scholarly journals Biomass burning emission inventory from burnt area data given by the SPOT-VEGETATION system in the frame of TRACE-P and ACE-Asia campaigns

2005 ◽  
Vol 110 (D9) ◽  
Author(s):  
C. Michel
Keyword(s):  
Biomass Burning ◽  
Emission Inventory ◽  
Burnt Area ◽  
Area Data

scholarly journals Emission Inventory Processing of Biomass Burning from A Global Dataset for Air Quality Modeling

2020 ◽  
Author(s):  
Ernesto Pino-Cortés ◽  
Samuel Carrasco ◽  
Luis A. Díaz-Robles ◽  
Francisco Cubillos ◽  
Fidel Vallejo ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Emission Inventory ◽  
Sparse Matrix ◽  
Local Level ◽  
Air Quality Modeling ◽  
Simulation Software ◽  
Atmospheric Pollutants ◽  
Fire Emissions ◽  
Quality Modeling

Wildfires generate large amounts of atmospheric pollutants yearly. The development of an emissions inventory for this activity is a challenge today, mainly to perform modeling of air quality. There are free available databases with historical information about this source. The main goal of this study was to process the results of biomass burning emissions for the year 2014 from the Global Fire Assimilation System (GFAS). The pollutants studied were the black carbon, the organic carbon, fine and coarse particulate matter, respectively. The inputs were pre-formatted to enter to the simulation software of the emission inventory. In this case, the Sparse Matrix Operator Kernel Emissions (SMOKE) was used and the values obtained in various cities were analyzed. As a result, the spatial distribution of the forest fire emissions in the Southern Hemisphere was achieved, with the polar stereographic projection. The highest emissions were located in the African continent, followed by the northern region of Australia. Future air quality modeling at a local level could apply the results and the methodology of this study. The biomass burning emissions could add a better performance of the results and more knowledge on the effect of this source.

scholarly journals The wildland fire emission inventory: western United States emission estimates and an evaluation of uncertainty

2011 ◽  
Vol 11 (24) ◽  
pp. 12973-13000 ◽  
Author(s):  
S. P. Urbanski ◽  
W. M. Hao ◽  
B. Nordgren
Keyword(s):  
United States ◽  
Biomass Burning ◽  
Emission Factor ◽  
Emission Inventory ◽  
Wildland Fire ◽  
Western United States ◽  
Burned Area ◽  
Emission Inventories ◽  
Fuel Loading ◽  
Global Modeling

Abstract. Biomass burning emission inventories serve as critical input for atmospheric chemical transport models that are used to understand the role of biomass fires in the chemical composition of the atmosphere, air quality, and the climate system. Significant progress has been achieved in the development of regional and global biomass burning emission inventories over the past decade using satellite remote sensing technology for fire detection and burned area mapping. However, agreement among biomass burning emission inventories is frequently poor. Furthermore, the uncertainties of the emission estimates are typically not well characterized, particularly at the spatio-temporal scales pertinent to regional air quality modeling. We present the Wildland Fire Emission Inventory (WFEI), a high resolution model for non-agricultural open biomass burning (hereafter referred to as wildland fires, WF) in the contiguous United States (CONUS). The model combines observations from the MODerate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua satellites, meteorological analyses, fuel loading maps, an emission factor database, and fuel condition and fuel consumption models to estimate emissions from WF. WFEI was used to estimate emissions of CO (ECO) and PM2.5 (EPM2.5) for the western United States from 2003–2008. The uncertainties in the inventory estimates of ECO and EPM2.5 (uECO and uEPM2.5, respectively) have been explored across spatial and temporal scales relevant to regional and global modeling applications. In order to evaluate the uncertainty in our emission estimates across multiple scales we used a figure of merit, the half mass uncertainty, ũEX (where X = CO or PM2.5), defined such that for a given aggregation level 50% of total emissions occurred from elements with uEX ũEX. The sensitivity of the WFEI estimates of ECO and EPM2.5 to uncertainties in mapped fuel loading, fuel consumption, burned area and emission factors have also been examined. The estimated annual, domain wide ECO ranged from 436 Gg yr−1 in 2004 to 3107 Gg yr−1 in 2007. The extremes in estimated annual, domain wide EPM2.5 were 65 Gg yr−1 in 2004 and 454 Gg yr−1 in 2007. Annual WF emissions were a significant share of total emissions from non-WF sources (agriculture, dust, non-WF fire, fuel combustion, industrial processes, transportation, solvent, and miscellaneous) in the western United States as estimated in a national emission inventory. In the peak fire year of 2007, WF emissions were ~20% of total (WF + non-WF) CO emissions and ~39% of total PM2.5 emissions. During the months with the greatest fire activity, WF accounted for the majority of total CO and PM2.5 emitted across the study region. Uncertainties in annual, domain wide emissions was 28% to 51% for CO and 40% to 65% for PM2.5. Sensitivity of ũECO and ũEPM2.5 to the emission model components depended on scale. At scales relevant to regional modeling applications (Δx = 10 km, Δt = 1 day) WFEI estimates 50% of total ECO with an uncertainty <133% and half of total EPM2.5 with an uncertainty <146%. ũECO and ũEPM2.5 are reduced by more than half at the scale of global modeling applications (Δ x = 100 km, Δ t = 30 day) where 50% of total emissions are estimated with an uncertainty <50% for CO and <64% for PM2.5. Uncertainties in the estimates of burned area drives the emission uncertainties at regional scales. At global scales ũECO is most sensitive to uncertainties in the fuel load consumed while the uncertainty in the emission factor for PM2.5 plays the dominant role in ũEPM2.5. Our analysis indicates that the large scale aggregate uncertainties (e.g. the uncertainty in annual CO emitted for CONUS) typically reported for biomass burning emission inventories may not be appropriate for evaluating and interpreting results of regional scale modeling applications that employ the emission estimates. When feasible, biomass burning emission inventories should be evaluated and reported across the scales for which they are intended to be used.

scholarly journals Evaluating simulated primary anthropogenic and biomass burning organic aerosols during MILAGRO: implications for assessing treatments of secondary organic aerosols

2009 ◽  
Vol 9 (16) ◽  
pp. 6191-6215 ◽  
Author(s):  
J. Fast ◽  
A. C. Aiken ◽  
J. Allan ◽  
L. Alexander ◽  
T. Campos ◽  
...  
Keyword(s):  
Organic Matter ◽  
Biomass Burning ◽  
Matrix Factorization ◽  
Emission Inventory ◽  
Organic Aerosols ◽  
Positive Matrix Factorization ◽  
Total Organic Matter ◽  
Positive Matrix ◽  
Large Fires ◽  
The City

Abstract. Simulated primary organic aerosols (POA), as well as other particulates and trace gases, in the vicinity of Mexico City are evaluated using measurements collected during the 2006 Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaigns. Since the emission inventories, transport, and turbulent mixing will directly affect predictions of total organic matter and consequently total particulate matter, our objective is to assess the uncertainties in predicted POA before testing and evaluating the performance of secondary organic aerosol (SOA) treatments. Carbon monoxide (CO) is well simulated on most days both over the city and downwind, indicating that transport and mixing processes were usually consistent with the meteorological conditions observed during MILAGRO. Predicted and observed elemental carbon (EC) in the city was similar, but larger errors occurred at remote locations since the overall CO/EC emission ratios in the national emission inventory were lower than in the metropolitan emission inventory. Components of organic aerosols derived from Positive Matrix Factorization of data from several Aerodyne Aerosol Mass Spectrometer instruments deployed both at ground sites and on research aircraft are used to evaluate the model. Modeled POA was consistently lower than the measured organic matter at the ground sites, which is consistent with the expectation that SOA should be a large fraction of the total organic matter mass. A much better agreement was found when modeled POA was compared with the sum of "primary anthropogenic" and "biomass burning" components derived from Positive Matrix Factorization (PMF) on most days, especially at the surface sites, suggesting that the overall magnitude of primary organic particulates released was reasonable. However, simulated POA from anthropogenic sources was often lower than "primary anthropogenic" components derived from PMF, consistent with two recent reports that these emissions are underestimated. The modeled POA was greater than the total observed organic matter when the aircraft flew directly downwind of large fires, suggesting that biomass burning emission estimates from some large fires may be too high.

scholarly journals Biomass burning emission inventory with daily resolution: Application to aircraft observations of Asian outflow

2003 ◽  
Vol 108 (D21) ◽  
Author(s):  
Colette L. Heald ◽  
Daniel J. Jacob ◽  
Paul I. Palmer ◽  
Mathew J. Evans ◽  
Glen W. Sachse ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Emission Inventory ◽  
Aircraft Observations

scholarly journals The Wildland Fire Emission Inventory: emission estimates and an evaluation of uncertainty

2011 ◽  
Vol 11 (8) ◽  
pp. 23349-23419
Author(s):  
S. P. Urbanski ◽  
W. M. Hao ◽  
B. Nordgren
Keyword(s):  
United States ◽  
Biomass Burning ◽  
Emission Inventory ◽  
Wildland Fire ◽  
Western United States ◽  
Emission Inventories ◽  
Wildland Fires ◽  
Global Modeling ◽  
Fire Emissions ◽  
Pm2.5 Emissions

Abstract. We present the Wildland Fire Emission Inventory (WFEI), a high resolution model for non-agricultural open biomass burning (hereafter referred to as wildland fires) in the contiguous United States (CONUS). WFEI was used to estimate emissions of CO and PM2.5 for the western United States from 2003–2008. The estimated annual CO emitted ranged from 436 Gg yr−1 in 2004 to 3107 Gg yr−1 in 2007. The extremes in estimated annual PM2.5 emitted were 65 Gg yr−1 in 2004 and 454 Gg yr−1 in 2007. Annual wildland fire emissions were significant compared to other emission sources in the western United States as estimated in a national emission inventory. In the peak fire year of 2007, fire emissions were ~20 % of total CO emissions and ~39 % of total PM2.5 emissions. During the months with the greatest fire activity, wildland fires accounted for the majority of CO and PM2.5 emitted across the study region. The uncertainty in the inventory estimates of CO and PM2.5 emissions (ECO and EPM2.5, respectively) have been quantified across spatial and temporal scales relevant to regional and global modeling applications. The uncertainty in annual, domain wide emissions was 28 % to 51 % for CO and 40 % to 65 % for PM2.5. Sensitivity of the uncertainty in ECO and EPM2.5 to the emission model components depended on scale. At scales relevant to regional modeling applications (Δx = 10 km, Δt = 1 day) WFEI estimates 50 % of total ECO with an uncertainty <133 % and half of total EPM2.5 with an uncertainty <146 %. The uncertainty in ECO and EPM2.5 is significantly reduced at the scale of global modeling applications (Δx = 100 km, Δt = 30 day). Fifty percent of total emissions are estimated with an uncertainty <50 % for CO and <64 % for PM2.5. Uncertainty in the burned area drives the emission uncertainties at regional scales. At global scales the uncertainty in ECO is most sensitive to uncertainties in the fuel load consumed while the uncertainty in the emission factor for PM2.5 drives the EPM2.5 uncertainty. Our uncertainty analysis indicates that the large scale aggregate uncertainties (e.g. annual, CONUS) that are typically reported for biomass burning emission inventories may not be appropriate for evaluating and interpreting results of modeling applications that employ the emission estimates. When feasible, biomass burning emission inventories should be evaluated and reported across the scales for which they are intended to be used.

scholarly journals Wildfires in Northern Eurasia affect the budget of black carbon in the Arctic. A 12-year retrospective synopsis (2002–2013).

2016 ◽  
Author(s):  
N. Evangeliou ◽  
Y. Balkanski ◽  
W. M. Hao ◽  
A. Petkov ◽  
R. P. Silverstein ◽  
...  
Keyword(s):  
Black Carbon ◽  
Northern Hemisphere ◽  
Biomass Burning ◽  
Emission Inventory ◽  
Atmospheric Composition ◽  
Anthropogenic Sources ◽  
The Arctic ◽  
Northern Eurasia ◽  
Fire Emissions ◽  
Vegetation Fires

Abstract. In recent decades much attention has been given to the Arctic environment, where climate change is happening rapidly. Black carbon (BC) has been shown to be a major component of Arctic pollution that also affects the radiative balance. In the present study, we focused on how vegetation fires that occurred in Northern Eurasia during the period of 2002–2013 influenced the budget of BC in the Arctic. For simulating the transport of fire emissions from Northern Eurasia to the Arctic, we adopted BC fire emission estimates developed independently by GFED3 (Global Fire Emissions Database) and FEI-NE (Fire Emission Inventory – Northern Eurasia). Both datasets were based on fire locations and burned areas detected by MODIS (MODerate resolution Imaging Spectroradiometer) instruments on NASA's (National Aeronautics and Space Administration) Terra and Aqua satellites. Anthropogenic sources of BC were estimated using the MACCity (Monitoring Atmospheric Composition &amp; Climate/megaCITY – Zoom for the ENvironment) emission inventory. During the 12-year period, an average area of 250,000 km2 yr−1 was burned in Northern Eurasia and the global emissions of BC ranged between 8.0 and 9.5 Tg yr−1. For the BC emitted in the Northern Hemisphere, about 70 % originated from anthropogenic sources and the rest from biomass burning (BB). Using the FEI-NE inventory, we found that 102 ± 29 kt yr−1 BC from biomass burning was deposited on the Arctic (defined here as the area north of 67º N) during the 12 years simulated, which was twice as much as when using MACCity inventory (56 ± 8 kt yr−1). The annual mass of BC deposited in the Arctic from all sources (FEI-NE in Northern Eurasia, MACCity elsewhere) is significantly higher by about 37 % in 2009 to 181 % in 2012, compared to the BC deposited using just the MACCity emission inventory. Deposition of BC in the Arctic from BB sources in the Northern Hemisphere thus represents 68 % of the BC deposited from all BC sources (the remaining being due to anthropogenic sources). Northern Eurasian vegetation fires (FEI-NE) contributed 85 % (79–91 %) to the BC deposited over the Arctic from all BB sources in the Northern Hemisphere. Arctic total BC burden showed strong seasonal variations, with highest values during the Arctic Haze season. High winter–spring values of BC burden were caused by transport of BC mainly from anthropogenic sources in Europe, whereas the peak in summer was mainly due to the fire emissions in Northern Eurasia. BC particles emitted from fires in lower latitudes (35° N–40° N) were found to remain the longest in the atmosphere due to the high release altitudes of smoke plumes, exhibit tropospheric transport resulting in a high summer peak of burden, and grow by condensation processes. In regards to the geographic contribution on the deposition of BC, we estimated that about 46 % of the BC deposited over the Arctic from vegetation fires in Northern Eurasia originated from Siberia, 6 % from Kazakhstan, 5 % from Europe, and about 1 % from Mongolia. The remaining 42 % originated from other areas in Northern Eurasia. For spring and summer, we computed that 42 % of the BC released from Northern Eurasian vegetation fires was deposited over the Arctic (annual average: 17 %). Vegetation fires in Northern Eurasia contributed to 14 % to 57 % of BC surface concentrations at the Arctic stations (Alert, Barrow, Zeppelin, Villum, and Tiksi), with fires in Siberia contributing the largest share. However, anthropogenic sources in the Northern Hemisphere remain essential, contributing 29 % to 54 % to the surface concentrations at the Arctic monitoring stations. The rest originated from North American fires.

scholarly journals A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China

2016 ◽  
Author(s):  
Ying Zhou ◽  
Xiaofan Xing ◽  
Jianlei Lang ◽  
Dongsheng Chen ◽  
Shuiyuan Cheng ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Emission Inventory ◽  
Harmful Effect ◽  
Temporal Distribution ◽  
Geographical Information ◽  
So2 Emissions ◽  
Crop Straw ◽  
Key Species ◽  
Straw Burning

Abstract. Biomass burning injects many different gases and aerosols into the atmosphere, which could have a harmful effect on air quality, climate change and human health. In this study, a comprehensive biomass burning emission inventory including crop straw domestic combustion and in field burning, firewood and livestock excrement combustion, forest and grassland fire was developed for mainland China in 2012 based on county-level activity data and updated source-specific emission factors (EFs). The emission inventory within 1 × 1 km grid was generated using geographical information system (GIS) technology according to source-based spatial surrogates. A range of key information related to emission estimation (e.g., province-specific proportion of crop straw domestic burning and open burning, detailed firewood combustion quantities, uneven temporal distribution coefficient) was obtained from field investigation, systematic combing of the latest research and regression analysis of statistical data. The established emission inventory includes the major precursors of complex pollution, greenhouse gases and heavy metal released from biomass burning. The results show that the emissions of SO2, NOx, PM10, PM2.5, VOC, NH3, CO, EC, OC, CO2, CH4 and Hg in 2012 were 332.8 Gg, 972.5 Gg, 3676.0 Gg, 3479.4 Gg, 3429.6 Gg, 395.8 Gg, 33987.9 Gg, 367.1 Gg, 1151.7 Gg, 665989.0 Gg, 2076.5 Gg and 3.65 Mg, respectively. Indoor and outdoor burning of straw and firewood combustion are identified as the dominant biomass burning sources. The largest contributing source is different for various pollutants. Straw indoor burning is the major source of SO2, CO, CH4 and Hg emission; firewood contributes most to EC and NH3 emission. Corn, rice and wheat represent the major crop straws, with their total emission contribution exceeding 80 % for each pollutant. Corn straw burning has the greatest contribution to EC, NOx and SO2 emissions; rice straw burning is dominant contributor to CO2, VOC, CH4 and NH3 emissions. Heilongjiang, Shandong, and Henan provinces located in northeast and central-south region of China have higher emissions. Gridded emissions, which were obtained through spatial allocation based on the gridded rural population and fire point data from emission inventory at county resolution, could better represent the actual situation. Higher biomass burning emissions are concentrated in the areas with greater agricultural and rural activity. The temporal distribution shows that higher emissions occurred in April, September, and October during the whole year. There’s regional difference in monthly variation due to the diversity of main planted crop and the climate conditions. Furthermore, PM2.5 component results showed that OC, Cl−, EC, K+, NH4+, K element and SO42− are the main PM2.5 species accounting for 80 % of the total emissions. The species with relatively higher contribution to VOCs emission including ethylene, propylene, toluene, mp-xylene and halocarbons which are key species for the formation of secondary air pollution. The detailed biomass burning emission inventory generated by this study could provide useful information for air quality modelling and support the development of appropriate pollution control strategies.

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