Search

Quantification of land surface–atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categorie

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990-2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK leve, SCOPUS: re.j, info:eu-repo/semantics/published

The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g. through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g. using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs., SCOPUS: ar.j, DecretOANoAutActif, info:eu-repo/semantics/published

The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.

The data provided here are aggregated regional estimates of net atmosphere-land CO2 fluxes from the five atmospheric inversions (Chevallier et al., 2005; Rödenbeck et al., 2003; van der Laan-Luijkx et al., 2017; Saeki and Patra, 2017) and 16 Dynamic Global Vegetation Models (TRENDY-v7) that contributed to the latest Global Carbon Budget (Le Quéré et al., 2018b)., The data provided here are aggregated regional estimates of net atmosphere-land CO2 fluxes from the five atmospheric inversions (Chevallier et al., 2005; Rödenbeck et al., 2003; van der Laan-Luijkx et al., 2017; Saeki and Patra, 2017) and 16 Dynamic Global Vegetation Models (TRENDY-v7) that contributed to the latest Global Carbon Budget (Le Quéré et al., 2018b). Inversions: The five inversions provided here are all based on in-situ CO2 observation measurements from 1) the Cooperative Global Atmospheric Data Integration Project; (2017): Multi-laboratory compilation of atmospheric carbon dioxide data obspack_co2_1_GLOBALVIEWplus_v3.2_2017_11_02 for the period 1957-2016; NOAA Earth System Research Laboratory, Global Monitoring Division. http://dx.doi.org/10.15138/G3704H; (2) Carbontracker Team; (2018) : Compilation of near real time atmospheric, carbon dioxide data; obspack_co2_1_NRT_v4.2_2018-04-06; NOAA Earth System Research Laboratory, Global Monitoring Division. http://doi.org/10.15138/G3RP8K. A complete description of the different atmospheric inversions can be found in Table A3 in Le Quéré et al. (2018b). Here we add two versions of CarboScope (Rödenbeck et al., 2003), both covering a period longer than 30 years: s76 (1976-2017, 8 stations) and s85 (1985-2017, 21 stations). As in Le Quéré et al. (2018b), we adjusted the ocean and land fluxes for differences in fossil fuel emission (EFF ) priors using as reference EFF used by CAMS (EDGAR (Olivier et al., 2017) scaled to the CDIAC (Marland and Andres, 2008)) over large latitudinal bands. However, this is only a first-order correction as the biases in EFF not only affect the flux estimation of the region in question but also the neighbouring regions (Saeki and Patra, 2017). The inversion surface fluxes were remapped to a regular 1x1 degree lat/lon grid and then aggregated to the 18 land regions in Tian et al. (2018). Based on the data-driven estimates of fluvial exports of organic and inorganic C to the coast, Zsche

Severe droughts in the Northern Hemisphere cause a widespread decline of agricultural yield, the reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency (WUE), as measured for many individual plants under laboratory conditions and field experiments. Here we analyse the 13C/12C stable isotope ratio in atmospheric CO2 to provide new observational evidence of the impact of droughts on the WUE across areas of millions of square kilometres and spanning one decade of recent climate variability. We find strong and spatially coherent increases in WUE along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia and the United States in 2001–2011. The impact of those droughts on WUE and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought-induced carbon–climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.

This zip file contains XX individual NetCDF files with the data used for the publication of van Schaik et al. 2018 in the Philosophical transactions of the Royal Society. Full description of the methodology used to create these numbers is available from the publication and its Supplement.

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world's 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of -0.46 (-0.70-0.24) PgC per year (median and range) for 1996-2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996-2001 and 2008-2012 by 0.56 (0.30-0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere 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 a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1s, reflecting the current capacity to characterise the annual estimates of each component of the global carbon

A state-of-the-art inverse model, CarbonTracker Data Assimilation Shell (CTDAS), was used to optimize estimates of methane (CH4) surface fluxes using atmospheric observations of CH4 as a constraint. The model consists of the latest version of the TM5 atmospheric chemistry-transport model and an ensemble Kalman filter based data assimilation system. The model was constrained by atmospheric methane surface concentrations, obtained from the World Data Centre for Greenhouse Gases (WDCGG). Prior methane emissions were specified for five sources: biosphere, anthropogenic, fire, termites and ocean, of which biosphere and anthropogenic emissions were optimized. Atmospheric CH4 mole fractions for 2007 from northern Finland calculated from prior and optimized emissions were compared with observations. It was found that the root mean squared errors of the posterior estimates were more than halved. Furthermore, inclusion of NOAA observations of CH4 from weekly discrete air samples collected at Pallas improved agreement between posterior CH4 mole fraction estimates and continuous observations, and resulted in reducing optimized biosphere emissions and their uncertainties in northern Finland.

Since 2004, atmospheric carbon dioxide (CO2) is being measured at the High Altitude Research Station Jungfraujoch by the division of Climate and Environmental Physics at the University of Bern (KUP) using a nondispersive infrared gas analyzer (NDIR) in combination with a paramagnetic O2 analyzer. In January 2010, CO2 measurements based on cavity ring-down spectroscopy (CRDS) as part of the Swiss National Air Pollution Monitoring Network were added by the Swiss Federal Laboratories for Materials Science and Technology (Empa). To ensure a smooth transition – a prerequisite when merging two data sets, e.g., for trend determinations – the two measurement systems run in parallel for several years. Such a long-term intercomparison also allows the identification of potential offsets between the two data sets and the collection of information about the compatibility of the two systems on different time scales. A good agreement of the seasonality, short-term variations and, to a lesser extent mainly due to the short common period, trend calculations is observed. However, the comparison reveals some issues related to the stability of the calibration gases of the KUP system and their assigned CO2 mole fraction. It is possible to adapt an improved calibration strategy based on standard gas determinations, which leads to better agreement between the two data sets. By excluding periods with technical problems and bad calibration gas cylinders, the average hourly difference (CRDS – NDIR) of the two systems is -0.03 ppm ± 0.25 ppm. Although the difference of the two data sets is in line with the compatibility goal of ±0.1 ppm of the World Meteorological Organization (WMO), the standard deviation is still too high. A significant part of this uncertainty originates from the necessity to switch the KUP system frequently (every 12 min) for 6 min from ambient air to a working gas in order to correct short-term variations of the O2 measurement system. Allowing additional time for signal

Atmospheric CO2 inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO2 measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2010. Mean fluxes for 2001-2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale subdivisions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (-3.4 Pg C yr(-1) (+/- 0.5 Pg C yr(-1) standard deviation), with slightly more uptake over land than over ocean), a significant although more variable source over the tropics (1.6 +/- 0.9 Pg C yr(-1)) and a compensatory sink of similar magnitude in the south (-1.4 +/- 0.5 Pg C yr(-1)) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.06 versus 0.33 Pg C yr(-1) for the 1996-2007 period), with much higher consistency among the inversions for the land. While the tropical land explains most of the IAV (standard deviation similar to 0.65 Pg C yr(-1)), the northern and southern land also contribute (standard deviation similar to 0.39 Pg C yr(-1)). Most inversions tend to indicate an increase of the northern land carbon uptake from late 1990s to 2008 (around 0.1 Pg C yr(-1)), predominantly in North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data o

We present results from an intercomparison program of CO2, d(O2/N2) and d13CO2 measurements from atmospheric flask samples. Flask samples are collected on a bi-weekly basis at the High Altitude Research Station Jungfraujoch in Switzerland for three European laboratories: the University of Bern, Switzerland, the University of Groningen, the Netherlands and the Max Planck Institute for Biogeochemistry in Jena, Germany. Almost 4 years of measurements of CO2, d(O2/N2) and d13CO2 are compared in this paper to assess the measurement compatibility of the three laboratories. While the average difference for the CO2 measurements between the laboratories in Bern and Jena meets the required compatibility goal as defined by the World Meteorological Organization, the standard deviation of the average differences between all laboratories is not within the required goal. However, the obtained annual trend and seasonalities are the same within their estimated uncertainties. For d(O2/N2) significant differences are observed between the three laboratories. The comparison for d13CO2 yields the least compatible results and the required goals are not met between the three laboratories. Our study shows the importance of regular intercomparison exercises to identify potential biases between laboratories and the need to improve the quality of atmospheric measurements

A new atmospheric measurement station has been established on the North Sea oil and gas production platform F3, 200 km north off the Dutch coast (54°51' N, 4°44' E). Atmospheric concentrations of O2 and CO2 are continuously measured using fuel cell technology and compact infrared absorption instruments, respectively. Furthermore, the station includes an automated air flask sampler for laboratory analysis of the atmospheric concentrations of CO2, CH4, CO and O2 and isotope measurements of d13C, d18O and ¿14C from CO2. This station is the first fixed sea based station with on-site continuous O2 and CO2 measurements and therefore yields valuable information about the CO2 uptake in coastal marine regions, specifically the North Sea. This paper presents the measurement station and the used methodologies in detail. In comparison to land-based stations, the data show low day-to-day variability, as they are practically free of nightly inversions as well as human influences, due to the station’s remoteness. Therefore, the data set collected at this measurement station serves directly as background data for the coastal northwest European region. Additionally, the first data are presented showing the seasonal cycle as expected during August 2008 through June 2009. Furthermore, some short-term O2 and CO2 signals are presented. The observations at the platform include several large and fast changing negative atmospheric O2 excursions without an accompanying change in the CO2 signal, which most likely indicate marine O2 uptake

We report results from our atmospheric flask sampling network for three European sites: Lutjewad in the Netherlands, Mace Head in Ireland and the North Sea F3 platform. The air samples from these stations are analyzed for their CO2 and O2 concentrations. In this paper we present the CO2 and O2 data series from these sites between 1998 and 2009, as well as the atmospheric potential oxygen (APO). The seasonal pattern and long term trends agree to a large extent between our three measurement locations. We however find a changing gradient between Mace Head and Lutjewad, both for CO2 and O2. To explain the potential contribution of fossil fuel emissions to this changing gradient we use an atmospheric transport model in combination with CO2 emission data and information on the fossil fuel mix per region. Using the APO trend from Mace Head we obtain an estimate for the global oceanic CO2 uptake of 1.8 ± 0.8 PgC/year.