ALBERT

Description: 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 TgCH4 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. Bottom-up approaches suggest larger global emissions (736 TgCH4 yr􀀀1, range 596–884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions ( 64% of the global budget, 〈 30 N) as compared to mid ( 32 %, 30–60 N) and high northern latitudes ( 4 %, 60–90 N). Top-down inversions consistently infer lower emissions in China ( 58 TgCH4 yr􀀀1, range 51–72, 􀀀14 %) and higher emissions in Africa (86 TgCH4 yr􀀀1, range 73–108, C19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30–40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.

Description: Published

Description: 697–751

Description: 6A. Geochimica per l'ambiente

Description: JCR Journal

Description: Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4/ budget over 2000– 2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from topdown studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches.The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr􀀀1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all topdown studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

Description: Published

Description: 11135–11161

Description: 6A. Geochimica per l'ambiente

Description: JCR Journal

Description: Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs.

Description: Published

Description: 1197–1268

Description: OSA2: Evoluzione climatica: effetti e loro mitigazione

Description: JCR Journal

Description: Characterizing methane sources in the Arctic remains challenging due to the remoteness, heterogeneity and variety of such emissions. In situ campaigns provide valuable datasets to reduce these uncertainties. Here we analyse data from the summer 2014 SWERUS-C3 campaign in the eastern Arctic Ocean, off the shore of Siberia and Alaska. Total concentrations of methane, as well as relative concentrations of 12CH4 and 13CH4, were measured continuously during this campaign for 35 d in July and August. Using a chemistry-transport model, we link observed concentrations and isotopic ratios to regional emissions and hemispheric transport structures. A simple inversion system helped constrain source signatures from wetlands in Siberia and Alaska, and oceanic sources, as well as the isotopic composition of lower-stratosphere air masses. The variation in the signature of lower-stratosphere air masses, due to strongly fractionating chemical reactions in the stratosphere, was suggested to explain a large share of the observed variability in isotopic ratios. These results point towards necessary efforts to better simulate large-scale transport and chemistry patterns to make relevant use of isotopic data in remote areas. It is also found that constant and homogeneous source signatures for each type of emission in a given region (mostly wetlands and oil and gas industry in our case at high latitudes) are not compatible with the strong synoptic isotopic signal observed in the Arctic. A regional gradient in source signatures is highlighted between Siberian and Alaskan wetlands, the latter having lighter signatures (more depleted in 13C). Finally, our results suggest that marine emissions of methane from Arctic continental-shelf sources are dominated by thermogenic-origin methane, with a secondary biogenic source as well.

Description: The contribution in terms of long-range transport of CO2, CH4, and CO concentrations to measurements at Lamto (5°02′ W–6°13′ N) was analyzed for the 2014–2017 period using the FLEXPART model that calculates the retro-plumes of air masses arriving at the station. The identification of the source-receptor relationships was also studied with a clustering technique applied on those retro-plumes. This clustering technique enabled us to distinguish four categories of air mass transports arriving at Lamto site described as follows: oceanic and maritime origin (≈37% of the retro-plumes), continental origin (≈21%), and two hybrid clusters (≈42%). The results show that continental emission sources contribute significantly to the increases in concentrations of CO2, CH4, and CO and explain ≈40% of their variance. These emission sources are predominantly from north and north-east directions of the measurement point, and where densely populated and economically developed areas are located. In addition, the transport of air masses from these directions lead to the accumulation of CO2, CH4, and CO. Furthermore, the ratios ΔCO/ΔCH4 and ΔCO/ΔCO2 observed in the groups associated with Harmattan flows clearly show an influence of combustion processes on the continent. Thus, the grouping based on FLEXPART footprints shows an advantage compared to the use of simple trajectories for analyzing source–receptor relationships.

Description: Understanding the recent evolution of methane emissions in the Arctic is necessary to interpret the global methane cycle. Emissions are affected by significant uncertainties and are sensitive to climate change, leading to potential feedbacks. A polar version of the CHIMERE chemistry-transport model is used to simulate the evolution of tropospheric methane in the Arctic during 2012, including all known regional anthropogenic and natural sources, in particular freshwater emissions which are often overlooked in methane modelling. CHIMERE simulations are compared to atmospheric continuous observations at six measurement sites in the Arctic region. In winter, the Arctic is dominated by anthropogenic emissions; emissions from continental seepages and oceans, including from the East Siberian Arctic Shelf, can contribute significantly in more limited areas. In summer, emissions from wetland and freshwater sources dominate across the whole region. The model is able to reproduce the seasonality and synoptic variations of methane measured at the different sites. We find that all methane sources significantly affect the measurements at all stations at least at the synoptic scale, except for biomass burning. In particular, freshwater systems play a decisive part in summer, representing on average between 11 and 26 % of the simulated Arctic methane signal at the sites. This indicates the relevance of continuous observations to gain a mechanistic understanding of Arctic methane sources. Sensitivity tests reveal that the choice of the land-surface model used to prescribe wetland emissions can be critical in correctly representing methane mixing ratios. The closest agreement with the observations is reached when using the two wetland models which have emissions peaking in August–September, while all others reach their maximum in June–July. Such phasing provides an interesting constraint on wetland models which still have large uncertainties at present. Also testing different freshwater emission inventories leads to large differences in modelled methane. Attempts to include methane sinks (OH oxidation and soil uptake) reduced the model bias relative to observed atmospheric methane. The study illustrates how multiple sources, having different spatiotemporal dynamics and magnitudes, jointly influence the overall Arctic methane budget, and highlights ways towards further improved assessments.

Description: This study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. We considered three spike detection methods known as coefficient of variation (COV), robust extraction of baseline signal (REBS) and standard deviation of the background (SD) to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the European ICOS (Integrated Carbon Observation System) Research Infrastructure network. The results of the different methods are compared to each other and against a manual detection performed by station managers. Four stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100 m height in eastern France (OPE), a high-mountain observatory in the south-west of France (PDM), a regional marine background site in Crete (FKL) and a marine clean-air background site in the Southern Hemisphere on Amsterdam Island (AMS). This selection allows us to address spike detection problems in time series with different variability. Two years of continuous measurements of CO2, CH4 and CO were analysed. All methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes) in the time series. Analysis of the results of each method leads us to exclude the COV method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over- or underestimate the actual number of spikes. The two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. More than 96 % of the spikes manually identified by station managers were successfully detected both in the SD and the REBS methods after the best adjustment of parameter values. At PDM, measurements made by two analyzers located 200 m from each other allow us to confirm that the CH4 spikes identified in one of the time series but not in the other correspond to a local source from a sewage treatment facility in one of the observatory buildings. From this experiment, we also found that the REBS method underestimates the number of positive anomalies in the CH4 data caused by local sewage emissions. As a conclusion, we recommend the use of the SD method, which also appears to be the easiest one to implement in automatic data processing, used for the operational filtering of spikes in greenhouse gases time series at global and regional monitoring stations of networks like that of the ICOS atmosphere network.

Description: Methane emissions on the national scale in France in 2012 are inferred by assimilating continuous atmospheric mixing ratio measurements from nine stations of the European network ICOS located in France and surrounding countries. To assess the robustness of the fluxes deduced by our inversion system based on an objectified quantification of uncertainties, two complementary inversion set-ups are computed and analysed: (i) a regional run correcting for the spatial distribution of fluxes in France and (ii) a sectorial run correcting fluxes for activity sectors on the national scale. In addition, our results for the two set-ups are compared with fluxes produced in the framework of the inversion inter-comparison exercise of the InGOS project. The seasonal variability in fluxes is consistent between different set-ups, with maximum emissions in summer, likely due to agricultural activity. However, very high monthly posterior uncertainties (up to ≈ 65 to 74 % in the sectorial run in May and June) make it difficult to attribute maximum emissions to a specific sector. On the yearly and national scales, the two inversions range from 3835 to 4050 Gg CH4 and from 3570 to 4190 Gg CH4 for the regional and sectorial runs, respectively, consistently with the InGOS products. These estimates are 25 to 55 % higher than the total national emissions from bottom-up approaches (biogeochemical models from natural emissions, plus inventories for anthropogenic ones), consistently pointing at missing or underestimated sources in the inventories and/or in natural sources. More specifically, in the sectorial set-up, agricultural emissions are inferred as 66% larger than estimates reported to the UNFCCC. Uncertainties in the total annual national budget are 108 and 312 Gg CH4, i.e, 3 to 8 %, for the regional and sectorial runs respectively, smaller than uncertainties in available bottom-up products, proving the added value of top-down atmospheric inversions. Therefore, even though the surface network used in 2012 does not allow us to fully constrain all regions in France accurately, a regional inversion set-up makes it possible to provide estimates of French methane fluxes with an uncertainty in the total budget of less than 10 % on the yearly timescale. Additional sites deployed since 2012 would help to constrain French emissions on finer spatial and temporal scales and attributing missing emissions to specific sectors.

Description: Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.