Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned ...area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.
This study presents the first modeling estimates of the potential effect of gas- and particle-phase organic photolysis reactions on the formation and lifetime of secondary organic aerosols (SOAs). ...Typically only photolysis of smaller organic molecules (e.g., formaldehyde) for which explicit data exist is included in chemistry-climate models. Here, we specifically examine the photolysis of larger molecules that actively partition between the gas and particle phases. The chemical mechanism generator GECKO-A is used to explicitly model SOA formation from alpha -pinene, toluene, and C12 and C16 n-alkane reactions with OH at low and high NOx. Simulations are conducted for typical mid-latitude conditions and a solar zenith angle of 45 degree (permanent daylight). The results show that after 4 days of chemical aging under those conditions (equivalent to 8 days in the summer mid-latitudes), gas-phase photolysis leads to a moderate decrease in SOA yields, i.e., ~15 % (low NOx) to ~45 % (high NOx) for alpha -pinene, ~15 % for toluene, ~25 % for C12 n-alkane, and ~10 % for C16 n-alkane. The small effect of gas-phase photolysis on low-volatility n-alkanes such as C16 n-alkane is due to the rapid partitioning of early-generation products to the particle phase, where they are protected from gas-phase photolysis. Minor changes are found in the volatility distribution of organic products and in oxygen to carbon ratios. The decrease in SOA mass is increasingly more important after a day of chemical processing, suggesting that most laboratory experiments are likely too short to quantify the effect of gas-phase photolysis on SOA yields. Our results also suggest that many molecules containing chromophores are preferentially partitioned into the particle phase before they can be photolyzed in the gas phase. Given the growing experimental evidence that these molecules can undergo in-particle photolysis, we performed sensitivity simulations using an empirically estimated SOA photolysis rate of JSOA = 4 10-4 JNO2. Modeling results indicate that this photolytic loss rate would decrease SOA mass by 40-60 % for most species after 10 days of equivalent atmospheric aging at mid-latitudes in the summer. It should be noted that in our simulations we do not consider in-particle or aqueous-phase reactions which could modify the chemical composition of the particle and thus the quantity of photolabile species. The atmospheric implications of our results are significant for both the SOA global distribution and lifetime. GEOS-Chem global model results suggest that particle-phase photolytic reactions could be an important loss process for SOA in the atmosphere, removing aerosols from the troposphere on timescales of less than 7 days that are comparable to wet deposition.
Biomass burning represents an important source of atmospheric aerosols and greenhouse gases, yet little is known about its interannual variability or the underlying mechanisms regulating this ...variability at continental to global scales. Here we investigated fire emissions during the 8 year period from 1997 to 2004 using satellite data and the CASA biogeochemical model. Burned area from 2001–2004 was derived using newly available active fire and 500 m. burned area datasets from MODIS following the approach described by Giglio et al. (2006). ATSR and VIRS satellite data were used to extend the burned area time series back in time through 1997. In our analysis we estimated fuel loads, including organic soil layer and peatland fuels, and the net flux from terrestrial ecosystems as the balance between net primary production (NPP), heterotrophic respiration (Rh), and biomass burning, using time varying inputs of precipitation (PPT), temperature, solar radiation, and satellite-derived fractional absorbed photosynthetically active radiation (fAPAR). For the 1997–2004 period, we found that on average approximately 58 Pg C year−1 was fixed by plants as NPP, and approximately 95% of this was returned back to the atmosphere via Rh. Another 4%, or 2.5 Pg C year−1 was emitted by biomass burning; the remainder consisted of losses from fuel wood collection and subsequent burning. At a global scale, burned area and total fire emissions were largely decoupled from year to year. Total carbon emissions tracked burning in forested areas (including deforestation fires in the tropics), whereas burned area was largely controlled by savanna fires that responded to different environmental and human factors. Biomass burning emissions showed large interannual variability with a range of more than 1 Pg C year−1, with a maximum in 1998 (3.2 Pg C year−1) and a minimum in 2000 (2.0 Pg C year−1).
We present a method for estimating monthly burned area globally at 1° spatial resolution using Terra MODIS data and ancillary vegetation cover information. Using regression trees constructed for 14 ...different global regions, MODIS active fire observations were calibrated to burned area estimates derived from 500-m MODIS imagery based on the assumption that burned area is proportional to counts of fire pixels. Unlike earlier methods, we allow the constant of proportionality to vary as a function of tree and herbaceous vegetation cover, and the mean size of monthly cumulative fire-pixel clusters. In areas undergoing active deforestation, we implemented a subsequent correction based on tree cover information and a simple measure of fire persistence. Regions showing good agreement between predicted and observed burned area included Boreal Asia, Central Asia, Europe, and Temperate North America, where the estimates produced by the regression trees were relatively accurate and precise. Poorest agreement was found for southern-hemisphere South America, where predicted values of burned area are both inaccurate and imprecise; this is most likely a consequence of multiple factors that include extremely persistent cloud cover, and lower quality of the 500-m burned area maps used for calibration. Application of our approach to the nine remaining regions yielded comparatively accurate, but less precise, estimates of monthly burned area. We applied the regional regression trees to the entire archive of Terra MODIS fire data to produce a monthly global burned area data set spanning late 2000 through mid-2005. Annual totals derived from this approach showed good agreement with independent annual estimates available for nine Canadian provinces, the United States, and Russia. With our data set we estimate the global annual burned area for the years 2001-2004 to vary between 2.97 million and 3.74 million km2, with the maximum occurring in 2001. These coarse-resolution burned area estimates may serve as a useful interim product until long-term burned area data sets from multiple sensors and retrieval approaches become available.
Drainage of peatlands and deforestation have led to large-scale fires in equatorial Asia, affecting regional air quality and global concentrations of greenhouse gases. Here we used several sources of ...satellite data with biogeochemical and atmospheric modeling to better understand and constrain fire emissions from Indonesia, Malaysia, and Papua New Guinea during 2000-2006. We found that average fire emissions from this region 128 ± 51 (1σ) Tg carbon (C) year⁻¹, T = 10¹² were comparable to fossil fuel emissions. In Borneo, carbon emissions from fires were highly variable, fluxes during the moderate 2006 El Niño more than 30 times greater than those during the 2000 La Niña (and with a 2000-2006 mean of 74 ± 33 Tg C yr⁻¹). Higher rates of forest loss and larger areas of peatland becoming vulnerable to fire in drought years caused a strong nonlinear relation between drought and fire emissions in southern Borneo. Fire emissions from Sumatra showed a positive linear trend, increasing at a rate of 8 Tg C year⁻² (approximately doubling during 2000-2006). These results highlight the importance of including deforestation in future climate agreements. They also imply that land manager responses to expected shifts in tropical precipitation may critically determine the strength of climate-carbon cycle feedbacks during the 21st century.
Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed ...an approach for representing synoptic‐ and diurnal‐scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003–2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)‐derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top‐down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.
Key Points
We developed an approach to distribute daily and hourly fire emissions
Daily and hourly patterns of fire activity varied among different land types
Daily and hourly fire emissions improved CO simulations
During the 1997 to 1998 El Niño, drought conditions triggered widespread increases in fire activity, releasing CH4and CO2to the atmosphere. We evaluated the contribution of fires from different ...continents to variability in these greenhouse gases from 1997 to 2001, using satellite-based estimates of fire activity, biogeochemical modeling, and an inverse analysis of atmospheric CO anomalies. During the 1997 to 1998 El Niño, the fire emissions anomaly was$2.1 \pm 0.8$petagrams of carbon, or$66 \pm 24%$of the CO2growth rate anomaly. The main contributors were Southeast Asia (60%), Central and South America (30%), and boreal regions of Eurasia and North America (10%).
Various land‐use transitions in the tropics contribute to atmospheric carbon emissions, including forest conversion for small‐scale farming, cattle ranching, and production of commodities such as ...soya and palm oil. These transitions involve fire as an effective and inexpensive means for clearing. We applied the DECAF (DEforestation CArbon Fluxes) model to Mato Grosso, Brazil to estimate fire emissions from various land‐use transitions during 2001–2005. Fires associated with deforestation contributed 67 Tg C/yr (17 and 50 Tg C/yr from conversion to cropland and pasture, respectively), while conversion of savannas and existing cattle pasture to cropland contributed 17 Tg C/yr and pasture maintenance fires 6 Tg C/yr. Large clearings (>100 ha/yr) contributed 67% of emissions but comprised only 10% of deforestation events. From a policy perspective, results imply that intensification of agricultural production on already‐cleared land and policies to discourage large clearings would reduce the major sources of emissions from fires in this region.
Three regions of the northern mid-latitudes, the continental-scale metro-agro-plexes, presently dominate global industrial and agricultural productivity. Although these regions cover only 23 percent ...of the Earth's continents, they account for most of the world's commercial energy consumption, fertilizer use, food-crop production, and food exports. They also account for more than half of the world's atmospheric nitrogen oxide (NO$_x$) emissions and, as a result, are prone to ground-level ozone (O$_3$) pollution during the summer months. On the basis of a global simulation of atmospheric reactive nitrogen compounds, it is estimated that about 10 to 35 percent of the world's grain production may occur in parts of these regions where ozone pollution may reduce crop yields. Exposure to yield-reducing ozone pollution may triple by 2025 if rising anthropogenic NO$_x$ emissions are not abated.
We present and discuss the use of Bayesian modeling and computational methods for atmospheric chemistry inverse analyses that incorporate evaluation of spatial structure in model-data residuals. ...Motivated by problems of refining bottom-up estimates of source/sink fluxes of trace gas and aerosols based on satellite retrievals of atmospheric chemical concentrations, we address the need for formal modeling of spatial residual error structure in global scale inversion models. We do this using analytically and computationally tractable conditional autoregressive (CAR) spatial models as components of a global inversion framework. We develop Markov chain Monte Carlo methods to explore and fit these spatial structures in an overall statistical framework that simultaneously estimates source fluxes. Additional aspects of the study extend the statistical framework to utilize priors on source fluxes in a physically realistic manner, and to formally address and deal with missing data in satellite retrievals. We demonstrate the analysis in the context of inferring carbon monoxide (CO) sources constrained by satellite retrievals of column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument on the TERRA satellite, paying special attention to evaluating performance of the inverse approach using various statistical diagnostic metrics. This is developed using synthetic data generated to resemble MOPITT data to define a proof-of-concept and model assessment, and then in analysis of real MOPITT data. These studies demonstrate the ability of these simple spatial models to substantially improve over standard non-spatial models in terms of statistical fit, ability to recover sources in synthetic examples, and predictive match with real data.
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