Constraining global methane emissions and uptake by ecosystems

Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Impact of an abrupt cooling event on interglacial methane emissions in northern peatlands

Rapid changes in atmospheric methane (CH4), temperature and precipitation are documented by Greenland ice core data both for glacial times (the so called Dansgaard-Oeschger (D-O) events) as well as for a cooling event in the early Holocene (the 8.2 kyr event). The onsets of D-O warm events are paralleled by abrupt increases in CH4 by up to 250 ppb in a few decades. Vice versa, the 8.2 kyr event is accompanied by an intermittent decrease in CH4 of about 80 ppb over 150 yr. The abrupt CH4 changes are thought to mainly originate from source emission variations in tropical and boreal wet ecosystems, but complex process oriented bottom-up model estimates of the changes in these ecosystems during rapid climate changes are still missing. Here we present simulations of CH4 emissions from northern peatlands with the LPJ-Bern dynamic global vegetation model. The model represents CH4 production and oxidation in soils and transport by ebullition, through plant aerenchyma, and by diffusion. Parameters are tuned to represent site emission data as well as inversion-based estimates of northern wetland emissions. The model is forced with climate input data from freshwater hosing experiments using the NCAR CSM1.4 climate model to simulate an abrupt cooling event. A concentration reduction of ~10 ppb is simulated per degree K change of mean northern hemispheric surface temperature in peatlands. Peatland emissions are equally sensitive to both changes in temperature and in precipitation. If simulated changes are taken as an analogy to the 8.2 kyr event, boreal peatland emissions alone could only explain 23 of the 80 ppb decline in atmospheric methane concentration. This points to a significant contribution to source changes from low latitude and tropical wetlands to this event.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Decision strategies for policy decisions under uncertainties: The case of mitigation measures addressing methane emissions from ruminants

Decision strategies aim at enabling reasonable decisions in cases of uncertain policy decision problems which do not meet the conditions for applying standard decision theory. This paper focuses on decision strategies that account for uncertainties by deciding whether a proposed list of policy options should be accepted or revised (scope strategies) and whether to decide now or later (timing strategies). They can be used in participatory approaches to structure the decision process. As a basis, we propose to classify the broad range of uncertainties affecting policy decision problems along two dimensions, source of uncertainty (incomplete information, inherent indeterminacy and unreliable information) and location of uncertainty (information about policy options, outcomes and values). Decision strategies encompass multiple and vague criteria to be deliberated in application. As an example, we discuss which decision strategies may account for the uncertainties related to nutritive technologies that aim at reducing methane (CH4) emissions from ruminants as a means of mitigating climate change, limiting our discussion to published scientific information. These considerations not only speak in favour of revising rather than accepting the discussed list of options, but also in favour of active postponement or semi-closure of decision-making rather than closure or passive postponement.

Evidence for past variations in methane availability in a Siberian thermokarst lake based on δ13C of chitinous invertebrate remains

Understanding past methane dynamics in arctic wetlands and lakes is crucial for estimating future methane release. Methane fluxes from lake ecosystems have increasingly been studied, yet only few reconstructions of past methane emissions from lakes are available. In this study, we develop an approach to assess changes in methane availability in lakes based on δ13C of chitinous invertebrate remains and apply this to a sediment record from a Siberian thermokarst lake. Diffusive methane fluxes from the surface of ten newly sampled Siberian lakes and seven previously studied Swedish lakes were compared to taxon-specific δ13C values of invertebrate remains from lake surface sediments to investigate whether these invertebrates assimilated 13C-depleted carbon typical for methane. Remains of chironomid larvae of the tribe Orthocladiinae that, in the study lakes, mainly assimilate plant-derived carbon had higher δ13C than other invertebrate groups. δ13C of other invertebrates such as several chironomid groups (Chironomus, Chironomini, Tanytarsini, and Tanypodinae), cladocerans (Daphnia), and ostracods were generally lower. δ13C of Chironomini and Daphnia, and to a lesser extent Tanytarsini was variable in the lakes and lower at sites with higher diffusive methane fluxes. δ13C of Chironomini, Tanytarsini, and Daphnia were correlated significantly with diffusive methane flux in the combined Siberian and Swedish dataset (r = −0.72, p = 0.001, r = −0.53, p = 0.03, and r = −0.81, p < 0.001, respectively), suggesting that δ13C in these invertebrates was affected by methane availability. In a second step, we measured δ13C of invertebrate remains from a sediment record of Lake S1, a shallow thermokarst lake in northeast Siberia. In this record, covering the past ca 1000 years, δ13C of taxa most sensitive to methane availability (Chironomini, Tanytarsini, and Daphnia) was lowest in sediments deposited from ca AD 1250 to ca AD 1500, and after AD 1970, coinciding with warmer climate as indicated by an independent local temperature record. As a consequence the offset in δ13C between methane-sensitive taxa and bulk organic matter was higher in these sections than in other parts of the core. In contrast, δ13C of other invertebrate taxa did not show this trend. Our results suggest higher methane availability in the study lake during warmer periods and that thermokarst lakes can respond dynamically in their methane output to changing environmental conditions.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Natural and anthropogenic methane fluxes in Eurasia: a mesoscale quantification by generalized atmospheric inversion

Eight surface observation sites providing quasi-continuous measurements of atmospheric methane mixingratios have been operated since the mid-2000’s in Siberia. For the first time in a single work, we assimilate 1 year of these in situ observations in an atmospheric inversion. Our objective is to quantify methane surface fluxes from anthropogenic and wetland sources at the mesoscale in the Siberian lowlands for the year 2010. To do so, we first inquire about the way the inversion uses the observations and the way the fluxes are constrained by the observation sites. As atmospheric inver- sions at the mesoscale suffer from mis-quantified sources of uncertainties, we follow recent innovations in inversion techniques and use a new inversion approach which quantifies the uncertainties more objectively than the previous inversion systems. We find that, due to errors in the representation of the atmospheric transport and redundant pieces of information, only one observation every few days is found valuable by the inversion. The remaining high-resolution quasi-continuous signal is representative of very local emission patterns difficult to analyse with a mesoscale system. An analysis of the use of information by the inversion also reveals that the observation sites constrain methane emissions within a radius of 500 km. More observation sites than the ones currently in operation are then necessary to constrain the whole Siberian lowlands. Still, the fluxes within the constrained areas are quantified with objectified uncertainties. Finally, the tolerance intervals for posterior methane fluxes are of roughly 20 % (resp. 50 %) of the fluxes for anthropogenic (resp. wetland) sources. About 50–70 % of Siberian lowlands emissions are constrained by the inversion on average on an annual basis. Extrapolating the figures on the constrained areas to the whole Siberian lowlands, we find a regional methane budget of 5–28 TgCH4 for the year 2010, i.e. 1–5 % of the global methane emissions. As very few in situ observations are available in the region of interest, observations of methane total columns from the Greenhouse Gas Observing SATellite (GOSAT) are tentatively used for the evaluation of the inversion results, but they exhibit only a marginal signal from the fluxes within the region of interest.

Evaluating atmospheric methane inversion model results for Pallas, northern Finland

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 bio-sphere and anthropogenic emissions were optimized. Atmospheric CH 4 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 esti - mates were more than halved. Furthermore, inclusion of NOAA observations of CH 4 from weekly discrete air samples collected at Pallas improved agreement between posterior CH 4 mole fraction estimates and continuous observations, and resulted in reducing optimized biosphere emissions and their uncertainties in northern Finland.

Age modeling of young non-varved lake sediments: methods and limits. Examples from two lakes in Central Chile

High-resolution and highly precise age models for recent lake sediments (last 100–150 years) are essential for quantitative paleoclimate research. These are particularly important for sedimentological and geochemical proxies, where transfer functions cannot be established and calibration must be based upon the relation of sedimentary records to instrumental data. High-precision dating for the calibration period is most critical as it determines directly the quality of the calibration statistics. Here, as an example, we compare radionuclide age models obtained on two high-elevation glacial lakes in the Central Chilean Andes (Laguna Negra: 33°38′S/70°08′W, 2,680 m a.s.l. and Laguna El Ocho: 34°02′S/70°19′W, 3,250 m a.s.l.). We show the different numerical models that produce accurate age-depth chronologies based on 210Pb profiles, and we explain how to obtain reduced age-error bars at the bottom part of the profiles, i.e., typically around the end of the 19th century. In order to constrain the age models, we propose a method with five steps: (i) sampling at irregularly-spaced intervals for 226Ra, 210Pb and 137Cs depending on the stratigraphy and microfacies, (ii) a systematic comparison of numerical models for the calculation of 210Pb-based age models: constant flux constant sedimentation (CFCS), constant initial concentration (CIC), constant rate of supply (CRS) and sediment isotope tomography (SIT), (iii) numerical constraining of the CRS and SIT models with the 137Cs chronomarker of AD 1964 and, (iv) step-wise cross-validation with independent diagnostic environmental stratigraphic markers of known age (e.g., volcanic ash layer, historical flood and earthquakes). In both examples, we also use airborne pollutants such as spheroidal carbonaceous particles (reflecting the history of fossil fuel emissions), excess atmospheric Cu deposition (reflecting the production history of a large local Cu mine), and turbidites related to historical earthquakes. Our results show that the SIT model constrained with the 137Cs AD 1964 peak performs best over the entire chronological profile (last 100–150 years) and yields the smallest standard deviations for the sediment ages. Such precision is critical for the calibration statistics, and ultimately, for the quality of the quantitative paleoclimate reconstruction. The systematic comparison of CRS and SIT models also helps to validate the robustness of the chronologies in different sections of the profile. Although surprisingly poorly known and under-explored in paleolimnological research, the SIT model has a great potential in paleoclimatological reconstructions based on lake sediments

Three decades of global methane sources and sinks

Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios � which differ in fossil fuel and microbial emissions � to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Independent variations of CH₄ emissions and isotopic composition over the past 160,000 years

During the last glacial cycle, greenhouse gas concentrations fluctuated on decadal and longer timescales. Concentrations of methane, as measured in polar ice cores, show a close connection with Northern Hemisphere temperature variability, but the contribution of the various methane sources and sinks to changes in concentration is still a matter of debate. Here we assess changes in methane cycling over the past 160,000 years by measurements of the carbon isotopic composition delta C-13 of methane in Antarctic ice cores from Dronning Maud Land and Vostok. We find that variations in the delta C-13 of methane are not generally correlated with changes in atmospheric methane concentration, but instead more closely correlated to atmospheric CO2 concentrations. We interpret this to reflect a climatic and CO2-related control on the isotopic signature of methane source material, such as ecosystem shifts in the seasonally inundated tropical wetlands that produce methane. In contrast, relatively stable delta C-13 values occurred during intervals of large changes in the atmospheric loading of methane. We suggest that most methane sources-most notably tropical wetlands-must have responded simultaneously to climate changes across these periods.

Modeling the formation and aging of secondary organic aerosols during CalNex 2010

Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model–measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model–measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35 %, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(+-3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μgm-3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr-1 of SOA globally, or 17% of global SOA, one third of which is likely to be non-fossil.