the development of a global gridded (1° × 1°) emission coefficients (Ce) product for smoke total particulate matter (TPM) based on a top-down approach using coincident measurements of fire radiative power (FRP) and aerosol optical thickness (AOT) from the Moderate-resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce product has now been released to the community and can be obtained from


2017 ◽  
Author(s):  
Francesca Di Giuseppe ◽  
Samuel Rémy ◽  
Florian Pappenberger ◽  
Fredrik Wetterhall

Abstract. The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass burning fire emission estimates from the Global Fire Assimilation System (GFAS). GFAS converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence where observed FRP from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an overestimation of fire duration, which in turn translates into an overestimation of emissions from fires. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.


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