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299 results on '"van der Werf, G. R."'

1. Global nitrous oxide budget (1980--2020)

Author

Tian, H., Pan, N., Thompson, R. L., Canadell, J. G., Suntharalingam, P., Regnier, P., Davidson, E. A., Prather, M., Ciais, P., Muntean, M., Pan, S., Winiwarter, W., Zaehle, S., Zhou, F., Jackson, R. B., Bange, H. W., Berthet, S., Bian, Z., Bianchi, D., Bouwman, A. F., Buitenhuis, E. T., Dutton, G., Hu, M., Ito, A., Jain, A. K., Jeltsch-Thömmes, A., Joos, F., Kou-Giesbrecht, S., Krummel, P. B., Lan, X., Landolfi, A., Lauerwald, R., Li, Y., Lu, C., Maavara, T., Manizza, M., Millet, D. B., Mühle, J., Patra, P. K., Peters, G. P., Qin, X., Raymond, P., Resplandy, L., Rosentreter, J. A., Shi, H., Sun, Q., Tonina, D., Tubiello, F. N., van der Werf, G. R., Vuichard, N., Wang, J., Wells, K. C., Western, L. M., Wilson, C., Yang, J., Yao, Y., You, Y., Zhu, Q., Tian, H., Pan, N., Thompson, R. L., Canadell, J. G., Suntharalingam, P., Regnier, P., Davidson, E. A., Prather, M., Ciais, P., Muntean, M., Pan, S., Winiwarter, W., Zaehle, S., Zhou, F., Jackson, R. B., Bange, H. W., Berthet, S., Bian, Z., Bianchi, D., Bouwman, A. F., Buitenhuis, E. T., Dutton, G., Hu, M., Ito, A., Jain, A. K., Jeltsch-Thömmes, A., Joos, F., Kou-Giesbrecht, S., Krummel, P. B., Lan, X., Landolfi, A., Lauerwald, R., Li, Y., Lu, C., Maavara, T., Manizza, M., Millet, D. B., Mühle, J., Patra, P. K., Peters, G. P., Qin, X., Raymond, P., Resplandy, L., Rosentreter, J. A., Shi, H., Sun, Q., Tonina, D., Tubiello, F. N., van der Werf, G. R., Vuichard, N., Wang, J., Wells, K. C., Western, L. M., Wilson, C., Yang, J., Yao, Y., You, Y., and Zhu, Q.

Abstract

Nitrous oxide (N2O) is a long-lived potent greenhouse gas and stratospheric ozone-depleting substance that has been accumulating in the atmosphere since the preindustrial period. The mole fraction of atmospheric N2O has increased by nearly 25 % from 270 ppb (parts per billion) in 1750 to 336 ppb in 2022, with the fastest annual growth rate since 1980 of more than 1.3 ppb yr−1 in both 2020 and 2021. According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6), the relative contribution of N2O to the total enhanced effective radiative forcing of greenhouse gases was 6.4 % for 1750–2022. As a core component of our global greenhouse gas assessments coordinated by the Global Carbon Project (GCP), our global N2O budget incorporates both natural and anthropogenic sources and sinks and accounts for the interactions between nitrogen additions and the biogeochemical processes that control N2O emissions. We use bottom-up (BU: inventory, statistical extrapolation of flux measurements, and process-based land and ocean modeling) and top-down (TD: atmospheric measurement-based inversion) approaches. We provide a comprehensive quantification of global N2O sources and sinks in 21 natural and anthropogenic categories in 18 regions between 1980 and 2020. We estimate that total annual anthropogenic N2O emissions have increased 40 % (or 1.9 Tg N yr−1) in the past 4 decades (1980–2020). Direct agricultural emissions in 2020 (3.9 Tg N yr−1, best estimate) represent the large majority of anthropogenic emissions, followed by other direct anthropogenic sources, including fossil fuel and industry, waste and wastewater, and biomass burning (2.1 Tg N yr−1), and indirect anthropogenic sources (1.3 Tg N yr−1) . For the year 2020, our best estimate of total BU emissions for natural and anthropogenic sources was 18.5 (lower–upper bounds: 10.6–27.0) Tg N yr−1, close to our TD estimate of 17.0 (16.6–17.4) Tg N yr−1. For the 2010–2019 period, the annual BU decad

Published
2024

2. Global burned area and biomass burning emissions from small fires

Author

Randerson, J. T, Chen, Y., van der Werf, G. R, Rogers, B. M, and Morton, D. C

Subjects
biomass burning, carbon flux, data set, drought stress, El Nino-Southern Oscillation, emission, fire behavior, MODIS, numerical model, reflectance, resolution, satellite imagery, spatial distribution, temperature effect, tropical forest, Africa, Australia, North America
Abstract

In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001–2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia—regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes.

Published
2012

3. Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

Author

Mu, M., Randerson, J. T, van der Werf, G. R, Giglio, L., Kasibhatla, P., Morton, D., Collatz, G. J, DeFries, R. S, Hyer, E. J, Prins, E. M, Griffith, D. W. T, Wunch, D., Toon, G. C, Sherlock, V., and Wennberg, P. O

Subjects
Active fires, Aerosol variability, Aqua satellites, Atmospheric model, Atmospheric model simulations, Atmospheric trace gas, Biomass-burning, Boreal ecosystems, Burned areas, Diurnal cycle, Fire behavior, Fire emissions, Fire radiative power, Future directions, Geostationary operational environmental satellites, Global fire, High resolution, High temporal resolution, Measurements of pollution in the tropospheres, Moderate resolution imaging spectroradiometer, Multiple satellites, Natural emissions, Temporal variability, Time step, Time-scales, Topdown, Total carbon, Atmospheric aerosols, Atmospherics, Carbon monoxide, Computer simulation, Ecosystems, Estimation, Gas emissions, Geostationary satellites, Radiometers, Satellite imagery, Time series, Uncertainty analysis, Fires, agricultural land, algorithm, Aqua (satellite), atmospheric modeling, biomass burning, carbon monoxide, database, emission inventory, GOES, grassland, MODIS, satellite sensor, savanna, temporal variation, Terra (satellite), time series, top-down approach, trace gas, troposphere, uncertainty analysis, wildfire
Abstract

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.

Published
2011

4. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009)

Author

van der Werf, G. R, Randerson, J. T, Giglio, L., Collatz, G. J, Mu, M., Kasibhatla, P. S, Morton, D. C, DeFries, R. S, Jin, Y., and van Leeuwen, T. T

Subjects
annual variation, atmospheric chemistry, AVHRR, biogeochemistry, carbon emission, concentration (composition), data set, database, deforestation, estimation method, global climate, MODIS, partitioning, satellite data, savanna, spatial resolution, agricultural land, Along Track Scanning Radiometer, carbon monoxide, detection method, emission inventory, fire history, forest fire, methane, peat, top-down approach, uncertainty analysis, Asia, South America
Abstract

New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

Published
2010

5. Assessing variability and long-term trends in burned area by merging multiple satellite fire products

Author

Giglio, L., Randerson, J. T, van der Werf, G. R, Kasibhatla, P. S, Collatz, G. J, Morton, D. C, and DeFries, R. S

Subjects
aerosol, Along Track Scanning Radiometer, annual variation, calibration, data set, fire history, MODIS, satellite data, satellite imagery, spatial resolution, surface reflectance, time series, trace gas
Abstract

Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.

Published
2010

6. A human-driven decline in global burned area

Author

Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Yue, C., and Randerson, J. T.

Published
2017

7. Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling

Author

van der Werf, G. R, Morton, D. C, DeFries, R. S, Giglio, L., Randerson, J. T, Collatz, G. J, and Kasibhatla, P. S

Subjects
agricultural practice, biogeochemistry, biomass burning, carbon dioxide, carbon emission, cerrado, deforestation, dry season, ecological modeling, forest fire, regrowth, remote sensing, satellite data, soil respiration, tropical forest, Amazonia, Brazil, Mato Grosso
Abstract

Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year−1, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth.

Published
2009

8. Fire-related carbon emissions from land use transitions in southern Amazonia

Author

DeFries, R. S, Morton, D. C, van der Werf, G. R, Giglio, L., Collatz, G. J, Randerson, J. T, Houghton, R. A, Kasibhatla, P. K, and Shimabukuro, Y.

Subjects
agriculture, air pollution, deforestation, disasters, land use, leakage (fluid), vegetable oils, agricultural productions, amazonia, atmospheric carbons, carbon emissions, cattle ranching, fire emissions, forest conversions, inexpensive means, mato grosso, palm oil, fires, agricultural land, agricultural production, atmospheric modeling, carbon emission, carbon flux, deforestation, environmental policy, land use change, pasture, prescribed burning, ranching, tropical region, air pollution, conversion, curl, deforestation, disasters, emission, fires, land use, leakage, oil, Amazonia, South America, Bos
Abstract

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.

Published
2008

9. Climate regulation of fire emissions and deforestation in equatorial Asia

Author

van der Werf, G. R, Dempewolf, J., Trigg, S. N, Randerson, J. T, Kasibhatla, P. S, Giglio, L., Murdiyarso, D., Peters, W., Morton, D. C, Collatz, G. J, Dolman, A. J, and DeFries, R. S

Subjects
carbon, fossil fuel, lanthanum, air quality, article, Asia, biogeochemistry, biomass, Borneo, carbon cycle, carbon dynamics, climate change, deforestation, drought, fire, fossil, greenhouse gas, human, Indonesia, Malaysia, nonhuman, Papua New Guinea, peatland, priority journal, Asia, Carbon Monoxide, Climate, Conservation of Natural Resources, Droughts, Ecosystem, Fires, Satellite Communications, Sphagnopsida
Abstract

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.

Published
2008

10. An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker

Author

Peters, W., Jacobson, A. R, Sweeney, C., Andrews, A. E, Conway, T. J, Masarie, K., Miller, J. B, Bruhwiler, L. M. P, Petron, G., Hirsch, A. I, Worthy, D. E. J, van der Werf, G. R, Randerson, J. T, Wennberg, P. O, Krol, M. C, and Tans, P. P

Subjects
carbon dioxide, fossil fuel, article, atmosphere, biosphere, carbon cycle, carbon sink, cement industry, combustion, forest, geographic distribution, land biome, North America, Poaceae, Trees
Abstract

We present an estimate of net CO2 exchange between the terrestrial biosphere and the atmosphere across North America for every week in the period 2000 through 2005. This estimate is derived from a set of 28,000 CO2 mole fraction observations in the global atmosphere that are fed into a state-of-the-art data assimilation system for CO2 called CarbonTracker. By design, the surface fluxes produced in CarbonTracker are consistent with the recent history of CO2 in the atmosphere and provide constraints on the net carbon flux independent from national inventories derived from accounting efforts. We find the North American terrestrial biosphere to have absorbed −0.65 PgC/yr (1 petagram = 1015 g; negative signs are used for carbon sinks) averaged over the period studied, partly offsetting the estimated 1.85 PgC/yr release by fossil fuel burning and cement manufacturing. Uncertainty on this estimate is derived from a set of sensitivity experiments and places the sink within a range of −0.4 to −1.0 PgC/yr. The estimated sink is located mainly in the deciduous forests along the East Coast (32%) and the boreal coniferous forests (22%). Terrestrial uptake fell to −0.32 PgC/yr during the large-scale drought of 2002, suggesting sensitivity of the contemporary carbon sinks to climate extremes. CarbonTracker results are in excellent agreement with a wide collection of carbon inventories that form the basis of the first North American State of the Carbon Cycle Report (SOCCR), to be released in 2007.

Published
2007

11. Small Fires, Big Impact: Evaluating Fire Emission Estimates in Southern Africa Using New Satellite Imagery of Burned Area and Carbon Monoxide.

Author

van der Velde, I. R., van der Werf, G. R., van Wees, D., Schutgens, N. A. J., Vernooij, R., Houweling, S., Tonucci, E., Chuvieco, E., Randerson, J. T., Frey, M. M., Borsdorff, T., and Aben, I.

Subjects
*REMOTE-sensing images, *CARBON monoxide, *FOREST fires, *FIRE, *ATMOSPHERIC transport, *WILDFIRES, *MINERAL dusts, *ATMOSPHERIC chemistry, *AIR pollution
Abstract

Various fire emission estimates for southern Africa during 2019, derived with multiple burned area data sets with resolutions ranging from 500 to 20 m, are evaluated using satellite carbon monoxide (CO) observations. Southern African emissions derived from burned area generated by 20 m Sentinel‐2 satellite imagery are up to 120% higher than other estimates because small fires are better detected with a higher‐resolution satellite instrument. A comprehensive comparison between simulated and observed atmospheric CO indicates that the Sentinel‐2 burned area data significantly improves emission estimates, with up to 15% reduction in CO concentration biases in comparison to emissions based on coarser resolution burned area data. We also found that the temporal lag between emissions and atmospheric CO concentrations during the peak fire month was related to atmospheric transport. These findings emphasize the importance of utilizing higher‐resolution satellite instruments in accurately estimating emissions and understanding the impact of small fires on global climate. Plain Language Summary: We studied how much carbon monoxide (CO) was released into the air in southern Africa due to fires. To derive CO emissions we used different remotely sensed data of area burned, with varying levels of detail, from 500 to 20 m, and used these emissions in a model to mimic atmospheric transport and chemistry of CO. We found that emissions derived from the very detailed 20‐m satellite images from Sentinel‐2 produced a similar large amount of CO in the atmosphere over southern Africa as seen by CO satellite observations. This is because the smaller fires, which are harder to spot, were detected with the 20‐m burned area satellite observations. We also found that the air movement and inflow of polluted air from outside Africa impacted the peak of air pollution. Key Points: Sentinel‐2 burned area detects small fires, resulting in up to 120% higher fire emissions compared to conventional resolution estimatesImproved fuel load modeling and new emission factors yield more trustworthy fire emissions that can be evaluated with top‐down constraintsAtmospheric modeling and TROPOMI CO observations indicate a 15% bias reduction using Sentinel‐2 burned area compared with coarser fire data [ABSTRACT FROM AUTHOR]

Published
2024
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12. Interannual variability in global biomass burning emissions from 1997 to 2004

Author

van der Werf, G. R, Randerson, J. T, Giglio, L., Collatz, G. J, Kasibhatla, P. S, and Arellano, A. F

Subjects
aerosol, Along Track Scanning Radiometer, annual variation, biogeochemical cycle, biomass burning, carbon emission, fire behavior, fuelwood, greenhouse gas, MODIS, net primary production, organic soil, satellite data, terrestrial ecosystem
Abstract

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).

Published
2006

13. Global estimation of burned area using MODIS active fire observations

Author

Giglio, L., van der Werf, G. R, Randerson, J. T, Collatz, G. J, and Kasibhatla, P.

Subjects
estimation method, forest fire, MODIS, regression analysis, satellite imagery, vegetation cover
Abstract

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.

Published
2006

14. Fire emissions from C 3 and C 4 vegetation and their influence on interannual variability of atmospheric CO 2 and δ 13 CO 2

Author

Randerson, J. T, van der Werf, G. R, Collatz, G. J, Giglio, L., Still, C. J, Kasibhatla, P., Miller, J. B, White, J. W. C, DeFries, R. S, and Kasischke, E. S

Subjects
biomass burning, carbon dioxide, El Nino, emission, Poaceae
Abstract

Measurements of atmospheric trace gases provide evidence that fire emissions increased during the 1997/1998 El Niño event and these emissions contributed substantially to global CO2, CO, CH4, and δ13CO2 anomalies. Interpretation and effective use of these atmospheric observations to assess changes in the global carbon cycle requires an understanding of the amount of biomass consumed during fires, the molar ratios of emitted trace gases, and the carbon isotope ratio of emissions. Here we used satellite data of burned area, a map of C4 canopy cover, and a global biogeochemical model to quantitatively estimate contributions of C3 and C4 vegetation to fire emissions during 1997–2001. We found that although C4 grasses contributed to 31% of global mean emissions over this period, they accounted for only 24% of the interannual emissions anomalies. Much of the drought and increase in fire emissions during the 1997/1998 El Niño occurred in tropical regions dominated by C3 vegetation. As a result, the δ13CO2 of the global fire emissions anomaly was depleted (−23.9‰), and explained approximately 27% of the observed atmospheric decrease in δ13CO2 between mid-1997 and the end of 1998 (and 61% of the observed variance in δ13CO2 during 1997–2001). Using fire emissions that were optimized in an atmospheric CO inversion, fires explained approximately 57% of the observed atmospheric δ13CO2 decrease between mid-1997 and the end of 1998 (and 72% of the variance in δ13CO2 during 1997–2001). The severe drought in tropical forests during the 1997/1998 El Niño appeared to allow humans to ignite fires in forested areas that were normally too moist to burn. Adjacent C4 grasses (in woodlands and moist savannas) also burned, but emissions were limited, in part, by aboveground biomass levels that were 2 orders of magnitude smaller than C3 biomass levels. Reduced fuel availability in some C4 ecosystems may have led to a negative feedback on emissions.

Published
2005

15. Top-down estimates of global CO sources using MOPITT measurements

Author

Arellano, Avelino F, Kasibhatla, P. S, Giglio, L., van der Werf, G. R, and Randerson, J. T

Subjects
Air pollution, Carbon monoxide, Climatology, Geographical regions, Troposphere, CO emissions, Measurements of pollution in the troposphere (MOPITT), Geophysics, carbon monoxide, emission inventory, fossil fuel, geographical variation
Published
2004

16. The use of ATSR active fire counts for estimating relative patterns of biomass burning- a study from the boreal forest region

Author

Kasischke, Eric S, Hewson, J. H, Stocks, B. J, van der Werf, G. R, and Randerson, J. T

Subjects
Biomass, Clouds, Forestry, Radiometers, Satellites, Scanning, Smoke, Fire activity, Geophysics, biomass burning, boreal forest, radiometer, satellite data, time series
Abstract

Satellite fire products have the potential to construct inter-annual time series of fire activity, but estimating area burned requires considering biases introduced by orbiting geometry, fire behavior, and the presence of clouds and smoke. Here we evaluated the performance of fire counts from the Advanced Thermal Scanning Radiometer (ATSR) for the boreal forest region using area burned information from other sources. We found ATSR detection rate varied between regions and different years, being higher during large fire years than during small fire years. The results show ATSR fire counts do not represent an unbiased sample of fire activity, and independent validation may be required prior to using this data set in studies of global emissions from biomass burning.

Published
2003

17. Global Carbon Budget 2023

Author

Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2023

18. Global Carbon Budget 2023

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2023

19. Global Carbon Budget 2022

Author

Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, College of Life and Environmental Sciences [Exeter], University of Exeter, Rice University [Houston], Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Meteorology and Air Quality Department [Wageningen] (MAQ), Ludwig-Maximilians-Universität München (LMU), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Stanford Woods Institute for the Environment, Stanford University, European Commission - Joint Research Centre [Ispra] (JRC), Karlsruhe Institute of Technology (KIT), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Earth Sciences, Amsterdam Sustainability Institute, and Isotope Research

Subjects
WIMEK, [SDE.MCG]Environmental Sciences/Global Changes, SDG 13 - Climate Action, Life Science, General Earth and Planetary Sciences, Luchtkwaliteit, Air Quality
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

Published
2022
Full Text
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21. Global Carbon Budget 2022

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2022

22. Contribution of anthropogenic and natural sources to atmospheric methane variability

Author

Bousquet, P., Ciais, P., Miller, J. B., Dlugokencky, E. J., Hauglustaine, D. A., Prigent, C., Van der Werf, G. R., Peylin, P., Brunke, E.-G., Carouge, C., Langenfelds, R. L., Lathiere, J., Papa, F., Ramonet, M., Schmidt, M., Steele, L. P., Tyler, S. C., and White, J.

Abstract

Author(s): P. Bousquet (corresponding author) [1, 2]; P. Ciais [1]; J. B. Miller [3, 4]; E. J. Dlugokencky [3]; D. A. Hauglustaine [1]; C. Prigent [5]; G. R. Van der [...]

Published
2006
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23. Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Author

Mu, M, Randerson, J. T, van der Werf, G. R, Giglio, L, Kasibhatla, P, Morton, D, Collatz, G. J, DeFries, R. S, Hyer, E. J, Prins, E. M, Griffith, D. W. T, Wunch, D, Toon, G. C, Sherlock, V, and Wennberg, P. O

Subjects
Environment Pollution
Abstract

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 distributed monthly GFED3 emissions during 2003-2009 on 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) active fire observations. We found that patterns of 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 bunting in savannas. On diurnal timescales, our analysis of the GOES 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.

Published
2011

24. Global carbon budget 2019

Author

Friedlingstein, P., Jones, M. W., O’Sullivan, M., Andrew, R. M., Hauck, J., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., DBakker, O. C. E., Canadell, J. G., Ciais, P., Jackson, R. B., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevallier, F., Chini, L. P., Currie, K. I., Feely, R. A., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D. S., Gruber, N., Gutekunst, S., Harris, I., Haverd, V., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Joetzjer, E., Kaplan, J. O., Kato, E., Goldewijk, K. K., Korsbakken, J. I., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, P. C., Melton, J. R., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Neill, C., Omar, A. M., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Séférian, R., Schwinger, J., Smith, N., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., Van Der Werf, G. R., Wiltshire, A. J., and Zaehle, S.

Published
2019
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25. Global carbon budget 2019 [Data paper]

Author

Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Hauck, J., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quere, C., Bakker, D. C. E., Canadell, J. G., Ciais, P., Jackson, R. B., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevallier, F., Chini, L. P., Currie, K. I., Feely, R. A., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D. S., Gruber, N., Gutekunst, S., Harris, I., Haverd, V., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Joetzjer, E., Kaplan, J. O., Kato, E., Goldewijk, K. K., Korsbakken, J. I., Landschutzer, P., Lauvset, S. K., Lefèvre, Nathalie, Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, P. C., Melton, J. R., Metzl, N., Munro, D. R., Nabel, Jems, Nakaoka, S. I., Neill, C., Omar, A. M., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rodenbeck, C., Seferian, R., Schwinger, J., Smith, N., Tans, P. P., Tian, H. Q., Tilbrook, B., Tubiello, F. N., van der Werf, G. R., Wiltshire, A. J., and Zaehle, S.

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere - the "global carbon budget" - is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (E-FF) are based on energy statistics and cement production data, while emissions from land use change (E-LUC), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (G(ATM)) is computed from the annual changes in concentration. The ocean CO2 sink (S-OCEAN) and terrestrial CO2 sink (S-LAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B-IM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as +/- 1 sigma. For the last decade available (2009-2018), E-FF was 9.5 +/- 0.5 GtC yr 1, E-LUC 1.5 +/- 0.7 GtC yr 1, G(ATM) 4.9 +/- 0.02 GtC yr(-1) (2.3 +/- 0.01 ppm yr(-1)), S-OCEAN 2.5 +/- 0.6 GtC yr(-1), and S-LAND 3.2 +/- 0.6 GtC yr(-1), with a budget imbalance B-IM of 0.4 GtC yr(-1) indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in E-FF was about 2.1% and fossil emissions increased to 10.0 +/- 0.5 GtC yr 1, reaching 10 GtC yr(-1) for the first time in history, E-LUC was 1.5 +/- 0.7 GtC yr(-1), for total anthropogenic CO2 emissions of 11.5 +/- 0.9 GtC yr(-1) (42.5 +/- 3.3 GtCO(2)). Also for 2018, G(ATM) was 5.1 +/- 0.2 GtC yr(-1) (2.4 +/- 0.1 ppm yr(-1)), S-OCEAN was 2.6 +/- 0.6 GtC yr(-1), and S-LAND was 3.5 +/- 0.7 GtC yr(-1), with a B-IM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38 +/- 0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6-10 months indicate a reduced growth in E-FF of +0.6% (range of -0.2% to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959-2018, but discrepancies of up to 1 GtC yr(-1) persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018a, b, 2016, 2015a, b, 2014, 2013).

Published
2019

26. State of the Climate in 2018

Author

Arndt, D. S., Blunden, J., Dunn, R. J. H., Stanitski, D. M., Gobron, N., Willett, K. M., Sanchez-lugo, A., Berrisford, P., Morice, C., Nicolas, Jp, Carrea, L., Woolway, R. I., Merchant, C. J., Dokulil, M. T., De Eyto, E., Degasperi, C. L., Korhonen, J., Marszelewski, W., May, L., Paterson, A. M., Rusak, J. A., Schladow, S. G., Schmid, M., Verburg, P., Watanabe, S., Weyhenmeyer, G. A., King, A. D., Donat, M. G., Christy, J. R., Po-chedley, S., Mears, C. R., Haimberger, L., Covey, C., Randel, W., Noetzli, J., Biskaborn, B. K., Christiansen, H. H., Isaksen, K., Schoeneich, P., Smith, S., Vieira, G., Zhao, L., Streletskiy, D. A., Robinson, D. A., Pelto, M., Berry, D. I., Bosilovich, M. G., Simmons, A. J., Mears, C., Ho, S. P., Bock, O., Zhou, X., Nicolas, J, Vose, R. S., Adler, R., Gu, G., Becker, A., Yin, X, Tye, M. R., Blenkinsop, S., Durre, I., Ziese, M., Collow, A. B. Marquardt, Rustemeier, E., Foster, M. J., Di Girolamo, L., Frey, R. A., Heidinger, A. K., Sun-mack, S., Phillips, C., Menzel, W. P., Stengel, M., Zhao, G., Kim, H., Rodell, M., Li, B., Famiglietti, J. S., Scanlon, T., Van Der Schalie, R., Preimesberger, W., Reimer, C., Hahn, S., Gruber, A., Kidd, R., De Jeu, R. A. M., Dorigo, W. A., Barichivich, J., Osborn, T. J., Harris, I., Van Der Schrier, G., Jones, P. D., Miralles, D. G., Martens, B., Beck, H. E., Dolman, A. J., Jimenez, C., Mccabe, M. F., Wood, E. F., Allan, R., Azorin-molina, C., Mears, C. A., Mcvicar, T. R., Mayer, M., Schenzinger, V., Hersbach, H., Stackhouse, P. W., Jr., Wong, T., Kratz, D. P., Sawaengphokhai, P., Wilber, A. C., Gupta, S. K., Loeb, N. G., Dlugokencky, E. J., Hall, B. D., Montzka, S. A., Dutton, G., Muhle, J., Elkins, J. W., Miller, Br, Remy, S., Bellouin, N., Kipling, Z., Ades, M., Benedetti, A., Boucher, O., Weber, M., Steinbrecht, W., Arosio, C., Van Der A, R., Frith, S. M., Anderson, J., Coldewey-egbers, M., Davis, S., Degenstein, D., Fioletov, V. E., Froidevaux, L., Hubert, D., Long, C. S., Loyola, D., Rozanov, A., Roth, C., Sofieva, V., Tourpali, K., Wang, R., Wild, J. D., Davis, S. M., Rosenlof, K. H., Hurst, D. F., Selkirk, H. B., Vomel, H., Ziemke, J. R., Cooper, O. R., Flemming, J., Inness, A., Pinty, B., Kaiser, J. W., Van Der Werf, G. R., Hemming, D. L., Garforth, J., Park, T., Richardson, A. D., Rutishauser, T., Sparks, T. H., Thackeray, S. J., Myneni, R., Lumpkin, R., Huang, B., Kennedy, J., Xue, Y., Zhang, H. -m., Hu, C., Wang, M., Johnson, G. C., Lyman, J. M., Boyer, T., Cheng, L., Domingues, C. M., Gilson, J., Ishii, M., Killick, R. E., Monselesan, D., Purkey, S. G., Wijffels, S. E., Locarnini, R., Yu, L., Jin, X., Stackhouse, P. W., Kato, S., Weller, R. A., Thompson, P. R., Widlansky, M. J., Leuliette, E., Sweet, W., Chambers, D. P., Hamlington, B. D., Jevrejeva, S., Marra, J. J., Merrifield, M. A., Mitchum, G. T., Nerem, R. S., Kelble, C., Karnauskas, M., Hubbard, K., Goni, G., Streeter, C., Dohan, K., Franz, B. A., Cetinic, I., Karakoylu, E. M., Siegel, D. A., Westberry, T. K., Feely, R. A., Wanninkhof, R., Carter, B. R., Landschutzer, P., Sutton, A. J., Cosca, C., Trinanes, J. A., Baxter, S., Schreck, C., Bell, G. D., Mullan, A. B., Pezza, A. B., Coelho, C. A. S., Wang, B., He, Q., Diamond, H. J., Schreck, C. J., Blake, E. S., Landsea, C. W., Wang, H., Goldenberg, S. B., Pasch, R. J., Klotzbach, P. J., Kruk, M. C., Camargo, S. J., Trewin, B. C., Pearce, P. R., Lorrey, A. M., Domingues, R., Goni, G. J., Knaff, J. A., Lin, I. -i., Bringas, F., Richter-menge, J., Osborne, E., Druckenmiller, M., Jeffries, M. O., Overland, J. E., Hanna, E., Hanssen-bauer, I., Kim, S. -j., Walsh, J. E., Bhatt, U. S., Timmermans, M. -l., Ladd, C., Perovich, D., Meier, W., Tschudi, M., Farrell, S., Hendricks, S., Gerland, S., Haas, C., Krumpen, T., Polashenski, C., Ricker, R, Webster, M., Stabeno, P. J., Tedesco, M., Box, J. E., Cappelen, J., Fausto, R. S., Fettweis, X., Andersen, J. K., Mote, T., Smeets, C. J. P. P., Van As, D., Van De Wal, R. S. W., Romanovsky, V. E., Smith, S. L., Shiklomanov, N. I., Kholodov, A. L., Drozdov, D. S., Malkova, G. V., Marchenko, S. S., Jella, K. B., Mudryk, L., Brown, R., Derksen, C., Luojus, K., Decharme, B., Holmes, R. M., Shiklomanov, A. I., Suslova, A., Tretiakov, M., Mcclelland, J. W., Spencer, R. G. M., Tank, S. E., Epstein, H., Bhatt, U., Raynolds, M., Walker, D., Forbes, B., Phoenix, G., Bjerke, J., Tommervik, H., Karlsen, S. -r., Goetz, S., Jia, G., Bernhard, G. H., Grooss, J. -u., Ialongo, I., Johnsen, B., Lakkala, K., Manney, G. L., Mueller, R., Scambos, T., Stammerjohn, S., Clem, K. R., Barreira, S., Fogt, R. L., Colwell, S., Keller, L. M., Lazzara, M. A., Reid, P., Massom, R. A., Lieser, J. L., Meijers, A., Sallee, J. -b., Grey, A., Johnson, K., Arrigo, K., Swart, S., King, B., Meredith, M., Mazloff, M., Scardilli, A., Claus, F., Shuman, C. A., Kramarova, N., Newman, P. A., Nash, E. R., Strahan, S. E., Johnson, B., Pitts, M., Santee, M. L., Petropavlovskikh, I., Braathen, G. O., Coy, L., De Laat, J., Bissolli, P., Ganter, C., Li, T., Mekonnen, A., Gleason, K., Smith, A., Fenimore, C., Heim, R. R., Jr., Nauslar, N. J., Brown, T. J., Mcevoy, D. J., Lareau, N. P., Amador, J. A., Hidalgo, H. G., Alfaro, E. J., Calderon, B., Mora, N., Stephenson, T. S., Taylor, M. A., Trotman, A. R., Van Meerbeeck, C. J., Campbell, J. D., Brown, A., Spence, J., Martinez, R., Diaz, E., Marin, D., Hernandez, R., Caceres, L., Zambrano, E., Nieto, J., Marengo, J. A., Espinoza, J. C., Alves, L. M., Ronchail, J., Lavado-casimiro, J. W., Ramos, I., Davila, C., Ramos, A. M., Diniz, F. A., Aliaga-nestares, V., Castro, A. Y., Stella, J. L., Aldeco, L. S., Diaz, D. A. Campos, Misevicius, N., Kabidi, K., Sayouri, A., Elkharrim, M., Mostafa, A. E., Hagos, S., Feng, Z., Ijampy, J. A., Sima, F., Francis, S. D., Tsidu, G. Mengistu, Kruger, A. C., Mcbride, C., Jumaux, G., Dhurmea, K. R., Belmont, M., Rakotoarimalala, C. L., Labbe, L., Rosner, B., Benedict, I., Van Heerwaarden, C., Weerts, A., Hazeleger, W., Trachte, K., Zhu, Z., Zhang, P., Lee, T. C., Ripaldi, A., Mochizuki, Y., Lim, J. -y, Oyunjargal, L., Timbal, B., Srivastava, A. K., Revadekar, J. V., Rajeevan, M., Shimpo, A., Khoshkam, M., Kazemi, A. Fazl, Zeyaeyan, S., Lander, M. A., Mcgree, S., Tobin, S., Bettio, L., Arndt, D. S., Blunden, J., Dunn, R. J. H., Stanitski, D. M., Gobron, N., Willett, K. M., Sanchez-lugo, A., Berrisford, P., Morice, C., Nicolas, Jp, Carrea, L., Woolway, R. I., Merchant, C. J., Dokulil, M. T., De Eyto, E., Degasperi, C. L., Korhonen, J., Marszelewski, W., May, L., Paterson, A. M., Rusak, J. A., Schladow, S. G., Schmid, M., Verburg, P., Watanabe, S., Weyhenmeyer, G. A., King, A. D., Donat, M. G., Christy, J. R., Po-chedley, S., Mears, C. R., Haimberger, L., Covey, C., Randel, W., Noetzli, J., Biskaborn, B. K., Christiansen, H. H., Isaksen, K., Schoeneich, P., Smith, S., Vieira, G., Zhao, L., Streletskiy, D. A., Robinson, D. A., Pelto, M., Berry, D. I., Bosilovich, M. G., Simmons, A. J., Mears, C., Ho, S. P., Bock, O., Zhou, X., Nicolas, J, Vose, R. S., Adler, R., Gu, G., Becker, A., Yin, X, Tye, M. R., Blenkinsop, S., Durre, I., Ziese, M., Collow, A. B. Marquardt, Rustemeier, E., Foster, M. J., Di Girolamo, L., Frey, R. A., Heidinger, A. K., Sun-mack, S., Phillips, C., Menzel, W. P., Stengel, M., Zhao, G., Kim, H., Rodell, M., Li, B., Famiglietti, J. S., Scanlon, T., Van Der Schalie, R., Preimesberger, W., Reimer, C., Hahn, S., Gruber, A., Kidd, R., De Jeu, R. A. M., Dorigo, W. A., Barichivich, J., Osborn, T. J., Harris, I., Van Der Schrier, G., Jones, P. D., Miralles, D. G., Martens, B., Beck, H. E., Dolman, A. J., Jimenez, C., Mccabe, M. F., Wood, E. F., Allan, R., Azorin-molina, C., Mears, C. A., Mcvicar, T. R., Mayer, M., Schenzinger, V., Hersbach, H., Stackhouse, P. W., Jr., Wong, T., Kratz, D. P., Sawaengphokhai, P., Wilber, A. C., Gupta, S. K., Loeb, N. G., Dlugokencky, E. J., Hall, B. D., Montzka, S. A., Dutton, G., Muhle, J., Elkins, J. W., Miller, Br, Remy, S., Bellouin, N., Kipling, Z., Ades, M., Benedetti, A., Boucher, O., Weber, M., Steinbrecht, W., Arosio, C., Van Der A, R., Frith, S. M., Anderson, J., Coldewey-egbers, M., Davis, S., Degenstein, D., Fioletov, V. E., Froidevaux, L., Hubert, D., Long, C. S., Loyola, D., Rozanov, A., Roth, C., Sofieva, V., Tourpali, K., Wang, R., Wild, J. D., Davis, S. M., Rosenlof, K. H., Hurst, D. F., Selkirk, H. B., Vomel, H., Ziemke, J. R., Cooper, O. R., Flemming, J., Inness, A., Pinty, B., Kaiser, J. W., Van Der Werf, G. R., Hemming, D. L., Garforth, J., Park, T., Richardson, A. D., Rutishauser, T., Sparks, T. H., Thackeray, S. J., Myneni, R., Lumpkin, R., Huang, B., Kennedy, J., Xue, Y., Zhang, H. -m., Hu, C., Wang, M., Johnson, G. C., Lyman, J. M., Boyer, T., Cheng, L., Domingues, C. M., Gilson, J., Ishii, M., Killick, R. E., Monselesan, D., Purkey, S. G., Wijffels, S. E., Locarnini, R., Yu, L., Jin, X., Stackhouse, P. W., Kato, S., Weller, R. A., Thompson, P. R., Widlansky, M. J., Leuliette, E., Sweet, W., Chambers, D. P., Hamlington, B. D., Jevrejeva, S., Marra, J. J., Merrifield, M. A., Mitchum, G. T., Nerem, R. S., Kelble, C., Karnauskas, M., Hubbard, K., Goni, G., Streeter, C., Dohan, K., Franz, B. A., Cetinic, I., Karakoylu, E. M., Siegel, D. A., Westberry, T. K., Feely, R. A., Wanninkhof, R., Carter, B. R., Landschutzer, P., Sutton, A. J., Cosca, C., Trinanes, J. A., Baxter, S., Schreck, C., Bell, G. D., Mullan, A. B., Pezza, A. B., Coelho, C. A. S., Wang, B., He, Q., Diamond, H. J., Schreck, C. J., Blake, E. S., Landsea, C. W., Wang, H., Goldenberg, S. B., Pasch, R. J., Klotzbach, P. J., Kruk, M. C., Camargo, S. J., Trewin, B. C., Pearce, P. R., Lorrey, A. M., Domingues, R., Goni, G. J., Knaff, J. A., Lin, I. -i., Bringas, F., Richter-menge, J., Osborne, E., Druckenmiller, M., Jeffries, M. O., Overland, J. E., Hanna, E., Hanssen-bauer, I., Kim, S. -j., Walsh, J. E., Bhatt, U. S., Timmermans, M. -l., Ladd, C., Perovich, D., Meier, W., Tschudi, M., Farrell, S., Hendricks, S., Gerland, S., Haas, C., Krumpen, T., Polashenski, C., Ricker, R, Webster, M., Stabeno, P. J., Tedesco, M., Box, J. E., Cappelen, J., Fausto, R. S., Fettweis, X., Andersen, J. K., Mote, T., Smeets, C. J. P. P., Van As, D., Van De Wal, R. S. W., Romanovsky, V. E., Smith, S. L., Shiklomanov, N. I., Kholodov, A. L., Drozdov, D. S., Malkova, G. V., Marchenko, S. S., Jella, K. B., Mudryk, L., Brown, R., Derksen, C., Luojus, K., Decharme, B., Holmes, R. M., Shiklomanov, A. I., Suslova, A., Tretiakov, M., Mcclelland, J. W., Spencer, R. G. M., Tank, S. E., Epstein, H., Bhatt, U., Raynolds, M., Walker, D., Forbes, B., Phoenix, G., Bjerke, J., Tommervik, H., Karlsen, S. -r., Goetz, S., Jia, G., Bernhard, G. H., Grooss, J. -u., Ialongo, I., Johnsen, B., Lakkala, K., Manney, G. L., Mueller, R., Scambos, T., Stammerjohn, S., Clem, K. R., Barreira, S., Fogt, R. L., Colwell, S., Keller, L. M., Lazzara, M. A., Reid, P., Massom, R. A., Lieser, J. L., Meijers, A., Sallee, J. -b., Grey, A., Johnson, K., Arrigo, K., Swart, S., King, B., Meredith, M., Mazloff, M., Scardilli, A., Claus, F., Shuman, C. A., Kramarova, N., Newman, P. A., Nash, E. R., Strahan, S. E., Johnson, B., Pitts, M., Santee, M. L., Petropavlovskikh, I., Braathen, G. O., Coy, L., De Laat, J., Bissolli, P., Ganter, C., Li, T., Mekonnen, A., Gleason, K., Smith, A., Fenimore, C., Heim, R. R., Jr., Nauslar, N. J., Brown, T. J., Mcevoy, D. J., Lareau, N. P., Amador, J. A., Hidalgo, H. G., Alfaro, E. J., Calderon, B., Mora, N., Stephenson, T. S., Taylor, M. A., Trotman, A. R., Van Meerbeeck, C. J., Campbell, J. D., Brown, A., Spence, J., Martinez, R., Diaz, E., Marin, D., Hernandez, R., Caceres, L., Zambrano, E., Nieto, J., Marengo, J. A., Espinoza, J. C., Alves, L. M., Ronchail, J., Lavado-casimiro, J. W., Ramos, I., Davila, C., Ramos, A. M., Diniz, F. A., Aliaga-nestares, V., Castro, A. Y., Stella, J. L., Aldeco, L. S., Diaz, D. A. Campos, Misevicius, N., Kabidi, K., Sayouri, A., Elkharrim, M., Mostafa, A. E., Hagos, S., Feng, Z., Ijampy, J. A., Sima, F., Francis, S. D., Tsidu, G. Mengistu, Kruger, A. C., Mcbride, C., Jumaux, G., Dhurmea, K. R., Belmont, M., Rakotoarimalala, C. L., Labbe, L., Rosner, B., Benedict, I., Van Heerwaarden, C., Weerts, A., Hazeleger, W., Trachte, K., Zhu, Z., Zhang, P., Lee, T. C., Ripaldi, A., Mochizuki, Y., Lim, J. -y, Oyunjargal, L., Timbal, B., Srivastava, A. K., Revadekar, J. V., Rajeevan, M., Shimpo, A., Khoshkam, M., Kazemi, A. Fazl, Zeyaeyan, S., Lander, M. A., Mcgree, S., Tobin, S., and Bettio, L.

Published
2019

27. Global carbon budget 2018 [Data Paper]

Author

Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P. A., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Arneth, A., Arora, V. K., Barbero, L., Bastos, A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Doney, S. C., Gkritzalis, T., Goll, D. S., Harris, I., Haverd, V., Hoffman, F. M., Hoppema, M., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Johannessen, T., Jones, C. D., Kato, E., Keeling, R. F., Goldewijk, K. K., Landschutzer, P., Lefèvre, Nathalie, Lienert, S., Liu, Z., Lombardozzi, D., Metzl, N., Munro, D. R., Nabel, Jems, Nakaoka, S., Neill, C., Olsen, A., Ono, T., Patra, P., Peregon, A., Peters, W., Peylin, P., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rocher, M., Rodenbeck, C., Schuster, U., Schwinger, J., Seferian, R., Skjelvan, I., Steinhoff, T., Sutton, A., Tans, P. P., Tian, H. Q., Tilbrook, B., Tubiello, F. N., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Wright, R., Zaehle, S., and Zheng, B.

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere - the "global carbon budget" - is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (E-FF) are based on energy statistics and cement production data, while emissions from land use and land-use change (E-LUC), mainly deforestation, are based on land use and land -use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (G(ATM)) is computed from the annual changes in concentration. The ocean CO2 sink (S-OCEAN) and terrestrial CO2 sink (S-LAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B-IM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as +/- 1 sigma. For the last decade available (2008-2017), E-FF was 9.4 +/- 0.5 GtC yr(-1), E-LUC 1.5 +/- 0.7 GtC yr(-1), G(ATM) 4.7 +/- 0.02 GtC yr(-1), S-OCEAN 2.4 +/- 0.5 GtC yr(-1), and S-LAND 3.2 +/- 0.8 GtC yr(-1), with a budget imbalance B-IM of 0.5 GtC yr(-1) indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E-FF was about 1.6 % and emissions increased to 9.9 +/- 0.5 GtC yr(-1). Also for 2017, E-LUC was 1.4 +/- 0.7 GtC yr(-1), G(ATM) was 4.6 +/- 0.2 GtC yr(-1), S-OCEAN was 2.5 +/- 0.5 GtC yr(-1), and S-LAND was 3.8 +/- 0.8 GtC yr(-1), with a B-IM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0 +/- 0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6-9 months indicate a renewed growth in E-FF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959-2017, but discrepancies of up to 1 GtC yr(-1) persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land -use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from

Published
2018

29. Global Carbon Budget 2017

Author

Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Pongratz, J., Manning, A. C., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Jackson, R. B., Boden, T. A., Tans, P. P., Andrews, O. D., Arora, V. K., Bakker, D. C. E., Barbero, L., Becker, M., Betts, R. A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Cosca, C. E., Cross, J., Currie, K., Gasser, T., Harris, I., Hauck, J., Haverd, V., Houghton, R. A., Hunt, C. W., Hurtt, G., Ilyina, T., Jain, A. K., Kato, E., Kautz, M., Keeling, R. F., Klein Goldewijk, K., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lima, I., Lombardozzi, D., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Nojiri, Y., Padin, X. A., Peregon, A., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Reimer, J., Rödenbeck, C., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Tian, H., Tilbrook, B., Tubiello, F. N., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Viovy, N., Vuichard, N., Walker, A. P., Watson, A. J., Wiltshire, A. J., Zaehle, S., Zhu, D., Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Pongratz, J., Manning, A. C., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Jackson, R. B., Boden, T. A., Tans, P. P., Andrews, O. D., Arora, V. K., Bakker, D. C. E., Barbero, L., Becker, M., Betts, R. A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Cosca, C. E., Cross, J., Currie, K., Gasser, T., Harris, I., Hauck, J., Haverd, V., Houghton, R. A., Hunt, C. W., Hurtt, G., Ilyina, T., Jain, A. K., Kato, E., Kautz, M., Keeling, R. F., Klein Goldewijk, K., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lima, I., Lombardozzi, D., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Nojiri, Y., Padin, X. A., Peregon, A., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Reimer, J., Rödenbeck, C., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Tian, H., Tilbrook, B., Tubiello, F. N., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Viovy, N., Vuichard, N., Walker, A. P., Watson, A. J., Wiltshire, A. J., Zaehle, S., and Zhu, D.

Published
2018

30. Biological and geophysical feedbacks with fire in the Earth system

Author

Archibald, Sally, Lehmann, Caroline E. R, Belcher, C, Bond, William J, Bradstock, Ross A, Daniau, A-L, Dexter, K, Forrestel, E, Greve, M, He, T, Higgins, S I, Hoffmann, W, Lamont, B B, McGlinn, D J, Moncrieff, G, Osborne, C P, Pausas, Juli G, Price, Owen F, Ripley, B, Rogers, B, Schwilk, D, Simon, M, Turetsky, M, Van Der Werf, G R, Zanne, A E, Archibald, Sally, Lehmann, Caroline E. R, Belcher, C, Bond, William J, Bradstock, Ross A, Daniau, A-L, Dexter, K, Forrestel, E, Greve, M, He, T, Higgins, S I, Hoffmann, W, Lamont, B B, McGlinn, D J, Moncrieff, G, Osborne, C P, Pausas, Juli G, Price, Owen F, Ripley, B, Rogers, B, Schwilk, D, Simon, M, Turetsky, M, Van Der Werf, G R, and Zanne, A E

Abstract

Roughly 3% of the Earth's land surface burns annually, representing a critical exchange of energy and matter between the land and atmosphere via combustion. Fires range from slow smouldering peat fires, to low-intensity surface fires, to intense crown fires, depending on vegetation structure, fuel moisture, prevailing climate, and weather conditions. While the links between biogeochemistry, climate and fire are widely studied within Earth system science, these relationships are also mediated by fuels-namely plants and their litter-that are the product of evolutionary and ecological processes. Fire is a powerful selective force and, over their evolutionary history, plants have evolved traits that both tolerate and promote fire numerous times and across diverse clades. Here we outline a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes. We explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes. Finally, we outline several research challenges that, when resolved, will improve our understanding of the role of plant evolution in mediating the fire feedbacks driving Earth system processes. Understanding current patterns of fire and vegetation, as well as patterns of fire over geological time, requires research that incorporates evolutionary biology, ecology, biogeography, and the biogeosciences.

Published
2018

31. Fine Particle Emissions From Tropical Peat Fires Decrease Rapidly With Time Since Ignition

Author

Roulston, Christopher, Paton-Walsh, Clare, Smith, T E L, Guerette, Elise-Andree, Evers, S, Yule, C, Rein, G, Van Der Werf, G R, Roulston, Christopher, Paton-Walsh, Clare, Smith, T E L, Guerette, Elise-Andree, Evers, S, Yule, C, Rein, G, and Van Der Werf, G R

Abstract

Southeast Asia experiences frequent fires in fuel-rich tropical peatlands, leading to extreme episodes of regional haze with high concentrations of fine particulate matter (PM 2.5 ) impacting human health. In a study published recently, the first field measurements of PM 2.5 emission factors for tropical peat fires showed larger emissions than from other fuel types. Here we report even higher PM 2.5 emission factors, measured at newly ignited peat fires in Malaysia, suggesting that current estimates of fine particulate emissions from peat fires may be underestimated by a factor of 3 or more. In addition, we use both field and laboratory measurements of burning peat to provide the first mechanistic explanation for the high variability in PM 2.5 emission factors, demonstrating that buildup of a surface ash layer causes the emissions of PM 2.5 to decrease as the peat fire progresses. This finding implies that peat fires are more hazardous (in terms of aerosol emissions) when first ignited than when still burning many days later. Varying emission factors for PM 2.5 also have implications for our ability to correctly model the climate and air quality impacts downwind of the peat fires. For modelers able to implement a time-varying emission factor, we recommend an emission factor for PM 2.5 from newly ignited tropical peat fires of 58 g of PM 2.5 per kilogram of dry fuel consumed (g/kg), reducing exponentially at a rate of 9%/day. If the age of the fire is unknown or only a single value may be used, we recommend an average value of 24 g/kg.

Published
2018

32. A carbon cycle science update since IPCC AR-4

Author

A. J. Dolman, van der Werf, G. R., van der Molen, M. K., Ganssen, G., Erisman, J.-W., and Strengers, B.

Subjects
Carbon cycle (Biogeochemistry) -- Environmental aspects, Carbon cycle (Biogeochemistry) -- Influence, Emissions (Pollution) -- Environmental aspects, Emissions (Pollution) -- Influence, Ocean-atmosphere interaction -- Environmental aspects, Environmental issues
Published
2010

33. The status and challenge of global fire modelling

Author

Hantson, S., Arneth, A., Harrison, Sandy P., Kelley, Doug I., Prentice, I.C, Rabin, S. S., Archibald, S., Mouillot, F., Arnold, S. R., Artaxo, P., Bachelet, D., Ciais, P., Forrest, M., Friedlingstein, P., Hickler, T., Kaplan, J. O., Kloster, S., Knorr, W., Laslop, G., Li, F., Melton, J. R., Meyn, A., Sitch, S., Spessa, Allan, van der Werf, G. R., Voulgarakis, A., and Yue, C.

Abstract

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what\ud essons may be learned from FireMIP.

Published
2016

34. Biological and geophysical feedbacks with fire in the Earth system

Author

Archibald, S, primary, Lehmann, C E R, additional, Belcher, C M, additional, Bond, W J, additional, Bradstock, R A, additional, Daniau, A-L, additional, Dexter, K G, additional, Forrestel, E J, additional, Greve, M, additional, He, T, additional, Higgins, S I, additional, Hoffmann, W A, additional, Lamont, B B, additional, McGlinn, D J, additional, Moncrieff, G R, additional, Osborne, C P, additional, Pausas, J G, additional, Price, O, additional, Ripley, B S, additional, Rogers, B M, additional, Schwilk, D W, additional, Simon, M F, additional, Turetsky, M R, additional, Van der Werf, G R, additional, and Zanne, A E, additional

Published
2018
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35. Ammonia emissions from biomass burning: comparison between satellite-derived emissions and bottom-up inventories

Author

Whitburn, S., van Damme, M., Kaiser, J. W., van Der Werf, G. R., Turquety, Solène, Hurtmans, Daniel, Clarisse, Lieven, Clerbaux, Cathy, Coheur, Pierre-François, Spectroscopie de l'atmosphère, Service de Chimie Quantique et Photophysique, Université libre de Bruxelles (ULB), Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), VU University Amsterdam, Cardon, Catherine, Vrije Universiteit Amsterdam [Amsterdam] (VU), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDE.MCG] Environmental Sciences/Global Changes, [SDE.MCG]Environmental Sciences/Global Changes, [PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

36. Global carbon budget 2014

Author

Le Quéré, C., Moriarty, R., Andrew, R. M., Peters, G. P., Ciais, P., Friedlingstein, P., Jones, S. D., Sitch, S., Tans, P., Arneth, A., Boden, T. A., Bopp, L., Bozec, Y., Canadell, J. G., Chevallier, F., Cosca, C. E., Harris, I., Hoppema, M., Houghton, R. A., House, J. I., Jain, A., Johannessen, T., Kato, E., Keeling, R. F., Kitidis, V., Klein Goldewijk, K., Koven, C., Landa, C. S., Landschützer, P., Lenton, A., Lima, I. D., Marland, G., Mathis, J. T., Metzl, N., Nojiri, Y., Olsen, A., Ono, T., Peters, W., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Salisbury, J. E., Schuster, U., Schwinger, J., Séférian, R., Segschneider, J., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Werf, G. R., Viovy, N., Wang, Y.-P., Wanninkhof, R., Wiltshire, A., Zeng, N., Environmental Sciences, LS Economische Geschiedenis, and Leerstoel Aarts

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2)emissions and their redistribution among the atmosphere, ocean, andterrestrial biosphere is important to better understand the globalcarbon cycle, support the development of climate policies, and projectfuture climate change. Here we describe datasets and a methodology toquantify all major components of the global carbon budget, includingtheir uncertainties, based on the combination of a range of data,algorithms, statistics and model estimates and their interpretation by abroad scientific community. We discuss changes compared to previousestimates, consistency within and among components, alongsidemethodology and data limitations. CO2 emissions from fossilfuel combustion and cement production (EFF) are based onenergy statistics and cement production data, respectively, whileemissions from Land-Use Change (ELUC), mainly deforestation,are based on combined evidence from land-cover change data, fireactivity associated with deforestation, and models. The globalatmospheric CO2 concentration is measured directly and itsrate of growth (GATM) is computed from the annual changes inconcentration. The mean ocean CO2 sink (SOCEAN) isbased on observations from the 1990s, while the annual anomalies andtrends are estimated with ocean models. The variability inSOCEAN is evaluated with data products based on surveys ofocean CO2 measurements. The global residual terrestrialCO2 sink (SLAND) is estimated by the difference ofthe other terms of the global carbon budget and compared to results ofindependent Dynamic Global Vegetation Models forced by observed climate,CO2 and land cover change (some including nitrogen-carboninteractions). We compare the variability and mean land and ocean fluxesto estimates from three atmospheric inverse methods for three broadlatitude bands. All uncertainties are reported as ±1σ,reflecting the current capacity to characterise the annual estimates ofeach component of the global carbon budget. For the last decadeavailable (2004-2013), EFF was 8.9 ± 0.4 GtCyr-1, ELUC 0.9 ± 0.5 GtC yr-1,GATM 4.3 ± 0.1 GtC yr-1, SOCEAN2.6 ± 0.5 GtC yr-1, and SLAND 2.9 ±0.8 GtC yr-1. For year 2013 alone, EFF grew to 9.9± 0.5 GtC yr-1, 2.3% above 2012, contining the growthtrend in these emissions. ELUC was 0.9 ± 0.5 GtCyr-1, GATM was 5.4 ± 0.2 GtCyr-1, SOCEAN was 2.9 ± 0.5 GtCyr-1 and SLAND was 2.5 ± 0.9 GtCyr-1. GATM was high in 2013 reflecting a steadyincrease in EFF and smaller and opposite changes betweenSOCEAN and SLAND compared to the past decade(2004-2013). The global atmospheric CO2 concentration reached395.31 ± 0.10 ppm averaged over 2013. We estimate thatEFF will increase by 2.5% (1.3-3.5%) to 10.1 ± 0.6 GtCin 2014 (37.0 ± 2.2 GtCO2 yr-1), 65% aboveemissions in 1990, based on projections of World Gross Domestic Productand recent changes in the carbon intensity of the economy. From thisprojection of EFF and assumed constant ELUC for2014, cumulative emissions of CO2 will reach about 545± 55 GtC (2000 ± 200 GtCO2) for 1870-2014,about 75% from EFF and 25% from ELUC. This paperdocuments changes in the methods and datasets used in this new carbonbudget compared with previous publications of this living dataset (LeQuéré et al., 2013, 2014). All observations presented herecan be downloaded from the Carbon Dioxide Information Analysis Center(doi:10.3334/CDIAC/GCP_2014). Italic font highlights significant methodological changesand results compared to the Le Quéré et al. (2015)manuscript that accompanies the previous version of this living data.

Published
2015

37. Global carbon budget 2014

Author

Canadell, J. G., Tilbrook, B., Raupach, M. R., House, J. I., Salisbury, J. E., Keeling, R. F., Steinhoff, T., Moriarty, R., Wanninkhof, R., Lenton, A., Andrew, R. M., Poulter, B., Koven, C., Schuster, U., Peters, G. P., Landa, C. S., Arneth, A., Bopp, L., Johannessen, T., Bozec, Y., Wang, Y.-P., Cosca, C. E., Ciais, P., Mathis, J. T., Tans, P., Viovy, N., Harris, I., Landschützer, P., Lima, I. D., Takahashi, T., Friedlingstein, P., Jain, A. K., Metzl, N., Regnier, P., Olsen, A., Hoppema, M., Jones, S. D., Le Quéré, C., Chevallier, F., Sitch, S., Klein Goldewijk, K., Marland, G., Boden, T. A., Ono, T., Houghton, R. A., Peters, W., Kato, E., Nojiri, Y., Peng, S., Wiltshire, A., Chini, L. P., Rödenbeck, C., Segschneider, J., Saito, S., Schwinger, J., Sutton, A. J., Zeng, N., Van Der Werf, G. R., Stocker, Benjamin, Séférian, R., Pfeil, B., and Kitidis, V.

Subjects
530 Physics
Published
2015
Full Text
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38. Global Carbon Budget 2016

Author

Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Zaehle, S., Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.

Published
2016

39. The global methane budget 2000–2012

Author

Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Brovkin, V., Bruhwiler, L., Crevoisier, C., Crill, Patrick, Covey, K., Curry, C., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H. -S, Kleinen, T., Krummel, P., Lamarque, J. -F, Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., McDonald, K. C., Marshall, J., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F. -JW., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prigent, C., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Steele, P., Takizawa, A., Thornton, Brett F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., van Weele, M., van der Werf, G. R., Weiss, R., Wiedinmyer, C., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., Zhu, Q., Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Brovkin, V., Bruhwiler, L., Crevoisier, C., Crill, Patrick, Covey, K., Curry, C., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H. -S, Kleinen, T., Krummel, P., Lamarque, J. -F, Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., McDonald, K. C., Marshall, J., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F. -JW., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prigent, C., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Steele, P., Takizawa, A., Thornton, Brett F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., van Weele, M., van der Werf, G. R., Weiss, R., Wiedinmyer, C., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., and Zhu, Q.

Abstract

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by top-down inversions at 558 Tg CH4 yr−1, range 540–568. About 60 % of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bott

Published
2016
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40. Global Carbon Budget 2016

Author

Environmental Sciences, Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Zaehle, S., Environmental Sciences, Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.

Published
2016

41. Ammonia emissions in biomass burning regions: estimation from satellite-derived measurements and comparison with bottom-up inventories

Author

4th IASI International Conference,Antibes, France,11-15 April 2016, Whitburn, Simon, Van Damme, Martin, Kaiser, Johannes, Van der Werf, G. R., Turquety, Solène, Clarisse, Lieven, Clerbaux, Cathy, Coheur, Pierre, 4th IASI International Conference,Antibes, France,11-15 April 2016, Whitburn, Simon, Van Damme, Martin, Kaiser, Johannes, Van der Werf, G. R., Turquety, Solène, Clarisse, Lieven, Clerbaux, Cathy, and Coheur, Pierre

Abstract

info:eu-repo/semantics/nonPublished

Published
2016

44. Global fire emission estimates for 2009-2010 derived from GOME-2 formaldehyde columns

Author

Bauwens, M., Stavrakou, T., Müller, J.-F., de Smedt, I., van Roozendael, M., van Der Werf, G. R., Wiedinmyer, C., George, Maya, Clerbaux, Cathy, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Vrije Universiteit Amsterdam [Amsterdam] (VU), National Center for Atmospheric Research [Boulder] (NCAR), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Cardon, Catherine

Subjects
[SDE.MCG] Environmental Sciences/Global Changes, [SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDE.MCG]Environmental Sciences/Global Changes
Abstract

To derive updated global biomass burning emission estimates for non-methane volatile organic compounds (NMVOCs), formaldehyde columns retrieved from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument (launched on MetOp-A in 2006) are used as top-down constraints in an inverse modeling scheme. Compared to GOME-1 the use of GOME-2 formaldehyde columns are found to be less sensitive to the South Atlantic Anomaly, offering new perspectives for the study of NMVOC emissions in the Amazon. Furthermore, the better Earth sampling of GOME-2 allows for a significant reduction of the noise on the monthly columns leading to a better identification of the emission sources. Furthermore, two corrections lead to a significant reduction of the scatter in the formaldehyde slant columns: a new retrieval scheme including a two-step fitting procedure that strongly reduces the interferences between formaldehyde and bromine oxide spectral structures, and a modified DOAS approach adopted to better handle the strong ozone absorption effects, improving the fit at large solar zenith angles. The new version of the Global Fire Emissions Database version 3 (GFEDv3) is used as bottom-up inventory in IMAGESv2 global chemistry-transport model for biomass burning. The principal updates of the GFEDv3 inventory with respect to the older GFEDv2 inventory are the use of improved satellite input data, the explicit inclusion of deforestation and forest degradation fires in the model, the partitioning of fire emissions into different source categories, and an uncertainty analysis. The agreement between formaldehyde columns calculated by the IMAGESv2 model and the formaldehyde columns from GOME-2 is optimized using the adjoint modelling technique. This technique allows for the optimization of the emission strengths at the model resolution and provides a differentiation among the emission sources. Updated biomass burning emissions estimates are obtained monthly for 2009 and 2010 at the model resolution (2 x 2.5°). They will be evaluated through comparison with the Fire INventory from NCAR 55 (FINN) for the target years. Further, CO columns retrieved from the Infrared Atmospheric Sounding Interferometer (IASI) abroad on MetOp-A will be compared with CO simulated columns over the fire affected regions using the a priori and the optimized biomass burning emission inventory.

Published
2012

46. The status and challenge of global fire modelling

Author

Hantson, S., primary, Arneth, A., additional, Harrison, S. P., additional, Kelley, D. I., additional, Prentice, I. C., additional, Rabin, S. S., additional, Archibald, S., additional, Mouillot, F., additional, Arnold, S. R., additional, Artaxo, P., additional, Bachelet, D., additional, Ciais, P., additional, Forrest, M., additional, Friedlingstein, P., additional, Hickler, T., additional, Kaplan, J. O., additional, Kloster, S., additional, Knorr, W., additional, Lasslop, G., additional, Li, F., additional, Mangeon, S., additional, Melton, J. R., additional, Meyn, A., additional, Sitch, S., additional, Spessa, A., additional, van der Werf, G. R., additional, Voulgarakis, A., additional, and Yue, C., additional

Published
2016
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48. Global Carbon Budget 2015

Author

Leerstoel Ridder, Environmental Sciences, Sub Algemeen Math. Inst, Le Quéré, C., Moriarty, R., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Friedlingstein, P., Peters, G. P., Andres, R. J., Boden, T. A., Houghton, R. A., House, J. I., Keeling, R. F., Tans, P., Arneth, A., Bakker, D. C. E., Barbero, L., Bopp, L., Chang, J., Chevallier, F., Chini, L. P., Ciais, P., Fader, M., Feely, R. A., Gkritzalis, T., Harris, I., Hauck, J., Ilyina, T., Jain, A. K., Kato, E., Kitidis, V., Klein Goldewijk, K., Koven, C., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lima, I. D., Metzl, N., Millero, F., Munro, D. R., Murata, A., Nabel, J. E. M. S., Nakaoka, S., Nojiri, Y., O'Brien, K., Olsen, A., Ono, T., Pérez, F. F., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Rödenbeck, C., Saito, S., Schuster, U., Schwinger, J., Séférian, R., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Vandemark, D., Viovy, N., Wiltshire, A., Zaehle, S., Zeng, N., Leerstoel Ridder, Environmental Sciences, Sub Algemeen Math. Inst, Le Quéré, C., Moriarty, R., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Friedlingstein, P., Peters, G. P., Andres, R. J., Boden, T. A., Houghton, R. A., House, J. I., Keeling, R. F., Tans, P., Arneth, A., Bakker, D. C. E., Barbero, L., Bopp, L., Chang, J., Chevallier, F., Chini, L. P., Ciais, P., Fader, M., Feely, R. A., Gkritzalis, T., Harris, I., Hauck, J., Ilyina, T., Jain, A. K., Kato, E., Kitidis, V., Klein Goldewijk, K., Koven, C., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lima, I. D., Metzl, N., Millero, F., Munro, D. R., Murata, A., Nabel, J. E. M. S., Nakaoka, S., Nojiri, Y., O'Brien, K., Olsen, A., Ono, T., Pérez, F. F., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Rödenbeck, C., Saito, S., Schuster, U., Schwinger, J., Séférian, R., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Vandemark, D., Viovy, N., Wiltshire, A., Zaehle, S., and Zeng, N.

Published
2015

49. Global carbon budget 2014

Author

Environmental Sciences, LS Economische Geschiedenis, Leerstoel Aarts, Le Quéré, C., Moriarty, R., Andrew, R. M., Peters, G. P., Ciais, P., Friedlingstein, P., Jones, S. D., Sitch, S., Tans, P., Arneth, A., Boden, T. A., Bopp, L., Bozec, Y., Canadell, J. G., Chevallier, F., Cosca, C. E., Harris, I., Hoppema, M., Houghton, R. A., House, J. I., Jain, A., Johannessen, T., Kato, E., Keeling, R. F., Kitidis, V., Klein Goldewijk, K., Koven, C., Landa, C. S., Landschützer, P., Lenton, A., Lima, I. D., Marland, G., Mathis, J. T., Metzl, N., Nojiri, Y., Olsen, A., Ono, T., Peters, W., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Salisbury, J. E., Schuster, U., Schwinger, J., Séférian, R., Segschneider, J., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Werf, G. R., Viovy, N., Wang, Y.-P., Wanninkhof, R., Wiltshire, A., Zeng, N., Environmental Sciences, LS Economische Geschiedenis, Leerstoel Aarts, Le Quéré, C., Moriarty, R., Andrew, R. M., Peters, G. P., Ciais, P., Friedlingstein, P., Jones, S. D., Sitch, S., Tans, P., Arneth, A., Boden, T. A., Bopp, L., Bozec, Y., Canadell, J. G., Chevallier, F., Cosca, C. E., Harris, I., Hoppema, M., Houghton, R. A., House, J. I., Jain, A., Johannessen, T., Kato, E., Keeling, R. F., Kitidis, V., Klein Goldewijk, K., Koven, C., Landa, C. S., Landschützer, P., Lenton, A., Lima, I. D., Marland, G., Mathis, J. T., Metzl, N., Nojiri, Y., Olsen, A., Ono, T., Peters, W., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Salisbury, J. E., Schuster, U., Schwinger, J., Séférian, R., Segschneider, J., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Werf, G. R., Viovy, N., Wang, Y.-P., Wanninkhof, R., Wiltshire, A., and Zeng, N.

Published
2015

50. Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories

Author

EUMETSAT conference (21-25.09.2015: Toulouse), Whitburn, Simon, Van Damme, Martin, Kaiser, Johannes, Van der Werf, G. R., Turquety, Solène, Hurtmans, Daniel, Clarisse, Lieven, Clerbaux, Cathy, Coheur, Pierre, EUMETSAT conference (21-25.09.2015: Toulouse), Whitburn, Simon, Van Damme, Martin, Kaiser, Johannes, Van der Werf, G. R., Turquety, Solène, Hurtmans, Daniel, Clarisse, Lieven, Clerbaux, Cathy, and Coheur, Pierre

Abstract

info:eu-repo/semantics/nonPublished

Published
2015

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