26 research outputs found

    New land-use-change emissions indicate a declining CO<sub>2</sub> airborne fraction

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    About half of the anthropogenic CO2 emissions remain in the atmosphere and half are taken up by the land and ocean1. If the carbon uptake by land and ocean sinks becomes less efficient, for example, owing to warming oceans2 or thawing permafrost3, a larger fraction of anthropogenic emissions will remain in the atmosphere, accelerating climate change. Changes in the efficiency of the carbon sinks can be estimated indirectly by analysing trends in the airborne fraction, that is, the ratio between the atmospheric growth rate and anthropogenic emissions of CO2 (refs. 4–10). However, current studies yield conflicting results about trends in the airborne fraction, with emissions related to land use and land cover change (LULCC) contributing the largest source of uncertainty7,11,12. Here we construct a LULCC emissions dataset using visibility data in key deforestation zones. These visibility observations are a proxy for fire emissions13,14, which are — in turn — related to LULCC15,16. Although indirect, this provides a long-term consistent dataset of LULCC emissions, showing that tropical deforestation emissions increased substantially (0.16 Pg C decade−1) since the start of CO2 concentration measurements in 1958. So far, these emissions were thought to be relatively stable, leading to an increasing airborne fraction4,5. Our results, however, indicate that the CO2 airborne fraction has decreased by 0.014 ± 0.010 decade−1 since 1959. This suggests that the combined land–ocean sink has been able to grow at least as fast as anthropogenic emissions

    African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data

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    Fires are a major contributor to atmospheric budgets of greenhouse gases and aerosols, affect soils and vegetation properties, and are a key driver of land use change. Since the 1990s, global burned area (BA) estimates based on satellite observations have provided critical insights into patterns and trends of fire occurrence. However, these global BA products are based on coarse spatial-resolution sensors, which are unsuitable for detecting small fires that burn only a fraction of a satellite pixel. We estimated the relevance of those small fires by comparing a BA product generated from Sentinel-2 MSI (Multispectral Instrument) images (20-m spatial resolution) with a widely used global BA product based on Moderate Resolution Imaging Spectroradiometer (MODIS) images (500 m) focusing on sub-Saharan Africa. For the year 2016, we detected 80% more BA with Sentinel-2 images than with the MODIS product. This difference was predominately related to small fires: we observed that 2.02 Mkm2 (out of a total of 4.89 Mkm2) was burned by fires smaller than 100 ha, whereas the MODIS product only detected 0.13 million km2 BA in that fire-size class. This increase in BA subsequently resulted in increased estimates of fire emissions; we computed 31 to 101% more fire carbon emissions than current estimates based on MODIS products. We conclude that small fires are a critical driver of BA in sub-Saharan Africa and that including those small fires in emission estimates raises the contribution of biomass burning to global burdens of (greenhouse) gases and aerosols

    Extratropical forests increasingly at risk due to lightning fires

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    Fires can be ignited by people or by natural causes, which are almost exclusively lightning strikes. Discriminating between lightning and anthropogenic fires is paramount when estimating impacts of changing socioeconomic and climatological conditions on fire activity. Here we use reference data of fire ignition locations, cause and burned area from seven world regions in a machine-learning approach to obtain a global attribution of lightning and anthropogenic ignitions as dominant fire ignition sources. We show that 77% (uncertainty expressed as one standard deviation = 8%) of the burned area in extratropical intact forests currently stems from lightning and that these areas will probably experience 11 to 31% more lightning per degree warming. Extratropical forests are of global importance for carbon storage. They currently experience high fire-related forest losses and have, per unit area, among the largest fire emissions on Earth. Future increases in lightning in intact forest may therefore compound the positive feedback loop between climate change and extratropical wildfires

    Global fire emissions based on native resolution satellite data

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    Modelling biomass burning emissions and the effect of spatial resolution:A case study for Africa based on the Global Fire Emissions Database (GFED)

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    Large-scale fire emission estimates may be influenced by the spatial resolution of the model and input datasets used. Especially in areas with relatively heterogeneous land cover, a coarse model resolution might lead to substantial errors in estimates. We developed a model using MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations of burned area and vegetation characteristics to study the impact of spatial resolution on modelled fire emission estimates. We estimated fire emissions for sub-Saharan Africa at 500 m spatial resolution (native MODIS burned area) for the 2002–2017 period, using a simplified version of the Global Fire Emissions Database (GFED) modelling framework, and compared this to model runs at a range of coarser resolutions (0.050, 0.125, 0.250∘). We estimated fire emissions of 0.68 Pg C yr−1 at 500 m resolution and 0.82 Pg C yr−1 at 0.25∘ resolution; a difference of 24 %. At 0.25∘ resolution, our model results were relatively similar to GFED4, which also runs at 0.25∘ resolution, whereas our 500 m estimates were substantially lower. We found that lower emissions at finer resolutions are mainly the result of reduced representation errors when comparing modelled estimates of fuel load and consumption to field measurements, as part of the model calibration. Additional errors stem from the model simulation at coarse resolution and lead to an additional 0.02 Pg C yr−1difference in estimates. These errors exist due to the aggregation of quantitative and qualitative model input data; the average- or majority- aggregated values are propagated in the coarse-resolution simulation and affect the model parameterization and the final result. We identified at least three error mechanisms responsible for the differences in estimates between 500 m and 0.25 resolution simulations, besides those stemming from representation errors in the calibration process, namely (1) biome misclassification leading to errors in parameterization, (2) errors due to the averaging of input data and the associated reduction in variability, and (3) a temporal mechanism related to the aggregation of burned area in particular. Even though these mechanisms largely neutralized each other and only modestly affect estimates at a continental scale, they lead to substantial error at regional scales with deviations of up to a factor 4 and may affect large-scale estimates differently for other continents. These findings could prove valuable in improving coarse-resolution models and suggest the need for increased spatial resolution in global fire emission models

    Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5)

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    Long-term records of burned area are needed to understand wildfire dynamics, assess fire impacts on ecosystems and air quality, and improve fire forecasts. Here, we fuse multiple streams of remote sensing data to create a 24 year (1997–2020) dataset of monthly burned area as a component of the fifth version of the Global Fire Emissions Database (GFED5). During 2001–2020, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product and adjust for the errors of commission and omission. Adjustment factors are estimated based on region, land cover, and tree cover fraction, using spatiotemporally aligned burned area from Landsat or Sentinel-2. Burned area in croplands, peatlands, and deforestation regions is estimated from MODIS active fire detections. Along-Track Scanning Radiometer (ATSR) and Visible and Infrared Scanner (VIRS) active fire data are used to extend the time series back to 1997. The global annual burned area during 2001–2020 is estimated to be 774 ± 63 Mha yr?1 or 5.9 ± 0.5 % of ice-free land. Burned area declined by 1.21 ± 0.66 % yr?1 , a cumulative decrease of 24.2 ± 13.2 % over 20 years. The global reduction is primarily driven by a decrease in fires in savannas, grasslands, and croplands. Forest, peat, and deforestation fires did not exhibit significant long-term trends. The GFED5 global burned area is 93 % higher than MCD64A1, 61 % higher than GFED4s, and in closer agreement with products from higher-resolution satellite sensors. These data may reduce discrepancies between fire emission estimates from activity-based and atmospheric-based approaches, and improve our understanding of global fire impacts on the carbon cycle and climate system. The GFED5 global burned area product is freely accessible at https://doi.org/10.5281/zenodo.7668423 (Chen et al., 2023)

    The impact of future atmospheric circulation changes over the Euro-Atlantic sector on urban PM2.5 concentrations

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    ir quality management is strongly driven by legislative aspects related to the exceedance of air quality limit values. Here we assume that future ambitious emission reductions are likely to be accompanied by more stringent air quality thresholds. Specifically, we use the Norwegian Climate Centre's Earth System Model to assess the impact of a future scenario of maximum feasible aerosol emission abatement and increasing greenhouse gases (RCP4.5) on urban PM2.5 concentrations in Europe, taking into account changes in the large-scale circulation patterns. Daily PM2.5 concentrations are assessed using a novel downscaling method which allows to compute exceedances of current and planned air quality thresholds. The changes in PM2.5 concentrations are discussed in the context of the large-scale atmospheric changes observed relative to the present-day climate. Our results show a more positive NAO mean state in the future, combined with a large eastward shift of both North Atlantic sea-level pressure centres of action. This is associated with more frequent mid-latitude blocking and a northward shift of the jet stream. These changes favour higher than expected anthropogenic urban PM2.5 concentrations in southern Europe, while they have the opposite effect on the northern half of the continent. In the future scenario, PM concentrations in substantial parts of Southern Europe are found to exceed the World Health Organisation Air Quality Guideline daily limit of 25 μg/m3 in 25 to over 50 days per year, and annual guidelines of 10 μg/m3 in more than 80% of the 30 years analysed in our study. In agreement with previous studies, we therefore conclude that alterations in atmospheric circulation in the future, induced by stringent maximum feasible air pollution mitigation as well as GHG emissions, will negatively influence the effectiveness of these emission abatements over large parts of Europe. This has important implications for future air quality policies.JRC.D.5-Food Securit

    Global fraction of lightning fires and burned area from lightning

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    This dataset contains the global fraction of lightning fires and burned area from lightning, and associated uncertainties, at 0.5 degree resolution. The dataset is representative for contemporary fire regimes (between 2001 and 2020). The dataset is based on a statistical model with two geospatial predictor variables: the seasonal correlation between lightning and burned area, and the fraction of low impact land. These variables are derivatives from remote sensing products. The statistical model was calibrated and validated with fire cause reference data from seven different parts of the world: USA including Alaska, Canada, Portugal, southern France, Yakutia (Russia), Victoria (Australia) and Tasmania (Australia). The statistical model explained 47 % of the variability in the reference data for the fraction of lightning fires, and 40 % for the burned area from lightning. All other relevant datasets from the study, processed to 0.5 degree resolution, are also provided. These include burned land, seasonal correlation between lightning and burned area, low impact land, fire cause reference data, intact forests, fire-related forest loss, carbon combustion and future lightning projections

    The role of fire in global forest loss dynamics

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    Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems
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