Biomass Burning Emission Estimates Research Articles

Dynamic savanna burning emission factors based on satellite data using a machine learning approach

Abstract. Landscape fires, predominantly found in the frequently burning global savannas, are a substantial source of greenhouse gases and aerosols. The impact of these fires on atmospheric composition is partially determined by the chemical breakup of the constituents of the fuel into individual emitted chemical species, which is described by emission factors (EFs). These EFs are known to be dependent on, amongst other things, the type of fuel consumed, the moisture content of the fuel, and the meteorological conditions during the fire, indicating that savanna EFs are temporally and spatially dynamic. Global emission inventories, however, rely on static biome-averaged EFs, which makes them ill-suited for the estimation of regional biomass burning (BB) emissions and for capturing the effects of shifts in fire regimes. In this study we explore the main drivers of EF variability within the savanna biome and assess which geospatial proxies can be used to estimate dynamic EFs for global emission inventories. We made over 4500 bag measurements of CO2, CO, CH4, and N2O EFs using a UAS and also measured fuel parameters and fire-severity proxies during 129 individual fires. The measurements cover a variety of savanna ecosystems under different seasonal conditions sampled over the course of six fire seasons between 2017 and 2022. We complemented our own data with EFs from 85 fires with locations and dates provided in the literature. Based on the locations, dates, and times of the fires we retrieved a variety of fuel, weather, and fire-severity proxies (i.e. possible predictors) using globally available satellite and reanalysis data. We then trained random forest (RF) regressors to estimate EFs for CO2, CO, CH4, and N2O at a spatial resolution of 0.25∘ and a monthly time step. Using these modelled EFs, we calculated their spatiotemporal impact on BB emission estimates over the 2002–2016 period using the Global Fire Emissions Database version 4 with small fires (GFED4s). We found that the most important field indicators for the EFs of CO2, CO, and CH4 were tree cover density, fuel moisture content, and the grass-to-litter ratio. The grass-to-litter ratio and the nitrogen-to-carbon ratio were important indicators for N2O EFs. RF models using satellite observations performed well for the prediction of EF variability in the measured fires with out-of-sample correlation coefficients between 0.80 and 0.99, reducing the error between measured and modelled EFs by 60 %–85 % compared to using the static biome average. Using dynamic EFs, total global savanna emission estimates for 2002–2016 were 1.8 % higher for CO, while CO2, CH4, and N2O emissions were, respectively, 0.2 %, 5 %, and 18 % lower compared to GFED4s. On a regional scale we found a spatial redistribution compared to GFED4s with higher CO, CH4, and N2O EFs in mesic regions and lower ones in xeric regions. Over the course of the fire season, drying resulted in gradually lower EFs of these species. Relatively speaking, the trend was stronger in open savannas than in woodlands, where towards the end of the fire season they increased again. Contrary to the minor impact on annual average savanna fire emissions, the model predicts localized deviations from static averages of the EFs of CO, CH4, and N2O exceeding 60 % under seasonal conditions.

Impacts of different biomass burning emission inventories: Simulations of atmospheric CO2 concentrations based on GEOS-Chem

Biomass burning has substantial spatiotemporal variabilities. It contributes significantly to the dynamics of global CO2 distributions and variances. Quantifying the impacts of biomass burning emissions on atmospheric CO2 concentrations is essential for global and regional carbon cycles and budgets. In this study, we performed several numerical experiments by switching and replacing inventories to estimate the impacts of four biomass burning emission inventories on atmospheric CO2 concentration simulations in 2006–2010 based on the global chemical transport model, GEOS-Chem. The results highlighted similarities and differences in the annual and seasonal variability of biomass burning emissions and simulated CO2 concentrations at global and regional scales. Based on four different biomass burning emission inventories, we found that biomass burning emissions could lead to a global CO2 concentration increase of 2.4 ppm annually. Africa contributed the largest global CO2 emissions among all continental regions, where the maximum CO2 concentration increase could reach 7.9–13.0 ppm in summer. Model evaluation results showed that simulation using the Quick Fire Emissions Database (QFED) as the model priori biomass burning emission inventory had the best performance compared with the satellite and surface observations. The sensitivity of simulated CO2 concentrations to the uncertainties in different biomass burning emission inventories was high in southern South America and most areas of the Eurasian continent, and low in central Africa and Southeast Asia. This study furthers our understanding of the critical role of biomass burning in atmospheric CO2 and indicates an urgent need to improve the accuracy of biomass burning emission estimates in CO2 simulations.

Sensitivity of biomass burning emissions estimates to land surface information

Abstract. Emissions from biomass burning (BB) are a key source of atmospheric tracer gases that affect the atmospheric carbon cycle. We developed four sets of global BB emissions estimates (named GlcGlob, GlcGeoc, McdGlob, and McdGeoc) using a bottom-up approach and by combining the remote sensing products related to fire distribution with two aboveground biomass (AGB) and two land cover classification (LCC) distributions. The sensitivity of the estimates of BB emissions to the AGB and LCC data was evaluated using the carbon monoxide (CO) emissions associated with each BB estimate. Using the AGB and/or LCC data led to substantially different spatial estimates of CO emissions, with a large (factor of approximately 3) spread of estimates for the mean annual CO emissions: 526±53, 219±35, 624±57, and 293±44 Tg CO yr−1 for GlcGlob, GlcGeoc, McdGlob, and McdGeoc, respectively, and 415±47 Tg CO yr−1 for their ensemble average (EsmAve). We simulated atmospheric CO variability at an approximately 2.5∘ grid using an atmospheric tracer transport model and the BB emissions estimates and compared it with ground-based and satellite observations. At ground-based observation sites during fire seasons, the impact of intermittent fire events was poorly defined in our simulations due to the coarse resolution, which obscured temporal and spatial variability in the simulated atmospheric CO concentration. However, when compared at the regional and global scales, the distribution of atmospheric CO concentrations in the simulations shows substantial differences among the estimates of BB emissions. These results indicate that the estimates of BB emissions are highly sensitive to the AGB and LCC data.

Ground/space, passive/active remote sensing observations coupled with particle dispersion modelling to understand the inter-continental transport of wildfire smoke plumes

During the 2017 record-breaking burning season in Canada/United States, intense wild fires raged during the first week of September in the Pacific northwestern region (British Columbia, Alberta, Washington, Oregon, Idaho, Montana and northern California) burning mostly temperate coniferous forests. The heavy loads of smoke particles emitted in the atmosphere reached the Iberian Peninsula (IP) a few days later on 7 and 8 September. Satellite imagery allows to identify two main smoke clouds emitted during two different periods that were injected and transported in the atmosphere at several altitude levels. Columnar properties on 7 and 8 September at two Aerosol Robotic Network (AERONET) mid-altitude, background sites in northern and southern Spain are: aerosol optical depth (AOD) at 440 nm up to 0.62, Ångström exponent of 1.6–1.7, large dominance of small particles (fine mode fraction >0.88), low absorption AOD at 440 nm (<0.008) and large single scattering albedo at 440 nm (>0.98). Profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) show the presence of smoke particles in the stratosphere during the transport, whereas the smoke is only observed in the troposphere at its arrival over the IP. Portuguese and Spanish ground lidar stations from the European Aerosol Research Lidar Network/Aerosols, Clouds, and Trace gases Research InfraStructure Network (EARLINET/ACTRIS) and the Micro-Pulse Lidar NETwork (MPLNET) reveal smoke plumes with different properties: particle depolarization ratio and color ratio, respectively, of 0.05 and 2.5 in the mid troposphere (5–9 km) and of 0.10 and 3.0 in the upper troposphere (10–13 km). In the mid troposphere the particle depolarization ratio does not seem time-dependent during the transport whereas the color ratio seems to increase (larger particles sediment first). To analyze the horizontal and vertical transport of the smoke from its origin to the IP, particle dispersion modelling is performed with the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) parameterized with satellite-derived biomass burning emission estimates from the Global Fire Assimilation System (GFAS) of the Copernicus Atmosphere Monitoring Service (CAMS). Three compounds are simulated: carbon monoxide, black carbon and organic carbon. The results show that the first smoke plume which travels slowly reaches rapidly (~1 day) the upper troposphere and lower stratosphere (UTLS) but also shows evidence of large scale horizontal dispersion, while the second plume, entrained by strong subtropical jets, reaches the upper troposphere much slower (~2.5 days). Observations and dispersion modelling all together suggest that particle depolarization properties are enhanced during their vertical transport from the mid to the upper troposphere.

The biomass burning contribution to climate–carbon-cycle feedback

Abstract. Temperature exerts strong controls on the incidence and severity of fire. All else equal, warming is expected to increase fire-related carbon emissions, and thereby atmospheric CO2. But the magnitude of this feedback is very poorly known. We use a single-box model of the land biosphere to quantify this positive feedback from satellite-based estimates of biomass burning emissions for 2000–2014 CE and from sedimentary charcoal records for the millennium before the industrial period. We derive an estimate of the centennial-scale feedback strength of 6.5 ± 3.4 ppm CO2 per degree of land temperature increase, based on the satellite data. However, this estimate is poorly constrained, and is largely driven by the well-documented dependence of tropical deforestation and peat fires (primarily anthropogenic) on climate variability patterns linked to the El Niño–Southern Oscillation. Palaeo-data from pre-industrial times provide the opportunity to assess the fire-related climate–carbon-cycle feedback over a longer period, with less pervasive human impacts. Past biomass burning can be quantified based on variations in either the concentration and isotopic composition of methane in ice cores (with assumptions about the isotopic signatures of different methane sources) or the abundances of charcoal preserved in sediments, which reflect landscape-scale changes in burnt biomass. These two data sources are shown here to be coherent with one another. The more numerous data from sedimentary charcoal, expressed as normalized anomalies (fractional deviations from the long-term mean), are then used – together with an estimate of mean biomass burning derived from methane isotope data – to infer a feedback strength of 5.6 ± 3.2 ppm CO2 per degree of land temperature and (for a climate sensitivity of 2.8 K) a gain of 0.09 ± 0.05. This finding indicates that the positive carbon cycle feedback from increased fire provides a substantial contribution to the overall climate–carbon-cycle feedback on centennial timescales. Although the feedback estimates from palaeo- and satellite-era data are in agreement, this is likely fortuitous because of the pervasive influence of human activities on fire regimes during recent decades.

Two global data sets of daily fire emission injection heights since 2003

Abstract. The Global Fire Assimilation System (GFAS) assimilates fire radiative power (FRP) observations from satellite-based sensors to produce daily estimates of biomass burning emissions. It has been extended to include information about injection heights derived from fire observations and meteorological information from the operational weather forecasts of ECMWF. Injection heights are provided by two distinct methods: the Integrated Monitoring and Modelling System for wildland fires (IS4FIRES) parameterisation and the one-dimensional plume rise model (PRM). A global database of daily biomass burning emissions and injection heights at 0.1° resolution has been produced for 2003–2015 and is continuously extended in near-real time with the operational GFAS service of the Copernicus Atmospheric Monitoring Service (CAMS). In this study, the two injection height data sets were compared with the new MPHP2 (MISR Plume Height Project 2) satellite-based plume height retrievals. The IS4FIRES parameterisation showed a better overall agreement than the observations, while the PRM was better at capturing the variability of injection heights. The performance of both parameterisations is also dependent on the type of vegetation. Furthermore, the use of biomass burning emission heights from GFAS in atmospheric composition forecasts was assessed in two case studies: the South AMerican Biomass Burning Analysis (SAMBBA) campaign which took place in September 2012 in Brazil, and a series of large fire events in the western USA in August 2013. For these case studies, forecasts of biomass burning aerosol species by the Composition Integrated Forecasting System (C-IFS) of CAMS were found to better reproduce the observed vertical distribution when using PRM injection heights from GFAS compared to aerosols emissions being prescribed at the surface. The globally available GFAS injection heights introduced and evaluated in this study provide a comprehensive data set for future fire and atmospheric composition modelling studies.

Seasonal, interannual, and long-term variabilities in biomass burning activity over South Asia.

The seasonal, interannual, and long-term variations in biomass burning activity and related emissions are not well studied over South Asia. In this regard, active fire location retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), the retrievals of aerosol optical depth (AOD) from MODIS Terra, and tropospheric column NO2 from Ozone Monitoring Instrument (OMI) are used to understand the effects of biomass burning on the tropospheric pollution loadings over South Asia during 2003-2013. Biomass burning emission estimates from Global Fire Emission Database (GFED) and Global Fire Assimilation System (GFAS) are also used to quantify uncertainties and regional discrepancies in the emissions of carbon monoxide (CO), nitrogen oxide (NOx), and black carbon (BC) due to biomass burning in South Asia. In the Asian continent, the frequency of fire activity is highest over Southeast Asia, followed by South Asia and East Asia. The biomass burning activity in South Asia shows a distinct seasonal cycle that peaks during February-May with some differences among four (north, central, northeast, and south) regions in India. The annual biomass burning activity in north, central, and south regions shows an increasing tendency, particularly after 2008, while a decrease is seen in northeast region during 2003-2013. The increase in fire counts over the north and central regions contributes 24 % of the net enhancement in fire counts over South Asia. MODIS AOD and OMI tropospheric column NO2 retrievals are classified into high and low fire activity periods and show that biomass burning leads to significant enhancement in tropospheric pollution loading over both the cropland and forest regions. The enhancement is much higher (110-176 %) over the forest region compared to the cropland (34-62 %) region. Further efforts are required to understand the implications of biomass burning on the regional air quality and climate of South Asia.

New fire diurnal cycle characterizations to improve fire radiative energy assessments made from MODIS observations

Abstract. Accurate near real time fire emissions estimates are required for air quality forecasts. To date, most approaches are based on satellite-derived estimates of fire radiative power (FRP), which can be converted to fire radiative energy (FRE) which is directly related to fire emissions. Uncertainties in these FRE estimates are often substantial. This is for a large part because the most often used low-Earth orbit satellite-based instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) have a relatively poor sampling of the usually pronounced fire diurnal cycle. In this paper we explore the spatial variation of this fire diurnal cycle and its drivers using data from the geostationary Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI). In addition, we sampled data from the SEVIRI instrument at MODIS detection opportunities to develop two approaches to estimate hourly FRE based on MODIS active fire detections. The first approach ignored the fire diurnal cycle, assuming persistent fire activity between two MODIS observations, while the second approach combined knowledge on the climatology of the fire diurnal cycle with active fire detections to estimate hourly FRE. The full SEVIRI time series, providing full coverage of the fire diurnal cycle, were used to evaluate the results. Our study period comprised of 3 years (2010–2012), and we focused on Africa and the Mediterranean basin to avoid the use of potentially lower quality SEVIRI data obtained at very far off-nadir view angles. We found that the fire diurnal cycle varies substantially over the study region, and depends on both fuel and weather conditions. For example, more "intense" fires characterized by a fire diurnal cycle with high peak fire activity, long duration over the day, and with nighttime fire activity are most common in areas of large fire size (i.e., large burned area per fire event). These areas are most prevalent in relatively arid regions. Ignoring the fire diurnal cycle generally resulted in an overestimation of FRE, while including information on the climatology of the fire diurnal cycle improved FRE estimates. The approach based on knowledge of the climatology of the fire diurnal cycle also improved distribution of FRE over the day, although only when aggregating model results to coarser spatial and/or temporal scale good correlation was found with the full SEVIRI hourly reference data set. We recommend the use of regionally varying fire diurnal cycle information within the Global Fire Assimilation System (GFAS) used in the Copernicus Atmosphere Monitoring Services, which will improve FRE estimates and may allow for further reconciliation of biomass burning emission estimates from different inventories.

Effect of dramatic land use change on gaseous pollutant emissions from biomass burning in Northeastern China

Biomass burning contributes a substantial amount of gas and particle emissions to the atmosphere. As China's breadbasket, northeast China has experienced dramatic land use change in the past century, converting approximately 55×104ha of wetland into farmland to feed a rapidly growing population. This study combines measured emission factors of dominant crops (rice and soybean) and wetland plants (Calamagrostis angu-stifolia, Carex lasiocarpa, Carex pseudo-curaica) and remote sensing land use data to estimate the effect of the unprecedented land use change on gaseous pollutants emissions from biomass burning. Our biomass burning emission estimates resulting from land use changes have increased because of increased post-harvest crop residue burning and decreased burning of wetland plants. From 1986 to 2005, the total emissions of CO2, CO, CXHY, SO2 and NO have increased by 18.6%, 35.7%, 26.8%, 66.2% and 33.2%, respectively. We have found two trends in agricultural burning: increased dryland crop residue burning and decreased wetland (rice paddy) burning. Our results revealed that the large scale land use change in northeastern China has induced more active biomass-burning emissions. The regional emission inventory of gaseous pollutants derived from this work may be used to support further examination of the subsequent effects on regional climate and air quality simulations with numerical atmospheric models.

Top-down estimates of biomass burning emissions of black carbon in the Western United States

Abstract. We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for May–October 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the spatiotemporal distributions of the biomass burning BC emissions from the Global Fire Emissions Database (GFEDv2). The adjustment primarily shifts emissions from late to middle and early summer (a 33% decrease in September–October and a 56% increase in June–August) and leads to appreciable increases in modeled surface BC concentrations in early and middle summer, especially at the 1–2 and 2–3 km altitude ranges. We then conduct analytical inversions at both 2° × 2.5° and 0.5° × 0.667° (nested over North America) horizontal resolutions. The a posteriori biomass burning BC emissions for July–September are 31.7 Gg at 2° × 2.5° (an increase by a factor of 4.7) and 19.2 Gg at 0.5° × 0.667° (an increase by a factor of 2.8). The inversion results are rather sensitive to model resolution. The a posteriori biomass burning emissions at the two model resolutions differ by a factor of ~6 in California and the Southwest and by a factor of 2 in the Pacific Northwest. The corresponding a posteriori anthropogenic BC emissions are 9.1 Gg at 2° × 2.5° (a decrease of 48%) and 11.2 Gg at 0.5° × 0.667° (a decrease of 36%). Simulated surface BC concentrations with the a posteriori emissions capture the observed major fire episodes at most sites and the substantial enhancements at the 1–2 and 2–3 km altitude ranges. The a posteriori emissions also lead to large bias reductions (by ~30% on average at both model resolutions) in modeled surface BC concentrations and significantly better agreement with observations (increases in Taylor skill scores of 95% at 2° × 2.5° and 42 % at 0.5° × 0.667°).

Measurements of Gas phase Acids in Diesel Exhaust: A Relevant Source of HNCO?

Gas-phase acids in light duty diesel (LDD) vehicle exhaust were measured using chemical ionization mass spectrometry (CIMS). Fuel based emission factors (EF) and NOx ratios for these species were determined under differing steady state engine operating conditions. The derived HONO and HNO3 EFs agree well with literature values, with HONO being the single most important acidic emission. Of particular importance is the quantification of the EF for the toxic species, isocyanic acid (HNCO). The emission factors for HNCO ranged from 0.69 to 3.96 mg kgfuel(-1), and were significantly higher than previous biomass burning emission estimates. Further ambient urban measurements of HNCO demonstrated a clear relationship with the known traffic markers of benzene and toluene, demonstrating for the first time that urban commuter traffic is a source of HNCO. Estimates based upon the HNCO-benzene relationship indicate that upward of 23 tonnes of HNCO are released annually from commuter traffic in the Greater Toronto Area, far exceeding the amount possible from LDD alone. Nationally, 250 to 770 tonnes of HNCO may be emitted annually from on-road vehicles, likely representing the dominant source of exposure in urban areas, and with emissions comparable to that of biomass burning.

The use of satellite‐measured aerosol optical depth to constrain biomass burning emissions source strength in the global model GOCART

Simulations of biomass burning (BB) emissions in chemistry transport models strongly depend on the inventories that define emission source location and strength. We use 13 global biomass burning emission estimates, including the widely used Global Fire Emission Database (GFED) monthly and daily versions, Fire Radiative Power (FRP)‐based Quick Fire Emission Data set QFED, and 11 calculated emissions from different combinations of burned area based on the Moderate Resolution Imaging Spectroradiometer (MODIS) products, effective fuel load, and species emission factors as alternative inputs to the global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. The resultant simulated aerosol optical depth (AOD) and its spatial distribution are compared to AOD snapshots measured by the MODIS instrument for 124 fire events occurring between 2006 and 2007. This comparison exposes the regional biases of each emission option. GOCART average fire AOD values compare best to MODIS‐measured AOD when the daily GFED inventory is used as input to GOCART. Even though GFED‐based emission options provide the lowest emissions in the tropics, GFED‐based GOCART AOD compares best with MODIS AOD in tropical cases. Fire‐counts‐based emission options give the largest emission estimates in the boreal regions, and the model performs best at higher latitudes with these inputs when compared to MODIS. Comparison of total annual BB emissions by all inventories suggests that burned area estimates are usually the largest source of disagreement. It is also shown that the quantitative relationship between BB aerosol emission rate and model‐simulated AOD is related to the horizontal plume dispersion, which can be approximated by the wind speed in the planetary boundary layer in most cases. Thus, given average wind speed of the smoke plume environment, MODIS‐measured AOD can provide a constraint to the strength of BB sources at the level of individual plumes.

Interannual variability of carbon monoxide emission estimates over South America from 2006 to 2010

We present the first inverse modeling study to estimate CO emissions constrained by both surface and satellite observations. Our 4D‐Var system assimilates National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) surface and Measurements Of Pollution In The Troposphere (MOPITT) satellite observations jointly by fitting a bias correction scheme. This approach leads to the identification of a positive bias of maximum 5 ppb in MOPITT column‐averaged CO mixing ratios in the remote Southern Hemisphere (SH). The 4D‐Var system is used to estimate CO emissions over South America in the period 2006–2010 and to analyze the interannual variability (IAV) of these emissions. We infer robust, high spatial resolution CO emission estimates that show slightly smaller IAV due to fires compared to the Global Fire Emissions Database (GFED3) prior emissions. South American dry season (August and September) biomass burning emission estimates amount to 60, 92, 42, 16 and 93 Tg CO/yr for 2006 to 2010, respectively. Moreover, CO emissions probably associated with pre‐harvest burning of sugar cane plantations in São Paulo state are underestimated in current inventories by 50–100%. We conclude that climatic conditions (such as the widespread drought in 2010) seem the most likely cause for the IAV in biomass burning CO emissions. However, socio‐economic factors (such as the growing global demand for soy, beef and sugar cane ethanol) and associated deforestation fires, are also likely as drivers for the IAV of CO emissions, but are difficult to link directly to CO emissions.

Near‐real‐time global biomass burning emissions product from geostationary satellite constellation

Near‐real‐time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near‐real‐time global biomass burning emission product from geostationary satellites (GBBEP‐Geo) produced from satellite‐derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second‐generation satellites (Meteosat‐09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport Satellite (MTSAT) operated by the Japan Meteorological Agency. These satellites observe wildfires at an interval of 15–30 min. Because of the impacts from sensor saturation, cloud cover, and background surface, the FRP values are generally not continuously observed. The missing observations are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems. Finally, the simulated diurnal variation in FRP is applied to quantify biomass combustion and emissions in individual fire pixels with a latency of 1 day. By analyzing global patterns in hourly biomass burning emissions in 2010, we find that peak fire season varied greatly and that annual wildfires burned 1.33 × 1012 kg dry mass, released 1.27 × 1010 kg of PM2.5 (particulate mass for particles with diameter &lt;2.5 μm) and 1.18 × 1011kg of CO globally (excluding most parts of boreal Asia, the Middle East, and India because of no coverage from geostationary satellites). The biomass burning emissions were mostly released from forest and savanna fires in Africa, South America, and North America. Evaluation of emission result reveals that the GBBEP‐Geo estimates are comparable with other FRP‐derived estimates in Africa, while the results are generally smaller than most of the other global products that were derived from burned area and fuel loading. However, the daily emissions estimated from GOES FRP over the United States are generally consistent with those modeled from GOES burned area and MODIS (Moderate Resolution Imaging Spectroradiometer) fuel loading, which produces an overall bias of 5.7% and a correlation slope of 0.97 ± 0.2. It is expected that near‐real‐time hourly emissions from GBBEP‐Geo could provide a crucial component for atmospheric and chemical transport modelers to forecast air quality and weather conditions.

Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem): chemistry evaluation and initial results

Abstract. This study presents annual simulations of tropospheric ozone and related species made for the first time using the WRF-Chem model over South Asia for the year 2008. The model-simulated ozone, CO, and NOx are evaluated against ground-based, balloon-borne and satellite-borne (TES, OMI and MOPITT) observations. The comparison of model results with surface ozone observations from seven sites and CO and NOx observations from three sites indicate the model's ability in reproducing seasonal variations of ozone and CO, but show some differences in NOx. The modeled vertical ozone distribution agrees well with the ozone soundings data from two Indian sites. The vertical distributions of TES ozone and MOPITT CO are generally well reproduced, but the model underestimates TES ozone, OMI tropospheric column NO2 and MOPITT total column CO retrievals during all the months, except MOPITT retrievals during August–January and OMI retrievals during winter. Largest differences between modeled and satellite-retrieved quantities are found during spring when intense biomass burning activity occurs in this region. The evaluation results indicate large uncertainties in anthropogenic and biomass burning emission estimates, especially for NOx. The model results indicate clear regional differences in the seasonality of surface ozone over South Asia, with estimated net ozone production during daytime (1130–1530 h) over inland regions of 0–5 ppbv h−1 during all seasons and of 0–2 ppbv h−1 over marine regions during outflow periods. The model results indicate that ozone production in this region is mostly NOx-limited. This study shows that WRF-Chem model captures many important features of the observations and gives confidence to using the model for understanding the spatio-temporal variability of ozone over South Asia. However, improvements of South Asian emission inventories and simulations at finer model resolution, especially over the complex Himalayan terrain in northern India, are also essential for accurately simulating ozone in this region.

The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010

Abstract. We have analysed the sensitivity of the tropospheric ozone distribution over North America and the North Atlantic to boreal biomass burning emissions during the summer of 2010 using the GEOS-Chem 3-D global tropospheric chemical transport model and observations from in situ and satellite instruments. We show that the model ozone distribution is consistent with observations from the Pico Mountain Observatory in the Azores, ozonesondes across Canada, and the Tropospheric Emission Spectrometer (TES) and Infrared Atmospheric Sounding Instrument (IASI) satellite instruments. Mean biases between the model and observed ozone mixing ratio in the free troposphere were less than 10 ppbv. We used the adjoint of GEOS-Chem to show the model ozone distribution in the free troposphere over Maritime Canada is largely sensitive to NOx emissions from biomass burning sources in Central Canada, lightning sources in the central US, and anthropogenic sources in the eastern US and south-eastern Canada. We also used the adjoint of GEOS-Chem to evaluate the Fire Locating And Monitoring of Burning Emissions (FLAMBE) inventory through assimilation of CO observations from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. The CO inversion showed that, on average, the FLAMBE emissions needed to be reduced to 89% of their original values, with scaling factors ranging from 12% to 102%, to fit the MOPITT observations in the boreal regions. Applying the CO scaling factors to all species emitted from boreal biomass burning sources led to a decrease of the model tropospheric distributions of CO, PAN, and NOx by as much as −20 ppbv, −50 pptv, and −20 pptv respectively. The modification of the biomass burning emission estimates reduced the model ozone distribution by approximately −3 ppbv (−8%) and on average improved the agreement of the model ozone distribution compared to the observations throughout the free troposphere, reducing the mean model bias from 5.5 to 4.0 ppbv for the Pico Mountain Observatory, 3.0 to 0.9 ppbv for ozonesondes, 2.0 to 0.9 ppbv for TES, and 2.8 to 1.4 ppbv for IASI.

The Impact of Uncertainties in African Biomass Burning Emission Estimates on Modeling Global Air Quality, Long Range Transport and Tropospheric Chemical Lifetimes

The chemical composition of the troposphere in the tropics and Southern Hemisphere (SH) is significantly influenced by gaseous emissions released from African biomass burning (BB). Here we investigate how various emission estimates given in bottom-up BB inventories (GFEDv2, GFEDv3, AMMABB) affect simulations of global tropospheric composition using the TM4 chemistry transport model. The application of various model parameterizations for introducing such emissions is also investigated. There are perturbations in near-surface ozone (O3) and carbon monoxide (CO) of ~60–90% in the tropics and ~5–10% in the SH between different inventories. Increasing the update frequency of the temporal distribution to eight days generally results in decreases of between ~5 and 10% in near-surface mixing ratios throughout the tropics, which is larger than the influence of increasing the injection heights at which BB emissions are introduced. There are also associated differences in the long range transport of pollutants throughout the SH, where the composition of the free troposphere in the SH is sensitive to the chosen BB inventory. Analysis of the chemical budget terms reveals that the influence of increasing the tropospheric CO burden due to BB on oxidative capacity of the troposphere is mitigated by the associated increase in NOx emissions (and thus O3) with the variations in the CO/N ratio between inventories being low. For all inventories there is a decrease in the tropospheric chemical lifetime of methane of between 0.4 and 0.8% regardless of the CO emitted from African BB. This has implications for assessing the effect of inter-annual variability in BB on the annual growth rate of methane.

Biomass burning emission estimates inferred from satellite column measurements of HCHO: Sensitivity to co-emitted aerosol and injection height

[1] We infer monthly regional biomass burning emissions of formaldehyde (HCHO) during 2006 from space-borne column measurements of HCHO from the SCIAMACHY instrument over Canada, boreal Asia, South America, southern Africa, and Indonesia. We remove the influence of biogenic volatile organic compounds using an offline chemical mechanism. We quantify the sensitivity of our emission estimates to aerosol single scattering albedo, ω, indicative of fresh (ω = 0.8) and aged (ω > 0.9) aerosol, and the relative vertical distribution of the aerosol and HCHO, both which compromise the interpretation of space-based HCHO columns. For our control calculation we assume freshly-emitted gases and aerosols that are mainly confined to the boundary layer. Associated posterior emissions are generally lower than the prior emissions except over Canada and boreal Asia during northern hemisphere summer months. Accounting for faster vertical mixing results in posterior emissions 20%–100% higher than the corresponding control calculation, and consequently more consistent with the prior. Assuming an aged aerosol generally results in a 20% decrease in posterior emissions relative to prior values. Based on the range of posterior estimates from our sensitivity analyses, not accounting for uncertainties associated with the underlying gas-phase and heterogeneous chemistry, we estimate HCHO emission uncertainties are typically 20%–30% but can be up to 300% in extreme cases.

Trends, temporal and spatial characteristics, and uncertainties in biomass burning emissions in the Pearl River Delta, China

Abstract Multi-year inventories of biomass burning emissions were established in the Pearl River Delta (PRD) region for the period 2003–2007 based on the collected activity data and emission factors. The results indicated that emissions of sulfur dioxide (SO 2 ), nitrogen oxide (NO x ), ammonia (NH 3 ), methane (CH 4 ), organic carbon (OC), non-methane volatile organic compounds (NMVOC), carbon monoxide (CO), and fine particulate matter (PM 2.5 ) presented clear declining trends. Domestic biofuel burning was the major contributor, accounting for more than 60% of the total emissions. The preliminary temporal profiles were established with MODIS fire count information, showing that higher emissions were observed in winter (from November to March) than other seasons. The emissions were spatially allocated into grid cells with a resolution of 3 km × 3 km, using GIS-based land use data as spatial surrogates. Large amount of emissions were observed mostly in the less developed areas in the PRD region. The uncertainties in biomass burning emission estimates were quantified using Monte Carlo simulation; the results showed that there were higher uncertainties in organic carbon (OC) and elemental carbon (EC) emission estimates, ranging from −71% to 133% and −70% to 128%, and relatively lower uncertainties in SO 2 , NO x and CO emission estimates. The key uncertainty sources of the developed inventory included emission factors and parameters used for estimating biomass burning amounts.

Regional modelling of Saharan dust and biomass-burning smoke

The spatio-temporal evolution of the Saharan dust and biomass-burning plume during the SAMUM-2 field campaign in January and February 2008 is simulated at 28 km horizontal resolution with the regional model-system COSMOMUSCAT. The model performance is thoroughly tested using routine ground-based and space-borne remote sensing and local field measurements. Good agreement with the observations is found in many cases regarding transport patterns, aerosol optical thicknesses and the ratio of dust to smoke aerosol. The model also captures major features of the complex aerosol layering. Nevertheless, discrepancies in the modelled aerosol distribution occur, which are analysed in detail. The dry synoptic dynamics controlling dust uplift and transport during the dry season are well described by the model, but surface wind peaks associated with the breakdown of nocturnal low-level jets are not always reproduced. Thus, a strong dust outbreak is underestimated. While dust emission modelling is a priori more challenging, since strength and placement of dust sources depend on on-line computed winds, considerable inaccuracies also arise in observation-based estimates of biomass-burning emissions. They are caused by cloud and spatial errors of satellite fire products and uncertainties in fire emission parameters, and can lead to unrealistic model results of smoke transport.