Global Fire Emissions Database Research Articles

Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)

Abstract. In fire emission models, the spatial resolution of both the modelling framework and the satellite data used to quantify burned area can have considerable impact on emission estimates. Consideration of this sensitivity is especially important in areas with heterogeneous land cover and fire regimes and when constraining model output with field measurements. We developed a global fire emissions model with a spatial resolution of 500 m using MODerate resolution Imaging Spectroradiometer (MODIS) data. To accommodate this spatial resolution, our model is based on a simplified version of the Global Fire Emissions Database (GFED) modelling framework. Tree mortality as a result of fire, i.e. fire-related forest loss, was modelled based on the overlap between 30 m forest loss data and MODIS burned area and active fire detections. Using this new 500 m model, we calculated global average carbon emissions from fire of 2.1±0.2 (±1σ interannual variability, IAV) Pg C yr−1 during 2002–2020. Fire-related forest loss accounted for 2.6±0.7 % (uncertainty range =1.9 %–3.3 %) of global burned area and 24±6 % (uncertainty range =16 %–31 %) of emissions, indicating that fuel consumption in forest fires is an order of magnitude higher than the global average. Emissions from the combustion of soil organic carbon (SOC) in the boreal region and tropical peatlands accounted for 13±4 % of global emissions. Our global fire emissions estimate was higher than the 1.5 Pg C yr−1 from GFED4 and similar to 2.1 Pg C yr−1 from GFED4s. Even though GFED4s included more burned area by accounting for small fires undetected by the MODIS burned area mapping algorithm, our emissions were similar to GFED4s due to higher average fuel consumption. The global difference in fuel consumption could mainly be explained by higher SOC emissions from the boreal region as constrained by additional measurements. The higher resolution of the 500 m model also contributed to the difference by improving the simulation of landscape heterogeneity and reducing the scale mismatch in comparing field measurements to model grid cell averages during model calibration. Furthermore, the fire-related forest loss algorithm introduced in our model led to more accurate and widespread estimation of high-fuel-consumption burned area. Recent advances in burned area detection at resolutions of 30 m and finer show a substantial amount of burned area that remains undetected with 500 m sensors, suggesting that global carbon emissions from fire are likely higher than our 500 m estimates. The ability to model fire emissions at 500 m resolution provides a framework for further improvements with the development of new satellite-based estimates of fuels, burned area, and fire behaviour, for use in the next generation of GFED.

Climate and socioeconomic drivers of biomass burning and carbon emissions from fires in tropical dry forests: A Pantropical analysis.

Global burned area has declined by nearly one quarter between 1998 and 2015. Drylands contain a large proportion of these global fires but there are important differences within the drylands, for example, savannas and tropical dry forests (TDF). Savannas, a biome fire-prone and fire-adapted, have reduced the burned area, while the fire in the TDF is one of the most critical factors impacting biodiversity and carbon emissions. Moreover, under climate change scenarios TDF is expected to increase its current extent and raise the risk of fires. Despite regional and global scale effects, and the influence of this ecosystem on the global carbon cycle, little effort has been dedicated to studying the influence of climate (seasonality and extreme events) and socioeconomic conditions of fire regimen in TDF. Here we use the Global Fire Emissions Database and, climate and socioeconomic metrics to better understand long-term factors explaining the variation in burned area and biomass in TDF at Pantropical scale. On average, fires affected 1.4% of the total TDF' area (60,208 km2 ) and burned 24.4% (259.6Tg) of the global burned biomass annually at Pantropical scales. Climate modulators largely influence local and regional fire regimes. Inter-annual variation in fire regime is shaped by El Niño and La Niña. During the El Niño and the forthcoming year of La Niña, there is an increment in extension (35.2% and 10.3%) and carbon emissions (42.9% and 10.6%). Socioeconomic indicators such as land-management and population were modulators of the size of both, burned area and carbon emissions. Moreover, fires may reduce the capability to reach the target of "half protected species" in the globe, that is, high-severity fires are recorded in ecoregions classified as nature could reach half protected. These observations may contribute to improving fire-management.

Acceleration of the southern African easterly jet driven by the radiative effect of biomass burning aerosols and its impact on transport during AEROCLO-sA

Abstract. The direct and semi-direct radiative effects of biomass burning aerosols (BBAs) are investigated over southern Africa and the southeastern Atlantic during the Aerosols, Radiation and Clouds in southern Africa (AEROCLO-sA) field campaign in September 2017. A reference convection-permitting simulation has been performed using the Meso-NH model with an online dust emission scheme, a strongly absorbing BBA tracer emitted using the daily Global Fire Emissions Database and online-computed backward Lagrangian trajectories. The simulation captures both the aerosol optical depth and the vertical distribution of aerosols as observed from airborne and spaceborne lidars. The occurrence of stratocumulus over the southeastern Atlantic, deep convective clouds over equatorial Africa and the large-scale circulation are all reproduced by the model. If the radiative effects of BBA are omitted in the model, we show that (i) the smoke plume is too low in altitude, (ii) the low-cloud cover is too weak, (iii) the deep convective activity is too frequent but not intense enough, (iv) the Benguela low-level jet is too strong, and (v) the southern African easterly jet is too weak. The Lagrangian analysis indicates that the radiative effect of BBA leads to the transport of BBA to higher altitudes, farther southwest and with a stronger diurnal oscillation. The higher smoke plume altitude can be explained by a combination of three factors: increased upward motion induced by the stronger southern African easterly jet, self-lofting of BBA and reduced subsidence associated with less frequent deep convective activity over western equatorial Africa.

Impacts of Fine Particulate Matter From Wildfire Smoke on Respiratory and Cardiovascular Health in California.

Increases in wildfire activity across the Western US pose a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM2.5) from wildfire smoke and unscheduled cardiorespiratory hospital visits in California during the 2004–2009 wildfire seasons. We estimate daily mean wildfire‐specific PM2.5 with Goddard Earth Observing System‐Chem, a global three‐dimensional model of atmospheric chemistry, with wildfire emissions estimates from the Global Fire Emissions Database. We defined a “smoke event day” as cumulative 0‐1‐day lag wildfire‐specific PM2.5 ≥ 98th percentile of cumulative 0–1 lag day wildfire PM2.5. Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%, 6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%, 19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0–5 years. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non‐Hispanic white individuals and those older than 65 years. Further, we found a significant interaction between smoke event days and daily average temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM2.5 concentrations and high temperatures may pose greater risk for cardiovascular disease. These results suggest substantial increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention strategies and adaptations to protect vulnerable populations.

Carbon dioxide and particulate emissions from the 2013 Tasmanian firestorm: implications for Australian carbon accounting

BackgroundUncontrolled wildfires in Australian temperate Eucalyptus forests produce significant smoke emissions, particularly carbon dioxide (CO2) and particulates. Emissions from fires in these ecosystems, however, have received less research attention than the fires in North American conifer forests or frequently burned Australian tropical savannas. Here, we use the 2013 Forcett–Dunalley fire that caused the first recorded pyrocumulonimbus event in Tasmania, to understand CO2 and particulate matter (PM2.5) emissions from a severe Eucalyptus forest fire. We investigate the spatial patterns of the two emissions using a fine scale mapping of vegetation and fire severity (50 m resolution), and utilising available emission factors suitable for Australian vegetation types. We compare the results with coarse-scale (28 km resolution) emissions estimates from Global Fire Emissions Database (GFED) to determine the reliability of the global model in emissions estimation.ResultsThe fine scale inventory yielded total CO2 emission of 1.125 ± 0.232 Tg and PM2.5 emission of 0.022 ± 0.006 Tg, representing a loss of 56 t CO2 ha−1 and 1 t PM2.5 ha−1. The CO2 emissions were comparable to GFED estimates, but GFED PM2.5 estimates were lower by a factor of three. This study highlights the reliability of GFED for CO2 but not PM2.5 for estimating emissions from Eucalyptus forest fires. Our fine scale and GFED estimates showed that the Forcett–Dunalley fire produced 30% of 2013 fire carbon emissions in Tasmania, and 26–36% of mean annual fire emissions for the State, representing a significant single source of emissions.ConclusionsOur analyses highlight the need for improved PM2.5 emission factors specific to Australian vegetation, and better characterisation of fuel loads, particularly coarse fuel loads, to quantify wildfire particulate and greenhouse gas emissions more accurately. Current Australian carbon accountancy approach of excluding large wildfires from final GHG accounts likely exaggerates Tasmania’s claim to carbon neutrality; we therefore recommend that planned and unplanned emissions are included in the final national and state greenhouse gas accounting to international conventions. Advancing these issues is important given the trajectory of more frequent large fires driven by anthropogenic climate change.

Global environmental controls on wildfire burnt area, size, and intensity

Fire is an important influence on the global patterns of vegetation structure and composition. Wildfire is included as a distinct process in many dynamic global vegetation models but limited current understanding of fire regimes restricts these models’ ability to reproduce more than the broadest geographic patterns. Here we present a statistical analysis of the global controls of remotely sensed burnt area (BA), fire size (FS), and a derived metric related to fire intensity (FI). Separate generalized linear models were fitted to observed monthly fractional BA from the Global Fire Emissions Database (GFEDv4), median FS from the Global Fire Atlas, and median fire radiative power from the MCD14ML dataset normalized by the square root of median FS. The three models were initially constructed from a common set of 16 predictors; only the strongest predictors for each model were retained in the final models. It is shown that BA is primarily driven by fuel availability and dryness; FS by conditions promoting fire spread; and FI by fractional tree cover and road density. Both BA and FS are constrained by landscape fragmentation, whereas FI is constrained by fuel moisture. Ignition sources (lightning and human population) were positively related to BA (after accounting for road density), but negatively to FI. These findings imply that the different controls on BA, FS and FI need to be considered in process-based models. They highlight the need to include measures of landscape fragmentation as well as fuel load and dryness, and to pay close attention to the controls of fire spread.

Aerosol optical properties calculated from size distributions, filter samples and absorption photometer data at Dome C, Antarctica, and their relationships with seasonal cycles of sources

Abstract. Optical properties of surface aerosols at Dome C, Antarctica, in 2007–2013 and their potential source areas are presented. Scattering coefficients (σsp) were calculated from measured particle number size distributions with a Mie code and from filter samples using mass scattering efficiencies. Absorption coefficients (σap) were determined with a three-wavelength Particle Soot Absorption Photometer (PSAP) and corrected for scattering by using two different algorithms. The scattering coefficients were also compared with σsp measured with a nephelometer at the South Pole Station (SPO). The minimum σap was observed in the austral autumn and the maximum in the austral spring, similar to other Antarctic sites. The darkest aerosol, i.e., the lowest single-scattering albedo ωo≈0.91, was observed in September and October and the highest ωo≈0.99 in February and March. The uncertainty of the absorption Ångström exponent αap is high. The lowest αap monthly medians were observed in March and the highest in August–October. The equivalent black carbon (eBC) mass concentrations were compared with eBC measured at three other Antarctic sites: the SPO and two coastal sites, Neumayer and Syowa. The maximum monthly median eBC concentrations are almost the same (∼3±1 ng m−3) at all these sites in October–November. This suggests that there is no significant difference in eBC concentrations between the coastal and plateau sites. The seasonal cycle of the eBC mass fraction exhibits a minimum f(eBC) ≈0.1 % in February–March and a maximum ∼4 %–5 % in August–October. Source areas were calculated using 50 d FLEXPART footprints. The highest eBC concentrations and the lowest ωo were associated with air masses coming from South America, Australia and Africa. Vertical simulations that take BC particle removal processes into account show that there would be essentially no BC particles arriving at Dome C from north of latitude 10∘ S at altitudes <1600 m. The main biomass-burning regions Africa, Australia and Brazil are more to the south, and their smoke plumes have been observed at higher altitudes than that, so they can get transported to Antarctica. The seasonal cycle of BC emissions from wildfires and agricultural burning and other fires in South America, Africa and Australia was calculated from data downloaded from the Global Fire Emissions Database (GFED). The maximum total emissions were in August–September, but the peak of monthly average eBC concentrations is observed 2–3 months later in November, not only at Dome C, but also at the SPO and the coastal stations. The air-mass residence-time-weighted BC emissions from South America are approximately an order of magnitude larger than from Africa and Oceania, suggesting that South American BC emissions are the largest contributors to eBC at Dome C. At Dome C the maximum and minimum scattering coefficients were observed in austral summer and winter, respectively. At the SPO σsp was similar to that observed at Dome C in the austral summer, but there was a large difference in winter, suggesting that in winter the SPO is more influenced by sea-spray emissions than Dome C. The seasonal cycles of σsp at Dome C and at the SPO were compared with the seasonal cycles of secondary and primary marine aerosol emissions. The σsp measured at the SPO correlated much better with the sea-spray aerosol emission fluxes in the Southern Ocean than σsp at Dome C. The seasonal cycles of biogenic secondary aerosols were estimated from monthly average phytoplankton biomass concentrations obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite sensor data. The analysis suggests that a large fraction of the biogenic scattering aerosol observed at Dome C has been formed in the polar zone, but it may take a month for the aerosol to be formed, be grown and get transported from the sea level to Dome C.

Climate drivers of global wildfire burned area

Wildfire is an integral part of the Earth system, but at the same time it can pose serious threats to human society and to certain types of terrestrial ecosystems. Meteorological conditions are a key driver of wildfire activity and extent, which led to the emergence of the use of fire danger indices that depend solely on weather conditions. The Canadian Fire Weather Index (FWI) is a widely used fire danger index of this kind. Here, we evaluate how well the FWI, its components, and the climate variables from which it is derived, correlate with observation-based burned area (BA) for a variety of world regions. We use a novel technique, according to which monthly BA are grouped by size for each Global Fire Emissions Database (GFED) pyrographic region. We find strong correlations of BA anomalies with the FWI anomalies, as well as with the underlying deviations from their climatologies for the four climate variables from which FWI is estimated, namely, temperature, relative humidity, precipitation, and wind. We quantify the relative sensitivity of the observed BA to each of the four climate variables, finding that this relationship strongly depends on the pyrographic region and land type. Our results indicate that the BA anomalies strongly correlate with FWI anomalies at a GFED region scale, compared to the strength of the correlation with individual climate variables. Additionally, among the individual climate variables that comprise the FWI, relative humidity and temperature are the most influential factors that affect the observed BA. Our results support the use of the composite fire danger index FWI, as well as its sub-indices, the Build-Up Index (BUI) and the Initial Spread Index (ISI), comparing to single climate variables, since they are found to correlate better with the observed forest or non-forest BA, for the most regions across the globe.

Temporal and Spatial Patterns of Biomass Burning Fire Counts and Carbon Emissions in the Beijing–Tianjin–Hebei (BTH) Region during 2003–2020 Based on GFED4

Biomass burning (BB) plays an important role in the formation of heavy pollution events during harvest seasons in the Beijing–Tianjin–Hebei (BTH) region by releasing trace gases and particulate matter into the atmosphere. A better understanding of spatial-temporal variations of BB in BTH is required to assess its impacts on air quality, especially on heavy haze pollution. The fourth version of the Global Fire Emissions Database (GFED4)’s fire counts and carbon emissions data were used in this research, which shows the varying number of fire counts in China from 2003 to 2020 demonstrated a fluctuating but generally rising trend, with a peak in 2013. Most fire counts were concentrated in three key periods: March (11%), June–July (33%), and October (9.68%). The increase in fire counts will inevitably lead to the growth of carbon emissions. The four major vegetation types of the fires were agriculture (58.1%), followed by grassland (35.5%), and forest (4.1%), with the fewest in peat. In addition, a separate study for the year 2020 found that the fire counts and carbon emissions were different for this year, with the overall average trend in the study time. For example, the monthly peak fire counts changed from June to March. The cumulative emissions of carbon, CO, CO2, CH4, dry matter, and particulate matter from BB in BTH reached 201 Gg, 39 Gg, 670 Gg, 2 Gg, 417 Gg, and 3 Gg in 2020, respectively.

Statistical Comparison and Assessment of Four Fire Emissions Inventories for 2013 and a Large Wildfire in the Western United States.

Wildland fires produce smoke plumes that impact air quality and human health. To understand the effects of wildland fire smoke on humans, the amount and composition of the smoke plume must be quantified. Using a fire emissions inventory is one way to determine the emissions rate and composition of smoke plumes from individual fires. There are multiple fire emissions inventories, and each uses a different method to estimate emissions. This paper presents a comparison of four emissions inventories and their products: Fire INventory from NCAR (FINN version 1.5), Global Fire Emissions Database (GFED version 4s), Missoula Fire Labs Emissions Inventory (MFLEI (250 m) and MFLEI (10 km) products), and Wildland Fire Emissions Inventory System (WFEIS (MODIS) and WFEIS (MTBS) products). The outputs from these inventories are compared directly. Because there are no validation datasets for fire emissions, the outlying points from the Bayesian models developed for each inventory were compared with visible images and fire radiative power (FRP) data from satellite remote sensing. This comparison provides a framework to check fire emissions inventory data against additional data by providing a set of days to investigate closely. Results indicate that FINN and GFED likely underestimate emissions, while the MFLEI products likely overestimate emissions. No fire emissions inventory matched the temporal distribution of emissions from an external FRP dataset. A discussion of the differences impacting the emissions estimates from the four fire emissions inventories is provided, including a qualitative comparison of the methods and inputs used by each inventory and the associated strengths and limitations.

Global intercomparison of functional pyrodiversity from two satellite sensors

ABSTRACT Fires create substantial ecosystem disturbances, which affect biodiversity and climate processes. Previously, satellite-derived burned areas were assessed, and fire patches and morphological traits related to fire spread functions identified. The cut-off value in days is a critical parameter for the algorithms used to identify fire patches, as it identifies when two contiguous burned pixels should be grouped together as one patch. Our understanding of how fire patches and their morphologies change with the cut-off values between satellite sensors is currently insufficient for model development and pyrogeographic studies. We have addressed this using the FRY v1.0 global database of fire patch functional traits, with cut-off values of 3, 5, 9, and 14 days, derived from two burned area products, the MERIS Fire_cci version 4.1 and MODIS MCD64A1 collection 6, from two satellite sensors with different spatial and temporal resolutions. We intercompared the FRY products with functional diversity trait methods that assess their morphological pyrodiversity structures and dissimilarities. We have assessed the functional pyrodiversity of the FRY products with four cut-off values, for fire patches ≥ 300 ha, on 1° resolution tiles for the world and Global Fire Emissions Database (GFED) region scales, from 2005–2011. The functional structures and dissimilarities between the FRY products varied with the regions, while cut-off value sensitivity varied with the regions and between the satellite sensor products. These variations in functional structures and dissimilarities mirrored the regional fire spread processes and satellite sensor resolutions. The functional pyrodiversity that varied with the regions and similar cut-off values did not lead to the best agreement between the satellite sensor products. These variations reinforce the need to combine high temporal resolution optical sensors with radar in tropical regions, to consistently meet the monitoring requirements and for international organizations, to enable improved assessments of climate and biodiversity.

Dimensions of the 2020 wildfire catastrophe in the Pantanal wetland: the case of the municipality of Poconé, Mato Grosso, Brazil

In 2020, a total of 3.9 million hectares were burned in the Pantanal biome, which represents approximately 30% of its total area. Of the three existing biomes in the state of Mato Grosso, the Pantanal was the most impacted and, among all the municipalities in Mato Grosso, Poconé had the largest burned area. We aimed to characterize the areas affected by fires in the municipality of Poconé in 2020 to support prevention and adaptation actions in future scenarios. For this, we used the mapping of areas affected by fires made from the detections of active fire collected by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor and available by the Global Fire Emissions Database (GFED). The results showed that a total of 869,170 hectares were burned in Poconé in 2020. Of this total, 97.3% were in natural areas, viz. forest formations (37%), savanna (2.8%), grassland formations (23.4%), wetlands (29.7%), and vegetation in dried-up rivers and lakes (4.4%). Concerning land categories, almost half of the fires occurred in private rural properties registered in the Rural Environmental Registry (CAR). In this scenario, we highlighted the importance of monitoring fires and holding those responsible for them accountable. It is also important to implement preventive actions in synergy with managers and local communities as a way of adapting to the climate crisis, intense drought, and less water surface available in the region, which increases the risk and damage of fires.

The influence of fire aerosols on surface climate and gross primary production in the Energy Exascale Earth System Model (E3SM)

AbstractFire-emitted aerosols play an important role in influencing Earth’s climate, directly by scattering and absorbing radiation and indirectly by influencing cloud microphysics. The quantification of fire-aerosol interactions, however, remains challenging and subject to uncertainties in emissions, plume parameterizations, and aerosol properties. Here we optimized fire-associated aerosol emissions in the Energy Exascale Earth System Model (E3SM) using the Global Fire Emissions Database (GFED) and AERONET aerosol optical depth (AOD) observations during 1997-2016. We distributed fire emissions vertically using smoke plume heights from Multi-angle Imaging SpectroRadiometer (MISR) satellite observations. From the optimization, we estimate that global fires emit 45.5 Tg y-1 of primary particulate organic matter and 3.9 Tg y-1 of black carbon. We then performed two climate simulations with and without the optimized fire emissions. We find that fire aerosols significantly increase global AOD by 14 ± 7% and contribute to a reduction in net shortwave radiation at the surface (-2.3 ± 0.5 W m-2). Together, fire-induced direct and indirect aerosol effects cause annual mean global land surface air temperature to decrease by 0.17 ± 0.15°C, relative humidity to increase by 0.4 ± 0.3%, and diffuse light fraction to increase by 0.5 ± 0.3%. In response, GPP declines by 2.8 Pg C y-1, as a result of large positive drivers (decreases in temperature and increases in humidity and diffuse light) nearly cancelling out large negative drivers (decreases shortwave radiation and soil moisture). Our analysis highlights the importance of fire aerosols in modifying surface climate and photosynthesis across the tropics.

A hydroclimatic model for the distribution of fire on Earth

The distribution of fire on Earth has been monitored from space for several decades, yet the geography of global fire regimes has proven difficult to reproduce from interactions of climate, vegetation, terrain, land use and other human activities by empirical and process-based fire models. Here, we propose a simple, yet robust, model for the global distribution of fire potential based on fundamental biophysical constraints controlling fire activity in all biomes. In our ‘top-down’ approach we ignored the dynamics of individual fires and focus on capturing hydroclimatic constraints on the production and (seasonal) desiccation of fuels to predict the potential mean annual fractional burned area at 0.25° spatial resolution, here estimated by the 0.99 quantile of the observed mean annual fractional burned area () over the 1995-2016 period of the Global Fire Emissions Database (GFED4). We show that 80% of the global variation in can be explained from a combination of mean annual precipitation and potential evapotranspiration. The proposed hydroclimatic model reproduced observed 0.99 quantile fire activity levels equally well across all biomes and provided the first objective underpinning for the dichotomy of global fire regimes in two domains characterised by either fuel production limitations on fire or fuel dryness limitations on fire. A sharp transition between the two climate-fire domains was found to occur at a mean annual aridity index of 1.9 (1.94 ± 0.02). Our model provides a simple but comprehensive basis for predicting fire potential under current and future climates, as well as an overarching framework for estimating effects of human activity via ignition regimes and manipulation of vegetation.

Estimation of Field-Level NOx Emissions from Crop Residue Burning Using Remote Sensing Data: A Case Study in Hubei, China

Crop residue burning is the major biomass burning activity in China, strongly influencing the regional air quality and climate. As the cultivation pattern in China is rather scattered and intricate, it is a challenge to derive an accurate emission inventory for crop residue burning. In this study, we proposed a remote sensing-based method to estimate nitrogen oxide (NOx) emissions related to crop residue burning at the field level over Hubei, China. The new method considers differences in emission factors and the spatial distribution for different crop types. Fire radiative power (FRP) derived from moderate-resolution imaging spectroradiometer (MODIS) was used to quantify NOx emissions related to agricultural biomass combustion. The spatial distribution of different crops classified by multisource remote sensing data was used as an a priori constraint. We derived a new NOx emission database for Hubei from 2014 to 2016 with spatial resolution of 1 × 1 km. Significant seasonal patterns were observed from the NOx emission database. Peak NOx emission occurring in October was related to the residue burning in late autumn harvesting. Another peak was observed between January and April, which was due to the frequent burning of stubble before spring sowing. Our results were validated by comparing our emission inventory with geostationary satellite observations, previous studies, global fire emission database (GFED), NO2 vertical column densities (VCDs) from ozone monitoring instrument (OMI) satellite observations, and measurements from environmental monitoring stations. The comparisons showed NOx emission from GFED database was 47% lower than ours, while the evaluations from most of the statistical studies were significantly higher than our results. The discrepancies were likely related to the differences of methodology and data sources. The spatiotemporal variations of NOx emission in this study showed strong correlations with NO2 VCDs, which agreed well with geostationary satellite observations. A reasonable correlation between in situ NO2 observations and our results in agricultural regions demonstrated that our method is reliable. We believe that the new NOx emission database for crop residue burning derived in this study can potentially improve the understanding of pollution sources and can provide additional information for the design of pollution control measures.

Spatiotemporal Variation of the Burned Area and Its Relationship with Climatic Factors in Central Kazakhstan

Central Asia is prone to wildfires, but the relationship between wildfires and climatic factors in this area is still not clear. In this study, the spatiotemporal variation in wildfire activities across Central Asia during 1997–2016 in terms of the burned area (BA) was investigated with Global Fire Emission Database version 4s (GFED4s). The relationship between BA and climatic factors in the region was also analyzed. The results reveal that more than 90% of the BA across Central Asia is located in Kazakhstan. The peak BA occurs from June to September, and remarkable interannual variation in wildfire activities occurs in western central Kazakhstan (WCKZ). At the interannual scale, the BA is negatively correlated with precipitation (correlation coefficient r = −0.66), soil moisture (r = −0.68), and relative humidity (r = −0.65), while it is positively correlated with the frequency of hot days (r = 0.37) during the burning season (from June to September). Composite analysis suggests that the years in which the BA is higher are generally associated with positive geopotential height anomalies at 500 hPa over the WCKZ region, which lead to the strengthening of the downdraft at 500 hPa and the weakening of westerlies at 850 hPa over the region. The weakened westerlies suppress the transport of water vapor from the Atlantic Ocean to the WCKZ region, resulting in decreased precipitation, soil moisture, and relative humidity in the lower atmosphere over the WCKZ region; these conditions promote an increase in BA throughout the region. Moreover, the westerly circulation index is positively correlated (r = 0.53) with precipitation anomalies and negatively correlated (r = −0.37) with BA anomalies in the WCKZ region during the burning season, which further underscores that wildfires associated with atmospheric circulation systems are becoming an increasingly important component of the relationship between climate and wildfire.

Human-caused fires release more carbon than lightning-caused fires in the conterminous United States

Anthropogenic carbon emissions from fires impact the global carbon budget and contribute to global warming. However, due to the lack of inventory data, little was known about how carbon emissions differed between human-caused and lightning-caused fires previously. In this study, the Fire Program Analysis fire-occurrence database (FPA FOD) and the Global Fire Emissions Database (GFED) were combined to analyze the influences of human-caused fires on carbon emissions. We found that the GFED burned area was larger than that of the FPA FOD since the FPA FOD did not cover human-caused fire usages like prescribed fires. Carbon emissions over the conterminous United States were increasing significantly from 1997 to 2015. Human-caused fires released 9.99 Tg C yr−1 over the conterminous United States, which were approximately twice those of carbon emissions from lightning-caused fires, 5.44 Tg C yr−1. Carbon emissions of lightning-caused fires were increasing while those of human-caused fires were decreasing significantly with rising temperatures. Emissions in ecoregions such as the Eastern Temperate Forests, the Great Plains, the Marine West Coast Forests, and the Northern Forests were dominated by human-caused fire emissions, whose proportions were over 86%. These results highlight the importance of human activities on carbon emissions, offering new insights into the role of humans in climate change mitigation.

Spaceborne detection of XCO2 enhancement induced by Australian mega-bushfires

The 2019–20 Australian mega-bushfires, which raged particularly over New South Wales and Victoria, released large amounts of toxic haze and CO2. Here, we investigate whether the resulting CO2 enhancement can be directly detected by satellite observations, based on National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 (OCO-2) column-averaged CO2 (XCO2) product. We find that smoke from wildfires can greatly obscure satellite observations, making the available XCO2 mainly locate over outer fringes of plumes downwind of the major mega-bushfires in eastern Australia in three orbit observations during November–December 2019, with their enhancements of approximately 1.5 ppm. This fire-induced CO2 enhancement is further confirmed using an atmospheric transport model, Goddard Earth Observing System-Chem, forced by satellite observation-derived fire product Global Fire Emissions Database, version 4.1 and wind observations, with comparable simulated XCO2 enhancements. Model simulation also suggests that the sensitivity of the downwind maximum XCO2 enhancement is 0.41 0.04 ppm for 1 TgC d−1 fire emissions. In sum, though detectable to some extent, it remains a challenge to get the accurate maximum XCO2 enhancements due to the gaps in XCO2 detections obscured by smoke. Understanding the capability of OCO-2 XCO2 detection is prerequisite for monitoring and constraining wildfire CO2 emissions by inversions.

Trends in eastern China agricultural fire emissions derived from a combination of geostationary (Himawari) and polar (VIIRS) orbiter fire radiative power products

Abstract. Open burning of agricultural crop residues is widespread across eastern China, and during certain post-harvest periods this activity is believed to significantly influence air quality. However, the exact contribution of crop residue burning to major air quality exceedances and air quality episodes has proven difficult to quantify. Whilst highly successful in many regions, in areas dominated by agricultural burning, MODIS-based (MODIS: Moderate Resolution Imaging Spectroradiometer) fire emissions inventories such as the Global Fire Assimilation System (GFAS) and Global Fire Emissions Database (GFED) are suspected of significantly underestimating the magnitude of biomass burning emissions due to the typically very small, but highly numerous, fires involved that are quite easily missed by coarser-spatial-resolution remote sensing observations. To address this issue, we use twice-daily fire radiative power (FRP) observations from the “small-fire-optimised” VIIRS-IM FRP product and combine them with fire diurnal cycle information taken from the geostationary Himawari-8 satellite. Using this we generate a unique high-spatio-temporal-resolution agricultural burning inventory for eastern China for the years 2012–2015, designed to fully take into account small fires well below the MODIS burned area or active fire detection limit, focusing on dry matter burned (DMB) and emissions of CO2, CO, PM2.5, and black carbon. We calculate DMB totals 100 % to 400 % higher than reported by the GFAS and GFED4.1s, and we quantify interesting spatial and temporal patterns previously un-noted. Wheat residue burning, primarily occurring in May–June, is responsible for more than half of the annual crop residue burning emissions of all species, whilst a secondary peak in autumn (September–October) is associated with rice and corn residue burning. We further identify a new winter (November–December) burning season, hypothesised to be caused by delays in burning driven by the stronger implementation of residue burning bans during the autumn post-harvest season. Whilst our emissions estimates are far higher than those of other satellite-based emissions inventories for the region, they are lower than estimates made using traditional “crop-yield-based approaches” (CYBAs) by a factor of between 2 and 5. We believe that this is at least in part caused by outdated and overly high burning ratios being used in the CYBA, leading to the overestimation of DMB. Therefore, we conclude that satellite remote sensing approaches which adequately detect the presence of agricultural fires are a far better approach to agricultural fire emission estimation.

Wildfire Smoke Transport and Air Quality Impacts in Different Regions of China

The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km2). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.